Search results for: Short term wind speed prediction

Authors: Ali Hussian Ali AlTimemy, Fawzi M. Al Naima

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This paper presents the prediction of kidney dysfunction using different neural network (NN) approaches. Self organization Maps (SOM), Probabilistic Neural Network (PNN) and Multi Layer Perceptron Neural Network (MLPNN) trained with Back Propagation Algorithm (BPA) are used in this study. Six hundred and sixty three sets of analytical laboratory tests have been collected from one of the private clinical laboratories in Baghdad. For each subject, Serum urea and Serum creatinin levels have been analyzed and tested by using clinical laboratory measurements. The collected urea and cretinine levels are then used as inputs to the three NN models in which the training process is done by different neural approaches. SOM which is a class of unsupervised network whereas PNN and BPNN are considered as class of supervised networks. These networks are used as a classifier to predict whether kidney is normal or it will have a dysfunction. The accuracy of prediction, sensitivity and specificity were found for each type of the proposed networks .We conclude that PNN gives faster and more accurate prediction of kidney dysfunction and it works as promising tool for predicting of routine kidney dysfunction from the clinical laboratory data.

Keywords: Kidney Dysfunction, Prediction, SOM, PNN, BPNN, Urea and Creatinine levels.

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Authors: Poopak Roshanfekr, Torbjörn Thiringer, Sonja Lundmark, Mikael Alatalo

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This article presents a performance comparison of an interior mounted permanent magnet synchronous generator (IPMSG) with a synchronous reluctance generator (SynRG) with the same size for a wind application. It is found that using the same geometrical dimensions, a SynRG can convert 74 % of the power that an IPMSG can convert, while it has 80% of the IPMSG weight. Moreover it is found that the efficieny for the IMPSG is 99% at rated power compared to 98.7% for the SynRG.

Keywords: Interior mounted permanent magnet synchronous generator (IPMSG), synchronous reluctance generator (SynRG), wind energy, annual energy efficiency.

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Authors: Alan Crowle, Philpp Thies

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s the floating offshore wind turbine industry continues to develop and grow, the capabilities of established port facilities need to be assessed as to their ability to support the expanding construction and installation requirements. This paper assesses current infrastructure requirements and projected changes to port facilities that may be required to support the floating offshore wind industry. Understanding the infrastructure needs of the floating offshore renewable industry will help to identify the port-related requirements. Floating offshore wind turbines can be installed further out to sea and in deeper waters than traditional fixed offshore wind arrays, meaning it can take advantage of stronger winds. Separate ports are required for substructure construction, fit-out of the turbines, moorings, subsea cables and maintenance. Large areas are required for the laydown of mooring equipment, inter array cables, turbine blades and nacelles. The capabilities of established port facilities to support floating wind farms are assessed by evaluation of size of substructures, height of wind turbine with regards to the cranes for fitting of blades, distance to offshore site and offshore installation vessel characteristics. The paper will discuss the advantages and disadvantages of using large land based cranes, inshore floating crane vessels or offshore crane vessels at the fit-out port for the installation of the turbine. Water depths requirements for import of materials and export of the completed structures will be considered. There are additional costs associated with any emerging technology. However, part of the popularity of Floating Offshore Wind Turbines stems from the cost savings against permanent structures like fixed wind turbines. Floating Offshore Wind Turbine developers can benefit from lighter, more cost effective equipment which can be assembled in port and towed to site rather than relying on large, expensive installation vessels to transport and erect fixed bottom turbines. The ability to assemble Floating Offshore Wind Turbines equipment on shore means minimising highly weather dependent operations like offshore heavy lifts and assembly, saving time and costs and reducing safety risks for offshore workers. Maintenance might take place in safer onshore conditions for barges and semi submersibles. Offshore renewables, such as floating wind, can take advantage of this wealth of experience, while oil and gas operators can deploy this experience at the same time as entering the renewables space. The floating offshore wind industry is in the early stages of development and port facilities are required for substructure fabrication, turbine manufacture, turbine construction and maintenance support. The paper discusses the potential floating wind substructures as this provides a snapshot of the requirements at the present time, and potential technological developments required for commercial development. Scaling effects of demonstration-scale projects will be addressed; however the primary focus will be on commercial-scale (30+ units) device floating wind energy farms.

Keywords: Floating offshore wind turbine, port logistics, installation, construction.

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Authors: Tae Yun Chung, Jungho Moon, Tae Kwon Ha

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Al/Cu clad sheet has been fabricated by using differential speed rolling (DSR) process, which caused severe shear deformation between Al and Cu plate to easily bond to each other. Rolling was carried out at 100 and 150oC with speed ratios from 1.4 to 2.2, in which the total thickness reduction was in the range between 14 and 46%. Interfacial microstructure and mechanical properties of Al/Cu clad were investigated by scanning electron microscope equipped with energy dispersive X-ray detector, and tension tests. The DSR process was very effective to provide a good interface for atoms diffusion during subsequent annealing. The strength of bonding was higher with the increasing speed ratio. Post heat treatment enhanced the mechanical properties of clad sheet by forming intermetallic compounds in the interface area. 

Keywords: Aluminum/Copper clad sheet, Differential speed rolling, Interface microstructure, Annealing, Tensile test.

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Authors: A. U. Haque, W. Asrar, A. A. Omar, E. Sulaeman, J. S. Mohamed Ali

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Due to the interference effects, the intrinsic aerodynamic parameters obtained from the individual component testing are always fundamentally different than those obtained for complete model testing. Consideration and limitation for such testing need to be taken into account in any design work related to the component buildup method. In this paper, the scaled model of a straight rectangular canard of a hybrid buoyant aircraft is tested at 50 m/s in IIUM-LSWT (Low Speed Wind Tunnel). Model and its attachment with the balance are kept rigid to have results free from the aeroelastic distortion. Based on the velocity profile of the test section’s floor; the height of the model is kept equal to the corresponding boundary layer displacement. Balance measurements provide valuable but limited information of overall aerodynamic behavior of the model. Zero lift coefficient is obtained at -2.2o and the corresponding drag coefficient was found to be less than that at zero angle of attack. As a part of the validation of low fidelity tool, plot of lift coefficient plot was verified by the experimental data and except the value of zero lift coefficients, the overall trend has under predicted the lift coefficient. Based on this comparative study, a correction factor of 1.36 is proposed for lift curve slope obtained from the panel method.

Keywords: Wind tunnel testing, boundary layer displacement, lift curve slope, canard, aerodynamics.

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Authors: Su Ying-Ming

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High density of high rise buildings in urban areas lead to a deteriorative Urban Heat Island Effect, gradually. This study focuses on discussing the relationship between urban layout and ventilation comfort in street canyons. This study takes Songjiang Nanjing Rd. area of Taipei, Taiwan as an example to evaluate the wind environment comfort index by field measurement and Computational Fluid Dynamics (CFD) to improve both the quality and quantity of the environment. In this study, different factors including street blocks size, the width of buildings, street width ratio and the direction of the wind were used to discuss the potential of ventilation. The environmental wind field was measured by the environmental testing equipment, Testo 480. Evaluation of blocks sizes, the width of buildings, street width ratio and the direction of the wind was made under the condition of constant floor area with the help of Stimulation CFD to adjust research methods for optimizing regional wind environment. The results of this study showed the width of buildings influences the efficiency of outdoor ventilation; improvement of the efficiency of ventilation with large street width was also shown. The study found that Block width and H/D value and PR value has a close relationship. Furthermore, this study showed a significant relationship between the alteration of street block geometry and outdoor comfortableness.

Keywords: Urban ventilation path, ventilation efficiency indices, CFD, building layout.

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Authors: M. Chandrasekaran, D. Devarasiddappa

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Metal matrix composites have been increasingly used as materials for components in automotive and aerospace industries because of their improved properties compared with non-reinforced alloys. During machining the selection of appropriate machining parameters to produce job for desired surface roughness is of great concern considering the economy of manufacturing process. In this study, a surface roughness prediction model using fuzzy logic is developed for end milling of Al-SiCp metal matrix composite component using carbide end mill cutter. The surface roughness is modeled as a function of spindle speed (N), feed rate (f), depth of cut (d) and the SiCp percentage (S). The predicted values surface roughness is compared with experimental result. The model predicts average percentage error as 4.56% and mean square error as 0.0729. It is observed that surface roughness is most influenced by feed rate, spindle speed and SiC percentage. Depth of cut has least influence.

Keywords: End milling, fuzzy logic, metal matrix composites, surface roughness

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Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: Decision tree, genetic algorithm, machine learning, software defect prediction.

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Authors: Tebogo Emma Makaba, Barnabas Ndlovu Gatsheni

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The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.

Keywords: Bagging ensemble methods, confusion matrix, multi-layer perceptron, vehicle traffic flow.

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Authors: Chantawan Noisri, Robert Harold Buchanan Exell

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A simple model for studying convectional lifting processes in the tropics is described in this paper with some tests of the model in dry air. The model consists of the density equation, the wind equation, the vertical velocity equation, and the temperature equation. The model domain is two-dimensional with length 100 km and height 17.5 km. Plan for experiments to investigate the effects of the heating surface, the deep convection approximation and the treatment of velocities at the boundaries are discussed. Equations for the simplified treatment of moisture in the atmosphere in future numerical experiments are also given.

Keywords: Numerical weather prediction, Finite differences, Convection lifting.

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Authors: Arun Kumar Datta, Manisha Dubey, Shailendra Jain

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Electric machines are driven nowadays by static system popularly known as soft starter. This paper describes a thyristor based static frequency converter (SFC) to run a large synchronous machine installed at a short circuit test laboratory. Normally a synchronous machine requires prime mover or some other driving mechanism to run. This machine doesn’t need a prime mover as it operates in dual mode. In the beginning SFC starts this machine as a motor to achieve the full speed. Thereafter whenever required it can be converted to generator mode. This paper begins with the various starting methodology of synchronous machine. Detailed of SFC with different operational modes have been analyzed. Shaft voltage is a very common phenomenon for the machines with static drives. Various causes of shaft voltages in perspective with this machine are the main attraction of this paper.

Keywords: Capacitive coupling, electric discharge machining, inductive coupling, Shaft voltage, static frequency converter.

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Authors: D. Czurratis, Y. Beyl, S. Zinober, R. Zengerle, F. Lärmer

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A new concept for long-term reagent storage for Labon- a-Chip (LoC) devices is described. Here we present a polymer multilayer stack with integrated stick packs for long-term storage of several liquid reagents, which are necessary for many diagnostic applications. Stick packs are widely used in packaging industry for storing solids and liquids for long time. The storage concept fulfills two main requirements: First, a long-term storage of reagents in stick packs without significant losses and interaction with surroundings, second, on demand releasing of liquids, which is realized by pushing a membrane against the stick pack through pneumatic pressure. This concept enables long-term on-chip storage of liquid reagents at room temperature and allows an easy implementation in different LoC devices.

Keywords: Lab-on-a-Chip, long-term storage, reagent storage, stick pack.

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Authors: Hiroki Satou, Kayoko Yamamoto

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This study aims to propose three evaluation methods to evaluate the Tokyo Cap and Trade Program when emissions trading is performed virtually among enterprises, focusing on carbon dioxide (CO2), which is the only emitted greenhouse gas that tends to increase. The first method clarifies the optimum reduction rate for the highest cost benefit, the second discusses emissions trading among enterprises through market trading, and the third verifies long-term emissions trading during the term of the plan (2010-2019), checking the validity of emissions trading partly using Geographic Information Systems (GIS). The findings of this study can be summarized in the following three points. 1. Since the total cost benefit is the greatest at a 44% reduction rate, it is possible to set it more highly than that of the Tokyo Cap and Trade Program to get more total cost benefit. 2. At a 44% reduction rate, among 320 enterprises, 8 purchasing enterprises and 245 sales enterprises gain profits from emissions trading, and 67 enterprises perform voluntary reduction without conducting emissions trading. Therefore, to further promote emissions trading, it is necessary to increase the sales volumes of emissions trading in addition to sales enterprises by increasing the number of purchasing enterprises. 3. Compared to short-term emissions trading, there are few enterprises which benefit in each year through the long-term emissions trading of the Tokyo Cap and Trade Program. Only 81 enterprises at the most can gain profits from emissions trading in FY 2019. Therefore, by setting the reduction rate more highly, it is necessary to increase the number of enterprises that participate in emissions trading and benefit from the restraint of CO2 emissions.

Keywords: Emissions Trading, Tokyo Cap and Trade Program, Carbon Dioxide (CO2), Global Warming, Geographic Information Systems (GIS)

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Authors: G. H. Senussi

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The present work is concerned with the effect of turning process parameters (cutting speed, feed rate, and depth of cut) and distance from the center of work piece as input variables on the chip micro-hardness as response or output. Three experiments were conducted; they were used to investigate the chip micro-hardness behavior at diameter of work piece for 30[mm], 40[mm], and 50[mm]. Response surface methodology (R.S.M) is used to determine and present the cause and effect of the relationship between true mean response and input control variables influencing the response as a two or three dimensional hyper surface. R.S.M has been used for designing a three factor with five level central composite rotatable factors design in order to construct statistical models capable of accurate prediction of responses. The results obtained showed that the application of R.S.M can predict the effect of machining parameters on chip micro-hardness. The five level factorial designs can be employed easily for developing statistical models to predict chip micro-hardness by controllable machining parameters. Results obtained showed that the combined effect of cutting speed at it?s lower level, feed rate and depth of cut at their higher values, and larger work piece diameter can result increasing chi micro-hardness.

Keywords: Machining Parameters, Chip Micro-Hardness, CNCMachining, 304-Austenic Stainless Steel.

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Authors: M. Hassani, Y. Hassani, N. Ajudanioskooei, N. N. Benvid

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Laser Forming process as a non-contact thermal forming process is widely used to forming and bending of metallic and non-metallic sheets. In this process, according to laser irradiation along a specific path, sheet is bent. One of the most important output parameters in laser forming is bending angle that depends on process parameters such as physical and mechanical properties of materials, laser power, laser travel speed and the number of scan passes. In this paper, Artificial Neural Network and Fuzzy Logic System were used to predict of bending angle in laser forming process. Inputs to these models were laser travel speed and laser power. The comparison between artificial neural network and fuzzy logic models with experimental results has been shown both of these models have high ability to prediction of bending angles with minimum errors.

Keywords: Artificial neural network, bending angle, fuzzy logic, laser forming.

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Authors: M. W. Siddiqi, M. Ilyas

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Availability and mobilization of revenue is the main essential with which an economy is managed and run. While planning or while making the budgets nations set revenue targets to be achieved. But later when the accounts are closed the actual collections of revenue through taxes or even the non-tax revenue collection would invariably be different as compared to the initial estimates and targets set to be achieved. This revenue-gap distorts the whole system and the economy disturbing all the major macroeconomic indicators. This study is aimed to find out short and long term impact of revenue gap on budget deficit, debt burden and economic growth on the economy of Pakistan. For this purpose the study uses autoregressive distributed lag approach to cointegration and error correction mechanism on three different models for the period 1980 to 2009. The empirical results show that revenue gap has a short and long run relationship with economic growth and budget deficit. However, revenue gap has no impact on debt burden.

Keywords: Revenue Gap, Economic Growth, Budget Deficit, Debt Burden

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Authors: Juhan Kim, Howon Kim

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EPC Class-1 Generation-2 UHF tags, one of Radio frequency identification or RFID tag types, is expected that most companies are planning to use it in the supply chain in the short term and in consumer packaging in the long term due to its inexpensive cost. Because of the very cost, however, its resources are extremely scarce and it is hard to have any valuable security algorithms in it. It causes security vulnerabilities, in particular cloning the tags for counterfeits. In this paper, we propose a product authentication solution for anti-counterfeiting at application level in the supply chain and mobile RFID environment. It aims to become aware of distribution of spurious products with fake RFID tags and to provide a product authentication service to general consumers with mobile RFID devices like mobile phone or PDA which has a mobile RFID reader. We will discuss anti-counterfeiting mechanisms which are required to our proposed solution and address requirements that the mechanisms should have.

Keywords: EPC, RFID, Anti-Counterfeiting, Mobile RFIDenvironment.

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Authors: A. Larabi, M. S. Boucherit

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In this paper, we show that the association of the PI regulators for the speed and stator currents with a control strategy using the linearization by state feedback for an induction machine without speed sensor, and with an adaptation of the rotor resistance. The rotor speed is estimated by using the model reference adaptive system approach (MRAS). This method consists of using two models: The first is the reference model and the second is an adjustable one in which two components of the stator flux, obtained from the measurement of the currents and stator voltages are estimated. The estimated rotor speed is then obtained by canceling the difference between stator-flux of the reference model and those of the adjustable one. Satisfactory results of simulation are obtained and discussed in this paper to highlight the proposed approach.

Keywords: Asynchronous actuator, PI Regulator, adaptivemethod with reference model, Vector control.

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Authors: Zicheng Wang

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Offshore wind energy provides a huge potential for the expansion of renewable energies to the coastal countries. High demands are required concerning the shape and type of foundations for offshore wind turbines (OWTs) to find an economically, technically and environmentally-friendly optimal solution. A promising foundation concept is the hybrid foundation system, which consists of a steel plate attached to the outer side of a hollow steel pipe pile. In this study, the bearing behavior of a large diameter foundation is analyzed using a 3-dimensional finite element (FE) model. Non-linear plastic soil behavior is considered. The results of the numerical simulations are compared to highlight the priority of the hybrid foundation to the conventional monopile foundation.

Keywords: Hybrid foundation system, mechanical parameters, plastic soil behaviors, numerical simulations.

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Authors: Jackson H. W. Chang, Jedol Dayou, Justin Sentian

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Long terms variation of solar insolation had been widely studied. However, its parallel observations in short time scale is rather lacking. This paper aims to investigate the short time scale evolution of solar radiation spectrum (UV, PAR, and NIR bands) due to atmospheric aerosols and water vapors. A total of 25 days of global and diffused solar spectrum ranges from air mass 2 to 6 were collected using ground-based spectrometer with shadowband technique. The result shows that variation of solar radiation is the least in UV fraction, followed by PAR and the most in NIR. Broader variations in PAR and NIR are associated with the short time scale fluctuations of aerosol and water vapors. The corresponding daily evolution of UV, PAR, and NIR fractions implies that aerosol and water vapors variation could also be responsible for the deviation pattern in the Langley-plot analysis.

Keywords: Aerosol, short time scale variation, solar radiation, water vapor.

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Authors: Sherif. S. Nafee, Ameer. K. Al-Ramady, Salem. A. Shaheen

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The analytical prediction of the decay heat results from the fast neutron fission of actinides was initiated under a project, 10-MAT1134-3, funded by king Abdulaziz City of Science and Technology (KASCT), Long-Term Comprehensive National Plan for Science, Technology and Innovations, managed by a team from King Abdulaziz University (KAU), Saudi Arabia, and supervised by Argonne National Laboratory (ANL) has collaborated with KAU's team to assist in the computational analysis. In this paper, the numerical solution of coupled linear differential equations that describe the decays and buildups of minor fission product MFA, has been used to predict the total decay heat and its components from the fast neutron fission of 235U and 239Pu. The reliability of the present approach is illustrated via systematic comparisons with the measurements reported by the University of Tokyo, in YAYOI reactor.

Keywords: Decay heat, fast neutron fission, and Numerical Solution of Linear Differential Equations.

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Authors: Youcef Bekakra, Djilani Ben attous

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In this paper, a field oriented control (FOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the Model Reference Adaptive System (MRAS) scheme, the rotor speed is tuned to obtain an exact FOC induction motor drive. The reference and adjustable models, developed in stationary stator reference frame, are used in the MRAS scheme to estimate induction rotor speed from measured terminal voltages and currents. The Integral Proportional (IP) gains speed controller are tuned by a modern approach that is the Particle Swarm Optimization (PSO) algorithm in order to optimize the parameters of the IP controller. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. The proposed algorithm has been tested by numerical simulation, showing the capability of driving load.

Keywords: Induction motor drive, field oriented control, model reference adaptive system (MRAS), particle swarm optimization (PSO).

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Authors: Yu Bin, Zhang Yan

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The prediction of transmembrane helical segments (TMHs) in membrane proteins is an important field in the bioinformatics research. In this paper, a new method based on discrete wavelet transform (DWT) has been developed to predict the number and location of TMHs in membrane proteins. PDB coded as 1KQG was chosen as an example to describe the prediction of the number and location of TMHs in membrane proteins by using this method. To access the effect of the method, 80 proteins with known 3D-structure from Mptopo database are chosen at random as the test objects (including 325 TMHs), 308 of which can be predicted accurately, the average predicted accuracy is 96.3%. In addition, the above 80 membrane proteins are divided into 13 groups according to their function and type. In particular, the results of the prediction of TMHs of the 13 groups are satisfying.

Keywords: discrete wavelet transform, hydrophobicity, membrane protein, transmembrane helical segments

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Authors: Asmir Gogic, Aljo Mujcic, Sandra Ibric, Nermin Suljanovic

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Ubiquity of natural disasters during last few decades have risen serious questions towards the prediction of such events and human safety. Every disaster regardless its proportion has a precursor which is manifested as a disruption of some environmental parameter such as temperature, humidity, pressure, vibrations and etc. In order to anticipate and monitor those changes, in this paper we propose an overall system for disaster prediction and monitoring, based on wireless sensor network (WSN). Furthermore, we introduce a modified and simplified WSN routing protocol built on the top of the trickle routing algorithm. Routing algorithm was deployed using the bluetooth low energy protocol in order to achieve low power consumption. Performance of the WSN network was analyzed using a real life system implementation. Estimates of the WSN parameters such as battery life time, network size and packet delay are determined. Based on the performance of the WSN network, proposed system can be utilized for disaster monitoring and prediction due to its low power profile and mesh routing feature.

Keywords: Bluetooth low energy, disaster prediction, mesh routing protocols, wireless sensor networks.

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: Deep learning, long-short-term memory, energy, renewable energy load forecasting.

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Authors: Maziar Ramezani, Thomas Neitzert, Timotius Pasang

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This paper aims at experimental and numerical investigation of springback behavior of sheet metals during L-bending process with emphasis on Stribeck-type friction modeling. The coefficient of friction in Stribeck curve depends on sliding velocity and contact pressure. The springback behavior of mild steel and aluminum alloy 6022-T4 sheets was studied experimentally and using numerical simulations with ABAQUS software with two types of friction model: Coulomb friction and Stribeck friction. The influence of forming speed on springback behavior was studied experimentally and numerically. The results showed that Stribeck-type friction model has better results in predicting springback in sheet metal forming. The FE prediction error for mild steel and 6022-T4 AA is 23.8%, 25.5% respectively, using Coulomb friction model and 11%, 13% respectively, using Stribeck friction model. These results show that Stribeck model is suitable for simulation of sheet metal forming especially at higher forming speed.

Keywords: Friction, L-bending, Springback, Stribeck curves.

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Authors: Jurifa Mat Lazi, Zulkifilie Ibrahim, Marizan Sulaiman, Fizatul Aini Patakor, Siti Noormiza Mat Isa

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Dual motor drives fed by single inverter is purposely designed to reduced size and cost with respect to single motor drives fed by single inverter. Previous researches on dual motor drives only focus on the modulation and the averaging techniques. Only a few of them, study the performance of the drives based on different speed controller other than Proportional and Integrator (PI) controller. This paper presents a detailed comparative study on fuzzy rule-base in Fuzzy Logic speed Controller (FLC) for Dual Permanent Magnet Synchronous Motor (PMSM) drives. Two fuzzy speed controllers which are standard and simplified fuzzy speed controllers are designed and the results are compared and evaluated. The standard fuzzy controller consists of 49 rules while the proposed controller consists of 9 rules determined by selecting the most dominant rules only. Both designs are compared for wide range of speed and the robustness of both controllers over load disturbance changes is tested to demonstrate the effectiveness of the simplified/reduced rulebase.

Keywords: Dual Motor Drives, Fuzzy Logic Speed Controller, Reduced Rule-Base, PMSM

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Authors: M. Jalali Azizpour, H. Mohammadi majd

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In this paper, the wear of high speed steel hobs during hobbing has been studied. The wear mechanisms are strongly influenced by the choice of cutting speed. At moderate and high cutting speeds three major wear mechanisms were identified: abrasion, mild adhesive and severe adhesive. The microstructure and wear behavior of two high speed steel grades (M2 and ASP30) has been compared. In contrast, a variation in chemical composition or microstructure of HSS tool material generally did not change the dominant wear mechanism. However, the tool material properties determine the resistance against the operating wear mechanism and consequently the tool life. The metallographic analysis and wear measurement at the tip of hob teeth included scanning electron microscopy and stereoscope microscopy. Roughness profilometery is used for measuring the gear surface roughness.

Keywords: abrasion, adhesion, cutting speed, hobbing, wear mechanism

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Authors: Yingyi Zhou, Tohru Kawabe

Abstract:

With the spread of EVs (electric Vehicles), the ride comfort has been gaining a lot of attention. The influence of the lateral acceleration is important for the improvement of ride comfort of EVs as well as the longitudinal acceleration, especially upon turning of the vehicle. Therefore, this paper proposes a practical optimal speed control method to greatly improve the ride comfort in the vehicle turning situation. For consturcting this method, effective criteria that can appropriately evaluate deterioration of ride comfort is derived. The method can reduce the influence of both the longitudinal and the lateral speed changes for providing a confortable ride. From several simulation results, we can see the fact that the method can prevent aggravation of the ride comfort by suppressing the influence of longitudinal speed change in the turning situation. Hence, the effectiveness of the method is recognized.

Keywords: Electric vehicle, speed control, ride comfort, optimal control theory, driving support system.

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Authors: D. S. Mohale, A. V. Chandewar

Abstract:

Aim- Study was undertaken to investigate the effect of altered behavioral condition like depression on various oxidative stress markers and biochemical parameters in rats. Methods- Rats were subjected for short (21 days) and long term (84 days) social isolation; the rats displayed an increase in depression on force swim test relative to control. Various markers of oxidative stress like lipid per oxidation (LPO), reduced glutathione (GSH), Supers oxide dismutase (SOD), catalase (CAT) and biochemical parameters like SGOT, SGPT, and blood glucose were determined. Results- There was significant increase in the level of LPO and decrease in the levels of GSH, SOD and CAT after long term isolation. Biochemical parameters were significantly altered after social isolation. Conclusion- Increased oxidative stress in depression which may leads to alteration of biochemical parameters.

Keywords: Depression, Glucose, LPO, Oxidative stress.

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