Miracle-dz/UniFAR-FTUs huggingface dataset:
Design challenges for long-term interaction with a robot in a science classroom

This paper aims to present the main challenges that emerged during the process of the research design of a longitudinal study on child-robot interaction for science education and to discuss relevant suggestions in the context. The theoretical rationale is based on aspects of the theory of social constructivism and we use the collaborative inquiry as a framework to examine children's learning process who interact with a robotic learning companion. We identify two main challenges; (i) the development of robust on-demand systems for long-term interaction; and (ii) the design of developmentally appropriate scaffolding in embodied, semi-structured learning tasks. To address these challenges, we suggest (i) the development of a system for the detection of child's intention for interaction in the context of a classroom and (ii) the design of sensorized learning materials for the support of developmentally appropriate embodied learning experience.
Finite Element Modeling of Common Lateral Systems in Tall Buildings: Insights from Full-Scale Monitoring

Tall buildings are one of the few constructed facilities whose design relies solely upon analytical and scaled models, which, though based upon fundamental mechanics and years of research and experience, lack thorough full-scale validation. In response to this deficiency, the Chicago Full-Scale Monitoring Program was instituted and has been continuously monitoring the responses of three tall buildings in Chicago since 2002, expanding recently to additional buildings internationally. Observations made through this program, while showing general agreement between measured and predicted behaviors, have also highlighted some discrepancies between the projected periods of vibration using finite element models and the in-situ periods drawn from full-scale data. The implications with respect to predicted accelerations are presented in this study, various techniques for modeling elements of the lateral systems of these buildings are explored, and sensitivity analyses are conducted to direct the physically-meaningful calibrations of these finite element models to the full-scale observations.
Empirical Evaluation of Customer Loyalty in Malaysian Retail Outlets

Customer loyalty is one of the important approaches for retailers to improve competitive edge. Despite the importance of customer loyalty, some of the retail stores have lack on service quality, product quality, price strategy as well as customer satisfaction whereas needs a comprehensive work to explain how customers develop loyalty to a particular store. This study aims to evaluate the retail customer loyalty from hypermarkets in Kuala Lumpur, Malaysia and sets out to determine what influence customers to shop continuous. A survey of 200 respondents was conducted and reliability test is measured to present the constructs whereas descriptive analysis and Pearson correlation is used to analyze the research questions. The overall findings confirm the importance of customer loyalty, need to upgrade strategic tool: customer service quality, product quality, price strategy, store attributes and customer satisfaction to remain competitive. These strategic goals may provide retailers with direction in strategy formulation and gaining competitive advantage.
An efficient parameter extraction methodology for the EKV MOST model

This paper presents a new parameter extraction methodology, based on an accurate and continuous MOS model dedicated to low-voltage and low-current analog circuit design and simulation (EKV MOST Model). The extraction procedure provides the key parameters from the pinch-off versus gate voltage characteristic, measured at constant current from a device biased in moderate inversion. Unique parameter sets, suitable for statistical analysis, describe the device behavior in all operating regions and over all device geometries. This efficient and simple method is shown to be accurate for both submicron bulk CMOS and fully depleted SOI technologies.
ISAM-based inter-organization information systems alignment process

To cope with environmental change, an organization has to perform dynamic adjustment of alignment between Information Systems (IS) and business. The paper establishes the Information Systems Alignment Model (ISAM) that is expanded and refined from Strategic Alignment Model (SAM) and describes the core factors and their relationships in the process of Information System Planning. In addition, ISAM analyzes the impacts of Inter-Organizational Information Systems (IOS) against the organization and defines the corresponding alignment processes according to the characteristics of the four application models of IOS - Consultation, Cooperation, Coordination and Collaboration. It includes four active and four passive alignment processes which explain the influences of different application models on the organization.
Nutrients and Risk of Colon Cancer

Dietary fats are thought to be important in the etiology of colon cancer. However, the evidence linking them is inconclusive. Studies on dietary protein, cholesterol and carbohydrate and the risk of colon cancer are also inconsistent. This study examined the association between dietary intake of protein, fats, cholesterol and carbohydrates, and the risk of colon cancer. Mailed questionnaires were completed by 1731 individuals with histologically confirmed cases of colon cancer and 3097 population controls between 1994 and 1997 in seven Canadian provinces. Measurements included socio-economic status, lifestyle habits and diet. A 69-item food frequency questionnaire was used to provide data on eating habits from two years before the study. Odds ratios (OR) and 95% confidence intervals (CI) were computed using unconditional logistic regression. The nutrients were categorized by quartiles based on the distributions among the controls. Intake of polyunsaturated fat, trans-fat and cholesterol were significantly associated with the risk of colon cancer; the ORs for the highest quartiles were 1.36 (95% CI, 1.02–1.80), 1.37 (95% CI, 1.10–1.71) and 1.42 (95% CI, 1.10–1.84), respectively. The association was stronger with proximal colon cancer (PCC). An increased risk was also observed with increasing intake of sucrose for both proximal and distal colon cancers; the ORs for the highest quartiles were 1.67 (95% CI, 1.22–2.29) for PCC and 1.58 (95% CI, 1.18–2.10) for distal colon cancer (DCC). An elevated risk of PCC was also found with increased lactose intake. Our findings provide evidence that a diet low in fat and sucrose could reduce the risk of various colon cancers.
Intangible activities—the prevalence of informal helping in Denmark

ABSTRACT ‘Informal helping’ is often associated with other types of prosocial behaviour such as formal voluntary work. Therefore, one could jump to the conclusion that it would be the same factors driving both types of activities. This article demonstrates that this is not the case. The study relies on a population survey on informal helping and volunteering in Denmark. The two contributions of this article are as follows: (1) it demonstrates that the socio-demographic indicators that are closely linked to formal volunteering are not related to informal helping in the same manner and (2) it demonstrates that it is necessary to separate the decision to help and the amount of hours that people help, a distinction that previous empirical studies on this topic fail to include. The results show that informal helping may not simply be compared to other instances of prosocial behaviour. In particular, the socio-demographic indicators that are closely linked to formal volunteering are not necessarily related to informal helping. Moreover, the results emphasize the need for including informal helping as an act of civic engagement, which ought not to be confused with other forms of engagement within the civil society.
The Margitron: A Generalised Perceptron with Margin

We identify the classical Perceptron algorithm with margin as a member of a broader family of large margin classifiers which we collectively call the Margitron. The Margitron, (despite its) sharing the same update rule with the Perceptron, is shown in an incremental setting to converge in a finite number of updates to solutions possessing any desirable fraction of the maximum margin. Experiments comparing the Margitron with decomposition SVMs on tasks involving linear kernels and 2-norm soft margin are also reported.
Energy Consumption Control for Large Scale Sensor Networks Using Partition Energy Balanced Adaptive Clustering Hierarchy Scheme

Segmentation of wireless sensor networks into clusters is a promising approach for efficient utilization and distribution of the limited energy resources within the deployed sensor nodes. In actual implementations, however, there are potential drawbacks that the unbalanced energy assignment and node's physical communication range limitation may restrict the node's operation, and in turn affect the performance of the entire network. In this paper, we propose a novel clustering algorithm named partition energy balanced adaptive clustering hierarchy (PEBACH), which is specially tailored for periodical data gathering applications. For this approach, the cluster heads of each partition of the network are elected based on the residual energy and their relative distance to the region of interest. Such a scheme overcomes the unbalanced energy assignment and node's physical communication range limitation discussed in previous work. Simulation results show that PEBACH outperforms other protocols significantly in prolonging the network lifetime, enlarging the node number, and simultaneously maintains the normal communication range for the nodes.
The event-flow technique for selecting test cases for object-oriented programs

We present a technique, termed event flow for selecting system level test cases using a hierarchical state machine model of the system. The strategy is to require test cases which stress the interactions between related events rather than to simply exercise each transition in the model. Event flow selects test cases which are functionally meaningful to the system level tester.
Detection and severity grading of COPD exacerbations using the exacerbations of chronic pulmonary disease tool (EXACT)

Uncertainty exists over the ability of the exacerbations of chronic pulmonary disease tool (EXACT) patient-reported outcome diary to quantify exacerbation severity and frequency. To clarify this, we investigated the ability of the EXACT to assess severity of exacerbations and examined the relationship between exacerbations diagnosed using London chronic obstructive pulmonary disease (COPD) cohort diary cards, physician review and symptom-defined events using the EXACT. 58 patients enrolled in the London Chronic Obstructive Pulmonary Disease (COPD) cohort prospectively completed the EXACT during 128 cohort diary card-defined exacerbations between January 2010 and April 2012. Mean±sd EXACT scores increased from 42.6±8.6 at baseline to 48.0±8.6 at exacerbation onset (p<0.001), and rose further to a maximum score of 54.1±8.9. Maximum EXACT scores were significantly higher in treated than untreated events. Time taken for EXACT scores to return to baseline was significantly related to symptom recovery time as judged by London COPD cohort diary cards, and to peak expiratory flow rate recovery. ∼50% of both diary card-defined and healthcare utilisation exacerbations crossed the EXACT event threshold. However, only 27.9% of diary card-defined and 34.6% of healthcare utilisation exacerbations fully met the criteria for an EXACT event. Patients exhibited smaller rises in the EXACT score at exacerbation as baseline disease severity increased. The EXACT is an effective method of evaluating chronic obstructive pulmonary disease exacerbation severity. However, concerns remain about the ability of the EXACT to accurately detect exacerbations. The EXACT is an effective method to assess exacerbation severity but uncertainty remains over its ability to detect exacerbations http://ow.ly/rHg1P
Euler Scheme for the Black-Scholes Model

"Monte Carlo simulation" in the context of option pricing refers to a set of techniques to generate underlying valuestypically stock prices or interest ratesover time. Typically the dynamics of these stock prices and interest rates are assumed to be driven by a continuous-time stochastic process. Simulation, however, is done at discrete time steps. Hence, the rst step in any simulation scheme is to nd a way to "discretize" a continuous-time process into a discrete time process. In this Note we present two discretization schemes, Euler and Milstein discretization, and illustrate both with the Black-Scholes and the Heston models. We assume that the stock price St is driven by the stochastic di¤erential equation (SDE) dSt = (St; t) dt+ (St; t) dWt (1)
On the X-ray time-lags in the black hole candidates

ABSTRA C T It is shown that the energy dependence of the time-lags in Cygnus X-1 excludes any significant contribution of the standard reflected component to the observed lags. The conclusion is valid in the 0:1‐10 Hz frequency range where time-lags have been detected with sufficient significance. In fact, the data hint that the reflected component is working in the opposite direction, reducing the lags at energies where the contribution of the reflected component is significant. We argue that the observed logarithmic dependence of time-lags on energy could be due to the small variations of the spectral index in the frame of a very simple phenomenological model. We assume that an optically thin flow/corona, emitting a power law like spectrum, is present at a range of distances from the compact object. The slope of the locally emitted spectrum is a function of distance, with the hardest spectrum emitted in the innermost region. If perturbations with different time-scales are introduced to the accretion flow at different radii, then X-ray lags naturally appear, caused by the inward propagation of perturbations on the diffusion time-scales.
Characterisation of Potential Antidiabetic-Related Proteins from Pleurotus pulmonarius (Fr.) Quél. (Grey Oyster Mushroom) by MALDI-TOF/TOF Mass Spectrometry

Pleurotus pulmonarius has been reported to have a potent remedial effect on diabetic property and considered to be an alternative for type 2 diabetes mellitus treatment. This study aimed to investigate the antidiabetic properties of ammonium sulphate precipitated protein fractions from P. pulmonarius basidiocarps. Preliminary results demonstrated that 30% (NH4)2SO4 precipitated fraction (F30) inhibited Saccharomyces cerevisiae α-glucosidase activity (24.18%), and 100% (NH4)2SO4 precipitated fraction (F100) inhibited porcine pancreatic α-amylase activity (41.80%). Following RP-HPLC purification, peak 3 from F30 fraction demonstrated inhibition towards α-glucosidase at the same time with meagre inhibition towards α-amylase activity. Characterisation of proteins using MALDI-TOF/TOF MS demonstrated the presence of four different proteins, which could be implicated in the regulation of blood glucose level via various mechanisms. Therefore, this study revealed the presence of four antidiabetic-related proteins which are profilin-like protein, glyceraldehyde-3-phosphate dehydrogenase-like protein, trehalose phosphorylase-like (TP-like) protein, and catalase-like protein. Hence, P. pulmonarius basidiocarps have high potential in lowering blood glucose level, reducing insulin resistance and vascular complications.
Soyeon Ahn outcomes : A meta-analysis The effects of anger management on children ' s social and emotional

The occurrence of violent behaviors and bullying in schools continues to be a recognized problem among students and school personnel. The concern caused by these behaviors have led many schools to implement anger management and other impulse control based programs for at-risk students in an effort to prevent many of these incidences. This study was a comprehensive, meta-analytic synthesis of the literature to assess the effectiveness of these interventions, using a total of 60 studies from 1979– 2010 for analysis. Results indicated an overall effect size (ES) of 0.27, showing a small to moderate intervention effect in reducing children’s negative emotional and behavioral outcomes including anger, aggression, and loss of self control. Many different types of anger management components were found to be effective in promoting positive outcomes. Implications for school psychologists are discussed.
AluY-mediated germline deletion, duplication and somatic stem cell reversion in UBE2T defines a new subtype of Fanconi anemia

Fanconi anemia (FA) is a rare inherited disorder clinically characterized by congenital malformations, progressive bone marrow failure and cancer susceptibility. At the cellular level, FA is associated with hypersensitivity to DNA-crosslinking genotoxins. Eight of 17 known FA genes assemble the FA E3 ligase complex, which catalyzes monoubiquitination of FANCD2 and is essential for replicative DNA crosslink repair. Here, we identify the first FA patient with biallelic germline mutations in the ubiquitin E2 conjugase UBE2T. Both mutations were aluY-mediated: a paternal deletion and maternal duplication of exons 2–6. These loss-of-function mutations in UBE2T induced a cellular phenotype similar to biallelic defects in early FA genes with the absence of FANCD2 monoubiquitination. The maternal duplication produced a mutant mRNA that could encode a functional protein but was degraded by nonsense-mediated mRNA decay. In the patient's hematopoietic stem cells, the maternal allele with the duplication of exons 2–6 spontaneously reverted to a wild-type allele by monoallelic recombination at the duplicated aluY repeat, thereby preventing bone marrow failure. Analysis of germline DNA of 814 normal individuals and 850 breast cancer patients for deletion or duplication of UBE2T exons 2–6 identified the deletion in only two controls, suggesting aluY-mediated recombinations within the UBE2T locus are rare and not associated with an increased breast cancer risk. Finally, a loss-of-function germline mutation in UBE2T was detected in a high-risk breast cancer patient with wild-type BRCA1/2. Cumulatively, we identified UBE2T as a bona fide FA gene (FANCT) that also may be a rare cancer susceptibility gene.
Animation Geometry Compression Using the Linear Discriminant Analysis

We propose a new method to compress the geometry component of 3D animation sequence. It is based on the linear discriminant analysis (LDA) of the animation geometry data. The redundancy across the animation frames has been exploited by using the LDA in the temporal direction. Owing to the redundancy between the frames of a class, the covariance matrix of that class for the LDA computation may become singular. To overcome this drawback, we first transform the data into a new basis using the principal component analysis (PCA) and then apply the LDA on a few principal components. The reconstruction is simple and involves two stages: firstly for the LDA and then for the PCA. The experimental results show that the proposed method has the advantage of better reconstruction error at high compression ratios.
Matrix and Tensor Factorization for Predicting Student Performance

Recommender systems are widely used in many areas, especially in e-commerce. Recently, they are also applied in technology enhanced learning such as recommending resources (e.g. papers, books,.) to the learners (students). In this study, we propose using state-of-the-art recommender system techniques for predicting student performance. We introduce and formulate the problem of predicting student performance in the context of recommender systems. We present the matrix factorization methods, known as the most effective recommendation approaches, to implicitly take into account the latent factors, e.g. “slip” and “guess”, in predicting student performance. Moreover, the knowledge of the learners has been improved over the time, thus, we propose tensor factorization methods to take the temporal effect into account. Experimental results show that the proposed approaches can improve the prediction results.
Effect of surface properties on wrinkling of ultrathin films

Thin films bonded to compliant substrates often develop wrinkles when subjected to an applied or inherent compressive stress. This paper presents a bilayer model to account for surface effects on the wrinkling of ultrathin solid films. Assuming a surface layer of finite thickness, effects of surface properties on the critical strain, the equilibrium wavelength, and the wrinkle amplitude are discussed in comparison with conventional analysis. We apply this model to explain experimental observations of wrinkling in thin polymer films. The measured wrinkle wavelengths and amplitudes deviate from conventional analysis for ultrathin films with thickness less than 30 nm. The bilayer model provides a consistent understanding of the observed deviations, based on which a set of material properties for the surface and the bulk of the polymer films are deduced from the experimental data.
A SURVEY OF INTELLIGENT INFORMATION FORWARDER FOR PUBLIC HEALTHCARE MONITORING SYSTEM

The Health Monitoring System is a greatly developed technology for controlling and monitoring the situation of patients based on Human-health parameters. As healthcare costs are increasing and the world population is ageing, there has been a need to monitor a patient’s health status while patient is out of the hospital in his personal environment. To address this demand, a variety of system prototypes and commercial products have been produced, which aim at providing real-time feedback information about one’s health condition. The Health Monitoring system is based on modern wearable and mobile technology. Wearable Health Monitoring Systems are used to enable prevention and early intervention in case of health problems. The aim of this paper is to survey regarding public health monitoring using smart phones. The wearable sensors and smart phones are used to monitor the wellbeing of high risk patients, according to the situation the smart phone can automatically alert pre assigned caregivers or call the ambulance. The location of the patient can be tracked by using GPS to help the patient in emergency situation.
Intelligent fault detection and diagnosis of a rotary cutoff in a corrugator

In this paper an artificial intelligence based framework for fault detection and diagnosis to support supervision of the cardboard production is presented. Cutting accuracy significantly affects the quality of the product and because there are many different causes of errors, their identification requires a sound knowledge and experience of the service staff. The authors observed that the sources of errors can be characterized by a probability density function (pdf) of these errors. Therefore, they proposed a diagnostic method based on classification of sources of disturbances via the analysis of pdf calculated by a kernel density estimator. The multilayer perceptron is proposed as a classifier. Classification procedure is discussed with emphasis on generalization properties of the classifier. The application for data acquired from a real industrial process is presented.