Miracle-dz/UniFAR-FTUs huggingface dataset:
CheekTouch: an affective interaction technique while speaking on the mobile phone

We present a new affective interaction technique, called CheekTouch, by combining tactile feedback, delivered through the cheek, and multi-finger input, while speaking on the mobile phone. We designed a prototype by using a multi-touch mobile device and a 4x3 vibrotactile display device. We identified six affective touch behaviors (pinching, stroking, patting, slapping, kissing and tickling) that can be exchanged through one another's cheeks while speaking on the phone. We mapped the affective touch behaviors on tactile feedback expressions of the vibrotactile display. Results of a preliminary user study suggest that our technique is positively evaluated by the participants and applicable to intimate and emotional communication.
PRACTICAL 3 D AERODYNAMIC DESIGN AND OPTIMIZATIONUSING UNSTRUCTURED MESHES

A methodology for performing optimization on 3D un-structured grids based on the Euler equations is presented. The same, low-memory-cost explicit relaxation algorithm is used to resolve the discrete equations which govern the ow, linearized direct and adjoint problems. The analysis scheme is a high resolution Local-Extremum-Diminishing (LED) scheme which uses Roe decomposition for the dissi-pative uxes. Mesh movement is performed in such a way that optimization of arbitrary geometries is allowed. The parallelization of the algorithm, which permits its extension to optimization of realistic, complete aircraft geometries is presented. Two sample optimizations are performed. The rst is the inverse pressure design of a transonic wing/body connguration using a target pressure found by analyzing the geometry for known design variable deeections. The second exercise is the inverse pressure design of a business jet con-guration consisting of wing, body, strut, nacelle, horizontal n and vertical n. The target in this case is provided by an analysis of the connguration with no strut-nacelle.
Addressing Disproportionality in School Discipline through Universal School-WidePositive Behavior Support

Suspensions are the most commonly used discipline strategy in schools and in many cases these lead to poor academic and behavioral outcomes for students. Suspensions are also implemented inconsistently as a consequence of disciplinary infractions; this has resulted in the disproportionate suspension rates of minority and special education students. Recently, school-wide Positive Behavior Support (SWPBS) has emerged as an alternative model to suspension. SWPBS is a proactive, school-wide approach to discipline, which focuses on teaching and reinforcing appropriate behavior to all students. The purpose of the current study is to examine the effectiveness of SWPBS on reducing disproportionate rates of suspension. Current suspension rates of a Maryland school implementing SPWBS were compared with baseline suspension rates prior to the implementation of the program. Specifically, the suspension rates of ethnic minority students and students with disabilities were analyzed to determine if the implementation of SWPBS resulted in a decrease in the suspension rates of these populations of students. Findings from the current study indicate that although universal SWPBS strategies are effective in reducing the overall out-of-school suspension rate of the student population, they are less effective for ethnic minority students and students with disabilities. Implications for schools and future research are discussed. Addressing Disproportionality Through SWPBS vi
Evaluating approaches to adaptive landscape visualization construction

The construction of an adaptive landscape visualization entails the representation of the higher dimensional chromosome space onto a two-dimensional plane from which a depiction of the landscape can be created. Although it can sometimes be difficult to justify the investment of computational expense necessary to perform this representation properly, Van Wijk's visualization model is ideally suited for use as a framework in which to compare different adaptive landscape visualizations. This model is used to demonstrate that an adaptive landscape visualization that is constructed with an established multidimensional scaling technique will result in a visualization that imparts more accurate insights, and is thus more valuable, than one that does not first attempt a multidimensional scaling of the chromosome space.
Steganalysis based on Markov Model of Thresholded Prediction-Error Image

A steganalysis system based on 2-D Markov chain of thresholded prediction-error image is proposed in this paper. Image pixels are predicted with their neighboring pixels, and the prediction-error image is generated by subtracting the prediction value from the pixel value and then thresholded with a predefined threshold. The empirical transition matrixes of Markov chain along the horizontal, vertical and diagonal directions serve as features for steganalysis. Support vector machines (SVM) are utilized as classifier. The effectiveness of the proposed system has been demonstrated by extensive experimental investigation. The detection rate for Cox et al.'s non-blind spread spectrum (SS) data hiding method, Piva et al.'s blind SS method, and a generic QIM method (as embedding data rate being 0.1 bpp (bits per pixel)) are all above 90% over an image database consisting of approximately 4000 images. For generic LSB method (with various embedding data rates), our steganalysis system achieves a detection rate above 85% as the embedding data rate is 0.1 bpp and above
Endothelial nitric oxide synthase levels and their response to exercise in patients with slow coronary flow

Summary Background Endothelial dysfunction plays a key role in the aetiopathogenesis of slow coronary flow (SCF) even if there is no obstructive epicardial lesion. Reduced plasma levels of endothelial nitric oxide synthase (eNOS) are an important indicator of endothelial dysfunction. We aimed to determine plasma levels of eNOS and their relationship with exercise in patients with SCF. Methods Twenty-two patients with SCF in at least one coronary artery and 17 healthy individuals were included in this study. The TIMI frame count method was used to determine SCF. Plasma levels of eNOS before and after effort were determined in the patient and control groups. Results Basal eNOS levels in the patient group were lower than in the control group (p = 0.040), and plasma eNOS levels after exercise decreased more significantly in the patient group compared to the control group (p = 0.002). Median decreases of eNOS in response to exercise were higher in the SCF group than in the control group (p < 0.001), and the decrease observed in the control group was not statistically significant (p = 0.35). There were significantly negative correlations between TIMI frame count and plasma levels of eNOS at baseline and after exercise (r = –0.51, p = 0.015, r = –0.58, p = 0.005, respectively). Moreover, there was also a positive correlation between the rate–pressure product and plasma levels of eNOS after exercise in patients with SCF (r = 0.494, p = 0.019). Conclusion Our findings indicate an important pathophysiological relationship between the severity of SCF in which endothelial dysfunction plays a role in its pathogenesis and the level of circulating plasma levels of eNOS.
CHAT - Towards a general-purpose infrastructure for multimodal situation-adaptive user assistance

position paper, we describe CHAT, an upcoming project aimed at providing multimodal context-sensitive services to mobile users. We specifically describe two conceptual corner stones of the project of relevance to the topic of user assistance in intelligent environments: a) a multimodal interaction framework targeted at providing service access through different modalities for different real-world situations and for improving interaction with mobile devices in general, b) an "egocentric interaction" model for framing interaction with objects in the vicinity of a mobile user, including also other real-world and/or computational entities than the mobile device itself, ranging from computationally "stupid" everyday objects to more advanced interactive devices such as desktop PCs. The final section of the paper is devoted to open issues in the design of the CHAT infrastructure related to the topic of user assistance in intelligent environments.
Determinants of restrictive dietary behaviors among female high school athletes

Several unhealthy behaviors occur on the continuum of disordered eating (DE). 1 The continuum starts with less severe behaviors such as restrictive dietary strategies, which may progress to more severe eating behaviors such as self-induced vomiting, diet pill use, as well as laxative and diuretic use.1,2 Ultimately, these behaviors may lead to clinical eating disorders such as anorexia nervosa (AN), bulimia nervosa (BN) and eating disorder not otherwise specified (EDNOS). 1,2 A significant proportion of high school female athletes as well as other adolescent girls engage in DE behaviors, reaching values as high as 40%. 3-7 Whether participating in a sport protects against or increases the risk of developing DE behaviors is controversial, partly due to the fact that the association is influenced by many confounding factors such as age, competition level, and type of sport practiced.2,8,9 Data suggest that DE behaviors are more prevalent among female elite athletes involved in sports that emphasize leanness, such as aesthetic, endurance and weight-class sports, than among nonelite female athletes involved in sports that do not emphasize leanness.2,8,10,11 Adolescent girls showing DE behaviors appear to be at increased risk for DE in adulthood.12 This has emphasized the importance of developing intervention programs aimed at preventing DE patterns at a young age, at least in young non-athlete girls. Considering that DE behaviors are not without consequences on athletic performance, physiological and psychological health, many authors are convinced that developing a targeted intervention for female athletes is also a necessity.2,8,13-15
Student assessment of quality of engineering education in India: evidence from a field survey

Purpose This paper aims to discuss students’ assessment of quality related issues in engineering education in India. Design/methodology/approach The paper uses primary survey data of 1,178 undergraduate engineering students in Delhi, India, in 2009-2010. Students’ experience and views of four important aspects such as teaching methods used in the classroom, evaluation pattern, skills acquired by students during the course and the involvement of students in different activities other than classroom teaching are discussed using descriptive statistics and correlation to examine the quality issues. Findings The study finds that the lecture method is still dominant in the teaching and learning of engineering institutions compared to technical demonstration and laboratory work. Around half of the engineering students reported that they had never gone through any field work or industrial visits during their entire program of study. Involvement of students in the activities other than classroom teaching (e.g. working on research projects, attending engineering internships, studying a foreign language and opting for interdisciplinary courses) is more prevalent in government institutions compared to private institutions. The findings suggest that engineering institutions (particularly private colleges) should change their focus from traditional methods of teaching and evaluation of students to interactive methods of learning to improve the quality of technical education in India. Originality/value The literature reveals that the quality assessment of engineering and technical education in India is largely based on the information collected from stakeholders other than students. Therefore, this study contributes a new dimension to the existing literature by considering students’ assessment of the quality of engineering education.
Methodology for Increasing Reliability of FPGA Design via Partial Reconfiguration

In the paper, the activities which aim at developing a methodology of fault tolerant systems design into FPGA platforms are presented. The methodology supports the detection and localization of soft errors in the design and recovery mechanism which is based on the principles of partial dynamic reconfiguration of the chip. The main features of methodology are presented in the paper.
Changes in miRNA Expression Profiling during Neuronal Differentiation and Methyl Mercury-Induced Toxicity in Human in Vitro Models

MicroRNAs (miRNAs) are implicated in the epigenetic regulation of several brain developmental processes, such as neurogenesis, neuronal differentiation, neurite outgrowth, and synaptic plasticity. The main aim of this study was to evaluate whether miRNA expression profiling could be a useful approach to detect in vitro developmental neurotoxicity. For this purpose, we assessed the changes in miRNA expression caused by methyl mercury chloride (MeHgCl), a well-known developmental neurotoxicant, comparing carcinoma pluripotent stem cells (NT-2) with human embryonic stem cells (H9), both analyzed during the early stage of neural progenitor commitment into neuronal lineage. The data indicate the activation of two distinct miRNA signatures, one activated upon neuronal differentiation and another upon MeHgCl-induced toxicity. Particularly, exposure to MeHgCl elicited, in both neural models, the down-regulation of the same six out of the ten most up-regulated neuronal pathways, as shown by the up-regulation of the corresponding miRNAs and further assessment of gene ontology (GO) term and pathway enrichment analysis. Importantly, some of these common miRNA-targeted pathways defined in both cell lines are known to play a role in critical developmental processes, specific for neuronal differentiation, such as axon guidance and neurotrophin-regulated signaling. The obtained results indicate that miRNAs expression profiling could be a promising tool to assess developmental neurotoxicity pathway perturbation, contributing towards improved predictive human toxicity testing.
THE POSSIBILITY OF A SOCIAL WELFARE FUNCTION

Ever since 1951, when Kenneth Arrow published his monograph showing the paradox that social welfare functions generate, there has been interest in overcoming or bypassing this paradox. ' The paradox is that, given certain simple and very persuasive conditions for collective rationality, there can be no decision rule which meets these conditions. The conditions, simply stated, are these: 1. Between three alternatives, the social welfare function must give rise to a unique social ordering, no matter how individual members of the group choose to order the three alternatives. 2. The social ordering must correspond positively, or at least not negatively, to changes in the ordering of any one individual. 3. The elimination of any one alternative shall not affect the ranking of the other alternatives in the social welfare function. 4. Voters can choose freely among all alternatives. S. No one individual's choice can dictate the social ordering independently of the choices of others. It is easy to show that even with three voters and three alternatives, a situation can exist in which these conditions are not met by a simple majority vote. For consider three voters, X, Y, and Z, and three alternatives, A, B, and C. The rankings given by X, Y, and Z are:
Examining IT Outsourcing Decisions and Practices of Small and Medium Enterprises in Malaysia

IT outsourcing business tends to be the domain of large companies. However, with increase saturation of outsourcing market among large companies, the under-exploited SME market emerges as a potentially lucrative playground for vendors. SMEs, confined by limited resources, can benefit from having external services. Literature review shows a lack of outsourcing research among SMEs in Malaysia. This paper thus aims at examining IT outsourcing decisions and practices of Malaysia SMEs. Data was collected from SMEs in the manufacturing and service sectors in Malaysia. The findings show that the lack of internal competency is the primary reason that drives IT outsourcing and that SMEs prefer shorter-term contractual agreements. To attract SMEs, vendors have to establish trust prior to contract signing. This trust is critical for long-term outsourcing engagement. If resources permit, SMEs would revert to in-house IT services to minimize dependency on vendors.
Particle filtering for state and parameter estimation in gas turbine engine fault diagnostics

In this paper, a novel method for a time-varying parameter estimation technique using particle filters is proposed based on the concept of Recursive Prediction Error (RPE). According to the proposed method, a parallel structure for both state and parameter estimation in a nonlinear non-Gaussian system is developed. The performance of the developed framework is evaluated in an application to the gas turbine engine state and health parameters estimation by using different scenarios. The developed method is identified to be applicable for fault diagnosis of an engine system while it is subjected to concurrent and simultaneous loss of effectiveness faults in the system components.
Classification and visualization for high-dimensional data

A geometrically motivated classi er is presented and applied, with both training and testing stages, to 3 real datasets. Our results compared to those from 23 other classi ers have the least error. The algorithm is based on parallel coordinates and : ~ has worst-case computational complexity O(NjP j) in the number of variables N and dataset size jP j, ~ provides comprehensible and explicit rules, ~ does dimensionality selection { where the minimal set of original variables (not transformed new variables as in Principal Component Analysis) required to state the rule is found, and ~ orders these variables so as to optimize the clarity of separation between the designated set and its complement.
Mode-dependent distortion modeling for H.264/SVC coarse grain SNR scalability

This paper presents a mode-dependent distortion model for H.264/SVC coarse grain SNR scalability. It estimates the base-layer and enhancement-layer's distortions with particular consideration of their prediction modes and inter-layer residual prediction. Based on a parametric signal model, the variances of the transformed prediction residual at both layers are first formulated analytically and approximated empirically. The results are then incorporated into the assumption that the transform coefficients are distributed according to the Laplacian distribution to obtain the final distortion estimates. Experimental results confirm its fairly good ability to predict the actual distortions in both the frame and macroblock levels.
Collaborative Representation Learning

This paper investigates an information-theoretic approach to the problem of collaborative representation learning: how to extract salient features of statistical relationships in order to build cooperatively meaningful representations of some relevant content. Modeling the structure of data and its hidden representations by independently identically distributed samples, our goal is to study fundamental limits of the so-called Two-way Collaborative Representation Learning (TW-CRL) and the Collaborative Distributed Representation Learning (CDRL) problems. The TW-CRL problem consists of two distant encoders that separately observe marginal (dependent) components $X_1$ and $X_2$ and can cooperate through multiple exchanges of limited information with the aim of learning hidden representations $(Y_1,Y_2)$, which can be arbitrarily dependent on $(X_1,X_2)$. On the other hand, in CDRL there are two cooperating encoders and the learner of the hidden representation $Y$ is a third node which can listen the exchanges between the two encoders. The relevance (figure-of-merit) of such learned representations is measured in terms of a normalized (per-sample) multi-letter mutual information metric. Inner and outer bounds to the complexity-relevance region of these problems are derived from which optimality is characterized for several cases of interest. Our resulting complexity-relevance regions are finally evaluated for binary symmetric and Gaussian statistical models showing how to identify comparatively random features that represent complexity-constrained statistics for the inference of the hidden representations.
Architecture for Hybrid Language Systems

An architecture for hybrid language systems is presented. A hybrid language has features of both textual languages and visual languages. Textual languages are computer-oriented and are geared toward storage, syntax analysis, and editing. On the other hand, visual languages are human-oriented and are geared toward expressive power, understandability, direct manipulation, and learning cost. Although a hybrid language system has the advantages of both textual and visual languages, general architectures to develop the corresponding programming environment considering real-time processing, synchronization, and multiple platforms have not yet been proposed. In the present paper, an architecture for hybrid language systems that support the development of new hybrid languages and the corresponding programming environments is presented. Implementation methods based on this architecture is demonstrated, and a case study is presented.
Agile open multiclass performance simulation model for a web server system

There have been numerous analytic computer system performance models based on the operational-law, arrival, and queuing theories. In today's speedcentric IT business environment, their simplicity is useful in ensuring the agile performance and capacity prediction of the computer system for the IT business. The analytic model is supplemented by simulation models, however, because it oversimplifies the system and also poorly represents the dynamic nature of the actual system. A simple and agile computer performance simulation model, which can support fast decision making, is more desirable than an accurate yet slow model. In this paper, an analytic model suggested by Menasce is examined based on the measurement data obtained from a Web server, and its simulation model is suggested, using ARENA, to verify that it allows simple and agile performance analysis and prediction.