User preferences

Recent high dynamic range (HDR) display devices provide significantly greater output brightness and dynamic range compared to conventional display technology. A possible concern for the extended use of HDR displays is the potential to cause visual fatigue. Furthermore, ambient illumination has a significant effect on the perception of the imagery displayed, and its impact on user preferences for brightness and contrast must be understood.

Larger display surfaces are becoming increasingly available due to multi-monitor capability built into many systems, in addition to the rapid decrease in their costs. However, little is known about the performance benefits of using these larger surfaces compared to traditional single-monitor displays. In addition, it is not clear that current software designs and interaction techniques have been properly tuned for

Background • Approaches to IP integration of WSNs so far: Pure TCP/IP solutions: sensor nodes implement the TCP/IP stack (or a compatible set of protocols such as 6LoWPAN in 802.15.4 networks); and Gateway solutions: System Architecture and Networking PAGE 3 6/30/2010 • One node acts as an application layer gateway (e.g. base station), to make the lower layer protocols from both networks (e.g. TCP/IP, IEEE 802.15.4) transparent and to route information. • Sensor nodes implement the TCP/IP stack (or a compatible protocols such as 6LoWPAN in 802.15.4 networks)

Sensory innovation in the flavor industry is a pro- cess that relies heavily on user involvement to carry out critical sampling trials at a high cost. We are interested in how recommender systems, in par- ticular, have an important role to play in view of addressing some of their key challenges and con- straints. We describe a purpose-built sensory rec-

Collaborative Filtering is one of the most widely used approaches in recommendation systems which predicts user preferences by learning past user-item relationships. In recent years, item-oriented collaborative filtering methods came into prominence as they are more scalable compared to useroriented methods. Item-oriented methods discover itemitem relationships from the training data and use these relations to compute predictions. In this paper, we propose a novel item-oriented algorithm, Random Walk Recommender, that first infers transition probabilities between items based on their similarities and models finite length random walks on the item space to compute predictions. This method is especially useful when training data is less than plentiful, namely when typical similarity measures fail to capture actual relationships between items. Aside from the proposed prediction algorithm, the final transition probability matrix computed in one of the intermediate steps can be used as an item similarity matrix in typical item-oriented approaches. Thus, this paper suggests a method to enhance similarity matrices under sparse data as well. Experiments on Movie-Lens data show that Random Walk Recommender algorithm outperforms two other item-oriented methods in different sparsity levels while having the best performance difference in sparse datasets.

With a rise in the technology for the production of electronic or digital materials, funders and administrators of libraries are increasingly leaning towards providing digital reading materials to users. In crowded cities like Hong Kong where space is a scarce commodity, the save-space feature of digital libraries is an even more attractive reason why users of library facilities in academic and public libraries are being encouraged to read electronic versions of publications.

This paper will discuss preliminary findings of user preferences regarding video game and VR game-based motor rehabilitation systems within a physical therapy clinic for patients with SCI, TBI and amputation. The video game and VR systems chosen for this research were the Sony PlayStation ® 2 EyeToy ™ , Nintendo ® Wii ™ , and Novint ® Falcon ™ and an optical tracking system developed at the Institute for Creative Technologies at the University of Southern California. The overall goals of the current project were to 1) identify and define user preferences regarding the VR games and interactive systems; 2) develop new games, or manipulate the current USC-ICT games to address these user-defined characteristics that were most enjoyable and motivating to use; and 3) develop and pilot test a training protocol aimed to improve function in each of the three groups (TBI, SCI and amputation). The first goal of this research will be discussed in this paper.

We present our experience of building a prototype system based on the Utility Model for adaptive multimedia. The Utility Model is proposed to capture the issues and dynamics in multi-session multimedia systems where the quality of service (QoS) of individual sessions is adapted to dynamic changes of available resources and of user preferences. We present the design and implementation of our prototype multimedia system, and report experimental results. We demonstrate that the Utility Model supports two types of adaptation: reactive adaptation for systems where only a subset of the applications follows the adaptation model, and proactive adaptation for systems where all the applications follow the adaptation model. Our results demonstrate that the Utility Model may be effectively used for dynamic quality adaptation in real-time multimedia systems.

Because of the variety of types of collaboration services used in enterprises today, there is difficulty in integrating related work threads from different collaboration environments. Each collaboration tool differs in storage model, APIs, content organization, content addressing, content formats, user authentication, and user interface. Nevertheless users prefer to be able to choose which collaboration tool they use for a given interaction, and over the course of long-term collaboration, will typically use a variety of tools, including email, instant messages, wikis, blogs, web conferences, and shared documents. The solution presented here is to provide a federated integration of these different collaboration tools to make content access and transfer straight forward between different systems. Additionally, we enable the user to achieve this federation by working directly in the client application of their choice; we illustrate this with plug-ins for MS Outlook, Internet Explorer and Skype. Our architecture integrates both desktop and servercentric tools.

As proved by the continuous growth of the number of web sites which embody recommender systems as a way of personalizing the experience of users with their content, recommender systems represent one of the most popular applications of principles and techniques com- ing from Information Filtering (IF). As IF techniques usually perform a progressive removal of non-relevant content according to

Music is a multi-dimensional experience informed by much more than hearing alone, and is thus accessible to people of all hearing abilities. In this paper we describe a prototype system designed to enrich the experience of music for the deaf by enhancing sensory input of information via channels other than in-air audio reception by the ear. The system has two main components-a vibrating 'Haptic Chair' and a computer display of informative visual effects that correspond to features of the music. The Haptic Chair provides sensory input of vibrations via touch. This system was developed based on an initial concept guided by information obtained from a background survey conducted with deaf people from multi-ethnic backgrounds and feedback received from two profoundly deaf musicians. A formal user study with 43 deaf participants suggested that the prototype system enhances the musical experience of a deaf person. All of the users preferred either the Haptic Chair alone (54%) or the Haptic Chair with the visual display (46%). The prototype system, especially the Haptic Chair was so enthusiastically received by our subjects that it is possible this system might significantly change the way the deaf community experiences music.

The purpose of this study was to examine the effect of depth and breadth in the arrangement of web link hierarchies on the user preference, response time and errors. An experiment is reported, where previous menu depth/breath tradeoff procedures are applied to the web link domain. The variables evaluated were five different web page linking strategies with varying depth and breadth. The results indicate that task completion time increases as the depth of the web site structure increases.

Our research agenda focuses on building software agents that can employ user modeling techniques to facilitate information access and management tasks. Personal assistant agents embody a clearly beneficial application of intelligent agent technology. A particular kind of assistant agents, recommender systems, can be used to recommend items of interest to users. To be successful, such systems should be able to

This study examines the implications of a gendered website production and preference aesthetic for the teaching of computer studies. Where the website production aesthetic is concerned, it finds evidence of statistically significant differences on 13 of the 23 factors against which sixty student websites were rated. These results were suggestive of a website aesthetic continuum with male and female production aesthetic tendencies at either end. The preference tests, conducted with 67 subjects, revealed preferences to be in tune with production aesthetics such that men had a statistically significant tendency to prefer home pages produced by men, and women those produced by women. This latter tendency was higher than the former.

The introductory article to this special issue points out that export-oriented policies have proven superior to inward-oriented policies in delivering both long-term economic growth and quality of life indicators. One reason is that export-oriented policies demand economic liberalization as well as reductions in market distortions fro m import barriers, subsidies, and internal market inefficiencies. However, a number of management writers, including Porter, Michael E., The Competitive Advantage of Nations, Free Press, New York, (1990), have suggested that factor costs and availability are not a sufficient basis for sustainable competitiveness in world markets. Nations will attain global competitive advantages to the extent that they are able to foster a spectrum of related industries led by companies possessing a broad set of managerial competencies. Understanding how world-class industries and companies develop remains one of the major research issues in public and corporate policy. This is even less well understood in the case of developing nations, because they have been less well researched and because most studies have focused on industry policy for newly industrializing countries (NICs) and highly industrialized nations. The dilemmas and decisions of Chocolates El Rey and the Venezuelan cocoa industry richly illustrate the commitment required to achieve world-class competitiveness at company and industry levels. In the early 1990s, Venezuela began to open its economy and to encourage nontraditional exports. This transition came to an early halt as a result of a number of political scandals and public opinion backlash in a country accustomed to big government and managed markets. The policy reversals that followed have had a dismal effect on the Venezuelan economy, which has plunged from one crisis to another. Nonetheless, there have been an increase in internal competition and a drive to increase nontraditional exports. Heightened competition has challenged Venezuelan companies to increase their capabilities, even if they do not enter international markets. Some companies simply have sold out to multinational firms. Others have attempted to develop into world-class competitors. For example, some have forged strate,~c alliances with multinational companies (see efforts made by that company both to raise standards in the Venezuelan cocoa industry and to forge a niche for high-quality products in industrial markets. In those markets, there is a wide supply of high-quality goods, intense competition, and well-defined user preferences. Two of the major challenges set forth in the case are: • Export Strategy: Which market segments to target, how to advantageously differentiate the company from entrenched competitors, how to distribute its products to the appropriate segments, what sort of presence to have in export markets, and what price to charge different channel members. • Developing Brand Equity: How to overcome the negative image associated with goods from underdeveloped countries in such a way that an adequate market share may be achieved at profitable prices. The case lends itself to other teaching purposes as well. It illustrates the scope, uses, and limitations of market research; it also is good for a discussion of the company-level process of industrial reconversion in countries that are liberalizing their economies. The case also would be suited to a discussion of the effects of development policies on company and industry performance. The clouds that were gathering over the Venezuelan economy in 1994 raised once again the specter of renewed exchange control regimes and overvalued currencies that have plagued Venezuela's economy. An overvalued currency could greatly complicate El Rey's pricing in export markets. We hope that the case will encourage research on the development of brand equity (Aaker, D. G., Managing Brand Equity,

We propose and examine the usability and security of Cued Click Points (CCP), a cued-recall graphical password technique. Users click on one point per image for a sequence of images. The next image is based on the previous click-point. We present the results of an initial user study which revealed positive results. Performance was very good in terms of speed, accuracy, and number of errors. Users preferred CCP to PassPoints (Wiedenbeck et al., 2005), saying that selecting and remembering only one point per image was easier, and that seeing each image triggered their memory of where the corresponding point was located. We also suggest that CCP provides greater security than PassPoints because the number of images increases the workload for attackers.

Water was sampled from over 100 sources in Nepal's Kathmandu Valley, including municipal taps, dug wells, shallow-aquifer tube wells, deep-aquifer tube wells, and dhunge dharas (or stone spouts, public water sources that capture groundwater or surface water). Information was gathered on user preference and site and well characteristics, and water was examined for indicators of contamination from sewage, agriculture, or industry. Most problematic were total coliform and Escherichia coli bacteria, which were present in 94 and 72% of all the water samples, respectively. Contamination by nitrate, ammonia and heavy metals was more limited; nitrate and ammonia exceeded Nepali guidelines in 11 and 45% of the samples, respectively. Arsenic and mercury exceeded WHO guidelines in 7 and 10% of the samples, respectively, but arsenic never exceeded the less strict Nepali guideline. Significant differences existed in contamination levels between types of sources; dug wells and dhunge dharas, being the shallowest, were the most contaminated by bacteria and nitrate; deep-aquifer tube wells were the most contaminated by arsenic. Whereas E. coli concentrations decreased with depth, iron and ammonia concentrations increased with depth. These relationships account for people choosing to drink water with higher levels of bacterial contamination based on its superior (non-metallic) taste and appearance. relaciones condicionan que la gente elija beber agua con un nivel alto de contaminación por bacterias debido a su mejor gusto (no metálico) y su apariencia.

One of the challenges today in human-computer interaction is to design systems that are not only usable but also appealing to users. In order to contribute to meet this challenge, our general objective in the present study was to enhance current understanding of the perceptual features that favour users' interactions with Websites. This is a particularly important issue, as users' first impressions when they land on a site determine whether or not they stay on it. We conducted two experimental studies, focusing on one specific perceptual feature: Website colour. The first study investigated designers' and users' preferred colours for a Web homepage. Although researchers generally flag up differences between designers and users, we found that the latter also had several favourite colours in common. On the basis of these initial results, three colours were selected for a second study exploring colour in relation to an entire Website. The main originality of this second study lays in the fact that we used both subjective and objective measurements to gauge the impact of colour, analyzing not only users' judgments but also their Website navigation and the items of information they memorized. Results of this second study showed that colours were a determining factor in the way that users interacted with the Website. Their influence was also observed afterwards, when users were asked to exploit the information they had gleaned from the Website. As such, these findings will have a practical value for Website designers.

In this paper, we discuss the use of knowledge for analyzing and retrieving music contents semantically. First, we present Context-based Music Recommendation (COMUS) ontology to reason desired user emotion state from context and user preference information in the ontology. COMUS is a music dedicated ontology in OWL constructed by incorporating domain specific classes for music recommendation into the Music Ontology, which include situation, mood and musical features. More specifically, we describe the ontologies of mood and situation in music using low-level features like pitch or duration and musical factors like tempo or rhythm. Our proposed ontology defines generic as well as domain-specific concepts whose detection is important for the analysis and description of music in a specific domain. As a novelty, our ontology can express detailed and complicated relations among the music, moods and situations, enabling users to find appropriate music for the music retrieval and recommendation application. We present some of the experiments we performed as a case-study for music recommendation.

... For example, tourists need indoor navigation services in some large museums to see the artifacts in different places in sequence. In addition, posi-tion information brings benefits to self-organization and self-formation of ad hoc networks in the future communications systems. ...

The vast amount of heterogeneous information sources available on the Internet demands advanced solutions for acquiring, mediating, and maintaining relevant information for the common user. Intelligent information agents are autonomous computational software entities that are especially meant to (1) provide pro-active resource discovery, (2) resolve information impedance of information consumers and providers, and (3) offer value-added information services and products. These agents are supposed to cope with the difficulties associated with the information overload of the user, preferably just in time.Based on a systematic classification of intelligent information agents, this paper presents an overview of the basic key enabling technologies needed to build such agents, and respective examples of information agent systems currently deployed on the Internet.

This article addresses the broad question of understanding whether and how a combination of tactile and visual information could be used to enhance the experience of music by the hearing impaired. Initially, a background survey was conducted with hearing-impaired people to find out the techniques they used to ''listen'' to music and how their listening experience might be enhanced. Information obtained from this survey and feedback received from two profoundly deaf musicians were used to guide the initial concept of exploring haptic and visual channels to augment a musical experience.

Operating systems and programmes are more protected these days and attackers have shifted their attention to human elements to break into the organisation's information systems. As the number and frequency of cyber-attacks designed to take advantage of unsuspecting personnel are increasing, the significance of the human factor in information security management cannot be understated. In order to counter cyber-attacks designed

Over the past two decades, great research efforts have been made towards the personalization of e-learning platforms. This feature increases remarkably the quality of the provided learning services, since the users’ special needs and capabilities are respected. The idea of predicting the users’ preferences and adapting the e-learning platform accordingly is the focal point of this paper. In particular, this paper starts with the main requirements of an advanced e-learning system, explains the way a user navigates in such a system, presents the architecture of a corresponding e-learning system and describes its main components. Research is focused on the User Model component, its role in the e-learning system and the parameters that comprise it. In this context, Bayesian Networks are used as a tool for the encoding, learning and reasoning of probabilistic relationships, with the aim to effectively predict user preferences. In support of this vision, four different scenarios are presented, in order to test the way Bayesian Networks apply in the e-learning field.

Considering the increasingly complex media landscape and diversity of use, it is important to establish a common ground for identifying and describing the variety of ways in which people use new media technologies. Characterising the nature of media-user behaviour and distinctive user types is challenging and the literature offers little guidance in this regard. Hence, the present research aims to classify diverse user behaviours into meaningful categories of user types, according to the frequency of use, variety of use and content preferences. To reach a common framework, a review of the relevant research was conducted. An overview and meta-analysis of the literature (22 studies) regarding user typology was established and analysed with reference to (1) method, (2) theory, (3) media platform, (4) context and year, and (5) user types. Based on this examination, a unified Media-User Typology (MUT) is suggested. This initial MUT goes beyond the current research literature, by unifying all the existing and various user type models. A common MUT model can help the Human-Computer Interaction community to better understand both the typical users and the diversification of media-usage patterns more qualitatively. Developers of media systems can match the users' preferences more precisely based on an MUT, in addition to identifying the target groups in the developing process. Finally, an MUT will allow a more nuanced approach when investigating the association between media usage and social implications such as the digital divide.

XML documents are used to exchange data. Data exchange implies the transformation of the original data to a different structure. Often such transformations need to be adapted to some specific situation, like the rendering to non-standard platforms for display or the support of special user preferences. Adaptations are, in fact, transformations of transformations. This report describes a system for specifying XML transformations that allows the transformations themselves to be transformed in the same way as the original data.

During the last decades, digital media have revolutionised media reproduction. The availability of cheap consumer electronic devices that allow the consumption and management of digital multimedia content (eg MP3 players, digital cameras, DV camcorders, smart phones) has caused a media availability explosion. The amount of digital media that has been generated and stored, and which continues to be at an exponential rate, has already become unmanageable without fine-grained computerised support.

The objective of this study was to investigate and report on user preference of natural search results, thus search engine optimisation (SEO), versus pay per click (PPC) results. This will assist online advertisers to identify their optimal search engine marketing (SEM) strategy for their specific target market. Research shows that online advertisers perceive PPC as a more effective SEM strategy than SEO. However, empirical evidence exists that PPC may not be the best SEM strategy for online advertisers. Not all advertisers have the funds to implement a dual SEM strategy and therefore advertisers need to choose between a PPC and SEO campaign. In order for online advertisers to choose the most relevant SEM strategy, it is crucial to understand user perceptions of SEM strategies. A quantitative research design was used to conduct this study, with the purpose to collect and analyze data. A questionnaire was designed and placed on a website for gathering data. The questionnaire focused on how search engine users perceive SEM and their click response towards PPC and SEO respectively. The data was analysed and the results inspected. Results showed that the user perceived relevancy split is roughly 40%-60% (PPC results to SEO results), regardless of demographic factors. This indicates that websites should invest in both PPC and SEO. Failing to invest in either one could cause a significant loss of traffic. For websites that can not afford a dual SEM strategy, advertisers should correlate the results of this study with their target market to establish their optimal SEM strategy, or invest in SEO as results showed more users click through on SEO results than on PPC results.

Collaborative filtering (CF) approaches proved to be effective for recommender systems in predicting user preferences in item selection using known user ratings of items. This subfield of machine learning has gained a lot of popularity with the Netflix Prize competition started in October 2006. Two major approaches for this problem are matrix factorization (MF) and the neighbor based approach (NB). In this work, we propose various variants of MF and NB that can boost the performance of the usual ensemble based scheme. First, we investigate various regularization scenarios for MF. Second, we introduce two NB methods: one is based on correlation coefficients and the other on linear least squares. At the experimentation part, we show that the proposed approaches compare favorably with existing ones in terms of prediction accuracy and/or required training time. We present results of blending the proposed methods.

This is a proposal for a half day tutorial on Weka, an open source Data Mining software package written in Java and available from www.cs.waikato.ac.nz/~ml/weka/index.html. The goal of the tutorial is to introduce faculty to the package and to the pedagogical possibilities for its use in the undergraduate computer science and engineering curricula. The Weka system provides a rich set of powerful Machine Learning algorithms for Data Mining tasks, some not found in commercial data mining systems. These include basic statistics and visualization tools, as well as tools for pre-processing, classification, and clustering, all available through an easy to use graphical user interface.

Product concept generation and evaluation in a product development environment has been identified as the two major activities needed for obtaining an optimal design scheme. Product conceptual design is of critical importance in design through customer involvement for the systematic and simultaneous consideration on the impact of design decisions on manufacturing and assembly leads to repeated and excessive changes in design and processes. This paper introduces a novel knowledge support approach for the organization and ranking of design feature knowledge towards an integrated product model that incorporates a feature-based representation scheme targeted to evaluate the impact of design on subsequent activities in the conceptual design phase, taking into account the presence of design information and user preferences. An uncertain linguistic multi-attribute decision-making evaluation model is proposed and discussed for obtaining an optimal design scheme during the evaluation and selection of product design alternatives in conceptual design. The focus of this paper is on the development of a knowledge-intensive support design scheme and a comprehensive systematic fuzzy evaluation methodology for product conceptual design generation, evaluation, and selection. A case study and the corresponding scenario of knowledge support for design alternatives generation, evaluation and selection are provided for illustration.

Whilst multimedia technology has been one of the main contributing factors behind the Web's success, delivery of personalised multimedia content has been a desire seldom achieved in practice. Moreover, the perspective adopted is rarely viewed from a cognitive styles standpoint, notwithstanding the fact that they have significant effects on users' preferences with respect to the presentation of multimedia content. Indeed, research has thus far neglected to examine the effect of cognitive styles on users' subjective perceptions of multimedia quality. This paper aims to examine the relationships between users' cognitive styles, the multimedia Quality of Service delivered by the underlying network, and users' Quality of Perception (understood as both enjoyment and informational assimilation) associated with the viewed multimedia content. Results from the empirical study reported here show that all users, regardless of cognitive style, have higher levels of understanding of informational content in multimedia video clips (represented in our study by excerpts from television programmes) with weak dynamism, but that they enjoy moderately dynamic clips most. Additionally, multimedia content was found to significantly influence users' levels of understanding and enjoyment. Surprisingly, our study highlighted the fact that Bimodal users prefer to draw on visual sources for informational purposes, and that the presence of text in multimedia clips has a detrimental effect on the knowledge acquisition of all three cognitive style groups.

Interaction patterns with handheld mobile devices are constantly evolving. Researchers observed that users prefer to interact with mobile device using one hand. However, only few interaction techniques support this mode of operation. We show that onehanded operations can be enhanced with coordinated interaction using for input the front and back of a mobile device, which we term as Dual-Surface interaction. We present some of the design rationale for introducing coordinated Dual-Surface interactions. We demonstrate that several tasks, including target selection, benefit from Dual-Surface input which allows users to rapidly select small targets in locations that are less accessible when interacting using the thumb with one-handed input. Furthermore, we demonstrate the benefits of virtual enhancements that are possible with behind-the-display relative input to perform complex tasks, such as steering. Our results show that Dual-Surface interactions offer numerous benefits that are not available with input on the front or the back alone.