Search results for: Wind-pvdiesel hybrid system.

Authors: Pavan K. Rallabandi, Kailash C. Patidar

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In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence/pattern recognition/classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: Hybrid systems, Hidden Markov Models, Recurrent neural networks, Deterministic finite state automata.

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Authors: Jonqlan Lin, C. Y. Tasi, K. H. Lin

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This paper addresses the issue of the autonomous mobile robot (AMR) navigation task based on the hybrid control modes. The novel hybrid control mode, based on multi-sensors information by using the fuzzy approach, has been presented in this research. The system operates in real time, is robust, enables the robot to operate with imprecise knowledge, and takes into account the physical limitations of the environment in which the robot moves, obtaining satisfactory responses for a large number of different situations. An experiment is simulated and carried out with a pioneer mobile robot. From the experimental results, the effectiveness and usefulness of the proposed AMR obstacle avoidance and navigation scheme are confirmed. The experimental results show the feasibility, and the control system has improved the navigation accuracy. The implementation of the controller is robust, has a low execution time, and allows an easy design and tuning of the fuzzy knowledge base.

Keywords: Autonomous mobile robot, obstacle avoidance, MEMS, hybrid control mode, navigation control.

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Authors: Rahmah, M., Farhan, M., Akidah, N.M.Y

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Polybag and mulch film in agricultural field are used plastics which caused environmental problems after transplantation and planting processes due to the discarded wastes. Thus a degradable polybag was designed in this study to replace non degradable polybag with natural biodegradable resin that is widely available, namely sago starch (SS) and polyvinyl alcohol (PVA). Hybrid blend consists of SS, PVA and linear low density polyethylene (LLDPE) was compounded at different ratios. The thermal and mechanical properties of the blends were investigated. Hybrid films underwent landfill degradation tests for up to 2 months. The films showed gelation and melting transition existed for all three systems with significant melting peaks by LLDPE and PVA. All hybrid blends loses its LLDPE semi crystalline characteristics as PVA and SS systems had disrupted crystallinity and enhanced the amorphosity of the hybrid system. Generally, blending SS with PVA improves the mechanical properties of the SS based materials. Tensile strength of each film was also decreased with the increase of SS contents while its modulus had increased with SS content.

Keywords: Appearance peak, LLDPE, PVA, sago starch.

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Authors: Jia-Shiun Chen, Hsiu-Ying Hwang

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Hybrid electric vehicles can reduce pollution and improve fuel economy. Power-split hybrid electric vehicles (HEVs) provide two power paths between the internal combustion engine (ICE) and energy storage system (ESS) through the gears of an electrically variable transmission (EVT). EVT allows ICE to operate independently from vehicle speed all the time. Therefore, the ICE can operate in the efficient region of its characteristic brake specific fuel consumption (BSFC) map. The two-mode powertrain can operate in input-split or compound-split EVT modes and in four different fixed gear configurations. Power-split architecture is advantageous because it combines conventional series and parallel power paths. This research focuses on input-split and compound-split modes in the two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an internal combustion engine (ICE) and PI control for electric machines (EMs) are derived for the urban driving cycle simulation. These control algorithms reduce vehicle fuel consumption and improve ICE efficiency while maintaining the state of charge (SOC) of the energy storage system in an efficient range.

Keywords: Hybrid electric vehicle, fuel economy, two-mode hybrid, fuzzy control.

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Authors: S. M. Azad, H. Ghodsipour, F. Roshannafas

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In recent years ‘technology management and policymaking’ is one of the most important problems in management science. In this field, different generations of innovation and technology management are presented which the earliest one is Innovation System (IS) approach. In a general classification, innovation systems are divided in to 4 approaches: technical, sectoral, regional, and national. There are many researches in relation to each of these approaches in different academic fields. Every approach has some benefits. If two or more approaches hybrid, their benefits would be combined. In addition, according to the sectoral structure of the governance model in Iran, in many sectors, such as information technology, the combination of three other approaches with sectoral approach is essential. Hence, in this paper, combining two IS approaches (technical and sectoral) and using system dynamics, a generic model is presented for a sample of software industry. As a complimentary point, this article is introducing a new hybrid approach called Techno-Sectoral Innovation System. This TSIS model is accomplished by Changing concepts of the ‘functions’-which came from Technological IS literature- and using them into sectoral system as measurable indicators.

Keywords: Innovation system, technology, techno-sectoral system, functional indicators, system dynamics.

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Authors: Moudar H. A. Zgoul, Amin Al Zamer

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Adhesive materials and adhesion have been the focal point of multiple research works related to numerous applications, particularly, aerospace, and aviation industries. To enhance the properties of conventional adhesive materials, additives have been introduced to the mix in order to enhance their mechanical and physical properties by creating a hybrid adhesive material. The evaluation of the mechanical properties of such hybrid adhesive materials is thus of an essential requirement for the purpose of properly modeling their behavior accurately. This paper presents an approach/tool to simulate the behavior such hybrid adhesives in a way that will allow researchers to better understand their behavior while in service.

Keywords: Adhesive materials, analysis, hybrid adhesives, mechanical properties, simulation.

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Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: Artificial Immune System, Breast Cancer Diagnosis, Euclidean Function, Gaussian Function.

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Authors: A. Meydanlioglu, F. Arikan

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In recent years, thanks to the development of information and communication technologies, the computer and internet have been used widely in higher education. Internet-based education is impacting traditional higher education as online components increasingly become integrated into face- to- face (FTF) courses. The goal of combined internet-based and traditional education is to take full advantage of the benefits of each platform in order to provide an educational opportunity that can promote student learning better than can either platform alone. Research results show that the use of hybrid learning is more effective than online or FTF models in higher education. Due to the potential benefits, an increasing number of institutions are interested in developing hybrid courses, programs, and degrees. Future research should evaluate the effectiveness of hybrid learning. This paper is designed to determine the impact of hybrid learning on higher education.

Keywords: E-learning, higher education, hybrid learning, online education.

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Authors: Juan Portoviejo Brito, Daniel Icaza Alvarez, Christian Castro Samaniego

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In this article, we present the modeling, simulations, and energy conversion analysis of the solar-wind system for the Quingeo Heritage Center in Ecuador. A numerical model was constructed based on the 19 equations, it was coded in MATLAB R2017a, and the results were compared with the experimental data of the site. The model is built with the purpose of using it as a computer development for the optimization of resources and designs of hybrid systems in the Parish of Quingeo and its surroundings. The model obtained a fairly similar pattern compared to the data and curves obtained in the field experimentally and detailed in manuscript. It is important to indicate that this analysis has been carried out so that in the near future one or two of these power generation systems can be exploited in a massive way according to the budget assigned by the Parish GAD of Quingeo or other national or international organizations with the purpose of preserving this unique colonial helmet in Ecuador.

Keywords: Hybrid system, wind turbine, modeling, simulation, Smart Grid, Quingeo Azuay Ecuador.

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Authors: M. Senthil Arumugam, M.V.C. Rao

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This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.

Keywords: Hybrid systems, optimal control, real coded genetic algorithm (RCGA), Particle swarm optimization (PSO), Hybrid real coded GA (HRCGA), and Hybrid genetic operators.

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Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: Data mining, hybrid storage system, recurrent neural network, support vector machine.

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Authors: Atul K. Desai, Hemal J. Shah

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The tall windmill towers are designed as monopole tower or lattice tower. In the present research, a 125-meter high hybrid tower which is a combination of lattice and monopole type is proposed. The response of hybrid tower is compared with conventional monopole tower. The towers were analyzed in finite element method software considering nonlinear seismic time history load. The synthetic seismic time history for different soil is derived using the SeismoARTIF software. From the present research, it is concluded that, in the hybrid tower, we are not getting resonance condition. The base shear is less in hybrid tower compared to monopole tower for different soil conditions.

Keywords: Dynamic analysis, hybrid wind mill tower, resonance condition, synthetic time history.

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Authors: Kandarpa Kumar Sarma

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The key to the continued success of ANN depends, considerably, on the use of hybrid structures implemented on cooperative frame-works. Hybrid architectures provide the ability to the ANN to validate heterogeneous learning paradigms. This work describes the implementation of a set of Distributed and Hybrid ANN models for Character Recognition applied to Anglo-Assamese scripts. The objective is to describe the effectiveness of Hybrid ANN setups as innovative means of neural learning for an application like multilingual handwritten character and numeral recognition.

Keywords: Assamese, Feature, Recurrent.

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Authors: Z. Abdollahnejad, M. Kheradmand, F. Pacheco Torgal

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The workability of hybrid alkaline cements is a field of knowledge that still needs further research efforts. This paper reports experimental results of 32 hybrid cement mixes regarding the joint effect of sodium hydroxide concentration, the use of a commercial superplasticizer and a biopolymer on the flow and compressive strength performance. The results show that the use of commercial admixtures led to a slightly increase in the flow of mortars with lower sodium hydroxide concentration.

Keywords: Waste reuse, fly ash, waste glass, hybrid cement, biopolymer, polycarboxylate, flow.

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Authors: Ventura Assuncao

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In automotive systems almost all steps concerning the calibration of several control systems, e.g., low idle governor or boost pressure governor, are made with the vehicle because the timeto- production and cost requirements on the projects do not allow for the vehicle analysis necessary to build reliable models. Here is presented a procedure using parametric and NN (neural network) models that enables the generation of vehicle system models based on normal ECU engine control unit) vehicle measurements. These models are locally valid and permit pre and follow-up calibrations so that, only the final calibrations have to be done with the vehicle.

Keywords: Automotive systems, neuro-hybrid models, demodulator, nonlinear systems, identification, and neural networks.

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Authors: Kamalendu Pal

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This paper describes the main features of a knowledge-based system evaluation method. System evaluation is placed in the context of a hybrid legal decision-support system, Advisory Support for Home Settlement in Divorce (ASHSD). Legal knowledge for ASHSD is represented in two forms, as rules and previously decided cases. Besides distinguishing the two different forms of knowledge representation, the paper outlines the actual use of these forms in a computational framework that is designed to generate a plausible solution for a given case, by using rule-based reasoning (RBR) and case-based reasoning (CBR) in an integrated environment. The nature of suitability assessment of a solution has been considered as a multiple criteria decision-making process in ASHAD evaluation. The evaluation was performed by a combination of discussions and questionnaires with different user groups. The answers to questionnaires used in this evaluations method have been measured as a fuzzy linguistic term. The finding suggests that fuzzy linguistic evaluation is practical and meaningful in knowledge-based system development purpose. 

Keywords: Case-based reasoning, decision-support system, fuzzy linguistic term, rule-based reasoning, system evaluation.

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Authors: R. Satish, G. Raja Rao

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In this paper a hybrid distributed generation (DG) system connected to isolated load is studied. The DG system consisting of photo voltaic (PV) system, fuel cells, aqua electrolyzer, diesel engine generator and a battery energy storage system. The ambient temperature value of PV is taken as constant to make the output power of PV is directly proportional to the radiation and output power of other DG sources and frequency of the system is controlled by simple integral (I), proportional plus integral (PI), and proportional plus integral and derivative(PID) controllers. A maiden attempt is made to apply a more recent and powerful optimization technique named as bacterial foraging technique for optimization of controllers gains of the proposed hybrid DG system. The system responses with bacterial foraging based controllers are compared with that of classical method. Investigations reveal that bacterial foraging based controllers gives better responses than the classical method and also PID controller is best. Sensitivity analysis is carried out which demonstrates the robustness of the optimized gain values for system loading condition.

Keywords: Aqua electrolyzer, bacterial foraging, battery energy storage system, diesel engine generator, distributed generation, fuel cells, photo voltaic system.

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Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

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In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other.

As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO.

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Authors: Ashkan Ebadi, Adam Krzyzak

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Recommender systems, also known as recommender engines, have become an important research area and are now being applied in various fields. In addition, the techniques behind the recommender systems have been improved over the time. In general, such systems help users to find their required products or services (e.g. books, music) through analyzing and aggregating other users’ activities and behavior, mainly in form of reviews, and making the best recommendations. The recommendations can facilitate user’s decision making process. Despite the wide literature on the topic, using multiple data sources of different types as the input has not been widely studied. Recommender systems can benefit from the high availability of digital data to collect the input data of different types which implicitly or explicitly help the system to improve its accuracy. Moreover, most of the existing research in this area is based on single rating measures in which a single rating is used to link users to items. This paper proposes a highly accurate hotel recommender system, implemented in various layers. Using multi-aspect rating system and benefitting from large-scale data of different types, the recommender system suggests hotels that are personalized and tailored for the given user. The system employs natural language processing and topic modelling techniques to assess the sentiment of the users’ reviews and extract implicit features. The entire recommender engine contains multiple sub-systems, namely users clustering, matrix factorization module, and hybrid recommender system. Each sub-system contributes to the final composite set of recommendations through covering a specific aspect of the problem. The accuracy of the proposed recommender system has been tested intensively where the results confirm the high performance of the system.

Keywords: Tourism, hotel recommender system, hybrid, implicit features.

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Authors: Hassan El Maia, Ahmed Hammouch, Driss Aboutajdine

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This work presents an approach for the construction of a hybrid color-texture space by using mutual information. Feature extraction is done by the Laws filter with SVM (Support Vectors Machine) as a classifier. The classification is applied on the VisTex database and a SPOT HRV (XS) image representing two forest areas in the region of Rabat in Morocco. The result of classification obtained in the hybrid space is compared with the one obtained in the RGB color space.

Keywords: Color, texture, laws filter, mutual information, SVM, hybrid space.

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Authors: S. S. Ghodsi, M. H. Mehrabi, Zainah Ibrahim, Meldi Suhatril

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This research examines the performance of a hybrid passive control device for enhancing the seismic response of steel frame structures. The device design comprises a damper which employs a viscoelastic material to control both shear and axial strain. In the design, energy is dissipated through the shear strain of a two-layer system of viscoelastic pads which are located between steel plates. In addition, viscoelastic blocks have been included on either side of the main shear damper which obtains compressive strains in the viscoelastic blocks. These dampers not only dissipate energy but also increase the stiffness of the steel frame structure, and the degree to which they increase the stiffness may be controlled by the size and shape. In this research, the cyclical behavior of the damper was examined both experimentally and numerically with finite element modeling. Cyclic loading results of the finite element modeling reveal fundamental characteristics of this hybrid viscoelastic damper. The results indicate that incorporating a damper of the design can significantly improve the seismic performance of steel frame structures.

Keywords: Cyclic loading, energy dissipation, hybrid damper, passive control system, viscoelastic damper.

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Authors: Bin Cai, Shilong Wang, Haibo Hu

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The job shop scheduling problem (JSSP) is a notoriously difficult problem in combinatorial optimization. This paper presents a hybrid artificial immune system for the JSSP with the objective of minimizing makespan. The proposed approach combines the artificial immune system, which has a powerful global exploration capability, with the local search method, which can exploit the optimal antibody. The antibody coding scheme is based on the operation based representation. The decoding procedure limits the search space to the set of full active schedules. In each generation, a local search heuristic based on the neighborhood structure proposed by Nowicki and Smutnicki is applied to improve the solutions. The approach is tested on 43 benchmark problems taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.

Keywords: Artificial immune system, Job shop scheduling problem, Local search, Metaheuristic algorithm

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Authors: K. Touafek, A. Khelifa, E. H. Khettaf, A. Embarek

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Hybrid photovoltaic thermal (PV/T) solar system comprises a solar collector which is disposed on photovoltaic solar cells. The disadvantage of a conventional photovoltaic cell is that its performance decreases as the temperature increases. Indeed, part of the solar radiation is converted into electricity and is dissipated as heat, increasing the temperature of the photovoltaic cell with respect to the ambient temperature. The objective of this work is to study experimentally and implement a hybrid prototype to evaluate electrical and thermal performance. In this paper, an experimental study of two new configurations of hybrid collectors is exposed. The results are given and interpreted. The two configurations of absorber studied are a new combination with tubes and galvanized tank, the other is a tubes and sheet.

Keywords: Experimental, Photovoltaic, Solar, Temperature.

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Authors: M.Takeuchi, T.Kitagaki, Y.Noguchi, T. Washiya

Abstract:

A high performance clarification system has been discussed for advanced aqueous reprocessing of FBR spent fuel. Dissolver residue gives the cause of troubles on the plant operation of reprocessing. In this study, the new clarification system based on the hybrid of centrifuge and filtration was proposed to get the high separation ability of the component of whole insoluble sludge. The clarification tests of simulated solid species were carried out to evaluate the clarification performance using small-scale test apparatus of centrifuge and filter unit. The density effect of solid species on the collection efficiency was mainly evaluated in the centrifugal clarification test. In the filtration test using ceramic filter with pore size of 0.2μm, on the other hand, permeability and filtration rate were evaluated in addition to the filtration efficiency. As results, it was evaluated that the collection efficiency of solid species on the new clarification system was estimated as nearly 100%. In conclusion, the high clarification performance of dissolver liquor can be achieved by the hybrid of the centrifuge and filtration system.

Keywords: Centrifuge, Clarification, FBR dissolver liquor, Filtration

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Authors: Jason Chien-Hsun Tseng

Abstract:

This paper evaluates performances of an adaptive noise cancelling (ANC) based target detection algorithm on a set of real test data supported by the Defense Evaluation Research Agency (DERA UK) for multi-target wideband active sonar echolocation system. The hybrid algorithm proposed is a combination of an adaptive ANC neuro-fuzzy scheme in the first instance and followed by an iterative optimum target motion estimation (TME) scheme. The neuro-fuzzy scheme is based on the adaptive noise cancelling concept with the core processor of ANFIS (adaptive neuro-fuzzy inference system) to provide an effective fine tuned signal. The resultant output is then sent as an input to the optimum TME scheme composed of twogauge trimmed-mean (TM) levelization, discrete wavelet denoising (WDeN), and optimal continuous wavelet transform (CWT) for further denosing and targets identification. Its aim is to recover the contact signals in an effective and efficient manner and then determine the Doppler motion (radial range, velocity and acceleration) at very low signal-to-noise ratio (SNR). Quantitative results have shown that the hybrid algorithm have excellent performance in predicting targets- Doppler motion within various target strength with the maximum false detection of 1.5%.

Keywords: Wideband Active Sonar Echolocation, ANC Neuro-Fuzzy, Wavelet Denoise, CWT, Hybrid Algorithm.

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Authors: Z. Abdollahnejad, M. Kheradmand, F. Pacheco-Torgal

Abstract:

The use of bio-based admixtures on construction materials is a recent trend that is gaining momentum. However, to our knowledge, no studies have been reported concerning the use of biopolymers on hybrid cement based mortars. This paper reports experimental results regarding the study of the influence of mix design of 43 hybrid cement mortars containing two different biopolymers on its mechanical performance. The results show that the use of the biopolymer carrageenan is much more effective than the biopolymer xanthan concerning the increase in compressive strength. An optimum biopolymer content was found.

Keywords: Waste reuse, fly ash, waste glass, hybrid cement, biopolymers, mechanical strength.

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Authors: C. Kalamani, V. Abishek Karthick, S. Anitha, K. Kavin Kumar

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The fault tolerant system plays a crucial role in the critical applications which are being used in the present scenario. A fault may change the functionality of circuits. Aim of this paper is to design multiplier using fault tolerant hybrid full adder. Fault tolerant hybrid full adder is designed to check and repair any fault in the circuit using self-checking circuit and the self-repairing circuit. Further, the use of conventional logic circuits may result in more area, delay as well as power consumption. In order to reduce these parameters of the circuit, GDI (Gate Diffusion Input) techniques with less number of transistors are used compared to conventional full adder circuit. This reduces the area, delay and power consumption. The proposed method solves the major problems occurring in the most crucial and critical applications.

Keywords: Gate diffusion input, hybrid full adder, self-checking, fault tolerant.

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Authors: Kayode A. Olaniyi, Adeola A. Ogunleye, Tola M. Osifeko

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Electric Vehicles (EV) appear to be gaining increasing patronage as a feasible alternative to Internal Combustion Engine Vehicles (ICEVs) for having low emission and high operation efficiency. The EV energy storage systems are required to handle high energy and power density capacity constrained by limited space, operating temperature, weight and cost. The choice of strategies for energy storage evaluation, monitoring and control remains a challenging task. This paper presents review of various energy storage technologies and recent researches in battery evaluation techniques used in EV applications. It also underscores strategies for the hybrid energy storage management and control schemes for the improvement of EV stability and reliability. The study reveals that despite the advances recorded in battery technologies there is still no cell which possess both the optimum power and energy densities among other requirements, for EV application. However combination of two or more energy storages as hybrid and allowing the advantageous attributes from each device to be utilized is a promising solution. The review also reveals that State-of-Charge (SoC) is the most crucial method for battery estimation. The conventional method of SoC measurement is however questioned in the literature and adaptive algorithms that include all model of disturbances are being proposed. The review further suggests that heuristic-based approach is commonly adopted in the development of strategies for hybrid energy storage system management. The alternative approach which is optimization-based is found to be more accurate but is memory and computational intensive and as such not recommended in most real-time applications.

Keywords: Hybrid electric vehicle, hybrid energy storage, battery state estimation, ate of charge, state of health.

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Authors: H. Shayeghi, A. Jalili

Abstract:

This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.

Keywords: AGC, Hybrid Fuzzy Controller, Deregulated Power System, Power System Control, GAs.

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Authors: L. G. Karancsi, K. Máriás

Abstract:

We examined the crop yield results of hybrids in 2012. We found out that in the control treatments the lowest yield was reached with the hybrid PR37M81: 10,012 kg ha^-1. The highest yield was in case of hybrid P37N01: 11,581 kg ha^-1. As we raised the nutrient doses the lowest yield of all examined nutrient levels was in case of hybrid PR37M81. We measured at N₆₀+PK nutrient level 12,517 kg ha^-1, at N₁₂₀+PK nutrient level 12,760 kg ha^-1, and at N₁₅₀+PK nutrient level 12,535 kg ha^-1 yield results. At N₆₀+PK and N₁₂₀+PK nutrient level the highest yield was reached with the hybrid P9494 (N₆₀+PK: 13,970 kg ha^-1, N₁₂₀+PK: 13,871 kg ha^-1). In case of the N₁₅₀+PK fertilization treatment the hybrid P37N01 gave the highest yield results (13,962 kg ha^-1).

Keywords: Hybrids, maize, nutrient levels, SPAD and LAI values.

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