Search results for: exponential fuzzy entropy.

Authors: Fatemeh Amiri, Caro Lucas, Nasser Yazdani

Abstract:

As the network based technologies become omnipresent, demands to secure networks/systems against threat increase. One of the effective ways to achieve higher security is through the use of intrusion detection systems (IDS), which are a software tool to detect anomalous in the computer or network. In this paper, an IDS has been developed using an improved machine learning based algorithm, Locally Linear Neuro Fuzzy Model (LLNF) for classification whereas this model is originally used for system identification. A key technical challenge in IDS and LLNF learning is the curse of high dimensionality. Therefore a feature selection phase is proposed which is applicable to any IDS. While investigating the use of three feature selection algorithms, in this model, it is shown that adding feature selection phase reduces computational complexity of our model. Feature selection algorithms require the use of a feature goodness measure. The use of both a linear and a non-linear measure - linear correlation coefficient and mutual information- is investigated respectively

Keywords: anomaly Detection, feature selection, Locally Linear Neuro Fuzzy (LLNF), Mutual Information (MI), liner correlation coefficient.

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Authors: Muhammad Muhsin, Abhishek Mishra, Shreyansh Vishwakarma, K. Dasaratha Babu, Anudevi Samuel

Abstract:

In an interconnected power system, any sudden small load perturbation in any of the interconnected areas causes the deviation of the area frequencies, the tie line power and voltage deviation at the generator terminals. This paper deals with the study of performance of intelligent Fuzzy Logic controllers coupled with Conventional Controllers (PI and PID) for Load Frequency Control. For analysis, an isolated single area and interconnected two area thermal power systems with and without generation rate constraints (GRC) have been considered. The studies have been performed with conventional PI and PID controllers and their performance has been compared with intelligent fuzzy controllers. It can be demonstrated that these controllers can successfully bring back the excursions in area frequencies and tie line powers within acceptable limits in smaller time periods and with lesser transients as compared to the performance of conventional controllers under same load disturbance conditions. The simulations in MATLAB have been used for comparative studies.

Keywords: Area Control Error, Fuzzy Logic, Generation rate constraint, Load Frequency, Tie line Power.

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Authors: L. Ludovic, R. Daniel, S-E Tbahriti

Abstract:

Database management systems that integrate user preferences promise better solution for personalization, greater flexibility and higher quality of query responses. This paper presents a tentative work that studies and investigates approaches to express user preferences in queries. We sketch an extend capabilities of SQLf language that uses the fuzzy set theory in order to define the user preferences. For that, two essential points are considered: the first concerns the expression of user preferences in SQLf by so-called fuzzy commensurable predicates set. The second concerns the bipolar way in which these user preferences are expressed on mandatory and/or optional preferences.

Keywords: Flexible query language, relational database, userpreference.

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Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

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In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc.).

Keywords: Defuzzification, floating search, fuzzy clustering, Zernike moments.

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

Abstract:

Series compensators have been used for many years, to increase the stability and load ability of transmission line. They compensate retarded or advanced volt drop of transmission lines by placing advanced or retarded voltage in series with them to compensate the effective reactance, which cause to increase load ability of transmission lines. In this paper, two method of fuzzy controller, based on power reference tracking and impedance reference tracking have been developed on TCSC controller in order to increase load ability and improving power oscillation damping of system. In these methods, fire angle of thyristors are determined directly through the special Rule-bases with the error and change of error as the inputs. The simulation results of two area four- machines power system show the good performance of power oscillation damping in system. Comparison of this method with classical PI controller shows the increasing speed of system response in power oscillation damping.

Keywords: TCSC, Two area network, Fuzzy controller, Power oscillation damping.

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Authors: P. Naderi, S.M.T. Bathaee, R. Hoseinnezhad, R. Chini

Abstract:

Using electrical machine in conventional vehicles, also called hybrid vehicles, has become a promising control scheme that enables some manners for fuel economy and driver assist for better stability. In this paper, vehicle stability control, fuel economy and Driving/Regeneration braking for a 4WD hybrid vehicle is investigated by using an electrical machine on each non-driven wheels. In front wheels driven vehicles, fuel economy and regenerative braking can be obtained by summing torques applied on rear wheels. On the other hand, unequal torques applied to rear wheels provides enhanced safety and path correction in steering. In this paper, a model with fourteen degrees of freedom is considered for vehicle body, tires and, suspension systems. Thereafter, powertrain subsystems are modeled. Considering an electrical machine on each rear wheel, a fuzzy controller is designed for each driving, braking, and stability conditions. Another fuzzy controller recognizes the vehicle requirements between the driving/regeneration and stability modes. Intelligent vehicle control to multi objective operation and forward simulation are the paper advantages. For reaching to these aims, power management control and yaw moment control will be done by three fuzzy controllers. Also, the above mentioned goals are weighted by another fuzzy sub-controller base on vehicle dynamic. Finally, Simulations performed in MATLAB/SIMULINK environment show that the proposed structure can enhance the vehicle performance in different modes effectively.

Keywords: Hybrid, pitch, roll, regeneration, yaw.

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Authors: Mohsen Masoomi, Fazel Asadi Amjad, Monireh Arvin

Abstract:

According to Naturalistic principles, human destiny in the form of blind chance and determinism, entraps the individual, so man is a defenceless creature unable to escape from the ruthless paws of a stoical universe. In Naturalism; nonetheless, melodrama mirrors a conscious alternative with a peculiar function. A typical American Naturalistic character thus cannot be a subject for social criticism of American society since they are not victims of the ongoing virtual slavery, capitalist system, nor of a ruined milieu, but of their own volition, and more importantly, their character frailty. Through a Postmodern viewpoint, each Naturalistic work can encompass some entropic trends and changes culminating in an entire failure and devastation. Frank Norris in McTeague displays the futile struggles of ordinary men and how they end up brutes. McTeague encompasses intoxication, abuse, violation, and ruthless homicides. Norris’ depictions of the falling individual as a demon represent the entropic dimension of Naturalistic novels. McTeague’s defeat is somewhat his own fault, the result of his own blunders and resolution, not the result of sheer accident. Throughout the novel, each character is a kind of insane quester indicating McTeague’s decadence and, by inference, the decadence of Western civilisation. McTeague seems to designate Norris’ solicitude for a community fabricated by the elements of human negative demeanours and conducts hauling acute symptoms of infectious dehumanisation. The aim of this article is to illustrate how one specific negative human disposition gradually, like a running fire, can spread everywhere and burn everything in itself. The author applies the concept of entropy metaphorically to describe the individual devolutions that necessarily comprise community entropy in McTeague, a dying universe.

Keywords: Animal imagery, entropy, Gypsy, melodrama.

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Authors: Masoud Sadeghian, Alireza Fatehi

Abstract:

In this paper, we use nonlinear system identification method to predict and detect process fault of a cement rotary kiln. After selecting proper inputs and output, an input-output model is identified for the plant. To identify the various operation points in the kiln, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOLIMOT algorithm which is an incremental treestructure algorithm. Then, by using this method, we obtained 3 distinct models for the normal and faulty situations in the kiln. One of the models is for normal condition of the kiln with 15 minutes prediction horizon. The other two models are for the two faulty situations in the kiln with 7 minutes prediction horizon are presented. At the end, we detect these faults in validation data. The data collected from White Saveh Cement Company is used for in this study.

Keywords: Cement Rotary Kiln, Fault Detection, Delay Estimation Method, Locally Linear Neuro Fuzzy Model, LOLIMOT.

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Authors: Wann-Ming Wey

Abstract:

In recent years, the problems of global climate change and natural disasters have induced the concerns and attentions of environmental sustainability issues for the public. Aside from the environmental planning efforts done for human environment, Transit-Oriented Development (TOD) has been widely used as one of the future solutions for the sustainable city development. In order to be more consistent with the urban sustainable development, the development of the built environment planning based on the concept of Green TOD which combines both TOD and Green Urbanism is adapted here. The connotation of the urban development under the green TOD including the design toward environment protect, the maximum enhancement resources and the efficiency of energy use, use technology to construct green buildings and protected areas, natural ecosystems and communities linked, etc. Green TOD is not only to provide the solution to urban traffic problems, but to direct more sustainable and greener consideration for future urban development planning and design. In this study, we use both the TOD and Green Urbanism concepts to proceed to the study of the built environment planning and design. Fuzzy Delphi Technique (FDT) is utilized to screen suitable criteria of the green TOD. Furthermore, Fuzzy Analytic Network Process (FANP) and Quality Function Deployment (QFD) were then developed to evaluate the criteria and prioritize the alternatives. The study results can be regarded as the future guidelines of the built environment planning and designing under green TOD development in Taiwan.

Keywords: Green transit-oriented development, built environment, fuzzy Delphi technique, quality function deployment, fuzzy analytic network process.

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Authors: Veeresham Mokali

Abstract:

The refractory alloys are crucial for high-temperature applications to improve performance and reduce cost. They are used in several applications such as aerospace, outer space, military and defense, nuclear powerplants, automobiles, and industry. The conventional refractory alloys show greater stability at high temperatures and in contrast they have operational limitations due to their low melting temperatures. However, there is a huge requirement to improve the refractory alloys’ operational temperatures and replace the conventional alloys. The newly emerging refractory high entropy alloys (RHEAs) could be alternative materials for conventional refractory alloys and fulfill the demands and requirements of various practical applications in the future. The RHEA TaHfNbZrTi was prepared through an arc melting process. The annealing behavior of severely deformed equiatomic RHEATaHfNbZrTi has been investigated. To obtain deformed condition, the alloy is cold-rolled to 90% thickness reduction and then subjected to an annealing process to observe recrystallization and microstructural evolution in the range of 800 °C to 1400 °C temperatures. The cold-rolled – 90% condition shows the presence of microstructural heterogeneity. The annealing microstructure of 800 °C temperature reveals that partial recrystallization and further annealing treatment carried out annealing treatment in the range of 850 °C to 1400 °C temperatures exhibits completely recrystallized microstructures, followed by coarsening with a degree of annealing temperature. The deformed and annealed conditions featured the development of body-centered cubic (BCC) fiber textures. The experimental investigation of heavy deformation and followed by high-temperature annealing up to 1400 °C temperature will contribute to the understanding of microstructure and texture evolution of emerging RHEAs.

Keywords: Refractory high entropy alloys, cold-rolling, annealing, microstructure, texture.

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Authors: Said Baadel, Fadi Thabtah, Joan Lu

Abstract:

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

Keywords: Data mining, k-means, MCOKE, overlapping.

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Authors: Latifeh PourMohammadBagher

Abstract:

In this paper I have developed a system for evaluating the degree of fear emotion that the intelligent agent-based system may feel when it encounters to a persecuting event. In this paper I want to describe behaviors of emotional agents using human behavior in terms of the way their emotional states evolve over time. I have implemented a fuzzy inference system using Java environment. As the inputs of this system, I have considered three parameters related on human fear emotion. The system outputs can be used in agent decision making process or choosing a person for team working systems by combination the intensity of fear to other emotion intensities.

Keywords: Emotion simulation, Fear, Fuzzy intelligent agent

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Authors: Norbik Bashah, Idris Bharanidharan Shanmugam, Abdul Manan Ahmed

Abstract:

Intrusion Detection Systems are increasingly a key part of systems defense. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic model Intelligent Intrusion Detection System, based on specific AI approach for intrusion detection. The techniques that are being investigated includes neural networks and fuzzy logic with network profiling, that uses simple data mining techniques to process the network data. The proposed system is a hybrid system that combines anomaly, misuse and host based detection. Simple Fuzzy rules allow us to construct if-then rules that reflect common ways of describing security attacks. For host based intrusion detection we use neural-networks along with self organizing maps. Suspicious intrusions can be traced back to its original source path and any traffic from that particular source will be redirected back to them in future. Both network traffic and system audit data are used as inputs for both.

Keywords: Intrusion Detection, Network Security, Data mining, Fuzzy Logic.

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Authors: Njiri J. G., Ikua B. W., Nyakoe G. N.

Abstract:

Optimization of cutting parameters important in precision machining in regards to efficiency and surface integrity of the machined part. Usually productivity and precision in machining is limited by the forces emanating from the cutting process. Due to the inherent varying nature of the workpiece in terms of geometry and material composition, the peak cutting forces vary from point to point during machining process. In order to increase productivity without compromising on machining accuracy, it is important to control these cutting forces. In this paper a fuzzy logic control algorithm is developed that can be applied in the control of peak cutting forces in milling of spherical surfaces using ball end mills. The controller can adaptively vary the feedrate to maintain allowable cutting force on the tool. This control algorithm is implemented in a computer numerical control (CNC) machine. It has been demonstrated that the controller can provide stable machining and improve the performance of the CNC milling process by varying feedrate.

Keywords: Ball-end mill, feedrate, fuzzy logic controller, machining optimization, spherical surface.

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Authors: Hamed.Vezvaei, Sepideh.Ordibeheshti, Mehdi.Ardjmand

Abstract:

Gasoline Octane Number is the standard measure of the anti-knock properties of a motor in platforming processes, that is one of the important unit operations for oil refineries and can be determined with online measurement or use CFR (Cooperative Fuel Research) engines. Online measurements of the Octane number can be done using direct octane number analyzers, that it is too expensive, so we have to find feasible analyzer, like ANFIS estimators. ANFIS is the systems that neural network incorporated in fuzzy systems, using data automatically by learning algorithms of NNs. ANFIS constructs an input-output mapping based both on human knowledge and on generated input-output data pairs. In this research, 31 industrial data sets are used (21 data for training and the rest of the data used for generalization). Results show that, according to this simulation, hybrid method training algorithm in ANFIS has good agreements between industrial data and simulated results.

Keywords: Adaptive Neuro-Fuzzy Inference Systems, GasolineOctane Number, Soft-sensor, Catalytic Naphtha Reforming

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Authors: Sarika Bahadure

Abstract:

Sustainability starts with conserving resources for future generations. Since human’s existence on this earth, he has been consuming natural resources. The resource consumption pace in the past was very slow, but industrialization in 18^th century brought a change in the human lifestyle. New inventions and discoveries upgraded the human workforce to machines. The mass manufacture of goods provided easy access to products. In the last few decades, the globalization and change in technologies brought consumer oriented market. The consumption of resources has increased at a very high scale. This overconsumption pattern brought economic boom and provided multiple opportunities, but it also put stress on the natural resources. This paper tries to put forth the facts and figures of the population growth and consumption of resources with examples. This is explained with the help of the mathematical expression of doubling known as exponential growth. It compares the carrying capacity of the earth and resource consumption of humans’ i.e. ecological footprint and bio-capacity. Further, it presents the need to conserve natural resources and re-examine sustainable resource use approach for sustainability.

Keywords: Consumption, exponential growth, population, resources, sustainability.

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Authors: P. Subha Karuvelam, M. Rajaram

Abstract:

Brushless DC motors (BLDC) are widely used in industrial areas. The BLDC motors are driven either by indirect ACAC converters or by direct AC-AC converters. Direct AC-AC converters i.e. matrix converters are used in this paper to drive the three phase BLDC motor and it eliminates the bulky DC link energy storage element. A matrix converter converts the AC power supply to an AC voltage of variable amplitude and variable frequency. A control technique is designed to generate the switching pulses for the three phase matrix converter. For the control of speed of the BLDC motor a separate PI controller and Fuzzy Logic Controller (FLC) are designed and a hysteresis current controller is also designed for the control of motor torque. The control schemes are designed and tested separately. The simulation results of both the schemes are compared and contrasted in this paper. The results show that the fuzzy logic control scheme outperforms the PI control scheme in terms of dynamic performance of the BLDC motor. Simulation results are validated with the experimental results.

Keywords: Fuzzy logic controller, matrix converter, permanent magnet brushless DC motor, PI controller.

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Authors: Omid Jadidi, Fatemeh Firouzi, Enzo Bagliery

Abstract:

Supplier selection, in real situation, is affected by several qualitative and quantitative factors and is one of the most important activities of purchasing department. Since at the time of evaluating suppliers against the criteria or factors, decision makers (DMS) do not have precise, exact and complete information, supplier selection becomes more difficult. In this case, Grey theory helps us to deal with this problem of uncertainty. Here, we apply Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to evaluate and select the best supplier by using interval fuzzy numbers. Through this article, we compare TOPSIS with some other approaches and afterward demonstrate that the concept of TOPSIS is very important for ranking and selecting right supplier.

Keywords: TOPSIS, fuzzy number, MADM, Supplier selection

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Authors: Geeta Partap, Nitika Chugh

Abstract:

The present paper deals with the flexural vibrations of homogeneous, isotropic, generalized micropolar microstretch thermoelastic thin Euler-Bernoulli beam resonators, due to Exponential time varying load. Both the axial ends of the beam are assumed to be at simply supported conditions. The governing equations have been solved analytically by using Laplace transforms technique twice with respect to time and space variables respectively. The inversion of Laplace transform in time domain has been performed by using the calculus of residues to obtain deflection.The analytical results have been numerically analyzed with the help of MATLAB software for magnesium like material. The graphical representations and interpretations have been discussed for Deflection of beam under Simply Supported boundary condition and for distinct considered values of time and space as well. The obtained results are easy to implement for engineering analysis and designs of resonators (sensors), modulators, actuators.

Keywords: Microstretch, deflection, exponential load, Laplace transforms, Residue theorem, simply supported.

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Authors: Takashi Mitsuishi, Koji Saigusa

Abstract:

This paper presents circular polar coordinates transformation of periodic fuzzy membership function. The purpose is identification of domain of periodic membership functions in consequent part of IF-THEN rules. Proposed methods in this paper remove complicatedness concerning domain of periodic membership function from defuzzification in fuzzy approximate reasoning. Defuzzification on circular polar coordinates is also proposed.

Keywords: Defuzzification, periodic membership function, polar coordinates transformation.

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Authors: Vahid Rostami, Saeed Ebrahimijam, P.khajehpoor, P.Mirzaei, Mahdi Yousefiazar

Abstract:

This paper introduces our first efforts of developing a new team for RoboCup Middle Size Competition. In our robots we have applied omni directional based mobile system with omnidirectional vision system and fuzzy control algorithm to navigate robots. The control architecture of MRL middle-size robots is a three layered architecture, Planning, Sequencing, and Executing. It also uses Blackboard system to achieve coordination among agents. Moreover, the architecture should have minimum dependency on low level structure and have a uniform protocol to interact with real robot.

Keywords: Robocup, Soccer robots, Fuzzy controller, Multi agent.

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Authors: Sanjay Kanade, Danielle Camara, Dijana Petrovska-Delacretaz, Bernadette Dorizzi

Abstract:

In this paper, a two factor scheme is proposed to generate cryptographic keys directly from biometric data, which unlike passwords, are strongly bound to the user. Hash value of the reference iris code is used as a cryptographic key and its length depends only on the hash function, being independent of any other parameter. The entropy of such keys is 94 bits, which is much higher than any other comparable system. The most important and distinct feature of this scheme is that it regenerates the reference iris code by providing a genuine iris sample and the correct user password. Since iris codes obtained from two images of the same eye are not exactly the same, error correcting codes (Hadamard code and Reed-Solomon code) are used to deal with the variability. The scheme proposed here can be used to provide keys for a cryptographic system and/or for user authentication. The performance of this system is evaluated on two publicly available databases for iris biometrics namely CBS and ICE databases. The operating point of the system (values of False Acceptance Rate (FAR) and False Rejection Rate (FRR)) can be set by properly selecting the error correction capacity (ts) of the Reed- Solomon codes, e.g., on the ICE database, at ts = 15, FAR is 0.096% and FRR is 0.76%.

Keywords:

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Authors: Somayeh Alizadeh, Mehdi Ghazanfari, Mostafa Jafari, Salman Hooshmand

Abstract:

Fuzzy Cognitive Maps (FCMs) is a causal graph, which shows the relations between essential components in complex systems. Experts who are familiar with the system components and their relations can generate a related FCM. There is a big gap when human experts cannot produce FCM or even there is no expert to produce the related FCM. Therefore, a new mechanism must be used to bridge this gap. In this paper, a novel learning method is proposed to construct causal graph based on historical data and by using metaheuristic such Tabu Search (TS). The efficiency of the proposed method is shown via comparison of its results of some numerical examples with those of some other methods.

Keywords: Fuzzy Cognitive Map (FCM), Learning, Meta heuristic, Genetic Algorithm, Tabu search.

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Authors: Hossein Gitinavard, Mohammad Hossein Fazel Zarandi

Abstract:

In the last decades, concerns about the environmental issues lead to professional and academic efforts on green supplier selection problems. In this sake, one of the main issues in evaluating the green supplier selection problems, which could increase the uncertainty, is the preferences of the experts' judgments about the candidate green suppliers. Therefore, preparing an expert system to evaluate the problem based on the historical data and the experts' knowledge can be sensible. This study provides an expert evaluation system to assess the candidate green suppliers under selected criteria in a multi-period approach. In addition, a ranking approach under interval-valued hesitant fuzzy set (IVHFS) environment is proposed to select the most appropriate green supplier in planning horizon. In the proposed ranking approach, the IVHFS and the last aggregation approach are considered to margin the errors and to prevent data loss, respectively. Hence, a comparative analysis is provided based on an illustrative example to show the feasibility of the proposed approach.

Keywords: Green supplier selection, expert system, ranking approach, interval-valued hesitant fuzzy setting.

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Authors: Lianglin Xiong, Shouming Zhong, Mao Ye

Abstract:

This paper considers the robust exponential stability issues for a class of uncertain switched neutral system which delays switched according to the switching rule. The system under consideration includes both stable and unstable subsystems. The uncertainties considered in this paper are norm bounded, and possibly time varying. Based on multiple Lyapunov functional approach and dwell-time technique, the time-dependent switching rule is designed depend on the so-called average dwell time of stable subsystems as well as the ratio of the total activation time of stable subsystems and unstable subsystems. It is shown that by suitably controlling the switching between the stable and unstable modes, the robust stabilization of the switched uncertain neutral systems can be achieved. Two simulation examples are given to demonstrate the effectiveness of the proposed method.

Keywords: Switched neutral system, exponential stability, multiple Lyapunov functional, dwell time technique, time-dependent switching rule.

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Authors: V. Prapulla, A. Mitra, R. Bhattacharjee, S. Nandi

Abstract:

We present a simplified equalization technique for a π/4 differential quadrature phase shift keying ( π/4 -DQPSK) modulated signal in a multipath fading environment. The proposed equalizer is realized as a fractionally spaced adaptive decision feedback equalizer (FS-ADFE), employing exponential step-size least mean square (LMS) algorithm as the adaptation technique. The main advantage of the scheme stems from the usage of exponential step-size LMS algorithm in the equalizer, which achieves similar convergence behavior as that of a recursive least squares (RLS) algorithm with significantly reduced computational complexity. To investigate the finite-precision performance of the proposed equalizer along with the π/4 -DQPSK modem, the entire system is evaluated on a 16-bit fixed point digital signal processor (DSP) environment. The proposed scheme is found to be attractive even for those cases where equalization is to be performed within a restricted number of training samples.

Keywords: Adaptive decision feedback equalizer, Fractionally spaced equalizer, π/4 DQPSK signal, Digital signal processor.

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Authors: Roza Afarin, Saeed Mozaffari

Abstract:

The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: Correlation coefficients, Genetic algorithm, Image encryption, Image entropy.

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Authors: Roberto Rosenhaim, Marcos Antonio Crus Moreira, Robson da Cunha, Gerson Gomes Cunha

Abstract:

This work provides details on the wind speed behavior within cities of Arraial do Cabo and São Pedro da Aldeia located in the Lakes Region of the State of Rio de Janeiro, Brazil. This region has one of the best potentials for wind power generation. In interurban layer, wind conditions are very complex and depend on physical geography, size and orientation of buildings and constructions around, population density, and land use. In the same context, the fundamental surface parameter that governs the production of flow turbulence in urban canyons is the surface roughness. Such factors can influence the potential for power generation from the wind within the cities. Moreover, the use of wind on a small scale is not fully utilized due to complexity of wind flow measurement inside the cities. It is difficult to accurately predict this type of resource. This study demonstrates how fuzzy logic can facilitate the assessment of the complexity of the wind potential inside the cities. It presents a decision support tool and its ability to deal with inaccurate information using linguistic variables created by the heuristic method. It relies on the already published studies about the variables that influence the wind speed in the urban environment. These variables were turned into the verbal expressions that are used in computer system, which facilitated the establishment of rules for fuzzy inference and integration with an application for smartphones used in the research. In the first part of the study, challenges of the sustainable development which are described are followed by incentive policies to the use of renewable energy in Brazil. The next chapter follows the study area characteristics and the concepts of fuzzy logic. Data were collected in field experiment by using qualitative and quantitative methods for assessment. As a result, a map of the various points is presented within the cities studied with its wind viability evaluated by a system of decision support using the method multivariate classification based on fuzzy logic.

Keywords: Behavior of winds, wind power, fuzzy logic, sustainable development.

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Authors: Musbah M. Aqel, P. K. Mahanti, Soumya Banerjee

Abstract:

This paper describes a simulation model for analyzing artificial emotion injected to design the game characters. Most of the game storyboard is interactive in nature and the virtual characters of the game are equipped with an individual personality and dynamic emotion value which is similar to real life emotion and behavior. The uncertainty in real expression, mood and behavior is also exhibited in game paradigm and this is focused in the present paper through a fuzzy logic based agent and storyboard. Subsequently, a pheromone distribution or labeling is presented mimicking the behavior of social insects.

Keywords: Artificial Emotion, Fuzzy logic, Game character, Pheromone label

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Authors: T. Wanyama, B. Far

Abstract:

Automatic irrigation systems usually conveniently protect landscape investment. While conventional irrigation systems are known to be inefficient, automated ones have the potential to optimize water usage. In fact, there is a new generation of irrigation systems that are smart in the sense that they monitor the weather, soil conditions, evaporation and plant water use, and automatically adjust the irrigation schedule. In this paper, we present an agent based smart irrigation system. The agents are built using a mix of commercial off the shelf software, including MATLAB, Microsoft Excel and KEPServer Ex5 OPC server, and custom written code. The Irrigation Scheduler Agent uses fuzzy logic to integrate the information that affect the irrigation schedule. In addition, the Multi-Agent system uses Open Platform Connectivity (OPC) technology to share data. OPC technology enables the Irrigation Scheduler Agent to communicate over the Internet, making the system scalable to a municipal or regional agent based water monitoring, management, and optimization system. Finally, this paper presents simulation and pilot installation test result that show the operational effectiveness of our system.

Keywords: Community water usage, fuzzy logic, irrigation, multi-agent system.

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