Miracle-dz/UniFAR-FTUs huggingface dataset:
Contribution à la modélisation et à l’optimisation de systèmes énergétiques multi-sources et multi-charges

La demande energetique mondiale continue d’augmenter. Les prix des energies fossiles sont instables et incertains. La liberalisation du marche electrique et une conscience environnementale des acteurs mondiaux sont des leviers au developpement des energies renouvelables. Ces dernieres se developpent a un rythme rapide dans le monde. Elles ont atteint une maturite technique qui leur permet de devenir un segment important de l’industrie de l’energie. Leur insertion dans le mix energetique pose de nouveaux defis par rapport aux sources d'energie traditionnelles. Avec un potentiel abondant encore sous-exploite, le photovoltaique et l'energie eolienne sont avantageux sur le plan economique et environnemental. Cependant, leur caractere intermittent diminue leur efficacite energetique lorsqu’elles sont exploitees individuellement. L'utilisation de systemes hybrides (multi-sources) combinant ces sources d'energie renouvelables, le reseau de distribution national (reseau electrique historique) et les systemes de stockage classiques, est generalement consideree par tous comme solution d’avenir, a la fois efficiente et fiable. Il est alors necessaire de repenser la structure des reseaux electriques et des marches de l’energie, ainsi que des changements dans les methodes de gestion de reseau. Dans ce contexte, l’apport envisage avec ce travail de these est de contribuer a la modelisation et l’optimisation de systemes multi-sources multi-charges pour alimenter aussi bien des sites isoles « energie de proximite » (campus, village) que des sites etendus tels que des regions francaises a travers leur interconnexion « pooling ». Differents scenarii de gestion et differentes configurations des systemes sont modelises, testes et compares pour analyser l’efficacite et la robustesse de chaque cas de figure. Une analyse technico-economique complete est realisee, dans le but d’etudier la faisabilite de chaque systeme. Pour demontrer la validation de ces modeles, des etudes ont ete realisees sur un campus Universitaire Francais, un micro-reseau au Mali et trois regions Francaises. Ces dernieres ont fait l’objet d’application a un modele original d’interconnexion base sur les reseaux de Petri pour l’aide a la decision en termes de configurations du reseau et le controle des flux d’energie echanges entre des territoires producteurs-consommateurs interconnectes sans systeme de stockage
Nambu monopoles interacting with lattice defects in a two-dimensional artificial square spin ice

The interactions between an excitation (similar to a pair of Nambu monopoles connected by their associated string) and a lattice defect are studied in an artificial two-dimensional square spin ice. This is done by considering a square array of islands containing only one island different from all others. This difference is incorporated in the magnetic moment (spin) of the ``imperfect'' island and several cases are studied, including the special situation in which this distinct spin is zero (vacancy). We show that the two extreme points of a defective island behave like two opposite magnetic charges. Then, the effective interaction between a pair of Nambu monopoles with the defective island is a problem involving four magnetic charges (two pairs of opposite poles) and a string. We also sketch the configuration of the field lines of these four charges to confirm this picture. The influence of the string on this interaction decays rapidly with the string distance from the defect.
Application of radio control cars as intelligent unmanned ground vehicles with collaborative and independent behavior

Simple radio control cars commonly sold as toys can provide a viable starting platform for the development of low-cost intelligent Unmanned Ground Vehicles (UGVs) for the study of robot collectives. In a collaborative effort, Sandia National Labs and New Mexico Tech have successfully demonstrated proof-of-concept by utilizing low-cost radio control cars manufactured by Nikko. Initial tests have involved using a small number (two to ten) of these UGVs to successfully demonstrate both collaborative and independent behavior simultaneously. In the tests individuals share their locations with the collective to cover an area, thus demonstrating collaborative behavior. Independent behavior is demonstrated as each member of the collective maintains a desired compass heading while simultaneously avoiding obstacles in its path. These UGVs are powered by high-capacity rechargeable batteries and equipped with a custom-designed microcontroller board with a stackable modular interface and wireless communication. The initial modular sensor configuration includes a digital compass and GPS unit for navigation as well as ultrasonic sensors for obstacle avoidance. This paper describes the design and operations of these UGVs, their possible uses, and the advantages of using a radio control car platform as a low-cost starting point for the development of intelligent UGV collectives.
Adaptive Data Propagation for Diverse Sensory Mobility

Motivated by emerging applications, we consider sensor networks where the sensors themselves (not just the sinks) are mobile. Furthermore, we focus on mobility scenarios characterized by heterogeneous, highly changing mobility roles in the network. To capture these high dynamics of diverse sensory motion we propose a novel network parameter, the mobility level, which, although simple and local, quite accurately takes into account both the spatial and speed characteristics of motion. We then propose adaptive data dissemination protocols that use the mobility level estimation to optimize performance, by basically exploiting high mobility (redundant message ferrying) as a cost-effective replacement of flooding, e.g. the sensors tend to dynamically propagate less data in the presence of high mobility, while nodes of high mobility are favored for moving data around. These dissemination schemes are enhanced by a distance-sensitive probabilistic message flooding inhibition mechanism that further reduces communication cost, especially for fast nodes of high mobility level, and as distance to data destination decreases. Our simulation findings demonstrate significant performance gains of our protocols compared to non-adaptive protocols, i.e. adaptation increases the success rate and reduces latency (even by 15%) while at the same time significantly reducing energy dissipation (in most cases by even 40%). Also, our adaptive schemes achieve significantly higher message delivery ratio and satisfactory energy-latency trade-offs when compared to flooding when sensor nodes have limited message queues.
CATTAGAT – Web Server for Primer Specificity Scan

1 Department of Computer Science, Faculty of Engineering, University of Iceland, IS107 Reykjavik, Iceland. 2 Iceland Genomics Corp., Snorrabraut 60, IS-101 Reykjavik, Iceland. 3 Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Iceland, IS-101 Reykjavik, Iceland. 4 BioCule, IS-101 Reykjavik, Iceland. 5 Department of Genetics and Molecular Medicine, Landspitali-University Hospital, IS-101 Reykjavik, Iceland.
Applying different classification techniques in reciprocal job recommender system for considering job candidate preferences

In this paper, a reciprocal job recommendation system, CCRS (Classification - Candidate Reciprocal Recommendation), is proposed. With this proposed system, offering job advertisements in a sequence for candidates that they can get feedback reciprocally by using the user's profile, interaction and preference information is aimed all together. An approach has been used based on the preference information of the candidates to determine the jobs' order in the proposed list and the success of different classification methods has been compared to estimate the feedback rate of the advertisements for the target candidate. CCRS also addresses the cold start problem of new candidates joining the site by providing recommendations based on their profiles. The performance of the proposed method was evaluated by using various performance measurements on an actual data set received from an online recruiting website. Evaluation results show that the proposed method outperforms the compared methods for the top 10 ranked recommendations.
Measurement Analysis of Cell Stream in ATM Network Integrating CATV and Internet

The project of interconnecting CATV in Hyogo Prefecture, Japan has started since March, 1998. In this project, there are three CATV companies in Hanshin area; Kobe, Nishinomiya and Amagasaki. An ATM switch is equipped in each company and these CATVs are connected serially in the above order. Each company provides the video service to the rest of companies using the MPEG2 over ATM. In the service area of each CATV, subscribers are able to access the Internet using cable modem. In our testbed network, cells with two types of requirement for QoS are multiplexed; cells for MPEG2 which require the real-time transmission and those for Internet packets which are much more sensitive for the cell loss ratio. Recently, it has been shown that the tra c such as Ethernet LAN, WAN, and ATM network has the statistical characteristics of self-similarity and long-range dependency (LRD). In general, the tra c with LRD degrades the network performance and hence it is important to capture the tra c characteristics in terms of LRD for investigating the performance measures such as cell loss probability, transmission delay, and jitter process. In this paper, we investigate the characteristics of cell stream from the point of view of self-similarity and estimate the Hurst parameters under the various situations on our experimental network. Our results show that if there exists self-similarity in the ATM network integrating CATV and Internet, cells for Internet play a crucial role for the self-similar nature of the network.
An adaptive security framework with extensible computational complexity for cipher systems

Algebraic cryptanalysis, uses a range of algebraic tools and techniques to assess the security of cryptosystems, which are essential for trusted communications over open networks. Recent trends in algebraic cryptanalysis tend to use Modular Addition 2n over logic Exclusive-OR as a mixing operator to guard against security threats. We propose a newly designed framework for Modular Addition over field GF(2) satisfying the algebraic properties of regular Modular Addition 2n albeit with cumulative security enhancements and increased complexity to address these challenges. Nevertheless, it has been observed that the complexity of Modular Addition can be drastically decreased with the appropriate formulation of polynomial equations and probabilistic conditions. In this article we propose a new extended design framework for advanced Modular Addition and it is characterized by user-specified extendable security which does not impose additional changes in existing layout of ciphers including both stream and block ciphers. This framework can be rapidly scaled to use-specific requirements which boosts the algebraic degree of the overall structure. This, in turn it thwarts the probabilistic conditions by retaining the original hardware complexity sans critical modifications of Modular Addition 2n.
Economic diversification in GCC countries: past record and future trends

Employing an empirical and comparative approach, this research paper analyses the past record and future trends of economic diversification efforts in the six Gulf Cooperation Council (GCC) countries. Applying the methodology of content analysis, possible future diversification trends are studied from current development plans and national visions published by the GCC governments. The past record of diversification has yielded only meagre results. Current development plans point unanimously to diversification as the means to secure the stability and the sustainability of income levels in the future. Even though the states continue to lead the economies, diversification entails a reinvigoration of the private sector and as such necessitates the implementation of broader reforms. The paper, however, questions the likelihood of diversification plans being translated into action. There are a number of structural barriers to diversification, which relate to the growth scenarios for the world economy, the duplication of economic activities among the GCC states, and, not least, the sizable barriers to interregional trade. Furthermore, the policy response to pre-empt the Arab Spring uprising indicates that these regimes easily give up their well-argued and planned policies when under pressure and fall back on established ways of doing business, namely through patronage and the predominant role of the public sector. Hence, the prospect of diversifying economies through politically difficult economic reforms has suffered a significant setback. This conclusion, however, does not rule out a piecemeal and ad hoc implementation of the diversification strategies in the future.
On 802.11 Access Point Locatability and Named Entity Recognition in Service Set Identifiers

The 802.11 active service discovery mechanism requires the transmission of various attributes in a plain text. These attributes can be collected using passive monitoring and can be used to enumerate the preferred network list (PNL) of client devices. In this paper, we focus on the information that can be obtained using the service set identifiers (SSIDs) that make up the PNL. First, we describe a simple model based on a wireless access point geolocation technique to gauge the potential device locatability using data available on WiGLE.net. Second, we look at additional information that can be extracted from the SSID strings. Our hypothesis is that the entities of potential interest, such as locations and personal names contained within SSIDs, can be recognized in an automated fashion. Using two freely available pretrained named entity recognizers, we were able to identify up to 49% of SSIDs as possibly carrying entities of interest based on multiple data sets. We also show that extracted attributes can be used as an inference basis for additional inference attacks, which presents further opportunities in forensic and intelligence contexts.
Overcoming the limitations of the MARTINI force field in Molecular Dynamics simulations of polysaccharides

Polysaccharides (carbohydrates) are key regulators of a large number of cell biological processes. However, precise biochemical or genetic manipulation of these often complex structures is laborious and hampers experimental structure-function studies. Molecular Dynamics (MD) simulations provide a valuable alternative tool to generate and test hypotheses on saccharide function. Yet, currently used MD force fields often overestimate the aggregation propensity of polysaccharides, affecting the usability of those simulations. Here we tested MARTINI, a popular coarse-grained (CG) force field for biological macromolecules, for its ability to accurately represent molecular forces between saccharides. To this end, we calculated a thermodynamic solution property, the second virial coefficient of the osmotic pressure ($B_{22}$). Comparison with light scattering experiments revealed a non-physical aggregation of a prototypical polysaccharide in MARTINI, pointing at an imbalance of the non-bonded solute-solute, solute-water, and water-water interactions. This finding also applies to smaller oligosaccharides which were all found to aggregate in simulations even at moderate concentrations, well below their solubility limit. Finally, we explored the influence of the Lennard-Jones (LJ) interaction between saccharide molecules and propose a simple scaling of the LJ interaction strength that makes MARTINI more reliable for the simulation of saccharides.
Group support system and explanatory feedback: An experimental study of mitigating halo effect

Comprehensive assessment potentially leads to halo effect that will affect accuracy of auditors’ decision-making process. Biased initial audit decision will potentially influence final audit decision. It is there-fore necessary to mitigate halo effect that is the consequence of auditors’ good impression on clients’ initial condition. This re-search aims to empirically show that halo effect can be mitigated by explanatory feedback and Group Support System (GSS). The researchers experimentally mani-pulate explanatory feedback and GSS using online web-site. The subjects are stu-dents who have already taken auditing courses. The results show that: 1) explanato-ry feedback can mitigate halo effect so that audit decision will be more accurate 2) GSS can also mitigate halo effect 3) explanatory feedback and GSS are the best me-thods to mitigate halo effect.
DWI denoising method based on BEMD and adaptive wiener filter

Diffusion weighted image (DWI), based on which a diffusion tensor image (DTI) is calculated, is affected by several artifacts and noise that complicate the analysis and interpretation of DTI. As DWI is multi-boundary in nature, to get accurate boundary signals of DWI is particularly important. A new method combing bidimensional empirical mode decomposition (BEMD) with adaptive wiener filter is proposed. Through the BEMD method the degraded image is decomposed to detail part and residual part. The detail part of the image contains the boundary signal and the noise of the degraded image, and residual part describe the image tendency. Then, the adaptive wiener filter is applied to remove the noise in the detail part of the DWI and the residual part is handled. At last, the denoised detail image and residual are combined to form the denoised DWI. The method is performed on the real DWI data. Experiment results positively show that this method removed noise effectively and kept the boundary of DWI successfully.
Game design strategies for collectivist persuasion

A fundamental feature of serious games is persuasion, an attempt to influence behaviors, feelings, or thoughts. Much of the existing research on serious games and, more generally, on persuasive technology (PT), does not address the important links between persuasion and culture. It has tended to originate from Western, individualist cultures, and has focused on how to design for these audiences. In this paper, we describe the design of one of two versions of a serious game we developed about quitting smoking titled Smoke? which is targeted at collectivist players. We show how the design was informed by persuasive strategies we identified from the cross-cultural psychology literature, intended for use in games for players of collectivist cultures: HARMONY, GROUP OPINION, MONITORING, DISESTABLISHING, and TEAM PERFORMANCE. We then discuss the results of a quantitative investigation of the effects of both game versions on both individualist and collectivist players.
The Depth Estimate of Interesting Points from Monocular Vision

We present a novel method to estimate the depth and the spatial locations of points in the three-dimensional scene from monocular vision. First, we take photos when the camera is moving forward and obtain a sequence of photos of a scene. From this sequence of photos, we choose two photos. From these two photos, we can estimate the spatial position of points in the scene. Second, let a corner detector detect the corners on the latter image of the two ordered photos. Third, by using a novel method we can search the points on the former photo which match the corners on the latter image. Fourth, calculate the depths and the spatial locations of the points in the scene whose projections are the corners, by using a formula this paper will present. Compared with previous techniques estimating the depths or positions, our approach does not need any geometric clues, and the required conditions are that take photos while moving to the exactly forward direction. In addition, experiments are carried out to validate each proposed method and algorithm, and the experimental results demonstrate the efficiency of every proposed method and algorithm.
Improving performance of a mobile personalized recommendation engine using multithreading

Popularity of social networking services (SNS) and location-based SNS (LBSNS) have an influence on lifestyles of many people. Furthermore, the advancement of mobile technology enables people to share their interests and lifestyles to their friends conveniently. These factors cause the Internet to become massive personal information resource. A mobile personalized recommendation (MPR) engine plays an important role in offering solely essential information to prevent information overload for the users. Unfortunately, processing time of traditional MPR engine is high. This paper proposes an approach to improve performance of MPR using multithread programming (MP). The experimental results indicate that the multithread programming (MP) could deliver higher performance than sequential programming (SP), especially speedup between 5 and 7 times approximately.
Consensus Clustering + Meta Clustering = Multiple Consensus Clustering

Consensus clustering and meta clustering are two important extensions of the classical clustering problem. Given a set of input clusterings of a given dataset, consensus clustering aims to find a single final clustering which is a better fit in some sense than the existing clusterings, and meta clustering aims to group similar input clusterings together so that users only need to examine a small number of different clusterings. In this paper, we present a new approach, MCC (stands for multiple consensus clustering), to explore multiple clustering views of a given dataset from the input clusterings by combining consensus clustering and meta clustering. In particular, given a set of input clusterings of a particular data set, MCC employs meta clustering to cluster the input clusterings and then uses consensus clustering to generate a consensus for each cluster of the input clusterings. Extensive experimental results on 11 real world data sets demonstrate the effectiveness of our proposed method.
Low latency and tight resources viseme recognition from speech using an artificial neural network

We present a speech driven real-time viseme recognition system based on Artificial Neural Network (ANN). A Multi-Layer Perceptron (MLP) is used to provide a light and responsive framework, adapted to the final application (i.e., the animation of the lips of an avatar on multi-task platforms with embedded resources and latency constraints). Several improvements of this system are studied such as data selection, network size, training set size, or choice of the best acoustic unit to recognize. All variants are compared to a baseline system, and the combined improvements achieve a recognition rate of 64.3% for a set of 18 visemes and 70.8% for 9 visemes. We then propose a tradeoff system between the recognition performance, the resource requirements and the latency constraints. A scalable method is also described.