Search results for: Hybrid fault diagnosis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1437

Search results for: Hybrid fault diagnosis

1047 Investigating Feed Mix Problem Approaches: An Overview and Potential Solution

Authors: Rosshairy Abd Rahman, Chooi-Leng Ang, Razamin Ramli

Abstract:

Feed is one of the factors which play an important role in determining a successful development of an aquaculture industry. It is always critical to produce the best aquaculture diet at a minimum cost in order to trim down the operational cost and gain more profit. However, the feed mix problem becomes increasingly difficult since many issues need to be considered simultaneously. Thus, the purpose of this paper is to review the current techniques used by nutritionist and researchers to tackle the issues. Additionally, this paper introduce an enhance algorithm which is deemed suitable to deal with all the issues arise. The proposed technique refers to Hybrid Genetic Algorithm which is expected to obtain the minimum cost diet for farmed animal, while satisfying nutritional requirements. Hybrid GA technique with artificial bee algorithm is expected to reduce the penalty function and provide a better solution for the feed mix problem.

Keywords: Artificial bee algorithm, feed mix problem, hybrid genetic algorithm.

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1046 Hybrid Genetic-Simulated Annealing Approach for Fractal Image Compression

Authors: Y.Chakrapani, K.Soundera Rajan

Abstract:

In this paper a hybrid technique of Genetic Algorithm and Simulated Annealing (HGASA) is applied for Fractal Image Compression (FIC). With the help of this hybrid evolutionary algorithm effort is made to reduce the search complexity of matching between range block and domain block. The concept of Simulated Annealing (SA) is incorporated into Genetic Algorithm (GA) in order to avoid pre-mature convergence of the strings. One of the image compression techniques in the spatial domain is Fractal Image Compression but the main drawback of FIC is that it involves more computational time due to global search. In order to improve the computational time along with acceptable quality of the decoded image, HGASA technique has been proposed. Experimental results show that the proposed HGASA is a better method than GA in terms of PSNR for Fractal image Compression.

Keywords: Fractal Image Compression, Genetic Algorithm, HGASA, Simulated Annealing.

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1045 Fault Detection and Identification of COSMED K4b2 Based On PCA and Neural Network

Authors: Jing Zhou, Steven Su, Aihuang Guo

Abstract:

COSMED K4b2 is a portable electrical device designed to test pulmonary functions. It is ideal for many applications that need the measurement of the cardio-respiratory response either in the field or in the lab is capable with the capability to delivery real time data to a sink node or a PC base station with storing data in the memory at the same time. But the actual sensor outputs and data received may contain some errors, such as impulsive noise which can be related to sensors, low batteries, environment or disturbance in data acquisition process. These abnormal outputs might cause misinterpretations of exercise or living activities to persons being monitored. In our paper we propose an effective and feasible method to detect and identify errors in applications by principal component analysis (PCA) and a back propagation (BP) neural network.

Keywords: BP Neural Network, Exercising Testing, Fault Detection and Identification, Principal Component Analysis.

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1044 A Hybrid Approach for Thread Recommendation in MOOC Forums

Authors: Ahmad. A. Kardan, Amir Narimani, Foozhan Ataiefard

Abstract:

Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC forums by applying social network analysis and association rule mining techniques. Initial results indicate that the proposed recommender system performs comparatively well with regard to limited available data from users' previous posts in the forum.

Keywords: Association rule mining, hybrid recommender system, massive open online courses, MOOCs, social network analysis.

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1043 Hybrid TOA/AOA Schemes for Mobile Location in Cellular Communication Systems

Authors: Chien-Sheng Chen, Szu-Lin Su, Chuan-Der Lu

Abstract:

Wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. When fewer base stations (BSs) may be available for location purposes or the measurements with large errors in non-line-of-sight (NLOS) environments, it is necessary to integrate all available heterogeneous measurements to achieve high location accuracy. This paper illustrates a hybrid proposed schemes that combine time of arrival (TOA) at three BSs and angle of arrival (AOA) information at the serving BS to give a location estimate of the MS. The proposed schemes mitigate the NLOS effect simply by the weighted sum of the intersections between three TOA circles and the AOA line without requiring a priori information about the NLOS error. Simulation results show that the proposed methods can achieve better accuracy when compare with Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP).

Keywords: Time of arrival (TOA), angle of arrival (AOA), non-line-of-sight (NLOS).

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1042 Study of Tribological Behaviour of Al6061/Silicon Carbide/Graphite Hybrid Metal Matrix Composite Using Taguchi's Techniques

Authors: Mohamed Zakaulla, A. R. Anwar Khan

Abstract:

Al6061 alloy base matrix, reinforced with particles of silicon carbide (10 wt %) and Graphite powder (1wt%), known as hybrid composites have been fabricated by liquid metallurgy route (stir casting technique) and optimized at different parameters like applied load, sliding speed and sliding distance by taguchi method. A plan of experiment generated through taguchi technique was used to perform experiments based on L27 orthogonal array. The developed ANOVA and regression equations are used to find the optimum coefficient of friction and wear under the influence of applied load, sliding speed and sliding distance. On the basis of “smaller the best” the dry sliding wear resistance was analysed and finally confirmation tests were carried out to verify the experimental results.

Keywords: Analysis of variance, dry sliding wear, Hybrid composite, orthogonal array, Taguchi technique.

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1041 Real Time Remote Monitoring and Fault Detection in Wind Turbine

Authors: Saad Chakkor, Mostafa Baghouri, Abderrahmane Hajraoui

Abstract:

In new energy development, wind power has boomed. It is due to the proliferation of wind parks and their operation in supplying the national electric grid with low cost and clean resources. Hence, there is an increased need to establish a proactive maintenance for wind turbine machines based on remote control and monitoring. That is necessary with a real-time wireless connection in offshore or inaccessible locations while the wired method has many flaws. The objective of this strategy is to prolong wind turbine lifetime and to increase productivity. The hardware of a remote control and monitoring system for wind turbine parks is designed. It takes advantage of GPRS or Wi-Max wireless module to collect data measurements from different wind machine sensors through IP based multi-hop communication. Computer simulations with Proteus ISIS and OPNET software tools have been conducted to evaluate the performance of the studied system. Study findings show that the designed device is suitable for application in a wind park.

Keywords: Embedded System, Monitoring, Wind Turbine, Faults Diagnosis, TCP/IP Protocol, Real Time, Web.

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1040 Hybrid Heat Pump for Micro Heat Network

Authors: J. M. Counsell, Y. Khalid, M. J. Stewart

Abstract:

Achieving nearly zero carbon heating continues to be identified by UK government analysis as an important feature of any lowest cost pathway to reducing greenhouse gas emissions. Heat currently accounts for 48% of UK energy consumption and approximately one third of UK’s greenhouse gas emissions. Heat Networks are being promoted by UK investment policies as one means of supporting hybrid heat pump based solutions. To this effect the RISE (Renewable Integrated and Sustainable Electric) heating system project is investigating how an all-electric heating sourceshybrid configuration could play a key role in long-term decarbonisation of heat.  For the purposes of this study, hybrid systems are defined as systems combining the technologies of an electric driven air source heat pump, electric powered thermal storage, a thermal vessel and micro-heat network as an integrated system.  This hybrid strategy allows for the system to store up energy during periods of low electricity demand from the national grid, turning it into a dynamic supply of low cost heat which is utilized only when required. Currently a prototype of such a system is being tested in a modern house integrated with advanced controls and sensors. This paper presents the virtual performance analysis of the system and its design for a micro heat network with multiple dwelling units. The results show that the RISE system is controllable and can reduce carbon emissions whilst being competitive in running costs with a conventional gas boiler heating system.

Keywords: Gas boilers, heat pumps, hybrid heating and thermal storage, renewable integrated& sustainable electric.

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1039 An Innovative Wireless Sensor Network Protocol Implementation using a Hybrid FPGA Technology

Authors: Danielle Reichel, Antoine Druilhe, Tuan Dang

Abstract:

Traditional development of wireless sensor network mote is generally based on SoC1 platform. Such method of development faces three main drawbacks: lack of flexibility in terms of development due to low resource and rigid architecture of SoC; low capability of evolution and portability versus performance if specific micro-controller architecture features are used; and the rapid obsolescence of micro-controller comparing to the long lifetime of power plants or any industrial installations. To overcome these drawbacks, we have explored a new approach of development of wireless sensor network mote using a hybrid FPGA technology. The application of such approach is illustrated through the implementation of an innovative wireless sensor network protocol called OCARI.

Keywords: Hybrid FPGA, Embedded system, Mote, flexibility, durability, OCARI protocol, SoC, Wireless Sensor Network

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1038 Performance of Hybrid-MIMO Receiver Scheme in Cognitive Radio Network

Authors: Tanapong Khomyat, Peerapong Uthansakul, Monthippa Uthansakul

Abstract:

In this paper, we evaluate the performance of the Hybrid-MIMO Receiver Scheme (HMRS) in Cognitive Radio network (CR-network). We investigate the efficiency of the proposed scheme which the energy level and user number of primary user are varied according to the characteristic of CR-network. HMRS can allow users to transmit either Space-Time Block Code (STBC) or Spatial-Multiplexing (SM) streams simultaneously by using Successive Interference Cancellation (SIC) and Maximum Likelihood Detection (MLD). From simulation, the results indicate that the interference level effects to the performance of HMRS. Moreover, the exact closed-form capacity of the proposed scheme is derived and compared with STBC scheme.

Keywords: Hybrid-MIMO, Cognitive radio network (CRnetwork), Symbol Error Rate (SER), Successive interference cancellation (SIC), Maximum likelihood detection (MLD).

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1037 A Hybrid Genetic Algorithm for the Sequence Dependent Flow-Shop Scheduling Problem

Authors: Mohammad Mirabi

Abstract:

Flow-shop scheduling problem (FSP) deals with the scheduling of a set of jobs that visit a set of machines in the same order. The FSP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To meet the requirements on time and to minimize the make-span performance of large permutation flow-shop scheduling problems in which there are sequence dependent setup times on each machine, this paper develops one hybrid genetic algorithms (HGA). Proposed HGA apply a modified approach to generate population of initial chromosomes and also use an improved heuristic called the iterated swap procedure to improve initial solutions. Also the author uses three genetic operators to make good new offspring. The results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of solution.

Keywords: Hybrid genetic algorithm, Scheduling, Permutationflow-shop, Sequence dependent

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1036 Operational Modal Analysis Implementation on a Hybrid Composite Plate

Authors: Z. A. C. Saffry, D. L. Majid, N. H. M. Haidzir

Abstract:

In aerospace applications, interactions of airflow with aircraft structures can result in undesirable structural deformations. This structural deformation in turn, can be predicted if the natural modes of the structure are known. This can be achieved through conventional modal testing that requires a known excitation force in order to extract these dynamic properties. This technique can be experimentally complex because of the need for artificial excitation and it is also does not represent actual operational condition. The current work presents part of research work that address the practical implementation of operational modal analysis (OMA) applied to a cantilevered hybrid composite plate employing single contactless sensing system via laser vibrometer. OMA technique extracts the modal parameters based only on the measurements of the dynamic response. The OMA results were verified with impact hammer modal testing and good agreement was obtained.

Keywords: Hybrid Kevlar composite, Laser Vibrometer, modal parameters, Operational Modal Analysis.

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1035 Trajectory Tracking of a Redundant Hybrid Manipulator Using a Switching Control Method

Authors: Atilla Bayram

Abstract:

This paper presents the trajectory tracking control of a spatial redundant hybrid manipulator. This manipulator consists of two parallel manipulators which are a variable geometry truss (VGT) module. In fact, each VGT module with 3-degress of freedom (DOF) is a planar parallel manipulator and their operational planes of these VGT modules are arranged to be orthogonal to each other. Also, the manipulator contains a twist motion part attached to the top of the second VGT module to supply the missing orientation of the endeffector. These three modules constitute totally 7-DOF hybrid (parallel-parallel) redundant spatial manipulator. The forward kinematics equations of this manipulator are obtained, then, according to these equations, the inverse kinematics is solved based on an optimization with the joint limit avoidance. The dynamic equations are formed by using virtual work method. In order to test the performance of the redundant manipulator and the controllers presented, two different desired trajectories are followed by using the computed force control method and a switching control method. The switching control method is combined with the computed force control method and genetic algorithm. In the switching control method, the genetic algorithm is only used for fine tuning in the compensation of the trajectory tracking errors.

Keywords: Computed force control method, genetic algorithm, hybrid manipulator, inverse kinematics of redundant manipulators, variable geometry truss.

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1034 Machine Learning for Aiding Meningitis Diagnosis in Pediatric Patients

Authors: Karina Zaccari, Ernesto Cordeiro Marujo

Abstract:

This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: Machine learning, medical diagnosis, meningitis detection, gradient boosting.

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1033 Structural Parsing of Natural Language Text in Tamil Using Phrase Structure Hybrid Language Model

Authors: Selvam M, Natarajan. A M, Thangarajan R

Abstract:

Parsing is important in Linguistics and Natural Language Processing to understand the syntax and semantics of a natural language grammar. Parsing natural language text is challenging because of the problems like ambiguity and inefficiency. Also the interpretation of natural language text depends on context based techniques. A probabilistic component is essential to resolve ambiguity in both syntax and semantics thereby increasing accuracy and efficiency of the parser. Tamil language has some inherent features which are more challenging. In order to obtain the solutions, lexicalized and statistical approach is to be applied in the parsing with the aid of a language model. Statistical models mainly focus on semantics of the language which are suitable for large vocabulary tasks where as structural methods focus on syntax which models small vocabulary tasks. A statistical language model based on Trigram for Tamil language with medium vocabulary of 5000 words has been built. Though statistical parsing gives better performance through tri-gram probabilities and large vocabulary size, it has some disadvantages like focus on semantics rather than syntax, lack of support in free ordering of words and long term relationship. To overcome the disadvantages a structural component is to be incorporated in statistical language models which leads to the implementation of hybrid language models. This paper has attempted to build phrase structured hybrid language model which resolves above mentioned disadvantages. In the development of hybrid language model, new part of speech tag set for Tamil language has been developed with more than 500 tags which have the wider coverage. A phrase structured Treebank has been developed with 326 Tamil sentences which covers more than 5000 words. A hybrid language model has been trained with the phrase structured Treebank using immediate head parsing technique. Lexicalized and statistical parser which employs this hybrid language model and immediate head parsing technique gives better results than pure grammar and trigram based model.

Keywords: Hybrid Language Model, Immediate Head Parsing, Lexicalized and Statistical Parsing, Natural Language Processing, Parts of Speech, Probabilistic Context Free Grammar, Tamil Language, Tree Bank.

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1032 A Hybrid Recommendation System Based On Association Rules

Authors: Ahmed Mohammed K. Alsalama

Abstract:

Recommendation systems are widely used in e-commerce applications. The engine of a current recommendation system recommends items to a particular user based on user preferences and previous high ratings. Various recommendation schemes such as collaborative filtering and content-based approaches are used to build a recommendation system. Most of current recommendation systems were developed to fit a certain domain such as books, articles, and movies. We propose1 a hybrid framework recommendation system to be applied on two dimensional spaces (User × Item) with a large number of Users and a small number of Items. Moreover, our proposed framework makes use of both favorite and non-favorite items of a particular user. The proposed framework is built upon the integration of association rules mining and the content-based approach. The results of experiments show that our proposed framework can provide accurate recommendations to users.

Keywords: Data Mining, Association Rules, Recommendation Systems, Hybrid Systems.

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1031 Design and Implementation of a Hybrid Fuzzy Controller for a High-Performance Induction

Authors: M. Zerikat, S. Chekroun

Abstract:

This paper proposes an effective algorithm approach to hybrid control systems combining fuzzy logic and conventional control techniques of controlling the speed of induction motor assumed to operate in high-performance drives environment. The introducing of fuzzy logic in the control systems helps to achieve good dynamical response, disturbance rejection and low sensibility to parameter variations and external influences. Some fundamentals of the fuzzy logic control are preliminary illustrated. The developed control algorithm is robust, efficient and simple. It also assures precise trajectory tracking with the prescribed dynamics. Experimental results have shown excellent tracking performance of the proposed control system, and have convincingly demonstrated the validity and the usefulness of the hybrid fuzzy controller in high-performance drives with parameter and load uncertainties. Satisfactory performance was observed for most reference tracks.

Keywords: Fuzzy controller, high-performance, inductionmotor, intelligent control, robustness.

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1030 Intelligent Automatic Generation Control of Two Area Interconnected Power System using Hybrid Neuro Fuzzy Controller

Authors: Sathans, A. Swarup

Abstract:

This paper presents the development and application of an adaptive neuro fuzzy inference system (ANFIS) based intelligent hybrid neuro fuzzy controller for automatic generation control (AGC) of two-area interconnected thermal power system with reheat non linearity. The dynamic response of the system has been studied for 1% step load perturbation in area-1. The performance of the proposed neuro fuzzy controller is compared against conventional proportional-integral (PI) controller, state feedback linear quadratic regulator (LQR) controller and fuzzy gain scheduled proportionalintegral (FGSPI) controller. Comparative analysis demonstrates that the proposed intelligent neuro fuzzy controller is the most effective of all in improving the transients of frequency and tie-line power deviations against small step load disturbances. Simulations have been performed using Matlab®.

Keywords: Automatic generation control, ANFIS, LQR, Hybrid neuro fuzzy controller

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1029 Adaptation of State/Transition-Based Methods for Embedded System Testing

Authors: Abdelaziz Guerrouat, Harald Richter

Abstract:

In this paper test generation methods and appropriate fault models for testing and analysis of embedded systems described as (extended) finite state machines ((E)FSMs) are presented. Compared to simple FSMs, EFSMs specify not only the control flow but also the data flow. Thus, we define a two-level fault model to cover both aspects. The goal of this paper is to reuse well-known FSM-based test generation methods for automation of embedded system testing. These methods have been widely used in testing and validation of protocols and communicating systems. In particular, (E)FSMs-based specification and testing is more advantageous because (E)FSMs support the formal semantic of already standardised formal description techniques (FDTs) despite of their popularity in the design of hardware and software systems.

Keywords: Formal methods, testing and validation, finite state machines, formal description techniques.

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1028 Hybrid Methods for Optimisation of Weights in Spatial Multi-Criteria Evaluation Decision for Fire Risk and Hazard

Authors: I. Yakubu, D. Mireku-Gyimah, D. Asafo-Adjei

Abstract:

The challenge for everyone involved in preserving the ecosystem is to find creative ways to protect and restore the remaining ecosystems while accommodating and enhancing the country social and economic well-being. Frequent fires of anthropogenic origin have been affecting the ecosystems in many countries adversely. Hence adopting ways of decision making such as Multicriteria Decision Making (MCDM) is appropriate since it will enhance the evaluation and analysis of fire risk and hazard of the ecosystem. In this paper, fire risk and hazard data from the West Gonja area of Ghana were used in some of the methods (Analytical Hierarchy Process, Compromise Programming, and Grey Relational Analysis (GRA) for MCDM evaluation and analysis to determine the optimal weight method for fire risk and hazard. Ranking of the land cover types was carried out using; Fire Hazard, Fire Fighting Capacity and Response Risk Criteria. Pairwise comparison under Analytic Hierarchy Process (AHP) was used to determine the weight of the various criteria. Weights for sub-criteria were also obtained by the pairwise comparison method. The results were optimised using GRA and Compromise Programming (CP). The results from each method, hybrid GRA and CP, were compared and it was established that all methods were satisfactory in terms of optimisation of weight. The most optimal method for spatial multicriteria evaluation was the hybrid GRA method. Thus, a hybrid AHP and GRA method is more effective method for ranking alternatives in MCDM than the hybrid AHP and CP method.

Keywords: Compromise programming, grey relational analysis, spatial multi-criteria, weight optimisation.

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1027 An Efficient Cache Replacement Strategy for the Hybrid Cache Consistency Approach

Authors: Aline Zeitunlian, Ramzi A. Haraty

Abstract:

Caching was suggested as a solution for reducing bandwidth utilization and minimizing query latency in mobile environments. Over the years, different caching approaches have been proposed, some relying on the server to broadcast reports periodically informing of the updated data while others allowed the clients to request for the data whenever needed. Until recently a hybrid cache consistency scheme Scalable Asynchronous Cache Consistency Scheme SACCS was proposed, which combined the two different approaches benefits- and is proved to be more efficient and scalable. Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. In this thesis, we proposed a new cache replacement strategy, the Least Unified Value strategy (LUV) to replace the Least Recently Used (LRU) that SACCS was based on. This paper studies the advantages and the drawbacks of the new proposed strategy, comparing it with different categories of cache replacement strategies.

Keywords: Cache consistency, hybrid algorithm, and mobileenvironments

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1026 Variation of CONWIP Systems

Authors: Joshua Prakash, Chin Jeng Feng

Abstract:

The paper describes the workings for four models of CONWIP systems used till date; the basic CONWIP system, the hybrid CONWIP system, the multi-product CONWIP system, and the parallel CONWIP system. The final novel model is introduced in this paper in a general form. These models may be adopted for analysis for both simulation studies and implementation on the shop floor. For each model, input parameters of interest are highlighted and their impacts on several system performance measures are addressed.

Keywords: CONWIP, hybrid CONWIP, mixed CONWIP, multi-product CONWIP.

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1025 Hybrid Algorithm for Frequency Channel Selection in Wi-Fi Networks

Authors: Cesar Hernández, Diego Giral, Ingrid Páez

Abstract:

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

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

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1024 Application of a New Hybrid Optimization Algorithm on Cluster Analysis

Authors: T. Niknam, M. Nayeripour, B.Bahmani Firouzi

Abstract:

Clustering techniques have received attention in many areas including engineering, medicine, biology and data mining. The purpose of clustering is to group together data points, which are close to one another. The K-means algorithm is one of the most widely used techniques for clustering. However, K-means has two shortcomings: dependency on the initial state and convergence to local optima and global solutions of large problems cannot found with reasonable amount of computation effort. In order to overcome local optima problem lots of studies done in clustering. This paper is presented an efficient hybrid evolutionary optimization algorithm based on combining Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), called PSO-ACO, for optimally clustering N object into K clusters. The new PSO-ACO algorithm is tested on several data sets, and its performance is compared with those of ACO, PSO and K-means clustering. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for handing data clustering.

Keywords: Ant Colony Optimization (ACO), Data clustering, Hybrid evolutionary optimization algorithm, K-means clustering, Particle Swarm Optimization (PSO).

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1023 Mining Sequential Patterns Using Hybrid Evolutionary Algorithm

Authors: Mourad Ykhlef, Hebah ElGibreen

Abstract:

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

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

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1022 A Novel Method for Non-Invasive Diagnosis of Hepatitis C Virus Using Electromagnetic Signal Detection: A Multicenter International Study

Authors: Gamal Shiha, Waleed Samir, Zahid Azam, Premashis Kar, Saeed Hamid, Shiv Sarin

Abstract:

A simple, rapid and non-invasive electromagnetic sensor (C-FAST device) was- patented; for diagnosis of HCV RNA. Aim: To test the validity of the device compared to standard HCV PCR. Subjects and Methods: The first phase was done as pilot in Egypt on 79 participants; the second phase was done in five centers: one center from Egypt, two centers from Pakistan and two centers from India (800, 92 and 113 subjects respectively). The third phase was done nationally as multicenter study on (1600) participants for ensuring its representativeness. Results: When compared to PCR technique, C-FAST device revealed sensitivity 95% to 100%, specificity 95.5% to 100%, PPV 89.5% to 100%, NPV 95% to 100% and positive likelihood ratios 21.8% to 38.5%. Conclusion: It is practical evidence that HCV nucleotides emit electromagnetic signals that can be used for its identification. As compared to PCR, C-FAST is an accurate, valid and non-invasive device.

Keywords: C-FAST- a valid and reliable device, Distant cellular interaction, Electromagnetic signal detection, Non-invasive diagnosis of HCV.

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1021 Finite Element Approach to Evaluate Time Dependent Shear Behavior of Connections in Hybrid Steel-PC Girder under Sustained Loading

Authors: Mohammad Najmol Haque, Takeshi Maki, Jun Sasaki

Abstract:

Headed stud shear connections are widely used in the junction or embedded zone of hybrid girder to achieve whole composite action with continuity that can sustain steel-concrete interfacial tensile and shear forces. In Japan, Japan Road Association (JRA) specifications are used for hybrid girder design that utilizes very low level of stud capacity than those of American Institute of Steel Construction (AISC) specifications, Japan Society of Civil Engineers (JSCE) specifications and EURO code. As low design shear strength is considered in design of connections, the time dependent shear behavior due to sustained external loading is not considered, even not fully studied. In this study, a finite element approach was used to evaluate the time dependent shear behavior for headed studs used as connections at the junction. This study clarified, how the sustained loading distinctively impacted on changing the interfacial shear of connections with time which was sensitive to lodging history, positions of flanges, neighboring studs, position of prestress bar and reinforcing bar, concrete strength, etc. and also identified a shear influence area. Stud strength was also confirmed through pushout tests. The outcome obtained from the study may provide an important basis and reference data in designing connections of hybrid girders with enhanced stud capacity with due consideration of their long-term shear behavior.

Keywords: Finite element approach, hybrid girder, headed stud shear connections, sustained loading, time dependent shear behavior.

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1020 Hybrid Control of Networked Multi-Vehicle System Considering Limitation of Communication Range

Authors: Toru Murayama, Akinori Nagano, Zhi-Wei Luo

Abstract:

In this research, we study a control method of a multivehicle system while considering the limitation of communication range for each vehicles. When we control networked vehicles with limitation of communication range, it is important to control the communication network structure of a multi-vehicle system in order to keep the network-s connectivity. From this, we especially aim to control the network structure to the target structure. We formulate the networked multi-vehicle system with some disturbance and the communication constraints as a hybrid dynamical system, and then we study the optimal control problems of the system. It is shown that the system converge to the objective network structure in finite time when the system is controlled by the receding horizon method. Additionally, the optimal control probrems are convertible into the mixed integer problems and these problems are solvable by some branch and bound algorithm.

Keywords: Hybrid system, multi-vehicle system, receding horizon control, topology control.

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1019 Computer Aided Detection on Mammography

Authors: Giovanni Luca Masala

Abstract:

A typical definition of the Computer Aided Diagnosis (CAD), found in literature, can be: A diagnosis made by a radiologist using the output of a computerized scheme for automated image analysis as a diagnostic aid. Often it is possible to find the expression Computer Aided Detection (CAD or CADe): this definition emphasizes the intent of CAD to support rather than substitute the human observer in the analysis of radiographic images. In this article we will illustrate the application of CAD systems and the aim of these definitions. Commercially available CAD systems use computerized algorithms for identifying suspicious regions of interest. In this paper are described the general CAD systems as an expert system constituted of the following components: segmentation / detection, feature extraction, and classification / decision making. As example, in this work is shown the realization of a Computer- Aided Detection system that is able to assist the radiologist in identifying types of mammary tumor lesions. Furthermore this prototype of station uses a GRID configuration to work on a large distributed database of digitized mammographic images.

Keywords: Computer Aided Detection, Computer Aided Diagnosis, mammography, GRID.

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1018 A Novel Architecture for Wavelet based Image Fusion

Authors: Susmitha Vekkot, Pancham Shukla

Abstract:

In this paper, we focus on the fusion of images from different sources using multiresolution wavelet transforms. Based on reviews of popular image fusion techniques used in data analysis, different pixel and energy based methods are experimented. A novel architecture with a hybrid algorithm is proposed which applies pixel based maximum selection rule to low frequency approximations and filter mask based fusion to high frequency details of wavelet decomposition. The key feature of hybrid architecture is the combination of advantages of pixel and region based fusion in a single image which can help the development of sophisticated algorithms enhancing the edges and structural details. A Graphical User Interface is developed for image fusion to make the research outcomes available to the end user. To utilize GUI capabilities for medical, industrial and commercial activities without MATLAB installation, a standalone executable application is also developed using Matlab Compiler Runtime.

Keywords: Filter mask, GUI, hybrid architecture, image fusion, Matlab Compiler Runtime, wavelet transform.

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