Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Modeling of Logical Connectors by Statistical Analysis of Context / Modélisation automatique de connecteurs logiques par analyse statistique du contexte

Dans cet article, nous décrivons un algorithme d’enrichissement de modèle de langue par un modèle de connecteurs logiques. Notre algorithme est capable, en partant de connecteurs amorces et en s’appuyant sur un corpus, de regrouper automatiquement des connecteurs logiques de sens identiques, en fonction du contexte. Ce regroupement peut être ensuite utilisé pour générer des automates à états finis capables d’identifier une articulation logique dans une phrase. À ce titre, il constitue un premier pas en direction de l’analyse automatique de textes argumentatifs. Nous utilisons ce dispositif dans un système de réécriture automatique de phrases, assisté par modèle de langue. In this paper we present an algorithm for the enrichment of the language model by a model of logical connectors. Using seed connectors based on a corpus, our algorithm is capable of grouping context-dependant logical connectors of identical meaning into classes. This categorization of links may then be employed to generate finite state machines (FSMs) capable of identifying logical articulation of a phrase. In this capacity, it constitutes a first step towards an automatic analysis of argumentative texts. We use this device (FSMs), assisted by a language model, to rewrite automatically sentences in a text processing system.
Dependence of HCI mechanism on temperature for 0.18 /spl mu/m technology and beyond

We have studied the temperature impact on the substrate current. For both NMOS and PMOS, the peak substrate current increases with the temperature at low drain bias. An analytical model was proposed to explain this result. More important, the HCI degradation under different temperatures was studied. The NMOS HCI degradation mechanism still follows the lucky electron model, while PMOS HCI degradation is faster at higher temperature for the same peak substrate current. The RO AC HCI test shows little change due to temperature impact. This is because NMOS degrades much faster than PMOS.
Applied Technology Based on NS2 the Research of Transmission of Video Streams in 802.11 Network

This paper analyzes several related parameters of multimedia data flow transmission with applied technology in wireless network environment and establishes simulation model in NS2, In view of the low bandwidth, the high error rate and the high delay of wireless networks, Through the simulation analysis of the different packet error rate, the compression quantization parameter, the length of GOP and packet for image quality based on the PSNR evaluation method respectively, the result of the simulation analysis provides the beneficial reference for the wireless network of more effectively in multimedia data transmission.
A SVM Intrusion Detection Method Based on GPU

To optimize training procedure of IDS based on SVM and reduce time consumption, a SVM intrusion detection method based on GPU is proposed in the study. During the simulation experiments with KDD Cup 1999 data, GPU-based parallel computing model is adopted. Results of the simulation experiments demonstrate that time consumption in the training procedure of IDS is reduced, and performance of IDS is kept as usual.
Stereo matching for large-scale high-resolution satellite images using new tiling technique

Stereo matching has been grabbing the attention of researchers because it plays an important role in computer vision, remote sensing and photogrammetry. Although most methods perform well with small size images, experiments applying them to large-scale data sets under uncontrolled conditions are still lacking. In this paper, we present an empirical study on stereo matching for large-scale high-resolution satellite images. A new method is studied to solve the problem of huge size and memory requirement when dealing with large-scale high resolution satellite images. Integrating the tiling technique with the well-known dynamic programming and coarse-to-fine pyramid scheme as well as using memory wisely, the suggested method can be utilized for huge stereo satellite images. Analyzing 350 points from an image of size of 8192 x 8192, disparity results attain an acceptable accuracy with RMS error of 0.5459. Taking the trade-off between computational aspect and accuracy, our method gives an efficient stereo matching for huge satellite image files.
Explicit solutions to analytical models of cross-layer protocol optimization in wireless sensor networks

The work is based on the interactions among the nodes of a wireless sensor network (WSN) to cooperatively process data from multiple sensors. Quality-of-service (QoS) metrics are associated with the quality of fused information: throughput, delay, packet error rate, etc. A multivariate point process (MVPP) model of discrete random events in WSNs establishes stochastic characteristics of optimal cross-layer protocols. In previous work by the author, discreteevent, cross-layer interactions in the MANET protocol are modeled in very general analytical terms with a set of concatenated design parameters and associated resource levels by multivariate point processes (MVPPs). Characterization of the "best" cross-layer designs for the MANET is formulated by applying the general theory of martingale representations to controlled MVPPs. Performance is described in terms of concatenated protocol parameters and controlled through conditional rates of the MVPPs. Assumptions on WSN characteristics simplify the dynamic programming conditions to yield mathematically tractable descriptions for the optimal routing protocols. Modeling limitations on the determination of closed-form solutions versus iterative explicit solutions for ad hoc WSN controls are presented.
Data-driven indexed hypotheses for distorted shape matching

The problem of identification of multiple flat objects in a cluttered environment is dealt with. The objects become distorted due to occlusion, noise and other spurious effects. Unlike the previous model-based approaches involving exhaustive searching, this paper utilizes a data-driven indexing mechanism for model retrieval. Groups of consecutive segments, called super segments, are used as boundary descriptors. The whole approach is based on attributed string matching. With this technique model library can be modified as per requirement. <<ETX>>
Feature Extraction by QuickReduct Algorithm: Assessment of Migraineurs Neurovascular Pattern

Migraine is a complex disease with neurovascular implications. The accurate assessment of the migraineur's cerebrovascular status can be used to optimize and personalize therapy and ensure a better quality of life. Migraine has been associated to a disregulation in the carbon dioxide concentration, which can be measured by near-infrared spectroscopy (NIRS). In this paper we present a novel and automated strategy for feature extraction from NIRS time and frequency parameters. We built a large dataset by measuring 26 features for each of the 80 subjects we analyzed (51 migraineurs with aura, 14 without aura, and 15 healthy controls). We applied the QuickReduct algorithm (QRA) for the automated selection of the relevant features. Results were compared to the features extracted by the conventional ANOVA analysis. An artificial neural network (ANN) was used to perform classification in both cases (QRA and ANOVA). QRA returned 9 variables, ANOVA only 3. Only one feature was common to the two techniques: the increase of oxygen during a voluntary breath-holding. QRA coupled to ANN reached a classification accuracy of 97.5%, whereas ANOVA plus ANN gave about 75%. We plan to adopt this automated feature extraction strategy for the reduction of the dataset dimension in vascular characterization of migraineurs. The selection of the most important features find its importance in the analysis of complex systems and in monitoring protocols, where reduction ensures light computational burden and speeds up the time required for the patients assessment
IMPACT OF LITERACY ON ORAL LANGUAGE PROCESSING: IMPLICATIONS FOR SECOND LANGUAGE ACQUISITION RESEARCH

In this chapter we describe a body of research on oral language processing that we believe has important implications for applied linguistics. This research documents the effects of literacy on human oral language processing. Studies in this area show that illiterate adults significantly differ from literate adults in their performance of oral processing tasks that require an awareness of linguistic segments. These studies provide evidence that the acquisition of the ability to decode an alphabetic script changes the way in which the individual processes oral language in certain kinds of cognitive tasks. At the same time, based on research establishing a clear reciprocal relationship between oral language processing skills and literacy, researchers on first language acquisition are extending the scope of their study to explore the way in which an individual's language competence is altered and extended by literacy itself. In this discussion, we describe the broad outlines of this new body of research and scholarship, and explore the implications for our understanding of second-language acquisition, and particularly for theories and research that explore the impact of “noticing” on SLA. We conclude by stressing the social and theoretical importance of including clearly-identified illiterate adults in our growing database on second language acquisition research.
Neural network model of dynamic form perception: implications of retinal persistence and extraretinal sharpening for the perception of moving boundaries

While temporal properties of the visual system have been the subject of extensive research in psychology, many computational theories are based on steady-state behavior. For example, Marr's theory requires early measurements to be instantaneous. Furthermore, optimizational type approaches to perception are designed around properties of equilibria, and very little attention is devoted to the relevance of trajectories to perceptual experience. Electrophysiological findings however show that visual neurons such as retinal ganglion cells possess strong transient components. Therefore, a fundamental issue in perceptual sciences is the understanding of the relevance of these transient components to visual perception. This study claims that adaptive, nonmonotonic transient properties of early visual units are crucial components in visual processing. An extra-retinal feedback on-center off-surround anatomy is proposed to sharpen the 'blurred output' from the retinal level. Based on theoretical studies of pattern transformation properties of recurrent networks for sustained inputs we propose a global model (including retina and extra-retinal areas) of visual processing where a reset from transient ganglion cells of the retina prevent smearing for moving images. The model provides a theoretical link between hyperacuity (achieved by denser extra-retinal packing and nonlinear contrast enhancement) and visual masking (resulting from inter-layer and intra-channel inhibition mechanisms).
A Comparison of Measured and Calculated Speech Temporal Parameters Relevant to Speech Activity Detection

This paper deals with the measurement and calculation of various speech temporal parameters of interest in an environment where speech activity detection is employed. In particular it is shown that, based on either a measurement or model of the probability density function (pdf) for silence durations for the case of zero talkspurt "hangover" or "fill-in," that the following temporal parameters can be computed for any value of hangover or fill-in: the mean (and pdf) for silence durations, the mean talkspurt duration, the mean talkspurt rate, and the speech activity. Directly measured values of these parameters and those computed from both measured and fitted versions of the pdf for silence durations are compared and are shown to be in reasonable agreement. The illustrated results are based on measurements of about two minutes of taped male monolog source speech. However, the approach to calculating the above parameters is general in the sense that it can be applied to any measured or modeled pdf for silence durations. The significance of this work lies in the important role that talkspurt hangover plays, for example, in minimizing speech detector induced back-end clipping of talkspurts, reducing exposure to the variable talkspurt delay impairment, and in determining signaling overhead and resource occupancy in various speech interpolation, packet voice, and integrated voice/data systems.
Compensation of frequency-selective I/Q imbalances in wideband receivers: models and algorithms

To achieve satisfactory performance in analog I/Q (inphase/quadrature) processing-based wireless receivers, the matching of amplitudes and phases of the I and Q branches becomes vital. In practice, there is always some imbalance and the image attenuation produced by the analog processing remains finite. Especially in wideband receivers, where the existence of strong image band signals makes the attenuation requirements extremely stringent, analog processing is incapable of providing adequate image rejection. We derive a general frequency-dependent signal model for an imbalanced analog front-end and present two alternative methods utilizing digital processing to enhance the analog front-end image rejection. Based on the obtained results, the proposed methods provide adequate image signal rejection with very few assumptions, even in the difficult cases of frequency-selective and/or time-varying imbalances.
Design of a Key Scheduler for Supporting the Parallel Encryption and Decryption Processes of HIGHT

HIGHT is an 64-bit block cipher, which is suitable for low power and ultra-light implementation that are used in the network that needs the consideration of security aspects. This paper presents a parallel key scheduler that generates the whitening keys and subkeys simultaneously for both encryption and decryption processes. We construct the reverse LFSR and key generation blocks to generate the keys for decryption process. Then, the new key scheduler is made by sharing the common logics for encryption and decryption processes to minimize the increase in hardware complexity. From the simulation results, the logic size is increased 1.31 times compared to the conventional HIGHT. However, the performance of HIGHT including the proposed key scheduler can be increased by two times compared to the conventional counterpart
Validating SAR interferometry applications by using EMSL

Interferometric fringes can be formed from couples of complex SAR images measured,with the a radar system positioned at two closely spaced looking angles. Indoor SAR imaging presents the advantage, over airborne and spaceborne SAR, of using very well defined geometries which gives the possibility to exploit it for validating SAR focusing algorithms and their interferometric applications. Furthermore, indoor SAR measurements can be conducted with frequency bandwidths not available yet to present airborne and spaceborne SAR systems. <<ETX>>
On the power of languages for manipulation of complex objects

Antimicrobial compositions are provided wherein there is obtained an enhancement of the activity of an antimicrobial agent exemplified by quaternary ammonium compounds, bisdiguanides, anti-fungal agents, phenols, hydroxydiphenyls, carbanilides, salicylanilides, organo-metallic antiseptics, antibiotics, halogens, organic halogen derivatives and iodophores derived from nonionic surface active agents and from polyvinylpyrrolidone by combining the antimicrobial agent with an effective amount of a potentiator. The potentiator is an alcohol or phenol derivative selected from the group consisting of a aliphatic straight or branched chain primary, secondary and tertiary monohydric alcohols wherein the straight chain alcohols have from about 5 to about 10 carbon atoms; and the branched chain alcohols have up to about 17 carbon atoms, their longest straight chain of carbon to carbon bonds having from about 5 to about 10 carbon atoms; (b) a primary, secondary tertiary cyclohexylalkanol or alkylcyclohexylalkanol where the alkanol is as more fully defined hereinafter; (c) a primary, secondary or tertiary phenylalkanol, halophenylalkanol or C1 to C3 alkylphenylalkanol where the alkanol has from about 3 to about 9 carbon atoms; and (d) a cyclohexyl phenol which may have a substituent on the phenyl ring selected from the group consisting of C1 to C3 alkyl and alkoxy, hydroxy, halo, amino and alkyl and dialkyl amino-substituents. Also provided are topically active compositions wherein topical activity of a medicament is enhanced by combining the medicament with an effective amount of a potentiator as defined in (a), (b) or (c) above. The compositions comprising an antimicrobial agent and a potentiating agent in a suitable carrier are useful for killing susceptible organisms on various surfaces. The novel compositions find special applications as surgical scrub solutions, and for use in dressing topical wounds where the presence of blood and wound exudate would otherwise inhibit the action of the antimicrobial agent if it were to be used alone. The topical compositions of the invention find special application as topical anesthetics, cell regulatory agents, antimicrobials, anti-inflammatory compositions, and the like.
Data Structures and Algorithms for Data-Parallel Computing in a Managed Runtime

Keywords: parallel programming ; data structures ; data-parallelism ; parallelization ; concatenation ; scheduling ; atomic snapshots ; concurrent data structures ; persistent data structures ; work-stealing ; linearizability ; lock-freedom These Ecole polytechnique federale de Lausanne EPFL, n° 6264 (2014)Programme doctoral Informatique, Communications et InformationFaculte informatique et communicationsInstitut d'informatique fondamentaleLaboratoire de methodes de programmation 1Jury: Prof. O.N. A. Svensson (president) ; Prof. M. Odersky (directeur) ; Prof. D.S. Lea, Prof. V. Kuncak, Prof. E. Meijer (rapporteurs) Public defense: 2014-9-1 Reference doi:10.5075/epfl-thesis-6264Print copy in library catalog Record created on 2014-08-25, modified on 2017-05-12
7月 いじめの社会問題化 (2012年の北海道)

В соответствии с пунктом 5.2. 7 Положения о Министерстве образования и науки Российской Федерации, утвержденного постановлением Правительства Российской Федерации от 15 мая 2010 г. N 337 (Собрание законодательства Российской Федерации, 2010, N 21, ст. 2603; N 26, ст. 3350; 2011, N 6, ст. 888; N 14, ст. 1935; N 28, ст. 4214; N 37, ст. 5257; N 47, ст. 6650, ст. 6662; 2012, N 7, ст. 861, ст. 868; N 14, ст. 1627; N 15, ст. 1796), пунктом 7 Правил разработки и утверждения федеральных государственных образовательных стандартов, утвержденных постановлением Правительства Российской Федерации от 24 февраля 2009 г. N 142 (Собрание законодательства Российской Федерации, 2009, N 9, ст. 1110), приказываю: Утвердить прилагаемый федеральный государственный образовательный стандарт среднего (полного) общего образования и ввести его в действие со дня вступления в силу настоящего приказа.
Architecting Publish/Subscribe-Based Middleware for Wireless Sensor Networks

Middleware for wireless sensor networks (WSNs) can help bridge the gap and remove impediments. Publish/Subscribe (P/S) is an asynchronous communication paradigm that supports many-to-many interactions between a set of clients. P/S paradigm is a suitable paradigm for WSNs middleware. This paper designs PSWSN, a WSNs middleware, whose architecture is composed of service management, P/S support and access management. Service management is an information publishing platform based on B/S mode, its main function is to abstract the various business functions into services. P/S support in PSWSN is a core and supports publishing and matching services. Access management is employed so that WSNs can be abstracted and accessed as logical rather than individual physical entities.
Simple SNR estimation methods for QPSK modulated short bursts

An accurate signal-to-noise ratio (SNR) measurement is essential for cellular and satellite communication receivers for various purposes, including the demodulation algorithm adaptation to the time-varying channel conditions. In this paper, computationally simple SNR estimation methods, called the error vector magnitude (EVM) method and the minimum mean-square error estimation (MMSE) method are proposed. Analytic derivations as well as simulation results are presented to demonstrate the performance of the proposed schemes.
Short-term Electric Load Forecasting Based on Wavelet Transform and GMDH

The group method of data handling (GMDH) algorithm has proven to be a powerful and effective way to extract rules or polynomials from an electric load pattern. However, because it is nonstationary, the load pattern needs to be decomposed using a discrete wavelet transform. In addition, if a load pattern has a complicated curve pattern, GMDH should use a higher polynomial, which requires complex computing and consumes a lot of time. This paper suggests a method for short-term electric load forecasting that uses a wavelet transform and a GMDH algorithm. Case studies with the proposed algorithm were carried out for one-day-ahead forecasting of hourly electric loads using data during the years 2008-2011. To prove the effectiveness of our proposed approach, the results were evaluated and compared with those obtained by Holt-Winters method and artificial neural network. Our suggested method resulted in better performance than either comparison group.
Blind separation of binary sources with less sensors than sources

Blind separation of unknown sources from their mixtures is currently a timely research topic in statistical signal processing and unsupervised neural learning. Several source separation algorithms have been presented where it is assumed that there are at least as many sensors as sources. In this paper, a practical algorithm is proposed for separating binary sources from less sensors than sources. The algorithm uses constrained competitive learning in the adaptation phase and the actual separation is achieved by simply selecting the best matching unit. The algorithm appears to be reasonably robust against small additive noise.
A New Intrusion Detection Method Based on Rough Sets for Network Security

In this paper, we introduce a new intrusion detection method based on rough sets for network. The first step consists of feature selection which is based on rough set theory. The next phase is clustering by using Fuzzy C-Means. Rough set theory is an efficient tool for further reducing redundancy. Fuzzy C-Means allows objects which are belong to several clusters simultaneously, with different degrees of membership. To evaluate the performance of the introduced approaches, we applied them to the international Knowledge Discovery and Data mining intrusion detection dataset. Experimental results illustrate that our algorithm is accurate models for handling complex attack patterns in large network.
Research and Design of The Firewall Penetration Technology Serving to Informati on Sharing Systems

In the current information sharing systems, there is a problem of firewall penetration. As for this problem and based on the existing TCP and UDP penetration schemes, we analyze all kinds of possible transmission environments in practical applications, and then present a technique of UDP coordinating with TCP to penetrate firewalls. Finally, we present the realization of this method: a network switch --XIPSwitch, which is independent from various applications. The realization method can further solve the firewall penetration problem of the internal terminals in the existing information sharing systems.