Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards an automatic generation of dense linear algebra solvers on parallel architectures

The increasing complexity of new parallel architectures has widened the gap between adaptability and efficiency of the codes. As high performance numerical libraries tend to focus more on performance, we wish to address this issue using a C++ library called NT2. By analyzing the properties of the linear algebra domain that can be extracted from numerical libraries and combining them with architectural features, we developed a generic approach to solve dense linear systems on various architectures including CPU and GPU. We have then extended our work with an example of a least squares solver based on semi-normal equations in mixed precision that cannot be found in current libraries. For the automatically generated solvers, we report performance comparison with state-of-the-art codes, showing that it is possible to obtain a generic code with a high-level interface (similar to Matlab) that can run either on CPU or GPU and that does not generate significant overhead.
Desde RNFs a Componentes a través de Tácticas de Arquitectura: Una Revisión Sistemática de la Literatura

La arquitectura de un sistema de software es resultado de numerosas decisiones de diseno sobre los compo- nentes y estructura adecuados para proveer las funcionalidades y propiedades requeridas. Las tacticas de arquitectura son una forma destacada de abordar requisitos no-funcionales (RNFs), pero parece existir poco trabajo metodologico que formalice el uso de tacticas para combinar componentes para abordar RNFs especificos. Este articulo describe una revision sistematica de la literatura (RSL) sobre el uso metodologico combinado de RNFs, tacticas de arquitectura, y componentes de software. Se definio preguntas de investigacion sobre (1) seleccion de componentes utilizando RNFs, (2) seleccion de componentes utilizando la relacion entre RNFs y arquitectura, y (3) relacion entre RNFs y tacticas. Se encontro 1964 articulos en directorios conocidos, luego filtrados a 59 articulos directamente relevantes al tema de estudio. Un examen detallado de estos articulos ilustra que las tacticas son utiles como concepto intermedio para identificar componentes desde RNFs, pero hasta ahora hay solo un grupo pequeno de propuestas especificas.
Event-triggered cooperative compensation control for consensus of heterogeneous multi-agent systems

This paper addresses the event-triggered consensus for heterogeneous multi-agent systems (He-MASs) via a distributed cooperative compensation control (D3C) strategy. The proposed D3C law involves two dynamics: (i) a pre-given virtual leader, which specifies the synchronisation trajectory for whole He-MASs; (ii) two intermediate compensation system, whose system state is broadcasted to neighbour agents through communication network for facilitating the consensus. To further reduce data exchanging frequency so as to alleviate communication burden, an exponential event-trigger is employed to determine whether the current sampled data need to be broadcasted or suspended. By two concise algebraic Riccati inequalities and some supplement conditions, a sufficient collaborative design method is presented for obtaining the values of D3C gains and the thresholds of event-trigger, while the Zeno phenomena is also excluded. The proposed strategy guarantees the consensus of He-MASs and significantly reduces data exchanging amounts. Finally, some illustrative examples are given to validate effectiveness of the proposed results.
Design of Parallel Architecture Co-Processor for Particle Swarm Optimization Algorithm

The direct implementation of parallel particle swarm optimization algorithm on Field Programmable Gate Array (FPGA) is presented in this paper. In the proposed design, the particle unit architecture is independent of fitness unit and hence the particle unit is reusable and flexible for different fitness function. The parallel co-processor implementation of each particle accelerates the execution speed and reduces the operating power as compared to the software execution of the design on a general purpose processor. The proposed implementation reduces the number of registers by 2.76% and the number of look-up-tables by 0.62% on average.
Specific incremental test in tennis

Physiological, technical, and tactical skills are all important to performance in racquet sports (Lee, 2003). A major determinant of the outcome of a tennis match is the player's physical fitness, which enables them to repeatedly generate power, explosive strokes and rapid court movements during extended matches (Konig et. al., 2001). Laboratory testing is commonly used to evaluate physical fitness or characterise training effects. It might also be performed for prescribing the sub-maximal training intensities used during the aerobic training for tennis. However, during treadmill testing,the modes of exercise tests (continuous activity) often do not simulate the specific demands of tennis (intermittent activity) and therefore do not reflect the specific muscular involvement of both lower and upper limbs with respect to the stop, start and change of direction movement patterns required during tennis play (Fernandez, 2005).
MicroC/OS-II 실시간 운영체제에서의 우선순위 역전현상 해결을 위한 일시적 우선순위 교환 프로토콜 설계 및 구현

실시간 운영체제는 효율적인 스케줄링, 최소화된 인터럽트 지연, 우선순위 역전현상 해결 등의 다양한 조건을 만족시킴과 동시에, 응용프로 그램이 정해진 기한 내에 수행되는 것을 보장하여야 한다. 따라서 실시간 운영체제는 상기 조건을 만족시킬 수 있도록 설계/개발되어야 한다. 대중적인 실시간 커널의 한 종류인 MicroC/OS-II에서는 우선순위 역전 현상에 대한 해결 기법으로 뮤텍스(Mutex)를 사용한 기본적인 우선순 위 상속(Basic Priority Inheritance) 프로토콜을 사용한다. 뮤텍스를 구현하려면 우선순위가 같은 여러 태스크를 사용할 수 있도록 커널이 지원 해야 하나 MicroC/OS-II 운영체제는 우선순위가 같은 여러 태스크의 동시 사용을 지원하지 않는다. 이를 해결하기 위해 추가적인 우선순위 예 약을 사용할 수밖에 없게 되고, 결과적으로 제한된 우선순위 자원을 낭비하게 된다. 본 논문에서는 MicroC/OS-II의 불필요한 우선순위 자원을 낭비하는 문제점을 해결할 수 있는 일시적 우선순위 교환 프로토콜(Temporary Priority Swapping Protocol; TPSP)을 설계 및 구현하여, 한정 된 자원 환경을 가진 임베디드 장비에 효율적으로 운용되도록 하는데 목적을 둔다. 【Real-time operating systems must have satisfying various conditions such as effective scheduling policies, minimized interrupt delay, resolved priority inversion problems, and its applications to be completed within desired deadline. The real-time operating systems, therefore, should be designed and developed to be optimal for these requirements. MicroC/OS-II, a kind of Real-time operating systems, uses the basic priority inheritance with a mutex to solve priority inversion problems. For the implementation of mutex, the kernel in an operating system should provide supports for numerous tasks with same priority. However, MicroC/OS-II does not provide this support for the numerous tasks of same priority. To solve this problem, MicroC/OS-II cannot but using priority reservation, which leads to the waste of unnecessary resources. In this study, we have dealt with new design a protocol, so called TPSP(Temporary Priority Swap Protocol), by an effective solution for above-mentioned problem, eventually enabling embedded systems with constrained resources environments to run applications. 】
A Minimum-energy Consumption Control Algorithm of Control Vector Parameterization for Four-wheel Drive Omni-directional Mobile Robots

Abstract A minimum-energy consumption control algorithm of control vector parameterization is applied to motion control of a four-wheel drive omni-directional mobile robot (FDOMR) in actual application environment. After establishing the robot’s dynamic equations about motor model, we have chosen a practical cost function as the total energy drawn from the batteries. By introducing a normalized time variable, the original problem is transformed into a fixed final time optimal control problem which is solved by using uniform control vector parameterization. Various simulations are performed and the consumed energy is compared to the normal control method that without minimum energy consumption control. Simulation results reveal that the energy saving is much more compared to the traditional control, the operational time of the FDOMR with given batteries is lengthened and the efficiency of battery is improved.
Drawing and guiding gestures in a mathematical task using the AHEAD application

This paper presents partial results from an evaluation done in practical school work of the audio haptic drawing editor and explorer (AHEAD). In this paper we focus on a mathematical design and reproduce group work task performed by two pupils (one sighted and one visually impaired pupil). Apart from the fact that the pupils were able to do the task, tentative results show some differences in the usage of the program functionality while no significant differences can be seen in the times spent drawing. We also present some discussion of the guiding gesture used by the mouse user to help the PHANToM user understand the drawn image.
Fundamental limitations on the capacity of wireless links that use polarimetric antenna arrays

It was recently speculated that six-component polarimetric antennas $comprising six co-located electric and magnetic dipoles that generate the six components of electric and magnetic current or that measure the six components of the electric and magnetic field - could give six-fold improvements in capacity over single-component antennas in Rayleigh flat fading. Using an exact wave propagation formulation involving the plane-wave spectral decompositions of the transmitted and scattered fields, we show that the behavior of wireless links based on arrays of polarimetric antennas is qualitatively different than that of links based on single polarimetric antennas. The MIMO channel can be viewed rigorously in the wavenumber domain. For dense planar arrays, the use of polarimetric antennas yields at most a fourfold improvement in capacity, which can be realized by particular combinations of four of the six dipoles. Six-component elements, the expansion of the planar arrays into volume arrays, or spacing elements at intervals less than a half-wavelength only give additional logarithmic improvements in capacity.
Data mining for a web-based educational system

Web-based educational technologies allow educators to study how students learn (descriptive studies) and which learning strategies are most effective (causal/predictive studies). Since web-based educational systems are capable of collecting vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of students, assessments, and the solution strategies adopted by students. The focus of this dissertation is three-fold: (1) to introduce an approach for predicting student performance; (2) to use clustering ensembles to build an optimal framework for clustering web-based assessment resources; and (3) to propose a framework for the discovery of interesting association rules within a web-based educational system. Taken together and used within the online educational setting, the value of these tasks lies in improving student performance and the effective design of the online courses. First, this research presents an approach to classifying student characteristics in order to predict performance on assessments based on features extracted from logged data in a web-based educational system. We show that a significant improvement in classification performance is achieved by using a combination of multiple classifiers. Furthermore, by “learning” an appropriate weighting of the features via a genetic algorithm (GA), we have successfully improved the accuracy of the combined classifier performance by another 10–12%. Such classification is the first step towards a “recommendation system” that will provide valuable, individualized feedback to students. Second, this project extends previous theoretical work regarding clustering ensembles with the goal of creating an optimal framework for categorizing web-based educational resources. We propose both non-adaptive and adaptive resampling schemes for the integration of multiple clusterings (independent and dependent). Experimental results show improved stability and accuracy for clustering structures obtained via bootstrapping, subsampling, and adaptive techniques. These improvements offer insights into specific associations within the data sets. Finally, this study turns toward developing a technique for discovering interesting associations between student attributes, problem attributes, and solution strategies. We propose an algorithm for the discovery of “interesting” association rules within a web-based educational system. The main focus is on mining interesting contrast rules, which are sets of conjunctive rules describing interesting characteristics of different segments within a population. In the context of web-based educational systems, contrast rules help to identify attributes characterizing patterns of performance disparity between various groups of students. We propose a general formulation of contrast rules as well as a framework for finding such patterns. Examining these contrasts can improve the online educational systems for both teachers and students—allowing for more accurate assessment and more effective evaluation of the learning process.
The Future of Competition Policy in Europe – Some Reflections on the Interaction Between Industrial Policy and Competition Law

The paper explores the interaction between industrial policy and competition law, in particular merger control in Europe. It reflects on the tensions, actual and perceived, between these two policies and critically assesses the substantive and institutional solutions that have been proposed, in particular in the recent Franco-German Manifesto for a European industrial policy fit for the 21st Century.
Measuring, refining and calibrating speaker and language information extracted from speech

We propose a new methodology, based on proper scoring rules, for the evaluation of the goodness of pattern recognizers with probabilistic outputs. The recognizers of interest take an input, known to belong to one of a discrete set of classes, and output a calibrated likelihood for each class. This is a generalization of the traditional use of proper scoring rules to evaluate the goodness of probability distributions. A recognizer with outputs in well-calibrated probability distribution form can be applied to make cost-effective Bayes decisions over a range of applications, having different cost functions. A recognizer with likelihood output can additionally be employed for a wide range of prior distributions for the to-be-recognized classes. We use automatic speaker recognition and automatic spoken language recognition as prototypes of this type of pattern recognizer. The traditional evaluation methods in these fields, as represented by the series of NIST Speaker and Language Recognition Evaluations, evaluate hard decisions made by the recognizers. This makes these recognizers cost-and-prior-dependent. The proposed methodology generalizes that of the NIST evaluations, allowing for the evaluation of recognizers which are intended to be usefully applied over a wide range of applications, having variable priors and costs. The proposal includes a family of evaluation criteria, where each member of the family is formed by a proper scoring rule. We emphasize two members of this family: (i) A non-strict scoring rule, directly representing error-rate at a given prior. (ii) The strict logarithmic scoring rule which represents information content, or which equivalently represents summarized error-rate, or expected cost, over a wide range of applications. We further show how to form a family of secondary evaluation criteria, which by contrasting with the primary criteria, form an analysis of the goodness of calibration of the recognizer’s likelihoods. Finally, we show how to use the logarithmic scoring rule as an objective function for the discriminative training of fusion and calibration of speaker and language recognizers.
Invariant-based registration of rotated and blurred images

Image registration is a classical problem in remotely sensed image analysis. In this paper, attention is paid to control point matching for the case when the images are blurred and rotated compared to one another. The matching is performed by means of a new class of moment invariants, which are calculated over the neighborhood of each candidate. The proposed invariants are invariant not only to rotation and translation but also to image blurring by any symmetric point spread function. Thanks to this, the authors can register blurred images directly without any de-blurring.
A measure of fairness of service for scheduling algorithms in multiuser systems

When considering issues of fairness of scheduling algorithms for packet data in networks, there is no well-defined quantitative value for the "fairness" of the system. Rather, fairness is usually expressed in broader terms. Generally, a system is deemed to be fair if it meets certain criteria on throughput or delay, and unfair if the criteria are not met. For example, a system in which some user receives a throughput less than Xbits/sec or experiences a delay /spl tau/ with probability greater than p% may be deemed to be unfair. These definitions of fairness say if the system is or is not fair, but not how fair or unfair. This paper attempts to make a quantitative definition for a value of "fairness" that makes sense from both a mathematical and semantic standpoint. Such a value could be used to quickly compare the fairness of differing systems or algorithms. Definitions for the self-fairness and self-unfairness of the users of the system, and the average fairness and average unfairness of the overall system are proposed. The case is first considered when all users are weighted equally. That is, every user is considered to have the same importance, and hence each user should receive an equal proportion of the allocated resources for the system to be fair. The definitions are then extended to the case when the users have different weightings (for example, to achieve different levels of quality of service). The definitions take the viewpoint that the users themselves control what resources they are allocated. However, the definitions can just as easily be applied to the case when a central scheduling algorithm determines the allocation of resources to the users.
Analysis of the influence of water body on polarimetric sar calibration

The information content retrievable from the China domestic X band polarimetric and interferometric synthetic aperture radar (XSAR, the China Electronics Technology Group Corporation 38 department product) is evaluated with respect to polarimetric calibration. The XSAR data includes a variety of natural and artificial targets. Low backscatter from water body poses challenges for polarimetric information and calibration parameter. A method for polarimetric calibration proposed by Ainsworth has the potential to provide wider application scope, which imposes only the weakest of constraints. The calibration method relied on range dependencies and low NESZ that, if not entirely fulfilled, may result in compromising the performance and accuracy of calibration. An investigation is presented of these statistics for river and agricultural scene. This paper discusses range dependencies and additive noise of Cross-polarization related to polarimetric calibration. The achieved enhancement in stability of cross-talk parameter estimation is demonstrated in terms of trihedral corner reflector response. (5 pages)
Development of physiological metabolic models in diabetes based on data mining techniques

Η παρούσα διδακτορική διατριβή πραγματεύεται το πρόβλημα της βραχυπρόθεσμης πρόβλεψης της συγκέντρωσης της γλυκόζης στον υποδόριο χώρο σε άτομα με σακχαρώδη διαβήτη τύπου 1 και υπό κανονικές συνθήκες διαβίωσης. Η διδακτορική διατριβή αποτελείται από τρία μέρη. Στο πρώτο μέρος, προσεγγίσαμε το συγκεκριμένο πρόβλημα μέσω μίας χρονικά-αμετάβλητης συνάρτησης παλινδρόμησης διανυσμάτων υποστήριξης, η αξιολόγηση (εκπαίδευση και έλεγχος) της οποίας πραγματοποιήθηκε ξεχωριστά για τον κάθε ασθενή. Η είσοδος του μοντέλου περιγράφει το πρόσφατο ιστορικό της υποδόριας γλυκόζης, την επίδραση του φαγητού και της θεραπείας ινσουλίνης, την κατανάλωση ενέργειας κατά τις φυσικές δραστηριότητες, και χρονική πληροφορία αναφορικά με την ώρα της ημέρας κατά την οποία πραγματοποιείται η πρόβλεψη. Εξετάζοντας διαφορετικές περιπτώσεις εισόδου, ποσοτικοποιήσαμε την επίδραση κάθε μεταβλητής στο σφάλμα πρόβλεψης της συγκέντρωσης της γλυκόζης, και δείξαμε ότι ο συνδυασμός πολύ-μεταβλητών δεδομένων βελτιώνει σημαντικά το σφάλμα πρόβλεψης. Εν συνεχεία, εξετάσαμε τη συμπεριφορά του προτεινομένου μοντέλου ως προς την πρόβλεψη των μεμονωμένων υπογλυκαιμικών επεισοδίων. Η μελέτη αυτή μας οδήγησε στην εισαγωγή νέων μεταβλητών εισόδου οι οποίες στοχεύουν να περιγράψουν την επίδραση της προηγηθείσας υπογλυκαιμίας, της άσκησης και του νυχτερινού ύπνου στην εκδήλωση ενός υπογλυκαιμικού επεισοδίου, οι οποίες και βελτίωσαν την ευαισθησία και τη θετική προγνωστική αξία του μοντέλου. Στο δεύτερο μέρος της παρούσας διδακτορικής διατριβής προχωρήσαμε σε τεχνικές κατάταξης χαρακτηριστικών για την αξιολόγηση της προβλεπτικής αξίας του συνόλου των χαρακτηριστικών, με απώτερο στόχο την εξατομίκευση της εισόδου της συνάρτησης παλινδρόμησης της συγκέντρωσης της γλυκόζης στον υποδόριο χώρο. Ειδικότερα, χρησιμοποιήσαμε τον αλγόριθμο τυχαίων δασών και τον αλγόριθμο RReliefF, και μέσω μιας διαδικασίας εμπρόσθιας διαδοχικής επιλογής χαρακτηριστικών, διερευνήσαμε την επίδραση των πιο σημαντικών χαρακτηριστικών στο σφάλμα πρόβλεψης των βασιζόμενων σε συναρτήσεις πυρήνα μοντέλων παλινδρόμησης (παλινδρόμηση διανυσμάτων υποστήριξης και Gaussian διαδικασίες). Στο τρίτο μέρος της παρούσας διδακτορικής διατριβής, προτείναμε την προσαρμοστική εκμάθηση και πρόβλεψης της βραχυπρόθεσμη πορείας την υποδόριας συγκέντρωσης της γλυκόζης στον διαβήτη τύπου 1 μέσω αραιών αναπαραστάσεων προσαρμοστικών φίλτρων πυρήνα. Ειδικότερα, οι αλγόριθμοι που εξετάσαμε αποτελούν αναπαραστάσεις της μεθόδου ελαχίστων μέσων τετραγώνων και επαναληπτικών ελαχίστων τετραγώνων στον χώρο συναρτήσεων Hilbert με αναπαραγωγικό πυρήνα. Παράλληλα, επαληθεύσαμε ότι, όταν λαμβάνονται υπόψιν οι εξωγενείς είσοδοι, υπάρχει συστηματική βελτίωση της ποιότητας των προβλέψεων, ως προς την ομαλότητα και τη χρονική υστέρηση, καθώς και μείωση του σφάλματος στις κρίσιμες περιοχές της υπογλυκαιμίας και υπεργλυκαιμίας.
Ideal GMM parameters & posterior log likelihood for speaker verification

Personal Identity Verification using non-alterable bio-characters is fast becoming a standard add-on layer of security for access to sensitive information. This paper presents a performance centric study of our text-independent speaker verification system using the highly parametric Gaussian Mixture Modeling [GMM] technique on the KING Speaker Verification database. The system was evaluated based on Equal Error Rate [EER] scores using different parameters - namely, the number of mixtures [M] and dimensions [D], applied to the Gaussian Mixture Model [GMM]. A new scoring method, in the quest for better performance in terms of EER is also discussed. These techniques aim to pre-determine the optimum values for M and D, and apply a scoring technique that provides optimum tradeoff between complexity and performance. Simulation results obtained confirm the implementation of speaker verification algorithms with minimal real-time adaptability requirements. This aids the development of more robust and predictive voice based authentication applications. Finally, we demonstrate that the proposed Posterior Log-Likelihood based scoring does not provide significant performance gains over log-likelihood based scoring techniques.