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AdaptNow - M-ITI · AdaptNow is a web-based application that allows users to adapt existing...
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AdaptNow
Roberto César Vasconcelos Dias (Bachelor)
Thesis submitted to the Universidade da Madeira for
Obtaining a Master Degree in Computer Engineering
Funchal – Portugal
Fevereiro 20014
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Supervising Teacher:
Professor PhD Sergi Bermudez
Invited Assistant Professor of M-ITI
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ABSTRACT Elderly population will become the largest age group of our society in the next twenty years.
Consequently, we need to be able to accommodate technologies to the needs of this population.
AdaptNow is a web-based application that allows users to adapt existing webpages and turn
them more accessible and user friendly. Users can do so directly from any web browser thanks
to AdaptNow's user personalisation and automatic adaptation artificial intelligence algorithms.
In this paper we present the design and implementation of AdaptNow, a solution that improves
navigation on the web for elderly users.
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KEYWORDS
Web enhance, AdaptNow, Elderly users
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RESUMO
Bla, bla, bla.
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KEYWORDS
Web enhance, AdaptNow, Elderly users
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ACKNOWLEDGMENT
…
Acknowledgements
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TABLE OF CONTENTS
I. Introduction 1
I.1. Motivation ..................................................................................................................... 1
I.2. Context/Problematical................................................................................................ 2
I.3. Contribution ................................................................................................................. 3
I.4. Structure ........................................................................................................................ 4
II. State of the Art 5
II.1. Overview ....................................................................................................................... 5
II.2. Accessible computer design approaches .................................................................. 6 Assistive technology ............................................................................................................ 6 II.2.1. Rehabilitation Engineering ................................................................................................. 9 II.2.2. Universal design/ Design for all ..................................................................................... 10 II.2.3. Transgenerational design .................................................................................................. 11 II.2.4. User pyramid design ......................................................................................................... 12 II.2.5. Inclusive design .................................................................................................................. 13 II.2.6. Ability-based design .......................................................................................................... 15 II.2.7. Conclusion .......................................................................................................................... 16 II.2.8.
II.3. Architecture design ................................................................................................... 16
II.4. Types of user interfaces ............................................................................................ 18
II.5. Types of users ............................................................................................................. 22 Elderly users ....................................................................................................................... 22 II.5.1. Low vision users vs. dexterity impaired users .............................................................. 25 II.5.1.
III. AdaptNow – Experiments and Artificial Intelligent System 27
III.1. Web enhancements and artificial intelligence (AI) modelling ............................ 27 Method ............................................................................................................................... 27 III.1.1. Results ................................................................................................................................ 29 III.1.2.
III.2. Enhanced historic and bookmark view .................................................................. 33 Methods ............................................................................................................................. 33 III.2.1. Results ................................................................................................................................ 34 III.2.2.
IV. AdaptNow – Implementation 49
IV.1. Use cases ..................................................................................................................... 49
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IV.2. Task model ................................................................................................................. 51
IV.3. Requirements ............................................................................................................. 52 Functional Requirements ................................................................................................ 55 IV.3.1. Non-Functional Requirements ....................................................................................... 56 IV.3.2.
V. Conclusion and Future Work 68
Index 4
VI. References 5
Table of Contents
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LIST OF FIGURES
Figure 1 - (a) Ideal system interaction. (B) The user does not fit the system, so the interaction with it is made through an adaptation. Adapted from [5]. ........................................... 8
Figure 2 - The pyramid design method.- Adapted from [25]. .......................................................... 13 Figure 3 - The inclusive design cube. Adapted from [27]................................................................... 14 Figure 4 - Ability-based design principles. Adapted from [5]. .......................................................... 15 Figure 5 - Adaption based system proposals. Adapted from [29] rever ......................................... 18 Figure 6 - Two aprotches to dropdow menus: (a) static split menu, (b) adaptable split menu.
Adapted from [30] ............................................................................................................. 20 Figure 7 - Boxplot of menu types versus speed, from Findlater et al. experiment (N=27).
Adapted from [30] ............................................................................................................. 20 Figure 8 - Example of GUI interface that was automatically generated using Supple++. A)
Typical interface, b) interface for a mouse users with impaired dexterity, c) adaptation for low vision user, and d) for users with both low vision and impaired dexterity. Adapted from [38] .......................................................................... 26
Figure 9 – Principle component analyses of the date with the objective of finding relations between the features. ........................................................................................................ 31
Figure 10 – Example of mouse model used during the experiment where we can see the different sizes used. a) normal mouse appearance; b) mouse appearance when hover a clickable area ........................................................................................................ 32
Figure 11 - Number of hour using the computer per week ............................................................... 34 Figure 12 – Features importance for adding a shortcut (bookmark) to the webpage from each
group of inquired. ............................................................................................................. 35 Figure 13 – Features used to differentiate the most visited webpages for each inquired group .. 36 Figure 14 - Features used to differentiate the webpage where the most time was spent
according to each inquired group ................................................................................... 36 Figure 15 – How should the historic be displayed to facilitate the search. ...................................... 37 Figure 16 – Inquired answer to if audio feedback would improve navigation. .............................. 38 Figure 17 – What inquired classified as the most relevant information that should be
transmitted through audio feedback. ............................................................................. 38 Figure 18 – Historic view presented to the users with the intent of them choosing which
information would be displayed. .................................................................................... 39 Figure 19 – Inquired classification which information was more relevant on this type (Figure
18) of historic view. ........................................................................................................... 40 Figure 20 - Historic tree view presented to the users with the intent of them choosing which
information would be displayed. .................................................................................... 41 Figure 21 - Inquired classification which information was more relevant on this type (Figure
20) of historic view. ........................................................................................................... 41 Figure 22 - Historic chain view presented to the users with the intent of them choosing
which information would be displayed. ........................................................................ 42 Figure 23 - Inquired classification which information was more relevant on this type (Figure
22) of historic view. ........................................................................................................... 42 Figure 24 – User classification of historic, being d – per day, w – per week, d/w – last 7 days
and they weekly and d/w/m - last 7 days them last 4 weeks and them per month. The graphs are split by groups .......................................................................... 43
List of Figures
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Figure 25 – Information placement on the historic icon view for the >40 group ........................... 45 Figure 26 - Information placement on the historic icon view for the >40 group ............................ 46 Figure 27 – Use case diagram for the AdaptNow application. ......................................................... 50 Figure 28 – Frequent user’s interaction with the AdaptNow system. ............................................. 51 Figure 29 – Users interaction for changing personal enhancement’s as mouse and colour. ........ 52
List of Figures
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LIST OF TABLES
Table 1 - The transgenerational design principles in order to provide a better product to everybody - Adapted from [22] ...................................................................................... 12
Table 2 - – Summary of the study analysed on the four types of interfaces and their result. ....... 22 Table 3 – Comparison table between different types of elderly users .............................................. 23 Table 4 – Elderly issues while navigating the web associated with the type of impairment it
is related. ............................................................................................................................. 25 Table 5 - Webpage characteristics and their corresponding significance in the web
enhancement AI model. The used web page characteristics are a) Screen Width, b) Page Height, c) Number of words, d) Biggest image Width, e) Average image width, f) Number of scripts, g) Number of H1 tags, h) Number of H2 tags, i) number of divisions. * p<0.05, ** p<0.01, and *** p<0.001. .......................................... 29
Table 6 - The weight and error of each of the feature model in relation to the webpage characteristic. The used web page characteristics are a) Screen Width, b) Page Height, c) Number of words, d) Biggest image Width, e) Average image width, f) Number of scripts, g) Number of H1 tags, h) Number of H2 tags, i) number of divisions. ............................................................................................................................. 31
Table 7 – Adaptation of Table 4, adding the solution to the uses present previously for the elderly interaction with the web. .................................................................................... 55
The functional requirements relate to all the operation that the system must allow the users perform. Through the analyses of Table 7 and the experiment conducted we got as requirements the following list: .................................................................................. 55
List of Figures
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ACRONYMS
AI – Artificial Intelligence
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I. INTRODUCTION
"People Propose, Science Studies, Technology Conforms"
Donald Norman person-centered motto for the 21st
century [Norman, 1993]
Bla, bla, bla.
I.1. MOTIVATION
"We see computers everywhere but in the productivity
statistics"
Attributed to Robert Solow [Landauer, 1997]
Bla, bla, bla.
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I.2. CONTEXT/PROBLEMATICAL
bla
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I.3. CONTRIBUTION
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I.4. STRUCTURE
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II. STATE OF THE ART
“The ideal engineer is a composite ... He is not a scientist, he is
not a mathematician, he is not a sociologist or a writer; but he
may use the knowledge and techniques of any or all of these
disciplines in solving engineering problems.”
—N. W. Dougherty (1955)
II.1. OVERVIEW
The difficulty in using technology for people with impairments is a well know problem. In an
attempt to make the usage of technology more comfortable there a large group of applications
designed to aid in the interaction with technology have been developed[1][2]. Unfortunately,
the development of some of these applications has been shut down, either by lack of funds, the
complexity and time required to spend is too high, and also the fact that the target audience is a
minority with low resources to pay to use these software. These types of software usually
change the interface of some application in an attempt to make his usage more comfortable,
since the interface is one of the key factors in the human-computer interaction.
Nowadays computer interfaces are typically designed with the assumptions 1) that they are
going to be used by an able-bodied individuals; 2) using an typical set of input/output devices;,
3) that users are in a stable environment [3]. This makes building user interfaces to allow access
to everyone a non-trivial task. Even non-impaired users sometimes cannot use certain tools
correctly if the environment is not the appropriated for the task that they are trying to perform.
This includes factors like location and technology used and the environment [4], for instance,
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designing for someone that is on a bus or a train changes radically the interaction paradigm.
Moreover, it is important to note that not everyone uses the same input/output devices in the
same way and that should be taken in consideration while building a user interface. These
factors create a growing necessity for creating interfaces that can adapt and change based on the
user behaviour and also on the environmental changes. Most of the existing solutions are
expensive what creates a great barrier for the users with special needs/user with impairments.
User abilities and needs vary from one individual to another and may change over time.
Among people with long-term impairments, even individuals with similar medical diagnoses
can have very distinct functional abilities. Abilities can fluctuate throughout the day due to
medication or fatigue, or evolve across days or months following longer-terms changes of the
underlying medical condition [3]. This makes it hard to create an application that can be a best
fit to everyone, so the ideal solution should be something that can adapt itself according to the
environment and the user condition. Consequently, technology should adapt to the person and
not the opposite.
II.2. ACCESSIBLE COMPUTER DESIGN APPROACHES
The approaches to accessible computing are numerous. All the accessible computing
approaches share the common goal of increasing the independence of people with disabilities
and also improving their quality of live [5]. Accessible computing approaches can be broadly
determined by the user group they address and how they aim at solving usability issues. When
studying the different approaches it is important to understand their temporal evolution and
that each of them was develop in different periods. The approaches that we are going to discuss
are: assistive technology, rehabilitation engineering, universal design, design for all,
transgenerational design, user pyramid design, inclusive design and ability-base design.
Assistive technology II.2.1.
Assistive technology is a standard term for devices or technological approaches with intend of
helping people to overcome their disabilities [6]. This concept was developed out of World War
II (WWII) and the post-war era with the objective to improve the quality of live for the war-
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wounded that had lost body parts in the battlefield [7]. Although this concept was coined only
after the WWII there are ancient records of such methods being used. For instance, in the
ancient Egypt artificial limbs made out of fibber were used [8].
Assistive technologies try to fit a “non-standard user” to standard technology through the use
of assistive components, like ad-on inserted between the user and the system. This method was
suggested after the WWII, thus it emerged prior to the proliferation of interactive computing.
Consequently, this method has a tendency to assume that the environment is immutable and
cannot be easily changed [5]. Immutability is something that we cannot assume nowadays
when interacting with a computer or other technologies. Nowadays we have mobile and
portable technology that can be virtually used everywhere, forcing designers to consider a
broad number of environments.
As we can see in Figure 1, the adaptation works like a mask that aids in the interaction with the
system. This architecture shifts the responsibility of adapting from the user to the system. This
adaptation can be done in four different ways: static where the adaptation made by the
developer cannot be changed; adaptable where users control the changes that happen on the
interface; adaptive where the system changes the interface in an attempt to find a best fit to the
user; and finally a mixed interface where both the system and the user can change the interface.
In the latter case, the system suggests some changes to be done but the user can also change the
interface, it is then a mixture of the adaptable and the adaptive. These four groups of interfaces
will be discussed later in section II.4.
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Figure 1 - (a) Ideal system interaction. (B) The user does not fit the
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Rehabilitation Engineering II.2.2.
Rehabilitation engineering is the process of designing, developing, adapting, testing,
evaluating, applying, and distributing technological solutions to problems faced by individuals
with disabilities [9]. The areas addressed through rehabilitation engineering include mobility,
communications, hearing, vision, and cognition, and activities associated with employment,
independent living, education, and integration into the community [10].
As in the case of assistive technology, the objective of this approach is to improve the quality of
live for people with disabilities. Rehabilitation engineering is an engineering approach, and as
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such quantifies, measures and tracks human performance in an attempt to provide the most
appropriated adaptation [5]. Rehabilitation engineering was created in part as a solution to the
trial and error approaches of many assistive technology practitioners [11].
Adaptations in rehabilitation engineering are often custom add-on devices or machines, giving
rehabilitation engineering a lot in common with assistive technology [5].
Universal design/ Design for all II.2.3.
Universal design aggregates a wide group of ideas that has the objective of producing
buildings, products and environments that are accessible and usable by both people with
disabilities and people without disabilities. Universal design was proposed by the architect
Ronald L. Mace to describe the concept of designing all products and the environment they are
built in to be aesthetic and usable to the greatest extent possible by everyone, regardless of their
age, ability, or status in life [12].This was also been focus by the European union as a priority
with them developing several projects [2], [13] This architectural approach was generalized [14],
mainly as an attempt to address the same limitations as assistive technologies and rehabilitation
engineering [15].
Although originally the main concerns were the physical aspects such as buildings and stairs,
the principles can be applied to many areas of design. This method is seen as a “one size fits all”
methodology, which may be valid for stairs, door handles and other physical objects is more
difficult to adapt to computer interfaces because it deals with complex motor, sensory, cognitive
and affective faculties of the user [5]. This method aims at guaranteeing that environments,
products, services and interfaces work for people of all ages and abilities under various
circumstances [16]. Design for all embraces the idea that is perfectly possible to design for all
potential users and that it should be easy to adapt according to different needs. According to
the European commission “The Design for All concept encourages manufacturers and service
providers to produce new technologies for everyone: technologies that are suitable for the
elderly and people with disabilities, as much as the teenage techno wizard” [13].
Design for all has become an important issue due to the aging of the population age and the
increasing multi-ethnic composition of our societies [17]. Some examples of designing for all
that where presented in the book “Diseños para Todos/Designs for All” [18]with the support of
Spain's Ministry of Education, Social Affairs and Sports (IMSERSO) and CEAPAT
[19].Automatic door , low-floor bus and audio books are some of the examples of the
application of this design for all. In conclusion design for all/universal design, focus on ways to
create a world accessible to everyone without the need of future customizations.
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Transgenerational design II.2.4.
Transgenerational design is the process of making products and environments compatible with
physical and sensory impairments associated with human aging, which limit major activities of
daily living. Transgenerational design aims at making aging more comfortable, it softens the
effect of the aging process, extends independent living, and increases the quality of life for all
the young, the old, the able and the disabled[20]. This method proposes that in the production
phase of software, the test group should have people from all age groups in an attempt to make
the application available for a wide range of ages without any future modification.
This concept focuses on the age and not on the impairments of the user, although people with
the same age do not necessarily share the same impairments [21]. The general principle of
trying to assess age related problems during the development phase is valid as it is easier to
change the design if it does not fit a determined group of users that we are addressing than
fixing the application after it has been released. Thus, by making the changes during the
developments phase we make sure that the product will adapt to the user and not the other
way around. Transgenerational design is base in seven principles: safety – making all products
free from danger, injury or damage under reasonable conditions by all expected users; comfort
– provide physical and sensory comfort to the user; convenience; convenience – creating
products that are convenient, handy and appropriate use for all; ease of use – it should be
simple and uncomplicated for all expected users; ergonomic fit – physical fit and
accommodation for all expected users; suitable – appropriate size, appearance a functionalities;
1. SAFETY Design must provide the users freedom from danger, injury, or damage under reasonable conditions by all who may be expected to handle, use them.
2. COMFORT Design must be free from disturbing, painful, or stigmatizing forms or features.
3. CONVENIENCE Design must provide a convenient, handy, and appropriate use for all who would use them.
4. EASE OF USE Design must be simple, uncomplicated, and easy to use. Designs should offer readable and understandable instructions and directions.
5. ERGONOMIC FIT Design must accommodate the physical fit and sensory accommodation for the
widest possible range of appropriate human dimensions.
6. SUITABILITY Design must take in consideration the appropriate size, function, appearance, adjustability, accommodation, and symbolism suitable for the widest spectrum of anticipated users.
7. USER VALUE Design has to be useful with user-sensitive value-added perceptions, components, and features. User value satisfies consumers' desire by translating expectations into positive reactions
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user vale – provide value for our users [22]. These are the basis of this design method, in which
the focus is to understand and neutralize the discriminating effects related to aging, and also
the impairments as sensory and physical. All this is done with the object of creating a product
without penalty to any of the users groups.
Table 1 - The transgenerational design principles in order to provide a better product to everybody - Adapted from [22]
User pyramid design II.2.5.
The pyramid design was proposed by Benktzon in 1993 as a graphic illustration that divided
the population into three broad and unequal groups (Figure 2). At the base of Benktzon’s
pyramid we find the larger group with the able-bodied people, the middle group comprises
people with reduced capabilities, and at the top people with severe impairments, including
people with very limited strength and mobility in their hands [23]. The principal idea of this
design strategy is that if we create software that can be used by the users at the top of the
pyramid, the users bellow will also be able to use. The main limitation here is that some designs
for impaired people may be sub-optimal for non-impaired users. When building a product
based on the pyramid concept, both a top-down and bottom-up approaches can be used. A
bottom-up approach takes a mainstream product and pushes the boundaries of the design
aiming at including as many users as possible. This kind of design is created for able-bodies
users and tries to make it more inclusive in an attempt to enlarge the target group of the
application [24].
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Figure 2 - The pyramid design method.- Adapted from [25].
As for the top-down approach, because generally an application build for severely disabled
people can be used by able-bodied users, the objective of this approach is aim at making the
interaction as much user friendly as possible for capable users [26]. In conclusion, this approach
has the caveat that an application made for the top group will probably result problematic for
the individuals on the bottom layer. Because the user interface is a key element on computer
systems, some caution needs to be taken to ensure a comfortable and appropriate interaction
with every user.
Inclusive design II.2.6.
Inclusive design was proposed in 2000 by Simeon Keates et al , and is an approach to the
creation of products and environments to be usable by the largest target population, regardless
of their age, abilities or situation in which they are used [27]. This method took the pyramid
design idea and push it forward by creating an inclusive design cube, where each axis of the
cube represent users capability and the enclosed volumes shows the population coverage
(Figure 3). The user pyramid approach as seen before split the users in three groups, severely
impaired, moderately impaired and unimpaired. The Inclusive design cube extends this concept
with tree design approaches, where each of the cube dimensions represents one skill and its
level. The X axis represents the cognitive capability, the Y axis represents the sensory capability
and finally the Z axis represents the motion capability. It shares the same working principle
with the pyramid design, if you design a product for the less capable, people with more
capabilities will be also able to use it.
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Figure 3 - The inclusive design cube. Adapted from [27].
The development process of inclusive design consists of five stages. All these stages of the
development process of inclusive design have the focus on the users and their needs, what is
one of the main concerns of adaptive systems [21]. The first stage of inclusive design relates to
the user needs [28]. In this stage we have to define the requirements of our system, for which
we need to take into account two aspects: first the product objective, and second the potential
users.
The second stage addresses user perception, in an attempt to understand how the information
will reach the user. Outputs to the user usually take one of three forms: visual symbolic
feedback, visual textual feedback and audio feedback. Visual symbolic feedback is often very
easy to understand - an image is worth a thousand words - but is difficult to reach users with
poor vision capabilities. Visual textual feedback is not as immediate as symbolic feedback, and
requires cognitive ability to read. Last, a main limitation of audio feedback is the sound
intensity, which limits its use in quiet spaces and in noisy or multiuser environments. The secret
to success is balancing the output of the system among the three modalities.
The third stage aims at assessing user cognitive abilities, in an attempt to understand if the
users understand what is going on and if the behaviour of the system is matching the user’s
expectations.
The fourth stage is about the user’s motor function and how the physical interaction will be. For
instance, touch-screens are easy to learn but hard to use if not positioned at the right height.
Further, height is important because it can exclude kids, short persons, or people on wheelchair.
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The fifth stage is the final usability stage where we have to evaluate the overall system usability
and accessibility. After this stage the system goes into re-designs taking into account all the data
gathered from the previous stages.
Ability-based design II.2.7.
Ability-based design was proposed in 2010 as a new approach to developing for everyone [5].
The question that this method tries to answer is “what can a person do?” instead of “what
disabilities does one have?”. The main idea behind it is to focus the development on the abilities
of the target group and design to take advantage of what the users’ condition still allows them
to do. Ability-based design consists of seven principles, split into three groups (Figure 4).
Figure 4 - Ability-based design principles. Adapted from [5].
The first two principles (1-2) relate to the designer’s group, and are the ability and accountability
principles. The ability principle states that development process show focus the user’s abilities
and not his dis-abilities, focusing on what all users can do, as for the accountability principle
that relates all the user performance issues to the designer and not to the users. These two
principles are classified as required for any ability-based design and constitute an essential
change from disability to ability design.
The next two principles (3-4) are adaptation that consist in transforming the interface self-
adaptive or user-adaptive in to provide the best possible match to the user abilities with the
objective of removing the need for external assistive systems and forces the system
accommodate user needs and not the opposite., and transparency which specify that the
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interface should give the user awareness of the adaptations and everything that can be done
with them. These two principles are related to the interface and they are classified as
recommended in all ability-based system.
The last three (5-7) principles concern the ability-based systems in general, and this principles
are: performance and context (5-6) which are both recommended and the last one (7) is
commodity which is encouraged to be used. The performance principle recommends that the
system should regard user’s performance and monitor, measure and predict that performance.
As for context principle it states that the system should be proactive and sense the context and
anticipate its effects on user’s abilities. The last principle it commodity and it is encouraged in
an attempted to remove the barriers cause by price/cost, complexity and maintenance. Through
the usage of commodity it is possible to distribute ability-based systems via web without the
challenge of manufacturing or distributing specialized hardware. In conclusion, for a design to
be considered ability-based it must have the first two principles of ability and accountability, as
for the rest of the principles if they are correctly applied it can significantly improve the design
usability and accessibility.
Conclusion II.2.8.
In this section we have described a set of design approaches. Some of them are being applied by
governments in an attempt to improve the quality of live for people with needs to the modern
society. Some of the methods originate from other disciplines aiming at physical accessibility,
but they can be generalized to software design. All of the presented approaches share the goal
of creating an environment that is accessible by everyone. Although the approach they take to
solve the problem is different, they share a common goal.
II.3. ARCHITECTURE DESIGN
A crucial step in designing any kind of application is to choose the most appropriated
architecture. We have studied two architectural approaches that can be used to build an
adaptive system. The first model is to build the program under the original application (Figure
5(a)). With this model the adaptation will interact directly with the application and change the
original source code, making the enhance merge with the application. For this we need to
ensure that the communication between the original application and the operative system is
successfully made through the adaptation that was built. Another was to merge the adaptation
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with the program is through the operation system, providing an infrastructure for the assistive
technology to communicate out of process to other application, what requires trustworthy
access to the operative system functionalities. Also these way users have a feeling of interacting
with the application and with the adaptation, which is good due to the important of notifying
the status to the users. The second option is to build an adaptation that is going to work over
the original application like a mask that will change the user interface without having to take in
account the communication with the operative system since it only work as a mask that changes
the interface without change the functionalities or the original source. Both this approaches
gives support on how should we project a user interface adaptation software, but it is important
to remind that this should only be used to improve de usability in existing software, because
when building new software this should be already taken in account right from the beginning.
As a result of this analysis the proposed adaptation-based system seems to be appropriate for
adaptive solution, since we don’t need to change the source of the base application there is no
policy violation problem with the creator company in case of the adaptation being an outside
job.
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Figure 5 - Adaption based system proposals. Adapted from [29]
rever
II.4. TYPES OF USER INTERFACES
The interface can be defined as where the interaction between humans and machines occurs,
and therefore it is the key element of any interactive application. Skipping over interface design
methods can result in interfaces that are confusing and hard to use. In this project we want to
adapt a computer program to be usable at the same time user-friendly for our target population.
For this we need to study what kind of interfaces can be build and what benefits would each of
them bring to our users [30]. The first and most common type of user interface is the Static User
Interface. This type of interface is present in almost all programs we use on a daily basis. This
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type of interface, as the name suggests, does no change over time and remains as the designer
created it. Another type of interface is the Adaptable User Interface. In this case users can
customize the interface as they want in an attempt to accommodate the user needs and leave’s
them more comfortable with the interface, allowing the user to take the most out of the
application. The third type is the Adaptive User Interface. In this case the computer stores user
action patterns and automatically changes the interface in an attempt to improve the
performance of the user. In essence, this approach adapts the layout and elements to the needs
of the user or to the context. The last type of interface is the Mixed User Interface, where the
adaptive and the adaptable interfaces are combined onto a single one. This type of interface
shares the control of the adaptation on the application with both the computer system and the
user, letting the user decide if he wants to adopt the changes that system proposes or if it is
more desirable to ignore them.
Figure 6 shows an example of a static menu (a) and an adaptable menu (b). It can be observed in
(b) that instead of having a group on the top of the menu created by the designer, the user can
chose the more frequently used options and place them manually at the top. This approach
gives the user more power over the application [29].
The experiment realized by Leah Findlater et al [30] studied the comparison between static,
adaptable and adaptive user interfaces. The goal of the experiment was to compare the
efficiencies of the different types of menus. For each type of interface, a split menu was
implemented (Figure 6). For the static interface, it consisted of a classic split menu where the
items on the top partition where the ones that occurred more frequently during the
experimental task. For the adaptive one, there was an algorithm that computed the most
frequently used options and moved them to the top. For the adaptable one, the goal was to
create a simple user customization process. The experiment was realized by 27 persons, users
where split between three different test paths: Static – Adaptive – Adaptable; Adaptive –
Adaptable – Static; and Adaptable – Static – Adaptive. Every participant was confronted with
the three types of menus and the time they took to perform the required tasks was recorded and
is showed in the Figure 7.
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Figure 6 - Two aprotches to dropdow menus: (a) static
split menu, (b) adaptable split menu. Adapted from
[30]
Figure 7 - Boxplot of menu types versus speed, from Findlater et al. experiment (N=27). Adapted from [30]
From the box plot in Figure 7 we can see that static and the adaptable had the same time
response median, but with a smaller dispersion of data in the static case. The adaptive revealed
to be slower than the adaptable one. This was not the case if users had used the adaptable
interface first [30]. Interestingly, four out of the five users that did not customize anything
experienced the adaptable menu first, suggesting that users did not understand the
customization process [30]. On the other hand, users that started with the static or adaptive
interface moved the more frequently used option to the top when confronted with the
adaptable menu. Overall, users preferred the adaptable over the static menu, but generally not
the adaptive one. Consequently, we see that even taking more time to do the tasks, users feel
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more comfortable when they control the menus and customize them. This led to better
perceived performance and higher overall satisfaction.
Another study that was conducted by Debevc et al. compare an Adaptive bar that allowed users
to customize the interface and also would suggest changes to the users in order to improve the
usage of the application, with the original built-in toolbar customization facility present in
MSword at the study Debevc et al. compare their Adaptive bar to the built-in toolbar
customization facility present in MSword at the study. The tool bar presented by them was
classified as mixed interface because it allowed the user to change as they want and on the other
hand would suggest the changes to the users. They stated that mixed interfaces give the user a
notion of what they can gain through adaptation through the suggestions given by the system,
and also by giving the final decisions to the user it increases the overall satisfaction as in
adaptable [31].
Paper Interface: Static Interface: Adaptable
Interface: Adaptive
Interface: Mixed
The experiments conducted in MsWord. Users where tested in the different interfaces with the objective of comparing the three approaches (static, adaptable, adaptive) [30]
Was the faster, but the difference was not significant.
Faster that adaptive, except for people that start with this type of menu.
Was the slowest, except for people that used the adaptable first.
*
Users preferred this menu over the others Four out of the five users that did not customize the application started with it.
The experiment was conducted on MsWord. First with an adaptable version for four weeks and then switched for the adaptive type for two weeks. [32]
20% of the participants of the two week experiment like better the original version of MsWord.
65% preferred the new adaptable version.
15% did prefer the adaptive version given later called Smart Menus.
*
Greenberg et al. compared an adaptive versus an static strategy for hierarchical menu organization in a telephone directory system [33]
Only 31% preferred the static.
* Was significantly faster.
*
Fewer errors. 69% preferred the
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adaptive. A simple interface where the most the items position would change according to the frequency of use [34]
81% of the users preferred the static.
* Was slower. *
Debevc et al. compare their adaptive bar to the built-in toolbar customization facilities present in Msword [35]
Was slower. * * Significantly improved the performance.
* Not considered in the experime
Table 2 - – Summary of the study analysed on the four types of interfaces and their result.
After analysing these experiments we find inconsistent results for the same types of menus.
This effect seems to be related to the nature of the application in cause. One hypothesis that
came out of these studies is that in more complex applications users tend to be more
comfortable with adaptive systems because they save time sorting the more frequently used
actions. However, when it comes to small lists of options, users feel confused by the changes
and can take more time performing the task. As for the mixed interface, it shows promise but
there is little research done on them and there is still need to do further research on this type of
interfaces.
II.5. TYPES OF USERS
A very important step in the development of any assistive application is to create study and
understand the group of users that our program will target. Therefore, we need to determine
the group of people we are addressing with our application so that we can design the
technology according to their needs. In this application domain, we can divide users in 3
groups: elderly people (usually taken as impaired users because they lose skill as they get older)
[29]; low vision users; and dexterity impaired users. The two last groups are presented
compared to each other to show their differences.
Elderly users II.5.1.
Elderly users usually lack confidence when confronted with technology because they feel that
they are too old for the new developments [29]. Further, complex and multi-functional systems
may present substantial cognitive challenges for elderly, on top of lack of confidence. When
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developing for elderly we need to support their confidence. For instance, one of the things that
elderly users do not like is undesired changes that result in confusion. To solve this problem we
should try a three step approach [29]. First we should let them know that there is a solution for
the problem they are facing, creating awareness for the issue and it is not their problem. Then
we should explain the existing solution, and finally present the solution to them. This approach
helps in the sense that the change is not so aggressive, and they can understand what has
changed and why. Also, according to the study made by Sloan et al. [29] elderly users tend to
like less disruptive accessibility technologies that does not change the interface completely.
Elderly users are generally classified as a group and they are compared to impaired users
because of the loss of motor and visual capabilities due to the ageing process. In the table (Table
3) below we can see three subtypes of elder users according to Peter et al. [36], where they
groups elderly users in three groups: fit older people that have less impairments and less need
for assistive technologies, frail older people which have one or more disabilities and great skill
reduction in comparison with the fit group, and finally disabled people who grow older and
with the aging the long term disabilities deteriorated and are the group that need assistive
technologies for most of their task.
Table 3 – Comparison table between different types of elderly users
Another study about elderly people and their problem while interaction with the web was
conducted by Kurniawan et al. [37] and they approach the by dividing the issues in three big
groups: vision impairments, dexterity impairments and cognitive impairments. The results they
got are summered in Table 4.
Area of impairments Type of the problem Problem
Vision impairments Use of graphics 1. Icons should be simple and meaningful
Fit Older people Frail older people Disabled People who grow older Do not appear disabled Has one or more disabilities The long term disabilities affected
the ageing process and created more disabilities
Still need some assistance on doing some tasks due to age
Often disabilities are severe The disabilities are severe
Great reduction of skills in comparison with fit older people
reduction of skills
Need a lot of assistance on performing task
Requires assistance on almost every task performed
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Target design 2. Providing larger targets
3. Clear confirmation of target capture
Navigation 4. Provide location of the current page
Content layout 5. Avoid irrelevant information on the screen
6. Important information should be highlighted
Text design 7. Avoid moving text
Dexterity impairments Target design 8. Providing larger targets
9. Do not expect double clicks
Browsers windows features 10. Avoid scroll bars
Cognitive impairments Use of graphics 11. Graphics should be relevant,
not for decoration
Navigation 12. Clear navigation should be provided
Browsers windows features 13. Avoid pop-ups and animated advertisement
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Cognitive design 14. Reduce the demand on working memory
Table 4 – Elderly issues while navigating the web associated with the type of impairment it is related.
Low vision users vs. dexterity impaired users II.5.1.
For low vision users the main challenge is related with the display, while the problem for motor
impaired users is in the physical interaction. In the case of low vision users, aspects such as
display size, lighting, and distance from the screen need to be addressed in order to allow for a
more comfortable use of a system. Instead, for motor impaired users not only the application
need to be adapted, but also the interaction with the system needs to be taken into account.
More concretely, the peripherals represent a key disabling aspect in the interaction [4]. If we
move away from the peripherals and focus only on the application, we need to adapt elements
such as tabs, multiple windows, the mouse double click. Low motor impaired users will not be
able to keep the mouse pointer still for the two clicks, or may not do it fast enough.
An example of the mentioned adaptations was presented by Gajos et al [38]. In Figure 8 we can
see the adaptations made in Supple++ to accommodate each type of user. For low vision users
the main change was the size of the objects and text. Instead, when addressing users with
impaired dexterity the main concern was the distance from the each available option so that
pointing and clicks would be less problematic for them. For this reason it is important to
understand what can we compacted in order to make objects bigger without making the
application not user friendly.
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Figure 8 - Example of GUI interface that was automatically generated using Supple++. A) Typical interface, b) interface for a mouse users with impaired dexterity, c) adaptation for low vision user, and d) for users with both low vision and impaired dexterity. Adapted from [38]
To conclude, related work shows that there is a lot of research done in this area over the past
years, and that governments are getting more interested in accessibility and inclusive design
methods in an attempt to provide a barrier free society. However, more work needs to be done
in this field to make informatics systems able to usable by everyone. It is important to note that
elderly users are an important segment, and studies conducted by the European Union [17]
predicts that the percentage of elderly people become a major group in our society in the next
twenty year. Therefore it is important to accommodate technologies to their needs.
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III. ADAPTNOW – EXPERIMENTS AND ARTIFICIAL INTELLIGENT SYSTEM
AdaptNow web base enhancement application for elderly and was designed throw an
interactive process with several experiments with users. The first interaction with users was
designed to understand how people would react to what we proposed and what they would do
with the given tools. Also we wanted to analyse if there was any relation between webpage
characteristics and user adaptations.
III.1. WEB ENHANCEMENTS AND ARTIFICIAL INTELLIGENCE (AI) MODELLING
In order to fully understand what elderly users would do with a toll like we proposed and how
would they react and use it we conducted an experiment that would help us better understand
our target group and what the issues that they really had.
Method III.1.1.
For the study (anexo X) we allowed users to modify several features of web pages, such as 1)
highlighting (box/underline) clickable objects with user defined colours; change the mouse
pointer 2) size and 3) visual aspect; modify 4) zoom as well 5) font sizes; and 6) page scrolling
mode. The highlighting features would mark all clickable links with a specific colour and
thickness controlled by the users as they fell. With this feature we wanted to understand if it
would create more awareness for what is around and what they can interact with.
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The second and third features was the mouse size and colour, this was done with a set of
custom make mouse pointers that we created in three different size and that would change
colour if hover a clickable area. We asked users for every webpage what mouse pointer they
would use and what size would be more suitable, we tested three different sizes and nine
different models. This was tested, since one of the problems detected was the fact that elderly
users would lose sight of the mouse pointer and by making it bigger we want to provide an
easier navigation.
The last feature test was tested was the automatic scroll that would allow user to scroll the page
depending the position of the mouse, this could be done in two different way, one being only if
the mouse moves on the top or bottom of the page and the other every time the mouse in o
certain position. With this we wanted to remove another of the issues related to mouse control.
This study was performed with 12 users between 51 and 63 year old and was conducted in 10
webpages from 5 different types (social, news, travel, mail and search engines), and in each
webpage we conducted the experiment two times if different resolutions. Due to the fact that
users had to enhance each webpage two times each users only experimented 5 distinct
webpages.
During the interview process we asked users how would they change the webpage, using a set
o given tools, how would they change the webpage in order to improve the comprehension and
effectiveness of the interaction with the given webpage. This process was repeated for all the
experiments webpage. With this type of approach we gave the users the system full control and
made them aware that all the changes should be undone and that they could change who they
fell would make them more comfortable. One of the aspects that we focuses was if the user
could read well the text on the webpage or if increasing the text font or applying zoom would
help in this situation. After finished the adaptation, the system would save the configuration as
well the webpage characteristics (website dimensions; number of images, buttons, heading tags,
divisions, scripts, and links; flash content; image sizes; and screen resolution).
Having in consideration all the data collect we realizes a multivariable linear modelling
approach, using step-wise regression to create a model of user’s preferences based on the web
page characteristics. Another mathematical model realized was a principle component analyses
with the intent of identifying possible behaviour groups and what would be the impact of that
in the analyses.
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Results III.1.2.
The first experiment, as explained before, allowed us to define the core AI that models each web
enhancement (zoom factor, font size, mouse cursor, etc.) as a multivariate linear regression of
the variables that define the web page characteristics (resolution, page height, number of words,
etc.). Interestingly, our modelling approach allows us to identify and quantify to what extent
web site features do determine the enhancement choices made by elderly (Table 5).
Propriety P-VAL Model signify-cance.
a) b) c) d) e) f) g) h) i)
Zoom (0-100) 2,61E-10 *** 0,0001 - - - 0,0088 - 0,0005 0,0237 -
Text Size (0-100) 3,06E-18 *** - 0,0001 0,0008 - - - 0,0001 - 0,0001
Link Enhances
Box (0-1)
0,4264 - - - - - - - - - -
Underline (0-1)
0,4264 - - - - - - - - - -
Colour 0,1851 - - - - - - - 0,0108 - -
Border Size (0-100)
0,0034 ** - 0,0001 - - - - - - 0,0001
Button
Enhanced (0-1)
3,60E-173 *** - - - - - - - - -
Colour 0,0356 * - - - - - 0,0003 - - -
Border Size (0-100)
1,38E-09 *** - - - 0,0003 - - - - -
Table 5 - Webpage characteristics and their corresponding significance in the web enhancement AI model. The used web page characteristics are a) Screen Width, b) Page Height, c) Number of words, d) Biggest image Width, e) Average image width, f) Number of scripts, g) Number of H1 tags, h) Number of H2 tags, i) number of divisions. * p<0.05, ** p<0.01, and *** p<0.001.
From the model built we were able identify a set of features that we could not model due to
their nature, this features where the underline and box due to the fact that they had binary
result and that when users did not choose one the other was chosen, and also because users
tended to keep their choice of underline of box during all the experiment webpage. With this
information we can conclude that box and underline is a user’s specific characteristics and that
should be treated as such. Another of the features that we were not able to model was button
enhance because it was also an binary option and due to the fact that 100% of the participant
activated this option we could only conclude that the button enhance should be active as
default.
The last feature that we could not model was the colour of the link and button enhance, even
though the model was given significant on the calculations we still could not model colours,
this happen because the values are completely district and we cannot compare red with blue.
But we could observe that approximately 91% of the users tend to keep the same colour during
the experiment, and with this in mind we can consider this also as a user’s characteristic.
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Finally we got the 4 models that where significant, zoom, text size, link border and button
border, and with them we calculated throw a step wise regression the weight of the webpages
characteristics on each (Table 6). We got for each model an AI algorithm that based on the
webpage characteristics would apply a certain value. Starting with the zoom, we got that the
zoom value would be equal to “0,0347 X Screen Width + 0,0209 X Average image width + 0,9153
* Number of H1 – 0,1047 * Number of H2”. With this formula we could calculate desired the
amount of zoom in any webpage with an error of 5,57% and considering that the zoom value
varies from 0% to 100% and that the minimum increment value is 10%.
Another significant model was the text size were the amount of increment on the font was
calculate from “0,0079 * page height - 0,0128 * number of words - 0,04 * number of H1 - 0,04 *
number of divisions”, this model had an error of 6,6% and with the value variation from 0% to
100% with a minimum amount of 10%.
As for the link border we got that the value was gotten from “0,0038 * page height - 0,0269 *
number of divisions”, this value had a 7,9% error with the border size going from 0% to 100%
and with the minimum increment value being 10% which again is bigger.
The last enhancement that we were able to model was border size and its calculation was only
relate to the biggest image with the value being “-5,533 * biggest image”, and again in contrast
with the other value we had the border amount ranging from 0% to 100% with an error of 5,6%.
All this calculation is going to be used in our AI enhancement that will enhance any webpage
based on its characteristics. And for the features that we were no able to fully model we will
used them as a user specific and associate them with the users account due to the nature of the
data and the tendencies of the users during the experiment.
Propriety Mean
Error (Un) a) b) c) d) e) f) g) h) i)
Zoom (0-100) 5,5739 0,0347 - - - 0,0209 - 0,9153 -0,1047 -
Text Size (0-100) 6,6132 - 0,0079 -0,0128 - - - -0,04 - -0,04
Link Enhances
Box 0,4207 - - - - - - - - -
(0-1)
Underline 0,4207 - - - - - - - - -
(0-1)
Colour 0,7008 - - - - - - 0,0724 - -
Border Size 7,8799 - 0,0038 - - - - - - -0,0269
(0-100)
Button Enhanced 0,0023 0,0004 -0,0002 - - -0,0765 -0,0031 -0,0765 -0,0124 0,0006
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(0-1)
Colour 0,5833 - - - - - 0,0247 - - -
Border Size 5,5729 - - - -5,533 - - - - -
(0-100)
Table 6 - The weight and error of each of the feature model in relation to the webpage characteristic. The used web page characteristics are a) Screen Width, b) Page Height, c) Number of words, d) Biggest image Width, e) Average image width, f) Number of scripts, g) Number of H1 tags, h) Number of H2 tags, i) number of divisions.
From the principle component analyses that we conducted (Figure 9) we were able to identify
user’s tendency and understand if there were relationship between featured and in case they
exist which are. With this analyses we were able to identify a clear relation between zoom and
text size which show that adding zoom reduces the amount of text size increment and vice
versa, which also indicates that we have two distinct groups of users, being that one focus more
on zoom and another on text size. This shows that creating personal models for each users after
they used the application a certain amount of time would be the most appropriate way since we
can’t identify which type of users we are dealing with. Also we were able to confirm the clear
relationship between link box and underline with their result being completely opposite.
Figure 9 – Principle component analyses of the date with the objective of finding relations between the features.
The last featured option was the scroll we got that in average users classified the scroll only
when the mouse is moving with 4 out of 5 for improving the navigation, while the scroll on
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fixed position only got 3 out of 5. From the interviews and the user’s reaction we understood
that the scroll on movements gave them more control and due to that was considered as better
and given preference due to that. Also one of the inquired suggested that the application should
support side scroll. Having in consideration this we fell that the scroll system gives more
control to users that lack motor coordination and cannot control with precision the original
scroll.
In relation to the mouse enhance where we proposed three different sizes (Figure 10) an several
models, we got hat all users went with the medium size, also everyone chose the same model
during the experiment, and taking in account that it was asked on every webpage if they
wanted to change they model we can say that the mouse model used it is not related to the
webpage but to an user preference. With this in consideration we decided that the mouse model
propriety should be a related to the account and that we should remove this customization from
the main view of our interface. As for the less liked features we got that 83% classified the font
family as the less important feature followed by the border thinness with 67% and the button
marking with 58%. From here we can say that the font family had no effect on the users and that
and due to that should be reconsidered as a feature, and as for the mouse enhance is the priority
feature and the one most users classified as a must have.
Figure 10 – Example of mouse model used during the experiment where we can see the different sizes used. a) normal mouse appearance; b) mouse appearance
when hover a clickable area
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In the end of our experiment we inquired users about the featured enhancements and asked
them to choose the three that helped them more. From here we got that 91% of the users chose
the mouse enhance as the feature that helped the more, followed by zoom with 50% and finally
the scroll on movement and the colour options with both having 42%. Also we inquired users
about the utility of such a toll on a daily basis we got a 4 out of 5 which we considered an
indication that such a toll would improve the navigation experience for elderly users.
III.2. ENHANCED HISTORIC AND BOOKMARK VIEW
After the analyses of the navigation, we concluded that other aspect could also be enhanced and
improved for a better an easier web experience. With that in mind we hypothesized a revamped
view for the historic and an addition of dynamic bookmark view. With that new hypothesis we
decided to conduct a new survey that would help us understand this issue and build a
validated new system.
Methods III.2.1.
This second survey conducted had the objective of understanding the most relevant
information while navigating, and how should it be displayed. With that in mind we wanted to
create a revamped historic view and a dynamic bookmark navigation, and for that we
conducted a new experiment where we interviewed 17 people of two age groups (>40 (A) and
<40 (B) years old). The average age from was 47.8 and 22.6 years old for A and B respectively.
The reason that made us interview also a younger group (B) was the fact that they have more
web experience. Information provided by B could bring in interesting insights and can acts as a
control group for A.
We asked users about what information they value more in a historic view (time spent on a web
page, number of visits, type of content), how to highlight pages they visit the most (icon size,
colour, contrast, total visits counter), and how to present the information (all pages at once,
showing the order of navigation, grouping pages of the same domain). Another aspect that we
focuses was how should the information be displayed, and so we asked users to create their
own icon displayed with the information that they felt relevant and on the position they
considered more relevant. With this in mind we wanted to build a model of the appropriate
icon that we should display either on the historic view or on the bookmarks view. Due to
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number of participants on the experiments the presented data was obtained throw the
calculation of the mean value.
Results III.2.2.
In relation to the performed survey we got an interesting insight to what users would react
better and what was really important for them while navigating the web. The following results
are splitted by each question asked, the obtained result and graphic that sums up the results.
Question: “Number of hour using the computer per week”, with possible answers 1 to 3 hours,
3 to 7 hours and +7 hours, from where we obtained ( Figure 11) >40 group uses the computer
between 1 and 7 hour per week, while the <40 group is situated almost on 7+ hour per week.
This shows that the <40 group is and experienced group, and also that the older group has a
certain level of experience, which may help us improve the accuracy of the result due to the
existence of web experience.
Figure 11 - Number of hour using the computer per week
Question: “Which features would be more important to add shortcut to a webpage on the
screen?” Figure 12, the featured options where: time spent on the webpage, number of times the
webpage was visited, and type of contend. This feature where all asked to classify from 1, very
low importance, to 5, very important. From this question we wanted to analyze what would it
be more import to add bookmarks, from where we got that according to >40 group the most
important is the number of visits, classified between average importance and important, while
the other two features where classified between low and very low importance. As for the <40
group both option, time on the page and number of visit, where classified as important while
the page content was classified has of average importance.
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Figure 12 – Features importance for adding a shortcut (bookmark) to the webpage from each group of inquired.
Question: “Which features would you use to differentiate the most visited webpages?” (Figure
13), the featured options where: icon size, color of webpage name, showing the number of visits
to the webpage, webpage icon background, and color contrast. This feature where all asked to
classify from 1, very little importance, to 5, very important. Here we got similar results on both
groups for some of the options, icon size and the color of webpage name where classified by
both as of average importance. As for Icon background as contrast the >40 groups classified it
as of average importance while <40 classified it between low and average importance. In
relation of number of visits >40 group classified it between low and average importance while
<40 puts it between average and important.
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Figure 13 – Features used to differentiate the most visited webpages for each inquired group
Question: “Which features would you use to differentiate the webpages where you spend more
time?” (Figure 14), the featured options where: icon size, color of webpage name, display the
number of visits to the webpage, webpage icon background, and color contrast. This feature
where all asked to classify from 1, very little importance, to 5, very important. In this features
both groups where in sync in most of the features, with classifying icon size, name color and
number of visits as of average importance. As for icon background and contras >40 group
classified It also of average importance while <40 gave it lo importance.
Figure 14 - Features used to differentiate the webpage where the most time was spent according to each inquired group
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Question: “On a search through the webpage historic, what would make it easier to find the
desired page?” (Figure 15), the featured options where group all pages of the same domain,
showing all pages at once, showing the pathway of pages visited webpages. This feature where
all asked to classify from 1, very little importance, to 5, very important. Here we want to
understand what would help during a search throw the navigation history so we could
compare to the actual model presented in the actual browsers. With this in mind we can see that
the actual model was classified by both groups as of low importance, while grouping all pages
of the same doing was classified as important. Also the other featured option, showing
pathways has average importance to the users.
Figure 15 – How should the historic be displayed to facilitate the search.
Question: “How much would it help having an application giving audio feedback?” (Figure 16).
This feature was asked to classify from 1, very little importance, to 5, very important. With this
we wanted to understand how users would feel by having voice feedback of their action while
navigating on the web. Here we got some expected results, with >40 classifying this as of
average importance and, in the other hand, the most experienced group, <40, gave it low
importance.
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Figure 16 – Inquired answer to if audio feedback would improve navigation.
Question: “What type of information should be communicated by voice” (Figure 17) we asked
users to select what would help them more, the available option where confirmation of insert
data, notification of webpage state, suggest possible option for next action, and explain all
available options. This question had Yes/No answers. Here we got that around 60% of the
inquired chose confirmation of inserted data as a viable feature, as for suggestions and
explaining all options both had around 25%. In relation to notifications, none of the inquired of
the >40 group selected it in the other hand around 50% of the <40 group chose it as a viable
option.
Figure 17 – What inquired classified as the most relevant information that should be transmitted through audio feedback.
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Question: “What would be the importance of having a bar with the most visited webpages?”
This feature was asked to classify from 1, very little importance, to 5, very important. In this
question we got similar results in both groups, with both answering as important the fact of
having a bar with the most visited webpages.
Question: “What would be used to identify the most visited webpages on Figure 18 ”(Figure 19)
we asked users to select what would help them more, the available option where A – Size of the
icon, B – Color of page title, C – Having the number of visit to the webpage on screen, D – Icon
background, and E – Color contrast. This question had Yes/No answers. In relation to this
question we got similar results on both groups for all of the featured options. Being that the
options that chosen the most where icon size, with 65% and number of visits, with 58%. The
other option where given less importance, with background being chosen around 23%, title
color around 27% and contrast scoring 30%.
Figure 18 – Historic view presented to the users with the intent of them choosing which information would be displayed.
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Figure 19 – Inquired classification which information was more relevant on this type (Figure 18) of historic view.
Question: “What would be used to identify the most visited webpages on Figure 20 ” (Figure
21) we asked users to select what would help them more, the available option where size of the
icon, color of page title, having the number of visit to the webpage on screen, icon background,
and color contrast. This question had Yes/No answers. In the above question there were some
disagreements between both groups’ answers. On the icon size feature we got similar results on
both groups, being that 47% chose it as a way to identify the most visited. In relation to the title
color feature, we got some discrepancies between the groups, even with the answer tending for
the same side the values had a considerable difference, with >40 choosing title color with 17%
and <40 group with 33%. In relation to the number of visits, >40 group had split opinions, with
50% selecting this feature, and from <40 group 78% of the inquired selected this feature. As for
the background option both groups were in agreement, with only 23% of the inquired selecting
this options. Finally for the contrast feature only 27% of the inquired chose it, while from <40
group 44% users chose it as a viable option.
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Figure 20 - Historic tree view presented to the users with the intent of them choosing which information would be displayed.
Figure 21 - Inquired classification which information was more relevant on this type (Figure 20) of historic view.
Question: “What would be used to identify the most visited webpages on Figure 22” (Figure 23)
we asked users to select what would help them more, the available option where size of the
icon, color of page title, having the number of visit to the webpage on screen, icon background,
and color contrast. This question had Yes/No answers. In this question groups had difrente
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opinions on most of the features. In relation to icon seize both groups had equal result, with
33% on the inquired slecting this option. In relation to title color and number of visits no one
one from >40 group selected this options leving it with 0%, on the other hand <40 group got
44% and 78% respectively. As for the background we got similar result on both groups again,
with 33% inquirid slecting this feature. Finaly the contrast got discrepant results, with 67 % of
the inquired from >40 group chosing it, and from <40 group only 44%.
Figure 22 - Historic chain view presented to the users with the intent of them choosing which information would be displayed.
Figure 23 - Inquired classification which information was more relevant on this type (Figure 22) of historic view.
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Question: “How would you group the webpage historic?” (Figure 24) we asked users to select
the one that would make it easier to find a designated webpage, the available option where per
day, per week, per month, per day (7 days) and others per week, per day (7 days) and others
per month, per week (4 weeks) and others per month, and per day (7 days), per week (4 weeks)
and others per month. This was a single selection question. Here both groups went with
different approaches; >40 group gave more credit to option per day (7 days) and others per
week with 50%, and <40 group chose option per day (7 days), per week (4 weeks) and others
per month with 56% of the inquired options.
Figure 24 – User classification of historic, being d – per day, w – per week, d/w – last 7 days and they weekly and d/w/m - last 7 days them last 4 weeks and them per month. The graphs are split by groups
Question: “Where would you place each of the following information on the icon?” we asked
users to select where would they place a certain amount of information on the displayed icon.
The information that was asked to be displayed was: A – Number of visits to this webpage, B –
Total time spent on that page, C – Page name, D – Hour of visit, and E – Number of grouped
pages. (Figure 25, Figure 26)
From the analyses of the date of >40 group we got that some types of information had a favorite
place to be placed between the inquired. Information like page name was the only option that
was place on the center bellow the icon. On the sides of the name inquired placed on the left
hour of the visit, this being the only information that they place there, and on the right the total
amount of time spent with a 83% choice. In relation to top, inquired were split between number
of visit to the page and number of grouped pages on the center, on the left side the options
selected where the name with 60% and the number of visits with 40%. As for the right side we
got 50% for the number of visits, and 25% for number of grouped and for the total amount of
time spend on the page. In relation to the information place on the side of the icon, nothing was
D 16%
W 17%
D/W 50%
D/W/M 17%
>40
D 22%
D/M 11%
W/M 11%
D/W/M 56%
<40
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placed on the left side, and on the right side 80% was number of grouped pages and 20% was
hour of visit.
From the analyses of the date from <40 group we got that the choice for the information place
on the bottom of the icon was: on the center 80% was for page name and 10% for number of
visit and number of grouped pages, on the left we got 100% for hour of visit, and on the right
we got 83% for total time spend on the page and 17% for number of visits. In relation to top,
inquired only place on the center total amount of time spent of the page, on the left side the
options selected where the number of visits to the page with 67% and number of grouped pages
with 33%. As for the right side we got 63% for number of grouped pages, and 37% number of
visits to the page. In relation to the information place on the side of the icon, on the left side we
got 100% for number of visits, and on the right side 40% was hour of the visit and 20% for total
time spent on that page, page name, and number of grouped pages. Also we got that 22% of the
inquired said that the number of grouped pages and the total amount of time spent on a
webpage should not be displayed, even though we did not ask that question to them.
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Figure 25 – Information placement on the historic icon view for the >40 group
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Figure 26 - Information placement on the historic icon view for the >40 group
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In conclusion, we got two groups of inquired where the younger group, <40, where a more
experienced group that used more the computer but the older group had a certain amount of
experience due to the fact that they used the computer regularly. The feature that inquired
chose more importance for having a bookmark to a webpage was the number of visits, also for
the <40 group classified as more experienced the time spent on a page is also important,
therefore we will consider both time spent on the webpage and number of visits when
considering adding a certain webpage to our most visited section. In relation to how we should
differentiate the most visited pages from the less visited the data was too similar with the
features of changing the webpage name color and having the total amount of visits to that
webpage present being the ones with a slight advantage, however the differences between the
features where small and so we may include others features as icon size.
In relation to the voice system where we would give some kind of feedback to the users, the
inquired from <40 group gave it low importance and we can relate that to their experience, on
the other hand the >40 groups considered that this may give some help during navigation. As
for what should be communicated both groups agreed that be best option was the confirmation
of data.
Another of the areas that we wanted to adapt was the historic of visited pages, because we felt
that the actual system was hard to use for the users. Whit that in mind we wanted to know
what would be the easier way to find a page on the historic and the answer we obtain was
group all pages of the same domain, what is the opposite of what we had right now on the
browsers. Also having the pathway of the visited pages was given some importance. After this
e tried to understand what kind of featured could be used to differentiate the most visited
pages while navigating so we could create a viable model to be implemented. The most
consensual feature between both groups was having the total amount of visits visible on the
webpage icon. Others features where selected in different way for each of our models, on the
most visited groups icon size was considered also a good option by both groups, this may be
one of the used features, but we still are unsure due to the visual impact that this may cause to
the others users we will add an option to enable and disable icon size. On the tree view historic
we got that icon size with around 50% from both groups and also contrast with around 50 from
<40 group, as for the contrast it could also be a good solution because it is more smother than
changing the size of the icon and had similar results of icon size for the <40 group. Our final
model was the timeline view where users could see their path of the navigation, and the chosen
feature to identify the most visited was the contrast with around 55% of both groups. Also
having the number of visits had 76% between the inquired of <40 group, another thing to note
here what the fact that the icon size only had 33% of selections on both groups, although we
can’t compare this result with the ones of the previous models it is important to note this
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difference. Another thing we wanted to know was how should we group the historic since we
wanted to compare with the actual model of the browsers, here we got different answers from
both groups but they were similar because one was a more generic visualization of the same
model, therefore we will adopt the model that was chosen by <40 group, split the first seven
days per day, the next 3 weeks per week and the rest per month, this was done because this
would group the option chosen by them >40 group, per day seven days and the rest per week,
and let us have a viable model since the only difference between the implemented model and
the chosen by the >40 will be for users that used the system for more than one month and that
want to search for pages that they have visits more than 4 weeks ago. About this theme we will
implement the three models and users can change between them as they like, also we will to
further test the visual impact of some of the features with a visual example of it.
The final question was to understand what data should be displayed and where, and after
analyzing the result from both groups can see that the hour of visit will be bottom left, the name
of the web page will be bellow de icon and that the number of visit to the webpage will be top
right of the icon. This will be the final model of the icon we will present. Although the other
options had valid results we decided not to place them on the final model due to the fact of a
substantial number of the enquired from <40 classifying it as not relevant even without we
asking.
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IV. ADAPTNOW – IMPLEMENTATION
With the knowledge from the two studies and from the state of art we started to build a web
application that will automatically enhance any given web page based on the it’s characteristics.
This would be done based on the AI model that was proposed with the data collected from the
first study. This web application while adapting and enhancing the user’s navigation would
collect and map user’s personal adaptation and webpage characteristics in order to change and
improve the accuracy of our model with more data. Also as said before, since there where two
types of behaviour in relation to adaptation where one group would focus on zoom and the
other on text size, this will allow us to build personal models after a certain amount of time that
would serve as a better fit the end user. With this in mind we will allow admin access to the
application in order to access this information and analyses it. From here we design a series of
model that would help us better understand the normal user’s interaction with the system and
with it improve the usability. This models will present all the desired features of the system,
even if some of them are not fully implemented in the first version, we hope to release them in
future versions of AdaptNow.
IV.1. USE CASES
Following the development of AdaptNow we built the use case diagram (Figure 27) that will
help us better identify the system requirements. With this model we also want understand what
will be the event step during the interaction with AdaptNow. For this model we user three
components, actor - that are both the user and the system admin; action – that specifies the
interaction; and system – that correspond to AdaptNow.
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Navigate to a webpage
Adaptnow User
Change zoom
Change text size
Change link border
Change button border
Activate/deactivate link enhance
Activate/deactivate button enhance
<extends><extends>
<extends>
<extends>
<extends><extends>
Change webpage
<extends>
<include>
Log in
Recover password
Create account
<extends><extends>
Enter AdaptNow <extends>
<inclu
de>
Change personal enhancements
Change link colour
Change button colour
Change mouse model
Change mouse size
<exte
nds>
<extends><extends> <e
xten
ds>
<extends>
Adaptnow Admin
Change AI model
View general adaptation data
View historic
View feeds<e
xten
ds>
System
Figure 27 – Use case diagram for the AdaptNow application.
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IV.2. TASK MODEL
Task models provide possible interactions with the system by the users and are used to provide
a better understanding of how the system interacts with the users and what should be the
expected interaction in the given time. The first model (Figure 28) presented is relates to a
normal interaction with the application, where a user visits a desired webpage through the
AdapNow application.
Figure 28 – Frequent user’s interaction with the AdaptNow system.
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Another of the interaction that we have is the change personal enhancements (Figure 29) where
we place the enhancements that we verified during the experiment as being users related and
not changed frequently. With that in mind we will place this controls all together and with that
remove unnecessary icons that could generate confusion.
Figure 29 – Users interaction for changing personal enhancement’s as mouse and colour.
The last interaction that we model was dedicated to the system admin (Figure 30) that will be
able to manually change the AI model, and also view the adaptation data with the objective of
understanding the evolution of the data and if there are any tendencies between the users.
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Figure 30 – System admin interaction with AdaptNow
IV.3. REQUIREMENTS
From everything that we analysed before in the state of art we built a series of system required
features that would help improving the elderly web experience. Base on Table 4 we created a
new table (Table 7) that to each issue offers a possible solution that we can implement to solve
it. With this in mind we built the system requirement table for the final system and with the
intent of a better understanding the needs of each stakeholder. The requirements were divided
into two groups, the functional that relate to all operation and non-function that relate to the
system.
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Area of impairments
Type of the problem
Problem Solution
Vision impairments
Use of graphics 1. Icons should be simple and meaningful
Try to use icons that they can relate to their world
Target design 2. Providing larger targets
Make the buttons bigger so they can be easily detected
3. Clear confirmation of target capture
Give constant feedback to the user, so user can see if their actions were successful
Navigation 4. Provide location of the current page
It is important for old users to know their current location in the web site, so we should give that feedback to them
Content layout 5. Avoid irrelevant information on the screen
Reduce page density and increase comprehension. It is important to keep the page simple.
6. Important information should be highlighted
Browsing time can be lowered by highlighting the important information
Text design 7. Avoid moving text Moving text confounds the user so it should be avoided
Dexterity impairments
Target design 8. Providing larger targets
Make the buttons bigger so they can be easy to click
9. Do not expect double clicks
Remove double clicks because it is hard for older people to do it
Browsers windows features
10. Avoid scroll bars Scroll bars should be avoided because elderly users tend to have problem with the mouse and scrolling will be another problem
Cognitive impairments
Use of graphics 11. Graphics should be relevant, not for decoration
Remove object that does not serve any purpose for the task that is being performed
Navigation 12. Clear navigation should be provided
Provide help for users to move smoothly over the page
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Browsers windows features
13. Avoid pop-ups and animated advertisement
Block pop-ups
Cognitive design
14. Reduce the demand on working memory
Identifying the clickable areas
Table 7 – Adaptation of Table 4, adding the solution to the uses present previously for the elderly interaction with the web.
Functional Requirements IV.3.1.
The functional requirements relate to all the operation that the system must allow the users
perform. Through the analyses of Table 8 and the experiment conducted we got as
requirements the following list:
1. Change the zoom.
2. Change the font size.
3. Activate and deactivate the link enhance.
4. Alternate link enhance from box to underline.
5. Change the link colour.
6. Change the link border.
7. Activate and deactivate the button enhance.
8. Change button colour.
9. Change button border.
10. Activate and deactivate the scrolling system.
11. Change the scrolling method.
12. Allow users to login.
13. Allow users to logout.
14. Reapply the original setting.
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15. Disable the enhancement on a desired page.
16. Allow users to go back and forward on the webpages
17. Visualize the navigation historic.
18. Alternate between feeds and regular webpage.
19. Change their account settings.
20. Allow users to refresh the current page.
21. Block popups.
22. Block adds.
23. Change the mouse size.
24. Change the mouse model.
25. Allow users registration
Non-Functional Requirements IV.3.2.
The non-functional requirements are related the functionalities which users don’t have control
but they interfere with their performance, but also are related with performance, robustness,
security, scalability, and other.
In our system scenario we can identify the following non-functional requirements:
1. Usability – The used icon must be standard and easy to understand by user.
2. Usability – Notify the user if the webpage has feeds
3. Operability – The system should allow users to adapt and save their setting even
without and account.
4. Operability – System must save the user session.
5. Security – System must save the session using MD5 encryption.
6. Portability – The system must be accessible from any browser.
7. Price – System must be free to everyone.
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8. Scalability – Save all webpage configuration and characteristics, link, buttons, etc., for
enhancement of the AI model.
9. Platform – System must be usable in all operating system.
10. Privacy – All sensible data must be encrypted with MD5.
IV.4. TECHNOLOGIES
Having built all the system requirements we have to analyses the available options for the
development of the application and chose the best option that will best fit our need and the
ones of the users, and in case that we need to adapt the requirements due to restrictions chose
accordingly. For the design of AdaptNow there were three approaches that we identify as
possible web enhancement applications. The three approaches were, first a browser plugin
which would work as mask changing the original webpage view; second would be build a new
browser with all the adaptations on its core; and third and would be Furthermore a web
application that would mask the original webpage. Furthermore
After analysis the proposed approaches we identified the limitation and advantages of each one
(Table 9). Starting with the plug-in we identified that it could a good option but since it
required installation and also users to have a specific web browser, the users that we could
address would be much smaller. With all this in mind we decided that the plug-in was not the
better option and decided to analyses the Browser approach. The browser would allow us
access every functionality that we need and was the most powerful option available, but again
the requirements of installations and requiring users to change the normal web browser would
represent a drastic change on the web usage habits. Furthermore the constant need to
maintenance for the browser led us to also give up on this approach. For the web application
we found that the biggest issues were the security concerns with cookies and associate with that
the cross domain access restriction that denies the ability to open a webpage from another
domain inside our own. For this to work we would need to create and application that would
rebuild the desired webpage locally in order for us to adapt. Being this the main barrier we
decided to further investigate this issue and search for applications that already solve this issue,
understand their approach to it and try finding a framework that would allow us to bypass this
setback.
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Problem Plug-in Browser Web site/server Session No problem No problem Security concerns with cookies
and cross domain access Edit CSS No problem No problem No problem
What does the hard work?
Browser Himself Server
Saves data online? Yes No Yes Multiple browser
compatibility Need some changes No Yes
Operative system compatibility
Yes No Yes
Table 9 – Comparison of possible technologies to use on AdaptNow
After a closer research we identified WebAnywhere platform [39] that was a web based screen
reader for blind users that allowed them access to the internet everywhere for free without the
need for installations. This platform was an open source project that allow users to create their
how screen reader and help improve it This would solve us the cross domain problem that they
already implemented and at the same time improve our application every time a new version of
WebAnywhere is released. With this solution we decided to build AdaptNow as a web
application based on the WebAnywhere platform. Having said this, it means that our project
will be based on a web page application that will use JavaScript to dynamically change the
webpage through the injection of CSS. As for the server side we will use PHP to execute the AI
algorithm and save the user settings and finally for the database we are going to user MySQL.
The reason we had to go with PHP ASP/.net is because the WebAnywhere users PHP and a
Linux server to run and so we keep the same technologies in order to facilitate the future
compatibility.
IV.5. ARCHITECTURE
AdaptNow is a client server web application that that users WebAnywhere platform.
WebAnywhere uses a web proxy to reconstruct the desired webpage locally to overcome the
cross domain restrictions, and with this allow us to apply modifications. What we do is during
the reconstruction of the webpage on the local server we inject a set of scripts that will enhance
the page (Figure 31). This way we are able to keep the compatibility with future versions if they
don’t change completely the reconstruction process. Also we execute some PHP function that
calculate during this reconstruction with the objective of calculating the enhancement values
and with this remove the need of another server communication to get the correct values and
with it improve the performance. AdaptNow also has function library that is responsible to
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interact with the data base and at the same time generate all the enhancements based on the AI
parameters.
Figure 31 –AdaptNow web application architecture based on the WebAnywhere platform.
IV.6. DATA BASE
As show before on the architecture of the system we have a data base that saves all the users
adaptation of the webpages and their characteristic to improve our model. The data base uses
MySQL and PHP and it is executed by a Linux server. This data base saves the data related to
the user historic so they can have access to it in any computer that they login and the
enhancements modal that we use, it is important to note that the data base is already prepared
for the possibility of adding personal adaptation model. In Figure 32 we present the data base
model that the AdaptNow system currently uses.
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Figure 32 - AdaptNow system data base model
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IV.7. APPLICATION FUNCTIONALITIES
Based on the requirements and the solutions presented on the Table 7 we started to implement
the system functionalities. The implemented functionalities that we were able to implement so
far were: zoom, text size, button and link enhance, rss reader, historic view and the mouse
enhance. Also the server side adaptation algorithm is fully implemented to generate adaptation
using the AI algorithm.
Zoom enhance IV.7.1.
The zoom functionality increases the size of everything of the webpage, and for a better
compatibility we users the function that access and uses the browser zoom functionality and
with it keep the compatibility between browser without the need of changes. The zoom
function can be seen in Figure 32 where we present the comparison between the original
webpage and the enhanced page, with the screenshot being in the same scale.
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Figure 33 – Zoom functionality example in the page www.sapo.pt (the two images are in the same scale); a) original page; b) adapted page with zoom
Text enhance IV.7.2.
The text enhance feature increases the text size, variation from 10 to 20 pixels in size. For this
functionality we users JavaScript to inject the font size we want. The result is presented on
Figure 34 were we can check the difference between the text and its readability.
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Figure 34 - Text size enhance feature (the two images are in the same scale); a) original page; b) adapted page with zoom.
Button and link enhance IV.7.3.
The button and link enhance where grouped together since we observed that the users tended
to keep the same colour for both and did not really understood the difference between them we
decided to group the functionalities together and with that reduce the number of item on the
interface. With this feature we can change the size of the border, change the colour that we want
to be marked and if we wanted the underline option or the box. In Figure 35 we can check the
example of a box enhance on the links.
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Figure 35 – Link enhance using the box option with the blue colour. a) Original page; b) adapted page with zoom.
Rss Reader IV.7.4.
The rss readers we build allow users to navigate throw the information with less background
noise and with it improving the navigation. This feature was designed with the objective of
facilitating the navigation on news webpages that usually have news feeds and very complex
webpages. The implemented page is available in Figure 36, and as any other page the
enhancement system also works here.
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Figure 36 – RSS reader of AdaptNow.
Historic IV.7.5.
The historic view will allow user to have a visual view of their navigation and for that we
present a tree view where users can see the navigation inside each webpage domain. The
example of an historic view is in Figure 37 where we present the historic navigation of the
www.sapo.pt webpage.
Figure 37 – AdaptNow historic view
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Ad removal IV.7.6.
With the WebAnywhere framework we are able to remove most of the ads when we rebuild the
webpage locally, what also solves one of our issues identified in Table 7. The example can be
seen in Figure 38 the example the removal of the ad.
Figure 38 – AdaptNow ad removal.
Mouse enhance IV.7.7.
As show before we created a mouse enhance that would change the appearance when over link
and it was customizable in three different sizes (Figure 10). This was done with the objective of
solve the dexterity problem and increase the control and visibility of the mouse. In Figure 39 we
can see an example of how the mouse reacts on a normal webpage.
Figure 39 – AdaptNow mouse enhance. A ) normal mouse; b) mouse when hover a link
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AdaptNow IV.7.8.
With all the features show before we present AdaptNow with its 3 main visual components:
navigation, adaptation, and webpage. The first component presents the user with: 1) an address
bar to choose where to navigate, and a back, forward and refresh buttons; 2) A login
button/functionality is also available where the user can access and modify his/her settings
and default information; and 3) a button to the historic view (Figure 40).
Figure 40 – The entire AdaptNow enhancement features during the navigation.
Uncompleted features IV.7.9.
Some of the AdaptNow feature still required some work, and some have not been
implemented, either due the lack of time or the complexity of the problem. In this section we
will explain the features that still need to be implemented. Starting with the historic there is the
need to implement the view for changing the pages and the period of time we want to view.
The current already has the queries that support that features just need graphic interface.
Another of the not implemented features that will be soon added is the registration feature that
currently has to be done manually by the admin. The interface to change the personal setting
related to the account also need interface. This happen because we decided to change the all this
feature to one place since they were no changed that often.
All this features will be implemented as soon as possible in order to have the first official
version released with 100% of the functionalities as soon as possible.
Limitation IV.7.10.
AdaptNow has some limitations that are inherited from WebAnywhere. Currently they don’t
fully support pages with flash, and have problem with pages like Facebook that don’t allow the
local reconstruction of the webpage. This is a disadvantage of this approach but since the
WebAnywhere is an ongoing project and some of the issues are said to be resolve soon, we can
integrate our application with the newer versions.
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V. CONCLUSION AND FUTURE WORK
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INDEX
References
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