Search results for: Fuzzy logic model.

Authors: Mohammad Najafi Nobar, Bahareh Pourmehr, Mehdi Hajimirarab

Abstract:

One of the main processes of supply chain management is supplier selection process which its accurate implementation can dramatically increase company competitiveness. In presented article model developed based on the features of second tiers suppliers and four scenarios are predicted in order to help the decision maker (DM) in making up his/her mind. In addition two tiers of suppliers have been considered as a chain of suppliers. Then the proposed approach is solved by a method combined of concepts of fuzzy set theory (FST) and linear programming (LP) which has been nourished by real data extracted from an engineering design and supplying parts company. At the end results reveal the high importance of considering second tier suppliers features as criteria for selecting the best supplier.

Keywords: Supply Chain Management (SCM), SupplierSelection, Second Tier Supplier, Scenario Planning, Green Factor, Linear Programming, Fuzzy Set Theory

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Authors: S. Logeswari, K. Premalatha

Abstract:

Search is the most obvious application of information retrieval. The variety of widely obtainable biomedical data is enormous and is expanding fast. This expansion makes the existing techniques are not enough to extract the most interesting patterns from the collection as per the user requirement. Recent researches are concentrating more on semantic based searching than the traditional term based searches. Algorithms for semantic searches are implemented based on the relations exist between the words of the documents. Ontologies are used as domain knowledge for identifying the semantic relations as well as to structure the data for effective information retrieval. Annotation of data with concepts of ontology is one of the wide-ranging practices for clustering the documents. In this paper, indexing based on concept and annotation are proposed for clustering the biomedical documents. Fuzzy c-means (FCM) clustering algorithm is used to cluster the documents. The performances of the proposed methods are analyzed with traditional term based clustering for PubMed articles in five different diseases communities. The experimental results show that the proposed methods outperform the term based fuzzy clustering.

Keywords: MeSH Ontology, Concept Indexing, Annotation, semantic relations, Fuzzy c-means.

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Authors: T. Benmiloud, A. Omari

Abstract:

This paper presents a new technique of compensation of the effect of variation parameters in the direct field oriented control of induction motor. The proposed method uses an adaptive tuning of the value of synchronous speed to obtain the robustness for the field oriented control. We show that this adaptive tuning allows having robustness for direct field oriented control to changes in rotor resistance, load torque and rotational speed. The effectiveness of the proposed control scheme is verified by numerical simulations. The numerical validation results of the proposed scheme have presented good performances compared to the usual direct-field oriented control.

Keywords: Induction motor, direct field-oriented control, compensation of variation parameters, fuzzy logic controller.

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Authors: Padmanabhan Balasubramanian, Ryuta Arisaka

Abstract:

Factoring Boolean functions is one of the basic operations in algorithmic logic synthesis. A novel algebraic factorization heuristic for single-output combinatorial logic functions is presented in this paper and is developed based on the set theory paradigm. The impact of factoring is analyzed mainly from a low power design perspective for standard cell based digital designs in this paper. The physical implementation of a number of MCNC/IWLS combinational benchmark functions and sub-functions are compared before and after factoring, based on a simple technology mapping procedure utilizing only standard gate primitives (readily available as standard cells in a technology library) and not cells corresponding to optimized complex logic. The power results were obtained at the gate-level by means of an industry-standard power analysis tool from Synopsys, targeting a 130nm (0.13μm) UMC CMOS library, for the typical case. The wire-loads were inserted automatically and the simulations were performed with maximum input activity. The gate-level simulations demonstrate the advantage of the proposed factoring technique in comparison with other existing methods from a low power perspective, for arbitrary examples. Though the benchmarks experimentation reports mixed results, the mean savings in total power and dynamic power for the factored solution over a non-factored solution were 6.11% and 5.85% respectively. In terms of leakage power, the average savings for the factored forms was significant to the tune of 23.48%. The factored solution is expected to better its non-factored counterpart in terms of the power-delay product as it is well-known that factoring, in general, yields a delay-efficient multi-level solution.

Keywords: Factorization, Set theory, Logic function, Standardcell based design, Low power.

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Authors: K. Muthukannan, P. Latha

Abstract:

In addition to environmental parameters like rain, temperature diseases on crop is a major factor which affects production quality & quantity of crop yield. Hence disease management is a key issue in agriculture. For the management of disease, it needs to be detected at early stage. So, treat it properly & control spread of the disease. Now a day, it is possible to use the images of diseased leaf to detect the type of disease by using image processing techniques. This can be achieved by extracting features from the images which can be further used with classification algorithms or content based image retrieval systems. In this paper, color image is used to extract the features such as mean and standard deviation after the process of region cropping. The selected features are taken from the cropped image with different image size samples. Then, the extracted features are taken in to the account for classification using Fuzzy Inference System (FIS).

Keywords: Image Cropping, Classification, Color, Fuzzy Rule, Feature Extraction.

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Authors: P. Cermak

Abstract:

This paper shows possibility of extraction Social, Group and Individual Mind from Multiple Agents Rule Bases. Types those Rule bases are selected as two fuzzy systems, namely Mambdani and Takagi-Sugeno fuzzy system. Their rule bases are describing (modeling) agent behavior. Modifying of agent behavior in the time varying environment will be provided by learning fuzzyneural networks and optimization of their parameters with using genetic algorithms in development system FUZNET. Finally, extraction Social, Group and Individual Mind from Multiple Agents Rule Bases are provided by Cognitive analysis and Matching criterion.

Keywords: Mind, Multi-agent system, Cognitive analysis, Fuzzy system, Neural network, Genetic algorithm, Rule base.

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Authors: J.L. Castro, K. Benghazi, M.V. Hurtado, M. Navarro, J.M. Zurita

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Nowadays, quick technological changes force companies to develop innovative products in an increasingly competitive environment. Therefore, how to enhance the time of new product development is very important. This design problem often lacks the exact formula for getting it, and highly depends upon human designers- past experiences. For these reasons, in this work, a Casebased reasoning (CBR) system to assist in new product development is proposed. When a case is recovered from the case base, the system will take into account not only the attribute-s specific value and how important it is. It will also take into account if the attribute has a positive influence over the product development. Hence the manufacturing time will be improved. This information will be introduced as a new concept called “adaptability". An application to this method for hearing instrument new design illustrates the proposed approach.

Keywords: Case based reasoning, Fuzzy logic, New product development, Retrieval stage, Similarity.

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Authors: Yan Xu, Toshihiro Nishimura

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Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edges detected by intensity, is used to extract speckle texture. And then, a spatial FCM clustering is applied on the image feature space for segmentation. In the experiments with simulated and clinical ultrasound images, the spatial FCM clustering with both intensity and texture information gets more accurate results than the conventional FCM or spatial FCM without texture information.

Keywords: fuzzy c-means, spatial information, structure tensor, ultrasound image segmentation

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Authors: Yang Luo, Beibei Wang

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In this paper, we present a design methodology of lightweight register transfer level (RTL) hardware threat implemented based on a MAX II FPGA platform. The dynamic power consumed by the toggling of the various bit of registers as well as the dynamic power consumed per unit of logic circuits were analyzed. The hardware threat was designed taking advantage of the differences in dynamic power consumed per unit of logic circuits to hide the transfer information. The experiment result shows that the register hardware threat was successfully implemented by using different dynamic power consumed per unit of logic circuits to hide the key information of DES encryption module. It needs more than 100000 sample curves to reduce the background noise by comparing the sample space when it completely meets the time alignment requirement. In additional, an external trigger signal is playing a very important role to detect the hardware threat in this experiment.

Keywords: Side-channel analysis, hardware threat, register transfer level, dynamic power.

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Authors: Chidentree Treesatayapun

Abstract:

A direct adaptive controller for a class of unknown nonlinear discrete-time systems is presented in this article. The proposed controller is constructed by fuzzy rules emulated network (FREN). With its simple structure, the human knowledge about the plant is transferred to be if-then rules for setting the network. These adjustable parameters inside FREN are tuned by the learning mechanism with time varying step size or learning rate. The variation of learning rate is introduced by main theorem to improve the system performance and stabilization. Furthermore, the boundary of adjustable parameters is guaranteed through the on-line learning and membership functions properties. The validation of the theoretical findings is represented by some illustrated examples.

Keywords: Neuro-Fuzzy, learning algorithm, nonlinear discrete time.

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Authors: Siamak Rasulzadeh

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Graph transformation has recently become more and more popular as a general visual modeling language to formally state the dynamic semantics of the designed models. Especially, it is a very natural formalism for languages which basically are graph (e.g. UML). Using this technique, we present a highly understandable yet precise approach to formally model and analyze the behavioral semantics of UML 2.0 Activity diagrams. In our proposal, AGG is used to design Activities, then using our previous approach to model checking graph transformation systems, designers can verify and analyze designed Activity diagrams by checking the interesting properties as combination of graph rules and LTL (Linear Temporal Logic) formulas on the Activities.

Keywords: UML 2.0 Activity, Verification, Model Checking, Graph Transformation, Dynamic Semantics.

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Authors: Rafat Alshorman, Walter Hussak

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Most of the concurrent transactional protocols consider serializability as a correctness criterion of the transactions execution. Usually, the proof of the serializability relies on mathematical proofs for a fixed finite number of transactions. In this paper, we introduce a protocol to deal with an infinite number of transactions which are iterated infinitely often. We specify serializability of the transactions and the protocol using a specification language based on temporal logics. It is worthwhile using temporal logics such as LTL (Lineartime Temporal Logic) to specify transactions, to gain full automatic verification by using model checkers.

Keywords: Multi-step transactions, LTL specifications, Model Checking.

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Authors: Reza Ghasemi, Negin Amiri Hazaveh

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In this paper, control methodology based on the selection of the type of traffic light and the period of the green phase to accomplish an optimum balance at intersections is proposed. This balance should be flexible to the static behavior of time, and randomness in a traffic situation; the goal of the proposed method is to reduce traffic volume in transportation, the average delay for each vehicle, and control over the crash of cars. The proposed method was specifically investigated at the intersection through an appropriate timing of traffic lights by sampling a multi-agent system. It consists of a large number of intersections, each of which is considered as an independent agent that exchanges information with each other, and the stability of each agent is provided separately. The robustness against uncertainties, scalability, and stability of the closed-loop overall system are the main merits of the proposed methodology. The simulation results show that the fuzzy intelligent controller in this multi-factor system which is a Takagi-Sugeno (TS) fuzzy is more useful than scheduling in the fixed-time method and it reduces the lengths of vehicles queuing.

Keywords: Fuzzy intelligent controller, traffic-light control, multi-agent systems, state space equations, stability.

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Authors: José M. Brotons, Manuel E. Sansalvador

Abstract:

The relationship between Corporate Social Responsibility (CSR) and financial performance (FP) is a subject of great interest that has not yet been resolved. In this work, we have developed a new and original tool to measure this relation. The tool quantifies the value contributed to companies that are committed to CSR. The theoretical model used is the fuzzy discounted cash flow method. Two assumptions have been considered, the first, the company has implemented the IQNet SR10 certification, and the second, the company has not implemented that certification. For the first one, the growth rate used for the time horizon is the rate maintained by the company after obtaining the IQNet SR10 certificate. For the second one, both, the growth rates company prior to the implementation of the certification, and the evolution of the sector will be taken into account. By using triangular fuzzy numbers, it is possible to deal adequately with each company’s forecasts as well as the information corresponding to the sector. Once the annual growth rate of the sales is obtained, the profit and loss accounts are generated from the annual estimate sales. For the remaining elements of this account, their regression with the nets sales has been considered. The difference between these two valuations, made in a fuzzy environment, allows obtaining the value of the IQNet SR10 certification. Although this study presents an innovative methodology to quantify the relation between CSR and FP, the authors are aware that only one company has been analyzed. This is precisely the main limitation of this study which in turn opens up an interesting line for future research: to broaden the sample of companies.

Keywords: Corporate social responsibility, case study, financial performance, company valuation.

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Authors: Yul Y. Nazaruddin, Anas Y. Widiaribowo, Satriyo Nugroho

Abstract:

Boiler is one of the critical unit in a petrochemical plant. Steam produced by the boiler is used for various processes in the plant such as urea and ammonia plant. An alternative method to optimize the boiler combustion system is presented in this paper. Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is applied to model the boiler using real-time operational data collected from a boiler unit of the petrochemical plant. Nonlinear equation obtained is then used to optimize the air to fuel ratio using Genetic Algorithm, resulting an optimal ratio of 15.85. This optimal ratio is then maintained constant by ratio controller designed using inverse dynamics based on ANFIS. As a result, constant value of oxygen content in the flue gas is obtained which indicates more efficient combustion process.

Keywords: ANFIS, boiler, combustion process, genetic algorithm, optimization.

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Authors: Michalis D. Galanis, Gregory Dimitroulakos, Costas E. Goutis

Abstract:

Speedups from mapping four real-life DSP applications on an embedded system-on-chip that couples coarsegrained reconfigurable logic with an instruction-set processor are presented. The reconfigurable logic is realized by a 2-Dimensional Array of Processing Elements. A design flow for improving application-s performance is proposed. Critical software parts, called kernels, are accelerated on the Coarse-Grained Reconfigurable Array. The kernels are detected by profiling the source code. For mapping the detected kernels on the reconfigurable logic a prioritybased mapping algorithm has been developed. Two 4x4 array architectures, which differ in their interconnection structure among the Processing Elements, are considered. The experiments for eight different instances of a generic system show that important overall application speedups have been reported for the four applications. The performance improvements range from 1.86 to 3.67, with an average value of 2.53, compared with an all-software execution. These speedups are quite close to the maximum theoretical speedups imposed by Amdahl-s law.

Keywords: Reconfigurable computing, Coarse-grained reconfigurable array, Embedded systems, DSP, Performance

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Authors: Ji-Hye Kim, Sung-Gaun Kim

Abstract:

Electro-hydraulic power steering (EHPS) system for the fuel rate reduction and steering feel improvement is comprised of ECU including the logic which controls the steering system and BL DC motor and produces the best suited cornering force, BLDC motor, high pressure pump integrated module and basic oil-hydraulic circuit of the commercial HPS system. Electro-hydraulic system can be studied in two ways such as experimental and computer simulation. To get accurate results in experimental study of EHPS system, the real boundary management is necessary which is difficult task. And the accuracy of the experimental results depends on the preparation of the experimental setup and accuracy of the data collection. The computer simulation gives accurate and reliable results if the simulation is carried out considering proper boundary conditions. So, in this paper, each component of EHPS was modeled, and the model-based analysis and control logic was designed by using AMESim

Keywords: Power steering system, Electro-Hydraulic power steering (EHPS) system, Modeling of EHPS system, Analysis modeling.

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Authors: Jeonghoon Han, Hanjae Jeong, Dongho Won, Seungjoo Kim

Abstract:

As the Internet technology has developed rapidly, the number of identities (IDs) managed by each individual person has increased and various ID management technologies have been developed to assist users. However, most of these technologies are vulnerable to the existing hacking methods such as phishing attacks and key-logging. If the administrator-s password is exposed, an attacker can access the entire contents of the stolen user-s data files in other devices. To solve these problems, we propose here a new ID management scheme based on a Single Password Protocol. The paper presents the details of the new scheme as well as a formal analysis of the method using BAN Logic.

Keywords: Anti-phishing, BAN Logic, ID management.

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Authors: Benjamin Y. M. Kwan, Hon Keung Kwan

Abstract:

Noise contamination in a magnetic resonance (MR) image could occur during acquisition, storage, and transmission in which effective filtering is required to avoid repeating the MR procedure. In this paper, an iterative asymmetrical triangle fuzzy filter with moving average center (ATMAVi filter) is used to reduce different levels of salt and pepper noise in a brain MR image. Besides visual inspection on filtered images, the mean squared error (MSE) is used as an objective measurement. When compared with the median filter, simulation results indicate that the ATMAVi filter is effective especially for filtering a higher level noise (such as noise density = 0.45) using a smaller window size (such as 3x3) when operated iteratively or using a larger window size (such as 5x5) when operated non-iteratively.

Keywords: Brain images, Fuzzy filters, Magnetic resonance imaging, Salt and pepper noise reduction.

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Authors: Sudha Bansal, Lalit Mohan Saini, Dheeraj Joshi

Abstract:

The controller is used to improve the dynamic performance of DC-DC converter by achieving a robust output voltage against load disturbances. This paper presents the performance of PI and Fuzzy controller for a phase- shifted zero-voltage switched full-bridge PWM (ZVS FB- PWM) converters with a closed loop control. The proposed converter is regulated with minimum overshoot and good stability. In this paper phase-shift control method is used as an effective tool to reduce switching losses and duty cycle losses. A 1kW/100KHz dc/dc converter is simulated and analyzed using MATLAB. The circuit is simulated for static and dynamic load (DC motor). It has been observed that performance of converter with fuzzy controller is better than that of PI controller. An efficiency comparison of the converter with a reported topology has also been carried out.

Keywords: Full-bridge converter, phase-shifted, synchronous rectifier (SR), zero-voltage switching (ZVS).

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Authors: Marzieh. Savoj, S. Amirhassan. Monadjemi

Abstract:

Iris localization is a very important approach in biometric identification systems. Identification process usually is implemented in three levels: iris localization, feature extraction, and pattern matching finally. Accuracy of iris localization as the first step affects all other levels and this shows the importance of iris localization in an iris based biometric system. In this paper, we consider Daugman iris localization method as a standard method, propose a new method in this field and then analyze and compare the results of them on a standard set of iris images. The proposed method is based on the detection of circular edge of iris, and improved by fuzzy circles and surface energy difference contexts. Implementation of this method is so easy and compared to the other methods, have a rather high accuracy and speed. Test results show that the accuracy of our proposed method is about Daugman method and computation speed of it is 10 times faster.

Keywords: Convolution, Edge detector filter, Fuzzy circle, Identification

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Authors: Ayman M. Mansour

Abstract:

In this paper, we propose a multi-agent intelligent system that is used for monitoring the health conditions of elderly people. Monitoring the health condition of elderly people is a complex problem that involves different medical units and requires continuous monitoring. Such expert system is highly needed in rural areas because of inadequate number of available specialized physicians or nurses. Such monitoring must have autonomous interactions between these medical units in order to be effective. A multi-agent system is formed by a community of agents that exchange information and proactively help one another to achieve the goal of elderly monitoring. The agents in the developed system are equipped with intelligent decision maker that arms them with the rule-based reasoning capability that can assist the physicians in making decisions regarding the medical condition of elderly people.

Keywords: Fuzzy Logic, Inference system, Monitoring system, Multi-agent system.

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Authors: Peyman Shadman Heidari, Mohammad Khorasani

Abstract:

The principal purpose of this article is to present a new method based on Adaptive Neural Network Fuzzy Inference System (ANFIS) to generate additional artificial earthquake accelerograms from presented data, which are compatible with specified response spectra. The proposed method uses the learning abilities of ANFIS to develop the knowledge of the inverse mapping from response spectrum to earthquake records. In addition, wavelet packet transform is used to decompose specified earthquake records and then ANFISs are trained to relate the response spectrum of records to their wavelet packet coefficients. Finally, an interpretive example is presented which uses an ensemble of recorded accelerograms to demonstrate the effectiveness of the proposed method.

Keywords: Adaptive Neural Network Fuzzy Inference System, Wavelet Packet Transform, Response Spectrum.

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Authors: Sufian Ashraf Mazhari, Surendra Kumar

Abstract:

This paper compares the heuristic Global Search Techniques; Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Generalized Pattern Search, genetic algorithm hybridized with Nelder–Mead and Generalized pattern search technique for tuning of fuzzy PID controller for Puma 560. Since the actual control is in joint space ,inverse kinematics is used to generate various joint angles correspoding to desired cartesian space trajectory. Efficient dynamics and kinematics are modeled on Matlab which takes very less simulation time. Performances of all the tuning methods with and without disturbance are compared in terms of ITSE in joint space and ISE in cartesian space for spiral trajectory tracking. Genetic Algorithm hybridized with Generalized Pattern Search is showing best performance.

Keywords: Controller tuning, Fuzzy Control, Genetic Algorithm, Heuristic search, Robot control.

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Authors: Prashanth C.M., K. Chandrashekar Shet

Abstract:

In recent past, the Unified Modeling Language (UML) has become the de facto industry standard for object-oriented modeling of the software systems. The syntax and semantics rich UML has encouraged industry to develop several supporting tools including those capable of generating deployable product (code) from the UML models. As a consequence, ensuring the correctness of the model/design has become challenging and extremely important task. In this paper, we present an approach for automatic verification of protocol model/design. As a case study, Session Initiation Protocol (SIP) design is verified for the property, “the CALLER will not converse with the CALLEE before the connection is established between them ". The SIP is modeled using UML statechart diagrams and the desired properties are expressed in temporal logic. Our prototype verifier “UML-SMV" is used to carry out the verification. We subjected an erroneous SIP model to the UML-SMV, the verifier could successfully detect the error (in 76.26ms) and generate the error trace.

Keywords: Unified Modeling Language, Statechart, Verification, Protocol Design, Model Checking.

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Authors: S. Ben Chaabane, M. Sayadi, F. Fnaiech, E. Brassart

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In this paper we propose a new knowledge model using the Dempster-Shafer-s evidence theory for image segmentation and fusion. The proposed method is composed essentially of two steps. First, mass distributions in Dempster-Shafer theory are obtained from the membership degrees of each pixel covering the three image components (R, G and B). Each membership-s degree is determined by applying Fuzzy C-Means (FCM) clustering to the gray levels of the three images. Second, the fusion process consists in defining three discernment frames which are associated with the three images to be fused, and then combining them to form a new frame of discernment. The strategy used to define mass distributions in the combined framework is discussed in detail. The proposed fusion method is illustrated in the context of image segmentation. Experimental investigations and comparative studies with the other previous methods are carried out showing thus the robustness and superiority of the proposed method in terms of image segmentation.

Keywords: Fuzzy C-means, Color image, data fusion, Dempster-Shafer's evidence theory

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Authors: Daniel Stamate

Abstract:

One of the most used assumptions in logic programming and deductive databases is the so-called Closed World Assumption (CWA), according to which the atoms that cannot be inferred from the programs are considered to be false (i.e. a pessimistic assumption). One of the most successful semantics of conventional logic programs based on the CWA is the well-founded semantics. However, the CWA is not applicable in all circumstances when information is handled. That is, the well-founded semantics, if conventionally defined, would behave inadequately in different cases. The solution we adopt in this paper is to extend the well-founded semantics in order for it to be based also on other assumptions. The basis of (default) negative information in the well-founded semantics is given by the so-called unfounded sets. We extend this concept by considering optimistic, pessimistic, skeptical and paraconsistent assumptions, used to complete missing information from a program. Our semantics, called extended well-founded semantics, expresses also imperfect information considered to be missing/incomplete, uncertain and/or inconsistent, by using bilattices as multivalued logics. We provide a method of computing the extended well-founded semantics and show that Kripke-Kleene semantics is captured by considering a skeptical assumption. We show also that the complexity of the computation of our semantics is polynomial time.

Keywords: Logic programs, imperfect information, multivalued logics, bilattices, assumptions.

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Authors: Chen-Yu Wang, Tsung-Chien Chen, Ming-Hui Lee, Jen-Feng Huang

Abstract:

In this paper, the innovative intelligent fuzzy weighted input estimation method (FWIEM) can be applied to the inverse heat transfer conduction problem (IHCP) to estimate the unknown time-varying heat flux efficiently as presented. The feasibility of this method can be verified by adopting the temperature measurement experiment. We would like to focus attention on the heat flux estimation to three kinds of samples (Copper, Iron and Steel/AISI 304) with the same 3mm thickness. The temperature measurements are then regarded as the inputs into the FWIEM to estimate the heat flux. The experiment results show that the proposed algorithm can estimate the unknown time-varying heat flux on-line.

Keywords: Fuzzy Weighted Input Estimation Method, IHCP andHeat Flux.

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Authors: Noraziah Ahmad, Roslina Mohd Sidek, Mohd Affendy Omardin

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E-Appointment Scheduling (EAS) has been developed to handle appointment for UMP students, lecturers in Faculty of Computer Systems & Software Engineering (FCSSE) and Student Medical Center. The schedules are based on the timetable and university activities. Constraints Logic Programming (CLP) has been implemented to solve the scheduling problems by giving recommendation to the users in part of determining any available slots from the lecturers and doctors- timetable. By using this system, we can avoid wasting time and cost because this application will set an appointment by auto-generated. In addition, this system can be an alternative to the lecturers and doctors to make decisions whether to approve or reject the appointments.

Keywords: EAS, Constraint Logic Programming, PHP, Apache.

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Authors: O. Poleshchuk, E. Komarov

Abstract:

The paper presents the method developed to assess rating points of objects with qualitative indexes. The novelty of the method lies in the fact that the authors use linguistic scales that allow to formalize the values of the indexes with the help of fuzzy sets. As a result it is possible to operate correctly with dissimilar indexes on the unified basis and to get stable final results. The obtained rating points are used in decision making based on fuzzy expert opinions.

Keywords: complete orthogonal semantic space, qualitativecharacteristic, rating points.

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