Miracle-dz/UniFAR-FTUs huggingface dataset:
Obtention de modèles de diffusion à partir d'équations cinétiques. Modélisation, étude mathématique et simulation

Cette these porte sur la modelisation du transport electronique dans les semi-conducteurs. Des modeles de diffusion sont couramment utilises (modeles de type Derive Diffusion), mais ils s'averent imprecis pour de petites echelles (composants nanometriques) et des systemes hors equilibre (regimes transitoires). Les modeles cinetiques, tres precis, sont generalement trop couteux en temps de calcul pour permettre une utilisation dans des contextes physiques realistes. Les modeles Spherical Harmonics Expansion (SHE) representent un intermediaire interessant entre ces deux types de modeles. Les modeles SHE sont des modeles de diffusion dans l'espace position-energie qui sont theoriquement adaptes a la modelisation de systemes de particules proches de l'equilibre (mais pas forcement d'un equilibre Maxwellien, contrairement aux modeles de Derive Diffusion), la thermalisation etant le fait de collisions de type elastique. Dans cette these, nous avons propose des modeles de type SHE couple qui permettent de modeliser des particules interagissant avec le milieu environnant de facon inelastique. Un modele SHE couple est introduit pour decrire les interactions entre electrons et phonons dans les semi-conducteurs. Un autre modele de type SHE couple est propose pour modeliser des situations ou la diffusion est engendree par des collisions entre les particules considerees (electrons par exemple) et les parois du materiau dans lequel elles evoluent. Une etude numerique montre que les modeles de type SHE et SHE couple donnent une representation fidele de la realite (montrant de faibles differences avec des modeles cinetiques), meme lorsque les collisions considerees sont fortement inelastiques. Enfin, nous proposons une hierarchie de modeles SHE quantiques pour la description de systemes de tres petite echelle, lorsque le transport electronique aussi bien que les interactions avec le milieu sont regies par la mecanique quantique. Ces modeles dissipent une entropie quantique.
Design and Implementation of IoT Testbed with Improved Reliability using Conditional Probability Techniques

Internet of Things (IoT) test beds are widely used by developers predominantly. Off late, Test beds are being used by data analysts, academicians, industrial persons and hardware ardent. The real purpose of test beds, is to achieve accurate testing results, mimicking the real time environment to the extent possible which is otherwise not possible to reproduce using simulators. As predicted by many industrial giants IoT based devices will reach the scale of billions by 2015. The applications and opportunities they create will also be innumerable. This has created a huge demand for such testing grounds, because a system deployed without proper testing may be vulnerable and sometimes disastrous. Thus our research aims to explore the qualities of test beds, the services they offer and how to enhance the performance of test beds. Our test bed framework is designed and developed with open-source boards to achieved heterogeneity, reusability, interoperability and scalability. This framework would like to be addressed as a utility, with “X” as service: data, sensor client, actuator client, and platform. To achieve this, APIs which is platform and language independent has been developed and provides third-party developer support. The APIs developed have shown considerable improvement in terms of data transfer rate, database upload and retrieval, and user responsiveness. Thus, our framework is capable of offering services through our API. And have demonstrated with the help of conditional probability techniques enhancement in performance and reusability, visualized the same in terms of graphs and datasets.
Designing a Subarray to Estimate Active Reflection Coefficients of an Infinite Array

This paper proposed a systematic method to estimate active reflection coefficients (active S11) of an infinite array from a subarray with finite elements. Detailed step-by-step procedures are illustrated to design a subarray with a minimum number of array antennas and to provide a reasonable accuracy for finding the active S11 through all scan angles. The active S11 are derived after processing the subarray’s coupling parameters. This method significantly reduces the computational time and resources once the coupling parameters among the antennas are obtained. The active S11 are estimated and benchmarked with the unit-cell simulation.
Locating the Clues of Declining Success Rate of Service Calls

For many on-line systems with massive users, to provide services continuously and steadily is vital for business, which requires the anomalies of services should be located and resolved in a timely manner. As a common IT infrastructure, various APM (Application Performance Management) systems/frameworks have been adopted to monitor each call request to a service. Nevertheless, the call request may contain multidimensional attributes (e.g., City, ISP, Platform, etc.), which may further contain multiple values (e.g., ISP could be T-Mobile, CMCC, etc.). As a result, an anomaly such as DSR (Declining Success Rate) to service typically occurs with a combination of such attribute values, which creates major challenges to locate the root cause of the anomaly due to potentially huge numbers of the combinations. In this paper, we propose a novel method, ImpAPTr (Impact Analysis based on Pruning Tree), to identify the combination of dimensional attributes as the clues leading to the root cause of anomalies regarding DSR timely. In the evaluation with the simulated dataset, ImpAPTr detects valid clues in milliseconds with an accuracy of 99.37% (within the top 10 candidate results), 97.72% (top 5), and 94.51% (top 3), respectively, which outperforms previous approaches to a large degree. A field test with a production environment dataset indicates that ImpAPTr is able to detect valid clues in a few seconds.
Adaptive Nonlinear Controller for the Trajectory Tracking of the Quadrotor with Uncertainties

This study presents the mathematical model of a quadrotor based on Newton-Euler equations and then proposes an adaptive backstepping sliding mode controller (ABSMC) to make the quadrotor system follows the desired trajectory without the knowledge of dynamic parameters. Therefore, the nominal law controls are based on BSMC and the parameter variations are estimated with adaptive rules. To estimate the mass and the moment’s inertia of the quadrotor, an adaptive law is developed to measure its parameters. The tracking performance of the proposed outer and inner loops and stability is proven by the use of Lyapunov’s theory that tracking errors converge asymptotically to the origin. In addition, the simulation results of the proposed BSMC is performed out MATLAB/Simulink.
Stress Reduction Using Bilateral Stimulation in Virtual Reality

The goal of this research is to integrate Virtual Reality (VR) with the bilateral stimulation used in EMDR as a tool to relieve stress. We created a 15 minutes relaxation training program for adults in a virtual, relaxing environment in form of a walk in the woods. The target platform for the tool is HTC Vive, however it can be easily ported to other VR platforms. An integral part of this tool is a set of sensors, which serves as physiological measures to evaluate the effectiveness of such system. What is more, the system integrate visual (passing sphere), auditory (surround sound) and tactile signals (vibration of controllers). A pilot treatment programme, incorporating the above mentioned VR system, was carried out. Experimental group consisting of 28 healthy adult volunteers (office workers), participated in three different sessions of relaxation training. Before starting, baseline features such as subjectively perceived stress, mood, heart rate, galvanic skin response and muscle response were registered. The monitoring of physiological indicators is continued during the training session and one minute after its completion. Before and after the session, volunteers were asked to re-fill questionnaires regarding the current stress level and mood. The obtained results were analyzed in terms of variability over time: before, during and after the session.
A Lightweight and Secure Attribute-Based Multi Receiver Generalized Signcryption Scheme for Body Sensor Networks

With the rising number of patients along with the same time, the comparative evolution in wireless technology has made Body Sensor Networks (BSNs) flourishing in the market. In BSNs, tiny biosensor nodes are deployed inside/outside of a human body to continuously monitor patient vital signs such as heartbeat rate, blood pressure, respiratory rate, and temperature. BSNs face various challenges due to their constrained nature environment. These are prioritized, delaying less, and secure patient data transmission using a public network, simultaneous reception of patient data by end-users, patient identity privacy, high overhead, and energy constraints. However, various researchers have worked in this domain, unable to cope with all these issues in one go. In this paper, we have proposed a novel cryptosystem covering the mentioned issues in a desirable way. For this purpose, we offer a novel concept of a lightweight and secure attribute-based multi-receiver generalized signcryption scheme that can adaptively work as an encryption mode, a signature mode, or a signcryption mode with a single algorithm that consume fewer resources by using shorter keys size of Hyper-elliptic Curve Cryptography (HECC). Similarly, we design a modified priority-based scheduling algorithm to delay less emergency patient data. Multiple end-users access the encoded data simultaneously by defining an access policy using AND & OR logic gates. Furthermore, we simulate our scheme using the AVISPA tool and demonstrate that our proposed scheme can meet the security requirements such as data confidentiality (IND-CCA), integrity, unforgeability (EUF-CMA), patient data authenticity, forward secrecy, and non-repudiation distinctly in the Random Oracle Model (ROM). Due to lower processing costs and transmission overhead, this scheme is more efficient and suitable for the resource-constrained environment of BSNs.
Parameter Design and Performance Analysis of an Improved MOCEO Algorithm

In order to solve the multi-objective optimization problem, this paper proposes a multi-objective cross-entropy optimization (MOCEO) algorithm based on the original single-objective cross-entropy (CE) optimization algorithm. Situations, with a low probability for optimal point, and also, locations with a high probability to fall into local optimum after tested with standard test function ZDT4 and ZDT6 problems. The algorithm is then introduced an improved method called disturbance, including recombination, variance disturbance and varying population size. Each operation contains a variable parameter. Appropriate selection of parameters can maximize the optimization ability. A set of optimal parameters is designed and the answers are verified by a comparative study with other meta-heuristic optimization algorithms such as NSGA-II, SPEA2, MOEA/D and PAES in similar conditions. The results indicate that those improvements are effective and the algorithm proposed in this paper is superior to other algorithms. It has the advantages of strong searching ability and high robustness which is applicable to challenging difficulties with unknown search spaces.
Reduction of Price Volatility using Thermostatically Controlled Loads in Local Electricity Markets

Price volatility in electricity markets could significantly increase as a result of the increase in demand due to the electrification of heating and transport and intermittent power generation from large scale integration of renewable energy sources. In some parts of the grid, price volatility may be even more extreme due to congestion. Energy storage and price responsive demand provide a potential source of flexibility to reduce excessive variations in price. In this paper, we investigate the potential of one such type of price responsive demand, namely thermostatically controlled loads, to mitigate against this adverse economic effect through a coordination mechanism that gives explicit constraints on the local electricity price. In a simulation based study that focuses on an energy community situated in a congested part of the distribution grid, we investigate to what extent thermostatically controlled loads can provide load reduction in order to cap prices at a specified limit. Results show that congestion and the resulting price spikes can effectively be mitigated by exploiting the thermal inertia of the households.
Detection of Military Targets from Satellite Images using Deep Convolutional Neural Networks

Due to the varying size, orientation, and background of images in the defense sector, it is a daunting task to discern and distinguish the military targets in them. Multitudes of solutions have been proposed in this arena, yet there is a significant need for much better and flawless outputs. In this chapter, we expound on a two-level solution–Edge Boxes and Convolutional Neural Network (CNN) for the detection of targets in satellite imagery, Super resolution of the image using Dense-skip-connections. In the first level, the military objects are detected from the satellite image using Edge Boxes. In satellite imagery, the edge data of targets contains very prominent and concise attributes. The traditionally engineered features such as Histogram of Oriented Gradients, Hough transform and Gabor feature do not work well for huge datasets. However, the Edge Boxes technique generates contours around the target objects and discards the remaining. The output of this level is fed to the second level, wherein, the proposed targets undergo image super resolution. The presented deep learning model tends to inherently learn an end-to-end mapping between images of lower resolution and higher resolution. This level can be portrayed as one which takes a low-resolution input image and constructs an up-sampled high-resolution image as the output. Unlike traditional methods (sparse coding based method, bicubic method) that handle each component separately, this method aims to optimize all the layers at once. Furthermore, for assuaging the vanishing gradient problem that is common to very deep networks, Dense-skip-connections are employed. These enable the building of shorter paths directly within multiple layers. Though the proposed model has a light weighted structure, it exhibits state-of-the-art restoration quality.
Environmental and Psychosocial Interventions in Age-Friendly Communities and Active Ageing: A Systematic Review

Background: The academic literature contains little information regarding the interventions that create age-friendly cities and communities in order to promote active ageing. Objectives: A systematic review was carried out to determine the available empirical evidence in relation to the characteristics, content and effectiveness of interventions aimed at improving environmental and psychosocial risk factors for older people, from the perspective of age-friendly communities and the promotion of active ageing. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the studies retained in this review were identified through a systematic search of the academic literature in selected electronic databases including Web of Science and Scopus. Independent critical appraisal and data extraction were conducted by two reviewers. The checklist was used to assess the quality of the articles. Findings: The search identified 1020 potentially eligible documents, of which 11 satisfied the established criteria. Non-exhaustive practices prevailed over rigorous investigations, with a high proportion of studies observed to be of low methodological quality and at high risk of bias. This reflected the predominance of uncontrolled interventions. Environmental interventions were focused on reducing risk and adapting the everyday environmental setting, while psychosocial interventions prioritised social strategies (behavioural changes, promotion of participation) and training. Interventions were more effective in certain domains of age-friendly cities and communities such as transportation and housing, followed by increased participation as a lifestyle-related behavioural change. The inferred changes were associated with providing information and enhancing skills; modifying access, barriers, exposures, and opportunities; enhancing services and support; continuity and effectiveness of changes over time; and modifying policies based on the bottom-up approach of age-friendly cities and communities (AFCC). Discussion and conclusion: Interventions focused on personal and organisational aspects might have positive effects in the longer term. However, fewer changes would be observed in interventions revolving around changing lifestyles owing to the impact of complex multi-causal factors. The relative effectiveness in terms of health calls into question the design of interventions and the supposed “friendliness” of certain communities. There is a need to encourage sound longitudinal research aimed at providing key knowledge for the implementation and evaluation of public policies, and to encourage age-friendly community programmes to promote active ageing.
A Comparative Study of Single-phase Non-isolated Bidirectional dc-dc Converters Suitability for Energy Storage Application in a dc Microgrid

Off-grid electricity provision in rural areas where extension of grid is impossible has seen a tremendous research in solar home systems and Islanded DC microgrid design. DC microgrid design has come in many forms, but the most interesting topologies are those that provide power sharing among distributed generators through equalization of state of charge of multiple BESS architecture in both charging and discharging mode. This is mostly implemented using droop control. Of importance in microgrid design is bidirectional DC-DC converters interfacing the BESSs with the DC Bus. Non-isolated bidirectional DC-DC converters are used when galvanic isolation and high-step up or step-down of voltage is not required as against isolated converters. This is commonly implemented using bidirectional buck-boost (half bridge) converters to ensure power flow both in and out of the BESS. This study carries out a comparative study of other single-phase non-isolated bidirectional converters suitability in DC microgrid design with respect to multiple BESS storage architecture for redundancy. The converters considered are buck-boost, Cascaded buck-boost, SEPIC and buck-boost with tapped inductor. They were operated under the same condition and compared using the following headings: SoC discharge rate, amount of discharge current, DC Bus voltage regulation, their capability and number of active and passive elements used. The cascaded half bridge shows the highest discharge current.
Graphène pour la nanoélectronique : de la croissance CVD jusqu'à la suparconductivité de proximité à deux dimensions

Cette these presente une etude du graphene complete depuis sa synthese par depot de vapeur chimique (CVD), la fonctionnalisation de sa surface, jusqu'aux mesures a basse temperatures des proprietes de supraconductivite. Je presente tout d'abord une nouvelle technique de croissance CVD basee sur une injection impulsionnelle du gaz precurseur en presence constante d'hydrogene. Cette technique permet de s'affranchir de la presence de multicouches de graphene aux points de nucleation, un type de defaut connu qui avait limite jusqu'a present les applications electroniques et optiques de ce materiau. Les dispositifs flexibles et optiquement transparents obtenus a partir de ce materiau presentent des caracteristiques ameliorees par rapport a l'etat de l'art notamment une homogeneite amelioree et une mobilite electronique depassant 8,000 cm^2/V/s. Un traitement chimique est ensuite introduit et nous montrons par diverses techniques microscopiques, spectroscopiques optiques et electroniques qu'il est possible de controler precisement la densite de defauts dans le graphene par voie chimique. Cette these s'acheve sur une etude a tres basse temperature (<1K) des proprietes de transport electronique d'un nouveau type de systemes base sur un reseau de plots d'etain depose sur un transistor en graphene. Ce type de systeme hybrides s'avere etre un systeme modele pour l'etude des transitions de phase quantique supra/isolant et supra/metal. Les resultats presentes sur les reseaux reguliers et dilues sont en bon accord avec les modeles theoriques predisant un etat metallique subsistant jusqu'a temperature nulle.
Mathematical Model of Microwave Devices on Resonant Tunneling Diodes for Practical Application in Radar and Electronic Systems

The paper presents results obtained after review and analysis of three mathematical models (Van der Pol, Lienard and FitzHugh-Nagumo) for investigation of dynamics of microwave radio-frequency devices based on a resonant tunneling diodes. A simple circuit of a non-autonomous radio-frequency device based on a resonant tunneling diode was proposed. A simplified mathematical model of Van der Pol was used. Mathematical modeling of electrical oscillation dynamics for the non-autonomous radio-frequency device based on a resonant tunneling diode was performed. Phase portraits of the non-autonomous radio-frequency device, time diagrams and amplitude spectra of its input and output signals in modes of fractional multiplication and division of frequency were obtained.
Taking on the “Dark Side”––Coping With Technostress

Technostress is stress that individuals experience due to their use of information technology. It is associated with critical workplace consequences including reduced productivity. While the negative consequences are well known, what is less understood is how individuals can cope with technostress to alleviate them. We report on two studies that explain how organizational IT users can cope with technostress. The first is a qualitative study conducted in the U.K., by interviewing thirty executives/knowledge workers. Here, we identified seven coping behaviors that individuals engage in, in response to technostress. The second is a survey of 846 U.S. employees who use IT in their workplace. Here, we examined the effects of these coping behaviors on the relationship between technostress creating conditions and the individual's IT-enabled productivity. We interpret our results to explain how employees and organizations can tackle technostress.
A Novel Link-Selection Strategy for DCSK-SWIPT Relay System with Buffer

Adaptive link selection for buffer-aided relaying can achieve significant performance gain compared with the conventional relaying with fixed transmission criterion. However, most of the existing link-selection strategies are designed based on perfect channel state information (CSI), which are very complex by requiring channel estimator. To solve this issue, in this paper, we investigate a buffer-aided differential chaos-shift-keying based simultaneous wireless information and power transfer (DCSK-SWIPT) relay system, where a decode-and-forward (DF) protocol is considered and the relay is equipped with a data buffer and an energy buffer. In particular, we propose a novel link-selection protocol for the proposed system based on harvested energy, data-buffer status and energy-shortage status, where the CSI is replaced by the harvested energy to avoid the channel estimation and the practical problem of the decoding cost at the relay is considered. Furthermore, the bit-error-rate (BER) and average-delay closed-form expressions of the proposed protocol are derived over multipath Rayleigh fading channels, which are validated via simulations. Numerical results demonstrate that the proposed protocol not only provides better BER performance than the conventional DCSK system and DCSK-SWIPT relay system but also achieves better BER performance and lower average delay in comparison to the conventional signal-to-noise-ratio-based-buffer-aided DCSK-SWIPT relay systems.