Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploiting FPGA-based architectures and design tools for problems of reconfigurable computations

This paper addresses the design and implementation of a configurable "combinatorial processor", a computational device, which can be used for solving different combinatorial problems. These can be characterized by a set of variables having a limited number of values with a corresponding set of operations that might be applied to these variables. Different mathematical models can be used to describe such tasks. We adopted a matrix representation, which is easier to treat in digital devices. The operations on discrete matrices are unique and cannot be efficiently performed on a general-purpose processor. Although the number of such operations grows exponentially with the number of variables, to solve a particular combinatorial problem a very small number of such operations is usually required. Hence the importance of providing for the dynamic change of operations. The paper presents an approach allowing the run-time modification of combinatorial computations via reloading the RAM-based configurable logic blocks of the FPGAs.
Arabic Dialectical Speech Recognition in Mobile Communication Services

We present in this chapter a practical approach in building Arabic automatic speech recognition (ASR) system for mobile telecommunication service applications. We also present a procedure in conducting acoustic modelling adaptation to better take into account the pronunciation variation across the Arabic speaking countries. Modern Standard Arabic (MSA) is the common spoken and written language for all the Arab countries, ranging from Morocco in the west to Syria in the East, including Egypt, and Tunisia. However, the pronunciation varies significantly from one country to another to a degree that two persons from different countries may not be able understand each other. This is because Arabic speaking countries are characterized by a large number of dialects that differ to an extent that they are no longer mutually intelligible and could almost be described as different languages. Arabic dialects are often spoken rather than written varieties. MSA is common across the Arab countries, but it is often influenced by the dialect of the speaker. This particularity of the Arabic countries constitutes a practical problem in the development of a speech-based application in this region; suppose a speech application system is built for one country influenced by one dialect, what does it take to adapt the system to serve another country with a different dialect region? This is particularly challenging since resource to build accurate speaker independent Arabic ASR system for mobile telecommunication service applications are limited for most of the Arabic dialects and countries. Recent advances in speaker independent automatic speech recognition (SI-ASR) have demonstrated that highly accurate recognition can be achieved, if enough training data is available. However, the amount of available speech data that take into account the dialectal variation of each Arabic country is limited, making it challenging to build a high performance SI-ASR system, especially when we target specific applications. Another big challenge when building an SI-ASR is to handle speaker variations in spoken language. These variations can be due to age, gender, educational level as well as the dialectical variants of Arabic language. Usually an ASR system trained in one regional variation exhibits poorer performance when applied to another regional variation. Three problems may arise when a SI-ASR system built for one dialect but applied to target users with a different dialect: (1) Acoustic model mismatch, (2) Pronunciation lexicon mismatch and (3) Language model mismatch.
Multi-graph sampling of online communities via mean hitting time

We derive a framework for sampling online communities based on the mean hitting time of its members, considering that there are multiple graphs associated with the same vertex set V representing the social network. First, we formulate random walk models on the multi-graph ensemble and define the essential properties of the mean hitting times associated with the corresponding Markov chains on the vertex set V . Then, we design a branch and bound optimization technique for computing the subset of vertices A that exhibits the shortest mean hitting time across the multi-graph, given a constraint on the size of A. We also design a greedy optimization method that computes an approximation to the optimal subset, at lower complexity, and that lends itself to a decentralized implementation, for further complexity reduction. We examine the performance of the sampling framework through a series of simulation experiments involving synthetic and actual samples of online community graphs. We demonstrate substantial improvements in terms of sampling (network) cost reduction and information dissemination speed relative to the state-of-the-art methods of node degree and eigenvector centrality.
Integrative genome‐wide analysis reveals a robust genomic glioblastoma signature associated with copy number driving changes in gene expression

Glioblastoma multiforme shows multiple chromosomal aberrations, the impact of which on gene expression remains unclear. To investigate this relationship and to identify putative initiating genomic events, we integrated a paired copy number and gene expression survey in glioblastoma using whole human genome arrays. Loci of recurrent copy number alterations were combined with gene expression profiles obtained on the same tumor samples. We identified a set of 406 “cis‐acting DNA targeted genes” corresponding to genomic aberrations with direct copy‐number‐driving changes in gene expression, defined as genes with either significantly concordant or correlated changes in DNA copy number and expression. Functional annotation revealed that these genes participate in key processes of cancer cell biology, providing insights into the genetic mechanisms driving glioblastoma. The robustness of the gene selection was validated on an external microarray data set including 81 glioblastomas and 23 non‐neoplastic brain samples. The integration of array CGH and gene expression data highlights a robust cis‐acting DNA targeted genes signature that may be critical for glioblastoma progression, with two tumor suppressor genes PCDH9 and STARD13 that could be involved in tumor invasiveness and resistance to etoposide. © 2008 Wiley‐Liss, Inc.
IMU-Based Online Kinematic Calibration of Robot Manipulator

Robot calibration is a useful diagnostic method for improving the positioning accuracy in robot production and maintenance. An online robot self-calibration method based on inertial measurement unit (IMU) is presented in this paper. The method requires that the IMU is rigidly attached to the robot manipulator, which makes it possible to obtain the orientation of the manipulator with the orientation of the IMU in real time. This paper proposed an efficient approach which incorporates Factored Quaternion Algorithm (FQA) and Kalman Filter (KF) to estimate the orientation of the IMU. Then, an Extended Kalman Filter (EKF) is used to estimate kinematic parameter errors. Using this proposed orientation estimation method will result in improved reliability and accuracy in determining the orientation of the manipulator. Compared with the existing vision-based self-calibration methods, the great advantage of this method is that it does not need the complex steps, such as camera calibration, images capture, and corner detection, which make the robot calibration procedure more autonomous in a dynamic manufacturing environment. Experimental studies on a GOOGOL GRB3016 robot show that this method has better accuracy, convenience, and effectiveness than vision-based methods.
Preventing Insider Information Leakage for Enterprises

This paper proposes a novel mechanism for protecting sensitive information inside big organisations against unauthorised disclosure by insider or outsider adversaries. Protecting sensitive content from being disclosed to unauthorised parties is a major concern for big enterprises, such as government agencies, banks, clinics and corporations. This paper mainly focuses on preventing insider information leakage whilst allowing authorised users to have privileged access on sensitive information from inside or outside an organisational premises. In this paper we use location-based services to bind devices to an organisational predefined geographical locations, helping to ensure that each organisation owns and manages its own devices (where its sensitive content can 'only' be accessed).
Adaptive Power Resource Allocation With Multi-Beam Directivity Control in High-Throughput Satellite Communication Systems

The demand for satellite communication (SATCOM) has been increasing to provide communication environments for terminals in areas with no terrestrial network coverage and to provide communication means with Internet of Things (IoT) equipment. Accordingly, a few schemes are being studied to efficiently allocate power resources with multi-beam directivity control through digital beam forming (DBF). Moreover, power resource allocation with simultaneous control of the transmit power and multi-beam directivity can be expected to increase the flexibility according to traffic demand. However, there is a trade-off between the transmit power and beam directivity under some physical constraints, and currently there is no mathematical model to solve this problem. The contributions of this letter are to construct a new mathematical model necessary for solving the trade-off, and to introduce a novel power resource allocation with fusion control of the transmit power and multi-beam directivity according to traffic demand with the objective of improving the allocation efficiency of communication resources. We carried out a numerical analysis to verify the effectiveness of our proposal.
On the Feasibility of Switching ISPs in Residential Multihoming

In theory, multi homed Internet hosts, that is, hosts simultaneously connected to multiple Internet service providers (ISP) should see increased access capacity, be able to circumvent possible last-mile congestion problems, and experience improved end-to-end quality of service (QoS). In practice however, the advantages one can gain from multi homing are highly dependent on the path switching mechanism used, that is, on dynamically deciding which ISP should be used as a first-hop. This paper is a first step toward understanding the trade-off between performance improvements multi homing can help achieve and the complexity of the decisions that must be made. We measure changes in end-to-end network layer metrics (loss, latency, jitter) over the different paths available from a multi homed host to a large population of Internet hosts. Our measurements indicate that (1) in over 60% of the cases, one only needs to reevaluate the service provided by each ISP every minute to improve the performance of a specific metric, and that (2) in approximately 85% of the cases, decisions to switch from one ISP to another can be treated independently of the service metric of interest. We conclude that multi homing could in practice result in noticeable performance improvements.
Data selection for compact adapted SMT models

Data selection is a common technique for adapting statistical translation models for a specific domain, which has been shown to both improve translation quality and to reduce model size. Selection relies on some in-domain data, of the same domain of the texts expected to be translated. Selecting the sentence-pairs that are most similar to the in-domain data from a pool of parallel texts has been shown to be effective; yet, this approach holds the risk of resulting in a limited coverage, when necessary n-grams that do appear in the pool are less similar to in-domain data that is available in advance. Some methods select additional data based on the actual text that needs to be translated. While useful, this is not always a practical scenario. In this work we describe an extensive exploration of data selection techniques over Arabic to French datasets, and propose methods to address both similarity and coverage considerations while maintaining a limited model size.
New Evidence on the Finite Sample Properties of Propensity Score Reweighting and Matching Estimators

Abstract Frölich (2004) compares the finite sample properties of reweighting and matching estimators of average treatment effects and concludes that reweighting performs far worse than even the simplest matching estimator. We argue that this conclusion is unjustified. Neither approach dominates the other uniformly across data-generating processes (DGPs). Expanding on Frölich's analysis, this paper analyzes empirical as well as hypothetical DGPs and also examines the effect of misspecification. We conclude that reweighting is competitive with the most effective matching estimators when overlap is good, but that matching may be more effective when overlap is sufficiently poor.
Luminosity distributions within rich clusters — II. Demonstration and verification via simulation

We present detailed simulations of long-exposure CCD images. The simulations are used to explore the validity of the statistical method for reconstructing the luminosity distribution of galaxies within a rich cluster, i.e., by the subtraction of field number-counts from those of a sight-line through the cluster. In particular, we use the simulations to establish the reliability of our observational data to be presented in Paper III. Based on our intended CCD field-of-view (6.5 × 6.5 arcmin2) and a 1σ detection limit of 26 mag arcsec−2, we conclude that the luminosity distribution can be robustly determined over a wide range of absolute magnitude (−23 < MR < −16) provided: (a) the cluster has an Abell richness 1.5 or greater; (b) the redshift of the cluster lies in the range 0.1 < z < 0.3; (c) the seeing is better than FWHM 1.25 arcsec, and (d) the photometric zero-points are accurate to within Δm = ± 0.12. If these conditions are not met, then the recovered luminosity distribution is unreliable. Finally, although the method clearly has limitations, within these limitations the technique represents an extremely promising probe of galaxy evolution and environmental dependences.
Cosmological smoothed particle hydrodynamics simulations: a hybrid multiphase model for star formation

We present a model for star formation and supernova feedback that describes the multiphase structure of star-forming gas on scales that are typically not resolved in cosmological simulations. Our approach includes radiative heating and cooling, the growth of cold clouds embedded in an ambient hot medium, star formation in these clouds, feedback from supernovae in the form of thermal heating and cloud evaporation, galactic winds and outflows, and metal enrichment. Implemented using smoothed particle hydrodynamics, our scheme is a significantly modified and extended version of the grid-based method of Yepes et al., and enables us to achieve a high dynamic range in simulations of structure formation. We discuss properties of the feedback model in detail and show that it predicts a self-regulated, quiescent mode of star formation, which, in particular, stabilizes the star-forming gaseous layers of disc galaxies. The parametrization of this mode can be reduced to a single free quantity that determines the overall time-scale for star formation. We fix this parameter numerically to match the observed rates of star formation in local disc galaxies. When normalized in this manner, cosmological simulations employing our model nevertheless overproduce the observed cosmic abundance of stellar material. We are thus motivated to extend our feedback model to include galactic winds associated with star formation. Using small-scale simulations of individual star-forming disc galaxies, we show that these winds produce either galactic fountains or outflows, depending on the depth of the gravitational potential. In low-mass haloes, winds can greatly suppress the overall efficiency of star formation. When incorporated into cosmological simulations, our combined model for star formation and winds predicts a cosmic star formation density that is consistent with observations, provided that the winds are sufficiently energetic. Moreover, outflows from galaxies in these simulations drive chemical enrichment of the intergalactic medium – in principle, accounting for the presence of metals in the Lyman α forest.
An Application for Stereo Vision based Vehicle/Obstacle Detection for Driver Assistance

A stereo vision based vehicle/obstacle detection system has been proposed that generates alarms when vehicles/obstacles are detected in vicinity of near/mid region. Numerous techniques have been applied to detect vehicles/obstacles using a forward facing monocular camera mounted inside a vehicle. This paper presents a methodology for vehicle/obstacle detection using high resolution stereo camera. Stereo cameras are calibrated; stereo images are undistorted and rectified using stereo calibration parameters. Stereo disparity image is then generated using stereo matching algorithm. To localize vehicles/obstacles, search space reduction forms a preliminary step by eliminating sky region retaining only road regions on which vehicles/obstacles are embedded. Periodic peaks in the histogram of stereo disparity image are used as a cue in vehicle/obstacle detection process. Line profiles corresponding to each periodic peak are extracted using vertical strokes. Statistical features are extracted and analyzed for each line profiles to determine the presence/absence of vehicles/obstacles. If vehicles/obstacles are detected in a line profile, then bounding box of blobs are detected using vertical projection technique. Blobs detected from all the gray level profiles are merged together and connected component analysis is applied to count the number of vehicles/obstacles. Color mapping of vehicles/obstacles detected are done to indicate the presence of vehicles/obstacles in near region or mid region thereby generating appropriate alarms.
Cooperative or collaborative learning: Is there a difference in university students’ perceptions?

espanolLa hipotesis de que un mismo objetivo educativo planteado como aprendizaje cooperativo o colaborativo en ensenanza universitaria no afecta a la percepcion que los estudiantes tienen de dicho modelo de aprendizaje, guia este trabajo. En el se analizan las reflexiones de dos grupos de estudiantes de ingenieria que compartieron los mismos objetivos educativos implementados a traves de dos estrategias metodologicas activas diferentes de aprendizaje: la simulacion como estrategia de aprendizaje cooperativo y el aprendizaje basado en problemas como estrategia colaborativa. El numero distinto de participantes por grupo (ochenta y cinco frente a sesenta y cinco, respectivamente) asi como el uso de dos estrategias de aprendizaje activas, bien colaborativa o cooperativa, no arrojaron diferencias en los resultados del analisis cualitativo. EnglishThe hypothesis that the same educational objective, raised as cooperative or collaborative learning in university teaching does not affect students’ perceptions of the learning model, leads this study. It analyses the reflections of two students groups of engineering that shared the same educational goals implemented through two different methodological active learning strategies: Simulation as cooperative learning strategy and Problem-based Learning as a collaborative one. The different number of participants per group (eighty-five and sixty-five, respectively) as well as the use of two active learning strategies, either collaborative or cooperative, did not show differences in the results from a qualitative perspective.
0.35 μm 22μW Multiphase Programmable Clock Generator for Circular Memory SC FIR Filter For Wireless Sensor Applications

The paper presents the programmable multiphase clock generator for switched-capacitor finite impulse response (SC FIR) circular memory filters. The proposed programmable clock circuit enables easy division of such kind of filters into different orders smaller sections, which when connected in series, lead to increase in filter efficiency: reduction of chip area, power dissipation, and rising up of the speed. The proposed clock generator enables adjustment of the impulses width, that simplifies design process and leads to structure, which is more robust to process variation. The clock circuit realized in CMOS 0.35 μm technology, dissipates 22 μW from 2 V power supply
Sharing Forecast Information in a Long-term Supply Chain Relationship

Forecast sharing in a supply chain using linear price contracts often leads to inefficiencies as the buyer has an incentive to inflate demand forecasts to ensure sufficient supply. Recent research in supply chain contracting has focused on one-shot relationships, and has identified various contracts that align incentives in the supply chain and induce the buyer to reveal forecast information truthfully. In this paper, we investigate the effect of having an infinitely repeated supplier relationship in achieving supply chain coordination. We analyze a capacity game with forecast sharing under information asymmetry. We establish conditions under which a buyer operating with a linear price contract reveals demand information truthfully with his supplier, who in turn allocates system-optimal capacity, both assuming that their business relationship is long-term. We show that in a repeated forecast sharing game coordination can be achieved when the industry is stable, both parties value their long-term relationship, and over-forecasting is easy to detect. ∗Operations and Technology Management Department, Boston University School of Management. †Operations and Information Management Department, The Wharton School, Univ. of Pennsylvania. ‡Marketing Group, Haas School of Business, University of California-Berkeley.
Audio Classification Using Semantic Transformation and Classifier Ensemble

This paper presents our winning audio classification system in MIREX 2010. Our system is implemented as follows. First, in the training phase, the frame-based 70-dimensional feature vectors are extracted from a training audio clip by MIRToolbox. Next, the Posterior Weighted Bernoulli Mixture Model (PWBMM) is applied to transform the frame-decomposed feature vectors of the training song into a fixed-dimensional semantic vector representation based on the pre-defined music tags; this procedure is called Semantic Transformation. Finally, for each class, the semantic vectors of associated training clips are used to train an ensemble classifier consisting of SVM and AdaBoost classifiers. In the classification phase, a testing audio clip is first represented by a semantic vector, and then the class with the highest score is selected as the final output. Our system was ranked first out of 36 submissions in the MIREX 2010 audio mood classification task.
What Role Does the Authoritarian Leadership and Benevolent Leadership Play in the Relationship Between Voice Behavior and Innovative Behavior

When individuals can actively and proposing suggestions, they will also show a stronger desire for innovation. The generation of voice behavior can promote the creation of individual innovative behavior. In the background of Chinese culture, this process will be influenced by authoritarian leadership and benevolent leadership. Authoritarian leaders play a negative regulatory role in the process of voice behavior influencing innovative behavior, while benevolent leadership plays a positive regulatory role.