Search results for: Inverse problem method

Authors: M. Zarebnia, R. Parvaz

Abstract:

In this paper, numerical solutions of the nonlinear Benjamin-Bona-Mahony-Burgers (BBMB) equation are obtained by a method based on collocation of cubic B-splines. Applying the Von-Neumann stability analysis, the proposed method is shown to be unconditionally stable. The method is applied on some test examples, and the numerical results have been compared with the exact solutions. The L∞ and L2 in the solutions show the efficiency of the method computationally.

Keywords: Benjamin-Bona-Mahony-Burgers equation, Cubic Bspline, Collocation method, Finite difference.

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Authors: Warattapop Chainate, Peeraya Thapatsuwan, Pupong Pongcharoen

Abstract:

The hybridisation of genetic algorithm with heuristics has been shown to be one of an effective way to improve its performance. In this work, genetic algorithm hybridised with four heuristics including a new heuristic called neighbourhood improvement were investigated through the classical travelling salesman problem. The experimental results showed that the proposed heuristic outperformed other heuristics both in terms of quality of the results obtained and the computational time.

Keywords: Genetic Algorithm, Hybridisation, Metaheuristics, Travelling Salesman Problem.

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Authors: M Nayeripour, E. Azad, A. Roosta, T. Niknam

Abstract:

In this paper, the transformers over-load problem of Shiraz substation in Fars Regional Electric Company (FREC) is investigated for a period of three years plan. So the suggestions for using phase shifting transformer (PST) and unified power flow controller (UPFC) in order to solve this problem are examined in details and finally, some economical and practical designs will be given in order to solve the related problems. Practical consideration and using the basic and fundamental concept of powers in transmission lines in order to find the economical design are the main advantages of this research. The simulation results of the integrated overall system with different designs compare them base on economical and practical aspects to solve the over-load and loss-reduction.

Keywords: Congestion management, Phase shifting transformer(PST), Unified power flow controller (UPFC), Transmission lines.

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Authors: Krishna S. Raghuwaiya, Shonal Singh, Jito Vanualailai

Abstract:

In this paper, we study the formation control problem for car-like mobile robots. A team of nonholonomic mobile robots navigate in a terrain with obstacles, while maintaining a desired formation, using a leader-following strategy. A set of artificial potential field functions is proposed using the direct Lyapunov method for the avoidance of obstacles and attraction to their designated targets. The effectiveness of the proposed control laws to verify the feasibility of the model is demonstrated through computer simulations

Keywords: Control, Formation, Lyapunov, Nonholonomic

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Authors: D. Mehdizadeh, M. Rahimian, M. Eskandari-Ghadi

Abstract:

This article is concerned with the determination of the static interaction of a vertically loaded rigid circular disc embedded at the interface of a horizontal layer sandwiched in between two different transversely isotropic half-spaces called as tri-material full-space. The axes of symmetry of different regions are assumed to be normal to the horizontal interfaces and parallel to the movement direction. With the use of a potential function method, and by implementing Hankel integral transforms in the radial direction, the government partial differential equation for the solely scalar potential function is transformed to an ordinary 4th order differential equation, and the mixed boundary conditions are transformed into a pair of integral equations called dual integral equations, which can be reduced to a Fredholm integral equation of the second kind, which is solved analytically. Then, the displacements and stresses are given in the form of improper line integrals, which is due to inverse Hankel integral transforms. It is shown that the present solutions are in exact agreement with the existing solutions for a homogeneous full-space with transversely isotropic material. To confirm the accuracy of the numerical evaluation of the integrals involved, the numerical results are compared with the solutions exists for the homogeneous full-space. Then, some different cases with different degrees of material anisotropy are compared to portray the effect of degree of anisotropy.

 

Keywords: Transversely isotropic, rigid disc, elasticity, dual integral equations, tri-material full-space.

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Authors: Sumachaya Harnsukworapanich, Tetsuo Ichimori

Abstract:

The apportionment method is used by many countries, to calculate the distribution of seats in political bodies. For example, this method is used in the United States (U.S.) to distribute house seats proportionally based on the population of the electoral district. Famous apportionment methods include the divisor methods called the Adams Method, Dean Method, Hill Method, Jefferson Method and Webster Method. Sometimes the results from the implementation of these divisor methods are unfair and include errors. Therefore, it is important to examine the optimization of this method by using a bias measurement to figure out precise and fair results. In this research we investigate the bias of divisor methods in the U.S. Houses of Representatives toward large and small states by applying the Stolarsky Mean Method. We compare the bias of the apportionment method by using two famous bias measurements: the Balinski and Young measurement and the Ernst measurement. Both measurements have a formula for large and small states. The Third measurement however, which was created by the researchers, did not factor in the element of large and small states into the formula. All three measurements are compared and the results show that our measurement produces similar results to the other two famous measurements.

Keywords: Apportionment, Bias, Divisor, Fair, Simulation

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Authors: A. Elmarhomy, S. Karungaru, K. Terada

Abstract:

Understanding the number of people and the flow of the persons is useful for efficient promotion of the institution managements and company-s sales improvements. This paper introduces an automated method for counting passerby using virtualvertical measurement lines. The process of recognizing a passerby is carried out using an image sequence obtained from the USB camera. Space-time image is representing the human regions which are treated using the segmentation process. To handle the problem of mismatching, different color space are used to perform the template matching which chose automatically the best matching to determine passerby direction and speed. A relation between passerby speed and the human-pixel area is used to distinguish one or two passersby. In the experiment, the camera is fixed at the entrance door of the hall in a side viewing position. Finally, experimental results verify the effectiveness of the presented method by correctly detecting and successfully counting them in order to direction with accuracy of 97%.

Keywords: counting passersby, virtual-vertical measurement line, passerby speed, space-time image

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Authors: H. Y. Jung, Ju H. Park, S. M. Lee

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Sampled-data controller is presented for solid oxide fuel cell systems which is expressed by a sector bounded nonlinear model. The proposed control law is obtained by solving a convex problem satisfying several linear matrix inequalities. Simulation results are given to show the effectiveness of the proposed design method.

Keywords: Sampled-data control, Sector bound, Solid oxide fuel cell, Time-delay.

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Authors: S. Raja Balachandar, K.Kannan

Abstract:

A new Meta heuristic approach called "Randomized gravitational emulation search algorithm (RGES)" for solving vertex covering problems has been designed. This algorithm is found upon introducing randomization concept along with the two of the four primary parameters -velocity- and -gravity- in physics. A new heuristic operator is introduced in the domain of RGES to maintain feasibility specifically for the vertex covering problem to yield best solutions. The performance of this algorithm has been evaluated on a large set of benchmark problems from OR-library. Computational results showed that the randomized gravitational emulation search algorithm - based heuristic is capable of producing high quality solutions. The performance of this heuristic when compared with other existing heuristic algorithms is found to be excellent in terms of solution quality.

Keywords: Vertex covering Problem, Velocity, Gravitational Force, Newton's Law, Meta Heuristic, Combinatorial optimization.

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Authors: Mohammad Izadkhah, Mojtaba Hoseini, Alireza Khalili Tehrani

Abstract:

In this paper we presented a new method for tracking flying targets in color video sequences based on contour and kernel. The aim of this work is to overcome the problem of losing target in changing light, large displacement, changing speed, and occlusion. The proposed method is made in three steps, estimate the target location by particle filter, segmentation target region using neural network and find the exact contours by greedy snake algorithm. In the proposed method we have used both region and contour information to create target candidate model and this model is dynamically updated during tracking. To avoid the accumulation of errors when updating, target region given to a perceptron neural network to separate the target from background. Then its output used for exact calculation of size and center of the target. Also it is used as the initial contour for the greedy snake algorithm to find the exact target's edge. The proposed algorithm has been tested on a database which contains a lot of challenges such as high speed and agility of aircrafts, background clutter, occlusions, camera movement, and so on. The experimental results show that the use of neural network increases the accuracy of tracking and segmentation.

Keywords: Video tracking, particle filter, greedy snake, neural network.

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Authors: K. M. Oba

Abstract:

The transportation modelling technique was adopted in the solution of the problem of transportation of Plaster of Paris (POP) cement from three supply locations (construction materials markets) to three demand locations (construction sites) in Port Harcourt. The study was carried out for 40 kg bags of POP cement fully loaded on 600 bags per truck from the three selected construction materials markets in Port Harcourt. The costs of transporting the POP cement were determined and subjected to the North-West Corner, Least Cost, and Vogel’s approximation methods to determine the initial feasible solution. Of the three results, the Least Cost Method turned out to have the lowest cost. Using the Stepping Stone Method, the optimum shipping cost was finally attained after two successive iterations. The optimum shipping cost was calculated to be $1,690 or ₦1,774,500 as of October 2023. As a result of this study, the application of transportation modelling can boost the effective management of the transportation of POP cement in construction projects.

Keywords: Cost of POP cement, management of transportation, optimization of shipping cost, Plaster of Paris, transportation model.

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Authors: Rami N. Khushaba, Adel Al-Jumaily

Abstract:

The myoelectric signal (MES) is one of the Biosignals utilized in helping humans to control equipments. Recent approaches in MES classification to control prosthetic devices employing pattern recognition techniques revealed two problems, first, the classification performance of the system starts degrading when the number of motion classes to be classified increases, second, in order to solve the first problem, additional complicated methods were utilized which increase the computational cost of a multifunction myoelectric control system. In an effort to solve these problems and to achieve a feasible design for real time implementation with high overall accuracy, this paper presents a new method for feature extraction in MES recognition systems. The method works by extracting features using Wavelet Packet Transform (WPT) applied on the MES from multiple channels, and then employs Fuzzy c-means (FCM) algorithm to generate a measure that judges on features suitability for classification. Finally, Principle Component Analysis (PCA) is utilized to reduce the size of the data before computing the classification accuracy with a multilayer perceptron neural network. The proposed system produces powerful classification results (99% accuracy) by using only a small portion of the original feature set.

Keywords: Biomedical Signal Processing, Data mining andInformation Extraction, Machine Learning, Rehabilitation.

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Authors: MP. Mulaudzi, MA. Petersen, J. Mukuddem-Petersen , IM. Schoeman, B. de Waal, JM. Manale

Abstract:

This conference paper discusses a risk allocation problem for subprime investing banks involving investment in subprime structured mortgage products (SMPs) and Treasuries. In order to solve this problem, we develop a L'evy process-based model of jump diffusion-type for investment choice in subprime SMPs and Treasuries. This model incorporates subprime SMP losses for which credit default insurance in the form of credit default swaps (CDSs) can be purchased. In essence, we solve a mean swap-at-risk (SaR) optimization problem for investment which determines optimal allocation between SMPs and Treasuries subject to credit risk protection via CDSs. In this regard, SaR is indicative of how much protection investors must purchase from swap protection sellers in order to cover possible losses from SMP default. Here, SaR is defined in terms of value-at-risk (VaR). Finally, we provide an analysis of the aforementioned optimization problem and its connections with the subprime mortgage crisis (SMC).

Keywords: Investors; Jump Diffusion Process, Structured Mortgage Products, Treasuries, Credit Risk, Credit Default Swaps, Tranching Risk, Counterparty Risk, Value-at-Risk, Swaps-at-Risk, Subprime Mortgage Crisis.

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Authors: A. G. Pradeep, Gorantla Giridhar Kumar, Vijay Turaga, Vinod Srinivasa

Abstract:

The major problem in the flow control valve is of lower Flow Capacity (Cv) which will reduce overall efficiency of flow circuit. Designers are continuously working to improve the Cv of the valve, but they need to validate the design ideas they have regarding the improvement of Cv. Traditional method of prototype and testing take a lot of time, that is where CFD comes into picture with very quick and accurate validation along with the visualization which is not possible with traditional testing method. We have developed a method to predict Cv value using CFD analysis by iterating on various Boundary conditions, solver settings and by carrying out grid convergence studies to establish correlation between the CFD model and Test data. The present study investigates 3 different ideas put forward by the designers for improving the flow capacity of the valves like reducing the cage thickness, changing the port position, and using the parabolic plug to guide the flow. Using CFD, we analyzed all design changes using the established methodology that we developed. We were able to evaluate the effect of these design changes on the Valve Cv. We optimized the wetted surface of the valve further by suggesting the design modification to the lower part of the valve to make the flow more streamlined. We could find that changing cage thickness and port position has little impact on the valve Cv. Combination of optimized wetted surface and introduction of parabolic plug improved the Cv of the valve significantly.

Keywords: Flow control valves, flow capacity, CFD simulations, design validation.

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Authors: S. Gao, S. Srirattayawong

Abstract:

In this study, a computational fluid dynamics (CFD) model has been developed for studying the effect of surface roughness profile on the EHL problem. The cylinders contact geometry, meshing and calculation of the conservation of mass and momentum equations are carried out using the commercial software packages ICEMCFD and ANSYS Fluent. The user defined functions (UDFs) for density, viscosity and elastic deformation of the cylinders as the functions of pressure and temperature are defined for the CFD model. Three different surface roughness profiles are created and incorporated into the CFD model. It is found that the developed CFD model can predict the characteristics of fluid flow and heat transfer in the EHL problem, including the main parameters such as pressure distribution, minimal film thickness, viscosity, and density changes. The results obtained show that the pressure profile at the center of the contact area directly relates to the roughness amplitude. A rough surface with kurtosis value of more than 3 has greater influence over the fluctuated shape of pressure distribution than in other cases.

Keywords: CFD, EHL, Kurtosis, Surface roughness.

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Authors: Chih-Cheng Chen, Yung-Tan Lee, Shih-Yang Lee, Shih-Kuei Huang, Tien-Tze Chen, Qiu-Jun Chen

Abstract:

The evaluation of the contribution of professional baseball starting pitchers is a complex decision-making problem that includes several quantitative attributes. It is considered a type of multi-attribute or multi-criteria decision making (MADM/MCDM) problem. This study proposes a model using the Grey Relational Analysis (GRA) to evaluate the starting pitcher contribution for teams of the Chinese Professional Baseball League. The GRA calculates the individual grey relational degree of each alternative to the positive ideal alternative. An empirical analysis was conducted to show the use of the model for the starting pitcher contribution problem. The results demonstrate the effectiveness and feasibility of the proposed model.

Keywords: Starting pitchers, Grey Relational Analysis, Chinese Professional Baseball

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Authors: Jinsiang Shaw, Ray Pan, Yin-Chieh Chang

Abstract:

In this paper, an magnetorheological (MR) mount with fuzzy sliding mode controller (FSMC) is studied for vibration suppression when the system is subject to base excitations. In recent years, magnetorheological fluids are becoming a popular material in the field of the semi-active control. However, the dynamic equation of an MR mount is highly nonlinear and it is difficult to identify. FSMC provides a simple method to achieve vibration attenuation of the nonlinear system with uncertain disturbances. This method is capable of handling the chattering problem of sliding mode control effectively and the fuzzy control rules are obtained by using the Lyapunov stability theory. The numerical simulations using one-dimension and two-dimension FSMC show effectiveness of the proposed controller for vibration suppression. Further, the well-known skyhook control scheme and an adaptive sliding mode controller are also included in the simulation for comparison with the proposed FSMC.

Keywords: adaptive sliding mode controller, fuzzy sliding modecontroller, magnetorheological mount, skyhook control.

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Authors: Adil AL-Rammahi

Abstract:

In this short paper, new properties of transition matrix were introduced. Eigen values for small order transition matrices are calculated in flexible method. For benefit of these properties applications of these properties were studied in the solution of Markov's chain via steady state vector, and information theory via channel entropy. The implemented test examples were promised for usages.

Keywords: Eigen value problem, transition matrix, state vector, information theory.

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Authors: Anirut Luadsong, Nitima Aschariyaphotha

Abstract:

The spectral action balance equation is an equation that used to simulate short-crested wind-generated waves in shallow water areas such as coastal regions and inland waters. This equation consists of two spatial dimensions, wave direction, and wave frequency which can be solved by finite difference method. When this equation with dominating convection term are discretized using central differences, stability problems occur when the grid spacing is chosen too coarse. In this paper, we introduce the splitting upwind schemes for avoiding stability problems and prove that it is consistent to the upwind scheme with same accuracy. The splitting upwind schemes was adopted to split the wave spectral action balance equation into four onedimensional problems, which for each small problem obtains the independently tridiagonal linear systems. For each smaller system can be solved by direct or iterative methods at the same time which is very fast when performed by a multi-processor computer.

Keywords: upwind scheme, parallel algorithm, spectral action balance equation, splitting method.

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Authors: I. V. Kuzminov

Abstract:

According to its content, the proposed article is a collection of articles with comments and additions. All articles, in one way or another, have a connection with the Second Law of Thermodynamics. The content of the articles is given in a concise form. The articles were published in different journals at different times. Main topics are presented: gravity, biography of the Earth, physics of global warming-cooling cycles, multiverse. The articles are based on the laws of classical physics. Along the way, it should be noted that the Second Law of Thermodynamics can be formulated as the Law of Matter Cooling. As it cools down, the processes of condensation, separation, and changes in the aggregate states of matter occur. In accordance with these changes, a picture of the world is being formed. Also, the main driving force of these processes is the inverse temperature dependence of the forces of gravity. As matter cools, the forces of gravity increase. The actions of these phenomena in the compartment form a picture of the world.

Keywords: Gravitational forces, cooling of matter, second law of thermodynamics, planetary model of the atom.

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Authors: Razib M. Othman, Safaai Deris, Rosli M. Illias, Zalmiyah Zakaria, Saberi M. Mohamad

Abstract:

Nowadays, Gene Ontology has been used widely by many researchers for biological data mining and information retrieval, integration of biological databases, finding genes, and incorporating knowledge in the Gene Ontology for gene clustering. However, the increase in size of the Gene Ontology has caused problems in maintaining and processing them. One way to obtain their accessibility is by clustering them into fragmented groups. Clustering the Gene Ontology is a difficult combinatorial problem and can be modeled as a graph partitioning problem. Additionally, deciding the number k of clusters to use is not easily perceived and is a hard algorithmic problem. Therefore, an approach for solving the automatic clustering of the Gene Ontology is proposed by incorporating cohesion-and-coupling metric into a hybrid algorithm consisting of a genetic algorithm and a split-and-merge algorithm. Experimental results and an example of modularized Gene Ontology in RDF/XML format are given to illustrate the effectiveness of the algorithm.

Keywords: Automatic clustering, cohesion-and-coupling metric, gene ontology; genetic algorithm, split-and-merge algorithm.

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Authors: Qing Lyu, Hang Zhu

Abstract:

Various flows in the network require to go through different types of middlebox. The improper placement of network middlebox and path assignment for flows could greatly increase the network latency and also decrease the performance of network. Minimizing the total end to end latency of all the ows requires to assign path for the incoming flows. In this paper, the flow path assignment problem in regard to the placement of various kinds of middlebox is studied. The flow path assignment problem is formulated to a linear programming problem, which is very time consuming. On the other hand, a naive greedy algorithm is studied. Which is very fast but causes much more latency than the linear programming algorithm. At last, the paper presents a heuristic algorithm named FPA, which takes bottleneck link information and estimated bandwidth occupancy into consideration, and achieves near optimal latency in much less time. Evaluation results validate the effectiveness of the proposed algorithm.

Keywords: Latency, Fast path assignment, Bottleneck link.

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Authors: Shigeaki Sakurai, Youichi Kitahata, Ryohei Orihara

Abstract:

This paper proposes a method that discovers sequential patterns corresponding to user-s interests from sequential data. This method expresses the interests as constraint patterns. The constraint patterns can define relationships among attributes of the items composing the data. The method recursively decomposes the constraint patterns into constraint subpatterns. The method evaluates the constraint subpatterns in order to efficiently discover sequential patterns satisfying the constraint patterns. Also, this paper applies the method to the sequential data composed of stock price indexes and verifies its effectiveness through comparing it with a method without using the constraint patterns.

Keywords: Sequential pattern mining, Constraint pattern, Attribute constraint, Stock price indexes

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Authors: P. Luangpaiboon

Abstract:

Various intelligences and inspirations have been adopted into the iterative searching process called as meta-heuristics. They intelligently perform the exploration and exploitation in the solution domain space aiming to efficiently seek near optimal solutions. In this work, the bee algorithm, inspired by the natural foraging behaviour of honey bees, was adapted to find the near optimal solutions of the transportation management system, dynamic multi-zone dispatching. This problem prepares for an uncertainty and changing customers- demand. In striving to remain competitive, transportation system should therefore be flexible in order to cope with the changes of customers- demand in terms of in-bound and outbound goods and technological innovations. To remain higher service level but lower cost management via the minimal imbalance scenario, the rearrangement penalty of the area, in each zone, including time periods are also included. However, the performance of the algorithm depends on the appropriate parameters- setting and need to be determined and analysed before its implementation. BEE parameters are determined through the linear constrained response surface optimisation or LCRSOM and weighted centroid modified simplex methods or WCMSM. Experimental results were analysed in terms of best solutions found so far, mean and standard deviation on the imbalance values including the convergence of the solutions obtained. It was found that the results obtained from the LCRSOM were better than those using the WCMSM. However, the average execution time of experimental run using the LCRSOM was longer than those using the WCMSM. Finally a recommendation of proper level settings of BEE parameters for some selected problem sizes is given as a guideline for future applications.

Keywords: Meta-heuristic, Bee Algorithm, Dynamic Multi-Zone Dispatching, Linear Constrained Response SurfaceOptimisation Method, Weighted Centroid Modified Simplex Method

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Authors: Çiğdem Bakır, Mecit Yüzkat

Abstract:

With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software used in the study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: Preprocessing of the data used, feature detection and classification. We tried to determine the success of our study with different accuracy metrics and the results were presented comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: Decision tree, water quality, water pollution, machine learning.

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Authors: Christian Böning, Henrik Prinzhorn, Eric C. Hund, Malte Stonis

Abstract:

In this article, the flexible job-shop scheduling problem is extended by consideration of energy costs which arise owing to the power peak, and further decision variables such as work in process and throughput time are incorporated into the objective function. This enables a production plan to be simultaneously optimized in respect of the real arising energy and logistics costs. The energy-costs-aware flexible job-shop scheduling problem (EFJSP) which arises is described mathematically, and a memetic algorithm (MA) is presented as a solution. In the MA, the evolutionary process is supplemented with a local search. Furthermore, repair procedures are used in order to rectify any infeasible solutions that have arisen in the evolutionary process. The potential for lowering the real arising costs of a production plan through consideration of energy consumption levels is highlighted.

Keywords: Energy costs, flexible job-shop scheduling, memetic algorithm, power peak.

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Authors: A.K. Baliarsingh, S. Panda, A.K. Mohanty, C. Ardil

Abstract:

This paper presents a systematic approach for designing Unified Power Flow Controller (UPFC) based supplementary damping controllers for damping low frequency oscillations in a single-machine infinite-bus power system. Detailed investigations have been carried out considering the four alternatives UPFC based damping controller namely modulating index of series inverter (mB), modulating index of shunt inverter (mE), phase angle of series inverter (δB ) and phase angle of the shunt inverter (δE ). The design problem of the proposed controllers is formulated as an optimization problem and Real- Coded Genetic Algorithm (RCGA) is employed to optimize damping controller parameters. Simulation results are presented and compared with a conventional method of tuning the damping controller parameters to show the effectiveness and robustness of the proposed design approach.

Keywords: Power System Oscillations, Real-Coded Genetic Algorithm (RCGA), Flexible AC Transmission Systems (FACTS), Unified Power Flow Controller (UPFC), Damping Controller.

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Authors: Witcha Chimphlee, Abdul Hanan Abdullah, Mohd Noor Md Sap, Siriporn Chimphlee, Surat Srinoy

Abstract:

It is important problems to increase the detection rates and reduce false positive rates in Intrusion Detection System (IDS). Although preventative techniques such as access control and authentication attempt to prevent intruders, these can fail, and as a second line of defence, intrusion detection has been introduced. Rare events are events that occur very infrequently, detection of rare events is a common problem in many domains. In this paper we propose an intrusion detection method that combines Rough set and Fuzzy Clustering. Rough set has to decrease the amount of data and get rid of redundancy. Fuzzy c-means clustering allow objects to belong to several clusters simultaneously, with different degrees of membership. Our approach allows us to recognize not only known attacks but also to detect suspicious activity that may be the result of a new, unknown attack. The experimental results on Knowledge Discovery and Data Mining-(KDDCup 1999) Dataset show that the method is efficient and practical for intrusion detection systems.

Keywords: Network and security, intrusion detection, fuzzy cmeans, rough set.

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Authors: Yue Zhao, Jianping Li

Abstract:

This paper covers the present situation and problem of experimental teaching of mathematics specialty in recent years, puts forward and demonstrates experimental teaching methods for different education. From the aspects of content and experimental teaching approach, uses as an example the course “Experiment for Program Designing & Algorithmic Language" and discusses teaching practice and laboratory course work. In addition a series of successful methods and measures are introduced in experimental teaching.

Keywords: Differentiated teaching, experimental teaching, program design and algorithmic language, teaching method.

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Authors: Diana Fajardo, Sebastián Ortiz, Oscar Herrera, Angélica Santis

Abstract:

Currently, in Colombia is arising a problem related to collecting used lubricant oils which are generated by the increment of the vehicle fleet. This situation does not allow a proper disposal of this type of waste, which in turn results in a negative impact on the environment. Therefore, through the comparative analysis of various heuristics, the best solution to the VRP (Vehicle Routing Problem) was selected by comparing costs and times for the collection of used lubricant oils in the city of Pereira, Colombia; since there is no presence of management companies engaged in the direct administration of the collection of this pollutant. To achieve this aim, six proposals of through methods of solution of two phases were discussed. First, the assignment of the group of generator points of the residue was made (previously identified). Proposals one and four of through methods are based on the closeness of points. The proposals two and five are using the scanning method and the proposals three and six are considering the restriction of the capacity of collection vehicle. Subsequently, the routes were developed - in the first three proposals by the Clarke and Wright's savings algorithm and in the following proposals by the Traveling Salesman optimization mathematical model. After applying techniques, a comparative analysis of the results was performed and it was determined which of the proposals presented the most optimal values in terms of the distance, cost and travel time.

Keywords: Heuristics, optimization model, savings algorithm used vehicular oil, VRP.

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