Miracle-dz/UniFAR-FTUs huggingface dataset:
Student Perspectives of Technology use for Learning in Higher Education

En este estudio, los estudiantes universitarios en una gran universidad pública en los EE. UU. fueron encuestados con respecto a qué tecnologías utilizan con más frecuencia para aprender, qué tecnologías valoran para el aprendizaje y cómo perciben efectividad de la tecnología para respaldar su aprendizaje. Los resultados revelaron que el uso y el valor de la tecnología estaban estrechamente alineados con ordenadores portátiles y teléfonos inteligentes, éstos fueron detallados como los más utilizados y valorados para el aprendizaje, lo que subraya la importancia de los dispositivos móviles y portátiles para respaldar el aprendizaje en cualquier momento y lugar. En términos de uso de software para el aprendizaje, los motores de búsqueda, las herramientas para compartir archivos, las bibliotecas digitales, los videos y los wikis obtuvieron los mejores resultados, lo que sugiere que los estudiantes están adoptando enfoques autodirigidos para su aprendizaje. Además, las herramientas de colaboración fueron percibidas como las más importantes para el aprendizaje, lo que destaca la necesidad de diseñar mejores estrategias de enseñanza e interacciones de aprendizaje para respaldar las prácticas de colaboración que utilizan la tecnología. En general, la mayoría de los participantes percibió que la tecnología era eficaz para fomentar el debate, la colaboración y la interacción. Esto permite el aprendizaje experiencial, apoya la organización, la planificación, la gestión de recursosy facilitar una experiencia de aprendizaje personalizada. Los resultados también revelaron diferencias estadísticamente significativas entre las experiencias de los estudiantes de pregrado y posgrado acerca de la efectividad de la tecnología. Se discuten las implicaciones para integrar las tecnologías Web 2.0 en las prácticas de enseñanza y aprendizaje
Parameters Selection of Hybrid Kernel Based on GA

Support vector machines (SVMs), a powerful machine method proposed by Vapnik have made significant achievement in pattern classification and regression estimation. In practice, when we use the method of SVM there exist two problems: the selection of kernel and the selection of parameters. In this paper, we discuss the hybrid kernels and propose a new method to select parameters, which uses genetic algorithm by designing relevant fitness function. Using some benchmark data sets, we show the effectiveness of our method.
Enabling Secure Ad-hoc Communication using Context-Aware Security Services Extended Abstract

It is a stated goal of the ubiquitous computing research thrust to make the computer “disappear”. One of the most intrusive aspects about computers today is security management. Thinking about security places an immense burden on users ( e.g.,Is it safe to open this attachment? Should I accept this cookie? Should I let Internet Explorer remember my password? , etc.). Moreover, managing security settings is cumbersome, difficult to understand, and often considered a hassle that is in the way of getting work done [8]. Making security management “disappear” does not only accomplish a goal of ubiquitous computing – we believe that it can, in fact, also make things more secure. If users are bothered less often with dialog boxes that they don’t understand, then they are less likely to make bad decisions. Likewise, if users don’t have to go through a difficult security setup, then they are less likely to skip that cumbersome step. In this paper, we propose a step toward making security management disappear in certain situations. Imagine the following situation: you are at a meeting in a conference room and would like to share a sensitive document you just received with members from various organizations in the conference room. Traditionally, you would have to have some sort of a priori trust information from the intended recipients of your sensitive message (such as their public keys). Exchanging this trust information is a cumbersome step, and not everybody in the room may participate in the same Public Key Infrastructure (PKI). Recently, mechanisms have been suggested to exchange trust information on-the-fly in an ad-hocmanner [2], which would reduce the need for cumbersome setup steps and also eliminate the need for an all-embracing PKI. But the ultimate automation of this process would be if, simply by entering the conference room, all participants of the meeting became members of some sort of secure group communication scheme they could use to communicate with each other. No setup would be necessary,
Human enterovirus surveillance in the Slovak Republic from 2001 to 2011

SUMMARY We report the outcome of an 11-year programme monitoring sewage water and acute flaccid paralysis (AFP) cases as part of the World Health Organization (WHO) strategy for polio eradication in the Slovak Republic (SR). Polioviruses (PV) and non-polio enteroviruses (NPEV), prior to and after the change in polio vaccination strategy, were detected. Sewage treatment plant samples from 48 localities spread over the Western, Central and Eastern regions and clinical material from AFP cases were examined. The WHO standard procedures were followed with regard to virus isolation and identification. There were 538 commonly detected human enteroviruses (HEVs) including 213 (40%) coxsackie B viruses (CBV), 200 (37%) echoviruses and 113 (21%) Sabin-like PVs (PV1, 2, 3) including vaccine-derived poliovirus (VDPV) isolates. The percentage of PV isolates fell from 66% to 30% during 2001–2005 and thereafter fell to zero. CBV5, CBV2 and echovirus 3 were the NPEVs endemic during the study period.
Clustering Beat-Chroma Patterns in a Large Music Database

A musical style or genre implies a set of common conventions and patterns combined and deployed in different ways to make individual musical pieces; for instance, most would agree that contemporary pop music is assembled from a relatively small palette of harmonic and melodic patterns. The purpose of this paper is to use a database of tens of thousands of songs in combination with a compact representation of melodic-harmonic content (the beatsynchronous chromagram) and data-mining tools (clustering) to attempt to explicitly catalog this palette ‐ at least within the limitations of the beat-chroma representation. We use online k-means clustering to summarize 3.7 million 4-beat bars in a codebook of a few hundred prototypes. By measuring how accurately such a quantized codebook can reconstruct the original data, we can quantify the degree of diversity (distortion as a function of codebook size) and temporal structure (i.e. the advantage gained by joint quantizing multiple frames) in this music. The most popular codewords themselves reveal the common chords used in the music. Finally, the quantized representation of music can be used for music retrieval tasks such as artist and genre classification, and identifying songs that are similar in terms of their melodic-harmonic content.
Development and validation of a situational judgement test of Japanese leadership knowledge

ABSTRACT Leadership research has accumulated a wealth of empirical findings about what leadership behaviours are effective in various business environments. We took advantage of these empirical findings to develop a situational judgement test (SJT) of leadership knowledge with correct answers. The SJT contains four leadership dimensions: task-focused, relationship-focused, transformational, and developmental leadership. Item response theory and confirmatory factor analyses were used to examine the psychometric properties of the SJT, based on a sample of 658 Japanese college students. Ultimately, we confirmed a four-factor model and retained 21 of 53 situation questions for the final SJT.
Capturing the Laws of (Data) Nature

Model tting is at the core of many scientic and industrial applications. These models encode a wealth of domain knowledge, something a database decidedly lacks. Except for simple cases, databases could not hope to achieve a deeper understanding of the hidden relationships in the data yet. We propose to harvest the statistical models that users t to the stored data as part of their analysis and use them to advance physical data storage and approximate query answering to unprecedented levels of performance. We motivate our approach with an astronomical use case and discuss its potential.
THE OLD-HALO GLOBULAR CLUSTER SYSTEM IN NGC

We present the results of a deep photometric study of the outer halo of NGC 1275, the highly active cD galaxy at the center of the Perseus cluster. We ﬁnd a modest excess of faint ( R > 22 . 5) starlike objects in its halo, indicating a population of old-halo globular clusters. However, the total estimated cluster population corresponds to a speciﬁc frequency of S N = 4 . 4 ± 1 . 2, no larger than that of normal giant ellipticals and three times lower than that of other central cD galaxies such as M87. We discuss several ideas for the origin of this galaxy. Our results reinforce the view that high S N (ie: highly eﬃcient globular cluster formation) is not associated with cooling ﬂows, or with recent starburst or merger phenomena.
Sustained Ventricular Tachycardia in Recent Canine Myocardial Infarction

To study recurrent ventricular tachycardia in the late phase of myocardial infarction (MI), transmural anteroapical infarcts were created by ligation of the left anterior descending (LAD) coronary artery in 25 dogs. Twenty dogs survived LAD ligation and underwent an open-chest electrophysiologic study an average of 20 days after MI. Programmed electrical stimulation was carried out using the extrastimulus technique and short bursts of rapid ventricular pacing via bipolar electrodes positioned at multiple left ventricular endocardial sites. Sixteen dogs had electrically induced ventricular tachycardia, and in 11, sustained ventricular tachycardia was reproducibly initiated and terminated by programmed ventricular stimulation. Short bursts of rapid left ventricular pacing from areas in periinfarct zone was the most effective technique for initiating ventricular tachycardia. The electrophysiologic phenomena in this model of sustained ventricular tachycardia in 3-week-old MI included electrically induced changes in rate and morphology and biventricular capture without termination during tachycardia.
A novel rate control scheme for H.264/SVC base layer

A novel rate control scheme for H.264/SVC base layer is presented in this paper. At first, a new mean-absolute-difference (MAD) estimation method is introduced to replace the traditional MAD linear prediction model. This new method could reduce the computation complexity sharply and decrease the MAD estimation error by up to 35.6%. Then, the quadratic rate quantization (R-Q) model and the linear R-Q model from [1] are introduced to describe the relation between the sum of texture bits and non-texture bits and the quantization parameters (QP). Meanwhile, temporal and spatial windows are designed to select data points for the update of above two R-Q models at frame level and basic unit (BU) level respectively. Furthermore, a linear distortion quantization (D-Q) model is formulated. Combining this D-Q model with the linear R-Q model, a simple close-form solution is developed to derive optimal QP for achieving optimal bit allocation at BU level. At last, based on above three ideas, a rate control scheme is proposed for H.264/SVC base layer. Compared with the rate control scheme JVT-G012 which is adopted by the H.264/SVC base layer, the proposed rate control scheme could increase the average luminance PSNR of reconstructed video by up to 0.58 dB.
Scribe: a large-scale and decentralized publish-subscribe infrastructure

This paper presents Scribe, a large-scale event notificatio n infrastructure for topic-based publishsubscribe applications. Scribe supports large numbers of t opics, with a potentially large number of subscribers per topic. Scribe is built on top of Pastry, a g eneric peer-to-peer object location and routing substrate overlayed on the Internet, and leverages Pastry’s reliability, self-organization, and locality properties. Pastry is used to create a topic (group ) and to build an efficient multicast tree for the dissemination of events within a topic with a potenti ally large set of subscribers (members). Scribe provides weak reliability guarantees, but we outlin e how an application can extend Scribe to provide stronger ones. Simulation results, based on a rea listic network topology model, show that Scribe scales across a wide range of topics and subscrib ers per topic. Also, it balances the load on the nodes while achieving acceptable delay and link stres s when compared to IP multicast.
The Niche-Derived Glial Cell Line-Derived Neurotrophic Factor (GDNF) Induces Migration of Mouse Spermatogonial Stem/Progenitor Cells

In mammals, the biological activity of the stem/progenitor compartment sustains production of mature gametes through spermatogenesis. Spermatogonial stem cells and their progeny belong to the class of undifferentiated spermatogonia, a germ cell population found on the basal membrane of the seminiferous tubules. A large body of evidence has demonstrated that glial cell line-derived neurotrophic factor (GDNF), a Sertoli-derived factor, is essential for in vivo and in vitro stem cell self-renewal. However, the mechanisms underlying this activity are not completely understood. In this study, we show that GDNF induces dose-dependent directional migration of freshly selected undifferentiated spermatogonia, as well as germline stem cells in culture, using a Boyden chamber assay. GDNF-induced migration is dependent on the expression of the GDNF co-receptor GFRA1, as shown by migration assays performed on parental and GFRA1-transduced GC-1 spermatogonial cell lines. We found that the actin regulatory protein vasodilator-stimulated phosphoprotein (VASP) is specifically expressed in undifferentiated spermatogonia. VASP belongs to the ENA/VASP family of proteins implicated in actin-dependent processes, such as fibroblast migration, axon guidance, and cell adhesion. In intact seminiferous tubules and germline stem cell cultures, GDNF treatment up-regulates VASP in a dose-dependent fashion. These data identify a novel role for the niche-derived factor GDNF, and they suggest that GDNF may impinge on the stem/progenitor compartment, affecting the actin cytoskeleton and cell migration.
Chapter 4 : Multiagent negotiation models for power system applications

There are a wide range of power system decision problems, traditionally falling under one of the three categories of operations, maintenance, and planning, with the delineation between categories derived from the nature of the decision and the time horizon. Some of these decision problems include generation dispatching, fuel scheduling, control-room preventive and corrective actions, incident restoration, transmission service scheduling, unit commitment, transmission equipment maintenance, control system planning, and transmission upgrades. All of these share common attributes, among which are: • Resulting decisions have system-wide impact and therefore require significant coordination of information among the various decision-makers. • Higher system integrity is only achieved with greater allocation of financial resources. • The essential decision variables are inherently uncertain. • Uncertainty is reduced via acquisition and processing of information • Important information tends to be spatially dispersed. • Complex and computationally-intensive applications are required. As a result, decision-making support aids require modeling of multiple objectives, application of significant computational resources, and use of flexible data access capability. Mathematical programming has been and continues to be a mainstay for such decision problems. However, traditional optimization tools, by their very nature, assume the existence of a single and benevolent decision-maker that has centralized access to all information, and coordination between decision-makers is embedded in the processes and of no threat to individuals carrying out those processes. Such was the case in the traditionally regulated world where ownership of all facilities, access to all information, and all authority for decision rested within the single umbrella of the vertically integrated utility company. With the advent of industry restructuring and associated organizational disaggregation, however, facility ownership is heavily balkanized, and in-
Smart Agriculture with an Automated IoT-Based Greenhouse System for Local Communities

Nowadays, smart agriculture using wireless communication is replacing the wired system which was difficult to install and manage. Then, this paper introduces a new design for IoT application on the greenhouse, which utilizes different technologies to present a new model for practical implementation in the IoT concept. This design can settle a new method to solve problems in Market Demand, Precision in Operation and supervision. Furthermore, this design can be used in many cases and assist farmers, cropper and planted people to develop their business.
Accuracy of Local Topographic Variables Derived from Digital Elevation Models

We study the accuracy of data on some local topographic attributes derived from digital elevation models (DEMs). First, we carry out a test for the precision of four methods for calculation of partial derivatives of elevations. We find that the Evans method is the most precision algorithm of this kind. Second, we produce formulae for root mean square errors of four local topographic variables (gradient, aspect, horizontal and vertical landsurface curvatures), provided that these variables are evaluated with the Evans method. Third, we demonstrate that mapping is the most convenient and pictorial way for the practical implementation of the formulae derived. A DEM of a part of the Kursk Region (Russia) is used as an example. We find that high errors of data on local topographic variables are typical for flat areas. Results of the study can be used to improve landscape investigations with digital terrain models.
Éco-conception de maisons à énergie positive assistée par optimisation multicritère

Concevoir des bâtiments a energie positive, a moindre impact environnemental et a moindre cout, constitue un probleme d’optimisation complexe. Dans ce contexte, cette communication presente une demarche d’eco-conception de maisons a energie positive assistee par optimisation multicritere. Illustree sur un cas reel, cette demarche utilise un algorithme genetique pour approcher le plus efficacement possible le front de Pareto theorique, i.e. l’ensemble des solutions presentant les meilleurs compromis du probleme formule. La performance des solutions est evaluee par un modele de simulation thermique dynamique (COMFIE), un modele d’analyse de cycle de vie (novaEQUER) et des donnees de couts de construction. Un modele stochastique de comportement des occupants a permis de generer des scenarios moyens plus realistes que les approches conventionnelles. La demarche proposee contribue ainsi a une aide a la decision, au-dela d’une simple evaluation par simulation.
Text-to-query: dynamically building structured analytics to illustrate textual content

Successfully structuring information in databases, OLAP cubes, and XML is a crucial element in managing data nowadays. However this process brought new challenges to usability. It is difficult for users to switch from common communication means using natural language to data models (e.g., database schemas) that are hard to work with and understand, especially for occasional users. This important issue is under intense scrutiny in the database community (e.g., keyword search over databases and query relaxation techniques), and the information extraction community (e.g., linking structured and unstructured data). However, there is still no comprehensive solution that automatically generates an OLAP (Online Analytical Processing) query and chooses a visualization based on textual content with high precision. We present such a method. We discuss how to dynamically generate interpretations of a textual content as an OLAP query, select the best visualization, and retrieve on the fly corresponding data from a data warehouse. To provide the most relevant aggregation results, we consider the user's actual context, described by a document's content. Moreover we provide a prototypical implementation of our method, the Text-To-Query system (T2Q) and show how T2Q can be successfully applied to an enterprise scenario as an extension for an office application.
From Assortative to Dissortative Networks: The Role of Capacity Constraints

We consider a dynamic model of network formation where agents form and sever links based on the centrality of their potential partners. We show that the existence of capacity constrains in the amount of links an agent can maintain introduces a transition from dissortative to assortative networks. This effect can shed light on the distinction between technological and social networks as it gives a simple mechanism explaining how and why this transition occurs.
An industrial case study of architecture conformance

A software designer often has little control over, or means of checking, whether his design is being adhered to, once the implementation begins. This 'architectural drift', where the original design of the system and the as-implemented design of the system diverge, can cause serious problems for evolution, maintenance and the comprehensibility of a system if it remains undocumented or uncorrected. The earlier such discrepancies can be identified, the better. This paper reports on a case study designed to evaluate a proposed approach for monitoring architectural drift during software development. The proposed approach differs significantly from existing design conformance approaches in that it has been designed for application within a forward engineering context. The findings show the utility of the approach in identifying architectural drift but also illustrate a number of improvements that could be made to the technique to further promote architecture conformance.
A divide-and-conquer approach to large scene reconstruction with interactive scene analysis and segmentation

3D reconstruction of real world objects is a fundamental problem in computer vision and computer graphics. It is a challenge for high fidelity reconstruction with consumer-grade depth camera, e.g. Microsoft Kinect on large scale scene. A divide-and-conquer approach could both preserve local geometry details of scene objects and global consistency of the whole scene, thus is superior to existing GPU based real-time/global optimization based offline methods. In this paper, we extend the state-of-the-art in two folds. First, more fine grit scene segmentation is conducted for better local details preservation. Second, a scene analysis procedure is proposed for more reasonable global error spread. Preliminary experiments show that our method achieves more convincing reconstruction results.
Analyzing and exploring feature detectors in images

In recent years, computer vision is being applied extensively in industry solution. It allows obtain color, shape and texture information in different situation. But in some applications, resolution and frame rate could limit it due high computation cost. This paper proposes analyze the most recent methods to detect feature in images in order to know the limitation in terms of computational complexity. It allows knowing where and when this kind of method could be applied. The most used methods, SIFT and SURF, are explored. Computational complexity is obtained analytically and compared with experimental results obtained with standard implementation. The results show similarity between the complexities, with advantage to SURF, due constants size.