Miracle-dz/UniFAR-FTUs huggingface dataset:
Atributos de una docencia de calidad en la educación superior: una revisión sistemática

espanolLa presente revision analiza de forma sistematica los atributos de una docencia de calidad en la educacion superior, extrayendo informacion sobre caracteristicas y cualidades que constituyen una docencia de 'excelencia'. La busqueda documental se llevo a cabo a traves de la triangulacion de diversas fuentes, identificando 25 articulos. Mediante un analisis tematico, dos autores de forma independiente analizaron y codificaron los atributos de un docente de calidad, clasificandolos en tres competencias: las genericas (caracteristicas personales, actitudinales y comunicativas); las pedagogicas (estrategias de ensenanza-aprendizaje y de planificacion-gestion); y las disciplinares. Se presentan sus implicancias y sus indicadores especificos. Las caracteristicas identificadas son factibles de ser modificadas, aprendidas y entrenadas. Estudiantes y profesores resaltan la necesidad fundamental de prepararse para ser profesor universitario, teniendo presente el papel crucial que juegan las variables de tipo genericas, pedagogicas y disciplinares, tanto en la interaccion profesor-estudiante como en la facilitacion del aprendizaje. EnglishThe aim of this systematic review is to analyse the attributes that constitute high quality teaching in higher education by extracting data on the characteristics of 'excellent' teachers. A literature search was conducted through the triangulation of multiple sources, identifying 25 articles. Through a thematic analysis, two authors independently reviewed and coded the attributes of quality teaching classifying them into three categories: generic competencies (personal, attitudinal, and communicational characteristics); pedagogical competencies (teaching and learning strategies, and planning and management); and disciplinary competencies. Further implications of each attribute with their specific indicators are described. The characteristics identified, in general, are feasible to be trained, modified, and learned. Students and faculty emphasised the critical need for university teachers to be professionally prepared to teach and for them to consider the relevance of generic, pedagogical, and disciplinary variables as determinants of a good teacher-student interaction and for the facilitation of learning.
Learning to Plan with Logical Automata

We present a framework for combining imitation learning and logical automata and introduce the Logic-based Value Iteration Network (LVIN) model. By appending a ‘logical’ dimension to the state space of the environment, LVIN can recover and incorporate the transition matrix of a finite state automaton derived from a Linear Temporal Logic formula into the policy learned through imitation. This approach improves upon the original VIN in several ways: LVIN (1) is capable of learning logic corresponding to long sequences of steps, (2) adapts easily to new specifications, and (3) is amenable to correction after faulty expert demonstrations.
A Simple SNR Representation Method for AMC Schemes of MIMO Systems with ML Detector

Adaptive modulation and coding (AMC) is a powerful technique to enhance the link performance by adjusting the transmission power, channel coding rates and modulation levels according to channel state information. In order to efficiently utilize the AMC scheme, an accurate signal-to-noise ratio (SNR) value is normally required for determining the AMC level. In this paper, we propose a simple method to represent the SNR values for maximum likelihood (ML) detector in multi-input multi-output (MIMO) systems. By analyzing the relation between the upper bound and the lower bound of the ML detector performance, we introduce an efficient way to determine the SNR for the ML receiver. Based on the proposed SNR representation, an AMC scheme for single antenna systems can be extended to MIMO systems with ML detector. From computer simulations, we confirm that the proposed SNR representation allows us to achieve almost the same system throughput as the optimum AMC systems in frequency selective channels with reduced complexity.
REAL TIME DETECTION OF CACHE-BASED SIDE-CHANNEL ATTACKS USING HARDWARE PERFORMANCE COUNTERS by

Cache-based side-channel attacks are increasingly exposing the weaknesses of many cryptographic libraries and tools by showing that, even though the algorithms might be considered strong, their implementations often lead to unexpected behaviors that can be exploited to obtain sensitive data, usually encryption keys. In this study we analyze three methods to detect cache-based side-channel attacks in real time, preventing or limiting the amount of leaked information. We focus our efforts on detecting three attacks on the well-known OpenSSL library: one that targets AES, one that targets RSA and one that targets ECDSA. The first method is based on monitoring the involved processes and assumes the victim process is known. By collecting and correlating the monitored data we find out whether there exists an attacker and pinpoint it. The second method uses anomaly detection techniques and assumes the benign processes and their behavior are known. By treating the attacker as a potential anomaly we understand whether an attack is in progress and which process is performing it. The last method is based on employing a neural network, a machine learning technique, to profile the attacker and to be able to recognize when a process that behaves suspiciously like the attacker is running. All the three of them can successfully detect an attack in about one fifth of the time required to complete it. We could not experience the presence of false positives in
Operational Satellite Sensing of Arctic First-Year Sea Ice Melt

RÉSUMÉ Le Service canadien des glaces fait appel à des techniques fiables et efficaces pour évaluer et faire le suivi de la décroissance des glaces à partir de capteurs satellitaires optique/infrarouge et hyperfréquences actifs. Cet article étudie le potentiel des données AVHRR et RADARSAT-1 en mode ScanSAR à fournir une information sur la fonte printanière de la glace de mer dans l'Arctique canadien. Des ensembles de données in situ et satellitaires acquis au cours de l'expérience C-ICE 2000 (Collaborative Interdisciplinary Cryospheric Sea Ice Experiment 2000) constituent la base de cette étude. L'évolution saisonnière des signatures AVHRR et RADARSAT-1 a été examinée et reliée aux changements saisonniers concomitants à l'intérieur du volume neige/glace. Les résultats indiquent que l'amplitude des signatures optiques et hyperfréquences varie suffisamment pour permettre la détection des phases de fonte: glace d'hiver, fonte de la neige, formation de mares, drainage et glace pourrie. Spécifiquement, les réflectances AVHRR 1 et 2 au sommet de l'atmosphère étaient efficaces pour l'identification de toutes les phases de fonte. De la même manière, les données RADARSAT-1 en mode ScanSAR se sont avérées efficaces pour l'identification des phases d'hiver et de fonte de la neige. La phase de formation de mares est plus susceptible au phénomène d'identification erronée dü à la grande sensibilité de la rétrodiffusion de l'eau à la rugosité induite par le vent à travers l'ensemble du faisceau ScanSAR. L'étude a démontré que le fait de limiter les observations du centre vers la limite éloignée du faisceau devrait donner un signal clair de formation de mares, facile à distinguer des phases voisines de fonte de la neige et de drainage qui sont caractérisées par une rétrodiffusion plus claire. Des caractéristiques de drainage uniques ont été identifiées dans les données RADARSAT-1 facilitant l'identification de la période de drainage. Les phases acquises à partir des deux capteurs présentent un potentiel d'identification erronée, démontrant ainsi la nécessité d'une procédure de mise en place capable de fournir un contexte saisonnier sous une forme quelconque (i.e. données de température).
Design of a Supernumerary Robotic Limb Based on Hybrid Control of Motion Imagination and Object Detection

Upper limb moto disorders are the main symptoms of stroke patients. Based on deep learning algorithms and object detection technology, we developed a brain-controlled supernumerary robotic limb system for upper-limb motion assistance. The system makes use of the motor imagery electroencephalogram (MI EEG) recognition model with graph convolutional network (GCN) and gated recurrent unit network (GRU) to obtain the patient’s motion intentions and control the supernumerary robotic limb to move. The object detection technology can compensate for the disadvantages when using MI EEG alone like fewer control instructions and lower control efficiency. We also validated the feasibility and effectiveness of the system by designing model training experiment and target object grasping experiment. The results showed that the highest EEG classification accuracy using GCN+GRU algorithm achieved 92.32%, and the average success rate of grasping tasks achieved 88.67±3.77%.
Intra-rater reliability and criterion-related validity of using an accelerometer to measure the impact force and knee joint sway during single-leg drop landing

[Purpose] This study aimed to clarify the reliability and validity of the impact force and knee joint sway measurement during single-leg drop landing by using a motion sensor with two built-in accelerometers. [Participants and Methods] Ten healthy college students (4 males and 6 females) who joined a basketball club participated in this study. Peak vertical acceleration, time between initial contact and peak vertical acceleration, and knee joint mediolateral sway were measured using the accelerometer during the landing motion. Reliability of the measurement with the accelerometer and the criterion-related validity between the accelerometer and force plate data were examined. [Results] The intraclass correlation coefficients indicated a peak vertical acceleration of 0.88, time between initial contact and peak vertical acceleration of 0.96, and knee joint mediolateral sway of 0.62. The magnitude and timing of the peak values between both measurement instruments showed high validity. [Conclusion] The measurement method using a motion sensor for the evaluation of the impact force and knee joint sway during landing has a moderate to high reliability and criterion-related validity. A motion sensor measurement might be a useful and easy method for evaluating landing impact force and knee joint stability.
Towards a Unified Internet Control Architecture

While the Internet has radically changed business and society over the past decades, its architecture has hardly evolved. Therefore, pressure from new applications, business models and networking technologies are distorting the architecture to a degree that requires a redesign. This paper presents two fundamental principles to redesign the Internet architecture. Firstly, the three fundamental building blocks reachabililty, resource control and socio-economic control must be unified to enhance flexibility while preserving its simplicity. Second, the architecture itself must be designed to evolve at run-time. The combination of these two principles will significantly enhance the reliability, robustness, manageability and functionality of the Internet, and will create new and varied business opportunities based around a common core architecture.
Using XML to Build Efficient Transaction-Time Temporal Database Systems on Relational Databases

Better support for temporal applications by database systems represents an important technical objective that is difficult to achieve since it requires an integrated solution for several problems, including (i) expressive temporal representations and data models, (ii) powerful languages for temporal queries and snapshot queries, (iii) indexing, clustering and query optimization techniques for managing temporal information efficiently, and (iv) architectures that bring together the different pieces of enabling technology into a robust system. In this paper, we present the ArchIS system that achieves these objectives by supporting a temporally grouped data model on top of RDBMS. ArchIS’ architecture uses (a) XML to support temporally grouped (virtual) representations of the database history, (b) XQuery to express powerful temporal queries on such views, (c) temporal clustering and indexing techniques for managing the actual historical data in a RDBMS, and (d) SQL/XML for executing the queries on the XML views as equivalent queries on the relational DB. The performance studies presented in the paper show that ArchIS is quite effective at storing and retrieving under complex query conditions the transaction-time history of relational databases. By supporting database compression as an option, ArchIS also assures excellent storage efficiency for archived histories. This approach achieves full-functionality transactiontime databases without requiring temporal extensions in XML or database standards.
Generalizing Temporal Dependencies for Non-Temporal Dimensions

Recently, there has been a lot of interest in temporal granularity, and its applications in temporal dependency theory and data mining. Generalization hierarchies used in multi-dimensional databases and OLAP serve a role similar to that of time granularity in temporal databases, but they also apply to non-temporal dimensions, like space. In this paper, we first generalize temporal functional dependencies for non-temporal dimensions, which leads to the notion of roll-up dependency (RUD). We show the applicability of RUDs in conceptual modeling and data mining. We then indicate that the notion of time granularity used in temporal databases is generally more expressive than the generalization hierarchies in multi-dimensional databases, and show how this surplus expressiveness can be introduced in non-temporal dimensions, which leads to the formalism of RUD with negation (RUD:). A complete axiomatization for reasoning about RUD: is given.
Generalizing Temporal Dependencies for Non-Temporal Dimensions

Recently, there has been a lot of interest in temporal granularity, and its applications in temporal dependency theory and data mining. Generalization hierarchies used in multi-dimensional databases and OLAP serve a role similar to that of time granularity in temporal databases, but they also apply to non-temporal dimensions, like space. In this paper, we first generalize temporal functional dependencies for non-temporal dimensions, which leads to the notion of roll-up dependency (RUD). We show the applicability of RUDs in conceptual modeling and data mining. We then indicate that the notion of time granularity used in temporal databases is generally more expressive than the generalization hierarchies in multi-dimensional databases, and show how this surplus expressiveness can be introduced in non-temporal dimensions, which leads to the formalism of RUD with negation (RUD ). A complete axiomatization for reasoning about RUD is given.
Adaptive H∞ formation control for Euler-Lagrange systems

Design methods of adaptive H∞ formation control of multi-agent systems composed of Euler-Lagrange systems are presented in this paper. The proposed control schemes are derived as solutions of certain H∞ control problems, where estimation errors of tuning parameters and error terms in potential functions are regarded as external disturbances to the process. It is shown that the resulting control systems are robust to uncertain system parameters and that the desirable formations are achieved asymptotically via adaptation schemes.
OWL 2 Web Ontology Language RDF-Based Semantics

The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents. The OWL 2 Document Overview describes the overall state of OWL 2, and should be read before other OWL 2 documents. This document defines the RDF-compatible model-theoretic semantics of OWL 2. OWL 2 Web Ontology LanguageRDF-Based Semantics W3C Candidate Recommendation 11 June 2009 Page 1 of 71 http://www.w3. org/TR/2009/CR-owl2-rdf-based-semantics-20090611/ Status of this Document
Summary for policymakers of the assessment report of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) on pollinators, pollination and food production

The thematic assessment of pollinators, pollination and food production carried out under the auspices of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services aims to assess animal pollination as a regulating ecosystem service underpinning food production in the context of its contribution to nature's gifts to people and supporting a good quality of life. To achieve this, it focuses on the role of native and managed pollinators, the status and trends of pollinators and pollinator-plant networks and pollination, drivers of change, impacts on human well-being, food production in response to pollination declines and deficits and the effectiveness of responses.
Multi Background Memory Testing

It is widely known that the Pattern sensitive faults are the most difficult to detect during RAM's testing process. One of the technique which can be used to effective detection of this kind of faults is multi-background test technique. According to this technique multiple run memory test execution is done. In this case to achieve high fault coverage the structure of the consecutive memory backgrounds are very important. This paper defines requirements which have to be taken into account in the background selection process. Set of backgrounds which satisfied those requirements guarantee us to achieve very high fault coverage for multi-background memory testing.
Sound Dynamic Deadlock Prediction in Linear Time

Deadlocks are one of the most notorious concurrency bugs, and significant research has focused on detecting them efficiently. Dynamic predictive analyses work by observing concurrent executions, and reason about alternative interleavings that can witness concurrency bugs. Such techniques offer scalability and sound bug reports, and have emerged as an effective approach for concurrency bug detection, such as data races. Effective dynamic deadlock prediction, however, has proven a challenging task, as no deadlock predictor currently meets the requirements of soundness , high-precision , and efficiency . In this paper, we first formally establish that this tradeoff is unavoidable, by showing that (a) sound and complete deadlock prediction is intractable, in general, and (b) even the seemingly simpler task of determining the presence of potential deadlocks, which often serve as unsound witnesses for actual predictable deadlocks, is intractable. The main contribution of this work is a new class of predictable deadlocks, called sync(hronization)-preserving deadlocks. Informally, these are deadlocks that can be predicted by reordering the observed execution while preserving the relative order of conflicting critical sections. We present two algorithms for sound deadlock prediction based on this notion. Our first algorithm SPDOffline detects all sync-preserving deadlocks, with running time that is linear per abstract deadlock pattern , a novel notion also introduced in this work. Our second algorithm SPDOnline predicts all sync-preserving deadlocks that involve two threads in a strictly online fashion, runs in overall linear time, and is better suited for a runtime monitoring setting. We implemented both our algorithms and evaluated their ability to perform offline and online deadlock-prediction on a large dataset of standard benchmarks. Our results indicate that our new notion of sync-preserving deadlocks is highly effective, as (i) it can characterize the vast majority of deadlocks and (ii) it can be detected using an online, sound, complete and highly efficient algorithm.
SAMPLING FREQUENCIES RATIO ESTIMATION AND SYMBOL TIMING RECOVERY FOR BASEBAND BINARY PULSE AMPLITUDE MODULATION

The original intent of this pro ject was to perform real time digital communications between a personal computer (PC) as the transmitter and a digital signal processor (DSP) as the receiver using the audio band analog channel. Although transmitter and receiver were both designed with baseband binary Pulse Amplitude Modulation (PAM), a low data rate and a sampling rate of 8 kilohertz, it was not possible to achieve communication between the two with traditional synchronization algorithms because of large diﬀerences in sampling clock frequencies. This thesis explores the theory and results of implementing digital communications between systems with diﬀerent sampling frequencies. The receiver structure has no a priori knowledge of the transmitter’s sampling rate, although it is assumed to be approximately equal to that of the receiver. Therefore, a receiver structure that can correct this clock frequency oﬀset is developed. Similar sampling frequencies at the transmitter and receiver are assumed in most derivations in the literature. A search of the literature found no cases of a large diﬀerence in the sampling frequencies. In general, if the receiver knows the transmitter’s sampling rate, a resampling ﬁlter at the receiver converts the signal to one compatible with the transmitters sampling rate. However, here it is assumed that the receiver does not know the transmitter’s exact sampling frequency and must be estimated. The mathematical expressions for the signals in the system are derived. The sampling frequency oﬀset introduces errors in the correct detection of the signal when it is done through traditional synchronization algorithms. Therefore, a receiver structure that corrects the sampling frequency oﬀset based on the interpolation concept is proposed. This structure will be shown to work when the correct sampling frequency ratio is known. Later, an approach to estimate the sampling frequency ratio is explored. A feedback estimator structure is derived from the Maximum Likelihood optimum criteria. A feed forward estimator that assumes the clock frequency of the transmitter and uses a synchronization sequence is explored as well.
Web surveys: a review of issues and approaches.

As we enter the twenty-first century, the Internet is having a profound effect on the survey research industry, as it is on almost every area of human enterprise. The rapid development of surveys on the World Wide Web (WWW) is leading some to argue that soon Internet (and, in particular, Web) surveys will replace traditional methods of survey data collection. Others are urging caution or even voicing skepticism about the future role Web surveys will play. Clearly, we stand at the threshold of a new era for survey research, but how this will play out is not yet clear. Whatever one's views about the likely future for survey research, the current impact of the Web on survey data collection is worthy of serious research attention. Given the rapidly growing interest in Web surveys,' it is important to distinguish among different types of Web surveys. The rubric "Web survey" encompasses a wide variety of methods, with different purposes, populations, target audiences, etc. I present an overview of some of the key types of Web surveys currently being implemented and do so using the language of survey errors. In order to judge the quality of a particular survey (be it Web or any other type), one needs to do so within the context of its stated aims and the claims it makes. By offering a typology of Web survey designs, the intent of this article is to facilitate the task of evaluating and improving Web surveys. Web surveys represent a double-edged sword for the survey industry. On the one hand, the power of Web surveys is that they make survey data collection (as opposed to survey participation) available to the masses. Not only can researchers get access to undreamed of numbers of respondents at dramatically lower costs than traditional methods, but members of the general