Search results for: electrical networks.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2586

Search results for: electrical networks.

336 Voltage Problem Location Classification Using Performance of Least Squares Support Vector Machine LS-SVM and Learning Vector Quantization LVQ

Authors: Khaled Abduesslam. M, Mohammed Ali, Basher H Alsdai, Muhammad Nizam, Inayati

Abstract:

This paper presents the voltage problem location classification using performance of Least Squares Support Vector Machine (LS-SVM) and Learning Vector Quantization (LVQ) in electrical power system for proper voltage problem location implemented by IEEE 39 bus New- England. The data was collected from the time domain simulation by using Power System Analysis Toolbox (PSAT). Outputs from simulation data such as voltage, phase angle, real power and reactive power were taken as input to estimate voltage stability at particular buses based on Power Transfer Stability Index (PTSI).The simulation data was carried out on the IEEE 39 bus test system by considering load bus increased on the system. To verify of the proposed LS-SVM its performance was compared to Learning Vector Quantization (LVQ). The results showed that LS-SVM is faster and better as compared to LVQ. The results also demonstrated that the LS-SVM was estimated by 0% misclassification whereas LVQ had 7.69% misclassification.

Keywords: IEEE 39 bus, Least Squares Support Vector Machine, Learning Vector Quantization, Voltage Collapse.

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335 Effects of Polluted Water on the Metallic Water Pipelines

Authors: Abdul-Khaliq M. Hussain, Bashir A. Tantosh, El-Sadeg A. Abdalla

Abstract:

Corrosion of metallic water pipelines buried below ground surface is a function of the nature of the surrounding soil and groundwater. This gives the importance of knowing the physical and chemical characteristics of the pipe-s surrounding environment. The corrosion of externally – unprotected metallic water pipelines, specially ductile iron pipes, in localities with aggressive soil conditions is becoming a significant problem. Anticorrosive protection for metallic water pipelines, their fittings and accessories is very important, because they may be attached by corrosion with time. The tendency of a metallic substrate to corrode is a function of the surface characteristics of the metal and of the metal/protective film interface, the physical, electrical and electrochemical properties of the film, and the nature of the environment in which the pipelines system is placed. In this work the authors have looked at corrosion problems of water pipelines and their control. The corrosive properties of groundwater and soil environments are reviewed, and parameters affecting corrosion are discussed. The purpose of this work is to provide guidelines for materials selection in water and soil environments, and how the water pipelines can be protected against metallic corrosion.

Keywords: Corrosion, Drinking Water, Metallic WaterPipelines, Polluted Water.

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334 Connected Vertex Cover in 2-Connected Planar Graph with Maximum Degree 4 is NP-complete

Authors: Priyadarsini P. L. K, Hemalatha T.

Abstract:

This paper proves that the problem of finding connected vertex cover in a 2-connected planar graph ( CVC-2 ) with maximum degree 4 is NP-complete. The motivation for proving this result is to give a shorter and simpler proof of NP-Completeness of TRA-MLC (the Top Right Access point Minimum-Length Corridor) problem [1], by finding the reduction from CVC-2. TRA-MLC has many applications in laying optical fibre cables for data communication and electrical wiring in floor plans.The problem of finding connected vertex cover in any planar graph ( CVC ) with maximum degree 4 is NP-complete [2]. We first show that CVC-2 belongs to NP and then we find a polynomial reduction from CVC to CVC-2. Let a graph G0 and an integer K form an instance of CVC, where G0 is a planar graph and K is an upper bound on the size of the connected vertex cover in G0. We construct a 2-connected planar graph, say G, by identifying the blocks and cut vertices of G0, and then finding the planar representation of all the blocks of G0, leading to a plane graph G1. We replace the cut vertices with cycles in such a way that the resultant graph G is a 2-connected planar graph with maximum degree 4. We consider L = K -2t+3 t i=1 di where t is the number of cut vertices in G1 and di is the number of blocks for which ith cut vertex is common. We prove that G will have a connected vertex cover with size less than or equal to L if and only if G0 has a connected vertex cover of size less than or equal to K.

Keywords: NP-complete, 2-Connected planar graph, block, cut vertex

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333 An Enhanced SAR-Based Tsunami Detection System

Authors: Jean-Pierre Dubois, Jihad S. Daba, H. Karam, J. Abdallah

Abstract:

Tsunami early detection and warning systems have proved to be of ultimate importance, especially after the destructive tsunami that hit Japan in March 2012. Such systems are crucial to inform the authorities of any risk of a tsunami and of the degree of its danger in order to make the right decision and notify the public of the actions they need to take to save their lives. The purpose of this research is to enhance existing tsunami detection and warning systems. We first propose an automated and miniaturized model of an early tsunami detection and warning system. The model for the operation of a tsunami warning system is simulated using the data acquisition toolbox of Matlab and measurements acquired from specified internet pages due to the lack of the required real-life sensors, both seismic and hydrologic, and building a graphical user interface for the system. In the second phase of this work, we implement various satellite image filtering schemes to enhance the acquired synthetic aperture radar images of the tsunami affected region that are masked by speckle noise. This enables us to conduct a post-tsunami damage extent study and calculate the percentage damage. We conclude by proposing improvements to the existing telecommunication infrastructure of existing warning tsunami systems using a migration to IP-based networks and fiber optics links.

Keywords: Detection, GIS, GSN, GTS, GPS, speckle noise, synthetic aperture radar, tsunami, wiener filter.

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332 A Trainable Neural Network Ensemble for ECG Beat Classification

Authors: Atena Sajedin, Shokoufeh Zakernejad, Soheil Faridi, Mehrdad Javadi, Reza Ebrahimpour

Abstract:

This paper illustrates the use of a combined neural network model for classification of electrocardiogram (ECG) beats. We present a trainable neural network ensemble approach to develop customized electrocardiogram beat classifier in an effort to further improve the performance of ECG processing and to offer individualized health care. We process a three stage technique for detection of premature ventricular contraction (PVC) from normal beats and other heart diseases. This method includes a denoising, a feature extraction and a classification. At first we investigate the application of stationary wavelet transform (SWT) for noise reduction of the electrocardiogram (ECG) signals. Then feature extraction module extracts 10 ECG morphological features and one timing interval feature. Then a number of multilayer perceptrons (MLPs) neural networks with different topologies are designed. The performance of the different combination methods as well as the efficiency of the whole system is presented. Among them, Stacked Generalization as a proposed trainable combined neural network model possesses the highest recognition rate of around 95%. Therefore, this network proves to be a suitable candidate in ECG signal diagnosis systems. ECG samples attributing to the different ECG beat types were extracted from the MIT-BIH arrhythmia database for the study.

Keywords: ECG beat Classification; Combining Classifiers;Premature Ventricular Contraction (PVC); Multi Layer Perceptrons;Wavelet Transform

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331 An Improved Particle Swarm Optimization Technique for Combined Economic and Environmental Power Dispatch Including Valve Point Loading Effects

Authors: Badr M. Alshammari, T. Guesmi

Abstract:

In recent years, the combined economic and emission power dispatch is one of the main problems of electrical power system. It aims to schedule the power generation of generators in order to minimize cost production and emission of harmful gases caused by fossil-fueled thermal units such as CO, CO2, NOx, and SO2. To solve this complicated multi-objective problem, an improved version of the particle swarm optimization technique that includes non-dominated sorting concept has been proposed. Valve point loading effects and system losses have been considered. The three-unit and ten-unit benchmark systems have been used to show the effectiveness of the suggested optimization technique for solving this kind of nonconvex problem. The simulation results have been compared with those obtained using genetic algorithm based method. Comparison results show that the proposed approach can provide a higher quality solution with better performance.

Keywords: Power dispatch, valve point loading effects, multiobjective optimization, Pareto solutions.

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330 MPPT Operation for PV Grid-connected System using RBFNN and Fuzzy Classification

Authors: A. Chaouachi, R. M. Kamel, K. Nagasaka

Abstract:

This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.

Keywords: MPPT, neuro-fuzzy, RBFN, grid-connected, photovoltaic.

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329 Malware Beaconing Detection by Mining Large-scale DNS Logs for Targeted Attack Identification

Authors: Andrii Shalaginov, Katrin Franke, Xiongwei Huang

Abstract:

One of the leading problems in Cyber Security today is the emergence of targeted attacks conducted by adversaries with access to sophisticated tools. These attacks usually steal senior level employee system privileges, in order to gain unauthorized access to confidential knowledge and valuable intellectual property. Malware used for initial compromise of the systems are sophisticated and may target zero-day vulnerabilities. In this work we utilize common behaviour of malware called ”beacon”, which implies that infected hosts communicate to Command and Control servers at regular intervals that have relatively small time variations. By analysing such beacon activity through passive network monitoring, it is possible to detect potential malware infections. So, we focus on time gaps as indicators of possible C2 activity in targeted enterprise networks. We represent DNS log files as a graph, whose vertices are destination domains and edges are timestamps. Then by using four periodicity detection algorithms for each pair of internal-external communications, we check timestamp sequences to identify the beacon activities. Finally, based on the graph structure, we infer the existence of other infected hosts and malicious domains enrolled in the attack activities.

Keywords: Malware detection, network security, targeted attack.

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328 Development of a Neural Network based Algorithm for Multi-Scale Roughness Parameters and Soil Moisture Retrieval

Authors: L. Bennaceur Farah, I. R. Farah, R. Bennaceur, Z. Belhadj, M. R. Boussema

Abstract:

The overall objective of this paper is to retrieve soil surfaces parameters namely, roughness and soil moisture related to the dielectric constant by inverting the radar backscattered signal from natural soil surfaces. Because the classical description of roughness using statistical parameters like the correlation length doesn't lead to satisfactory results to predict radar backscattering, we used a multi-scale roughness description using the wavelet transform and the Mallat algorithm. In this description, the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each having a spatial scale. A second step in this study consisted in adapting a direct model simulating radar backscattering namely the small perturbation model to this multi-scale surface description. We investigated the impact of this description on radar backscattering through a sensitivity analysis of backscattering coefficient to the multi-scale roughness parameters. To perform the inversion of the small perturbation multi-scale scattering model (MLS SPM) we used a multi-layer neural network architecture trained by backpropagation learning rule. The inversion leads to satisfactory results with a relative uncertainty of 8%.

Keywords: Remote sensing, rough surfaces, inverse problems, SAR, radar scattering, Neural networks and Fractals.

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327 Conventional Four Steps Travel Demand Modeling for Kabul New City

Authors: Ahmad Mansoor Stanikzai, Yoshitaka Kajita

Abstract:

This research is a very essential towards transportation planning of Kabul New City. In this research, the travel demand of Kabul metropolitan area (Existing and Kabul New City) are evaluated for three different target years (2015, current, 2025, mid-term, 2040, long-term). The outcome of this study indicates that, though currently the vehicle volume is less the capacity of existing road networks, Kabul city is suffering from daily traffic congestions. This is mainly due to lack of transportation management, the absence of proper policies, improper public transportation system and violation of traffic rules and regulations by inhabitants. On the other hand, the observed result indicates that the current vehicle to capacity ratio (VCR) which is the most used index to judge traffic status in the city is around 0.79. This indicates the inappropriate traffic condition of the city. Moreover, by the growth of population in mid-term (2025) and long-term (2040) and in the case of no development in the road network and transportation system, the VCR value will dramatically increase to 1.40 (2025) and 2.5 (2040). This can be a critical situation for an urban area from an urban transportation perspective. Thus, by introducing high-capacity public transportation system and the development of road network in Kabul New City and integrating these links with the existing city road network, significant improvements were observed in the value of VCR.

Keywords: Afghanistan, Kabul New City, planning, policy, urban transportation.

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326 Performance of Derna Steam Power Plant at Varying Super-Heater Operating Conditions Based on Exergy

Authors: Idris Elfeituri

Abstract:

In the current study, energy and exergy analysis of a 65 MW steam power plant was carried out. This study investigated the effect of variations of overall conductance of the super heater on the performance of an existing steam power plant located in Derna, Libya. The performance of the power plant was estimated by a mathematical modelling which considers the off-design operating conditions of each component. A fully interactive computer program based on the mass, energy and exergy balance equations has been developed. The maximum exergy destruction has been found in the steam generation unit. A 50% reduction in the design value of overall conductance of the super heater has been achieved, which accordingly decreases the amount of the net electrical power that would be generated by at least 13 MW, as well as the overall plant exergy efficiency by at least 6.4%, and at the same time that would cause an increase of the total exergy destruction by at least 14 MW. The achieved results showed that the super heater design and operating conditions play an important role on the thermodynamics performance and the fuel utilization of the power plant. Moreover, these considerations are very useful in the process of the decision that should be taken at the occasions of deciding whether to replace or renovate the super heater of the power plant.

Keywords: Exergy, super-heater, fouling, steam power plant, off-design.

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325 Virtual Reality for Mutual Understanding in Landscape Planning

Authors: Ball J., Capanni N., Watt S.

Abstract:

This paper argues that fostering mutual understanding in landscape planning is as much about the planners educating stakeholder groups as the stakeholders educating the planners. In other words it is an epistemological agreement as to the meaning and nature of place, especially where an effort is made to go beyond the quantitative aspects, which can be achieved by the phenomenological experience of the Virtual Reality (VR) environment. This education needs to be a bi-directional process in which distance can be both temporal as well as spatial separation of participants, that there needs to be a common framework of understanding in which neither 'side' is disadvantaged during the process of information exchange and it follows that a medium such as VR offers an effective way of overcoming some of the shortcomings of traditional media by taking advantage of continuing technological advances in Information, Technology and Communications (ITC). In this paper we make particular reference to this as an extension to Geographical Information Systems (GIS). VR as a two-way communication tool offers considerable potential particularly in the area of Public Participation GIS (PPGIS). Information rich virtual environments that can operate over broadband networks are now possible and thus allow for the representation of large amounts of qualitative and quantitative information 'side-by-side'. Therefore, with broadband access becoming standard for households and enterprises alike, distributed virtual reality environments have great potential to contribute to enabling stakeholder participation and mutual learning within the planning context.

Keywords: 3D, communication, geographical information systems, planning, public participation, virtual reality, visualisation.

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324 Network Effects and QoS as Determining Factors in Selection of Mobile Operator: A Case Study from Higher Learning Institution in Dodoma Municipality in Tanzania

Authors: Justinian Anatory, Ekael Stephen Manase

Abstract:

The use of mobile phones is growing tremendously all over the world. In Tanzania there are a number of operators licensed by Tanzania Communications Regulatory Authority (TCRA) aiming at attracting customers into their networks. So far telecommunications market competition has been very stiff. Various measures are being taken by mobile operators to survive in the market. Such measure include introducing of different air time bundles on daily, weekly and monthly at lower tariffs. Other measures include the introduction of normal tariff, tourist package and one network. Despite of all these strategies, there is a dynamic competition in the market which needs to be explored. Some influences which attract customers to choose a certain mobile operator are of particular interest. This paper is investigating if the network effects and Quality of Services (QoS) influence mobile customers in selection of their mobile network operators. Seventy seven students from high learning institutions in Dodoma Municipality in Tanzania participated in responding to prepared questionnaires. The data was analyzed using Statistical Package for Social Science (SPSS) Software. The results indicate that, network coverage does influence customers in selection of mobile operators. In addition, this paper proposes further research in some areas especially where the study came up with different findings from what the theory has in place.

Keywords: Network effects, Quality of services, Consumer Buying, mobile operators.

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323 Agile Methodology for Modeling and Design of Data Warehouses -AM4DW-

Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

Abstract:

The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: Data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse.

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322 Accurate Time Domain Method for Simulation of Microstructured Electromagnetic and Photonic Structures

Authors: Vijay Janyani, Trevor M. Benson, Ana Vukovic

Abstract:

A time-domain numerical model within the framework of transmission line modeling (TLM) is developed to simulate electromagnetic pulse propagation inside multiple microcavities forming photonic crystal (PhC) structures. The model developed is quite general and is capable of simulating complex electromagnetic problems accurately. The field quantities can be mapped onto a passive electrical circuit equivalent what ensures that TLM is provably stable and conservative at a local level. Furthermore, the circuit representation allows a high level of hybridization of TLM with other techniques and lumped circuit models of components and devices. A photonic crystal structure formed by rods (or blocks) of high-permittivity dieletric material embedded in a low-dielectric background medium is simulated as an example. The model developed gives vital spatio-temporal information about the signal, and also gives spectral information over a wide frequency range in a single run. The model has wide applications in microwave communication systems, optical waveguides and electromagnetic materials simulations.

Keywords: Computational Electromagnetics, Numerical Simulation, Transmission Line Modeling.

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321 Compressed Sensing of Fetal Electrocardiogram Signals Based on Joint Block Multi-Orthogonal Least Squares Algorithm

Authors: Xiang Jianhong, Wang Cong, Wang Linyu

Abstract:

With the rise of medical IoT technologies, Wireless body area networks (WBANs) can collect fetal electrocardiogram (FECG) signals to support telemedicine analysis. The compressed sensing (CS)-based WBANs system can avoid the sampling of a large amount of redundant information and reduce the complexity and computing time of data processing, but the existing algorithms have poor signal compression and reconstruction performance. In this paper, a Joint block multi-orthogonal least squares (JBMOLS) algorithm is proposed. We apply the FECG signal to the Joint block sparse model (JBSM), and a comparative study of sparse transformation and measurement matrices is carried out. A FECG signal compression transmission mode based on Rbio5.5 wavelet, Bernoulli measurement matrix, and JBMOLS algorithm is proposed to improve the compression and reconstruction performance of FECG signal by CS-based WBANs. Experimental results show that the compression ratio (CR) required for accurate reconstruction of this transmission mode is increased by nearly 10%, and the runtime is saved by about 30%.

Keywords: telemedicine, fetal electrocardiogram, compressed sensing, joint sparse reconstruction, block sparse signal

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320 Embedding a Large Amount of Information Using High Secure Neural Based Steganography Algorithm

Authors: Nameer N. EL-Emam

Abstract:

In this paper, we construct and implement a new Steganography algorithm based on learning system to hide a large amount of information into color BMP image. We have used adaptive image filtering and adaptive non-uniform image segmentation with bits replacement on the appropriate pixels. These pixels are selected randomly rather than sequentially by using new concept defined by main cases with sub cases for each byte in one pixel. According to the steps of design, we have been concluded 16 main cases with their sub cases that covere all aspects of the input information into color bitmap image. High security layers have been proposed through four layers of security to make it difficult to break the encryption of the input information and confuse steganalysis too. Learning system has been introduces at the fourth layer of security through neural network. This layer is used to increase the difficulties of the statistical attacks. Our results against statistical and visual attacks are discussed before and after using the learning system and we make comparison with the previous Steganography algorithm. We show that our algorithm can embed efficiently a large amount of information that has been reached to 75% of the image size (replace 18 bits for each pixel as a maximum) with high quality of the output.

Keywords: Adaptive image segmentation, hiding with high capacity, hiding with high security, neural networks, Steganography.

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319 Development of Synthetic Jet Air Blower for Air-breathing PEM Fuel Cell

Authors: Jongpil Choi, Eon-Soo Lee, Jae-Huk Jang, Young Ho Seo, Byeonghee Kim

Abstract:

This paper presents a synthetic jet air blower actuated by PZT for air blowing for air-breathing micro PEM fuel cell. The several factors to affect the performance of air-breathing PEM fuel cell such as air flow rate, opening ratio and cathode open type in the cathode side were studied. Especially, an air flow rate is critical condition to improve its performance. In this paper, we developed a synthetic jet air blower to supply a high stoichiometric air flow. The synthetic jet mechanism is a zero mass flux device that converts electrical energy into the momentum. The synthetic jet actuation is usually generated by a traditional PZT actuator, which consists of a small cylindrical cavity, in/outlet channel and PZT diaphragms. The flow rate of the fabricated synthetic jet air blower was 400cc/min at 550Hz and its power consumption was very low under 0.3W. The proposed air-breathing PEM fuel cell which installed synthetic jet air blower was higher performance and stability during continuous operation than the air-breathing fuel cell without auxiliary device to supply the air. The results showed that the maximum power density was 188mW/cm2 at 400mA/cm2. This maximum power density and durability were improved more than 40% and 20%, respectively.

Keywords: Air-breathing PEM fuel cell, Synthetic jet air blower, Opening ratio, Power consumption.

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318 An Effective Decision-Making Strategy Based on Multi-Objective Optimization for Commercial Vehicles in Highway Scenarios

Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

Abstract:

Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: Decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle.

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317 Sleep Scheduling Schemes Based on Location of Mobile User in Sensor-Cloud

Authors: N. Mahendran, R. Priya

Abstract:

The mobile cloud computing (MCC) with wireless sensor networks (WSNs) technology gets more attraction by research scholars because its combines the sensors data gathering ability with the cloud data processing capacity. This approach overcomes the limitation of data storage capacity and computational ability of sensor nodes. Finally, the stored data are sent to the mobile users when the user sends the request. The most of the integrated sensor-cloud schemes fail to observe the following criteria: 1) The mobile users request the specific data to the cloud based on their present location. 2) Power consumption since most of them are equipped with non-rechargeable batteries. Mostly, the sensors are deployed in hazardous and remote areas. This paper focuses on above observations and introduces an approach known as collaborative location-based sleep scheduling (CLSS) scheme. Both awake and asleep status of each sensor node is dynamically devised by schedulers and the scheduling is done purely based on the of mobile users’ current location; in this manner, large amount of energy consumption is minimized at WSN. CLSS work depends on two different methods; CLSS1 scheme provides lower energy consumption and CLSS2 provides the scalability and robustness of the integrated WSN.

Keywords: Sleep scheduling, mobile cloud computing, wireless sensor network, integration, location, network lifetime.

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316 Investigation of SSR Characteristics of SSSC With GA Based Voltage Controller

Authors: R. Thirumalaivasan, M.Janaki, Nagesh Prabhu

Abstract:

In this paper, investigation of subsynchronous resonance (SSR) characteristics of a hybrid series compensated system and the design of voltage controller for three level 24-pulse Voltage Source Converter based Static Synchronous Series Compensator (SSSC) is presented. Hybrid compensation consists of series fixed capacitor and SSSC which is a active series FACTS controller. The design of voltage controller for SSSC is based on damping torque analysis, and Genetic Algorithm (GA) is adopted for tuning the controller parameters. The SSR Characteristics of SSSC with constant reactive voltage control modes has been investigated. The results show that the constant reactive voltage control of SSSC has the effect of reducing the electrical resonance frequency, which detunes the SSR.The analysis of SSR with SSSC is carried out based on frequency domain method, eigenvalue analysis and transient simulation. While the eigenvalue and damping torque analysis are based on D-Q model of SSSC, the transient simulation considers both D-Q and detailed three phase nonlinear system model using switching functions.

Keywords: FACTS, SSR, SSSC, damping torque, GA.

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315 Study of Fire Propagation and Soot Flow in a Pantry Car of Railway Locomotive

Authors: Juhi Kaushik, Abhishek Agarwal, Manoj Sarda, Vatsal Sanjay, Arup Kumar Das

Abstract:

Fire accidents in trains bring huge disaster to human life and property. Evacuation becomes a major challenge in such incidents owing to confined spaces, large passenger density and trains moving at high speeds. The pantry car in Indian Railways trains carry inflammable materials like cooking fuel and LPG and electrical fittings. The pantry car is therefore highly susceptible to fire accidents. Numerical simulations have been done in a pantry car of Indian locomotive train using computational fluid dynamics based software. Different scenarios of a fire outbreak have been explored by varying Heat Release Rate per Unit Area (HRRPUA) of the fire source, introduction of exhaust in the cooking area, and taking a case of an air conditioned pantry car. Temporal statures of flame and soot have been obtained for each scenario and differences have been studied and reported. Inputs from this study can be used to assess casualties in fire accidents in locomotive trains and development of smoke control/detection systems in Indian trains.

Keywords: Fire propagation, flame contour, pantry fire, soot flow.

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314 High-Frequency Spectrum Analysis of VFTO Generated inside Gas Insulated Substations

Authors: M. A. Abd-Allah, A. Said, Ebrahim A. Badran

Abstract:

Worldwide many electrical equipment insulation failures have been reported caused by switching operations, while those equipments had previously passed all the standard tests and complied with all quality requirements. The problem is mostly associated with high-frequency overvoltages generated during opening or closing of a switching device. The transients generated during switching operations in a Gas Insulated Substation (GIS) are associated with high frequency components in the order of few tens of MHz. The frequency spectrum of the VFTO generated in the 220/66 kV Wadi-Hoff GIS is analyzed using Fast Fourier Transform technique. The main frequency with high voltage amplitude due to the operation of disconnector (DS5) is 5 to 10 MHz, with the highest amplitude at 9 MHz. The main frequency with high voltage amplitude due to the operation of circuit breaker (CB5) is 1 to 25 MHz, with the highest amplitude at 2 MHz. Mitigating techniques damped the oscillating frequencies effectively. The using of cable terminal reduced the frequency oscillation effectively than that of OHTL terminal. The using of a shunt capacitance results in vanishing the high frequency components. Ferrite rings reduces the high frequency components effectively especially in the range 2 to 7 MHz. The using of RC and RL filters results in vanishing the high frequency components.

Keywords: GIS, VFTO, Mitigation Techniques, Frequency spectrum, FFT, EMTP/ATP.

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313 Hand Gesture Interpretation Using Sensing Glove Integrated with Machine Learning Algorithms

Authors: Aqsa Ali, Aleem Mushtaq, Attaullah Memon, Monna

Abstract:

In this paper, we present a low cost design for a smart glove that can perform sign language recognition to assist the speech impaired people. Specifically, we have designed and developed an Assistive Hand Gesture Interpreter that recognizes hand movements relevant to the American Sign Language (ASL) and translates them into text for display on a Thin-Film-Transistor Liquid Crystal Display (TFT LCD) screen as well as synthetic speech. Linear Bayes Classifiers and Multilayer Neural Networks have been used to classify 11 feature vectors obtained from the sensors on the glove into one of the 27 ASL alphabets and a predefined gesture for space. Three types of features are used; bending using six bend sensors, orientation in three dimensions using accelerometers and contacts at vital points using contact sensors. To gauge the performance of the presented design, the training database was prepared using five volunteers. The accuracy of the current version on the prepared dataset was found to be up to 99.3% for target user. The solution combines electronics, e-textile technology, sensor technology, embedded system and machine learning techniques to build a low cost wearable glove that is scrupulous, elegant and portable.

Keywords: American sign language, assistive hand gesture interpreter, human-machine interface, machine learning, sensing glove.

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312 Methodology: A Review in Modelling and Predictability of Embankment in Soft Ground

Authors: Bhim Kumar Dahal

Abstract:

Transportation network development in the developing country is in rapid pace. The majority of the network belongs to railway and expressway which passes through diverse topography, landform and geological conditions despite the avoidance principle during route selection. Construction of such networks demand many low to high embankment which required improvement in the foundation soil. This paper is mainly focused on the various advanced ground improvement techniques used to improve the soft soil, modelling approach and its predictability for embankments construction. The ground improvement techniques can be broadly classified in to three groups i.e. densification group, drainage and consolidation group and reinforcement group which are discussed with some case studies.  Various methods were used in modelling of the embankments from simple 1-dimensional to complex 3-dimensional model using variety of constitutive models. However, the reliability of the predictions is not found systematically improved with the level of sophistication.  And sometimes the predictions are deviated more than 60% to the monitored value besides using same level of erudition. This deviation is found mainly due to the selection of constitutive model, assumptions made during different stages, deviation in the selection of model parameters and simplification during physical modelling of the ground condition. This deviation can be reduced by using optimization process, optimization tools and sensitivity analysis of the model parameters which will guide to select the appropriate model parameters.

Keywords: Embankment, ground improvement, modelling, model prediction.

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311 Understanding Innovation by Analyzing the Pillars of the Global Competitiveness Index

Authors: Ujjwala Bhand, Mridula Goel

Abstract:

Global Competitiveness Index (GCI) prepared by World Economic Forum has become a benchmark in studying the competitiveness of countries and for understanding the factors that enable competitiveness. Innovation is a key pillar in competitiveness and has the unique property of enabling exponential economic growth. This paper attempts to analyze how the pillars comprising the Global Competitiveness Index affect innovation and whether GDP growth can directly affect innovation outcomes for a country. The key objective of the study is to identify areas on which governments of developing countries can focus policies and programs to improve their country’s innovativeness. We have compiled a panel data set for top innovating countries and large emerging economies called BRICS from 2007-08 to 2014-15 in order to find the significant factors that affect innovation. The results of the regression analysis suggest that government should make policies to improve labor market efficiency, establish sophisticated business networks, provide basic health and primary education to its people and strengthen the quality of higher education and training services in the economy. The achievements of smaller economies on innovation suggest that concerted efforts by governments can counter any size related disadvantage, and in fact can provide greater flexibility and speed in encouraging innovation.

Keywords: Innovation, Global Competitiveness Index, BRICS, economic growth.

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310 Intelligent Transport System: Classification of Traffic Signs Using Deep Neural Networks in Real Time

Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

Abstract:

Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: Multiclass classification, convolution neural network, OpenCV, Data Augmentation.

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309 High Gain Broadband Plasmonic Slot Nano-Antenna

Authors: H. S. Haroyan, V. R. Tadevosyan

Abstract:

High gain broadband plasmonic slot nano-antenna has been considered. The theory of plasmonic slot nano-antenna (PSNA) has been developed. The analytical model takes into account also the electrical field inside the metal due to imperfectness of metal in optical range, as well as numerical investigation based on finite element method (FEM) has been realized. It should be mentioned that Yagi-Uda configuration improves directivity in the plane of structure. In contrast, in this paper the possibility of directivity improvement of proposed PSNA in perpendicular plane of structure by using reflection metallic surface placed under the slot in fixed distance has been demonstrated. It is well known that a directivity improvement brings to the antenna gain increasing. This method of diagram improving is also well known from RF antenna design theory. Moreover the improvement of directivity in the perpendicular plane gives more flexibility in such application as improving the light and atom, ion, molecule interactions by using such type of plasmonic slot antenna. By the analogy of dipole type optical antennas the widening of working wavelengths has been realized by using bowtie geometry of slots, which made the antenna broadband.

Keywords: Broadband antenna, high gain, slot nano-antenna, plasmonics.

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308 Geophysical Investigation of Abnormal Seepages in Goronyo Dam Sokoto, North Western Nigeria Using Self-Potential Method

Authors: A. I. Augie, M. Saleh, A. A. Gado

Abstract:

In this research, Self-Potential (SP) method was employed to locate anomalous electrical conductivity located in Goronyo area and also to determine the condition of the embankment of the dam. SP data were plotted against distance along with the profile and spacing of electrode using surfer software (version 12). High and low zones of SP values were identified along the right and left abutments of the dam reservoir. The regions with high SP values were described to be high tendency of fluid flow associate with wet sandy soil. These zones have the SP values ranging from 200 mV and above. High SP values were due to the high moisture content that may lead to the seepage of water leaking through this zone. The zones with high SP values occupied Profiles S1, S2, S3, S4 and S5 indicating the presence of potential seepage paths within the subsurface of the embankment. These regions of seepage were identified as weak zones and potential pathways through which water could be lost from the dam reservoir. The SP values for the regions range from 250 m to 400 m (S1), 306 m to 400 m (S2), 192 m to 400 m (S3), 48 m to 200 m (S4) and 7 m to 170 m (S5) with their corresponding maximum depths of 30 m, 28 m, 28 m, 30 m and 26 m respectively. However, zones of low SP values in the overburden were observed which shows the presence of intact regions, which may be due to the compactness and dryness around the dam. The weak zones were considered as geological features (such as fractures, joints, and faults) that have undermined the integrity of the dam structure, which has led to the abnormal seepage.

Keywords: Self-potential, subsurface, seepage, condition and dam.

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307 Optimizing Electrospinning Parameters for Finest Diameter of Nano Fibers

Authors: M. Maleki, M. Latifi, M. Amani-Tehran

Abstract:

Nano fibers produced by electrospinning are of industrial and scientific attention due to their special characteristics such as long length, small diameter and high surface area. Applications of electrospun structures in nanotechnology are included tissue scaffolds, fibers for drug delivery, composite reinforcement, chemical sensing, enzyme immobilization, membrane-based filtration, protective clothing, catalysis, solar cells, electronic devices and others. Many polymer and ceramic precursor nano fibers have been successfully electrospun with diameters in the range from 1 nm to several microns. The process is complex so that fiber diameter is influenced by various material, design and operating parameters. The objective of this work is to apply genetic algorithm on the parameters of electrospinning which have the most significant effect on the nano fiber diameter to determine the optimum parameter values before doing experimental set up. Effective factors including initial polymer concentration, initial jet radius, electrical potential, relaxation time, initial elongation, viscosity and distance between nozzle and collector are considered to determine finest diameter which is selected by user.

Keywords: Electrospinning, genetic algorithm, nano fiber diameter, optimization.

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