Search results for: power system modeling

Authors: Gheida J. Shahrour, Martin J. Russell

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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that intersubject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: Person Recognition, Topic Recognition, Culture Recognition, 3D Body Movement Signals, Variability Compensation.

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Authors: N. Ravi Kumar, R. Kamalakannan

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The advancement of hybrid energy resources such as solar and wind power leading to the emergence of customer owned grid. It provides an opportunity to regulars to obtain low energy costs as well as enabling the power supplier to regulate the utility grid. There is a need to develop smart systems that will automatically submit energy demand schedule and monitors energy price signals in real-time without the prompt of customers. In this paper, a demand side energy management for a grid connected household and also smart preparation of electrical appliance have been presented. It also reduces electricity bill for the consumers in the grid. In addition to this, when production is high, the surplus energy fashioned in the customer owned grid is given to main grid or neighboring micro grids. The simulation of the entire system is presented using LabVIEW software.

Keywords: Distributed renewable energy resource, power storage devices, scheduling, smart meters, smart micro grid, electric vehicle.

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Authors: Chin-Cheh Yi, Pei-Wen Liao, Chin-Feng Huang, I-Hui Hwang

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With the proliferation of mobile computing technology, mobile learning (m-learning) will play a vital role in the rapidly growing electronic learning market. However, the acceptance of m-learning by individuals is critical to the successful implementation of m-learning systems. Thus, there is a need to research the factors that affect users- intention to use m-learning. Based on an updated information system (IS) success model, data collected from 350 respondents in Taiwan were tested against the research model using the structural equation modeling approach. The data collected by questionnaire were analyzed to check the validity of constructs. Then hypotheses describing the relationships between the identified constructs and users- satisfaction were formulated and tested.

Keywords: m-learning, information system success, users' satisfaction, perceived value.

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Authors: Mehmet Savsar

Abstract:

This paper presents a model for an unreliable production line, which is operated according to demand with constant work-in-process (CONWIP). A simulation model is developed based on the discrete model and several case problems are analyzed using the model. The model is utilized to optimize storage space capacities at intermediate stages and the number of kanbans at the last stage, which is used to trigger the production at the first stage. Furthermore, effects of several line parameters on production rate are analyzed using design of experiments.

Keywords: Production line simulator, Push-pull system, JIT system, Constant WIP, Machine failures.

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Authors: V. Masilamani, D.K. Sheena Christy, D.G. Thomas

Abstract:

Image synthesis is an important area in image processing. To synthesize images various systems are proposed in the literature. In this paper, we propose a bio-inspired system to synthesize image and to study the generating power of the system, we define the class of languages generated by our system. We call image as array in this paper. We use a primitive called iso-array to synthesize image/array. The operation is double splicing on iso-arrays. The double splicing operation is used in DNA computing and we use this to synthesize image. A comparison of the family of languages generated by the proposed self restricted double splicing systems on iso-arrays with the existing family of local iso-picture languages is made. Certain closure properties such as union, concatenation and rotation are studied for the family of languages generated by the proposed model.

Keywords: DNA computing, splicing system, iso-picture languages, iso-array double splicing system, iso-array self splicing.

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Authors: Sungjin Lee, Donghyun Choi, Choonsik Park, Seungjoo Kim

Abstract:

A SCADA (Supervisory Control And Data Acquisition) system is an industrial control and monitoring system for national infrastructures. The SCADA systems were used in a closed environment without considering about security functionality in the past. As communication technology develops, they try to connect the SCADA systems to an open network. Therefore, the security of the SCADA systems has been an issue. The study of key management for SCADA system also has been performed. However, existing key management schemes for SCADA system such as SKE(Key establishment for SCADA systems) and SKMA(Key management scheme for SCADA systems) cannot support broadcasting communication. To solve this problem, an Advanced Key Management Architecture for Secure SCADA Communication has been proposed by Choi et al.. Choi et al.-s scheme also has a problem that it requires lots of computational cost for multicasting communication. In this paper, we propose an enhanced scheme which improving computational cost for multicasting communication with considering the number of keys to be stored in a low power communication device (RTU).

Keywords: SCADA system, SCADA communication, Key management, Distributed networks.

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Authors: Tudor Deaconescu, Andrea Deaconescu

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Deployment of pneumatic muscles in various industrial applications is still in its early days, considering the relative newness of these components. The field of robotics holds particular future potential for pneumatic muscles, especially in view of their specific behaviour known as compliance. The paper presents and discusses an innovative constructive solution for a gripper system mountable on an industrial robot, based on actuation by a linear pneumatic muscle and transmission of motion by gear and rack mechanism. The structural, operational and constructive models of the new gripper are presented, along with some of the experimental results obtained subsequently to the testing of a prototype. Further presented are two control variants of the gripper system, one by means of a 3/2-way fast-switching solenoid valve, the other by means of a proportional pressure regulator. Advantages and disadvantages are discussed for both variants.

Keywords: Gripper system, pneumatic muscle, structural modeling.

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Authors: Y. Yudin, T. Krasikova, Y. Dorozhko, N. Currle-Linde

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Nowadays, HPC, Grid and Cloud systems are evolving very rapidly. However, the development of infrastructure solutions related to HPC is lagging behind. While the existing infrastructure is sufficient for simple cases, many computational problems have more complex requirements.Such computational experiments use different resources simultaneously to start a large number of computational jobs.These resources are heterogeneous. They have different purposes, architectures, performance and used software.Users need a convenient tool that allows to describe and to run complex computational experiments under conditions of HPC environment. This paper introduces a modularworkflow system called SEGL which makes it possible to run complex computational experiments under conditions of a real HPC organization. The system can be used in a great number of organizations, which provide HPC power. Significant requirements to this system are high efficiency and interoperability with the existing HPC infrastructure of the organization without any changes.

Keywords: HPC, Molecular Dynamics, Workflow Languages, Workflow Management.

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Authors: A. M. Alaskari, S. E. Oraby

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The quality of a machined surface is becoming more and more important to justify the increasing demands of sophisticated component performance, longevity, and reliability. Usually, any machining operation leaves its own characteristic evidence on the machined surface in the form of finely spaced micro irregularities (surface roughness) left by the associated indeterministic characteristics of the different elements of the system: tool-machineworkpart- cutting parameters. However, one of the most influential sources in machining affecting surface roughness is the instantaneous state of tool edge. The main objective of the current work is to relate the in-process immeasurable cutting edge deformation and surface roughness to a more reliable easy-to-measure force signals using a robust non-linear time-dependent modeling regression techniques. Time-dependent modeling is beneficial when modern machining systems, such as adaptive control techniques are considered, where the state of the machined surface and the health of the cutting edge are monitored, assessed and controlled online using realtime information provided by the variability encountered in the measured force signals. Correlation between wear propagation and roughness variation is developed throughout the different edge lifetimes. The surface roughness is further evaluated in the light of the variation in both the static and the dynamic force signals. Consistent correlation is found between surface roughness variation and tool wear progress within its initial and constant regions. At the first few seconds of cutting, expected and well known trend of the effect of the cutting parameters is observed. Surface roughness is positively influenced by the level of the feed rate and negatively by the cutting speed. As cutting continues, roughness is affected, to different extents, by the rather localized wear modes either on the tool nose or on its flank areas. Moreover, it seems that roughness varies as wear attitude transfers from one mode to another and, in general, it is shown that it is improved as wear increases but with possible corresponding workpart dimensional inaccuracy. The dynamic force signals are found reasonably sensitive to simulate either the progressive or the random modes of tool edge deformation. While the frictional force components, feeding and radial, are found informative regarding progressive wear modes, the vertical (power) components is found more representative carrier to system instability resulting from the edge-s random deformation.

Keywords: Dynamic force signals, surface roughness (finish), tool wear and deformation, tool wear modes (nose, flank)

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Authors: Junjie Chen, Deguang Xu

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The high energy density of hydrocarbon fuels creates a great opportunity to develop catalytic combustion based micro-power generation systems to meet increasing demands for micro-scale devices. In this work, the recent technological development progress in fundamental understanding of the catalytic combustion at micro-scales are reviewed. The underlying fundamental mechanisms, flame stability, hetero-homogeneous interaction, catalytic ignition, and catalytic reforming are reviewed in catalytic micro-scale combustion systems. Catalytic combustion and its design, diagnosis, and modeling operation are highlighted for micro-combustion application purpose; these fundamental aspects are reviewed. Finally, an overview of future studies is made. The primary objective of this review is to present an overview of the development of micro-power generators by focusing more on the advances and challenges in the fundamental understanding of the catalytic combustion at micro-scales.

Keywords: Micro-combustion, catalytic combustion, flame stability, hetero-homogeneous interaction, catalytic ignition, catalytic reforming.

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Authors: Javad Khazaei, Rick S. Blum

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Distributed control is an efficient and flexible approach for coordination of multi-agent systems. One of the main challenges in designing a distributed controller is identifying the governing dynamics of the dynamical systems. Data-driven system identification is currently undergoing a revolution. With the availability of high-fidelity measurements and historical data, model-free identification of dynamical systems can facilitate the control design without tedious modeling of high-dimensional and/or nonlinear systems. This paper develops a distributed control design using consensus theory for linear and nonlinear dynamical systems using sparse identification of system dynamics. Compared with existing consensus designs that heavily rely on knowing the detailed system dynamics, the proposed model-free design can accurately capture the dynamics of the system with available measurements and input data and provide guaranteed performance in consensus and tracking problems. Heterogeneous damped oscillators are chosen as examples of dynamical system for validation purposes.

Keywords: Consensus tracking, distributed control, model-free control, sparse identification of dynamical systems.

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Authors: Farhad Kolahan, Mohammad Bironro

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This paper addresses modeling and optimization of process parameters in powder mixed electrical discharge machining (PMEDM). The process output characteristics include metal removal rate (MRR) and electrode wear rate (EWR). Grain size of Aluminum powder (S), concentration of the powder (C), discharge current (I) pulse on time (T) are chosen as control variables to study the process performance. The experimental results are used to develop the regression models based on second order polynomial equations for the different process characteristics. Then, a genetic algorithm (GA) has been employed to determine optimal process parameters for any desired output values of machining characteristics.

Keywords: Regression modeling, PMEDM, GeneticAlgorithm, Optimization.

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Authors: Okan Özgönenel

Abstract:

This paper presents the development of a wavelet based algorithm, for distinguishing between magnetizing inrush currents and power system fault currents, which is quite adequate, reliable, fast and computationally efficient tool. The proposed technique consists of a preprocessing unit based on discrete wavelet transform (DWT) in combination with an artificial neural network (ANN) for detecting and classifying fault currents. The DWT acts as an extractor of distinctive features in the input signals at the relay location. This information is then fed into an ANN for classifying fault and magnetizing inrush conditions. A 220/55/55 V, 50Hz laboratory transformer connected to a 380 V power system were simulated using ATP-EMTP. The DWT was implemented by using Matlab and Coiflet mother wavelet was used to analyze primary currents and generate training data. The simulated results presented clearly show that the proposed technique can accurately discriminate between magnetizing inrush and fault currents in transformer protection.

Keywords: Artificial neural network, discrete wavelet transform, fault detection, magnetizing inrush current.

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Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh

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Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.

Keywords: Malmquist Index, Grey's Theory, Charnes Cooper & Rhodes (CCR) Model, network data envelopment analysis, Iran electricity power chain.

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Authors: Purnomo Yustianto, Robin Doss, Suhardi, Novianto Budi Kurniawan

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As a term for characterizing a process of devising a service system, the term ‘service engineering’ is still regarded as an ‘open’ research challenge due to unspecified details and conflicting perspectives. This paper presents consolidated service engineering ontologies in collecting, specifying and defining relationship between components pertinent within the context of service engineering. The ontologies are built by way of literature surveys from the collected conceptual works by collating various concepts into an integrated ontology. Two ontologies are produced: general service ontology and software service ontology. The software-service ontology is drawn from the informatics domain, while the generalized ontology of a service system is built from both a business management and the information system perspective. The produced ontologies are verified by exercising conceptual operationalizations of the ontologies in adopting several service orientation features and service system patterns. The proposed ontologies are demonstrated to be sufficient to serve as a basis for a service engineering framework.

Keywords: Engineering, ontology, service, SoaML.

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Authors: Amir Lotfi, Seyed Hamid Hosseini

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During the recent past, due to the increase of electrical energy demand and governmental resources constraints in creating additional capacity in the generation, transmission, and distribution, privatization, and restructuring in electrical industry have been considered. So, in most of the countries, different parts of electrical industry like generation, transmission, and distribution have been separated in order to create competition. Considering these changes, environmental issues, energy growth, investment of private equity in energy generation units and difficulties of transmission lines expansion, distributed generation (DG) units have been used in power systems. Moreover, reduction in the need for transmission and distribution, the increase of reliability, improvement of power quality, and reduction of power loss have caused DG to be placed in power systems. On the other hand, considering low liquidity need, private investors tend to spend their money for DGs. In this project, the main goal is to offer an algorithm for planning and placing DGs in order to reduce the need for transmission and distribution network.

Keywords: Planning, transmission, distributed generation, power security, power systems.

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Authors: Yu Zhang, Pedro Desouza

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Since big data has become substantially more accessible and manageable due to the development of powerful tools for dealing with unstructured data, people are eager to mine information from social media resources that could not be handled in the past. Sentiment analysis, as a novel branch of text mining, has in the last decade become increasingly important in marketing analysis, customer risk prediction and other fields. Scientists and researchers have undertaken significant work in creating and improving their sentiment models. In this paper, we present a concept of selecting appropriate classifiers based on the features and qualities of data sources by comparing the performances of five classifiers with three popular social media data sources: Twitter, Amazon Customer Reviews, and Movie Reviews. We introduced a couple of innovative models that outperform traditional sentiment classifiers for these data sources, and provide insights on how to further improve the predictive power of sentiment analysis. The modeling and testing work was done in R and Greenplum in-database analytic tools.

Keywords: Sentiment Analysis, Social Media, Twitter, Amazon, Data Mining, Machine Learning, Text Mining.

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Authors: Phumelele P. Kubheka, Pius A. Owolawi, Gbolahan Aiyetoro

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Twitter is one of the most popular social media platforms where users share their opinions on different subjects. Twitter can be considered a great source for mining text due to the high volumes of data generated through the platform daily. Many industries such as telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model in this experiment. A higher topic coherence score indicates better performance of the model.

Keywords: Big data, latent Dirichlet allocation, latent semantic indexing, Telco, topic modeling, Twitter.

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Authors: Gionata Carmignani, Mario G. C. A. Cimino, Franco Failli

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Business Processes (BPs) are the key instrument to understand how companies operate at an organizational level, taking an as-is view of the workflow, and how to address their issues by identifying a to-be model. In last year’s, the BP Model and Notation (BPMN) has become a de-facto standard for modeling processes. However, this standard does not incorporate explicitly the Problem- Solving (PS) knowledge in the Process Modeling (PM) results. Thus, such knowledge cannot be shared or reused. To narrow this gap is today a challenging research area. In this paper we present a framework able to capture the PS knowledge and to improve a workflow. This framework extends the BPMN specification by incorporating new general-purpose elements. A pilot scenario is also presented and discussed.

Keywords: Business Process Management, BPMN, Problem Solving, Process mapping.

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Authors: L. Boukhris, A. Boudjemai, A. Bellar, R. Roubache, M. Bensaada

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In space during functioning, a satellite will be heated up due to the behavior of its components such as power electronics. In order to prevent problems in the satellite, this heat has to be released in space thanks to the cooling system. This system consists of a loop heat pipe (LHP), in which a fluid streams through an evaporator and a condenser. In the evaporator, the fluid captures the heat from the satellite and evaporates. Then it flows to the condenser where it releases the heat and it condenses. In this project, the two mains parts of a cooling system are studied: the evaporator and the condenser. The study of the diphasic loop was done starting from digital simulations carried out under Matlab and Femlab.

Keywords: capillarity, condenser, evaporator, phase change, transfer of heat.

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Authors: Mohamed A. Khlifi, Badr M. Alshammari

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This paper discusses the general methods to saturation in the steady-state, two axis (d & q) frame models of synchronous machines. In particular, the important role of the magnetic coupling between the d-q axes (cross-magnetizing phenomenon), is demonstrated. For that purpose, distinct methods of saturation modeling of dumper synchronous machine with cross-saturation are identified, and detailed models synthesis in d-q axes. A number of models are given in the final developed form. The procedure and the novel models are verified by a critical application to prove the validity of the method and the equivalence between all developed models is reported. Advantages of some of the models over the existing ones and their applicability are discussed.

Keywords: Cross-magnetizing, models synthesis, synchronous machine, saturated modeling, state-space vectors.

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Authors: Anjali Chatterjee, Nirmal Kumar Roy

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Economically transformers constitute one of the largest investments in a Power system. For this reason, transformer condition assessment and management is a high priority task. If a transformer fails, it would have a significant negative impact on revenue and service reliability. Monitoring the state of health of power transformers has traditionally been carried out using laboratory Dissolved Gas Analysis (DGA) tests performed at periodic intervals on the oil sample, collected from the transformers. DGA of transformer oil is the single best indicator of a transformer-s overall condition and is a universal practice today, which started somewhere in the 1960s. Failure can occur in a transformer due to different reasons. Some failures can be limited or prevented by maintenance. Oil filtration is one of the methods to remove the dissolve gases and prevent the deterioration of the oil. In this paper we analysis the DGA data by regression method and predict the gas concentration in the oil in the future. We bring about a comparative study of different traditional methods of regression and the errors generated out of their predictions. With the help of these data we can deduce the health of the transformer by finding the type of fault if it has occurred or will occur in future. Additional in this paper effect of filtration on the transformer health is highlight by calculating the probability of failure of a transformer with and without oil filtrating.

Keywords: Power Transformers, Dissolve gas Analysis, Regression method, Filtration, oil.

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Authors: Yasuo Obikane

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This work is to study a roll of the fluctuating density gradient in the compressible flows for the computational fluid dynamics (CFD). A new anisotropy tensor with the fluctuating density gradient is introduced, and is used for an invariant modeling technique to model the turbulent density gradient correlation equation derived from the continuity equation. The modeling equation is decomposed into three groups: group proportional to the mean velocity, and that proportional to the mean strain rate, and that proportional to the mean density. The characteristics of the correlation in a wake are extracted from the results by the two dimensional direct simulation, and shows the strong correlation with the vorticity in the wake near the body. Thus, it can be concluded that the correlation of the density gradient is a significant parameter to describe the quick generation of the turbulent property in the compressible flows.

Keywords: Turbulence Modeling , Density Gradient Correlation, Compressible

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Authors: Aumnad Phdungsilp, Teeradej Wuttipornpun

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Decision support based upon risk analysis into comparison of the electricity generation from different renewable energy technologies can provide information about their effects on the environment and society. The aim of this paper is to develop the assessment framework regarding risks to health and environment, and the society-s benefits of the electric power plant generation from different renewable sources. The multicriteria framework to multiattribute risk analysis technique and the decision analysis interview technique are applied in order to support the decisionmaking process for the implementing renewable energy projects to the Bangkok case study. Having analyses the local conditions and appropriate technologies, five renewable power plants are postulated as options. As this work demonstrates, the analysis can provide a tool to aid decision-makers for achieving targets related to promote sustainable energy system.

Keywords: Analytic Hierarchy Process, Bangkok, MultiattributeRisk Analysis, Renewable Energy Technology.

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Authors: Rafayel A. Azizyan, Aram E. Gevogyan, Valeri B. Arakelyan, Emil S. Gevorgyan

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The mathematical modeling of different biological processes is usually used to predict or assess behavior of systems in which these processes take place. This study deals with mathematical and computer modeling of bi-substrate enzymatic reactions with ping-pong mechanism, which play an important role in different biochemical pathways. Besides that, three models of competitive inhibition were designed using different software packages. The main objective of this study is to represent the results from in silico investigation of bi-substrate enzymatic reactions with ordered pingpong mechanism in the presence of competitive inhibitors, as well as to describe in details the inhibition effects. The simulation of the models with certain kinetic parameters allowed investigating the behavior of reactions as well as determined some interesting aspects concerning influence of different cases of competitive inhibition. Simultaneous presence of two inhibitors, competitive to the S1 and S2 substrates have been studied. Moreover, we have found the pattern of simultaneous influence of both inhibitors.

Keywords: Mathematical modeling, bi-substrate enzymatic reactions, ping-pong mechanism, competitive inhibition.

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Authors: Labar Hocine, Dgeghader Yacine, Kelaiaia Mounia Samira, Bounaya Kamel

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To maximise furnace production it-s necessary to optimise furnace control, with the objectives of achieving maximum power input into the melting process, minimum network distortion and power-off time, without compromise on quality and safety. This can be achieved with on the one hand by an appropriate electrode control and on the other hand by a minimum of AC transformer switching. Electrical arc is a stochastic process; witch is the principal cause of power quality problems, including voltages dips, harmonic distortion, unbalance loads and flicker. So it is difficult to make an appropriate model for an Electrical Arc Furnace (EAF). The factors that effect EAF operation are the melting or refining materials, melting stage, electrode position (arc length), electrode arm control and short circuit power of the feeder. So arc voltages, current and power are defined as a nonlinear function of the arc length. In this article we propose our own empirical function of the EAF and model, for the mean stages of the melting process, thanks to the measurements in the steel factory.

Keywords: Modelling, electrical arc, melting, power, EAF, steel.

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Authors: Vijay Kumar Sharma, Manisha Pattanaik, Balwinder Raj

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Minimizations of power dissipation, chip area with higher circuit performance are the necessary and key parameters in deep submicron regime. The leakage current increases sharply in deep submicron regime and directly affected the power dissipation of the logic circuits. In deep submicron region the power dissipation as well as high performance is the crucial concern since increasing importance of portable systems. Number of leakage reduction techniques employed to reduce the leakage current in deep submicron region but they have some trade-off to control the leakage current. ONOFIC approach gives an excellent agreement between power dissipation and propagation delay for designing the efficient CMOS logic circuits. In this article ONOFIC approach is compared with LECTOR technique and output results show that ONOFIC approach significantly reduces the power dissipation and enhance the speed of the logic circuits. The lower power delay product is the big outcome of this approach and makes it an influential leakage reduction technique.

Keywords: Deep submicron, Leakage Current, LECTOR, ONOFIC, Power Delay Product

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Authors: Jianping Hu, Xiaolei Sheng

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This paper introduces an adiabatic register file based on two-phase CPAL (Complementary Pass-Transistor Adiabatic Logic circuits) with power-gating scheme, which can operate on a single-phase power clock. A 32×32 single-phase adiabatic register file with power-gating scheme has been implemented with TSMC 0.18μm CMOS technology. All the circuits except for the storage cells employ two-phase CPAL circuits, and the storage cell is based on the conventional memory one. The two-phase non-overlap power-clock generator with power-gating scheme is used to supply the proposed adiabatic register file. Full-custom layouts are drawn. The energy and functional simulations have been performed using the net-list extracted from their layouts. Compared with the traditional static CMOS register file, HSPICE simulations show that the proposed adiabatic register file can work very well, and it attains about 73% energy savings at 100 MHz.

Keywords: Low power, Register file, Complementarypass-transistor logic, Adiabatic logic, Single-phase power clock.

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Authors: Banaja Mohanty, Prakash Kumar Hota

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This paper demonstrates dynamic performance evaluation of load frequency control (LFC) with different intelligent techniques. All non-linearities and physical constraints have been considered in simulation studies such as governor dead band (GDB), generation rate constraint (GRC) and boiler dynamics. The conventional integral time absolute error has been considered as objective function. The design problem is formulated as an optimisation problem and particle swarm optimisation (PSO), bacterial foraging optimisation algorithm (BFOA) and differential evolution (DE) are employed to search optimal controller parameters. The superiority of the proposed approach has been shown by comparing the results with published fuzzy logic control (FLC) for the same interconnected power system. The comparison is done using various performance measures like overshoot, undershoot, settling time and standard error criteria of frequency and tie-line power deviation following a step load perturbation (SLP). It is noticed that, the dynamic performance of proposed controller is better than FLC. Further, robustness analysis is carried out by varying the time constants of speed governor, turbine, tie-line power in the range of +40% to -40% to demonstrate the robustness of the proposed DE optimized PID controller.

Keywords: Automatic generation control, governor dead band, generation rate constraint, differential evolution.

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Authors: Bu Seog Ju, Woo Young Jung

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The cost of damage to the non-structural systems in critical facilities like nuclear power plants and hospitals can exceed 80% of the total cost of damage during an earthquake. The failure of nonstructural components, especially, piping systems led to leakage of water and subsequent shut-down of hospitals immediately after the event. Consequently, the evaluation of performance of these types of structural configurations has become necessary to mitigate the risk and to achieve reliable designs. This paper focuses on a methodology to evaluate the static and dynamic characteristics of complex actual piping system based on NFPA-13 and SMACNA guidelines. The result of this study revealed that current piping system subjected to design lateral force and design spectrum based on UBC-97 was failed in both cases and mode shapes between piping system and building structure were very different

Keywords: Nonstructural component, piping, hospital, seismic, bracing.

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