Interactive graphics, graphical user interfaces and software interfaces for the analysis of biological experimental data and networks

Biologists need to analyze and comprehend increasingly large and more complex multivariate experimental data. Biological experiments often produce multiple data sets, each describing one aspect of the system, such as the transcriptome recorded by a microarray or metabolome recorded using gas chromatography mass spectrometry (GC-MS). A biochemical network model provides a conceptual system-level framework for integrating data from different sources.;Effective use of graphics enhances the comprehension of data, and interactive graphics permit the analyst to actively explore data, check its integrity, satiate curiosities and reveal the unexpected. Interactive graphics have not been widely applied as a means for understanding data from biological experiments.;This thesis addresses these needs by providing new methods and software that apply interactive graphics in coordination with numerical methods to the analysis of biological data, in a manner that is accessible to biologists

Proceedings of the GIS Research UK 18th Annual Conference GISRUK 2010

This volume holds the papers from the 18th annual GIS Research UK (GISRUK). This year the conference, hosted at University College London (UCL), from Wednesday 14 to Friday 16 April 2010. The conference covered the areas of core geographic information science research as well as applications domains such as crime and health and technological developments in LBS and the geoweb. UCL’s research mission as a global university is based around a series of Grand Challenges that affect us all, and these were accommodated in GISRUK 2010. The overarching theme this year was “Global Challenges”, with specific focus on the following themes: * Crime and Place * Environmental Change * Intelligent Transport * Public Health and Epidemiology * Simulation and Modelling * London as a global city * The geoweb and neo-geography * Open GIS and Volunteered Geographic Information * Human-Computer Interaction and GIS Traditionally, GISRUK has provided a platform for early career researchers as well as those with a significant track record of achievement in the area. As such, the conference provides a welcome blend of innovative thinking and mature reflection. GISRUK is the premier academic GIS conference in the UK and we are keen to maintain its outstanding record of achievement in developing GIS in the UK and beyond

International Academic Symposium of Social Science 2022

This conference proceedings gathers work and research presented at the International Academic Symposium of Social Science 2022 (IASSC2022) held on July 3, 2022, in Kota Bharu, Kelantan, Malaysia. The conference was jointly organized by the Faculty of Information Management of Universiti Teknologi MARA Kelantan Branch, Malaysia; University of Malaya, Malaysia; Universitas Pembangunan Nasional Veteran Jakarta, Indonesia; Universitas Ngudi Waluyo, Indonesia; Camarines Sur Polytechnic Colleges, Philippines; and UCSI University, Malaysia. Featuring experienced keynote speakers from Malaysia, Australia, and England, this proceeding provides an opportunity for researchers, postgraduate students, and industry practitioners to gain knowledge and understanding of advanced topics concerning digital transformations in the perspective of the social sciences and information systems, focusing on issues, challenges, impacts, and theoretical foundations. This conference proceedings will assist in shaping the future of the academy and industry by compiling state-of-the-art works and future trends in the digital transformation of the social sciences and the field of information systems. It is also considered an interactive platform that enables academicians, practitioners and students from various institutions and industries to collaborate

Cognition-Based Evaluation of Visualisation Frameworks for Exploring Structured Cultural Heritage Data

It is often claimed that Information Visualisation (InfoVis) tools improve the audience’s engagement with the display of cultural heritage (CH) collections, open up CH content to new audiences and support teaching and learning through interactive experiences. But there is a lack of studies systematically evaluating these claims, particularly from the perspective of modern educational theory. As far as the author is aware no experimental investigation has been undertaken until now, that attempts to measure deeper levels of user engagement and learning with InfoVis tools. The investigation of this thesis complements InfoVis research by initiating a human-centric approach since little previous research has attempted to incorporate and integrate human cognition as one of the fundamental components of InfoVis. In this thesis, using Bloom’s taxonomy of learning objectives as well as individual learning characteristics (i.e. cognitive preferences), I have evaluated the visitor experience of an art collection both with and without InfoVis tools (between subjects design). Results indicate that whilst InfoVis tools have some positive effect on the lower levels of learning, they are less effective for higher levels. In addition, this thesis shows that InfoVis tools seem to be more effective when they match specific cognitive preferences. These results have implications for both the designers of tools and for CH venues in terms of expectation of effectiveness and exhibition design; the proposed cognitive based evaluation framework and the results of this investigation could provide a valuable baseline for assessing the effectiveness of visitors’ interaction with the artifacts of online and physical exhibitions where InfoVis tools such as Timelines and Maps along with storytelling techniques are being used

Exploratory search in time-oriented primary data

In a variety of research fields, primary data that describes scientific phenomena in an original condition is obtained. Time-oriented primary data, in particular, is an indispensable data type, derived from complex measurements depending on time. Today, time-oriented primary data is collected at rates that exceed the domain experts’ abilities to seek valuable information undiscovered in the data. It is widely accepted that the magnitudes of uninvestigated data will disclose tremendous knowledge in data-driven research, provided that domain experts are able to gain insight into the data. Domain experts involved in data-driven research urgently require analytical capabilities. In scientific practice, predominant activities are the generation and validation of hypotheses. In analytical terms, these activities are often expressed in confirmatory and exploratory data analysis. Ideally, analytical support would combine the strengths of both types of activities. Exploratory search (ES) is a concept that seamlessly includes information-seeking behaviors ranging from search to exploration. ES supports domain experts in both gaining an understanding of huge and potentially unknown data collections and the drill-down to relevant subsets, e.g., to validate hypotheses. As such, ES combines predominant tasks of domain experts applied to data-driven research. For the design of useful and usable ES systems (ESS), data scientists have to incorporate different sources of knowledge and technology. Of particular importance is the state-of-the-art in interactive data visualization and data analysis. Research in these factors is at heart of Information Visualization (IV) and Visual Analytics (VA). Approaches in IV and VA provide meaningful visualization and interaction designs, allowing domain experts to perform the information-seeking process in an effective and efficient way. Today, bestpractice ESS almost exclusively exist for textual data content, e.g., put into practice in digital libraries to facilitate the reuse of digital documents. For time-oriented primary data, ES mainly remains at a theoretical state. Motivation and Problem Statement. This thesis is motivated by two main assumptions. First, we expect that ES will have a tremendous impact on data-driven research for many research fields. In this thesis, we focus on time-oriented primary data, as a complex and important data type for data-driven research. Second, we assume that research conducted to IV and VA will particularly facilitate ES. For time-oriented primary data, however, novel concepts and techniques are required that enhance the design and the application of ESS. In particular, we observe a lack of methodological research in ESS for time-oriented primary data. In addition, the size, the complexity, and the quality of time-oriented primary data hampers the content-based access, as well as the design of visual interfaces for gaining an overview of the data content. Furthermore, the question arises how ESS can incorporate techniques for seeking relations between data content and metadata to foster data-driven research. Overarching challenges for data scientists are to create usable and useful designs, urgently requiring the involvement of the targeted user group and support techniques for choosing meaningful algorithmic models and model parameters. Throughout this thesis, we will resolve these challenges from conceptual, technical, and systemic perspectives. In turn, domain experts can benefit from novel ESS as a powerful analytical support to conduct data-driven research. Concepts for Exploratory Search Systems (Chapter 3). We postulate concepts for the ES in time-oriented primary data. Based on a survey of analysis tasks supported in IV and VA research, we present a comprehensive selection of tasks and techniques relevant for search and exploration activities. The assembly guides data scientists in the choice of meaningful techniques presented in IV and VA. Furthermore, we present a reference workflow for the design and the application of ESS for time-oriented primary data. The workflow divides the data processing and transformation process into four steps, and thus divides the complexity of the design space into manageable parts. In addition, the reference workflow describes how users can be involved in the design. The reference workflow is the framework for the technical contributions of this thesis. Visual-Interactive Preprocessing of Time-Oriented Primary Data (Chapter 4). We present a visual-interactive system that enables users to construct workflows for preprocessing time-oriented primary data. In this way, we introduce a means of providing content-based access. Based on a rich set of preprocessing routines, users can create individual solutions for data cleansing, normalization, segmentation, and other preprocessing tasks. In addition, the system supports the definition of time series descriptors and time series distance measures. Guidance concepts support users in assessing the workflow generalizability, which is important for large data sets. The execution of the workflows transforms time-oriented primary data into feature vectors, which can subsequently be used for downstream search and exploration techniques. We demonstrate the applicability of the system in usage scenarios and case studies. Content-Based Overviews (Chapter 5). We introduce novel guidelines and techniques for the design of contentbased overviews. The three key factors are the creation of meaningful data aggregates, the visual mapping of these aggregates into the visual space, and the view transformation providing layouts of these aggregates in the display space. For each of these steps, we characterize important visualization and interaction design parameters allowing the involvement of users. We introduce guidelines supporting data scientists in choosing meaningful solutions. In addition, we present novel visual-interactive quality assessment techniques enhancing the choice of algorithmic model and model parameters. Finally, we present visual interfaces enabling users to formulate visual queries of the time-oriented data content. In this way, we provide means of combining content-based exploration with content-based search. Relation Seeking Between Data Content and Metadata (Chapter 6). We present novel visual interfaces enabling domain experts to seek relations between data content and metadata. These interfaces can be integrated into ESS to bridge analytical gaps between the data content and attached metadata. In three different approaches, we focus on different types of relations and define algorithmic support to guide users towards most interesting relations. Furthermore, each of the three approaches comprises individual visualization and interaction designs, enabling users to explore both the data and the relations in an efficient and effective way. We demonstrate the applicability of our interfaces with usage scenarios, each conducted together with domain experts. The results confirm that our techniques are beneficial for seeking relations between data content and metadata, particularly for data-centered research. Case Studies - Exploratory Search Systems (Chapter 7). In two case studies, we put our concepts and techniques into practice. We present two ESS constructed in design studies with real users, and real ES tasks, and real timeoriented primary data collections. The web-based VisInfo ESS is a digital library system facilitating the visual access to time-oriented primary data content. A content-based overview enables users to explore large collections of time series measurements and serves as a baseline for content-based queries by example. In addition, VisInfo provides a visual interface for querying time oriented data content by sketch. A result visualization combines different views of the data content and metadata with faceted search functionality. The MotionExplorer ESS supports domain experts in human motion analysis. Two content-based overviews enhance the exploration of large collections of human motion capture data from two perspectives. MotionExplorer provides a search interface, allowing domain experts to query human motion sequences by example. Retrieval results are depicted in a visual-interactive view enabling the exploration of variations of human motions. Field study evaluations performed for both ESS confirm the applicability of the systems in the environment of the involved user groups. The systems yield a significant improvement of both the effectiveness and the efficiency in the day-to-day work of the domain experts. As such, both ESS demonstrate how large collections of time-oriented primary data can be reused to enhance data-centered research. In essence, our contributions cover the entire time series analysis process starting from accessing raw time-oriented primary data, processing and transforming time series data, to visual-interactive analysis of time series. We present visual search interfaces providing content-based access to time-oriented primary data. In a series of novel explorationsupport techniques, we facilitate both gaining an overview of large and complex time-oriented primary data collections and seeking relations between data content and metadata. Throughout this thesis, we introduce VA as a means of designing effective and efficient visual-interactive systems. Our VA techniques empower data scientists to choose appropriate models and model parameters, as well as to involve users in the design. With both principles, we support the design of usable and useful interfaces which can be included into ESS. In this way, our contributions bridge the gap between search systems requiring exploration support and exploratory data analysis systems requiring visual querying capability. In the ESS presented in two case studies, we prove that our techniques and systems support data-driven research in an efficient and effective way

Evaluating human-centered approaches for geovisualization

Working with two small group of domain experts I evaluate human-centered approaches to application development which are applicable to geovisualization, following an ISO13407 taxonomy that covers context of use, eliciting requirements, and design. These approaches include field studies and contextual analysis of subjects' context; establishing requirements using a template, via a lecture to communicate geovisualization to subjects and by communicating subjects' context to geovisualization experts with a scenario; autoethnography to understand the geovisualization design process; wireframe, paper and digital interactive prototyping with alternative protocols; and a decision making process for prioritising application improvement. I find that the acquisition and use of real user data is key; that a template approach and teaching subjects about visualization tools and interactions both fail to elicit useful requirements for a visualization application. Consulting geovisualization experts with a scenario of user context and samples of user data does yield suggestions for tools and interactions of use to a visualization designer. The complex and composite natures of both visualization and human-centered domains, incorporating learning from both domains, with user context, makes design challenging. Wireframe, paper and digital interactive prototypes mediate between the user and visualization domains successfully, eliciting exploratory behaviour and suggestions to improve prototypes. Paper prototypes are particularly successful at eliciting suggestions and especially novel visualization improvements. Decision-making techniques prove useful for prioritising different possible improvements, although domain subjects select data-related features over more novel alternative and rank these more inconsistently. The research concludes that understanding subject context of use and data is important and occurs throughout the process of engagement with domain experts, and that standard requirements elicitation techniques are unsuccessful for geovisualization. Engagement with subjects at an early stage with simple prototypes incorporating real subject data and moving to successively more complex prototypes holds the best promise for creating successful geovisualization applications

Visualization Authoring for Data-driven Storytelling

Data-driven storytelling is the process of communicating insights and findings that are supported by data, forming a visualization-based narrative. However, most current visualization creation tools either only support fixed sets of designs or require an in-depth understanding of programming concepts. To enable non-programmers to create custom visualizations for data-driven storytelling, we design interactions and implement user interfaces for visualization authoring. In the first part of this dissertation, we introduce and evaluate a series of three visualization authoring tools using traditional user interfaces: (1) iVisDesigner, which uses a data-flow model and enables users to author visualizations by specifying mappings from data to graphics interactively; (2) ChartAccent, a tool for annotating a given visualization; and (3) Charticulator, which allows users to design custom layouts interactively. We then reflect on the evaluation of visualization authoring user interfaces. In the second part of the dissertation, we extend our approach to multiple presentation media or display environments, including traditional 2-dimensional screens, large projection-based virtual-reality (VR) systems, and head-mounted virtual/augmented reality displays (HMDs). To leverage such immersive visualization environments, we ported and extended the iVisDesigner authoring approach to projection-based virtual reality. To facilitate the development of immersive visualizations, we built a visualization library called Stardust, which provides a familiar API to utilize GPU processing power in a cross-platform way. Finally, we present Idyll-MR, a system for authoring data-driven stories in virtual and augmented reality. We evaluated these authoring tools and libraries, and demonstrated high expressiveness, usability, and performance, as well as portability across platforms. In summary, our contributions enable larger audiences to create visual data-driven stories using different presentation media, leading to an overall enriched diversity of visualization designs

Factors Influencing Customer Satisfaction towards E-shopping in Malaysia

Online shopping or e-shopping has changed the world of business and quite a few people have decided to work with these features. What their primary concerns precisely and the responses from the globalisation are the competency of incorporation while doing their businesses. E-shopping has also increased substantially in Malaysia in recent years. The rapid increase in the e-commerce industry in Malaysia has created the demand to emphasize on how to increase customer satisfaction while operating in the e-retailing environment. It is very important that customers are satisfied with the website, or else, they would not return. Therefore, a crucial fact to look into is that companies must ensure that their customers are satisfied with their purchases that are really essential from the ecommerce’s point of view. With is in mind, this study aimed at investigating customer satisfaction towards e-shopping in Malaysia. A total of 400 questionnaires were distributed among students randomly selected from various public and private universities located within Klang valley area. Total 369 questionnaires were returned, out of which 341 questionnaires were found usable for further analysis. Finally, SEM was employed to test the hypotheses. This study found that customer satisfaction towards e-shopping in Malaysia is to a great extent influenced by ease of use, trust, design of the website, online security and e-service quality. Finally, recommendations and future study direction is provided. Keywords: E-shopping, Customer satisfaction, Trust, Online security, E-service quality, Malaysia

OBSERVER-BASED-CONTROLLER FOR INVERTED PENDULUM MODEL

This paper presents a state space control technique for inverted pendulum system. The system is a common classical control problem that has been widely used to test multiple control algorithms because of its nonlinear and unstable behavior. Full state feedback based on pole placement and optimal control is applied to the inverted pendulum system to achieve desired design specification which are 4 seconds settling time and 5% overshoot. The simulation and optimization of the full state feedback controller based on pole placement and optimal control techniques as well as the performance comparison between these techniques is described comprehensively. The comparison is made to choose the most suitable technique for the system that have the best trade-off between settling time and overshoot. Besides that, the observer design is analyzed to see the effect of pole location and noise present in the system