Search results for: simulation algorithm.

Authors: Vrince Vimal, Madhav J. Nigam

Abstract:

Wireless sensor networks have enticed much of the spotlight from researchers all around the world, owing to its extensive applicability in agricultural, industrial and military fields. Energy conservation node deployment stratagems play a notable role for active implementation of Wireless Sensor Networks. Clustering is the approach in wireless sensor networks which improves energy efficiency in the network. The clustering algorithm needs to have an optimum size and number of clusters, as clustering, if not implemented properly, cannot effectively increase the life of the network. In this paper, an algorithm has been proposed to address connectivity issues with the aim of ensuring the uniform energy consumption of nodes in every part of the network. The results obtained after simulation showed that the proposed algorithm has an edge over existing algorithms in terms of throughput and networks lifetime.

Keywords: WSN, random deployment, clustering, isolated nodes, network lifetime.

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Authors: Mohammed M. Siddeq, Mohammed H. Rasheed, Omar M. Salih, Marcos A. Rodrigues

Abstract:

This research proposes a data encoding and decoding method based on the Matrix Minimization algorithm. This algorithm is applied to high-frequency coefficients for compression/encoding. The algorithm starts by converting every three coefficients to a single value; this is accomplished based on three different keys. The decoding/decompression uses a search method called QSS (Quick Sequential Search) Decoding Algorithm presented in this research based on the sequential search to recover the exact coefficients. In the next step, the decoded data are saved in an auxiliary array. The basic idea behind the auxiliary array is to save all possible decoded coefficients; this is because another algorithm, such as conventional sequential search, could retrieve encoded/compressed data independently from the proposed algorithm. The experimental results showed that our proposed decoding algorithm retrieves original data faster than conventional sequential search algorithms.

Keywords: Matrix Minimization Algorithm, Decoding Sequential Search Algorithm, image compression, Discrete Cosine Transform, Discrete Wavelet Transform.

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Authors: Jixin Liu, Zheming Lu

Abstract:

In this paper, a novel multipurpose audio watermarking algorithm is proposed based on Vector Quantization (VQ) in Discrete Cosine Transform (DCT) domain using the codeword labeling and index-bit constrained method. By using this algorithm, it can fulfill the requirements of both the copyright protection and content integrity authentication at the same time for the multimedia artworks. The robust watermark is embedded in the middle frequency coefficients of the DCT transform during the labeled codeword vector quantization procedure. The fragile watermark is embedded into the indices of the high frequency coefficients of the DCT transform by using the constrained index vector quantization method for the purpose of integrity authentication of the original audio signals. Both the robust and the fragile watermarks can be extracted without the original audio signals, and the simulation results show that our algorithm is effective with regard to the transparency, robustness and the authentication requirements

Keywords: Copyright Protection, Discrete Cosine Transform, Integrity Authentication, Multipurpose Audio Watermarking, Vector Quantization.

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Authors: Wen-Tzu Chen, Wen-Bin Kao

Abstract:

This paper provides a scheme to improve the read efficiency of anti-collision algorithm in EPCglobal UHF Class-1 Generation-2 RFID standard. In this standard, dynamic frame slotted ALOHA is specified to solve the anti-collision problem. Also, the Q-algorithm with a key parameter C is adopted to dynamically adjust the frame sizes. In the paper, we split the C parameter into two parameters to increase the read speed and derive the optimal values of the two parameters through simulations. The results indicate our method outperforms the original Q-algorithm.

Keywords: RFID, anti-collision, Q algorithm, ALOHA

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Authors: Qing Zhang, Jiachen Nie, Yujia Wen, Guanyuan Kou, Peng Yu, Kun Xia, Qin Yang, Li Ding

Abstract:

Background: A facility layout problem (FLP) is an NP-complete (non-deterministic polynomial) problem, for which is hard to obtain an exact optimal solution. FLP has been widely studied in various limited spaces and workflows. For example, cafeterias with many types of equipment for troops cause chaotic processes when dining. Objective: This article tried to optimize the layout of a troops’ cafeteria and to improve the overall efficiency of the dining process. Methods: First, the original cafeteria layout design scheme was analyzed from an ergonomic perspective and two new design schemes were generated. Next, three facility layout models were designed, and further simulation was applied to compare the total time and density of troops between each scheme. Last, an experiment of the dining process with video observation and analysis verified the simulation results. Results: In a simulation, the dining time under the second new layout is shortened by 2.25% and 1.89% (p<0.0001, p=0.0001) compared with the other two layouts, while troops-flow density and interference both greatly reduced in the two new layouts. In the experiment, process completing time and the number of interferences reduced as well, which verified corresponding simulation results. Conclusion: Our two new layout schemes are tested to be optimal by a series of simulation and space experiments. In future research, similar approaches could be applied when taking layout-design algorithm calculation into consideration.

Keywords: Troops’ cafeteria, layout optimization, dining efficiency, AnyLogic simulation, field experiment

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Authors: Marian Dragomir, Alin Dragomir

Abstract:

In the paper, two fault location algorithms are presented for transmission lines which use the line parameters to estimate the distance to the fault. The first algorithm uses only the measurements from one end of the line and the positive and zero sequence parameters of the line, while the second one uses the measurements from both ends of the line and only the positive sequence parameters of the line. The algorithms were tested using a transmission grid transposed in MATLAB. In a first stage it was established a fault location base line, where the algorithms mentioned above estimate the fault locations using the exact line parameters. After that, the positive and zero sequence resistance and reactance of the line were calculated again for different ground resistivity values and then the fault locations were estimated again in order to compare the results with the base line results. The results show that the algorithm which uses the zero sequence impedance of the line is the most sensitive to the line parameters modifications. The other algorithm is less sensitive to the line parameters modification.

Keywords: Estimation algorithms, fault location, line parameters, simulation tool.

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Authors: Mohammed T. Taher, Usman Ghani, Ahmed S. Khan

Abstract:

This paper compares the findings of two studies conducted to determine the effectiveness of simulation-based, hands-on and feedback mechanism on students learning by answering the following questions: 1). Does the use of simulation improve students’ learning outcomes? 2). How do students perceive the instructional design features embedded in the simulation program such as exploration and scaffolding support in learning new concepts? 3.) What is the effect of feedback mechanisms on students’ learning in the use of simulation-based labs? The paper also discusses the other aspects of findings which reveal that simulation by itself is not very effective in promoting student learning. Simulation becomes effective when it is followed by hands-on activity and feedback mechanisms. Furthermore, the paper presents recommendations for improving student learning through the use of simulation-based, hands-on, and feedback-based teaching methodologies.

Keywords: Simulation-based teaching, hands-on learning, feedback-based learning, scaffolding.

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Authors: Soottipoom Yaowiwat, Manoj Lohatepanont, Proadpran Punyabukkana

Abstract:

Several approaches such as linear programming, network modeling, greedy heuristic and decision support system are well-known approaches in solving irregular airline operation problem. This paper presents an alternative approach based on Multi Objective Micro Genetic Algorithm. The aim of this research is to introduce the concept of Multi Objective Micro Genetic Algorithm as a tool to solve irregular airline operation, combine and reroute problem. The experiment result indicated that the model could obtain optimal solutions within a few second.

Keywords: Irregular Airline Operation, Combine and RerouteRoutine, Genetic Algorithm, Micro Genetic Algorithm, Multi ObjectiveOptimization, Evolutionary Algorithm.

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Authors: Radhwan Yousif Sedik Al-Jawadi

Abstract:

Optimization is necessary for finding appropriate solutions to a range of real-life problems. In particular, genetic (or more generally, evolutionary) algorithms have proved very useful in solving many problems for which analytical solutions are not available. In this paper, we present an optimization algorithm called Dynamic Schema with Dissimilarity and Similarity of Chromosomes (DSDSC) which is a variant of the classical genetic algorithm. This approach constructs new chromosomes from a schema and pairs of existing ones by exploring their dissimilarities and similarities. To show the effectiveness of the algorithm, it is tested and compared with the classical GA, on 15 two-dimensional optimization problems taken from literature. We have found that, in most cases, our method is better than the classical genetic algorithm.

Keywords: Genetic algorithm, similarity and dissimilarity, chromosome injection, dynamic schema.

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Authors: Z. Pooranian, A. Barati, A. Movaghar

Abstract:

Wireless sensor networks include small nodes which have sensing ability; calculation and connection extend themselves everywhere soon. Such networks have source limitation on connection, calculation and energy consumption. So, since the nodes have limited energy in sensor networks, the optimized energy consumption in these networks is of more importance and has created many challenges. The previous works have shown that by organizing the network nodes in a number of clusters, the energy consumption could be reduced considerably. So the lifetime of the network would be increased. In this paper, we used the Queen-bee algorithm to create energy efficient clusters in wireless sensor networks. The Queen-bee (QB) is similar to nature in that the queen-bee plays a major role in reproduction process. The QB is simulated with J-sim simulator. The results of the simulation showed that the clustering by the QB algorithm decreases the energy consumption with regard to the other existing algorithms and increases the lifetime of the network.

Keywords: Queen-bee, sensor network, energy efficient, clustering.

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Authors: Mehrdad Mahmudizad, Roya Ahmadi Ahangar

Abstract:

This paper presents the method of designing the type 2 fuzzy PID controllers in order to solve the problem of Load Frequency Control (LFC). The Harmony Search (HS) algorithm is used to regulate the measurement factors and the effect of uncertainty of membership functions of Interval Type 2 Fuzzy Proportional Integral Differential (IT2FPID) controllers in order to reduce the frequency deviation resulted from the load oscillations. The simulation results implicitly show that the performance of the proposed IT2FPID LFC in terms of error, settling time and resistance against different load oscillations is more appropriate and preferred than PID and Type 1 Fuzzy Proportional Integral Differential (T1FPID) controllers.

Keywords: Load Frequency Control, Fuzzy-PID controller, Type 2 fuzzy system, Harmony Search algorithm.

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Authors: Mohammed Zidane, Said Safi, Mohamed Sabri, Ahmed Boumezzough

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This paper describes a blind algorithm, which is compared with two another algorithms proposed in the literature, for estimating of the minimum phase channel parameters. In order to identify blindly the impulse response of these channels, we have used Higher Order Statistics (HOS) to build our algorithm. The simulation results in noisy environment, demonstrate that the proposed method could estimate the phase and magnitude with high accuracy of these channels blindly and without any information about the input, except that the input excitation is identically and independent distribute (i.i.d) and non-Gaussian.

Keywords: System Identification, Higher Order Statistics, Communication Channels.

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Authors: Mohamed Azab

Abstract:

In this paper a new maximum power point tracking algorithm for photovoltaic arrays is proposed. The algorithm detects the maximum power point of the PV. The computed maximum power is used as a reference value (set point) of the control system. ON/OFF power controller with hysteresis band is used to control the operation of a Buck chopper such that the PV module always operates at its maximum power computed from the MPPT algorithm. The major difference between the proposed algorithm and other techniques is that the proposed algorithm is used to control directly the power drawn from the PV. The proposed MPPT has several advantages: simplicity, high convergence speed, and independent on PV array characteristics. The algorithm is tested under various operating conditions. The obtained results have proven that the MPP is tracked even under sudden change of irradiation level.

Keywords: Photovoltaic, maximum power point tracking, MPPT.

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Authors: Cesar Hernández, Diego Giral, Ingrid Páez

Abstract:

This article proposes a hybrid algorithm for spectrum allocation in cognitive radio networks based on the algorithms Analytical Hierarchical Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to improve the performance of the spectrum mobility of secondary users in cognitive radio networks. To calculate the level of performance of the proposed algorithm a comparative analysis between the proposed AHP-TOPSIS, Grey Relational Analysis (GRA) and Multiplicative Exponent Weighting (MEW) algorithm is performed. Four evaluation metrics are used. These metrics are accumulative average of failed handoffs, accumulative average of handoffs performed, accumulative average of transmission bandwidth, and accumulative average of the transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm provides 2.4 times better performance compared to a GRA Algorithm and, 1.5 times better than the MEW Algorithm.

Keywords: Cognitive radio, decision making, hybrid algorithm, spectrum handoff, wireless networks.

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Authors: C. Patrascioiu

Abstract:

The paper describes the modeling and simulation of the heat pumps domain processes. The main objective of the study is the use of the heat pump in propene–propane distillation processes. The modeling and simulation instrument is the Unisim^® Design simulator. The paper is structured in three parts: An overview of the compressing gases, the modeling and simulation of the freezing systems, and the modeling and simulation of the heat pumps. For each of these systems, there are presented the Unisim^® Design simulation diagrams, the input–output system structure and the numerical results. Future studies will consider modeling and simulation of the propene–propane distillation process with heat pump.

Keywords: Distillation, heat pump, simulation, Unisim Design.

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Authors: Meng Wang, Qi-rui Han

Abstract:

Because of excellent properties, people has paid more attention to SPIHI algorithm, which is based on the traditional wavelet transformation theory, but it also has its shortcomings. Combined the progress in the present wavelet domain and the human's visual characteristics, we propose an improved algorithm based on human visual characteristics of SPIHT in the base of analysis of SPIHI algorithm. The experiment indicated that the coding speed and quality has been enhanced well compared to the original SPIHT algorithm, moreover improved the quality of the transmission cut off.

Keywords: Lifted wavelet transform, SPIHT, Human Visual Characteristics.

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Authors: Chang Liu, Zishu He

Abstract:

Adaptive echo cancellers with two-path algorithm are applied to avoid the false adaptation during the double-talk situation. In the two-path algorithm, several transfer logic solutions have been proposed to control the filter update. This paper presents an improved transfer logic solution. It improves the convergence speed of the two-path algorithm, and allows the reduction of the memory elements and computational complexity. Results of simulations show the improved performance of the proposed solution.

Keywords: Acoustic echo cancellation, Echo return lossenhancement (ERLE), Two-path algorithm, Transfer logic

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Authors: Awadhesh Kumar Singh

Abstract:

Jayanti-s algorithm is one of the best known abortable mutual exclusion algorithms. This work is an attempt to overcome an already known limitation of the algorithm while preserving its all important properties and elegance. The limitation is that the token number used to assign process identification number to new incoming processes is unbounded. We have used a suitably adapted alternative data structure, in order to completely eliminate the use of token number, in the algorithm.

Keywords: Abortable, deterministic, local spin, mutual exclusion.

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Authors: Bin Cai, Shilong Wang, Haibo Hu

Abstract:

The job shop scheduling problem (JSSP) is well known as one of the most difficult combinatorial optimization problems. This paper presents a hybrid genetic algorithm for the JSSP with the objective of minimizing makespan. The efficiency of the genetic algorithm is enhanced by integrating it with a local search method. The chromosome representation of the problem is based on operations. Schedules are constructed using a procedure that generates full active schedules. In each generation, a local search heuristic based on Nowicki and Smutnicki-s neighborhood is applied to improve the solutions. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.

Keywords: Genetic algorithm, Job shop scheduling problem, Local search, Meta-heuristic algorithm

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Authors: Jungho Choi, Youngwan Cho

Abstract:

This paper presents an algorithm for the recognition and tracking of moving objects, 1/10 scale model car is used to verify performance of the algorithm. Presented algorithm for the recognition and tracking of moving objects in the paper is as follows. SURF algorithm is merged with Lucas-Kanade algorithm. SURF algorithm has strong performance on contrast, size, rotation changes and it recognizes objects but it is slow due to many computational complexities. Processing speed of Lucas-Kanade algorithm is fast but the recognition of objects is impossible. Its optical flow compares the previous and current frames so that can track the movement of a pixel. The fusion algorithm is created in order to solve problems which occurred using the Kalman Filter to estimate the position and the accumulated error compensation algorithm was implemented. Kalman filter is used to create presented algorithm to complement problems that is occurred when fusion two algorithms. Kalman filter is used to estimate next location, compensate for the accumulated error. The resolution of the camera (Vision Sensor) is fixed to be 640x480. To verify the performance of the fusion algorithm, test is compared to SURF algorithm under three situations, driving straight, curve, and recognizing cars behind the obstacles. Situation similar to the actual is possible using a model vehicle. Proposed fusion algorithm showed superior performance and accuracy than the existing object recognition and tracking algorithms. We will improve the performance of the algorithm, so that you can experiment with the images of the actual road environment.

Keywords: SURF, Optical Flow Lucas-Kanade, Kalman Filter, object recognition, object tracking.

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Authors: Hemant I. Joshi, Vivek J. Pandya

Abstract:

This paper discusses the simulation and experimental work of small Smart Grid containing ten consumers. Smart Grid is characterized by a two-way flow of real-time information and energy. RTP (Real Time Pricing) based tariff is implemented in this work to reduce peak demand, PAR (peak to average ratio) and cost of energy consumed. In the experimental work described here, working of Smart Plug, HEC (Home Energy Controller), HAN (Home Area Network) and communication link between consumers and utility server are explained. Algorithms for Smart Plug, HEC, and utility server are presented and explained in this work. After receiving the Real Time Price for different time slots of the day, HEC interacts automatically by running an algorithm which is based on Linear Programming Problem (LPP) method to find the optimal energy consumption schedule. Algorithm made for utility server can handle more than one off-peak time period during the day. Simulation and experimental work are carried out for different cases. At the end of this work, comparison between simulation results and experimental results are presented to show the effectiveness of the minimization method adopted.

Keywords: Smart Grid, Real Time Pricing, Peak to Average Ratio, Home Area Network, Home Energy Controller, Smart Plug, Utility Server, Linear Programming Problem.

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Authors: Mourad Ykhlef, Hebah ElGibreen

Abstract:

Mining Sequential Patterns in large databases has become an important data mining task with broad applications. It is an important task in data mining field, which describes potential sequenced relationships among items in a database. There are many different algorithms introduced for this task. Conventional algorithms can find the exact optimal Sequential Pattern rule but it takes a long time, particularly when they are applied on large databases. Nowadays, some evolutionary algorithms, such as Particle Swarm Optimization and Genetic Algorithm, were proposed and have been applied to solve this problem. This paper will introduce a new kind of hybrid evolutionary algorithm that combines Genetic Algorithm (GA) with Particle Swarm Optimization (PSO) to mine Sequential Pattern, in order to improve the speed of evolutionary algorithms convergence. This algorithm is referred to as SP-GAPSO.

Keywords: Genetic Algorithm, Hybrid Evolutionary Algorithm, Particle Swarm Optimization algorithm, Sequential Pattern mining.

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Authors: J. B. Seo, K. J. Kim, S. W. Nam

Abstract:

In this paper, a nonlinear acoustic echo cancellation (AEC) system is proposed, whereby 3rd order Volterra filtering is utilized along with a variable step-size Gauss-Seidel pseudo affine projection (VSSGS-PAP) algorithm. In particular, the proposed nonlinear AEC system is developed by considering a double-talk situation with near-end signal variation. Simulation results demonstrate that the proposed approach yields better nonlinear AEC performance than conventional approaches.

Keywords: Acoustic echo cancellation (AEC), Volterra filtering, variable step-size, GS-PAP.

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Authors: Qin Ding, Jim Gasvoda

Abstract:

Clustering is the process of subdividing an input data set into a desired number of subgroups so that members of the same subgroup are similar and members of different subgroups have diverse properties. Many heuristic algorithms have been applied to the clustering problem, which is known to be NP Hard. Genetic algorithms have been used in a wide variety of fields to perform clustering, however, the technique normally has a long running time in terms of input set size. This paper proposes an efficient genetic algorithm for clustering on very large data sets, especially on image data sets. The genetic algorithm uses the most time efficient techniques along with preprocessing of the input data set. We test our algorithm on both artificial and real image data sets, both of which are of large size. The experimental results show that our algorithm outperforms the k-means algorithm in terms of running time as well as the quality of the clustering.

Keywords: Clustering, data mining, genetic algorithm, image data.

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Authors: Si-Gwan Kim

Abstract:

Small-size and low-power sensors with sensing, signal processing and wireless communication capabilities is suitable for the wireless sensor networks. Due to the limited resources and battery constraints, complex routing algorithms used for the ad-hoc networks cannot be employed in sensor networks. In this paper, we propose node-disjoint multi-path hexagon-based routing algorithms in wireless sensor networks. We suggest the details of the algorithm and compare it with other works. Simulation results show that the proposed scheme achieves better performance in terms of efficiency and message delivery ratio.

Keywords: Clustering, multi-path, routing protocol, sensor network.

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Authors: Jeffrey L. Duffany

Abstract:

An optimal solution for a large number of constraint satisfaction problems can be found using the technique of substitution and elimination of variables analogous to the technique that is used to solve systems of equations. A decision function f(A)=max(A2) is used to determine which variables to eliminate. The algorithm can be expressed in six lines and is remarkable in both its simplicity and its ability to find an optimal solution. However it is inefficient in that it needs to square the updated A matrix after each variable elimination. To overcome this inefficiency the algorithm is analyzed and it is shown that the A matrix only needs to be squared once at the first step of the algorithm and then incrementally updated for subsequent steps, resulting in significant improvement and an algorithm complexity of O(n3).

Keywords: Algorithm, complexity, constraint, np-complete.

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Authors: S. A. Banani, M. A. Masnadi-Shirazi

Abstract:

This paper presents a new algorithm which yields a nonlinear state estimator called iterated unscented Kalman filter. This state estimator makes use of both statistical and analytical linearization techniques in different parts of the filtering process. It outperforms the other three nonlinear state estimators: unscented Kalman filter (UKF), extended Kalman filter (EKF) and iterated extended Kalman filter (IEKF) when there is severe nonlinearity in system equation and less nonlinearity in measurement equation. The algorithm performance has been verified by illustrating some simulation results.

Keywords: Extended Kalman Filter, Iterated EKF, Nonlinearstate estimator, Unscented Kalman Filter.

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Authors: Siddhartha Chauhan, Kumar S. Pandey, Prateek Chandra

Abstract:

One of the key research issues in wireless sensor networks (WSNs) is how to efficiently deploy sensors to cover an area. In this paper, we present a Fishnet Based Dispatch Scheme (FiBDS) with energy aware mobility and interest based sensing angle. We propose two algorithms, one is FiBDS centralized algorithm and another is FiBDS distributed algorithm. The centralized algorithm is designed specifically for the non-time critical applications, commonly known as non real-time applications while the distributed algorithm is designed specifically for the time critical applications, commonly known as real-time applications. The proposed dispatch scheme works in a phase-selection manner. In this in each phase a specific constraint is dealt with according to the specified priority and then moved onto the next phase and at the end of each only the best suited nodes for the phase are chosen. Simulation results are presented to verify their effectiveness. 

Keywords: Dispatch Scheme, Energy Aware Mobility, Interest based Sensing, Wireless Sensor Networks (WSNs).

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Authors: Mustafa Sahin, İlkay Yavrucuk

Abstract:

This paper presents a wind turbine envelope protection control algorithm that protects Variable Speed Variable Pitch (VSVP) wind turbines from damage during operation throughout their below and above rated regions, i.e. from cut-in to cut-out wind speed. The proposed approach uses a neural network that can adapt to turbines and their operating points. An algorithm monitors instantaneous wind and turbine states, predicts a wind speed that would push the turbine to a pre-defined envelope limit and, when necessary, realizes an avoidance action. Simulations are realized using the MS Bladed Wind Turbine Simulation Model for the NREL 5 MW wind turbine equipped with baseline controllers. In all simulations, through the proposed algorithm, it is observed that the turbine operates safely within the allowable limit throughout the below and above rated regions. Two example cases, adaptations to turbine operating points for the below and above rated regions and protections are investigated in simulations to show the capability of the proposed envelope protection system (EPS) algorithm, which reduces excessive wind turbine loads and expectedly increases the turbine service life.

Keywords: Adaptive envelope protection control, limit detection and avoidance, neural networks, ultimate load reduction, wind turbine power control.

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Authors: Abdel-Reza Hatamlou, Mohammad Reza Meybodi

Abstract:

In this paper we present a hybrid search algorithm for solving constraint satisfaction and optimization problems. This algorithm combines ideas of two basic approaches: complete and incomplete algorithms which also known as systematic search and local search algorithms. Different characteristics of systematic search and local search methods are complementary. Therefore we have tried to get the advantages of both approaches in the presented algorithm. The major advantage of presented algorithm is finding partial sound solution for complicated problems which their complete solution could not be found in a reasonable time. This algorithm results are compared with other algorithms using the well known n-queens problem.

Keywords: Constraint Satisfaction Problem, Hybrid SearchAlgorithm.

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