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Articles 1 - 16 of 16
Full-Text Articles in Physical Sciences and Mathematics
Designing For Positive Health Affect: Decoupling Negative Emotion And Health Monitoring Technologies, Tammy R. Toscos, Kay Connelly, Yvonne Rogers
Designing For Positive Health Affect: Decoupling Negative Emotion And Health Monitoring Technologies, Tammy R. Toscos, Kay Connelly, Yvonne Rogers
Tammy R Toscos
Through various health-focused technology projects, we discovered that the emotional response to technology was related to uptake and sustained use of health monitoring technologies. In this paper we present a case study of how we synthesized constructs of social cognitive theory, technology as experience, and diabetes management guidelines as a framework for making design recommendations for blood glucose monitoring technology that address the emotional response of users. We suggest applying this theoretical lens for design may help attend to emotional responses of users in an effort to decouple strong negative emotions that are paired to health monitoring technologies that provide …
Theory And Practice, Do They Match? A Case With Spectrum-Based Fault Localization, Tien-Duy B. Le, Ferdian Thung, David Lo
Theory And Practice, Do They Match? A Case With Spectrum-Based Fault Localization, Tien-Duy B. Le, Ferdian Thung, David Lo
David LO
Spectrum-based fault localization refers to the process of identifying program units that are buggy from two sets of execution traces: normal traces and faulty traces. These approaches use statistical formulas to measure the suspiciousness of program units based on the execution traces. There have been many spectrum-based fault localization approaches proposing various formulas in the literature. Two of the best performing and well-known ones are Tarantula and Ochiai. Recently, Xie et al. find that theoretically, under certain assumptions, two families of spectrum-based fault localization formulas outperform all other formulas including those of Tarantula and Ochiai. In this work, we empirically …
L-Opacity: Linkage-Aware Graph Anonymization, Sadegh Nobari, Panagiotis Karras, Hwee Hwa Pang, Stephane Bressan
L-Opacity: Linkage-Aware Graph Anonymization, Sadegh Nobari, Panagiotis Karras, Hwee Hwa Pang, Stephane Bressan
Sadegh Nobari
The wealth of information contained in online social networks has created a demand for the publication of such data as graphs. Yet, publication, even after identities have been removed, poses a privacy threat. Past research has suggested ways to publish graph data in a way that prevents the re-identification of nodes. However, even when identities are effectively hidden, an adversary may still be able to infer linkage between individuals with sufficiently high confidence. In this paper, we focus on the privacy threat arising from such link disclosure. We suggest L-opacity, a sufficiently strong privacy model that aims to control an …
Random Set Theory And Problems Of Modeling, Noel A. Cressie, G M. Laslett
Random Set Theory And Problems Of Modeling, Noel A. Cressie, G M. Laslett
Professor Noel Cressie
The three- or four-dimensional world in which we live is full of objects to be measured and summarized. Very often a parsimonious finite collection of measurements is enough for scientific investigation into an object’s genesis and evolution. There is a growing need, however, to describe and model objects through their form as well as their size. The purpose of this article is to show the potentials and limitations of a probabilistic and statistical approach. Collections of objects (the data) are assimilated to a random set (the model), whose parameters provide description and/or explanation.
Considering Cognitive Load Theory Within E-Learning Environments, Abdullah Al Asraj, Mark Freeman, Paul Chandler
Considering Cognitive Load Theory Within E-Learning Environments, Abdullah Al Asraj, Mark Freeman, Paul Chandler
Dr Mark Freeman
This study seeks to investigate how cognitive load influences knowledge construction and what is the role of layered integrated instructional techniques in facilitating the construction and automation of schemas whilst users are interacting with e-learning tools. Initially the literature on how Cognitive Load Theory (CLT) plays a role in e-learning tools is presented, this is followed by the considerations that need to be taken when developing e-learning tools with CLT as a focus so that learners can gain the best possible learning outcomes. This paper finally presents three different ways that e-learning tools can be designed when considering the cognitive …
Affine Hecke Algebras, Cyclotomic Hecke Algebras And Clifford Theory, Arun Ram, Jacqueline Ramagge
Affine Hecke Algebras, Cyclotomic Hecke Algebras And Clifford Theory, Arun Ram, Jacqueline Ramagge
Professor Jacqui Ramagge
We show that the Young tableaux theory and constructions of the irreducible representations of the Weyl groups of type A, B and D, Iwahori-Hecke algebras of types A, B, and D, the complex reflection groups G(r, p, n) and the corresponding cyclotomic Hecke algebras Hr,p,n, can be obtained, in all cases, from the affine Hecke algebra of type A. The Young tableaux theory was extended to affine Hecke algebras (of general Lie type) in recent work of A. Ram. We also show how (in general Lie type) the representations of general affine Hecke algebras can be constructed from the representations …
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Associate Professor Golshah Naghdy
A new method of texture classification comprising two processing stages, namely a low-level evolutionary feature extraction based on Gabor wavelets and a high-level neural network based pattern recognition, is proposed. The design of these stages is motivated by the processes involved in the human visual system: low-level receptors responsible for early vision processing and the high-level cognition. Gabor wavelets are used as extractors of ‘‘lowlevel’’ features that feed the feature-adaptive adaptive resonance theory (ART) neural network acting as a high-level ‘‘cognitive system.’’ The novelty of the model developed in this paper lies in the use of a self-organizing input layer …
Performance Enhancement For Fuzzy Adaptive Resonance Theory (Art) Neural Networks, Golshah Naghdy, Jiazhao Wang, Philip Ogunbona
Performance Enhancement For Fuzzy Adaptive Resonance Theory (Art) Neural Networks, Golshah Naghdy, Jiazhao Wang, Philip Ogunbona
Associate Professor Golshah Naghdy
A modified fuzzy adaptive resonance theory neural network (ART) is used as a classifier for a texture recognition system. The system consists of a wavelet based low level feature detector and a high level ART classifier. The performance improvement is measured in terms of identification accuracy and computational burden.
Considering Cognitive Load Theory Within E-Learning Environments, Abdullah Al Asraj, Mark Freeman, Paul A. Chandler
Considering Cognitive Load Theory Within E-Learning Environments, Abdullah Al Asraj, Mark Freeman, Paul A. Chandler
Paul Chandler
This study seeks to investigate how cognitive load influences knowledge construction and what is the role of layered integrated instructional techniques in facilitating the construction and automation of schemas whilst users are interacting with e-learning tools. Initially the literature on how Cognitive Load Theory (CLT) plays a role in e-learning tools is presented, this is followed by the considerations that need to be taken when developing e-learning tools with CLT as a focus so that learners can gain the best possible learning outcomes. This paper finally presents three different ways that e-learning tools can be designed when considering the cognitive …
Performance Enhancement For Fuzzy Adaptive Resonance Theory (Art) Neural Networks, Golshah Naghdy, Jiazhao Wang, Philip Ogunbona
Performance Enhancement For Fuzzy Adaptive Resonance Theory (Art) Neural Networks, Golshah Naghdy, Jiazhao Wang, Philip Ogunbona
Professor Philip Ogunbona
A modified fuzzy adaptive resonance theory neural network (ART) is used as a classifier for a texture recognition system. The system consists of a wavelet based low level feature detector and a high level ART classifier. The performance improvement is measured in terms of identification accuracy and computational burden.
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Professor Philip Ogunbona
A new method of texture classification comprising two processing stages, namely a low-level evolutionary feature extraction based on Gabor wavelets and a high-level neural network based pattern recognition, is proposed. The design of these stages is motivated by the processes involved in the human visual system: low-level receptors responsible for early vision processing and the high-level cognition. Gabor wavelets are used as extractors of ‘‘lowlevel’’ features that feed the feature-adaptive adaptive resonance theory (ART) neural network acting as a high-level ‘‘cognitive system.’’ The novelty of the model developed in this paper lies in the use of a self-organizing input layer …
Minimal Test Collections For Retrieval Evaluation, Ben Carterette, James Allan, Ramesh Sitaraman
Minimal Test Collections For Retrieval Evaluation, Ben Carterette, James Allan, Ramesh Sitaraman
Ramesh Sitaraman
Accurate estimation of information retrieval evaluation metrics such as average precision require large sets of relevance judgments. Building sets large enough for evaluation of real-world implementations is at best inefficient, at worst infeasible. In this work we link evaluation with test collection construction to gain an understanding of the minimal judging effort that must be done to have high confidence in the outcome of an evaluation. A new way of looking at average precision leads to a natural algorithm for selecting documents to judge and allows us to estimate the degree of confidence by defining a distribution over possible document …
Web Mining For Web Personalization, Magdalini Eirinaki, Michalis Vazirgiannis
Web Mining For Web Personalization, Magdalini Eirinaki, Michalis Vazirgiannis
Magdalini Eirinaki
Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user's navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content, and user profile data. Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. In this article we present a survey of the use of Web mining for Web personalization. More specifically, we introduce the modules that comprise a Web personalization …
Auroral Electrojet Irregularity Theory And Experiment: A Criticalreview Of Present Understanding And Future Directions, J. D. Sahr, Bela G. Fejer
Auroral Electrojet Irregularity Theory And Experiment: A Criticalreview Of Present Understanding And Future Directions, J. D. Sahr, Bela G. Fejer
Bela G. Fejer
We review the experimental observations of meter scale plasma irregularities in the auroral E region and the status of their theoretical understanding. Most of the experimental data is derived from VHF radar scatter experiments, but sounding rockets also provide crucial information not obtainable from radars. Linear theories correctly predict the altitude of occurence, strong magnetic aspect sensitivity, marginal instability, and typical phase velocities. Subsequent nonlinear theories have been developed to account for other observed features but with less satisfying application. Further understanding of auroral electrojet irregularities is impeded by precision limitations of existing instruments, by radar data which may seem …
Theory Of Spectral Asymmetries And Nonlinear Currentsin The Equatorial Electrojet, E. Kudeki, D. T. Farley, Bela G. Fejer
Theory Of Spectral Asymmetries And Nonlinear Currentsin The Equatorial Electrojet, E. Kudeki, D. T. Farley, Bela G. Fejer
Bela G. Fejer
The spectral up-down asymmetry of type 1 echoes returned from the equatorial electrojet irregularities is shown to be a consequence of the nonlinear development of the horizontally propagating large scale primary waves which dominate the k spectrum of the electrojet turbulence. The waves reduce the vertical electric polarization field of the electrojet and suffer second harmonic distortion as they grow. These effects together could cause an asymmetry exceeding 20% between the upward and downward components of the relative (to the ions) electron velocity associated with the primary waves. This asymmetry, which changes its direction from day to night as does …
Theory Of Plasma Waves In The Auroral E-Region, Bela G. Fejer, J. Providakes, D. T. Farley
Theory Of Plasma Waves In The Auroral E-Region, Bela G. Fejer, J. Providakes, D. T. Farley
Bela G. Fejer
We have extended the linear fluid theory of electrojet plasma waves to the region where ion magnetization effects are important. Our general dispersion relation includes the effect of cross-field and field-aligned drifts, ion inertia, electron density gradients, and recombination. In the absence of density gradients and recombinational damping, the oscillation frequency at marginal instability is changed by the ion magnetization effects from the ion acoustic frequency, ω = kCs, to the modified ion cyclotron frequency ω² = Ωi² + k²Cs². These upper E region waves can be driven by field-aligned and/or cross-field drifts and have the smallest threshold drift velocities …