Search results for: friendly algorithm

Authors: Seyedmahdi Mousavihashemi

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One of the most important subjects of interest in researches is 'improving' which result in various algorithms. In so many geometrical problems we are faced with target functions which should be optimized. In group practices, all the functions’ cooperation lead to convergence. In the study, the optimization algorithm of dense particles is used. Usage of the algorithm improves the given performance norms. The results reveal that usage of swarm algorithm for reinforced particles in designing state feedback improves the given performance norm and in optimized designing of multi-target state feedback controlling, the network will maintain its bearing structure. The results also show that PSO is usable for optimization of state feedback controllers.

Keywords: multi-objective, enhanced, feedback, optimization, algorithm, particle, design

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Authors: Fariborz Ahmadi, Hamid Salehi, Khosrow Karimi

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A sensor network is set of sensor nodes that cooperate together to perform a predefined tasks. The important problem in this network is power consumption. So, in this paper one algorithm based on the eurygaster life is introduced to minimize power consumption by the nodes of these networks. In this method the search space of problem is divided into several partitions and each partition is investigated separately. The evaluation results show that our approach is more efficient in comparison to other evolutionary algorithm like genetic algorithm.

Keywords: evolutionary computation, genetic algorithm, particle swarm optimization, sensor network optimization

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Authors: Adeniran K. Ademuwagun, Alastair Allen

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The relationship dependence between RSS and distance in an enclosed environment is an important consideration because it is a factor that can influence the reliability of any localization algorithm founded on RSS. Several algorithms effectively reduce the variance of RSS to improve localization or accuracy performance. Our proposed algorithm essentially avoids this pitfall and consequently, its high adaptability in the face of erratic radio signal. Using 3 anchors in close proximity of each other, we are able to establish that RSS can be used as reliable indicator for localization with an acceptable degree of accuracy. Inherent in this concept, is the ability for each prospective anchor to validate (guarantee) the position or the proximity of the other 2 anchors involved in the localization and vice versa. This procedure ensures that the uncertainties of radio signals due to multipath effects in enclosed environments are minimized. A major driver of this idea is the implicit topological relationship among sensors due to raw radio signal strength. The algorithm is an area based algorithm; however, it does not trade accuracy for precision (i.e the size of the returned area).

Keywords: anchor nodes, centroid algorithm, communication graph, radio signal strength

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Authors: Said Baadel, Fadi Thabtah, Joan Lu

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Clustering involves the partitioning of n objects into k clusters. Many clustering algorithms use hard-partitioning techniques where each object is assigned to one cluster. In this paper, we propose an overlapping algorithm MCOKE which allows objects to belong to one or more clusters. The algorithm is different from fuzzy clustering techniques because objects that overlap are assigned a membership value of 1 (one) as opposed to a fuzzy membership degree. The algorithm is also different from other overlapping algorithms that require a similarity threshold to be defined as a priority which can be difficult to determine by novice users.

Keywords: data mining, k-means, MCOKE, overlapping

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Authors: Younis R. Elhaddad, Mohamed A. Alshaari

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Since 2700 B.C the problem of constructing magic squares attracts many researchers. Magic squares one of most difficult challenges for mathematicians. In this work, we describe how to construct and enumerate Pan- magic squares using genetic algorithm, using new chromosome encoding technique. The results were promising within reasonable time.

Keywords: genetic algorithm, magic square, pan-magic square, computational intelligence

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Authors: Yuqing Chen, Ying Xu, Renfa Li

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The development of matrix completion theory provides new approaches for data gathering in Wireless Sensor Networks (WSN). The existing matrix completion algorithms for WSN mainly consider how to reduce the sampling number without considering the real-time performance when recovering the data matrix. In order to guarantee the recovery accuracy and reduce the recovery time consumed simultaneously, we propose a new ALM algorithm to recover the weather monitoring data. A lot of experiments have been carried out to investigate the performance of the proposed ALM algorithm by using different parameter settings, different sampling rates and sampling models. In addition, we compare the proposed ALM algorithm with some existing algorithms in the literature. Experimental results show that the ALM algorithm can obtain better overall recovery accuracy with less computing time, which demonstrate that the ALM algorithm is an effective and efficient approach for recovering the real world weather monitoring data in WSN.

Keywords: wireless sensor network, matrix completion, singular value thresholding, augmented Lagrange multiplier

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Authors: Sahin Emrah Amrahov, Fatih Aybar, Serhat Dogan

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In this paper we consider the rule reduct generation problem. Rule Reduct Generation (RG) and Modified Rule Generation (MRG) algorithms, that are used to solve this problem, are well-known. Alternative to these algorithms, we develop Pruning Rule Generation (PRG) algorithm. We compare the PRG algorithm with RG and MRG.

Keywords: rough sets, decision rules, rule induction, classification

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Authors: Nirmal Yadav, Tanuja Srivastava

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Shannon theory is an exact method to recover a band limited signals from its sampled values in discrete implementation, using sinc interpolators. But sinc based results are not much satisfactory for band-limited calculations so that convolution with window function, having compact support, has been introduced. Convolution Backprojection algorithm with window function is an approximation algorithm. In this paper, the error has been calculated, arises due to this approximation nature of reconstruction algorithm. This result will be defined for fan beam projection data which is more faster than parallel beam projection.

Keywords: computed tomography, convolution backprojection, radon transform, fan beam

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Authors: Shahram Jamali, Samira Hamed

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One of the open issues in Random Early Detection (RED) algorithm is how to set its parameters to reach high performance for the dynamic conditions of the network. Although original RED uses fixed values for its parameters, this paper follows a model-based approach to upgrade performance of the RED algorithm. It models the routers queue behavior by using the Markov model and uses this model to predict future conditions of the queue. This prediction helps the proposed algorithm to make some tunings over RED's parameters and provide efficiency and better performance. Widespread packet level simulations confirm that the proposed algorithm, called Markov-RED, outperforms RED and FARED in terms of queue stability, bottleneck utilization and dropped packets count.

Keywords: active queue management, RED, Markov model, random early detection algorithm

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Authors: Juan Manuel Sanchez-Cartas, Gonzalo Leon

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A price competition algorithm for ABMs based on game theory principles is proposed to deal with the simulation of theoretical market models. The algorithm is applied to the classical Hotelling’s model and to a two-sided market model to show it leads to the optimal behavior predicted by theoretical models. However, when theoretical models fail to predict the equilibrium, the algorithm is capable of reaching a feasible outcome. Results highlight that the algorithm can be implemented in other simulation models to guarantee rational users and endogenous optimal behaviors. Also, it can be applied as a tool of verification given that is theoretically based.

Keywords: agent-based models, algorithmic game theory, multi-sided markets, price optimization

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Authors: Kalyan Kumar Moulick

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In this paper the author studied the possibilities of using Rice Husk Ash (RHA) available in India; to produce concrete. The effect of RHA on concrete discussed. Traditional uses of Rice Husk in India pointed out and the advantages of using RHA in making concrete highlighted. Suggestion provided regarding prospective application of RHA concrete in India which in turn will definitely reduce the cost of concrete and environmental friendly due to utilization of waste and replacement of Cement.

Keywords: cement replacement, concrete, environmental friendly, rice husk ash

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Authors: Smail Tigani, Mohamed Ouzzif

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This work presents a discrete quantitative state prediction algorithm with intelligent behavior making it able to self-improve some performance aspects. The specificity of this algorithm is the capacity of self-rectification of the prediction strategy before the final decision. The auto-rectification mechanism is based on two parallel mathematical models. In one hand, the algorithm predicts the next state based on event transition matrix updated after each observation. In the other hand, the algorithm extracts its residues trend with a linear regression representing historical residues data-points in order to rectify the first decision if needs. For a normal distribution, the interactivity between the two models allows the algorithm to self-optimize its performance and then make better prediction. Designed key performance indicator, computed during a Monte Carlo simulation, shows the advantages of the proposed approach compared with traditional one.

Keywords: discrete state, Markov Chains, linear regression, auto-adaptive systems, decision making, Monte Carlo Simulation

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Authors: B. Selma, S. Chouraqui

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The pancreas is an elongated organ that extends across the abdomen, below the stomach. In addition, it secretes certain enzymes that aid in food digestion. The pancreas also manufactures hormones responsible for regulating blood glucose levels. In the present paper, we propose a mathematical model to study the homeostasis of glucose and insulin in healthy human, and a simulation of this model, which depicts the physiological events after a meal, will be represented in ordinary humans. The aim of this paper is to design an algorithm which regulates the level of glucose in the blood. The algorithm applied the concept of expert system for performing an algorithm control in the form of an "active" used to prescribe the rate of insulin infusion. By decomposing the system into subsystems, we have developed parametric models of each subsystem by using a forcing function strategy. The results showed a performance of the control system.

Keywords: modeling, algorithm, regulation, glucose-insulin, blood, control system

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Authors: Bircan Demiral

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Cognitive radio (CR) is the promising technology that addresses the spectrum scarcity problem for future wireless communications. Orthogonal Frequency Division Multiplexing (OFDM) technology provides more power band ratios for cognitive radio networks (CRNs). While CR is a solution to the spectrum scarcity, it also brings up the capacity problem. In this paper, a novel power allocation algorithm that aims at maximizing the sum capacity in the OFDM based cognitive radio networks is proposed. Proposed allocation algorithm is based on the previously developed water-filling algorithm. To reduce the computational complexity calculating in water filling algorithm, proposed algorithm allocates the total power according to each subcarrier. The power allocated to the subcarriers increases sum capacity. To see this increase, Matlab program was used, and the proposed power allocation was compared with average power allocation, water filling and general power allocation algorithms. The water filling algorithm performed worse than the proposed algorithm while it performed better than the other two algorithms. The proposed algorithm is better than other algorithms in terms of capacity increase. In addition the effect of the change in the number of subcarriers on capacity was discussed. Simulation results show that the increase in the number of subcarrier increases the capacity.

Keywords: cognitive radio network, OFDM, power allocation, water filling

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Authors: Syeda Afsana Azad

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Climate change, due to the release of greenhouse gases into the atmosphere has been recognized as one of the biggest threats to the present world. The condition of the earth is getting worse day by day due to climate change. Bangladesh is considered to be one of the most vulnerable countries to climate change due to large population, sharp urbanization, etc. Construction of green building is a very good solution to reduce the greenhouse effect. Green building technology refers to that kind of structures which are environmentally friendly and resource-efficient throughout a building’s service life. This technology can provide at least 50% energy saving opportunity to the nation. The necessity of the construction of structures in an environment-friendly way is increasing now. This study shows the scenario of rapid population growth, urbanization, necessity of green building in Bangladesh and also discusses the construction process of green building. As the present climate condition of Bangladesh is not friendly, construction of green building is very much needed. To battle climate change, it is mandatory to construct green building.

Keywords: Bangladesh, climate change, green building, green house effect

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Authors: J. Sahari, S. M. Sapuan

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Eco-friendly composites have been successfully prepared by using sugar palm tree as a sources. The effect of fibre content on mechanical properties of (SPF/SPS) biocomposites have been done and the experimentally tensile properties (tensile strength and modulus) of biocomposites have been compared with the existing theories of reinforcement. The biocomposites were prepared with different amounts of fibres (i.e. 10%, 20% and 30% by weight percent). The mechanical properties of plasticized SPS improved with the incorporation of fibres. Both approaches (experimental and theoretical) show that the young’s modulus of the biocomposites is consistently increased when the sugar palm fibre (SPF) are placed into the sugar palm starch matrix (SPS). Surface morphological study through scanning electron microscopy showed homogeneous distribution of fibres and matrix with good adhesion which play an important role in improving the mechanical properties of biocomposites. The observed deviations between the experimental and theoretical values are explained by the simplifying model assumptions applied for the configuration of the composites, in particular the sugar palm starch composites.

Keywords: eco-friendly, biocomposite, mechanical, experimental, theoretical

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Authors: Majid Khalili

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This paper deals with a bi-objective hybrid no-wait flowshop scheduling problem minimizing the makespan and total weighted tardiness, in which we consider transportation times between stages. Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. This paper presents a new multi-objective variable neighborhood algorithm (MOVNS). A set of experimental instances are carried out to evaluate the algorithm by advanced multi-objective performance measures. The algorithm is carefully evaluated for its performance against available algorithm by means of multi-objective performance measures and statistical tools. The related results show that a variant of our proposed MOVNS provides sound performance comparing with other algorithms.

Keywords: no-wait hybrid flowshop scheduling; multi-objective variable neighborhood algorithm; makespan; total weighted tardiness

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Authors: Duckyong Kim, Jong Kang Park, Jong Tae Kim

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DOA (Direction of Arrival) estimation is an important method in array signal processing and has a wide range of applications such as direction finding, beam forming, and so on. In this paper, we briefly introduce the MUSIC (Multiple Signal Classification) Algorithm, one of DOA estimation methods for analyzing several targets. Then we apply the MUSIC algorithm to the two-dimensional antenna array to analyze DOA estimation in 3D space through MATLAB simulation. We also analyze the design factors that can affect the accuracy of DOA estimation through simulation, and proceed with further consideration on how to apply the system.

Keywords: DOA estimation, MUSIC algorithm, spatial spectrum, array signal processing

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Authors: Supriady R. P. Siregar, Rizki Barkah Aulia, Dhiya Fadilla Dewi

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Polybag is a plastic that is used to seed plants. The common type that used for polybag is a synthetic that made from petroleum such as polyethylene. Beside the character of the raw material that are non-renewable and limited, synthetic polybag ability to disintegrate in the environment is very low. According to that situation, we need a solution to overcome these problems by creating an environmentally friendly polybag. In this research, using the water hyacinth plant fibers (Eichornia crassipes) as a major component in manufacturing the environmentally friendly polybag, the water hyacinth (Eichornia crassipes) contains approximately 60% cellulose. The research method used is an experiment by testing the mechanical characters and biodegradability bio-polybag water hyacinth fibers (Eichornia crassipes) on three medium that is dissolved in water, river water and buried in soil. The research shows bio-polybag of hyacinth fibers can rapidly degraded. This study is expected to be the beginning of the creation bio-polybag of water hyacinth fiber (Eichornia crassipes) and can be applied in agriculture.

Keywords: revolution, biopolybag, renewable, environment

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Authors: Archit Yajnik

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Part of Speech Tagging has always been a challenging task in the era of Natural Language Processing. This article presents POS tagging for Nepali text using Hidden Markov Model and Viterbi algorithm. From the Nepali text, annotated corpus training and testing data set are randomly separated. Both methods are employed on the data sets. Viterbi algorithm is found to be computationally faster and accurate as compared to HMM. The accuracy of 95.43% is achieved using Viterbi algorithm. Error analysis where the mismatches took place is elaborately discussed.

Keywords: hidden markov model, natural language processing, POS tagging, viterbi algorithm

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Authors: Hussain K. Chaiel

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The development in the field of the digital signal processing (DSP) and the microelectronics technology reduces the complexity of the iterative algorithms that need large number of arithmetic operations. Virtex-Field Programmable Gate Arrays (FPGAs) are programmable silicon foundations which offer an important solution for addressing the needs of high performance DSP designer. In this work, Virtex-7 FPGA technology is used to implement an iterative algorithm to estimate the earthquake location. Simulation results show that an implementation based on block RAMB36E1 and DSP48E1 slices of Virtex-7 type reduces the number of cycles of the clock frequency. This enables the algorithm to be used for earthquake prediction.

Keywords: DSP, earthquake, FPGA, iterative algorithm

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Authors: A. Andreasyan, C. Connors

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The Elliptic Curve Digital Signature algorithm-based X509v3 certificates are becoming more popular due to their short public and private key sizes. Moreover, these certificates can be stored in Internet of Things (IoT) devices, with limited resources, using less memory and transmitted in network security protocols, such as Internet Key Exchange (IKE), Transport Layer Security (TLS) and Secure Shell (SSH) with less bandwidth. The proposed method gives another advantage, in that it increases the performance of the above-mentioned protocols in terms of key exchange by saving one scalar multiplication operation.

Keywords: cryptography, elliptic curve digital signature algorithm, key exchange, network security protocol

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Authors: Meng Wu

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Motion planning is a common task required to be fulfilled by robots. A strategy combining Ant Colony Optimization (ACO) and gravity gradient inversion algorithm is proposed for motion planning of mobile robots. In this paper, in order to realize optimal motion planning strategy, the cost function in ACO is designed based on gravity gradient inversion algorithm. The obstacles around mobile robot can cause gravity gradient anomalies; the gradiometer is installed on the mobile robot to detect the gravity gradient anomalies. After obtaining the anomalies, gravity gradient inversion algorithm is employed to calculate relative distance and orientation between mobile robot and obstacles. The relative distance and orientation deduced from gravity gradient inversion algorithm is employed as cost function in ACO algorithm to realize motion planning. The proposed strategy is validated by the simulation and experiment results.

Keywords: motion planning, gravity gradient inversion algorithm, ant colony optimization

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Authors: C. A. Akaash Emmanuel Raj, V. R. Sanal Kumar

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In this paper using smart materials we have proposed a specially manufactured variable volume spin tub for loading clothes for negating the vibration to a certain extent for getting better operating performance. Additionally, we have recommended a variable spinning speed rotor for handling varieties of garments for an efficient washing, aiming for increasing the life span of both the garments and the machine. As a part of the conflicting dynamic constraints and demands of the customer friendly design optimization of a lucrative and cosmetic washing machine we have proposed a drier and a desalination system capable to supply desirable heat and a pleasing fragrance to the garments. We thus concluded that while incorporating variable volume and variable spinning speed tub integrated with a drier and desalination system, the washing machine could meet the varieties of domestic requirements of the customers cost-effectively.

Keywords: customer friendly washing machine, drier design, quick cloth cleaning, variable tub volume washing machine, variable spinning speed washing machine

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Authors: Sofiane Bououden, Ilyes Boulkaibet

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In terms of security of the information signal, the meta-heuristic Penguins Search Optimization Algorithm (PeSOA) is applied to synchronize chaotic encryption communications in the case of sensitive dependence on initial conditions in chaotic generator oscillator. The objective of this paper is the use of the PeSOA algorithm to exploring search space with random and iterative processes for synchronization of symmetric keys in both transmission and reception. Simulation results show the effectiveness of the PeSOA algorithm in generating symmetric keys of the encryption process and synchronizing.

Keywords: meta-heuristic, PeSOA, chaotic systems, encryption, synchronization optimization

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Authors: Watchara Songserm, Teeradej Wuttipornpun

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This paper presents a genetic algorithm based permutation and non-permutation scheduling heuristics (GAPNP) to solve a multi-stage finite capacity material requirement planning (FCMRP) problem in automotive assembly flow shop with unrelated parallel machines. In the algorithm, the sequences of orders are iteratively improved by the GA characteristics, whereas the required operations are scheduled based on the presented permutation and non-permutation heuristics. Finally, a linear programming is applied to minimize the total cost. The presented GAPNP algorithm is evaluated by using real datasets from automotive companies. The required parameters for GAPNP are intently tuned to obtain a common parameter setting for all case studies. The results show that GAPNP significantly outperforms the benchmark algorithm about 30% on average.

Keywords: capacitated MRP, genetic algorithm, linear programming, automotive industries, flow shop, application in industry

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Authors: Shreya Pare, Parvin Akhter

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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.

Keywords: clustering, load profiling, load modeling, machine learning, energy efficiency and quality

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Authors: Nevena Jakovčević Stor, Ivan Slapničar

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Any polynomial can be expressed as a characteristic polynomial of a complex symmetric arrowhead matrix. This expression is not unique. If the polynomial is real with only real distinct roots, the matrix can be chosen as real. By using accurate forward stable algorithm for computing eigen values of real symmetric arrowhead matrices we derive a forward stable algorithm for computation of roots of such polynomials in O(n^2 ) operations. The algorithm computes each root to almost full accuracy. In some cases, the algorithm invokes extended precision routines, but only in the non-iterative part. Our examples include numerically difficult problems, like the well-known Wilkinson’s polynomials. Our algorithm compares favorably to other method for polynomial root-finding, like MPSolve or Newton’s method.

Keywords: roots of polynomials, eigenvalue decomposition, arrowhead matrix, high relative accuracy

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a new hybrid particle swarm optimization algorithm is proposed for the multi-objective flexible job shop scheduling problem that is very important and hard combinatorial problem. The Pareto approach is used for solving the multi-objective problem. Several new local search heuristics are integrated into an algorithm based on the critical block concept to enhance the performance of the algorithm. The algorithm is compared with the recently published multi-objective algorithms based on benchmarks selected from the literature. Several metrics are used for quantifying performance and comparison of the achieved solutions. The algorithms are also compared based on the Weighting summation of objectives approach. The proposed algorithm can find the Pareto solutions more efficiently than the compared algorithms in less computational time.

Keywords: swarm-based optimization, local search, Pareto optimality, flexible job shop scheduling, multi-objective optimization

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