Miracle-dz/UniFAR-FTUs huggingface dataset:
Pengaruh Self-Acceptance Importance, Affiliation Importance, dan Community Feeling Importance terhadap Compulsive Buying

This study focused on phenomenon behavior of compulsive buying. The study examined how Self-Acceptance Importance, Affiliation Importance, and Community Feeling Importance influenced on Compulsive Buying. Population in this research was students in Kota Semarang, and 104 students become samples. To answer problem that is accurate, researcher applies econometrics Logit model. Result of research indicates that there were negativity influence Self-Acceptance Importance, Affiliation Importance and Community Feeling to Compulsive Buying. Result of this supports all hypothesis and consistent with theory. Keywords: compulsive buying, self-acceptance Importance, affiliation Importance, community feeling Importance, Logit Model
Exploring the Relationship between Impression Management, Emotional Intelligence and Locus of Control: Evidence from Egypt

Research on impression management is still in the infancy stage. The aim of this study was to explore the interaction between impression management and two organizational variables, namely emotional intelligence and locus of control. A sample of 106 participants was extracted from the Egyptian working population. The analysis was conducted using Spearman rho’s. Results indicated insignificant correlation between impression management and emotional intelligence. A weak association was found between impression management and external locus of control and an insignificant, yet negative, correlation was found between emotional intelligence and locus of control. Further analyses, implications and future research recommendations are provided.
Change Detection: Paying Attention To Detail

Changes made during a brief visual interruption sometimes go undetected, even when the object undergoing the change is at the center of the observer's interest and spatial attention (Simons & Levin, 1998). This study examined two potentially important attentional variables in change blindness: spatial distribution, manipulated via set size, and detail level, varied by having the change at either the global or local level of a compound letter. Experiment 1 revealed that both types of change were equally detectable in a single item, but that global change was detected more readily when attention was distributed among several items. Variation of target level probability in Experiment 2 showed further that observers could flexibly set the detail level in monitoring both single and multiple items. Sensitivity to change therefore depends not only on the spatial focus of attention; it depends critically on the match between the detail level of the change and the level-readiness of the observer.
Human detection and tracking using apparent features under multi-cameras with non-overlapping

This paper describes a human detection and tracking system under multi-cameras with non-overlapping views using apparent features only. Our system is able to first detect people and then perform object matching. In the distributed intelligent surveillance system, computers need to detect pedestrians automatically under multi-cameras probably with non-overlapping views for providing a steady and continuous tracking of the pedestrian targets. In this paper, we combine Histograms of Oriented Gradients (HOG) and Local Binary Pattern (LBP) to detect human and segment human body from the background using GrabCut algorithm. We also study the method of pedestrian feature extraction and object matching based on appearance. We connect all the modules above in series to obtain a complete system and test it on samples we collect over three cameras with non-overlapping views to prove the effectiveness. We believe that our system will be helpful to the development of the public security system.
On the Calculation of Arbitrary Moments of Polygons

This paper describes a method to calculate moments of arbitrary order from polygons that enclose a region of two-dimensional space. These include various and often used shape features, such as area, center of gravity, and second order moments. Contrary to most approaches, which compute these features from discrete pixel data, here they are calculated by using only the points of the enclosing polygon, which may be sub-pixel accurate. This has two main advantages. Firstly, since the precise points of the boundary of the shape are used, the resulting features will be computed with maximum accuracy. Furthermore, since the boundary typically consists of fewer points than the whole region, the procedure is computationally more efficient.
Communities of Practice in Study Abroad: A Four‐Year Study of an Indonesian Student's Experience in Japan

This 4-year case study used a photo-elicitation approach to language learning history research in an individual case study of an Indonesian student's experiences of communities of practice while studying abroad in Japan. The study showed how the student's opportunities for interaction in Japanese were at first limited by his peripheral participation in institutionally organized communities of practice that consisted of international students and local Japanese support staff. Toward the end of his 4 years, however, the student succeeded in becoming a central participant in an informal self-organized community of practice that consisted mainly of local Japanese friends, who were more supportive of his interactions and language development. The study also shows how earlier experiences of peripheral participation scaffolded the student's later experience as a central participant. Photographs taken by the student over the 4 years were both a valuable source of data on the nature of his participation in communities and a stimulus to reflection that enriched the language learning history data. [ABSTRACT FROM AUTHOR]
Multi-view Face Detection Based on the Enhanced AdaBoost Using Walsh Features

A novel face detection algorithm is proposed in this paper to improve the training speed and detection performance. Firstly, we used Walsh features instead of Haar-like features in the AdaBoost algorithm. Walsh features have less redundancy than Haar-like features due to its orthogonal specialty. Then, we defined a kind of week classifiers with dual-threshold to speedup training process and increase accuracy. Furthermore, during training, dual-threshold of every classifier is adoptively adjusted to separate the face and non-face as far as possible. Experimental results on MIT+CMU frontal face set and CMU profile face set demonstrated that the proposed technique can achieve better results on the detection speed and accuracy than the corresponding method.
Comparison of Short-Text Sentiment Analysis Methods for Croatian

We focus on the task of supervised sentiment classification of short and informal texts in Croatian, using two simple yet effective methods: word embeddings and string kernels. We investigate whether word embeddings offer any advantage over corpus- and preprocessing-free string kernels, and how these compare to bag-of-words baselines. We conduct a comparison on three different datasets, using different preprocessing methods and kernel functions. Results show that, on two out of three datasets, word embeddings outperform string kernels, which in turn outperform word and n-gram bag-of-words baselines.
Gender-related associations of genetic polymorphisms of α-adrenergic receptors, endothelial nitric oxide synthase and bradykinin B2 receptor with treadmill exercise test responses

Background Treadmill exercise test responses have been associated with cardiovascular prognosis in individuals without overt heart disease. Neurohumoral and nitric oxide responses may influence cardiovascular performance during exercise testing. Therefore, we evaluated associations between functional genetic polymorphisms of α-adrenergic receptors, endothelial nitric oxide synthase, bradykinin receptor B2 and treadmill exercise test responses in men and women without overt heart disease. Methods We enrolled 766 (417 women; 349 men) individuals without established heart disease from a check-up programme at the Heart Institute, University of São Paulo Medical School. Exercise capacity, chronotropic reserve, maximum heart-rate achieved, heart-rate recovery, exercise systolic blood pressure (SBP), exercise diastolic blood pressure (DBP) and SBP recovery were assessed during exercise testing. Genotypes for the α-adrenergic receptors ADRA1A Arg347Cys (rs1048101), ADRA2A 1780 C>T (rs553668), ADRA2B Del 301–303 (rs28365031), endothelial nitric synthase (eNOS) 786 T>C (rs2070744), eNOS Glu298Asp (rs1799983) and BK2R (rs5810761) polymorphisms were assessed by PCR and high-resolution melting analysis. Results Maximum SBP was associated with ADRA1A rs1048101 (p=0.008) and BK2R rs5810761 (p=0.008) polymorphisms in men and ADRA2A rs553668 (p=0.008) and ADRA2B rs28365031 (p=0.022) in women. Maximum DBP pressure was associated with ADRA2A rs553668 (p=0.002) and eNOS rs1799983 (p=0.015) polymorphisms in women. Exercise capacity was associated with eNOS rs2070744 polymorphisms in women (p=0.01) and with eNOS rs1799983 in men and women (p=0.038 and p=0.024). Conclusions The findings suggest that genetic variants of α-adrenergic receptors and bradykinin B2 receptor may be involved with blood pressure responses during exercise tests. Genetic variants of endothelial nitric oxide synthase may be involved with exercise capacity and blood pressure responses during exercise tests. These responses may be gender-related.
Understanding Research Methods to Study African American Males in College

Abstract:This review explores the recent research methods used to understand the transitional experiences of African American males in college. Qualitative studies have been prevalent in recent research, focusing on understanding the social, interpersonal, and intrapersonal experiences of Black males. Quantitative studies show a trend to measure rates of Black males’ satisfaction with their college experience on the basis of grades, support, and identity. Further research should increase the utilization of quantitative research methods in order to better balance both qualitative and quantitative practice, as well as to bolster exploration on the college experiences of African American males. The terms ‘Black’ and ‘African American’ are used interchangeably throughout this text.
Performance improvement of GSC algorithms by near channel subtraction-based blocking matrix

For generalized sidelobe canceller (GSC)-based multi-channel speech enhancement, reference noise generation is essential to reduce remaining noises after fixed beamforming. However, the target signal leakage in the blocking matrix of GSC is inevitable. Thus, in this paper, near-channel subtraction scheme is proposed to improve the blocking matrix of the GSC tightly related with the reference noise. The performance of the proposed algorithm is compared with that of the conventional reference channel subtraction algorithm in the aspect of speech recognition rates and output SNR gains.
Parametric sensitivity analysis of a mathematical model of facultative mutualism

The complex dynamics of facultative mutualism is best described by a system of continuous non-linear first order ordinary differential equations. The methods of 1-norm, 2-norm, and infinity-norm will be used to quantify and differentiate the different forms of the sensitivity of model parameters. These contributions will be presented and discussed.
Model-based Gaussian and non-Gaussian clustering

Abstract : The classification maximum likelihood approach is sufficiently general to encompass many current clustering algorithms, including those based on the sum of squares criterion and on the criterion of Friedman and Rubin (1967). However, as currently implemented, it does not allow the specification of which features (orientation, size and shape) are to be common to all clusters and which may differ between clusters. Also, it is restricted to Gaussian distributions and it does not allow for noise. We propose ways of overcoming these limitations. A reparameterization of the covariance matrix allows us to specify that some features, but not all, be the same for all clusters. A practical framework for non-Gaussian clustering is outlined, and a means of incorporating noise in the form of a Poisson process is described. An approximate Bayesian method for choosing the number of clusters is given. The performance of the proposed methods is studied by simulation, with encouraging results. The methods are applied to the analysis of a data set arising in the study of diabetes, and the results seem better than those of previous analyses. (RH)
Localization system of autonomous vehicle via Kalman filtering

This paper proposes a localization system for autonomous vehicle via Kalman filtering. Absolute positioning is required to obtain successful operation of an autonomous vehicle's process. To get reliable positions, there are two ways, either using a GPS or dead reckoning from velocity and steering angle of the vehicle. Error elements exist in both the uses of GPS and dead reckoning. Stable position data of the autonomous vehicle is necessary for a successful operation even with the error elements. Kalman filter is suggested between the GPS and dead reckoning to get stable position data. Correction is performed during the localization of the processing position by using Kalman filter between GPS and dead reckoning.
The impact of time-window bias on the assessment of the long-term effect of medication adherence: the case of secondary prevention after myocardial infarction

Objectives Time-window bias was described in case–control studies and led to a biased estimate of drug effect. No studies have measured the impact of this bias on the assessment of the effect of medication adherence on health outcomes. Our goals were to estimate the association between adherence to drug therapies after myocardial infarction (MI) and the incidence of a new MI, and to quantify the error that would have been produced by a time-window bias. Setting This is a population-based study. Data were obtained from the Regional Health Information Systems of the Lazio Region in Central Italy (around 5 million inhabitants). Participants Patients discharged after MI in 2006–2007 were enrolled in the cohort and followed through 2009. Outcome measure The study outcome was reinfarction: either mortality, or hospital admission for MI, whichever occurred first. Design A nested case–control study was performed. Controls were selected using both time-dependent and time-independent sampling. Adherence to antiplatelets, β-blockers, ACE inhibitors/angiotensin receptor blockers (ACEI/ARBs) and statins was calculated using the proportion of days covered (PDC). Results A total of 6880 patients were enrolled in the cohort. Using time-dependent sampling, a protective effect was detected for all study drugs. Conversely, using time-independent sampling, the beneficial effect was attenuated, as in the case of antiplatelet agents and statins, or completely masked, as in the case of ACEI/ARBs and β-blockers. For ACEI/ARBs, the time-dependent approach produced ORs of 0.83 (95% CI 0.57 to 1.21) and 0.72 (0.55 to 0.95), respectively, for ‘0.50. 75’ versus ‘0≤PDC≤0.5’. Using the time-independent approach, the ORs were 0.96 (0.65 to 1.43) and 1.00 (0.76 to 1.33), respectively. Conclusions A time-independent definition of a time-dependent exposure introduces a bias when the length of follow-up varies with the outcome. The persistence of time-related biases in peer-reviewed papers strongly suggests the need for increased awareness of this methodological pitfall.
N-Glycoproteome of E14.Tg2a Mouse Embryonic Stem Cells

E14.Tg2a mouse embryonic stem (mES) cells are a widely used host in gene trap and gene targeting techniques. Molecular characterization of host cells will provide background information for a better understanding of functions of the knockout genes. Using a highly selective glycopeptide-capture approach but ordinary liquid chromatography coupled mass spectrometry (LC-MS), we characterized the N-glycoproteins of E14.Tg2a cells and analyzed the close relationship between the obtained N-glycoproteome and cell-surface proteomes. Our results provide a global view of cell surface protein molecular properties, in which receptors seem to be much more diverse but lower in abundance than transporters on average. In addition, our results provide a systematic view of the E14.Tg2a N-glycosylation, from which we discovered some striking patterns, including an evolutionarily preserved and maybe functionally selected complementarity between N-glycosylation and the transmembrane structure in protein sequences. We also observed an environmentally influenced N-glycosylation pattern among glycoenzymes and extracellular matrix proteins. We hope that the acquired information enhances our molecular understanding of mES E14.Tg2a as well as the biological roles played by N-glycosylation in cell biology in general.
Advances in Algorithms for Time-Dependent Recommender Systems

Nowadays, Online Social Networks have given the opportunity to users to share their interests. Moreover Location-Based Social Network added the location factor giving a new perspective to users' check-ins in POIs through smartphones. There are three main parameters characterizing these networks: mobility, proximity and periodicity. Here, we argue that periodicity is a significant upcoming trend in recommender systems. In particular, we present an extended comparison among 9 recommendation frameworks and their structural components. Moreover, we examine whether they provide personalized recommendations or not, the recommendation type they support, the data factors/features they use, the preferred methodology with which they model the problem and the data representation model they have chosen. By gathering this information we give an overview of the techniques and the features used and define new trends in this domain. The main factor is time that refines the final recommendation revealing relations among entities, which can increase accuracy of the proposals.
The Trait Anxiety Scale for Children: A validation study for European Portuguese children and adolescents

Abstract The State-Trait Anxiety Inventory for Children is a self-report instrument inspired on the State-Trait theory extended by Spielberger that measures a momentary state of anxiety (state) and a stable tendency to experience anxiety (trait). This study presents an exploratory adaptation of the Trait Scale and provides its psychometric properties for European Portuguese children and adolescents. The influence of sex and age were also explored. Our sample, composed of 402 participants aged 8–14 years, revealed a mean anxiety value of 28.37 (SD = 5.99). As expected, females revealed higher levels of anxiety than boys. Higher anxiety was obtained in our youngest group as compared to the oldest group. The exploratory factor analysis led to retaining only 16-items that presented acceptable adjustment to a one-factorial solution. Good indexes were obtained in the confirmatory analysis. The results also revealed good internal consistency and good test-retest reliability. Our results provide initial evidence that this scale is adequate to measure trait-anxiety in European Portuguese young people.
The Effects of Online Shopping Familiarity and Internet Self-Efficacy on the Formation of Trust Toward Online Shopping

Insufficient trust is one of the reasons suggested that individuals hesitate to purchase via Internet. This study integrates the literature on familiarity and self efficacy to determine their joint impact upon individual trust toward shopping online. Based on social cognition theory, we advance a new nomological structure that positions online shopping anxiety as a proximal mediating construct between online shopping familiarity, Internet self-efficacy, and the dependent constructs of trust toward shopping online. This research finds empirically that Internet self-efficacy and online shopping familiarity contribute to online shopping anxiety; online shopping anxiety fully mediates the relationship between the general constructs and trust toward online shopping; and online shopping familiarity contribute to trust toward online shopping.
Topology, entropy, and Witten index of dilaton black holes.

We have found that for extreme dilaton black holes an inner boundary must be introduced in addition to the outer boundary to give an integer value to the Euler number. The resulting manifolds have (if one identifies imaginary time) a topology [ital S][sup 1][times][ital R][times][ital S][sup 2] and Euler number [chi]=0 in contrast with the nonextreme case with [chi]=2. The entropy of extreme U(1) dilaton black holes is already known to be zero. We include a review of some recent ideas due to Hawking on the Reissner-Nordstroem case. By regarding all extreme black holes as having an inner boundary, we conclude that the entropy of [ital all] extreme black holes, including [U(1)][sup 2] black holes, vanishes. We discuss the relevance of this to the vanishing of quantum corrections and the idea that the functional integral for extreme holes gives a Witten index. We have studied also the topology of moduli space'' of multi-black-holes. The quantum mechanics on black hole moduli spaces is expected to be supersymmetric despite the fact that they are not hyper-Kaehler since the corresponding geometry has a torsion unlike the BPS monopole case. Finally, we describe the possibility of extreme black hole fission for states with anmore » energy gap. The energy released, as a proportion of the initial rest mass, during the decay of an electromagnetic black hole is 300 times greater than that released by the fission of a [sup 235]U nucleus. « less
Dynamic structure from motion using uncalibrated cameras and unsegmented scenes (חישובי מבנה של סצנה דינאמית מתנועת מצלמה, עבור מצלמות לא ידועות וללא סגמנטציה נתונה.)

Much work has been done in the last decade by the Computer Vision community in understanding the geometry of images of a rigid scene taken by a moving camera. The case of a scene containing motion has been largely ignored. Since most video footage aim at capturing events, hence motion, the need for handling dynamic scenes became apparent. Our work deals with discovering the geometrical models and the mathematical tools that we can use to analyze views of such scenes. In particular, we focus on the extraction of information about multiple independently moving objects. Unlike previous work which at best tried to ignore such moving objects, we show that valuable information can be extracted from such motions. The main mathematical tools that we have used are projective algebra and multi-linear tensors. Projective algebra has long been used to model the process of imaging of rigid scenes. From this model multiple views’ invariants can be derived to describe for example stereo vision. It was shown that these invariants can be described most generally by using multi-linear tensors. In our work, we further use multi-linear tensors to model dynamic scenes. In order to handle dynamic scenes we have often lifted the model of the scene to higher projective spaces. In these higher spaces, we were able to derive novel multi-linear invariants. We then found ways to decompose these invariants to unravel underlying information such as scene structure, motion in the scene and the motion of the camera. The research presented in this thesis appears in the following papers [46, 57, 33, 56, 58, 61]. These papers are reprinted as chapters of this thesis: Chapter 2 describes the recovery of structure and motion of a scene containing points moving along coplanar lines, appeared in ECCV2000 European Conference on Computer Vision [46]. Chapter 3 describes the recovery of structure and motion of a scene containing points in 3D moving in constant velocity, and other scenarios, appeared in International Journal on Computer Vision (IJCV) 48(1), 2002. [57]. Chapter 4 describes the derivation multi linear constraints used to recognize a moving object from a single view appeared in CVPR 2001 IEEE Conf. on Computer Vision and Pattern Recognition [33]