Miracle-dz/UniFAR-FTUs huggingface dataset:
INTEGRATED SYSTEM FOR MONITORING AND RECOGNIZING STUDENTS DURING CLASS SESSION

In this paper we propose a new student attendance system based on biometric authentication protocol. This system is basically using the face detection and the recognition protocols to facilitate checking students’ attendance in the classroom. In the proposed system, the classroom’s camera is capturing the students’ photo, directly the face detection and recognition processes will be implemented to produce the instructor attendance report. Actually, this system is more efficient than others student attendance methods since the detection and the recognition are considered to be the best and fastest method for biometric attendance system. Regarding to the students and instructor sides, the system is working without any preparation and with no more effort.
Federal Reserve Bank of Dallas Globalization and Monetary Policy Institute Teams of Rivals: Endogenous Markups in a Ricardian World

We show that an ostensibly disparate set of stylized facts regarding firm pricing behavior can arise in a Ricardian model with Bertrand competition. Generalizing the Bernard, Eaton, Jensen, and Kortum (2003) model allows firms' markups over marginal cost to fall under trade liberalization, but increase with FDI, matching empirical studies in international trade. We are able to mesh this dichotomy with the existence of pricing-to-market and imperfect pass-through, as well as to capture stylized facts regarding the frequency and synchronization of price adjustment across markets. The result is a well specified distribution for markups that previously could only be seen numerically and a way to quantify endogenous pricing rigidities emerging from a market structure governed by fierce competition among rivals. and the 2010 Western Economics Association International meetings. Beatriz de Blas acknowledges financial support from ECO2008-04073 project of the Spanish MEC, and CCG08-UAM/HUM-4438. The views in this paper are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Dallas or the Federal Reserve System.
Collaborative Learning with the Cognitive Tutor Algebra. An Experimental Classroom Study.

Interest in developing improved methods for mathematics instruction has increased since TIMSS and PISA. In our project, we investigate a new way to promote learning in mathematics: we enhanced the Cognitive Tutor Algebra, a computer-based intelligent tutoring system for mathematics at the high school level, to a collaborative learning setting. Although the Algebra Tutor has shown to increase learning substantially, there are also several shortcomings. For instance, learning with the Algebra Tutor places emphasis on improving students’ problem solving skills, yet a deep understanding of underlying mathematical concepts is not necessarily achieved. To reduce these shortcomings, we extended the learning environment to a dyadic setting, thus adding new learning opportunities such as the possibility to mutually elaborate on the learning content. A script was developed to guide students’ interaction and to ensure that students profit from these new learning opportunities. Our script followed a general jigsaw-scheme, i.e. it distributed expertise for the problem between partners and allowed them to prepare individually for the following interaction, thus laying the grounds for effective collaboration. During the collaboration, the script provided additional support: it prompted fruitful interaction and adaptively supported students as they encountered difficulties. Following each problem, it guided the dyads to reflect on their interaction in order to improve subsequent collaboration. In an experimental classroom study taking place over the course of one week, we compared three conditions to evaluate the impact of collaboration in a cognitive tutoring setting: individual learning, unscripted collaborative learning, and scripted collaborative learning. After a two-day learning phase, several post tests were administered to assess learning on three levels: reproduction, transfer and future learning. In the collaborative reproduction test, we found a higher need for cognitive tutor assistance in scripted students with low prior knowledge (note that this was the first post test after script support had been removed). In the subsequent individual reproduction test, however, differences between conditions were no longer observed. In fact, the learning outcomes of students in the two collaborative conditions were comparable to those in the individual condition even though collaborative students had solved fewer problems, i.e. had had less practice, during the learning phase. Analysis of the transfer test did not reveal differences between conditions. Finally, scripted collaboration better prepared students for future collaborative learning situations as compared to the unscripted collaboration condition. In addition to presenting the study
Density-Based Multi Feature Background Subtraction with Support Vector Machine

Video surveillance systems have long been in use to monitor security sensitive areas. The making of video surveillance systems “smart” requires fast, reliable and robust algorithms for moving object detection, classification, tracking and activity analysis. Moving object detection is the basic step for further analysis of video. It handles segmentation of moving objects from stationary background objects. Object classification step categorizes detected objects into predefined classes such as human, vehicle, animal, clutter, etc. It is necessary to distinguish objects from each other in order to track and analyse their actions reliably.
Phosphorylation-dependent Pex11p and Fis1p interaction regulates peroxisome division

Pex11p plays a conserved role in peroxisome division. Although Pex11p is phosphorylated, the exact role of this modification was either unknown or confusing. Phosphorylation of Pichia pastoris Pex11p at serine 173 occurs at the peroxisome and is necessary for its interaction with Fis1p, a key protein of the peroxisome division complex.
Passive reduction algorithm for RLC interconnect circuits with embedded state-space systems (PRESS)

With the increasing operating frequencies and functionality in modern designs, the resulting size of circuit equations of high-frequency interconnect and microwave subnetworks are becoming large. Model-order reduction-based algorithms were recently suggested to handle the solution complexity of such circuits. The major objectives in state-of-the-art model-reduction algorithms are: 1) achieving accurate and compact models; 2) numerically stable and efficient generation of models; and 3) preservation of system properties such as passivity. Algorithms such as PRIMA generate guaranteed passive reduced-order models for large interconnect circuits described by RLC type of circuits. However, with the diverse technologies and complex geometries, it is becoming prevalent to describe some of the embedded linear modules in terms of state-space equations. In this paper, we show how to extend the scope of PRIMA-type first-level reduction algorithms for simultaneous reduction of combined circuits containing both RLC interconnects and embedded modules described by general passive state-space equations, while preserving the passivity of the resulting reduced-order model. Necessary formulation, proof of macromodel passivity, and validation examples are given.
Las tecnologías de la información y comunicaciones (TIC) y la brecha digital: su impacto en la sociedad de México

Es deseable alcanzar una sociedad del conocimiento donde la inclusion de los individuos en la generacion de conocimiento sea total, que las sociedades del conocimiento sean fuentes de desarrollo para todos, y sobre todo para los paises menos adelantados. El presente articulo tiene como proposito analizar el papel de la brecha digital y la brecha cognitiva en las sociedades del conocimiento como causales de la exclusion de las empresas e individuos en el uso de las tecnologias de la informacion y comunicacion (TIC) en Mexico.
The role of temporal flexibility on person–environment fit and job satisfaction

Abstract The present study investigated the role of temporal flexibility on three conceptualizations of person–environment fit and job satisfaction. Data were collected from 320 full-time employees in Canada and America. Using structural equation modeling, it was found that temporal flexibility was directly related to increased job satisfaction and indirectly related to job satisfaction through supplementary fit, demands–abilities fit, and needs–supplies fit. Moreover, supplementary fit and demands–abilities fit were influential on perceptions of needs–supplies fit, although we acknowledge that additional research is required to further explore our novel findings of the relative relationships between the three conceptualizations of person–environment fit. The present research supports the idea that giving employees greater control over their schedule increases their autonomy, thus helping to satisfy a core psychological need. Organizations that provide employees with the opportunity to choose their own schedules may be more likely to retain satisfied and committed people who believe they fit well with their employer.
Lifestyle Physical Activity Among Older Adults: The Health Implications

The aging of the American population brings increased concerns about the consequences of chronic diseases and the associated health challenges related to these illnesses. Regular exercise is linked to reducing or eliminating risks of disease and provides the ability to delay the onset of disabilities. Despite the known benefits of exercise, there is a low adherence to exercise regimens among older Americans. This study used a conceptual approach that was informed by Dweck and Leggett’s incremental theory, Cockerham’s health lifestyle theory, and Ajzen’s theory of planned behavior to look at lifestyle physical activity—the daily accumulation of nonstructured physical activities (i.e., chores, gardening, incidental walking)—and its impact on health among adults. Analyzing data from the Active for Life: Translation of Physical Activity Programs for Mid-Life and Older Adults, the study explored the effects of lifestyle physical activity on self-rated health and self-reported health conditions among adults 50+. Results demonstrated that lifestyle physical activity is a protective factor for positive self-rated health scores and self-reported health conditions. This study offers a significant contribution to the understanding of the importance of lifestyle physical activities while providing policy implications and future research directions.
Preparing for Climate Change: A Perspective from Local Public Health Officers in California

Background The most recent scientific findings show that even with significant emission reductions, some amount of climate change is likely inevitable. The magnitude of the climate changes will depend on future emissions and climate sensitivity. These changes will have local impacts, and a significant share of coping with these changes will fall on local governmental agencies. Public health is no exception, because local public health agencies are crucial providers of disease prevention, health care, and emergency preparedness services. Methods This article presents the results of a survey of California’s local pubic health officers conducted between August and October 2007. The survey gauged health officers’ concerns about the public health impacts of climate change, programs in place that could help to mitigate these health effects, and information and resource needs for better coping with a changing climate. Results The results of this survey show that most public health officers feel that climate change poses a serious threat to public health but that they do not feel well equipped in terms of either resources or information to cope with that threat. Nonetheless, public health agencies currently implement a number of programs that will help these agencies handle some of the challenges posed by a changing climate. Conclusions Overall, the results suggest that local public health agencies in California are likely in a better position than they perceive to address the threats associated with climate change but that there is a larger role for them to play in climate policy.
Topic model tutorial: A basic introduction on latent dirichlet allocation and extensions for web scientists

In this tutorial, we teach the intuition and the assumptions behind topic models. Topic models explain the co-occurrences of words in documents by extracting sets of semantically related words, called topics. These topics are semantically coherent and can be interpreted by humans. Starting with the most popular topic model, Latent Dirichlet Allocation (LDA), we explain the fundamental concepts of probabilistic topic modeling. We organise our tutorial as follows: After a general introduction, we will enable participants to develop an intuition for the underlying concepts of probabilistic topic models. Building on this intuition, we cover the technical foundations of topic models, including graphical models and Gibbs sampling. We conclude the tutorial with an overview on the most relevant adaptions and extensions of LDA.
The duality of space: The built world of Du Bois’ double-consciousness

Using Du Bois’ concept of double-consciousness, this article explores African Americans’ responses to urban redevelopment strategies that undermine their claims to urban space. Set in post-Katrina New Orleans, this study centers residents’ visions for urban redevelopment, which reveal the severe economic, social, and spatial inequalities that they have historically faced but also the beauty and vibrancy of these communities. This article explores the spatiality of black residents’ double-consciousness and argues that space’s material and symbolic functions contribute to residents’ subaltern visions for urban development, views which counter the denigration of spaces inhabited by people of color with more socially and racially just visions for the future of the city.
The philosophy of science foundations of marketing research: For scientific realism and the inductive realist models of theory status and generation

Abstract All marketing research requires philosophy of science foundations. That is, every marketing research project presumes an ontology (what entities – the referents of the constructs – does the research assume to have real existence? ), a methodology (what procedures are to be followed for good research? ), and an epistemology (how are the knowledge claims of the research to be properly evaluated? ). This article argues for scientific realism and the inductive realist models of theory status and generation as providing an appropriate philosophy of science foundation for marketing research. The article (1) explicates the nature of scientific realism, (2) discusses the advantages for marketing researchers of using it as a philosophical foundation, (3) points out three major problems associated with scientific realism, which are labeled the problems of “approximate truth,” “sociological/political factors,” and “theory development,” (4) reviews the inductive realist model of theory status and shows how it can address the first two problems, (5) reviews the inductive realist model of theory generation and shows how it can address the third problem, and (6) concludes with an invitation for readers to propose viable alternatives to scientific realism so that productive discussion on the philosophical foundations issue can take place.
Dictionary-based Domain Adaptation of MT Systems without Retraining

We describe our submission to the ITdomain translation task of WMT 2016. We perform domain adaptation with dictionary data on already trained MT systems with no further retraining. We apply our approach to two conceptually different systems developed within the QTLeap project: TectoMT and Moses, as well as Chimera, their combination. In all settings, our method improves the translation quality. Moreover, the basic variant of our approach is applicable to any MT system, including a black-box one.
Parallel Depth First Proof Number Search

The depth first proof number search (df-pn) is an effective and popular algorithm for solving and-or tree problems by using proof and disproof numbers. This paper presents a simple but effective parallelization of the df-pn search algorithm for a shared-memory system. In this parallelization, multiple agents autonomously conduct the df-pn with a shared transposition table. For effective cooperation of agents, virtual proof and disproof numbers are introduced for each node, which is an estimation of future proof and disproof numbers by using the number of agents working on the node's descendants as a possible increase. Experimental results on large checkmate problems in shogi, which is a popular chess variant in Japan, show that reasonable increases in speed were achieved with small overheads in memory.
Performance Comparison of Multipath and Unipath Routing in Static Scenarios

In the past decade, multipath routing has been proposed to provide reliability for mobile ad hoc networks (MANETs). As wireless mesh networks become more and more popular, performance evaluation of different routing algorithms is required in static scenarios. Performance comparison between unipath routing and multipath routing is conducted in this paper. From the simulation results we find that multiple paths should not be employed simultaneously to avoid interference among paths. Researchers should focus on how to find the path with the best quality.
A novel mechanism for enhancing software transactional memory

This paper proposes efficient object-based implementations for Software Transactional Memory (stm). The proposed implementations are based on using multiple versions of the transactional objects to increase the concurrency of stm execution. In this work, we propose 3 algorithms for enhancing concurrency in stm. We also propose a new approach for determining the optimal number of versions to keep. Finally, we present experimental results that show the efficiency of the proposed implementations.
A Computational Model of the Fetal Circulation to Quantify Blood Redistribution in Intrauterine Growth Restriction

Intrauterine growth restriction (IUGR) due to placental insufficiency is associated with blood flow redistribution in order to maintain delivery of oxygenated blood to the brain. Given that, in the fetus the aortic isthmus (AoI) is a key arterial connection between the cerebral and placental circulations, quantifying AoI blood flow has been proposed to assess this brain sparing effect in clinical practice. While numerous clinical studies have studied this parameter, fundamental understanding of its determinant factors and its quantitative relation with other aspects of haemodynamic remodeling has been limited. Computational models of the cardiovascular circulation have been proposed for exactly this purpose since they allow both for studying the contributions from isolated parameters as well as estimating properties that cannot be directly assessed from clinical measurements. Therefore, a computational model of the fetal circulation was developed, including the key elements related to fetal blood redistribution and using measured cardiac outflow profiles to allow personalization. The model was first calibrated using patient-specific Doppler data from a healthy fetus. Next, in order to understand the contributions of the main parameters determining blood redistribution, AoI and middle cerebral artery (MCA) flow changes were studied by variation of cerebral and peripheral-placental resistances. Finally, to study how this affects an individual fetus, the model was fitted to three IUGR cases with different degrees of severity. In conclusion, the proposed computational model provides a good approximation to assess blood flow changes in the fetal circulation. The results support that while MCA flow is mainly determined by a fall in brain resistance, the AoI is influenced by a balance between increased peripheral-placental and decreased cerebral resistances. Personalizing the model allows for quantifying the balance between cerebral and peripheral-placental remodeling, thus providing potentially novel information to aid clinical follow up.
Effects of theta-frequency binaural beats on post-exercise recovery and stress responsivity

Binaural beats are an auditory illusion perceived when two or more pure tones of similar frequencies are presented dichotically through stereo headphones. This phenomenon is thought to have the potential to facilitate changes in arousal. The present study investigated the effects of 7 Hz binaural beating on post-exercise recovery and stress responsivity in college-aged students (n = 21; 18-29 years old). Psychological measures consisted of the positive and negative affect schedule and self-reported stress and relaxation. Physiological measures consisted of heart rate, heart rate variability, blood pressure and salivary α-amylase. Participants visited the laboratory twice over a two-week period at the same time of day to complete both a control (pink noise and carrier tone placebo) and an experimental (multilayered theta-frequency binaural beats with pink noise) session in a crossover controlled design. Participants exercised for 20min at 70% of their predicted VO2max with a 5-min warm-up and cool-down at 50% of their exercise workload. After exercising, participants listened to either binaural beats or placebo while relaxing alone in a quiet, low-light environment. Lastly, participants completed a short, timed 20-question mental arithmetic battery designed to elicit a stress response. Measurements were taken at four time points during each session: at baseline, post-exercise, post-relaxation and post-stress. Heart rate variability analyses comprised 2min windows corresponding to salivary-amylase acquisition. Theta binaural beats failed to outperform placebo in altering post-exercise recovery or stress responsivity. However, after listening to binaural beats, participants reported feeling more relaxed (6.4% change) and less stressed (11.5% change). Findings from the present study suggest that listening to binaural beats may have subtle psychological effects. Further research in a sample more representative of the general population is recommended.
UNCERTAINTY EVALUATION OF MULTI-SENSOR FLOW MEASUREMENT IN A SEWER SYSTEM USING MONTE CARLO METHOD

Technical requirements and economical impacts of flow measurements in sewer systems are a issue c oncern in today's system's management. Thus, the quality of t he measurements is considered to be a critical issue. Considering the complex nature of the measurand and the metrological requirements of local installations, the best avail able level of accuracy in measurement results should be sought. Therefore, both the knowledge of the measurand estimates and measurement of uncertainties are required for achieving robust res ults. Within this context, the quality of measurement res ults depends on the knowledge of the uncertainty contributions a nd on the selection of an appropriate method to evaluate the measurement uncertainty. The study of these aspects can be of m ajor importance in providing information to management of the syste m, namely in the selection of appropriate technology, upgrading and maintenance activities. The Monte Carlo method is used in this paper to carr y out the evaluation of the measurement uncertainty, consider ing its inherent capacity to deal with non-linear and multi-stage ma thematical models. Influence of geometric conditions and other relevant parameters in the quality of measurements is discus sed. The study was developed within the context of a specific sewe r system, using a particular measurement system, from which measurement data was gathered.