Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact des projets de coopération décentralisée sur la réduction des inégalités d'accès aux services sociaux de base : Cas des coopérations décentralisées franco-burkinabés et francobéninoises

Des premiers jumelages a la cooperation decentralisee, les collectivites territoriales francaises ont vu evoluer leur objet et leurs pratiques, mais l’acces aux services sociaux de base demeure l’une de leurs principales thematiques d’intervention dans les territoires partenaires d’Afrique subsaharienne. Le transfert de cette competence a leurs communes partenaires du Sud dans le cadre de la mise en œuvre du processus de decentralisation, ont vu celles-ci faire face aux grandes attentes des habitants de leur territoire qui esperent une amelioration de leurs conditions de vie. La cooperation decentralisee a alors vu se reporter sur elle ces attentes et est de plus en plus percue comme un atout majeur dans la lutte contre la pauvrete et la reduction des inegalites d’acces aux services sociaux de base dans les territoires partenaires du Sud.Afin d’evaluer l’impact de cette forme de partenariat sur la reduction des inegalites d’acces a l’education, a l’eau potable et a la sante, deux methodes d’evaluation ont ete combinees : la methode quasi experimentale (ou de la double difference) et l’appariement.La mise en œuvre de cette methode a travers la comparaison et la mesure de la difference entre huit communes burkinabes et beninoises en cooperation decentralisee avec des collectivites territoriales francaises, et huit communes appariees n’ayant jamais eu des partenariats de cooperation decentralisee, nous a permis de mesurer un impact inegal et diversifie de la cooperation decentralisee. Cette methode d’evaluation innovante de la cooperation decentralisee de par la specificite de cette forme d’intervention qui en limite l’application, nous a egalement permis d’etablir un lien entre l’impact de celle-ci et la diversite des pratiques et des acteurs impliques. La cooperation decentralisee est en pleine evolution et encore dans un processus de construction, mais elle peut cependant constituer une forme d’intervention efficace dans la lutte contre la pauvrete et la reduction des inegalites.
Orchestrating Economic, Socio-Technical and Technical Validation Using Visual Modelling

The paper presents an approach for orchestrating validation of project results from different perspectives by using visual modelling techniques. The context for the paper is the FP6 project MAPPER. Validation in MAPPER covers economic, socio-technical and technical viewpoints. The economic viewpoint mainly focuses on business value and coherence with business drivers like reduced lifecycle time or increased flexibility. Sustainable collaboration for joint value creation of various units in a networked organisation is the main aspect of the socio-technical viewpoint. From a technical point of view, usability of IT-infrastructure and services is a key aspect. The MAPPER Validation Framework includes and orchestrates approaches and methodologies from these three viewpoints and defines the validation actions to be performed. The main contributions of the paper to research in the field are (1) the structure of the MAPPER Validation Framework integrating different validation perspectives, (2) experiences from using a visual modelling environment for framework development and (3) experiences from orchestrating different validation perspectives.
Myoclonies et épilepsies chez l'enfant

The possible associations of myoclonic phenomena, progressive or non progressive encephalopathies and epileptic phenomena are reviewed with special emphasis on childhood. This leads to the following five groups of conditions: (1) myoclonus without encephalopathy and without epilepsy; (2) encephalopathies with non-epileptic myoclonus; (3) progressive encephalopathies with myoclonic seizures or epileptic syndromes (Progressive myoclonus epilepsies); (4) epileptic encephalopathies with myoclonic seizures; (5) myoclonic epilepsies. In the first group, which also includes physiological myoclonus, a more thorough description of "benign sleep myoclonus of newborn" and "benign myoclonus of early infancy" is given. Characteristic of group 2 are "Kinsbourne syndrome" and certain types of "Hyperekplexia" which pose interesting differential diagnosis problems with stimulus-sensitive epilepsies. In group 3, the concept of progressive encephalopathies is stressed, meaning that "Progressive Myoclonus Epilepsies" are always in fact progressive encephalopathies presenting with myoclonic types of seizures or epileptic syndromes among other neurologic and psychologic signs and symptoms. Major and rare causes are reviewed. The term major is applied to typical features or to frequency, whereas rare causes include not only those what are rarely seen, but also some myoclonic variants of diseases which usually have different symptoms. The fourth group refers to severe epilepsies, mainly in infancy and childhood, which lead to mental retardation irrespective of their cause. The assumption is that diffuse and persistent epileptic activity may interfere with normal development of the higher cerebral functions. "West syndrome" and "Lennox-Gastaut syndrome" are the more representative examples and may present with myoclonic type of seizures, but they are not dealt with in detail here. Group 5 comprises true myoclonic epilepsies, differentiating syndromes recognized as idiopathic, such as "benign myoclonic epilepsy of infancy" and "juvenile myoclonic epilepsy", from those which are cryptogenic and carry a more cautious prognosis--i.e.: "cryptogenic myoclonic and myoclono-astatic epilepsies" and "Severe myoclonic epilepsy of infancy". Finally other epileptic syndromes usually not considered as myoclonic epilepsies, but presenting sometimes myoclonic seizures, are mentioned.
On the Applicability of Rules to Automate Data Warehouse Logical Design

Data Warehouse logical design involves the definition of structures that enable an efficient access to information. The designer builds relational or multidimensional structures taking into account a conceptual schema representing the information requirements, the source databases, and non functional (mainly performance) requirements. Existing work in this area has mainly focused into aspects like data models, data structures specifically designed for DWs, and criteria for defining table partitions and indexes. This paper proposes a step forward on the automation of DW relational design through a rule-based mechanism, which automatically generates the DW schema by applying existing DW design knowledge. The proposed rules embed design strategies which are triggered by conditions on requirements and source databases, and perform the schema generation through the application of predefined DW design oriented transformations.
Clustering simulated Event-Related Potentials based on similarity of centroids

Event-Related Potentials (ERPs) are electrical signals produced by the brain in response to external stimuli. Due to the enormous noise affecting them, traditionally, the analysis of ERPs has relied of averaging the signals recorded in many repetitions of an experiment. However, while averaging helps to improve the signal to noise ratio of an ERP, it does so at the expense of blurring it, thereby making it possible to observe only large scale effects. It has recently been shown that binning ERPs based on user response-times and then averaging can mitigate this problem. However, this technique relies the availability of a physical manifestation of a user's mental processes (e.g., a key press), and could not be used in experiments where this is not desirable or possible. In our programme of research, we attempt to go beyond this limitation by using forms of unsupervised clustering of ERPs prior to averaging. In this paper, we test clustering based on similarity of centroids with simulated ERPs.
Local sensing with global recovery

In this paper, we study Locally Compressed Sensing for images, where sampling process is allowed to be performed on arbitrary local regions of the images. We propose a fast and efficient reconstruction algorithm which utilizes local structures of images. Several numerical experiments on real images demonstrates that our algorithm yields better reconstruction quality than existing techniques at much lower computational complexity and memory requirement.
CyberCut: An Internet-based CAD/CAM System

“CyberCut TM ” is a testbed for an Internet-based CAD/CAM system. It was specifically designed to be a networked, automated system, with a seamless communication flow from a client-side designer to a server-side machining service. The creation of CyberCut required several new software modules. These include: a) a Web-based design tool in which Design-forManufacturing information and machining rules constrain the designer to manufacturable parts; b) a geometric representation called SIF-DSG, for unambiguous communication between the client-side designer and the server-side process planner; c) an automated process planning system with several sub-modules that convert an incoming design to a set of tool-paths for execution on a 3-axis CNC milling machine. Using this software-pipeline, a CyberCut service, modeled on the MOSIS service for VLSI chips, has been now been launched for limited studentuse at a group of cooperating universities.
Financial LPPL Bubbles with Mean-Reverting Noise in the Frequency Domain

The log-periodic power law (LPPL) is a model of asset prices during endogenous bubbles. A major open issue is to verify the presence of LPPL in price sequences and to estimate the LPPL parameters. Estimation is complicated by the fact that daily LPPL returns are typically orders of magnitude smaller than measured price returns, suggesting that noise obscures the underlying LPPL dynamics. However, if noise is mean-reverting, it would quickly cancel out over subsequent measurements. In this paper, we attempt to reject mean-reverting noise from price sequences by exploiting frequency-domain properties of LPPL and of mean reversion. First, we calculate the spectrum of mean-reverting \ou noise and devise estimators for the noise's parameters. Then, we derive the LPPL spectrum by breaking it down into its two main characteristics of power law and of log-periodicity. We compare price spectra with noise spectra during historical bubbles. In general, noise was strong also at low frequencies and, even if LPPL underlied price dynamics, LPPL would be obscured by noise.
Gaze in Human-Robot Communication

Gaze in Human-Robot Communication is a volume collecting recent research studying gaze behaviour in human-robot interaction (HRI). The selected articles draw inspiration from related research into gaze in human-human interaction in fields ranging from ethnography to neuroscience. The major themes of these articles include: the experimental investigation of human responses to robot gaze, the investigation of the impact of coordinating gaze acts with speech, and the development of hardware and software technologies for enabling robot gaze. This volume provides an excellent introduction to the depth and breadth of this growing research area in HRI. The highly interdisciplinary nature of the work presented should make it of interest both to robotics researchers and to researchers from other fields with an interest in the role of gaze in communication.Originally published in Interaction Studies Vol. 14:3 (2013).
Mathematical Models for Cell-Matrix Interactions during Dermal Wound Healing

This paper contains a review of our recent work on the mathematical modeling of cell interaction with extracellular matrix components during the process of dermal wound healing. The models are of partial differential equation type and allow us to investigate in detail how various mechanochemical effects may be responsible for certain wound healing disorders such as fibrocontractive and fibroproliferative diseases. We also present a model for wound healing angiogenesis. The latter has several features in common with angiogenesis during cancer tumour growth and spread so a deeper understanding of the phenomenon in the context of wound healing may also help in the treatment of certain cancers.
A Text Independent Speaker Recognition System Using a Novel Parametric Neural Network

This paper presents a new Speaker Recognition Technique aimed at high identification accuracy and low impostor acceptance. This method is based on a modified neural network, which is an extended and improved version of a Self-Organizing Map in multiple dimensions. The goal of this methodology is to achieve high accuracy identification and impostor rejection. The proposed method, Multiple Parametric Self-Organizing Maps (M-PSOM) is a classification and verification technique. This novel method was successfully implemented and tested using the CSLU Speaker Recognition Corpora of the Oregon School of Engineering with excellent results. This method builds a unique parametric neural network for each speaker as opposed to a single neural network for the whole system as it has been done in the past. With this technology a parametric neural network is a unique representation of a speaker’s acoustic signature.
Crowdsourcing Empathetic Intelligence

Unobtrusive recognition of the user's mood is an essential capability for affect-adaptive systems. Mood is a subtle, long-term affective state, often misrecognized even by humans. The challenge to train a machine to recognize it from, for example, a video of the user, is significant, and already begins with the lack of ground truth for supervised learning. Existing affective databases consist mainly of short videos, annotated in terms of expressed emotions rather than mood. In very few cases, we encounter perceived mood annotations, of questionable reliability, however, due to the subjectivity of mood estimation and the small number of coders involved. In this work, we introduce a new database for mood recognition from video. Our database contains 180 long, acted videos, depicting typical daily scenarios, and subtle facial and bodily expressions. The videos cover three visual modalities (face, body, Kinect data), and are annotated in terms of emotions (via G-trace) and mood (via the Self-Assessment Manikin and the AffectButton). To annotate the database exhaustively, we exploit crowdsourcing to reach out to an extensive number of nonexpert coders. We validate the reliability of our crowdsourced annotations by (1) adopting a number of criteria to filter out unreliable coders, and (2) comparing the annotations of a subset of our videos with those collected in a controlled lab setting.
Sparse Graph Codes for the Two-Way Relay Network with Correlated Sources

We design sparse graph codes for the two-way relay network with an orthogonal multi-access uplink channel and correlated sources. Recent results on source-channel separation demonstrate the optimality of individual optimisation of source and channel codes. We present a coding scheme based on low-density parity-check codes that performs close to the theoretical limits. Furthermore, we consider the case of non capacity-achieving codes and show the benefits of joint source-channel decoding.
CS 229 Final Project Sentiment Causation Extraction

In state of the art sentiment analysis, text is analyzed for a single unidimensional sentiment or opinion score. This unidimensional sentiment, however, cannot capture the nuances of emotions: for example, two texts that respectively convey anger and sadness will both have a negative sentiment associated with them, while carrying very different connotations. Thus, we require a tool that allows more sophisticated analysis of emotional text. This need for more sophisticated relation extraction is relevant outside of sentiment analysis as well. For example, causal relation extraction has important applications for building question and answer systems. Relation extraction remains an incredibly difficult problem to solve, but offers many promises such as constructing abstract knowledge representations or constructing narrative sequences from newspapers [1]. In this work, we propose building a causal relation extraction tool specifically for extracting the cause of emotions. Although we focus on causal extraction of emotions, the tool is generalizable to causal extraction in other domains.
ON ALEXANDER MODULES AND BLANCHFIELD FORMS OF NULL-HOMOLOGOUS KNOTS IN RATIONAL HOMOLOGY SPHERES

In this paper, we give a classification of Alexander modules of null-homologous knots in rational homology spheres. We characterize these modules $\mathcal{A}$ equipped with their Blanchfield forms ϕ, and the modules $\mathcal{A}$ such that there is a unique isomorphism class of $(\mathcal{A}, \phi)$, and we prove that for the other modules $\mathcal{A}$, there are infinitely many such classes. We realize all these $(\mathcal{A}, \phi)$ by explicit knots in ℚ-spheres.
Literature review of fMRI image processing techniques

Functional Magnetic Resonance imaging is an aid in identifying the brain activated regions by certain stimuli and tasks. It can be used to identify the psychological or other disease states resulting from various neurological impairments and also to make implication on brain connectivity. Several techniques are used for the functional analysis of fMRI neuroimaging data. Here our endeavor is to make a review of various computational methodologies used by fMRI data analysis, which includes various preprocessing methods used for removing noise and enhancing quality in fMRI as well as various statistical methods of fMRI image analysis.
The impact of narcotic drugs and psychotropic on social security

The consumption, sale and traffic of narcotic drugs and psychotropic have always been a major parameter with regard to social security affecting a wide spectrum of legal, political, health and educational activities as well as normative procedures and moral values. The purpose of this research is to investigate the effects of narcotic drugs and psychotropic substances on social security. The research has an applied objective and a descriptive methodology and the researcher has made use of the existing library sources, the internet and documents’ archive and views expressed by the United Nations Office on Drugs and Crime and the International Narcotics Control Board. The research indicated that social security is a social need and narcotic drugs pose a serious threat to the society. On this basis, awarenessraising has to be institutionalized and importance must be attached to educational syllabus on the subject of narcotic drugs and psychotropic substances. The community-based approach for combating narcotic drugs and psychotropic substances must continue and a number of issues have to be followed up including the creation of job opportunities, facilitating marriage, advocating sporting activities, developing research and studies, parental responsibilities and improving harms reduction centers.
TR – 026 Efficient Heuristics for the Time Dependent Team Orienteering Problem with Time Windows

The Time Dependent Team Orienteering Problem with Time Windows (TDTOPTW) can be used to model several real life problems. Among them, the route planning problem for tourists interested in visiting multiple points of interest (POIs) using public transport. The main objective of this problem is to select POIs that match tourist preferences, while taking into account a multitude of parameters and constraints and respecting the time available for sightseeing in a daily basis. TDTOPTW is NP-hard while almost the whole body of the related literature addresses the non time dependent version of the problem. The only TDTOPTW heuristic proposed so far is based on the assumption of periodic service schedules. Herein, we propose two efficient cluster-based heuristics for the TDTOPTW which yield high quality solutions, take into account time dependency in calculating travel times between POIs and make no assumption on periodic service schedules. The validation scenario for our prototyped algorithms included the metropolitan transit network and real POI sets compiled from Athens (Greece).
New features in UML syntax and semantics

This paper is an overview of the most important new features introduced to version 2.0 of Unified Modeling Language. We denote the changes to existing diagram and present four new modeling techniques. We present the changes in definitions of syntax, semantics and pragmatics of behavioral and static models of systems designed with UML 2.0. Particular emphasis is put on the changes to sequence and activity diagrams and to component diagrams. The newly introduced diagrams, unknown in previous UML versions – interaction overview diagrams, timing diagrams, composite structure diagrams and package diagrams – are described with the most detail.
Practical Dynamic Software Updating for C

Software updates are a fact of life which means updating to add new some features and fix some bugs. Current software update methodology is stop/restart. However, many system would prefer no-line upgrades in lien of having to stop and restart the system every time it must be patched. Dynamic software updating (DSU) address such difficulty by update a running program with new code and data on-the-fly. DSU is appealing compared to other approaches for on-line upgrades because it is quite general and on need for redundant hardware or special purpose software architectures. The challenge for making DSU practical is that DSU should be flexible, and yet safe, efficient, and easy to use. In this paper, we present Ginseng, a DSU implementation which can compile C programs specially to support dynamic updates. We compile programs so that they can not only be dynamically patched in the same time performs a series of safety analysis to prove type-safety of update while guaranteeing that date is kept up-to-date, but also generate most of an update automatically.
Power control for interference mitigation between coexisting UWB systems

In this paper, we investigate the coexistence issue of two type of ultra-wideband (UWB) systems under IEEE 802.15. 3a, i.e. Direct-Sequence UWB and MultiBand-Orthogonal Frequency Division Multiplexing UWB. The mutual interference of such coexistence scenarios is analyzed by physical layer Monte Carlo simulations. We observe severe and asymmetric performance degradation due to the mutual interference between the two systems. Therefore, we propose the goodput-oriented utility-based transmit power control (GUTPC) algorithm to improve the performance. The feasible condition and the convergence property of GUTPC are investigated, and the choice of the coefficients is discussed for fairness and efficiency. Numerical results demonstrate that GUTPC improves the goodput of the coexisting systems effectively and fairly.
TCP Pacing Revisited

TCP pacing promises to reduce burstiness of TCP traffic and alleviate the impact of under-buffered routers and switches on flow throughput. However, current research literatures have not always agreed on the overall benefits of pacing. In this paper, we re-examine the benefits and drawbacks of TCP pacing in light of new TCP variants, new application requirements, and trends in router technologies. We found that pacing primarily has three effects: reduced burstiness of traffic, increased synchronization amnog the flows and fragmented SACK blocks in a flow. We analysis how these factors play out for different TCP implementations (Reno, NewReno, SACK, FACK) and new high-speed TCP protocols (BIC-TCP and FAST). We conclude that TCP pacing brings significant benefits for many applications, and though paced flows sometimes suffer in performance when competing with non-paced flows, there are enough incentives for applications to migrate from using nonpaced TCP to paced TCP.