Search results for: subspace rotation algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4078

Search results for: subspace rotation algorithm

3958 Left to Right-Right Most Parsing Algorithm with Lookahead

Authors: Jamil Ahmed

Abstract:

Left to Right-Right Most (LR) parsing algorithm is a widely used algorithm of syntax analysis. It is contingent on a parsing table, whereas the parsing tables are extracted from the grammar. The parsing table specifies the actions to be taken during parsing. It requires that the parsing table should have no action conflicts for the same input symbol. This requirement imposes a condition on the class of grammars over which the LR algorithms work. However, there are grammars for which the parsing tables hold action conflicts. In such cases, the algorithm needs a capability of scanning (looking-ahead) next input symbols ahead of the current input symbol. In this paper, a ‘Left to Right’-‘Right Most’ parsing algorithm with lookahead capability is introduced. The 'look-ahead' capability in the LR parsing algorithm is the major contribution of this paper. The practicality of the proposed algorithm is substantiated by the parser implementation of the Context Free Grammar (CFG) of an already proposed programming language 'State Controlled Object Oriented Programming' (SCOOP). SCOOP’s Context Free Grammar has 125 productions and 192 item sets. This algorithm parses SCOOP while the grammar requires to ‘look ahead’ the input symbols due to action conflicts in its parsing table. Proposed LR parsing algorithm with lookahead capability can be viewed as an optimization of ‘Simple Left to Right’-‘Right Most’ (SLR) parsing algorithm.

Keywords: left to right-right most parsing, syntax analysis, bottom-up parsing algorithm

Procedia PDF Downloads 111
3957 Improved Whale Algorithm Based on Information Entropy and Its Application in Truss Structure Optimization Design

Authors: Serges Mendomo Meye, Li Guowei, Shen Zhenzhong, Gan Lei, Xu Liqun

Abstract:

Given the limitations of the original whale optimization algorithm (WAO) in local optimum and low convergence accuracy in truss structure optimization problems, based on the fundamental whale algorithm, an improved whale optimization algorithm (SWAO) based on information entropy is proposed. The information entropy itself is an uncertain measure. It is used to control the range of whale searches in path selection. It can overcome the shortcomings of the basic whale optimization algorithm (WAO) and can improve the global convergence speed of the algorithm. Taking truss structure as the optimization research object, the mathematical model of truss structure optimization is established; the cross-sectional area of truss is taken as the design variable; the objective function is the weight of truss structure; and an improved whale optimization algorithm (SWAO) is used for optimization design, which provides a new idea and means for its application in large and complex engineering structure optimization design.

Keywords: information entropy, structural optimization, truss structure, whale algorithm

Procedia PDF Downloads 234
3956 Parallel Version of Reinhard’s Color Transfer Algorithm

Authors: Abhishek Bhardwaj, Manish Kumar Bajpai

Abstract:

An image with its content and schema of colors presents an effective mode of information sharing and processing. By changing its color schema different visions and prospect are discovered by the users. This phenomenon of color transfer is being used by Social media and other channel of entertainment. Reinhard et al’s algorithm was the first one to solve this problem of color transfer. In this paper, we make this algorithm efficient by introducing domain parallelism among different processors. We also comment on the factors that affect the speedup of this problem. In the end by analyzing the experimental data we claim to propose a novel and efficient parallel Reinhard’s algorithm.

Keywords: Reinhard et al’s algorithm, color transferring, parallelism, speedup

Procedia PDF Downloads 600
3955 A Filtering Algorithm for a Nonlinear State-Space Model

Authors: Abdullah Eqal Al Mazrooei

Abstract:

Kalman filter is a famous algorithm that utilizes to estimate the state in the linear systems. It has numerous applications in technology and science. Since of the most of applications in real life can be described by nonlinear systems. So, Kalman filter does not work with the nonlinear systems because it is suitable to linear systems only. In this work, a nonlinear filtering algorithm is presented which is suitable to use with the special kinds of nonlinear systems. This filter generalizes the Kalman filter. This means that this filter also can be used for the linear systems. Our algorithm depends on a special linearization of the second degree. We introduced the nonlinear algorithm with a bilinear state-space model. A simulation example is presented to illustrate the efficiency of the algorithm.

Keywords: Kalman filter, filtering algorithm, nonlinear systems, state-space model

Procedia PDF Downloads 363
3954 Chemical Reaction Algorithm for Expectation Maximization Clustering

Authors: Li Ni, Pen ManMan, Li KenLi

Abstract:

Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: chemical reaction optimization, expection maimization, initia, objective function clustering

Procedia PDF Downloads 695
3953 An Improved Genetic Algorithm for Traveling Salesman Problem with Precedence Constraint

Authors: M. F. F. Ab Rashid, A. N. Mohd Rose, N. M. Z. Nik Mohamed, W. S. Wan Harun, S. A. Che Ghani

Abstract:

Traveling salesman problem with precedence constraint (TSPPC) is one of the most complex problems in combinatorial optimization. The existing algorithms to solve TSPPC cost large computational time to find the optimal solution. The purpose of this paper is to present an efficient genetic algorithm that guarantees optimal solution with less number of generations and iterations time. Unlike the existing algorithm that generates priority factor as chromosome, the proposed algorithm directly generates sequence of solution as chromosome. As a result, the proposed algorithm is capable of generating optimal solution with smaller number of generations and iteration time compare to existing algorithm.

Keywords: traveling salesman problem, sequencing, genetic algorithm, precedence constraint

Procedia PDF Downloads 546
3952 Process Parameter Study on Friction Push Plug Welding of AA6061 Alloy

Authors: H. Li, W. Qin, Ben Ye

Abstract:

Friction Push Plug Welding (FPPW) is a solid phase welding suitable for repairing defective welds and filling self-reacting weld keyholes in Friction Stir Welds. In FPPW process, a tapered shaped plug is rotated at high speed and forced into a tapered hole in the substrate. The plug and substrate metal is softened by the increasing temperature generated by friction and material plastic deformation. This paper aims to investigate the effect of process parameters on the quality of the weld. Orthogonal design methods were employed to reduce the amount of experiment. Three values were selected for each process parameter, rotation speed (1500r/min, 2000r/min, 2500r/min), plunge depth (2mm, 3mm, 4mm) and plunge speed (60mm/min, 90mm/min, 120r/min). AA6061aluminum alloy plug and substrate plate was used in the experiment. In a trial test with the plunge depth of 1mm, a noticeable defect appeared due to the short plunge time and insufficient temperature. From the recorded temperature profiles, it was found that the peak temperature increased with the increase of the rotation speed, plunge speed and plunge depth. In the initial stage, the plunge speed was the main factor affecting heat generation, while in the steady state welding stage, the rotation speed played a more important role. The FPPW weld defect includes flash and incomplete penetration in the upper, middle and bottom interface with the substrate. To obtain defect free weld, the higher rotation speed and proper plunge depth were recommended.

Keywords: friction push plug welding, process parameter, weld defect, orthogonal design

Procedia PDF Downloads 136
3951 Vortex Flows under Effects of Buoyant-Thermocapillary Convection

Authors: Malika Imoula, Rachid Saci, Renee Gatignol

Abstract:

A numerical investigation is carried out to analyze vortex flows in a free surface cylinder, driven by the independent rotation and differentially heated boundaries. As a basic uncontrolled isothermal flow, we consider configurations which exhibit steady axisymmetric toroidal type vortices which occur at the free surface; under given rates of the bottom disk uniform rotation and for selected aspect ratios of the enclosure. In the isothermal case, we show that sidewall differential rotation constitutes an effective kinematic means of flow control: the reverse flow regions may be suppressed under very weak co-rotation rates, while an enhancement of the vortex patterns is remarked under weak counter-rotation. However, in this latter case, high rates of counter-rotation reduce considerably the strength of the meridian flow and cause its confinement to a narrow layer on the bottom disk, while the remaining bulk flow is diffusion dominated and controlled by the sidewall rotation. The main control parameters in this case are the rotational Reynolds number, the cavity aspect ratio and the rotation rate ratio defined. Then, the study proceeded to consider the sensitivity of the vortex pattern, within the Boussinesq approximation, to a small temperature gradient set between the ambient fluid and an axial thin rod mounted on the cavity axis. Two additional parameters are introduced; namely, the Richardson number Ri and the Marangoni number Ma (or the thermocapillary Reynolds number). Results revealed that reducing the rod length induces the formation of on-axis bubbles instead of toroidal structures. Besides, the stagnation characteristics are significantly altered under the combined effects of buoyant-thermocapillary convection. Buoyancy, induced under sufficiently high Ri, was shown to predominate over the thermocapillay motion; causing the enhancement (suppression) of breakdown when the rod is warmer (cooler) than the ambient fluid. However, over small ranges of Ri, the sensitivity of the flow to surface tension gradients was clearly evidenced and results showed its full control over the occurrence and location of breakdown. In particular, detailed timewise evolution of the flow indicated that weak thermocapillary motion was sufficient to prevent the formation of toroidal patterns. These latter detach from the surface and undergo considerable size reduction while moving towards the bulk flow before vanishing. Further calculations revealed that the pattern reappears with increasing time as steady bubble type on the rod. However, in the absence of the central rod and also in the case of small rod length l, the flow evolved into steady state without any breakdown.

Keywords: buoyancy, cylinder, surface tension, toroidal vortex

Procedia PDF Downloads 345
3950 Improved FP-Growth Algorithm with Multiple Minimum Supports Using Maximum Constraints

Authors: Elsayeda M. Elgaml, Dina M. Ibrahim, Elsayed A. Sallam

Abstract:

Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FP-growth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.

Keywords: association rules, FP-growth, multiple minimum supports, Weka tool

Procedia PDF Downloads 469
3949 An Improved Many Worlds Quantum Genetic Algorithm

Authors: Li Dan, Zhao Junsuo, Zhang Wenjun

Abstract:

Aiming at the shortcomings of the Quantum Genetic Algorithm such as the multimodal function optimization problems easily falling into the local optimum, and vulnerable to premature convergence due to no closely relationship between individuals, the paper presents an Improved Many Worlds Quantum Genetic Algorithm (IMWQGA). The paper using the concept of Many Worlds; using the derivative way of parallel worlds’ parallel evolution; putting forward the thought which updating the population according to the main body; adopting the transition methods such as parallel transition, backtracking, travel forth. In addition, the algorithm in the paper also proposes the quantum training operator and the combinatorial optimization operator as new operators of quantum genetic algorithm.

Keywords: quantum genetic algorithm, many worlds, quantum training operator, combinatorial optimization operator

Procedia PDF Downloads 725
3948 Multi-Subpopulation Genetic Algorithm with Estimation of Distribution Algorithm for Textile Batch Dyeing Scheduling Problem

Authors: Nhat-To Huynh, Chen-Fu Chien

Abstract:

Textile batch dyeing scheduling problem is complicated which includes batch formation, batch assignment on machines, batch sequencing with sequence-dependent setup time. Most manufacturers schedule their orders manually that are time consuming and inefficient. More power methods are needed to improve the solution. Motivated by the real needs, this study aims to propose approaches in which genetic algorithm is developed with multi-subpopulation and hybridised with estimation of distribution algorithm to solve the constructed problem for minimising the makespan. A heuristic algorithm is designed and embedded into the proposed algorithms to improve the ability to get out of the local optima. In addition, an empirical study is conducted in a textile company in Taiwan to validate the proposed approaches. The results have showed that proposed approaches are more efficient than simulated annealing algorithm.

Keywords: estimation of distribution algorithm, genetic algorithm, multi-subpopulation, scheduling, textile dyeing

Procedia PDF Downloads 290
3947 A Rapid Code Acquisition Scheme in OOC-Based CDMA Systems

Authors: Keunhong Chae, Seokho Yoon

Abstract:

We propose a code acquisition scheme called improved multiple-shift (IMS) for optical code division multiple access systems, where the optical orthogonal code is used instead of the pseudo noise code. Although the IMS algorithm has a similar process to that of the conventional MS algorithm, it has a better code acquisition performance than the conventional MS algorithm. We analyze the code acquisition performance of the IMS algorithm and compare the code acquisition performances of the MS and the IMS algorithms in single-user and multi-user environments.

Keywords: code acquisition, optical CDMA, optical orthogonal code, serial algorithm

Procedia PDF Downloads 528
3946 Efficient Heuristic Algorithm to Speed Up Graphcut in Gpu for Image Stitching

Authors: Tai Nguyen, Minh Bui, Huong Ninh, Tu Nguyen, Hai Tran

Abstract:

GraphCut algorithm has been widely utilized to solve various types of computer vision problems. Its expensive computational cost encouraged many researchers to improve the speed of the algorithm. Recent works proposed schemes that work on parallel computing platforms such as CUDA. However, the problem of low convergence speed prevents the usage of GraphCut for real time applications. In this paper, we propose global suppression heuristic to boost the conver-gence process of the algorithm. A parallel implementation of GraphCut algorithm on CUDA designed for the image stitching problem is introduced. Our method achieves up to 3× time boost on the graph of size 80 × 480 compared to the best sequential GraphCut algorithm while achieving satisfactory stitched images, suitable for panorama applications. Our source code will be soon available for further research.

Keywords: CUDA, graph cut, image stitching, texture synthesis, maxflow/mincut algorithm

Procedia PDF Downloads 116
3945 Finite Elemental Simulation of the Combined Process of Asymmetric Rolling and Plastic Bending

Authors: A. Pesin, D. Pustovoytov, M. Sverdlik

Abstract:

Traditionally, the need in items represents a large body of rotation (e.g. shrouds of various process units: a converter, a mixer, a scrubber, a steel ladle and etc.) is satisfied by using them at engineering enterprises. At these enterprises large parts of bodies of rotation are made on stamping units or bending and forming machines. In Nosov Magnitogorsk State Technical University in alliance with JSC "Magnitogorsk Metal and Steel Works" there was suggested and implemented the technology for producing such items based on a combination of asymmetric rolling processes and plastic bending under conditions of the plate mill. In this paper, based on finite elemental mathematical simulation in technology of a combined process of asymmetric rolling and bending plastic has been improved. It is shown that for the same curvature along the entire length of the metal sheet it is necessary to introduce additional asymmetry speed when rolling front end and tape trailer. Production of large bodies of rotation at mill 4500 JSC "Magnitogorsk Metal and Steel Works" showed good convergence of theoretical and experimental values of the curvature of the metal. Economic effect obtained more than 1.0 million dollars.

Keywords: asymmetric rolling, plastic bending, combined process, FEM

Procedia PDF Downloads 307
3944 Travel Planning in Public Transport Networks Applying the Algorithm A* for Metropolitan District of Quito

Authors: M. Fernanda Salgado, Alfonso Tierra, Wilbert Aguilar

Abstract:

The present project consists in applying the informed search algorithm A star (A*) to solve traveler problems, applying it by urban public transportation routes. The digitization of the information allowed to identify 26% of the total of routes that are registered within the Metropolitan District of Quito. For the validation of this information, data were taken in field on the travel times and the difference with respect to the times estimated by the program, resulting in that the difference between them was not greater than 2:20 minutes. We validate A* algorithm with the Dijkstra algorithm, comparing nodes vectors based on the public transport stops, the validation was established through the student t-test hypothesis. Then we verified that the times estimated by the program using the A* algorithm are similar to those registered on field. Furthermore, we review the performance of the algorithm generating iterations in both algorithms. Finally, with these iterations, a hypothesis test was carried out again with student t-test where it was concluded that the iterations of the base algorithm Dijsktra are greater than those generated by the algorithm A*.

Keywords: algorithm A*, graph, mobility, public transport, travel planning, routes

Procedia PDF Downloads 224
3943 Assessment of Memetic and Genetic Algorithm for a Flexible Integrated Logistics Network

Authors: E. Behmanesh, J. Pannek

Abstract:

The distribution-allocation problem is known as one of the most comprehensive strategic decision. In real-world cases, it is impossible to solve a distribution-allocation problem in traditional ways with acceptable time. Hence researchers develop efficient non-traditional techniques for the large-term operation of the whole supply chain. These techniques provide near-optimal solutions particularly for large scales test problems. This paper, presents an integrated supply chain model which is flexible in the delivery path. As the solution methodology, we apply a memetic algorithm with a novelty in population presentation. To illustrate the performance of the proposed memetic algorithm, LINGO optimization software serves as a comparison basis for small size problems. In large size cases that we are dealing with in the real world, the Genetic algorithm as the second metaheuristic algorithm is considered to compare the results and show the efficiency of the memetic algorithm.

Keywords: integrated logistics network, flexible path, memetic algorithm, genetic algorithm

Procedia PDF Downloads 366
3942 A Speeded up Robust Scale-Invariant Feature Transform Currency Recognition Algorithm

Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

Abstract:

All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.

Keywords: currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features

Procedia PDF Downloads 224
3941 Features Reduction Using Bat Algorithm for Identification and Recognition of Parkinson Disease

Authors: P. Shrivastava, A. Shukla, K. Verma, S. Rungta

Abstract:

Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset.

Keywords: parkinson, gait, feature selection, bat algorithm

Procedia PDF Downloads 529
3940 Selecting the Best RBF Neural Network Using PSO Algorithm for ECG Signal Prediction

Authors: Najmeh Mohsenifar, Narjes Mohsenifar, Abbas Kargar

Abstract:

In this paper, has been presented a stable method for predicting the ECG signals through the RBF neural networks, by the PSO algorithm. In spite of quasi-periodic ECG signal from a healthy person, there are distortions in electro cardiographic data for a patient. Therefore, there is no precise mathematical model for prediction. Here, we have exploited neural networks that are capable of complicated nonlinear mapping. Although the architecture and spread of RBF networks are usually selected through trial and error, the PSO algorithm has been used for choosing the best neural network. In this way, 2 second of a recorded ECG signal is employed to predict duration of 20 second in advance. Our simulations show that PSO algorithm can find the RBF neural network with minimum MSE and the accuracy of the predicted ECG signal is 97 %.

Keywords: electrocardiogram, RBF artificial neural network, PSO algorithm, predict, accuracy

Procedia PDF Downloads 611
3939 Application of a New Efficient Normal Parameter Reduction Algorithm of Soft Sets in Online Shopping

Authors: Xiuqin Ma, Hongwu Qin

Abstract:

A new efficient normal parameter reduction algorithm of soft set in decision making was proposed. However, up to the present, few documents have focused on real-life applications of this algorithm. Accordingly, we apply a New Efficient Normal Parameter Reduction algorithm into real-life datasets of online shopping, such as Blackberry Mobile Phone Dataset. Experimental results show that this algorithm is not only suitable but feasible for dealing with the online shopping.

Keywords: soft sets, parameter reduction, normal parameter reduction, online shopping

Procedia PDF Downloads 497
3938 Research of the Rotation Magnetic Field Current Driven Effect on Pulsed Plasmoid Acceleration of Electric Propulsion

Authors: X. F. Sun, X. D. Wen, L. J. Liu, C. C. Wu, Y. H. Jia

Abstract:

The field reversed closed magnetic field configuration plasmoid has a potential for large thrust and high power propulsion missions such as deep space exploration due to its high plasma density and larger azimuthal current, which will be a most competitive program for the next generation electric propulsion technology. Moreover, without the electrodes, it also has a long lifetime. Thus, the research on this electric propulsion technology is quite necessary. The plasmoid will be formatted and accelerated by applying a rotation magnetic field (RMF) method. And, the essence of this technology lies on the generation of the azimuthal electron currents driven by RMF. Therefore, the effect of RMF current on the plasmoid acceleration efficiency is a concerned problem. In the paper, the influences of the penetration process of RMF in plasma, the relations of frequency and amplitude of input RF power with current strength and the RMF antenna configuration on the plasmoid acceleration efficiency will be given by a two-fluid numerical simulation method. The results show that the radio-frequency and input power have remarkable influence on the formation and acceleration of plasmoid. These results will provide useful advice for the development, and optimized designing of field reversed configuration plasmoid thruster.

Keywords: rotation magnetic field, current driven, plasma penetration, electric propulsion

Procedia PDF Downloads 103
3937 Numerical Study on the Effect of Spudcan Penetration on the Jacket Platform

Authors: Xiangming Ge, Bing Pan, Wei He, Hao Chen, Yong Zhou, Jiayao Wu, Weijiang Chu

Abstract:

How the extraction and penetration of spudcan affect the performance of the adjacent pile foundation supporting the jacket platform was studied in the program FLAC3D depending on a wind farm project in Bohai sea. The simulations were conducted at the end of the spudcan penetration, which induced a pockmark in the seabed. The effects of the distance between the pile foundation and the pockmark were studied. The displacement at the mudline arose when the pockmark was closer. The bearing capacity of this jacket platform with deep pile foundations has been less influenced by the process of spudcan penetration, which can induce severe stresses on the pile foundation. The induced rotation was also satisfied with the rotation-controlling criteria.

Keywords: offshore foundation, pile-soil interaction, spudcan penetration, FLAC3D

Procedia PDF Downloads 198
3936 Researches Concerning Photons as Corpuscles with Mass and Negative Electrostatic Charge

Authors: Ioan Rusu

Abstract:

Let us consider that the entire universe is composed of a single hydrogen atom within which the electron is moving around the proton. In this case, according to classical theories of physics, radiation and photons, respectively, should be absorbed by the electron. Depending on the number of photons absorbed, the electron radius of rotation around the proton is established. Until now, the principle of photon absorption by electrons and the electron transition to a new energy level, namely to a higher radius of rotation around the proton, is not clarified in physics. This paper aims to demonstrate that photons have mass and negative electrostatic charge similar to electrons but infinitely smaller. The experiments which demonstrate this theory are simple: thermal expansion, photoelectric effect and thermonuclear reaction.

Keywords: electrostatic, electron, photon, proton, radiation

Procedia PDF Downloads 383
3935 Discretization of Cuckoo Optimization Algorithm for Solving Quadratic Assignment Problems

Authors: Elham Kazemi

Abstract:

Quadratic Assignment Problem (QAP) is one the combinatorial optimization problems about which research has been done in many companies for allocating some facilities to some locations. The issue of particular importance in this process is the costs of this allocation and the attempt in this problem is to minimize this group of costs. Since the QAP’s are from NP-hard problem, they cannot be solved by exact solution methods. Cuckoo Optimization Algorithm is a Meta-heuristicmethod which has higher capability to find the global optimal points. It is an algorithm which is basically raised to search a continuous space. The Quadratic Assignment Problem is the issue which can be solved in the discrete space, thus the standard arithmetic operators of Cuckoo Optimization Algorithm need to be redefined on the discrete space in order to apply the Cuckoo Optimization Algorithm on the discrete searching space. This paper represents the way of discretizing the Cuckoo optimization algorithm for solving the quadratic assignment problem.

Keywords: Quadratic Assignment Problem (QAP), Discrete Cuckoo Optimization Algorithm (DCOA), meta-heuristic algorithms, optimization algorithms

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3934 Constant Factor Approximation Algorithm for p-Median Network Design Problem with Multiple Cable Types

Authors: Chaghoub Soraya, Zhang Xiaoyan

Abstract:

This research presents the first constant approximation algorithm to the p-median network design problem with multiple cable types. This problem was addressed with a single cable type and there is a bifactor approximation algorithm for the problem. To the best of our knowledge, the algorithm proposed in this paper is the first constant approximation algorithm for the p-median network design with multiple cable types. The addressed problem is a combination of two well studied problems which are p-median problem and network design problem. The introduced algorithm is a random sampling approximation algorithm of constant factor which is conceived by using some random sampling techniques form the literature. It is based on a redistribution Lemma from the literature and a steiner tree problem as a subproblem. This algorithm is simple, and it relies on the notions of random sampling and probability. The proposed approach gives an approximation solution with one constant ratio without violating any of the constraints, in contrast to the one proposed in the literature. This paper provides a (21 + 2)-approximation algorithm for the p-median network design problem with multiple cable types using random sampling techniques.

Keywords: approximation algorithms, buy-at-bulk, combinatorial optimization, network design, p-median

Procedia PDF Downloads 186
3933 A Minimum Spanning Tree-Based Method for Initializing the K-Means Clustering Algorithm

Authors: J. Yang, Y. Ma, X. Zhang, S. Li, Y. Zhang

Abstract:

The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.

Keywords: degree, initial cluster center, k-means, minimum spanning tree

Procedia PDF Downloads 397
3932 The Effect of Modified Posterior Shoulder Stretching Exercises on Posterior Shoulder Tightness, Shoulder Pain, and Dysfunction in Patients with Subacromial Impingement

Authors: Ozge Tahran, Sevgi Sevi Yesilyaprak

Abstract:

Objective: The aim of the study was to investigate the effect of the Wilk’s modified two different stretching exercises on posterior shoulder tightness, pain, and dysfunction in patients with subacromial impingement syndrome (SIS). Method: This study was carried out on 67 patients who have more than 15° difference in shoulder internal rotation range of motion between two sides and had been diagnosed as SIS. Before treatment, all patients were randomly assigned into three groups. Standard physiotherapy programme was applied to the Group 3 (n=23), standard physiotherapy program with Wilk’s modified cross-body stretching exercises were applied to Group 1 (n=22), and standard physiotherapy program with Wilk’s modified sleeper stretching exercises were applied to Group 2 (n= 23). All the patients received 20 sessions of physiotherapy during 4 weeks, 5 days in a week by a physiotherapist. The patients continued their exercises at home at the weekends. Pain severity, shoulder rotation range of motion, posterior shoulder tightness, upper extremity functionality with Constant and Murley Score (CMS) and disability level with The Disabilities of the Arm, Shoulder and Hand Score (QuickDASH) were evaluated before and after physiotherapy programme. Results: Before treatment, demographic and anthropometric characteristics were similar in groups and there was no statistical difference (p > 0.05). It was determined that pain severity decreased, shoulder rotation range of motion, posterior shoulder tightness, upper extremity functionality, and disability were improved after physiotherapy in both groups (p < 0.05). Group 1 and 2 had better results in terms of reduction of pain severity during activity, increase in shoulder rotation range of motion, posterior shoulder mobility and upper extremity functionality and improvement in upper extremity disability, compared to Group 3 (p < 0.05). Conclusion: Modified posterior shoulder stretching exercises in addition to standard physiotherapy programme is more effective for reduction of pain during activity, to improve shoulder rotation range of motion, posterior shoulder mobility, and upper extremity functionality in patients with SIS compared to standard physiotherapy programme alone.

Keywords: modified posterior shoulder stretching exercises, posterior shoulder tightness, shoulder complex, subacromial impingement syndrome

Procedia PDF Downloads 165
3931 An Optimized Association Rule Mining Algorithm

Authors: Archana Singh, Jyoti Agarwal, Ajay Rana

Abstract:

Data Mining is an efficient technology to discover patterns in large databases. Association Rule Mining techniques are used to find the correlation between the various item sets in a database, and this co-relation between various item sets are used in decision making and pattern analysis. In recent years, the problem of finding association rules from large datasets has been proposed by many researchers. Various research papers on association rule mining (ARM) are studied and analyzed first to understand the existing algorithms. Apriori algorithm is the basic ARM algorithm, but it requires so many database scans. In DIC algorithm, less amount of database scan is needed but complex data structure lattice is used. The main focus of this paper is to propose a new optimized algorithm (Friendly Algorithm) and compare its performance with the existing algorithms A data set is used to find out frequent itemsets and association rules with the help of existing and proposed (Friendly Algorithm) and it has been observed that the proposed algorithm also finds all the frequent itemsets and essential association rules from databases as compared to existing algorithms in less amount of database scan. In the proposed algorithm, an optimized data structure is used i.e. Graph and Adjacency Matrix.

Keywords: association rules, data mining, dynamic item set counting, FP-growth, friendly algorithm, graph

Procedia PDF Downloads 407
3930 Improved K-Means Clustering Algorithm Using RHadoop with Combiner

Authors: Ji Eun Shin, Dong Hoon Lim

Abstract:

Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

Procedia PDF Downloads 418
3929 Finite Element Study of Coke Shape Deep Beam to Column Moment Connection Subjected to Cyclic Loading

Authors: Robel Wondimu Alemayehu, Sihwa Jung, Manwoo Park, Young K. Ju

Abstract:

Following the aftermath of the 1994 Northridge earthquake, intensive research on beam to column connections is conducted, leading to the current design basis. The current design codes require the use of either a prequalified connection or a connection that passes the requirements of large-scale cyclic qualification test prior to use in intermediate or special moment frames. The second alternative is expensive both in terms of money and time. On the other hand, the maximum beam depth in most of the prequalified connections is limited to 900mm due to the reduced rotation capacity of deeper beams. However, for long span beams the need to use deeper beams may arise. In this study, a beam to column connection detail suitable for deep beams is presented. The connection detail comprises of thicker-tapered beam flange adjacent to the beam to column connection. Within the thicker-tapered flange region, two reduced beam sections are provided with the objective of forming two plastic hinges within the tapered-thicker flange region. In addition, the length, width, and thickness of the tapered-thicker flange region are proportioned in such a way that a third plastic hinge forms at the end of the tapered-thicker flange region. As a result, the total rotation demand is distributed over three plastic zones. Making it suitable for deeper beams that have lower rotation capacity at one plastic hinge. The effectiveness of this connection detail is studied through finite element analysis. For the study, a beam that has a depth of 1200mm is used. Additionally, comparison with welded unreinforced flange-welded web (WUF-W) moment connection and reduced beam section moment connection is made. The results show that the rotation capacity of a WUF-W moment connection is increased from 2.0% to 2.2% by applying the proposed moment connection detail. Furthermore, the maximum moment capacity, energy dissipation capacity and stiffness of the WUF-W moment connection is increased up to 58%, 49%, and 32% respectively. In contrast, applying the reduced beam section detail to the same WUF-W moment connection reduced the rotation capacity from 2.0% to 1.50% plus the maximum moment capacity and stiffness of the connection is reduced by 22% and 6% respectively. The proposed connection develops three plastic hinge regions as intended and it shows improved performance compared to both WUF-W moment connection and reduced beam section moment connection. Moreover, the achieved rotation capacity satisfies the minimum required for use in intermediate moment frames.

Keywords: connections, finite element analysis, seismic design, steel intermediate moment frame

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