Grid structure impact in sparse point representation of derivatives

In the Sparse Point Representation (SPR) method the principle is to retain the function data indicated by significant interpolatory wavelet coefficients, which are defined as interpolation errors by means of an interpolating subdivision scheme. Typically, a SPR grid is coarse in smooth regions, and refined close to irregularities. Furthermore, the computation of partial derivatives of a function from the information of its SPR content is performed in two steps. The first one is a refinement procedure to extend the SPR by the inclusion of new interpolated point values in a security zone. Then, for points in the refined grid, such derivatives are approximated by uniform finite differences, using a step size proportional to each point local scale. If required neighboring stencils are not present in the grid, the corresponding missing point values are approximated from coarser scales using the interpolating subdivision scheme. Using the cubic interpolation subdivision scheme, we demonstrate that such adaptive finite differences can be formulated in terms of a collocation scheme based on the wavelet expansion associated to the SPR. For this purpose, we prove some results concerning the local behavior of such wavelet reconstruction operators, which stand for SPR grids having appropriate structures. This statement implies that the adaptive finite difference scheme and the one using the step size of the finest level produce the same result at SPR grid points. Consequently, in addition to the refinement strategy, our analysis indicates that some care must be taken concerning the grid structure, in order to keep the truncation error under a certain accuracy limit. Illustrating results are presented for 2D Maxwell's equation numerical solutions.

Study of distribution network demand response events in the Portuguese system

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. Grid operators and utilities are taking new initiatives, recognizing the value of demand response for grid reliability and for the enhancement of organized spot markets’ efficiency. This paper proposes a methodology for the selection of the consumers that participate in an event, which is the responsibility of the Portuguese transmission network operator. The proposed method is intended to be applied in the interruptibility service implemented in Portugal, in convergence with Spain, in the context of the Iberian electricity market. This method is based on the calculation of locational marginal prices (LMP) which are used to support the decision concerning the consumers to be schedule for participation. The proposed method has been computationally implemented and its application is illustrated in this paper using a 937 bus distribution network with more than 20,000 consumers.

Intelligent behavior in a Cyber-Ambient training system for control center operators

This paper deals with the application of an intelligent tutoring approach to delivery training in diagnosis procedures of a Power System. In particular, the mechanisms implemented by the training tool to support the trainees are detailed. This tool is part of an architecture conceived to integrate Power Systems tools in a Power System Control Centre, based on an Ambient Intelligent paradigm. The present work is integrated in the CITOPSY project which main goal is to achieve a better integration between operators and control room applications, considering the needs of people, customizing requirements and forecasting behaviors.

Training control centers' operators in incident diagnosis and power restoration using intelligent tutoring systems

The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults like blackouts. In this paper, we present an Intelligent Tutoring approach for training Portuguese Control Center operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, having into account context awareness and the unobtrusive integration in the working environment. Several Artificial Intelligence techniques were criteriously used and combined together to obtain an effective Intelligent Tutoring environment, namely Multiagent Systems, Neural Networks, Constraint-based Modeling, Intelligent Planning, Knowledge Representation, Expert Systems, User Modeling, and Intelligent User Interfaces.

Fractional generalization of memristor and higher order elements

Fractional calculus generalizes integer order derivatives and integrals. Memristor systems generalize the notion of electrical elements. Both concepts were shown to model important classes of phenomena. This paper goes a step further by embedding both tools in a generalization considering complex-order objects. Two complex operators leading to real-valued results are proposed. The proposed class of models generate a broad universe of elements. Several combinations of values are tested and the corresponding dynamical behavior is analyzed.

Development of a platform for lean manufacturing simulation games

More than ever, the economic globalization is creating the need to increase business competitiveness. Lean manufacturing is a management philosophy oriented to the elimination of activities that do not create any type of value and are thus considered a waste. One of the main differences from other management philosophies is the shop-floor focus and the operators' involvement. Therefore, the training of all organization levels is crucial for the success of lean manufacturing. Universities should also participate actively in this process by developing students' lean management skills and promoting a better and faster integration of students into their future organizations. This paper proposes a single realistic manufacturing platform, involving production and assembly operations, to learn by playing many of the lean tools such as VSM, 5S, SMED, poke-yoke, line balance, TPM, Mizusumashi, plant layout, and JIT/kanban. This simulation game was built in tight cooperation with experienced lean companies under the international program “Lean Learning Academy,”http://www.leanlearningacademy.eu/ and its main aim is to make bachelor and master courses in applied sciences more attractive by integrating classic lectures with a simulated production environment that could result in more motivated students and higher study yields. The simulation game results show that our approach is efficient in providing a realistic platform for the effective learning of lean principles, tools, and mindset, which can be easily included in course classes of less than two hours.

Numerical analysis of the initial conditions in fractional systems

Fractional dynamics is a growing topic in theoretical and experimental scientific research. A classical problem is the initialization required by fractional operators. While the problem is clear from the mathematical point of view, it constitutes a challenge in applied sciences. This paper addresses the problem of initialization and its effect upon dynamical system simulation when adopting numerical approximations. The results are compatible with system dynamics and clarify the formulation of adequate values for the initial conditions in numerical simulations.

Realistic Multi-Agent Simulation of Competitive Electricity Markets

The dynamism and ongoing changes that the electricity markets sector is constantly suffering, enhanced by the huge increase in competitiveness, create the need of using simulation platforms to support operators, regulators, and the involved players in understanding and dealing with this complex environment. This paper presents an enhanced electricity market simulator, based on multi-agent technology, which provides an advanced simulation framework for the study of real electricity markets operation, and the interactions between the involved players. MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) uses real data for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations bring to different countries. Also, the development of an upper-ontology to support the communication between participating agents, provides the means for the integration of this simulator with other frameworks, such as MAN-REM (Multi-Agent Negotiation and Risk Management in Electricity Markets). A case study using the enhanced simulation platform that results from the integration of several systems and different tools is presented, with a scenario based on real data, simulating the MIBEL electricity market environment, and comparing the simulation performance with the real electricity market results.

On the iteration of Katsuno and Mendelzon update

In this dissertation we present a model for iteration of Katsuno and Mendelzon’s Update, inspired in the developments for iteration in AGM belief revision. We adapt Darwiche and Pearls’ postulates of iterated belief revision to update (as well as the independence postulate proposed in [BM06, JT07]) and show two families of such operators, based in natural [Bou96] and lexicographic revision [Nay94a, NPP03]. In all cases, we provide a possible worlds semantics of the models.

Numerical analysis of the initial conditions in fractional systems

Fractional dynamics is a growing topic in theoretical and experimental scientific research. A classical problem is the initialization required by fractional operators. While the problem is clear from the mathematical point of view, it constitutes a challenge in applied sciences. This paper addresses the problem of initialization and its effect upon dynamical system simulation when adopting numerical approximations. The results are compatible with system dynamics and clarify the formulation of adequate values for the initial conditions in numerical simulations.

Intracoronary Delivery of Human Mesenchymal/Stromal Stem Cells: Insights from Coronary Microcirculation Invasive Assessment in a Swine Model

BACKGROUND: Mesenchymal stem/stromal cells have unique properties favorable to their use in clinical practice and have been studied for cardiac repair. However, these cells are larger than coronary microvessels and there is controversy about the risk of embolization and microinfarctions, which could jeopardize the safety and efficacy of intracoronary route for their delivery. The index of microcirculatory resistance (IMR) is an invasive method for quantitatively assessing the coronary microcirculation status. OBJECTIVES: To examine heart microcirculation after intracoronary injection of mesenchymal stem/stromal cells with the index of microcirculatory resistance. METHODS: Healthy swine were randomized to receive by intracoronary route either 30x106 MSC or the same solution with no cells (1% human albumin/PBS) (placebo). Blinded operators took coronary pressure and flow measurements, prior to intracoronary infusion and at 5 and 30 minutes post-delivery. Coronary flow reserve (CFR) and the IMR were compared between groups. RESULTS: CFR and IMR were done with a variance within the 3 transit time measurements of 6% at rest and 11% at maximal hyperemia. After intracoronary infusion there were no significant differences in CFR. The IMR was significantly higher in MSC-injected animals (at 30 minutes, 14.2U vs. 8.8U, p = 0.02) and intragroup analysis showed a significant increase of 112% from baseline to 30 minutes after cell infusion, although no electrocardiographic changes or clinical deterioration were noted. CONCLUSION: Overall, this study provides definitive evidence of microcirculatory disruption upon intracoronary administration of mesenchymal stem/stromal cells, in a large animal model closely resembling human cardiac physiology, function and anatomy.

Evaluation of exposure biomarkers in offshore workers exposed to low benzene and toluene concentrations.

Characterize ethylbenzene and xylene air concentrations, and explore the biological exposure markers (urinary t,t-muconic acid (t,t-MA) and unmetabolized toluene) among petroleum workers offshore. Offshore workers have increased health risks due to simultaneous exposures to several hydrocarbons present in crude oil. We discuss the pooled benzene exposure results from our previous and current studies and possible co-exposure interactions. BTEX air concentrations were measured during three consecutive 12-h work shifts among 10 tank workers, 15 process operators, and 18 controls. Biological samples were collected pre-shift on the first day of study and post-shift on the third day of the study. The geometric mean exposure over the three work shifts were 0.02 ppm benzene, 0.05 ppm toluene, 0.03 ppm ethylbenzene, and 0.06 ppm xylene. Benzene in air was significantly correlated with unmetabolized benzene in blood (r = 0.69, p < 0.001) and urine (r = 0.64, p < 0.001), but not with urinary t,t-MA (r = 0.27, p = 0.20). Toluene in air was highly correlated with the internal dose of toluene in both blood (r = 0.70, p < 0.001) and urine (r = 0.73, p < 0.001). Co-exposures were present; however, an interaction of metabolism was not likely at these low benzene and toluene exposures. Urinary benzene, but not t,t-MA, was a reliable biomarker for benzene at low exposure levels. Urinary toluene was a useful biomarker for toluene exposure. Xylene and ethylbenzene air levels were low. Dermal exposure assessment needs to be performed in future studies among these workers.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Application of Reptation Quantum Monte Carlo and Related Methods to LiH

This work investigates mathematical details and computational aspects of Metropolis-Hastings reptation quantum Monte Carlo and its variants, in addition to the Bounce method and its variants. The issues that concern us include the sensitivity of these algorithms' target densities to the position of the trial electron density along the reptile, time-reversal symmetry of the propagators, and the length of the reptile. We calculate the ground-state energy and one-electron properties of LiH at its equilibrium geometry for all these algorithms. The importance sampling is performed with a single-determinant large Slater-type orbitals (STO) basis set. The computer codes were written to exploit the efficiencies engineered into modern, high-performance computing software. Using the Bounce method in the calculation of non-energy-related properties, those represented by operators that do not commute with the Hamiltonian, is a novel work. We found that the unmodified Bounce gives good ground state energy and very good one-electron properties. We attribute this to its favourable time-reversal symmetry in its target density's Green's functions. Breaking this symmetry gives poorer results. Use of a short reptile in the Bounce method does not alter the quality of the results. This suggests that in future applications one can use a shorter reptile to cut down the computational time dramatically.

Dramatizing whoredom : prostitution in the work of Tennessee Williams

Cette thèse explore le leitmotiv de la prostitution dans l’oeuvre de Tennessee Williams et soutient que la plupart des personnages de Williams sont engagés dans une forme de prostitution ou une autre. En effectuant une analyse formaliste des textes de Williams qui illustrent toute forme de prostitution, avec une attention particulière à quatre grandes pièces, A Streetcar Named Desire (1947), Cat on a Hot Tin Roof (1955), Suddenly Last Summer (1958) et Sweet Bird of Youth (1959), cette présente étude fait valoir que le dramaturge utilise un mode de fiction—le gothique—en lien avec une pratique transgressive—la prostitution—pour relier les classes sociales et troubler les catégories de prostitution. Ce faisant, Williams offre une vision plus représentative et nuancée de la prostitution. Théoriquement, cette thèse repose sur des oeuvres critiques portant sur le genre, la sexualité et l'histoire de Michel Foucault, David Savran, et Michael Paller afin de situer la dramaturgie de Williams dans le contexte historique et culturel des années 1940 et 1950. La première partie de cette thèse (chapitres un et deux) fournit de nombreuses informations autobiographiques et biographiques qui expliquent pourquoi la prostitution est devenue le thème de prédilection pour Williams. Cette section met l’accent sur sa préoccupation constante à l’égard de sa prostitution artistique (en prostituant son art pour le succès commercial) et sexuelle (en payant pour des prostitués). Cette partie présente également un inventaire détaillé des prostituté(e)s, que je divise en trois catégories: 1) la prostitution des enfants, 2) la prostitution masculine et 3) la prostitution féminine. La deuxième partie de cette étude, composée des chapitres trois et quatre, identifie les personnages de Williams qui s’engagent dans une forme de prostitution morale. Ce groupe comprend ceux qui tirent directement profit de la prostitution des autres ainsi que ceux qui se marient uniquement pour un gain financier ou une promotion sociale ou les deux. L’oeuvre de Williams résiste la représentation stéréotypée de la prostituée en littérature comme étant uniquement de sexe féminin ou provenant des classes sociales défavorisées ou les deux. La prostituée de Williams n’est ni une figure romantique ni une rebelle menaçant la société. Cette thèse conclut qu’en représentant des enfants prostitués, des femmes de rue, des prostitués de sexe masculin, des souteneurs, des proxénètes, des propriétaires de bordels, des leaders corrompus et des personnes qui se prostituent en concluant des mariages de convenance, Williams a effectivement et incontestablement dramatisé la prostitution sous toutes ses formes.