Search results for: robust switching vector

Authors: Gaddafi Sani Shehu, Tankut Yalcınoz, Abdullahi Bala Kunya

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Multilevel inverters such as flying capacitor, diode-clamped, and cascaded H-bridge inverters are very popular particularly in medium and high power applications. This paper focuses on a cascaded H-bridge module using a single direct current (DC) source in order to generate an 11-level output voltage. The noble approach reduces the number of switches and gate drivers, in comparison with a conventional method. The anticipated topology produces more accurate result with an isolation transformer at high switching frequency. Different modulation techniques can be used for the multilevel inverter, but this work features modulation techniques known as selective harmonic elimination (SHE).This modulation approach reduces the number of carriers with reduction in Switching Losses, Total Harmonic Distortion (THD), and thereby increasing Power Quality (PQ). Based on the simulation result obtained, it appears SHE has the ability to eliminate selected harmonics by chopping off the fundamental output component. The performance evaluation of the proposed cascaded multilevel inverter is performed using PSIM simulation package and THD of 0.94% is obtained.

Keywords: cascaded H-bridge multilevel inverter, power quality, selective harmonic elimination

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Authors: Christiana Gauci-Sciberras

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The first language (L1) could be used in foreign language teaching and learning as a pedagogical tool to scaffold new knowledge in the target language (TL) upon linguistic knowledge that the learner already has. In a bilingual context, code-switching between the two languages usually occurs in classrooms. One of the reasons for code-switching is because both languages are used for scaffolding new knowledge. This research paper aims to find out why both the L1 (Maltese) and the L2 (English) are used in the classroom of Mandarin Chinese as a foreign language (CFL) in the bilingual context of Malta. This research paper also aims to find out the learners’ perceptions of the use of a bilingual medium of instruction. Two research methods were used to collect qualitative data; semi-structured interviews with adult learners of Mandarin Chinese and lesson observations. These two research methods were used so that the data collected in the interviews would be triangulated with data collected in lesson observations. The L1 (Maltese) is the language of instruction mostly used. The teacher and the learners switch to the L2 (English) or to any other foreign language according to the need at a particular instance during the lesson.

Keywords: Chinese, bilingual, pedagogical purpose of L1 and L2, CFL acquisition

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Authors: Noureddine Henka, Sami Tazi, Mohamad Assaad

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The electrical grid is a highly intricate system designed to transfer electricity from production areas to consumption areas. The Transmission System Operator (TSO) is responsible for ensuring the efficient distribution of electricity and maintaining the grid's safety and quality. However, due to the increasing integration of intermittent renewable energy sources, there is a growing level of uncertainty, which requires a faster responsive approach. A potential solution involves the use of electrical segmentation, which involves creating coherence zones where electrical disturbances mainly remain within the zone. Indeed, by means of coherent electrical zones, it becomes possible to focus solely on the sub-zone, reducing the range of possibilities and aiding in managing uncertainty. It allows faster execution of operational processes and easier learning for supervised machine learning algorithms. Electrical segmentation can be applied to various applications, such as electrical control, minimizing electrical loss, and ensuring voltage stability. Since the electrical grid can be modeled as a graph, where the vertices represent electrical buses and the edges represent electrical lines, identifying coherent electrical zones can be seen as a clustering task on graphs, generally called community detection. Nevertheless, a critical criterion for the zones is their ability to remain resilient to the electrical evolution of the grid over time. This evolution is due to the constant changes in electricity generation and consumption, which are reflected in graph structure variations as well as line flow changes. One approach to creating a resilient segmentation is to design robust zones under various circumstances. This issue can be represented through a multiplex graph, where each layer represents a specific situation that may arise on the grid. Consequently, resilient segmentation can be achieved by conducting community detection on this multiplex graph. The multiplex graph is composed of multiple graphs, and all the layers share the same set of vertices. Our proposal involves a model that utilizes a unified representation to compute a flattening of all layers. This unified situation can be penalized to obtain (K) connected components representing the robust electrical segmentation clusters. We compare our robust segmentation to the segmentation based on a single reference situation. The robust segmentation proves its relevance by producing clusters with high intra-electrical perturbation and low variance of electrical perturbation. We saw through the experiences when robust electrical segmentation has a benefit and in which context.

Keywords: community detection, electrical segmentation, multiplex graph, power grid

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation

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Authors: Y. Kobori, S. Tanaka, N. Tsukiji, N. Takai, H. Kobayashi

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This paper proposes two kinds of new single-inductor dual-output (SIDO) DC-DC switching converters with ripple-based hysteretic control. First SIDO converters of type 1 utilize the triangular signal generated by the CR-circuit connected across the inductor. This triangular signal is used for generating the PWM signal instead of the saw-tooth signal used in the conventional converters. Second SIDO converters of type 2 utilize the triangular signal generated by the CR-circuit connected across the voltage error amplifier. This paper describes circuit topologies, Operation principles, simulation results and experimental results of the proposed SIDO converters. In simulation results of both type of SIDO converters, static output voltage ripples are less than 5mVpp and over/under shoots of the dynamic load regulations for the output current step are less than +/- 10mV. In experimental results of single output converter of type 2, static output voltage ripples are about 20mVpp. Output ripples of SIDO type 1 converter are about 80mVpp.

Keywords: DC-DC converter, switching converter, SIDO converter, hysteretic control, ripple-based control

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Authors: Mohamed Raouf Benmakrelouf, Joseph Rynkiewicz

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Targeted maximum likelihood estimation (TMLE) is well-established method for causal effect estimation with desirable statistical properties. TMLE is a doubly robust maximum likelihood based approach that includes a secondary targeting step that optimizes the target statistical parameter. A causal interpretation of the statistical parameter requires assumptions of the Rubin causal framework. The causal effect of binary variable, E, on outcomes, Y, is defined in terms of comparisons between two potential outcomes as E[YE=1 − YE=0]. Our aim in this paper is to present an adaptation of TMLE methodology to estimate the causal effect of a non-binary categorical variable, providing a large application. We propose coding on the initial data in order to operate a binarization of the interest variable. For each category, we get a transformation of the non-binary interest variable into a binary variable, taking value 1 to indicate the presence of category (or group of categories) for an individual, 0 otherwise. Such a dummy variable makes it possible to have a pair of potential outcomes and oppose a category (or a group of categories) to another category (or a group of categories). Let E be a non-binary interest variable. We propose a complete disjunctive coding of our variable E. We transform the initial variable to obtain a set of binary vectors (dummy variables), E = (Ee : e ∈ {1, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when its category is not present, and the value of 1 when its category is present, which allows to compute a pairwise-TMLE comparing difference in the outcome between one category and all remaining categories. In order to illustrate the application of our strategy, first, we present the implementation of TMLE to estimate the causal effect of non-binary variable on outcome using simulated data. Secondly, we apply our TMLE adaptation to survey data from the French Political Barometer (CEVIPOF), to estimate the causal effect of education level (A five-level variable) on a potential vote in favor of the French extreme right candidate Jean-Marie Le Pen. Counterfactual reasoning requires us to consider some causal questions (additional causal assumptions). Leading to different coding of E, as a set of binary vectors, E = (Ee : e ∈ {2, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when the first category (reference category) is present, and the value of 1 when its category is present, which allows to apply a pairwise-TMLE comparing difference in the outcome between the first level (fixed) and each remaining level. We confirmed that the increase in the level of education decreases the voting rate for the extreme right party.

Keywords: statistical inference, causal inference, super learning, targeted maximum likelihood estimation

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Authors: Alexandra Monteiro, K. Bousson, Fernando J. O. Moreira, Ricardo Reis

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Fixed-wing flying vehicles are usually controlled by means of control surfaces such as elevators, ailerons, and rudders. The failure of these systems may lead to severe or even fatal crashes. These failures resulted in increased popularity for research activities on propulsion control in the last decades. The present work deals with a hybrid control architecture in which the propulsion-controlled vehicle maintains its traditional control surfaces, addressing the issue of robust lateral-directional dynamics control. The challenges stem from the parameter uncertainties in the stability and control derivatives and some unknown terms in the flight dynamics model. Two approaches are implemented and tested: linear quadratic regulation with robustness characteristics and H∞ control. The problem is centered on roll-yaw controller design with full state-feedback, which is able to deal with a standalone propulsion control mode as well as a hybrid mode combining both propulsion control and conventional control surface concepts while maintaining the original flight maneuverability characteristics. The results for both controllers emphasized very good control performances; however, the H∞ controller showed higher stabilization rates and robustness albeit with a slightly higher control magnitude than using the linear quadratic regulator.

Keywords: robust propulsion control, h-infinity control, lateral-directional flight dynamics, parameter uncertainties

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Authors: Rafik Djemili, Hocine Bourouba, M. C. Amara Korba

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In this paper, we present a method in order to classify EEG signals for Brain-Computer Interfaces (BCI). EEG signals are first processed by means of spectral estimation methods to derive reliable features before classification step. Spectral estimation methods used are standard periodogram and the periodogram calculated by the Welch method; both methods are compared with Logarithm of Band Power (logBP) features. In the method proposed, we apply Linear Discriminant Analysis (LDA) followed by Support Vector Machine (SVM). Classification accuracy reached could be as high as 85%, which proves the effectiveness of classification of EEG signals based BCI using spectral methods.

Keywords: brain-computer interface, motor imagery, electroencephalogram, linear discriminant analysis, support vector machine

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Authors: Ibrahim Djelloul Berkane

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A survey was conducted to assess the presence of the virus in Citrus tristeza one of the main citrus regions of Algeria, namely the Chlef region, using the technique of Direct Tissue Print Immunoprinting Assay (DTBIA) and the Double Sandwich ELISA antibodies. A nursery citrus, lumber yards, and commercial orchards, which are the main varieties cultivated citrus were subjected to samples collected samples for laboratory analysis. 0.91% of the plants tested orchards were infected with CTV, while no positive case was detected at the nursery the yard, however, it is reported that an alarming rate of 10,5% of orchards tested at the common Chettia were infected with tristeza virus. The investigation was launched to identify the vector species tristeza revealed the presence of a vector is important Aphis gossypii.

Keywords: aphis, chlef, citrus, DAS-ELISA, DTBIA, tristeza

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Authors: Muhammad Kamran Asif

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MPLS stands for Multi-Protocol Label Switching. It is the technology which replaces ATM (Asynchronous Transfer Mode) and frame relay. In this paper, we have designed a full fledge small scale MPLS based service provider network core network model, which provides communication services (e.g. voice, video and data) to the customer more efficiently using label switching technique. Using MPLS VPN provides security to the customers which are either on LAN or WAN. It protects its single customer sites from being attacked by any intruder from outside world along with the provision of concept of extension of a private network over an internet. In this paper, we tried to implement a service provider network using minimum available resources i.e. five 3800 series CISCO routers comprises of service provider core, provider edge routers and customer edge routers. The customers on the one end of the network (customer side) is capable of sending any kind of data to the customers at the other end using service provider cloud which is MPLS VPN enabled. We have also done simulation and emulation for the model using GNS3 (Graphical Network Simulator-3) and achieved the real time scenarios. We have also deployed a NMS system which monitors our service provider cloud and generates alarm in case of any intrusion or malfunctioning in the network. Moreover, we have also provided a video help desk facility between customers and service provider cloud to resolve the network issues more effectively.

Keywords: MPLS, VPN, NMS, ATM, asynchronous transfer mode

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Authors: Ali Mashayekh, Mahdiye Khorasani, Thomas Weyh

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The tendency to use the Battery-Electric vehicle (BEV) for the low and medium driving range or even high driving range has been growing more and more. As a result, higher safety, reliability, and durability of the battery pack as a component of electric vehicles, which has a great share of cost and weight of the final product, are the topics to be considered and investigated. Battery aging can be considered as the predominant factor regarding the reliability and durability of BEV. To better understand the aging process, offline battery characterization has been widely used, which is time-consuming and needs very expensive infrastructures. This paper presents the substitute method for the conventional battery characterization methods, which is based on battery Modular Multilevel Management (BM3). According to this Topology, the battery cells can be drained and charged concerning their capacity, which allows varying battery pack structures. Due to the integration of the power electronics, the output voltage of the battery pack is no longer fixed but can be dynamically adjusted in small steps. In other words, each cell can have three different states, namely series, parallel, and bypass in connection with the neighbor cells. With the help of MATLAB/Simulink and by using the BM3 modules, the battery string model is created. This model allows us to switch two cells with the different SoC as parallel, which results in the internal balancing of the cells. But if the parallel switching lasts just for a couple of ms, we can have a perturbation pulse which can stimulate the cells out of the relaxation phase. With the help of modeling the voltage response pulse of the battery, it would be possible to characterize the cell. The Online EIS method, which is discussed in this paper, can be a robust substitute for the conventional battery characterization methods.

Keywords: battery characterization, SoH estimation, RLS, BEV

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Authors: W. M. Ng, O. B. Iskender, L. Simonini, J. M. Gonzalez

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A multitude of factors, including mechanical imperfections of the deployment system and separation instance of satellites from launchers, oftentimes results in highly uncontrolled initial tumbling motion immediately after deployment. In particular, small satellites which are characteristically launched as a piggyback to a large rocket, are generally allocated a large time window to complete detumbling within the early orbit phase. Because of the saturation risk of the actuators, current algorithms are conservative to avoid draining excessive power in the detumbling phase. This work aims to enable time-optimal switching of control modes during the early phase, reducing the time required to transit from launch to sun-pointing mode for power budget conscious satellites. This assumes the usage of B-dot controller for detumbling and PD controller for pointing. Nonlinear Euler's rotation equations are used to represent the attitude dynamics of satellites and Commercial-off-the-shelf (COTS) reaction wheels and magnetorquers are used to perform the manoeuver. Simulation results will be based on a spacecraft attitude simulator and the use case will be for multiple orbits of launch deployment general to Low Earth Orbit (LEO) satellites.

Keywords: attitude control, detumbling, small satellites, spacecraft autonomy, time optimal control

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Authors: Abderazak Guettaf

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The mathematical models of the physical phenomena interacting in inductive plasma were described by the physics equations of the continuous mediums. A 3D model based on magnetic potential vector and electric scalar potential (A, V) formulation is used. The finished volume method is applied to electromagnetic equation, to obtain the field distribution inside the plasma. The numerical results of the method developed on a basic model designed starting from a real three-dimensional model were exposed. From the mathematical model 3D spreading assumptions and boundary conditions, we evaluated the electric field in the load and we have developed a numerical code made under the MATLAB environment, all verifying the effectiveness and validity of this code.

Keywords: electric field, 3D magnetic potential vector and electric scalar potential (A, V) formulation, finished volumes, annular plasma

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Authors: Bessaad Taieb, Benbouali Abderrahmen

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Fuzzy controllers are a powerful tool for controlling complex processes. However, its robustness capacity remains moderately limited because it loses its property for large ranges of parametric variations. In this paper, the proposed control method is designed, based on a fuzzy adaptive controller used as a remedy for this problem. For increase the robustness of the vector control and to maintain the performance of the five-phase asynchronous machine despite the presence of disturbances (variation of rotor resistance, rotor inertia variations, sudden variations in the load etc.), by applying the method of behaviour model control (BMC). The results of simulation show that the fuzzy adaptive control provides best performance and has a more robustness as the fuzzy (FLC) and as a conventional (PI) controller.

Keywords: fuzzy adaptive control, behaviour model control, vector control, five-phase asynchronous machine

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Authors: A. Roomy

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The dramatic rise in violence against game officials has affected all levels of sports including recreational, amateur, and professional sports. One way to combat this rise in violence is through the creation of laws specifically aimed at preventing and punishing this kind of violence. This paper will use related legal cases as a starting point to explore possible ways of better protecting the safety of game officials. It will do this by looking at relevant cases, related legal issues, and two specific ways of reducing violence against game officials. In closing, it will be argued that there needs to be a more robust legal approach with emphasis on criminal and civil penalties for assault and battery, and a more comprehensive social approach with emphasis on raising social awareness on the need to protect game officials from violence.

Keywords: game officials, legal issues, safety, violence

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Authors: Muhammad Sohail Sajid, Qurat-ul-Ain, Zafar Iqbal, Muhammad Nisar Khan, Asma Kausar, Adil Ejaz

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Rickettsiosis, caused by a Spotted Fever Group Rickettsiae (SFGR), is considered as an emerging infectious disease from public and veterinary perspective. The present study reports distribution of SFGR in the host (buffalo and cattle) and vector (ticks) population determined through gene specific amplification through PCR targeting outer membrane protein (ompA). Tick and blood samples were collected using standard protocols through convenient sampling from district Faisalabad. Ticks were dissected to extract salivary glands (SG). Blood and tick SG pools were subjected to DNA extraction and amplification of ompA using PCR. Overall prevalence of SFGR was reported as 21.5% and 33.6 % from blood and ticks, respectively. Hyalomma anatolicum was more prevalent tick associated with SFGR as compared to Rhipicephalus sp. Higher prevalence of SFGR was reported in cattle (25%) population as compared to that of buffalo (17.07%). On seasonal basis, high SFGR prevalence was recorded during spring season (48.1%, 26.32%, 17.76%) as compared to winter (27.9%, 21.43%, 15.38%) in vector and host (cattle and buffalo respectively) population. Sequencing analysis indicated that rickettsial endo-symbionts were associated with ticks of the study area. These results provided baseline information about the prevalence of SFGR in vector and host population.

Keywords: Rickettsia, livestock, polymerase chain reaction, sequencing, ticks, vectors

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Authors: Sandeep Singh

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In this article, two classes of iterative schemes are proposed for approximating solutions of nonlinear systems of equations whose orders of convergence are six and eight respectively. Sixth order scheme requires the evaluation of two vector-functions, two first Fr'echet derivatives and three matrices inversion per iteration. This three-step sixth-order method is further extended to eighth-order method which requires one more step and the evaluation of one extra vector-function. Moreover, computational efficiency is compared with some other recently published methods in which we found, our methods are more efficient than existing numerical methods for higher and medium size nonlinear system of equations. Numerical tests are performed to validate the proposed schemes.

Keywords: Nonlinear systems, Computational complexity, order of convergence, Jarratt-type scheme

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Authors: Randa M. Ali, Naguiba F. Loutfy, Osama M. Awad

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Background: Leishmaniasis is a worldwide disease, affecting 88 countries, it is estimated that about 350 million people are at risk of leishmaniasis. Overall prevalence is 12 million people with annual mortality of about 60,000. Annual incidence is 1,500,000 cases of cutaneous leishmaniasis (CL) worldwide and half million cases of visceral Leishmaniasis (VL). Objectives: The objective of this study was to assess primary health care physicians knowledge (PHP) and attitude about leishmaniasis and to assess awareness of local inhabitants about the disease and its vector in four areas in west Alexandria, Egypt. Methods: This study was a cross sectional survey that was conducted in four PHC units in west Alexandria. All physicians currently working in these units during the study period were invited to participate in the study, only 20 PHP completed the questionnaire. 60 local inhabitant were selected randomly from the four areas of the study, 15 from each area; Data was collected through two different specially designed questionnaires. Results: 11(55%) percent of the physicians had satisfactory knowledge, they answered more than 9 (60%) questions out of a total 14 questions about leishmaniasis and sandfly. The second part of the questionnaire is concerned with attitude of the primary health care physicians about leishmaniasis, 17 (85%) had good attitude and 3 (15%) had poor attitude. The second questionnaire showed that the awareness of local inhabitants about leishmaniasis and sandly as a vector of the disease is poor and needs to be corrected. Most of the respondents (90%) had not heard about leishmaniasis, Only 3 (5%) of the interviewed inhabitants said they know sandfly and its role in transmission of leishmaniasis. Conclusions: knowledge and attitudes of physicians are acceptable. However, there is, room for improvement and could be done through formal training courses and distribution of guidelines. In addition to raising the awareness of primary health care physicians about the importance of early detection and notification of cases of lesihmaniasis. Moreover, health education for raising awareness of the public regarding the vector and the disease is necessary because related studies have demonstrated that if the inhabitants do not perceive mosquitoes to be responsible for diseases such as malaria they do not take enough measures to protect themselves against the vector.

Keywords: leishmaniasis, PHP, knowledge, attitude, local inhabitants

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Authors: Andrey V. Timofeev, Viktor M. Denisov

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A robust sequential nonparametric method is proposed for adaptation to background noise parameters for real-time. The distribution of background noise was modelled like to Huber contamination mixture. The method is designed to operate as an adaptation-unit, which is included inside a detection subsystem of an integrated multichannel monitoring system. The proposed method guarantees the given size of a nonasymptotic confidence set for noise parameters. Properties of the suggested method are rigorously proved. The proposed algorithm has been successfully tested in real conditions of a functioning C-OTDR monitoring system, which was designed to monitor railways.

Keywords: guaranteed estimation, multichannel monitoring systems, non-asymptotic confidence set, contamination mixture

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Authors: Jay Prakash Singh

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The aim of the present paper is to study properties of Quasi conformally flat LP-Sasakian manifolds with a coefficient α. In this paper, we prove that a Quasi conformally flat LP-Sasakian manifold M (n > 3) with a constant coefficient α is an η−Einstein and in a quasi conformally flat LP-Sasakian manifold M (n > 3) with a constant coefficient α if the scalar curvature tensor is constant then M is of constant curvature.

Keywords: LP-Sasakian manifolds, quasi-conformal curvature tensor, concircular vector field, torse forming vector field, Einstein manifold

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Authors: Zain Ul Abdin, Mirza Aizaz Asim, Rao Sohail Ahmad Khan, Luqman Amrao, Fiaz Hussain, Hasooba Hira, Saqi Kosar Abbas

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The success of Integrated vector management programmes mainly depends on the correct identification of insect vector species involved in vector borne diseases. Based on molecular data the most important insect species involved as vectors for Zoonotic diseases in Pakistan were identified. The precise and accurate identification of such type of organism is only possible through molecular based techniques like “DNA barcoding”. Morphological species identification in insects at any life stage, is very challenging, therefore, DNA barcoding was used as a tool for rapid and accurate species identification in a wide variety of taxa across the globe and parallel studies revealed that DNA barcoding data can be effectively used in resolving taxonomic ambiguities, detection of cryptic diversity, invasion biology, description of new species etc. A comprehensive survey was carried out for the collection of insects (both adult and immature stages) in district Faisalabad, Pakistan and their DNA was extracted and mitochondrial cytochrome oxidase subunit I (COI-59) barcode sequences was used for molecular identification of immature and adult life stage.This preliminary research work opens new frontiers for developing sustainable insect vectors management programmes for saving lives of mankind from fatal diseases.

Keywords: zoonotic diseases, cytochrome oxidase, and insect vectors, CO1

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Authors: Ghada A. Alfattni

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Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates. 

Keywords: imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour

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Authors: Macdonald Kanyangale, Sandram Naluso

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Globally, researchers have struggled over time to adequately define the notion of health system to inform research. This study is significant because it proposes an integrative framework for a robust definition of the health system. The objective of this article is to examine major pitfalls in definitions of health system used in prior literature and implications of these for research and management. The study used methodological steps of a scoping review proposed by Arksey and O'Malley to identify and examine 24 definitions of a health system in articles selected from six databases and web search engines. Thematic analysis was used to delineate and categorise definitional pitfalls into broader themes. There are a plethora of five major pitfalls in the extant definitions of a health system which may easily scupper any unsuspecting researcher if not avoided or addressed in research. These definitional pitfalls are reductionist assumptions which ignore dynamic and complex connections, overly wide boundary and lack of specification of levels in a health system, and limited focus on process in a health system. In addition, there is the tendency of treating different components of the health system as equal and simplifying of the ontological complexity of the health system. Future scholars are advised to avoid or address the identified five major pitfalls if they are to develop robust definitions of an HS. The use of an integrative framework for a robust definition of a health system is recommended, while implications of the pitfalls are discussed as a basis and catalyst for complexity-informed research and managing interactively.

Keywords: complexity management, health system, pitfalls, reductionism, research

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Authors: Rumana Ali

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The presence of nonlinear and power electronic switching devices produce distorted output and harmonics into the system. This paper presents a technique to analyze harmonics using digital series oscilloscope (DSO). In power distribution system further measurements are done by DSO, and the waveforms are analyzed using FFT program. The results of this proposed work are helpful for the investigator to install an appropriate compensating device to mitigate the harmonics, in turn, improve the power quality. This case study is carried out at AIT Chikmagalur. It is done as a starting step towards the improvement of energy efficiency at AIT Chikmagalur, and with an overall aim of reducing the electricity bill with a complete energy audit of the institution. Strategies were put forth to reach the above objective: The following strategies were proposed to be implemented to analyze the power quality in EEE department of the institution. Strategy 1: The power factor has to be measured using the energy meter. Power factor improvement may reduce the voltage drop in lines. This brings the voltages at the socket in the labs closer to the nominal voltage of 230V, and thus power quality improves. Strategy 2: The harmonics at the power inlet has to be measured by means of a DSO. The DSO waveform is analyzed using FFT to know the percentage harmonic up to the 13th harmonics of 50Hz. Reduction in the harmonics in the inlet of the EEE department may reduce line losses and therefore reduces energy bill to the institution.

Keywords: harmonic analysis, energy bill, power quality, electronic switching devices

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Authors: Harsh Thakkar, Ganesh Iyer

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In this paper, we survey various user-centered or context-based biomedical health information retrieval systems. We present and discuss the performance of systems submitted in CLEF eHealth 2014 Task 3 for this purpose. We classify and focus on comparing the two most prevalent retrieval models in biomedical information retrieval namely: Language Model (LM) and Vector Space Model (VSM). We also report on the effectiveness of using external medical resources and ontologies like MeSH, Metamap, UMLS, etc. We observed that the LM based retrieval systems outperform VSM based systems on various fronts. From the results we conclude that the state-of-art system scores for MAP was 0.4146, P@10 was 0.7560 and NDCG@10 was 0.7445, respectively. All of these score were reported by systems built on language modeling approaches.

Keywords: clinical document retrieval, concept-based information retrieval, query expansion, language models, vector space models

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Authors: Dihia Sidi Ahmed, Hiba Mili

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In the current context of European and global energy transition and the accelerated integration of renewable energies, the transition to electric vehicles with V2X (Vehicle-to-anything) charging options is favored to enhance the power grid and to serve as an energy supply in peak demand periods. Regarding the fast development of EV charging infrastructures, a cost-effective and efficient solution is required to meet OEM's (Original Equipment Manufacturers) needs. In this context, a single-phase 7.4 kW bidirectional on-board charger with G2V, V2G and V2L capabilities has been developed to support faster charging. The proposed architecture consists of two power stages. A Totem Pole PFC stage works as a rectifier in G2V with a unity power factor and as an inverter in V2G and V2L. The second stage is a CLLLC resonant converter selected to achieve higher energy efficiency, ZVS and ZCS and cost-effectiveness. SiC technology is used for switching devices to maximize power efficiency by lowering switching losses and to improve power density by minimizing the size of filters and passive components. Pulse frequency modulation (PWM) control is used for the Totem Pole PFC and pulse frequency modulation (PFM) control is used for the CLLC stage to control the stage gain in both energy transfer directions. In the context of validating the topology, this paper elaborates the simulation and the performance evaluation of the first power stage in the Matlab/Simulink environment.

Keywords: V2G, V2X, OBC, CLLC.

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Authors: Kyoung-Jin Joo, In-Gun Kim, Hyun-Seok Hong, Dong-Woo Kang, Ju Lee

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Recently, the permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) that can be substituted for the induction motor has been studying because of the needs of the development of the premium high efficiency motor for the minimum energy performance standard (MEPS). PMa-SynRM is required to the speed and position information for motor speed and torque controls. However, to apply the sensors has many problems that are sensor mounting space shortage and additional cost, etc. Therefore, in this paper, speed-sensorless control based on model reference adaptive system (MRAS) is introduced to eliminate the sensor. The sensorless method is constructed in a reference model as standard and an adaptive model as the state observer. The proposed algorithm is verified by the simulation.

Keywords: PMa-SynRM, sensorless control, robust estimation, MRAS method

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Authors: Ender Su, Kai Wen Wong, I-Ling Ju, Ya-Ling Wang

Abstract:

In this study, the systemic risk change of Taiwan’s banking sector is analyzed during the financial crisis. The risk expose of each financial institutions to the whole Taiwan banking systemic risk or vice versa under financial distress are measured by conditional Value-at-Risk (CoVaR) and conditional coherent expected shortfall (CoES). The CoVaR and CoES are estimated by using vector quantile autoregression (MVMQ-CaViaR) with the daily stock returns of each banks included domestic and foreign banks in Taiwan. The daily in-sample data covered the period from 05/20/2002 to 07/31/2007 and the out-of-sample period until 12/31/2013 spanning the 2008 U.S. subprime crisis, 2010 Greek debt crisis, and post risk duration. All banks in Taiwan are categorised into several groups according to their size of market capital, leverage and domestic/foreign to find out what the extent of changes of the systemic risk as the risk changes between the individuals in the bank groups and vice versa. The final results can provide a guidance to financial supervisory commission of Taiwan to gauge the downside risk in the system of financial institutions and determine the minimum capital requirement hold by financial institutions due to the sensibility changes in CoVaR and CoES of each banks.

Keywords: bank financial distress, vector quantile autoregression, CoVaR, CoES

Procedia PDF Downloads 352

Authors: Muna Tabuni

Abstract:

The paper contains an investigation of the notion of Q algebras. A brief introduction to quantum mechanics is given, in that systems the state defined by a vector in a complex vector space H which have Hermitian inner product property. H may be finite or infinite-dimensional. In quantum mechanics, operators must be hermitian. These facts are saved by Lie algebra operators but not by those of quantum algebras. A Hilbert space H consists of a set of vectors and a set of scalars. Lie group is a differentiable topological space with group laws given by differentiable maps. A Lie algebra has been introduced. Q-algebra has been defined. A brief introduction to BCI-algebra is given. A BCI sub algebra is introduced. A brief introduction to BCK=BCH-algebra is given. Every BCI-algebra is a BCH-algebra. Homomorphism maps meanings are introduced. Homomorphism maps between two BCK algebras are defined. The mathematical formulations of quantum mechanics can be expressed using the theory of unitary group representations. A generalization of Q algebras has been introduced, and their properties have been considered. The Q- quantum algebra has been studied, and various examples have been given.

Keywords: Q-algebras, BCI, BCK, BCH-algebra, quantum mechanics

Procedia PDF Downloads 178

Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

Abstract:

To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

Procedia PDF Downloads 293