Search results for: Hybrid heuristic algorithm.

Authors: Noor Atinah Ahmad

Abstract:

The Minimal Residual (MR) is modified for adaptive filtering application. Three forms of MR based algorithm are presented: i) the low complexity SPCG, ii) MREDSI, and iii) MREDSII. The low complexity is a reduced complexity version of a previously proposed SPCG algorithm. Approximations introduced reduce the algorithm to an LMS type algorithm, but, maintain the superior convergence of the SPCG algorithm. Both MREDSI and MREDSII are MR based methods with Euclidean direction of search. The choice of Euclidean directions is shown via simulation to give better misadjustment compared to their gradient search counterparts.

Keywords: Adaptive filtering, Adaptive least square, Minimalresidual method.

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Authors: Usman Mahmood, Khawaja M. U. Suleman

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A peer-to-peer storage system has challenges like; peer availability, data protection, churn rate. To address these challenges different redundancy, replacement and repair schemes are used. This paper presents a hybrid scheme of redundancy using replication and erasure coding. We calculate and compare the storage, access, and maintenance costs of our proposed scheme with existing redundancy schemes. For realistic behaviour of peers a trace of live peer-to-peer system is used. The effect of different replication, and repair schemes are also shown. The proposed hybrid scheme performs better than existing double coding hybrid scheme in all metrics and have an improved maintenance cost than hierarchical codes.

Keywords: Erasure Coding, P2P, Redundancy, Replication.

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Authors: Pavel K. Lopatin, Artyom S. Yegorov

Abstract:

An exact algorithm for a n-link manipulator movement amidst arbitrary unknown static obstacles is presented. The algorithm guarantees the reaching of a target configuration of the manipulator in a finite number of steps. The algorithm is reduced to a finite number of calls of a subroutine for planning a trajectory in the presence of known forbidden states. The polynomial approximation algorithm which is used as the subroutine is presented. The results of the exact algorithm implementation for the control of a seven link (7 degrees of freedom, 7DOF) manipulator are given.

Keywords: Manipulator, trajectory planning, unknown obstacles

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Authors: Jayant V Kulkarni, Jayadevan R, Suresh N Mali, Hemant K Abhyankar, Raghunath S Holambe

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The paper describes a new approach for fingerprint classification, based on the distribution of local features (minute details or minutiae) of the fingerprints. The main advantage is that fingerprint classification provides an indexing scheme to facilitate efficient matching in a large fingerprint database. A set of rules based on heuristic approach has been proposed. The area around the core point is treated as the area of interest for extracting the minutiae features as there are substantial variations around the core point as compared to the areas away from the core point. The core point in a fingerprint has been located at a point where there is maximum curvature. The experimental results report an overall average accuracy of 86.57 % in fingerprint classification.

Keywords: Minutiae distribution, Minutiae, Classification, Orientation, Heuristic.

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Authors: Reza Sedaghati

Abstract:

Given the increasing energy demand in the world as well as limited fossil energy fuel resources, it is necessary to use renewable energy resources more than ever. Developing a hybrid energy system is suggested to overcome the intermittence of renewable energy resources such as sun and wind, in which the excess electrical energy can be converted and stored. While these resources store the energy, they can provide a more reliable system that is really suitable for off-grid applications. In hybrid systems, a methodology for optimal sizing of power generation systems components is of great importance in terms of economic aspects and efficiency. In this study, a hybrid energy system is designed to supply an off-grid sample load pattern with the aim of supplying necessary energy and minimizing the total production cost throughout the system life as well as increasing the reliability. For this purpose, the optimal size and the cost function of these resources is determined and minimized using evolutionary algorithms and system efficiency is studied with real-time load and meteorological information of Kazerun, a city in southern Iran under different conditions.

Keywords: Hybrid energy system, intelligent method, optimal size, minimal.

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Authors: Usman Qamar, Younus Javed

Abstract:

Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and roughsets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.

Keywords: Rough-sets, Classification, Feature Selection, Entropy, Outliers, Frequent itemset mining.

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Authors: A. M. Fahim, G. Saake, A. M. Salem, F. A. Torkey, M. A. Ramadan

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Data clustering is an important data exploration technique with many applications in data mining. We present an enhanced version of the well known single link clustering algorithm. We will refer to this algorithm as DCBOR. The proposed algorithm alleviates the chain effect by removing the outliers from the given dataset. So this algorithm provides outlier detection and data clustering simultaneously. This algorithm does not need to update the distance matrix, since the algorithm depends on merging the most k-nearest objects in one step and the cluster continues grow as long as possible under specified condition. So the algorithm consists of two phases; at the first phase, it removes the outliers from the input dataset. At the second phase, it performs the clustering process. This algorithm discovers clusters of different shapes, sizes, densities and requires only one input parameter; this parameter represents a threshold for outlier points. The value of the input parameter is ranging from 0 to 1. The algorithm supports the user in determining an appropriate value for it. We have tested this algorithm on different datasets contain outlier and connecting clusters by chain of density points, and the algorithm discovers the correct clusters. The results of our experiments demonstrate the effectiveness and the efficiency of DCBOR.

Keywords: Data Clustering, Clustering Algorithms, Handling Noise, Arbitrary Shape of Clusters.

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Authors: K. Touafek, A. Khelifa, I. Tabet, H. Haloui, H. Bencheikh El Houcine, M. Adouane

Abstract:

Hybrid photovoltaic thermal (PVT) collectors allow simultaneous production of electrical energy thus heat energy. There are several configurations of hybrid collectors (to produce water or air). For hybrids water collectors, there are several configurations that differ by the nature of the absorber (serpentine, tubes...). In this paper, an absorber tank is studied. The circulation of the coolant is natural (we do not use the pump). We present the obtained results in our experimental study and we analyzed the data, and then we compare the results with the theory practices. The electrical performances of the hybrid collector are compared with those of conventional photovoltaic module mounted on the same structure and measured under the same conditions.

We conducted experiments with natural circulation of the coolant (Thermosyphon), for a flow rate of 0.025kg/m².

Keywords: Experimental, Photovoltaic, Solar, Temperature, Tank.

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Authors: N. Praveen Kumar, Abhijit Mitra, C. Ardil

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Decision feedback equalizers are commonly employed to reduce the error caused by intersymbol interference. Here, an adaptive decision feedback equalizer is presented with a new adaptation algorithm. The algorithm follows a block-based approach of normalized least mean square (NLMS) algorithm with set-membership filtering and achieves a significantly less computational complexity over its conventional NLMS counterpart with set-membership filtering. It is shown in the results that the proposed algorithm yields similar type of bit error rate performance over a reasonable signal to noise ratio in comparison with the latter one.

Keywords: Decision feedback equalizer, Adaptive algorithm, Block based computation, Set membership filtering.

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Authors: Neveen I. Ghali, Nahed El-Dessouki, Mervat A. N., Lamiaa Bakrawi

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In this paper we use exponential particle swarm optimization (EPSO) to cluster data. Then we compare between (EPSO) clustering algorithm which depends on exponential variation for the inertia weight and particle swarm optimization (PSO) clustering algorithm which depends on linear inertia weight. This comparison is evaluated on five data sets. The experimental results show that EPSO clustering algorithm increases the possibility to find the optimal positions as it decrease the number of failure. Also show that (EPSO) clustering algorithm has a smaller quantization error than (PSO) clustering algorithm, i.e. (EPSO) clustering algorithm more accurate than (PSO) clustering algorithm.

Keywords: Particle swarm optimization, data clustering, exponential PSO.

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Authors: Rohana Mahmud, Hairul Aysa Abdul Halim Sithiq, Haryuna Mohd Taharim

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In this paper, the authors present architecture of a multi agent consultation system for obesity related problems, which hybrid the technology of an expert system (ES) and an intelligent agent (IA). The strength of the ES which is capable of pulling the expert knowledge is consulted and presented to the end user via the autonomous and friendly pushing environment of the intelligent agent.

Keywords: Expert System, Hybrid Technology, Intelligent Agent, Medical Informatics, Multi Agent Consultation System.

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Authors: Min-Hsun Kuo, Yun-Shiow Chen

Abstract:

The running logs of a process hold valuable information about its executed activity behavior and generated activity logic structure. Theses informative logs can be extracted, analyzed and utilized to improve the efficiencies of the process's execution and conduction. One of the techniques used to accomplish the process improvement is called as process mining. To mine similar processes is such an improvement mission in process mining. Rather than directly mining similar processes using a single comparing coefficient or a complicate fitness function, this paper presents a simplified heuristic process mining algorithm with two similarity comparisons that are able to relatively conform the activity logic sequences (traces) of mining processes with those of a normalized (regularized) one. The relative process conformance is to find which of the mining processes match the required activity sequences and relationships, further for necessary and sufficient applications of the mined processes to process improvements. One similarity presented is defined by the relationships in terms of the number of similar activity sequences existing in different processes; another similarity expresses the degree of the similar (identical) activity sequences among the conforming processes. Since these two similarities are with respect to certain typical behavior (activity sequences) occurred in an entire process, the common problems, such as the inappropriateness of an absolute comparison and the incapability of an intrinsic information elicitation, which are often appeared in other process conforming techniques, can be solved by the relative process comparison presented in this paper. To demonstrate the potentiality of the proposed algorithm, a numerical example is illustrated.

Keywords: process mining, process similarity, artificial intelligence, process conformance.

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Authors: Mohsen Ebrahimi, Milad M. Rabieh

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In this paper, two very different optimization algorithms, Genetic and DIRECT algorithms, are used to history match a bottomhole pressure response for a reservoir with wellbore storage and skin with the best possible analytical model. No initial guesses are available for reservoir parameters. The results show that the matching process is much faster and more accurate for DIRECT method in comparison with Genetic algorithm. It is furthermore concluded that the DIRECT algorithm does not need any initial guesses, whereas Genetic algorithm needs to be tuned according to initial guesses.

Keywords: DIRECT algorithm, Genetic algorithm, Analytical modeling, History match

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Authors: Mohammad Reza Ghasemi, Ali Ehsani

Abstract:

In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.

Keywords: Composite Laminates, GA, Multi-objectiveOptimization, Neural Networks, RBFNN.

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Authors: Kavita Burse, Manish Manoria, Vishnu P. S. Kirar

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The back propagation algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a training algorithm consisting of a learning rate and a momentum factor. The major drawbacks of above learning algorithm are the problems of local minima and slow convergence speeds. The addition of an extra term, called a proportional factor reduces the convergence of the back propagation algorithm. We have applied the three term back propagation to multiplicative neural network learning. The algorithm is tested on XOR and parity problem and compared with the standard back propagation training algorithm.

Keywords: Three term back propagation, multiplicative neuralnetwork, proportional factor, local minima.

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Authors: Shima Rajabi, Leila Vafajoo

Abstract:

Compost manufacturing plants are one of units where wastewater is produced in significantly large amounts. Wastewater produced in these plants contains high amounts of substrate (organic loads) and is classified as stringent waste which creates significant pollution when discharged into the environment without treatment. A compost production plant in the one of the Iran-s province treating 200 tons/day of waste is one of the most important environmental pollutant operations in this zone. The main objectives of this paper are to investigate the compost wastewater treatability in hybrid anaerobic reactors with an upflow-downflow arrangement, to determine the kinetic constants, and eventually to obtain an appropriate mathematical model. After starting the hybrid anaerobic reactor of the compost production plant, the average COD removal rate efficiency was 95%.

Keywords: Leachate treatment, anaerobic hybrid reactor

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Authors: H. Shayeghi, H. Hosseini, A. Shabani, M. Mahdavi

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In this paper, optimal generation expansion planning (GEP) is investigated considering purchase prices, profits of independent power producers (IPPs) and reliability criteria using a new method based on hybrid coded Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). In this approach, optimal purchase price of each IPP is obtained by HCGA and reliability criteria are calculated by PSO technique. It should be noted that reliability criteria and the rate of carbon dioxide (CO2) emission have been considered as constraints of the GEP problem. Finally, the proposed method has been tested on the case study system. The results evaluation show that the proposed method can simply obtain optimal purchase prices of IPPs and is a fast method for calculation of reliability criteria in expansion planning. Also, considering the optimal purchase prices and profits of IPPs in generation expansion planning are caused that the expansion costs are decreased and the problem is solved more exactly.

Keywords: GEP Problem, IPPs, Reliability Criteria, GA, PSO.

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Authors: Jianwei Wu

Abstract:

Based on the one-bit-matching principle and by turning the de-mixing matrix into an orthogonal matrix via certain normalization, Ma et al proposed a one-bit-matching learning algorithm on the Stiefel manifold for independent component analysis [8]. But this algorithm is not adaptive. In this paper, an algorithm which can extract kurtosis and its sign of each independent source component directly from observation data is firstly introduced.With the algorithm , the one-bit-matching learning algorithm is revised, so that it can make the blind separation on the Stiefel manifold implemented completely in the adaptive mode in the framework of natural gradient.

Keywords: Independent component analysis, kurtosis, Stiefel manifold, super-gaussians or sub-gaussians.

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Authors: E. Hajizadeh, H. Garmabi

Abstract:

Toughening of polyamide 6 (PA6)/ Nanoclay (NC) nanocomposites with styrene-ethylene/butadiene-styrene copolymer (SEBS) using maleated styrene-ethylene/butadiene-styrene copolymer (mSEBS)/ as a compatibilizer were investigated by blending them in a co-rotating twin-screw extruder. Response surface method of experimental design was used for optimizing the material and processing parameters. Effect of four factors, including SEBS, mSEBS and NC contents as material variables and order of mixing as a processing factor, on toughness of hybrid nanocomposites were studied. All the prepared samples showed ductile behavior and low temperature Izod impact toughness of some of the hybrid nanocomposites demonstrated 900% improvement compared to the PA6 matrix while the modulus showed maximum enhancement of 20% compared to the pristine PA6 resin.

Keywords: Hybrid nanocomposites, PA6, SEBS rubber, toughness.

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Authors: L. G. Karancsi

Abstract:

The research was set up on chernozem soil at the Látókép AGTC MÉK research area of the University of Debrecen in Hungary. We examined the yield, the yield production per 1kg NPK fertilizer and the water and nutrient utilization of hybrid PR37N01 and PR37M81 in 2013. We found that PR37N01 produced the most yield at the level of N₁₂₀+P (17,476kg ha^-1) while PR37M81 reached the highest yield at level N₁₅₀+PK (16,754kg ha^-1). Studies related to yield production per 1kg NPK indicated that the best results were achieved at level N₃₀+PK compared to the control treatment. Yield production per 1kg NPK was17.6kg kg^-1 by P37N01 and 44.2kg kg^-1 by PR37M81. By comparing the water utilization of hybrids we found that the worst water utilization results were reached in the control treatment (PR37N01: 26.2kg mm^-1, PR37M81: 19.5kg mm^-1). The best water utilization values were produced at level N₁₂₀+PK in the case of hybrid PR37N01 (32.1kg mm^-1) and at N₁₅₀+PK in the case of hybrid PR37M81 (30.8kg mm^-1). We established the values of the nutrient reaction and the fertilizer optimum of hybrids. We discovered a strong relationship between the amount of fertilizer applied and the yield produced (r²= 0.8228–0.9515). The best nutrient response was induced by hybrid PR37N01, while the weakest results were reached by hybrid PR37M81.

Keywords: Hybrid, maize, nutrient, yield, water utilization.

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Authors: Wang Tong, He Pi-lian

Abstract:

This paper sets forth the possibility and importance about applying Data Mining in Web logs mining and shows some problems in the conventional searching engines. Then it offers an improved algorithm based on the original AprioriAll algorithm which has been used in Web logs mining widely. The new algorithm adds the property of the User ID during the every step of producing the candidate set and every step of scanning the database by which to decide whether an item in the candidate set should be put into the large set which will be used to produce next candidate set. At the meantime, in order to reduce the number of the database scanning, the new algorithm, by using the property of the Apriori algorithm, limits the size of the candidate set in time whenever it is produced. Test results show the improved algorithm has a more lower complexity of time and space, better restrain noise and fit the capacity of memory.

Keywords: Candidate Sets Pruning, Data Mining, ImprovedAlgorithm, Noise Restrain, Web Log

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Authors: Zicheng Wang

Abstract:

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: Vahid Salmani, Saman Taghavi Zargar, Mahmoud Naghibzadeh

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This paper presents a modified version of the maximum urgency first scheduling algorithm. The maximum urgency algorithm combines the advantages of fixed and dynamic scheduling to provide the dynamically changing systems with flexible scheduling. This algorithm, however, has a major shortcoming due to its scheduling mechanism which may cause a critical task to fail. The modified maximum urgency first scheduling algorithm resolves the mentioned problem. In this paper, we propose two possible implementations for this algorithm by using either earliest deadline first or modified least laxity first algorithms for calculating the dynamic priorities. These two approaches are compared together by simulating the two algorithms. The earliest deadline first algorithm as the preferred implementation is then recommended. Afterwards, we make a comparison between our proposed algorithm and maximum urgency first algorithm using simulation and results are presented. It is shown that modified maximum urgency first is superior to maximum urgency first, since it usually has less task preemption and hence, less related overhead. It also leads to less failed non-critical tasks in overloaded situations.

Keywords: Modified maximum urgency first, maximum urgency first, real-time systems, scheduling.

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Authors: Mircea I. Pastrav, Cornelia Baera, Florea Dinu

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A different concept for designing and detailing of reinforced concrete precast frame structures is analyzed in this paper. The new detailing of the joints derives from the special hybrid moment frame joints. The special reinforcements of this alternative detailing, named modified special hybrid joint, are bondless with respect to both column and beams. Full scale tests were performed on a plan model, which represents a part of 5 story structure, cropped in the middle of the beams and columns spans. Theoretical approach was developed, based on testing results on twice repaired model, subjected to lateral seismic type loading. Discussion regarding the modified special hybrid joint behavior and further on widening research needed concludes the presentation.

Keywords: Acceptance criteria, modified hybrid joint, repair, seismic loading type.

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Authors: Ezequiel Herruzo, Juan José Cruz, José Ignacio Benavides, Oscar Plata

Abstract:

This paper describes a new algorithm of arrangement in parallel, based on Odd-Even Mergesort, called division and concurrent mixes. The main idea of the algorithm is to achieve that each processor uses a sequential algorithm for ordering a part of the vector, and after that, for making the processors work in pairs in order to mix two of these sections ordered in a greater one, also ordered; after several iterations, the vector will be completely ordered. The paper describes the implementation of the new algorithm on a Message Passing environment (such as MPI). Besides, it compares the obtained experimental results with the quicksort sequential algorithm and with the parallel implementations (also on MPI) of the algorithms quicksort and bitonic sort. The comparison has been realized in an 8 processors cluster under GNU/Linux which is running on a unique PC processor.

Keywords: Parallel algorithm, arrangement, MPI, sorting, parallel program.

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Authors: Mehdi Ghayoumi

Abstract:

We have applied new accelerated algorithm for linear discriminate analysis (LDA) in face recognition with support vector machine. The new algorithm has the advantage of optimal selection of the step size. The gradient descent method and new algorithm has been implemented in software and evaluated on the Yale face database B. The eigenfaces of these approaches have been used to training a KNN. Recognition rate with new algorithm is compared with gradient.

Keywords: lda, adaptive, svm, face recognition.

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Authors: A. R. Seifi

Abstract:

This work presents a new algorithm based on a combination of fuzzy (FUZ), Dynamic Programming (DP), and Genetic Algorithm (GA) approach for capacitor allocation in distribution feeders. The problem formulation considers two distinct objectives related to total cost of power loss and total cost of capacitors including the purchase and installation costs. The novel formulation is a multi-objective and non-differentiable optimization problem. The proposed method of this article uses fuzzy reasoning for sitting of capacitors in radial distribution feeders, DP for sizing and finally GA for finding the optimum shape of membership functions which are used in fuzzy reasoning stage. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder for the sake of conclusions supports. A comparison has been done among the proposed method of this paper and similar methods in other research works that shows the effectiveness of the proposed method of this paper for solving optimum capacitor planning problem.

Keywords: Capacitor planning, Fuzzy logic method, Genetic Algorithm, Dynamic programming, Radial Distribution feeder

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Authors: Juan Li, Chunfu Shao, Chunjiao Dong, Dan Zhao, Yinhong Liu

Abstract:

Mixed-traffic (e.g., pedestrians, bicycles, and vehicles) data at an intersection is one of the essential factors for intersection design and traffic control. However, some data such as pedestrian volume cannot be directly collected by common detectors (e.g. inductive loop, sonar and microwave sensors). In this paper, a video based detection algorithm is proposed for mixed-traffic data collection at intersections using surveillance cameras. The algorithm is derived from Gaussian Mixture Model (GMM), and uses a mergence time adjustment scheme to improve the traditional algorithm. Real-world video data were selected to test the algorithm. The results show that the proposed algorithm has the faster processing speed and more accuracy than the traditional algorithm. This indicates that the improved algorithm can be applied to detect mixed-traffic at signalized intersection, even when conflicts occur.

Keywords: detection, intersection, mixed traffic, moving objects.

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Authors: D. Karnawati, T.F. Fathani , B. Andayani, Suharto

Abstract:

This paper highlights the importance of integrating social and technical approach (which is so called a “hybrid socio-technical approach") as one innovative and strategic program to support the social development in geodisaster prone area in Indonesia. Such program mainly based on public education and community participation as a partnership program by the University, local government and may also with the private company and/ or local NGO. The indigenous, simple and low cost technology has also been introduced and developed as a part of the hybrid sociotechnical system, in order to ensure the life and environmental protection, with respect to the sustainable human and social development.

Keywords: Hybrid socio-technical system, indigenoustechnology, life and environmental protection, public education.

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Authors: Yi Zhang, Quan Zhou, Jun Li, Yanlang Hu

Abstract:

Scheduling algorithm is a key technology in satellite switching system with input-buffer. In this paper, a new scheduling algorithm and its realization are proposed. Based on Crossbar switching fabric, the algorithm adopts serial scheduling strategy and adjusts the output port arbitrating strategy for the better equity of every port. Consequently, it increases the matching probability. The algorithm can greatly reduce the scheduling delay and cell loss rate. The analysis and simulation results by OPNET show that the proposed algorithm has the better performance than others in average delay and cell loss rate, and has the equivalent complexity. On the basis of these results, the hardware realization and simulation based on FPGA are completed, which validate the feasibility of the new scheduling algorithm.

Keywords: Scheduling algorithm, input-buffer, serial scheduling, hardware design.

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