Miracle-dz/UniFAR-FTUs huggingface dataset:
Le comportement de boycott basé sur le sentiment d’animosité: proposition d’un cadre conceptuel

Cet article permet la conceptualisation d’un modele de comportement de boycott base sur le sentiment d’animosite dans le cadre de la campagne internationale qui a touche des produits associes a l’Etat d’Israel lors de la guerre contre Gaza. Ce modele sera extrapole au cadre tunisien en integrant des variables instrumentales, socio-psychologiques, rationnelles et culturelles permettant de tester differentes relations et contribuant a la comprehension des motivations individuelles qui regissent ce phenomene.
Solving POMDP by Onolicy Linear Approximate Learning Algorithm

This paper presents a fast Reinforcement Learning (RL) algorithm to solve Partially Observable Markov Decision Processes (POMDP) problem. The proposed algorithm is devised to provide a policy-making framework for Network Management Systems (NMS) which is in essence an engineering application without an exact model. The algorithm consists of two phases. Firstly, the model is estimated and policy is learned in a completely observable simulator. Secondly, the estimated model is brought into the partially observed real-world where the learned policy is then fine-tuned. The learning algorithm is based on the on-policy linear gradient-descent learning algorithm with eligibility traces. This implies that the Q-value on belief space is linearly approximated by the Q-value at vertex over the belief space where on-line TD method will be applied. The proposed algorithm is tested against the exact solutions to extensive small/middle-siz benchmark examples from POMDP literature and found near optimal in terms of average-discounted-reward and step-to-goal. The proposed algorithm significantly reduces the convergence time and can easily be adapted to large state-number problems.
Covert Research

covert study explored fictive kinship, choreographed bravado, violence, and hypermasculinity in the subculture of bouncers. His study was of a purist type and involved no gatekeeping, key informants, or retrospective debriefing. His study challenged the popular demonization of bouncers. Katherine Frank’s cultural anthropological work, G-Strings and Sympathy (2002), which formed the basis of her on erotic dancing, includes 6 years’ intermittent work as a nude entertainer with five different strip clubs in the United States. Her covert first-hand insider experience, combined with interview data from regular patrons and dancers, covers male desire, sexual fantasy, and counterfeit intimacy. Her work has a landmark status within the field, particularly in providing the male consumer perspective.
Towards a new approach of haptic human-robot interaction for collaborative manipulation

This work presents a new approach of haptic human-robot interaction for joint manipulation of large objects. As a shared manipulation strategy, we propose to decompose any task in different non-honolomic motions (rotations and translations). The intention of the next non-honolomic motion is detected by analysing haptic cues. An experiment with ten subjects is realised to compare this proposed approach with a backdrivable robot interaction. Results show the efficiency of the new approach to realize a task involving rotations and translations. The task is performed faster and lower torque is applied by the operator.
The Sensorimotor Control of Speech Production

A model of the sensorimotor control of speech production is presented. The model is being implemented as a set of computer simulations. It converts an input sequence of discrete phonemes into quasi-continuous motor commands and a sound output. A key feature of the model is that the goals for speech movements, at least for some kinds of sounds, are regions in auditory-temporal space. The model is designed to have properties that are as faithful as possible to data from speakers – including measures of brain function, speech motor control mechanisms, physiology, anatomy, biomechanics and acoustics. Examples of simulations and actual data from some of these domains are presented. The examples demonstrate properties of the model or they are consistent with hypotheses generated from it. Our long-range goal is to implement the model completely and test it exhaustively, in the belief that doing so will significantly advance our understanding of speech motor control.
Learning Person-Specific Representations From Faces in the Wild

Humans are natural face recognition experts, far out-performing current automated face recognition algorithms, especially in naturalistic, “in the wild” settings. However, a striking feature of human face recognition is that we are dramatically better at recognizing highly familiar faces, presumably because we can leverage large amounts of past experience with the appearance of an individual to aid future recognition. Meanwhile, the analogous situation in automated face recognition, where a large number of training examples of an individual are available, has been largely underexplored, in spite of the increasing relevance of this setting in the age of social media. Inspired by these observations, we propose to explicitly learn enhanced face representations on a per-individual basis, and we present two methods enabling this approach. By learning and operating within person-specific representations, we are able to significantly outperform the previous state-of-the-art on PubFig83, a challenging benchmark for familiar face recognition in the wild, using a novel method for learning representations in deep visual hierarchies. We suggest that such person-specific representations aid recognition by introducing an intermediate form of regularization to the problem.
Multidrug Resistance and Plasmid Patterns of Escherichia coli O157 and Other E. coli Isolated from Diarrhoeal Stools and Surface Waters from Some Selected Sources in Zaria, Nigeria

We have assessed the prevalence of Escherichia coli O157 in diarrhoeal patients and surface waters from some selected sources in Zaria (Nigeria), evaluating the antibiotic susceptibility and plasmid profiles of 184 E. coli isolates, obtained from 228 water samples and 112 diarrhoeal stool specimens (collected from children aged <15 years), using standard methods. The detection rate of E. coli O157 in surface waters was 2.2% and its prevalence in children with diarrhoea was 5.4%. The most active antibiotics were gentamicin, chloramphenicol and fluoroquinolones. Seventy-nine (42.9%) of 184 E. coli isolates were resistant to four or more antibiotics. Multidrug resistance (MDR) was higher amongst aquatic isolates than the clinical isolates. Out of 35 MDR isolates (20 of which were O157 strains), 22 (62.9%) harboured plasmids all of which were no less than 2.1 kb in size. Amongst the 20 E. coli O157 strains, only seven (35.0%) contained multiple plasmids. An aquatic O157 isolate containing two plasmids was resistant to seven drugs, including ampicillin, cefuroxime, ciprofloxacin, cotrimoxazole, nalidixic acid, nitrofurantoin and tetracycline. Loss of plasmid correlated with loss of resistance to antibiotics in cured (mutant) strains selected in tetracycline (50 μg/mL)-nutrient agar plates. Our findings revealed that plasmids were prevalent in both the aquatic and clinical isolates, and suggest that the observed MDR is plasmid-mediated. The occurrence of plasmid-mediated multidrug resistant E. coli O157 in surface waters used as sources for drinking, recreation and fresh produce irrigation heightens public health concern.
Infringo ergo sum: when will software engineering support infringements?

Once upon a time a professor of computing and a father was complaining at a radiology ward. A CD with the X-rays of his son's chest had garbled images. Unfortunately, the CD burning process has been outsourced and, in compliance with e-health security policies, technicians could not see the images on the system. Only doctors could. The nurse had a decision to make: sidestep the father (send him away with empty hands to the pneumology ward) or sidestep the system (give the technician the doctor's password and thus the ability to access all images and not just this one). As a father he was happy of her decision. As a professor, this knowledge was of meager and unsatisfactory kind. Any human decision maker who experienced the need of a local IT infringement in order to achieve her business goals knows that she is offered only the choice between strict compliance (and failure of business goals) or global violation (and failure of security goals). Software engineers do not simply know how to deal with infringements. I believe that a different alternative should be possible. The goal of this paper is to sketch the challenges of such unexplored scientific alternative.
Protease inhibitor-associated dyslipidemia in HIV-infected patients is strongly influenced by the APOA5-1131T->C gene variation.

BACKGROUND Hyperlipidemia associated with the protease inhibitor (PI) component of highly active antiretrovial treatment can lead to accelerated atherosclerosis. The apolipoprotein A-V (APOA5) gene, which affects VLDL production and lipolysis, may play a role in PI-induced hyperlipidemia, particularly in individuals with the APOA5-1131T-->C genotype. METHODS We measured lipoprotein changes in HIV-positive patients (n = 229) who had been followed for 5 years. For statistical analyses, we segregated the patients with respect to PI treatment and APOA5-1131T-->C genotype. RESULTS The frequency of the C allele was 0.08, similar to that in the general population. We found a strong effect of the APOA5-1131T-->C genotype among patients receiving PIs. Carriers of the C allele had consistently increased mean (SD) triglyceride concentrations compared with noncarriers after 1 year [2.11 (1.62) vs 3.71 (4.27) mmol/L; P = 0.009], 2 years [2.48 (2.09) vs 4.02 (4.05) mmol/L, P = 0.050], 3 years [2.32 (1.71) vs 4.13 (4.26) mmol/L; P = 0.013], 4 years [2.90 (2.95) vs 5.35 (7.12) mmol/L; P was not significant], and 5 years [4.25 (5.58) vs 9.23 (9.63) mmol/L; P was not significant]. We observed the same effect on total cholesterol concentrations: after 1 year [4.93 (1.31) vs 5.87 (1.66) mmol/L; P = 0.006], 2 years [5.03 (1.12) vs 6.42 (2.48) mmol/L; P = 0.001], 3 years [5.11 (1.17) vs 6.38 (2.43) mmol/L; P = 0.009], 4 years [5.49 (1.71) vs 6.78 (3.03) mmol/L; P was not significant], and 5 years [5.56 (1.75) vs 7.90 (3.60) mmol/L; P was not significant]. HDL cholesterol showed a progressive reduction, leading to a considerably higher cholesterol/HDL cholesterol ratio after 3 years. CONCLUSION Variability in the APOA5 gene predisposes patients with HIV, particularly those treated with PI, to severe hyperlipidemia.
Research and application of One-class small hypersphere support vector machine for network anomaly detection

In recent years, machine learning technology often used as a recognition method of anomaly in anomaly detection. In this paper we have proposed a One-class small hypersphere support vector machine classifier (OCSHSVM) algorithm, which builds a learning classifier model via both normal and abnormal network traffic. This combination of normal and abnormal traffic for training model gives the better performance and generalization for proposed classifier Experimental results show that high detection rates and low false positive rates are achieves by our proposed approach. We have demonstrate proposed algorithm by using of KDD [1] and NSL-KDD [2] dataset.
Traces d'interactions et processus cognitifs en activité conjointe

La problematique de la comprehension des activites humaines instrumentees par des systemes informatiques se developpe depuis vingt ans. De plus en plus de situations passent par l'utilisation d'artefacts numeriques dont les capacites techniques sont croissantes, mais dont les usages reels sont eloignes des usages attendus. De nombreux travaux s'interessent a l'analyse de ces activites et produisent des resultats tant sur les proprietes des fonctions cognitives humaines que sur des principes de conception et d'evaluation anthropocentres de systemes. Neanmoins, la plupart decompose les processus cognitifs en modules de traitement de l'information, et ne fait que tres peu appel a des elements du contexte de l'activite. Ils ignorent presque toujours les composantes sociales et materielles des interactions, et leur dimension historique. Cet ouvrage tente de prendre en compte ces dimensions des activites humaines instrumentees et a analyser leur importance dans leur deploiement. Il releve des champs de l'informatique (CSCW et IHM) et de la psychologie sociale et cognitive (analyse d'une situation conjointe et inscription dans le paradigme de la cognition situee et distribuee).
Protein classification artificial neural system

A neural network classification method is developed as an alternative approach to the large database search/organization problem. The system, termed Protein Classification Artificial Neural System (ProCANS), has been implemented on a Cray supercomputer for rapid superfamily classification of unknown proteins based on the information content of the neural interconnections. The system employs an n‐gram hashing function that is similar to the k‐tuple method for sequence encoding. A collection of modular back‐propagation networks is used to store the large amount of sequence patterns. The system has been trained and tested with the first 2,148 of the 8,309 entries of the annotated Protein Identification Resource protein sequence database (release 29). The entries included the electron transfer proteins and the six enzyme groups (oxidoreductases, transferases, hydrolases, lyases, isomerases, and ligases), with a total of 620 superfamilies. After a total training time of seven Cray central processing unit (CPU) hours, the system has reached a predictive accuracy of 90%. The classification is fast (i.e., 0.1 Cray CPU second per sequence), as it only involves a forward‐feeding through the networks. The classification time on a full‐scale system embedded with all known superfamilies is estimated to be within 1 CPU second. Although the training time will grow linearly with the number of entries, the classification time is expected to remain low even if there is a 10–100‐fold increase of sequence entries. The neural database, which consists of a set of weight matrices of the networks, together with the ProCANS software, can be ported to other computers and made available to the genome community. The rapid and accurate superfamily classification would be valuable to the organization of protein sequence databases and to the gene recognition in large sequencing projects.
Spatial Representation in Cognitive Science and Film

Levin and Simons (2000) argued that perceptual experience in film and the real world share a deep similarity in that both rely on inferences that visual properties are stable across views. This article argues that the perception and representation of visual space also reveal deep commonalities between film and the real world. The article reviews psychological research on visual space that suggests that we not only attend to similar spatial cues both in film and in nonmediated settings, but also that the rules for combining and selecting among these cues are similar. In exploring these links, it becomes clear that there is a bidirectional relationship between cognitive psychology and film editing that allows each to provide important insights about the other.
Analysis of access control mechanisms for users' check-ins in Location-Based Social Network Systems

Location-Based Social Network Systems (LBSNSs) are becoming increasingly popular. In LBSNSs, users can check in at various places, connect with their friends and share their check-ins (including users' locations and timestamps) with their friends and even the public. However, most LBSNSs pay on more attention to attracting users to join and actively use their systems rather than protecting users' privacy preferences for their check-ins. In this paper, we analyze access control mechanisms for users' check-ins in four of the most popular existing LBSNSs: Facebook Places, Foursquare, Google Latitude and Yelp. We first generalize a model for users' check-ins based on these LBSNSs. Considering users' check-ins as the protection objects, we then generalize an access control policy model for them. We use these two models as criteria to analyze these access control mechanisms for users' check-ins and compare them in these LBSNSs. Additionally, we identify the common vulnerabilities in these access control mechanisms. Understanding the access control mechanisms for users' check-ins and their limitations can help users who care more about their privacy to choose a LBSNS where their location privacy is better protected.
Improving microaneurysm detection in color fundus images by using an optimal combination of preprocessing methods and candidate extractors

In this paper, we present an approach to improve microaneurysm detection in color fundus images. This task is usually realized by candidate extraction, which is followed by a classification step. The proposed method aims to increase the number of true positives in the first phase of the microaneurysm detection process. Thus, we establish a framework for selecting an optimal combination of preprocessing methods and candidate extractors. Our investigation shows that the state-of-the-art candidate extractors provide significantly improved results, when they are optimally combined with preprocessing approaches. We show that this performance can be further increased with an ensemble formed by a globally optimal combination of the preprocessing methods and candidate extractors.
Robust Downlink Precoding in Multiuser MIMO-OFDM Systems with Time-Domain Quantized Feedback

We consider the robust linear precoding (LP) and Tomlinson-Harashima precoding (THP) schemes for multiuser MIMO-OFDM downlink channels with limited feedback. Benefiting from the correlation of spatial channels, the mobile terminal compresses and feeds back the time-domain channel vectors instead of the corresponding frequency-domain vectors to substantially reduce the feedback signalling overhead. A compression and restoration method and a codebook design for channel state information at the transmitter (CSIT) feedback are proposed in the time domain. By treating the partial CSIT as a random quantity, we develop the robust precoders to combat the truncation and quantization errors introduced in the feedback procedure. In comparison with the non-robust designs, both the robust LP and THP have better bit-error rate performance especially in high signal-to-noise ratio region.
Dependence of particle nucleation and growth on high molecular weight gas phase products during ozonolysis of α-pinene

Abstract. We report the first time-dependent measurements of high-molecular-weight (up to 700 amu) gas-phase oxidation products from α-pinene ozonolysis in an aerosol chamber under dry and low-NO x conditions. Measurements of products having mole fractions ranging from 10 −14 to 10 −11 were carried out with a chemical ionization mass spectrometer (the Cluster CIMS). Most products that were correlated with number concentrations of the smallest particles measured (10–20 nm) had molecular weights in the 430–560 amu range. Those products are proposed to be likely responsible for the initial nuclei formation and the early growth of the freshly nucleated particles based on their high molecular weights and chemical identities, both of which suggest low-volatility compounds. Another group of oxidation products in the lower mass range of 140–380 amu was well correlated with particles larger than 20 nm. We postulate that those products contributed to the later growth of particles (i.e., larger than 20 nm in diameter). Although particle nucleation in this study was primarily due to condensation of oxidation products from α-pinene ozonolysis, the involvement of residual sulfuric acid vapor in particle nucleation cannot be totally excluded.
Band Structure of a GaN Photonic Crystal Slab 61 Band Structure Measurements and Calculations of Epitaxially Grown GaN Based Photonic Crystal Slabs with Semipolar Quantum Wells

We report on the large area realization of GaN photonic crystal slabs with semipolar InGaN quantum wells (QWs) using laser interference lithography and selective area metalorganic vapour phase epitaxy (MOVPE). Directional extraction of guided modes was observed in angle-resolved photoluminescence spectroscopy (ARPL), and the photonic crystal slab dispersion relation was measured. A comparison of the observed band structure to theory was made using the finite difference time domain method (FDTD).
Investigation of oscillations in a 6.5-kV, 1-kA SiC diode module

SiC technology is attractive for power devices, as it potentially offers many advantages over traditional Si-based devices. However, many issues still need to be properly addressed in order to become a popular and cost-effective alternative to Si devices. One of these issues are high-frequency oscillations that appear during commutation, which limit the switching speed of the device and can produce undesired EMC problems. This paper analyzes the source of the oscillations that appear during the turn-off transient of a recently developed SiC PiN diode module (6.5 kV, 1 kA). A behavioral model derived from the device characterization was elaborated and verified. Through simulation, the main ringing sources are identified and assessed. The positive effect of an RC snubber circuit for dampening the oscillations is presented and experimentally verified.
Supertagging: Introduction, learning, and application

Supertagging is an approach originally developed by Bangalore and Joshi (1999) to improve the parsing efficiency. In the beginning, the scholars used small training datasets and somewhat na\"ive smoothing techniques to learn the probability distributions of supertags. Since its inception, the applicability of Supertags has been explored for TAG (tree-adjoining grammar) formalism as well as other related yet, different formalisms such as CCG. This article will try to summarize the various chapters, relevant to statistical parsing, from the most recent edited book volume (Bangalore and Joshi, 2010). The chapters were selected so as to blend the learning of supertags, its integration into full-scale parsing, and in semantic parsing.
Modeling " Reality " , Theory and Experiment

One of the most difficult things to convey to students is the fact that when we explain a subject and provide solutions to practical problems, we are always dealing with models that represent through a mathematical formulation the behavior of "real" structures and materials. The difficulties arise from many different causes. In explaining a discipline by tradition a historical path is followed, even names are added to certain problems and their solution. To the eyes of the students these solutions appear to be arbitrary and not well connected among themselves. The students are right because the difficulties arise from the modeling and the underlying mathematics and not from the basic concepts of the discipline. A great deal of attention has been paid to the fundamentals of consolidated disciplines in an effort to make them as more mathematical as possible. However, not in all the cases the effort has yielded the hoped results because in many instances the adopted model gives results that are "good" or "very good" in spite of shaking foundations. Models are assumed to be reliable if they can survive the experimental verification and if they are internally consistent. The internal consistency is related to the mathematical formulation. How is it possible to reach a good balance between a pragmatic point of view, rigor, theory and experiment? One thing is certain, without mathematics and theory it will be very difficult to proceed in the understanding of nature but the ultimate test of a theory is its experimental verification and that "reality" is very complex and only experimental observation can guide us towards to sound models of the "reality". Some example are given of some important fields of solid mechanics, accepted models and actual experimental observations.