Building peace by supporting post-conflict electoral processes

Les élections post-conflit ou élections de sortie de crise organisées sous l’égide de la communauté internationale en vue de rétablir la paix dans les pays sortant de violents conflits armés ont un bilan mixte caractérisé par le succès ou l’échec selon les cas. Ce bilan mitigé représente le problème principal auquel cette recherche tente de répondre à travers les questions suivantes : l’assistance électorale étrangère est-elle efficace comme outil de rétablissement de la paix dans les sociétés post-conflit? Qu’est ce qui détermine le succès ou l’échec des élections post-conflit à contribuer efficacement au rétablissement de la paix dans les sociétés déchirées par la guerre? Pour résoudre cette problématique, cette thèse développe une théorie de l’assistance électorale en période post-conflit centrée sur les parties prenantes à la fois du conflit armé et du processus électoral. Cette théorie affirme que l’élément clé pour le succès des élections post-conflit dans le rétablissement de la paix est le renforcement de la capacité de négociation des parties prenantes à la fois dans le processus de paix et dans le processus électoral post-conflit. Dans les situations post-conflit, une assistance électorale qui se voudrait complète et efficace devra combiner à la fois le processus électoral et le processus de paix. L’assistance électorale sera inefficace si elle se concentre uniquement sur les aspects techniques du processus électoral visant à garantir des élections libres, transparentes et équitables. Pour être efficace, l’accent devra également être mis sur les facteurs supplémentaires qui peuvent empêcher la récurrence de la guerre, tels que l’habilité des individus et des groupes à négocier et à faire des compromis sur les grandes questions qui peuvent menacer le processus de paix. De fait, même des élections transparentes comme celles de 1997 au Liberia saluées par la communauté internationale n’avaient pas réussi à établir des conditions suffisantes pour éviter la reprise des hostilités. C’est pourquoi, pour être efficace, l’assistance électorale dans les situations de post-conflit doit prendre une approche globale qui priorise l’éducation civique, la sensibilisation sur les droits et responsabilités des citoyens dans une société démocratique, le débat public sur les questions qui divisent, la participation politique, la formation au dialogue politique, et toute autre activité qui pourrait aider les différentes parties à renforcer leur capacité de négociation et de compromis. Une telle assistance électorale fera une contribution à la consolidation de la paix, même dans le contexte des élections imparfaites, comme celles qui se sont détenues en Sierra Leone en 2002 ou au Libéria en 2005. Bien que la littérature sur l’assistance électorale n’ignore guère l’importance des parties prenantes aux processus électoraux post-conflit (K. Kumar, 1998, 2005), elle a fortement mis l’accent sur les mécanismes institutionnels. En effet, la recherche académique et professionnelle est abondante sur la réforme des lois électorales, la reforme constitutionnelle, et le développement des administrations électorales tels que les commissions électorales, ainsi que l’observation électorale et autres mécanismes de prévention de la fraude électorale, etc. (Carothers & Gloppen, 2007). En d’autres termes, les décideurs et les chercheurs ont attribué jusqu’à présent plus d’importance à la conception et au fonctionnement du cadre institutionnel et des procédures électorales. Cette thèse affirme qu’il est désormais temps de prendre en compte les participants eux-mêmes au processus électoral à travers des types d’assistance électorale qui favoriseraient leur capacité à participer à un débat pacifique et à trouver des compromis aux questions litigieuses. Cette approche plus globale de l’assistance électorale qui replace l’élection post-conflit dans le contexte plus englobant du processus de paix a l’avantage de transformer le processus électoral non pas seulement en une expérience d’élection de dirigeants légitimes, mais aussi, et surtout, en un processus au cours duquel les participants apprennent à régler leurs points de vue contradictoires à travers le débat politique dans un cadre institutionnel avec des moyens légaux et légitimes. Car, si le cadre institutionnel électoral est important, il reste que le résultat du processus électoral dépendra essentiellement de la volonté des participants à se conformer au cadre institutionnel et aux règles électorales.

An Estimation of Distribution Algorithm with Intelligent Local Search for Rule-based Nurse Rostering

This paper proposes a new memetic evolutionary algorithm to achieve explicit learning in rule-based nurse rostering, which involves applying a set of heuristic rules for each nurse's assignment. The main framework of the algorithm is an estimation of distribution algorithm, in which an ant-miner methodology improves the individual solutions produced in each generation. Unlike our previous work (where learning is implicit), the learning in the memetic estimation of distribution algorithm is explicit, i.e. we are able to identify building blocks directly. The overall approach learns by building a probabilistic model, i.e. an estimation of the probability distribution of individual nurse-rule pairs that are used to construct schedules. The local search processor (i.e. the ant-miner) reinforces nurse-rule pairs that receive higher rewards. A challenging real world nurse rostering problem is used as the test problem. Computational results show that the proposed approach outperforms most existing approaches. It is suggested that the learning methodologies suggested in this paper may be applied to other scheduling problems where schedules are built systematically according to specific rules.

Rule Generalisation in Intrusion Detection Systems using Snort

Intrusion Detection Systems (IDSs) provide an important layer of security for computer systems and networks, and are becoming more and more necessary as reliance on Internet services increases and systems with sensitive data are more commonly open to Internet access. An IDS’s responsibility is to detect suspicious or unacceptable system and network activity and to alert a systems administrator to this activity. The majority of IDSs use a set of signatures that define what suspicious traffic is, and Snort is one popular and actively developing open-source IDS that uses such a set of signatures known as Snort rules. Our aim is to identify a way in which Snort could be developed further by generalising rules to identify novel attacks. In particular, we attempted to relax and vary the conditions and parameters of current Snort rules, using a similar approach to classic rule learning operators such as generalisation and specialisation. We demonstrate the effectiveness of our approach through experiments with standard datasets and show that we are able to detect previously undetected variants of various attacks. We conclude by discussing the general effectiveness and appropriateness of generalisation in Snort based IDS rule processing. Keywords: anomaly detection, intrusion detection, Snort, Snort rules

An Estimation of Distribution Algorithm with Intelligent Local Search for Rule-based Nurse Rostering

This paper proposes a new memetic evolutionary algorithm to achieve explicit learning in rule-based nurse rostering, which involves applying a set of heuristic rules for each nurse's assignment. The main framework of the algorithm is an estimation of distribution algorithm, in which an ant-miner methodology improves the individual solutions produced in each generation. Unlike our previous work (where learning is implicit), the learning in the memetic estimation of distribution algorithm is explicit, i.e. we are able to identify building blocks directly. The overall approach learns by building a probabilistic model, i.e. an estimation of the probability distribution of individual nurse-rule pairs that are used to construct schedules. The local search processor (i.e. the ant-miner) reinforces nurse-rule pairs that receive higher rewards. A challenging real world nurse rostering problem is used as the test problem. Computational results show that the proposed approach outperforms most existing approaches. It is suggested that the learning methodologies suggested in this paper may be applied to other scheduling problems where schedules are built systematically according to specific rules.

Rule Generalisation in Intrusion Detection Systems using Snort

Intrusion Detection Systems (IDSs) provide an important layer of security for computer systems and networks, and are becoming more and more necessary as reliance on Internet services increases and systems with sensitive data are more commonly open to Internet access. An IDS’s responsibility is to detect suspicious or unacceptable system and network activity and to alert a systems administrator to this activity. The majority of IDSs use a set of signatures that define what suspicious traffic is, and Snort is one popular and actively developing open-source IDS that uses such a set of signatures known as Snort rules. Our aim is to identify a way in which Snort could be developed further by generalising rules to identify novel attacks. In particular, we attempted to relax and vary the conditions and parameters of current Snort rules, using a similar approach to classic rule learning operators such as generalisation and specialisation. We demonstrate the effectiveness of our approach through experiments with standard datasets and show that we are able to detect previously undetected variants of various attacks. We conclude by discussing the general effectiveness and appropriateness of generalisation in Snort based IDS rule processing. Keywords: anomaly detection, intrusion detection, Snort, Snort rules

Reasonableness in European and Chinese Contract Law. A Comparative Law Study

Contemporary private law, in teh last few decades, TEMPhas been increasingly characterized by teh spread of general clauses and standards and by teh growing role of interpreters in teh framework of teh sources of law. dis process TEMPhas also consistently effected those systems dat are not typically centered on judge-made law. In particular in contract law general clauses and standards has assumed a leading role and has become protagonists of processes of integration and harmonization of teh law. Wifin dis context, teh reasonableness clause TEMPhas come to teh attention of scholars, emerging as a new element of connection between different legal systems -first of all between common law and civil law – and even between different legal traditions. dis research aims at reconstructing teh patterns of emersion and evolution of teh TEMPprincipal of reasonableness in contract law both wifin European Union Law and in teh Chinese legal system, in order to identify evolutionary trends, processes of emersion and circulation of legal models and teh scope of operation of teh TEMPprincipal in teh two contexts. In view of teh increasingly intense economic relations between Europe and China, wifin teh framework of teh new project called Belt and Road Initiative, a comparative survey of dis type can foster mutual understanding and make communications more TEMPeffective, at teh level of legal culture and commercial relations, and to support teh processes of supranational harmonization of contract law rules.

Investimenti infrastrutturali nei porti e negli aeroporti e aiuti di Stato

Gli investimenti alle infrastrutture di trasporto sono stati per lungo tempo considerati misure di politica generale di competenza esclusiva degli Stati membri, nonostante il generale divieto di misure di sostegno pubblico a favore delle imprese ai sensi dell’art. 107 TFUE. Le sentenze rese dalle corti eurounitarie in relazione agli aeroporti di Parigi e di Lipsia Halle hanno dato avvio ad un vero e proprio revirement giurisprudenziale, in considerazione delle trasformazioni economiche internazionali, rimettendo in discussione il concetto di impresa, nonché la ferma interpretazione secondo cui il finanziamento alle infrastrutture – in quanto beni pubblici intesi a soddisfare i bisogni di mobilità dei cittadini – sfuggirebbe all’applicazione della disciplina degli aiuti di Stato. Nonostante le esigenze di costante ammodernamento e sviluppo delle infrastrutture, il nuovo quadro regolatorio adottato dall’Unione europea a seguire ha condotto inevitabilmente gli Stati membri a dover sottoporre al vaglio preventivo della Commissione ogni nuovo investimento infrastrutturale. La presente trattazione, muovendo dall’analisi della disciplina degli aiuti di Stato di cui agli artt. 107 e ss. TFUE, analizza i principi di creazione giurisprudenziale e dottrinale che derivano dall’interpretazione delle fonti primarie, mettendo in evidenza le principali problematiche giuridiche sottese, anche in considerazione delle peculiarità delle infrastrutture in questione, dei modelli proprietari e di governance, delle competenze e dei poteri decisionali in merito a nuovi progetti di investimento. Infine, la trattazione si concentra sui grandi progetti infrastrutturali a livello europeo e internazionale che interessano le reti di trasporto, analizzando le nuove sfide, pur considerando la necessità di assicurare, anche rispetto ad essi, la salvaguardia del cd. level playing field e l’osservanza sostanziale delle norme sugli aiuti di Stato.

Unsupervised KDD to creatively support managers' decision making with fuzzy association rules:a distribution channel application

To be competitive in contemporary turbulent environments, firms must be capable of processing huge amounts of information, and effectively convert it into actionable knowledge. This is particularly the case in the marketing context, where problems are also usually highly complex, unstructured and ill-defined. In recent years, the development of marketing management support systems has paralleled this evolution in informational problems faced by managers, leading to a growth in the study (and use) of artificial intelligence and soft computing methodologies. Here, we present and implement a novel intelligent system that incorporates fuzzy logic and genetic algorithms to operate in an unsupervised manner. This approach allows the discovery of interesting association rules, which can be linguistically interpreted, in large scale databases (KDD or Knowledge Discovery in Databases.) We then demonstrate its application to a distribution channel problem. It is shown how the proposed system is able to return a number of novel and potentially-interesting associations among variables. Thus, it is argued that our method has significant potential to improve the analysis of marketing and business databases in practice, especially in non-programmed decisional scenarios, as well as to assist scholarly researchers in their exploratory analysis. © 2013 Elsevier Inc.

HW Implementation of a Optimized Algorithm for the Application of Active Rules in a Transition P-system

P systems or Membrane Computing are a type of a distributed, massively parallel and non deterministic system based on biological membranes. They are inspired in the way cells process chemical compounds, energy and information. These systems perform a computation through transition between two consecutive configurations. As it is well known in membrane computing, a configuration consists in a m-tuple of multisets present at any moment in the existing m regions of the system at that moment time. Transitions between two configurations are performed by using evolution rules which are in each region of the system in a non-deterministic maximally parallel manner. This work is part of an exhaustive investigation line. The final objective is to implement a HW system that evolves as it makes a transition P-system. To achieve this objective, it has been carried out a division of this generic system in several stages, each of them with concrete matters. In this paper the stage is developed by obtaining the part of the system that is in charge of the application of the active rules. To count the number of times that the active rules is applied exist different algorithms. Here, it is presents an algorithm with improved aspects: the number of necessary iterations to reach the final values is smaller than the case of applying step to step each rule. Hence, the whole process requires a minor number of steps and, therefore, the end of the process will be reached in a shorter length of time.

Cluster Analysis of Some Clases of Objects by Application of the Test Recognition Algorithms

The paper treats the task for cluster analysis of a given assembly of objects on the basis of the information contained in the description table of these objects. Various methods of cluster analysis are briefly considered. Heuristic method and rules for classification of the given assembly of objects are presented for the cases when their division into classes and the number of classes is not known. The algorithm is checked by a test example and two program products (PP) – learning systems and software for company management. Analysis of the results is presented.

Realization of fractional-order controllers: analysis, synthesis and application to the velocity control of a servo system

The synthesis and application of fractional-order controllers is now an active research field. This article investigates the use of fractional-order PID controllers in the velocity control of an experimental modular servo system. The systern consists of a digital servomechanism and open-architecture software environment for real-time control experiments using MATLAB/Simulink. Different tuning methods will be employed, such as heuristics based on the well-known Ziegler Nichols rules, techniques based on Bode’s ideal transfer function and optimization tuning methods. Experimental responses obtained from the application of the several fractional-order controllers are presented and analyzed. The effectiveness and superior performance of the proposed algorithms are also compared with classical integer-order PID controllers.

Application of genetic algorithms in the design of an electrical potential of fractional order

Fractional calculus (FC) is currently being applied in many areas of science and technology. In fact, this mathematical concept helps the researches to have a deeper insight about several phenomena that integer order models overlook. Genetic algorithms (GA) are an important tool to solve optimization problems that occur in engineering. This methodology applies the concepts that describe biological evolution to obtain optimal solution in many different applications. In this line of thought, in this work we use the FC and the GA concepts to implement the electrical fractional order potential. The performance of the GA scheme, and the convergence of the resulting approximation, are analyzed. The results are analyzed for different number of charges and several fractional orders.

Application of fractional algorithms in the control of a robotic bird

In this paper, it is studied the dynamics of the robotic bird in terms of time response and robustness. It is analyzed the wing angle of attack and the velocity of the bird, the tail influence, the gliding flight and the flapping flight. The results are positive for the construction of flying robots. The development of computational simulation based on the dynamic of the robotic bird should allow testing strategies and different algorithms of control such as integer and fractional controllers.

Can genetic algorithms explain experimental anomalies? An application to common property resources

It is common to find in experimental data persistent oscillations in the aggregate outcomes and high levels of heterogeneity in individual behavior. Furthermore, it is not unusual to find significant deviations from aggregate Nash equilibrium predictions. In this paper, we employ an evolutionary model with boundedly rational agents to explain these findings. We use data from common property resource experiments (Casari and Plott, 2003). Instead of positing individual-specific utility functions, we model decision makers as selfish and identical. Agent interaction is simulated using an individual learning genetic algorithm, where agents have constraints in their working memory, a limited ability to maximize, and experiment with new strategies. We show that the model replicates most of the patterns that can be found in common property resource experiments.

A 2D/3D image analysis system to track fluorescently labeled structures in rod-shaped cells: application to measure spindle pole asymmetry during mitosis.

BACKGROUND: The yeast Schizosaccharomyces pombe is frequently used as a model for studying the cell cycle. The cells are rod-shaped and divide by medial fission. The process of cell division, or cytokinesis, is controlled by a network of signaling proteins called the Septation Initiation Network (SIN); SIN proteins associate with the SPBs during nuclear division (mitosis). Some SIN proteins associate with both SPBs early in mitosis, and then display strongly asymmetric signal intensity at the SPBs in late mitosis, just before cytokinesis. This asymmetry is thought to be important for correct regulation of SIN signaling, and coordination of cytokinesis and mitosis. In order to study the dynamics of organelles or large protein complexes such as the spindle pole body (SPB), which have been labeled with a fluorescent protein tag in living cells, a number of the image analysis problems must be solved; the cell outline must be detected automatically, and the position and signal intensity associated with the structures of interest within the cell must be determined. RESULTS: We present a new 2D and 3D image analysis system that permits versatile and robust analysis of motile, fluorescently labeled structures in rod-shaped cells. We have designed an image analysis system that we have implemented as a user-friendly software package allowing the fast and robust image-analysis of large numbers of rod-shaped cells. We have developed new robust algorithms, which we combined with existing methodologies to facilitate fast and accurate analysis. Our software permits the detection and segmentation of rod-shaped cells in either static or dynamic (i.e. time lapse) multi-channel images. It enables tracking of two structures (for example SPBs) in two different image channels. For 2D or 3D static images, the locations of the structures are identified, and then intensity values are extracted together with several quantitative parameters, such as length, width, cell orientation, background fluorescence and the distance between the structures of interest. Furthermore, two kinds of kymographs of the tracked structures can be established, one representing the migration with respect to their relative position, the other representing their individual trajectories inside the cell. This software package, called "RodCellJ", allowed us to analyze a large number of S. pombe cells to understand the rules that govern SIN protein asymmetry. CONCLUSIONS: "RodCell" is freely available to the community as a package of several ImageJ plugins to simultaneously analyze the behavior of a large number of rod-shaped cells in an extensive manner. The integration of different image-processing techniques in a single package, as well as the development of novel algorithms does not only allow to speed up the analysis with respect to the usage of existing tools, but also accounts for higher accuracy. Its utility was demonstrated on both 2D and 3D static and dynamic images to study the septation initiation network of the yeast Schizosaccharomyces pombe. More generally, it can be used in any kind of biological context where fluorescent-protein labeled structures need to be analyzed in rod-shaped cells. AVAILABILITY: RodCellJ is freely available under http://bigwww.epfl.ch/algorithms.html, (after acceptance of the publication).