Proposed model of persuasive visual design for web design

This paper presents the foundation for systematically investigating the possibility of influencing users' motivation with visual persuasion which the constructs are divided into two factors; hygiene and motivation. Visual persuasion is identified as the design triggers that affect users’ first impression, which are seen as the conceptualization of motivation. While past research studied the effect of web design toward users’ motivation; not many are looking into the persuasive value of the design. It is foreseen that the power of visual persuasion would produce a more persuasive website and consequently give impact on the users' first impression, and thus motivate them to stay at a site long enough to influence specific behavioral intentions. The proposed model aims to discover the potential of visual persuasion in influencing web users’ motivation. This paper offers new insights into the role of visual persuasion in a web design with respect to the relationships between the dimensions of motivation and behavioral intention

Review of EEG-based pattern classification frameworks for dyslexia

Dyslexia is a disability that causes difficulties in reading and writing despite average intelligence. This hidden disability often goes undetected since dyslexics are normal and healthy in every other way. Electroencephalography (EEG) is one of the upcoming methods being researched for identifying unique brain activation patterns in dyslexics. The aims of this paper are to examine pros and cons of existing EEG-based pattern classification frameworks for dyslexia and recommend optimisations through the findings to assist future research. A critical analysis of the literature is conducted focusing on each framework’s (1) data collection, (2) pre-processing, (3) analysis and (4) classification methods. A wide range of inputs as well as classification approaches has been experimented for the improvement in EEG-based pattern classification frameworks. It was uncovered that incorporating reading- and writing-related tasks to experiments used in data collection may help improve these frameworks instead of using only simple tasks, and those unwanted artefacts caused by body movements in the EEG signals during reading and writing activities could be minimised using artefact subspace reconstruction. Further, support vector machine is identified as a promising classifier to be used in EEG-based pattern classification frameworks for dyslexia

Measuring the moderating influence of gender on the acceptance of e-book amongst mathematics and statistics students at universities in Libya

The success of using any types of technology in education depends on a large extent of the acceptance of information technology (IT) by students. Therefore, understanding the factors influencing the acceptance of electronic book (e-book) is essential for decision-makers and those interested in the e-book industry. Based on an extended technology acceptance model (TAM), this paper examines the impact of some factors on the students' behavioural intention (BI) toward adoption of the e-book in mathematics and statistics. This paper also investigates the effect of gender differences on the relationship between the factors affecting the acceptance of e-book. A self-administered survey was used to collect data from 392 mathematics and statistics undergraduate students. The research model has shown that the factors related to the social factor and users' characteristics are the critical factors that affect the acceptance of the e-book. The results also indicated that perceived usefulness (PU), perceived ease of use (PEOU) and students' attitude (AU) have strongly affected students' BI. Self-efficacy (SE) has a significant impact on PEOU while social influence (SI) has a significant influence on students' AU. Moreover, the results confirmed that most of the TAM constructs were significant in both models (males and females), where there are no differences between males and females; however, only PEOU has been affected by the gender moderator. The results showed that the impact of the factor of SI on females was more than males. On the other hand, female students were more confident in the use of the e-book than males. In general, the female students' model was more powerful in explaining the variance than males' model

Proposed model of persuasive visual design for web design

This paper presents the foundation for systematically investigating the possibility of influencing users' motivation with visual persuasion which the constructs are divided into two factors; hygiene and motivation. Visual persuasion is identified as the design triggers that affect users’ first impression, which are seen as the conceptualization of motivation. While past research studied the effect of web design toward users’ motivation; not many are looking into the persuasive value of the design. It is foreseen that the power of visual persuasion would produce a more persuasive website and consequently give impact on the users' first impression, and thus motivate them to stay at a site long enough to influence specific behavioral intentions. The proposed model aims to discover the potential of visual persuasion in influencing web users’ motivation. This paper offers new insights into the role of visual persuasion in a web design with respect to the relationships between the dimensions of motivation and behavioral intention

Comparing the influence of non-persuasive and persuasive visual on a website and their impact on users behavioural intention

Research related to first impression formation has highlighted the importance of visual appeal in influencing favourable attitude towards a website. It is proposed that users are actually drawn to specific characteristics or aspects of visual design of a website, and tend to disregard other features. Therefore, this study aims to investigate which visual design strongly appeals to the users by comparing the impact of common visuals with persuasive visuals.The principles of social influence are proposed as added value to the persuasiveness of the web visuals.An experimental study is conducted and the PLS-SEM method is employed to analyse the obtained data. The result of the exploratory and confirmatory analyses demonstrated that the structural model displays better quality when tested with persuasive data sample compared to non-persuasive data sample. Thus, it is concluded that persuasive visual helps to better explain the relationship between users' attitude and intention. This means that exposure to persuasive visuals brings about consistent favourable perception to the web design

PWIDB: A framework for learning to classify imbalanced data streams with incremental data re-balancing technique

The performance of classification algorithms with highly imbalanced streaming data depends upon efficient balancing strategy. Some techniques of balancing strategy have been applied using static batch data to resolve the class imbalance problem, which is difficult if applied for massive data streams. In this paper, a new Piece-Wise Incremental Data re-Balancing (PWIDB) framework is proposed. The PWIDB framework combines automated balancing techniques using Racing Algorithm (RA) and incremental rebalancing technique. RA is an active learning approach capable of classifying imbalanced data and can provide a way to select an appropriate re-balancing technique with imbalanced data. In this paper, we have extended the capability of RA for handling imbalanced data streams in the proposed PWIDB framework. The PWIDB accumulates previous knowledge with increments of re-balanced data and captures the concept of the imbalanced instances. The PWIDB is an incremental streaming batch framework, which is suitable for learning with streaming imbalanced data. We compared the performance of PWIDB with a well-known FLORA technique. Experimental results show that the PWIDB framework exhibits an improved and stable performance compared to FLORA and accumulative re-balancing techniques

Fivebranes and 4-manifolds

We describe rules for building 2d theories labeled by 4-manifolds. Using the proposed dictionary between building blocks of 4-manifolds and 2d N=(0,2) theories, we obtain a number of results, which include new 3d N=2 theories T[M_3] associated with rational homology spheres and new results for Vafa-Witten partition functions on 4-manifolds. In particular, we point out that the gluing measure for the latter is precisely the superconformal index of 2d (0,2) vector multiplet and relate the basic building blocks with coset branching functions. We also offer a new look at the fusion of defect lines / walls, and a physical interpretation of the 4d and 3d Kirby calculus as dualities of 2d N=(0,2) theories and 3d N=2 theories, respectivelyComment: 81 pages, 18 figures. v2: misprints corrected, clarifications and references added. v3: additions and corrections about lens space theory, 4-manifold gluing, smooth structure

Plan d'expériences séquentiel appliqué à la dosimétrie numérique

Dans ce papier nous allons proposer une méthodologie consistant à trouver la valeur du Débit d'Absorption Spécifique du Corps Entier (DAS_CE) qui couvre 95% d'une population donnée. Cette méthode repose d'une part sur de l'Inférence Bayesienne et d'autre part sur un modèle paramétrique de prédiction du DAS_CE en fonction de la morphologie ainsi que des outils de simulations numériques

Number of distinct sites visited by N random walkers on a Euclidean lattice

The evaluation of the average number S_N(t) of distinct sites visited up to time t by N independent random walkers all starting from the same origin on an Euclidean lattice is addressed. We find that, for the nontrivial time regime and for large N, S_N(t) \approx \hat S_N(t) (1-\Delta), where \hat S_N(t) is the volume of a hypersphere of radius (4Dt \ln N)^{1/2}, \Delta={1/2}\sum_{n=1}^\infty \ln^{-n} N \sum_{m=0}^n s_m^{(n)} \ln^{m} \ln N, d is the dimension of the lattice, and the coefficients s_m^{(n)} depend on the dimension and time. The first three terms of these series are calculated explicitly and the resulting expressions are compared with other approximations and with simulation results for dimensions 1, 2, and 3. Some implications of these results on the geometry of the set of visited sites are discussed.Comment: 15 pages (RevTex), 4 figures (eps); to appear in Phys. Rev.

Metabolomic analysis of low and high biofilm-forming Helicobacter pylori strains

The biofilm-forming-capability of Helicobacter pylori has been suggested to be among factors influencing treatment outcome. However, H. pylori exhibit strain-to-strain differences in biofilm-forming-capability. Metabolomics enables the inference of spatial and temporal changes of metabolic activities during biofilm formation. Our study seeks to examine the differences in metabolome of low and high biofilm-formers using the metabolomic approach. Eight H. pylori clinical strains with different biofilm-forming-capability were chosen for metabolomic analysis. Bacterial metabolites were extracted using Bligh and Dyer method and analyzed by Liquid Chromatography/Quadrupole Time-of-Flight mass spectrometry. The data was processed and analyzed using the MassHunter Qualitative Analysis and the Mass Profiler Professional programs. Based on global metabolomic profiles, low and high biofilm-formers presented as two distinctly different groups. Interestingly, low-biofilm-formers produced more metabolites than high-biofilm-formers. Further analysis was performed to identify metabolites that differed significantly (p-value < 0.005) between low and high biofilm-formers. These metabolites include major categories of lipids and metabolites involve in prostaglandin and folate metabolism. Our findings suggest that biofilm formation in H. pylori is complex and probably driven by the bacterium' endogenous metabolism. Understanding the underlying metabolic differences between low and high biofilm-formers may enhance our current understanding of pathogenesis, extragastric survival and transmission of H. pylori infections