Search results for: Anti fuzzy subgroup

Authors: Anna Lower, Michal Lower, Robert Masztalski, Agnieszka Szumilas

Abstract:

The paper presents a method in which the expert knowledge is applied to fuzzy inference model. Even a less experienced person could benefit from the use of such a system, e.g. urban planners, officials. The analysis result is obtained in a very short time, so a large number of the proposed locations can also be verified in a short time. The proposed method is intended for testing of locations of car parks in a city. The paper shows selected examples of locations of the P&R facilities in cities planning to introduce the P&R. The analyses of existing objects are also shown in the paper and they are confronted with the opinions of the system users, with particular emphasis on unpopular locations. The results of the analyses are compared to expert analysis of the P&R facilities location that was outsourced by the city and the opinions about existing facilities users that were expressed on social networking sites. The obtained results are consistent with actual users’ feedback. The proposed method proves to be good, but does not require the involvement of a large experts team and large financial contributions for complicated research. The method also provides an opportunity to show the alternative location of P&R facilities. Although the results of the method are approximate, they are not worse than results of analysis of employed experts. The advantage of this method is ease of use, which simplifies the professional expert analysis. The ability of analyzing a large number of alternative locations gives a broader view on the problem. It is valuable that the arduous analysis of the team of people can be replaced by the model's calculation. According to the authors, the proposed method is also suitable for implementation on a GIS platform.

Keywords: Fuzzy logic inference, P&R facilities, P&R location.

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Authors: N. Tadrisi Parsa, A. R. Vali, R. Ghasemi

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Diabetes is a growing health problem in worldwide. Especially, the patients with Type 1 diabetes need strict glycemic control because they have deficiency of insulin production. This paper attempts to control blood glucose based on body mathematical body model. The Bergman minimal mathematical model is used to develop the nonlinear controller. A novel back-stepping based sliding mode control (B-SMC) strategy is proposed as a solution that guarantees practical tracking of a desired glucose concentration. In order to show the performance of the proposed design, it is compared with conventional linear and fuzzy controllers which have been done in previous researches. The numerical simulation result shows the advantages of sliding mode back stepping controller design to linear and fuzzy controllers.

Keywords: Back stepping, Bergman Model, Nonlinear control, Sliding mode control.

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Authors: Bogdan Walek, Cyril Klimes

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This paper focuses on testing database of existing information system. At the beginning we describe the basic problems of implemented databases, such as data redundancy, poor design of database logical structure or inappropriate data types in columns of database tables. These problems are often the result of incorrect understanding of the primary requirements for a database of an information system. Then we propose an algorithm to compare the conceptual model created from vague requirements for a database with a conceptual model reconstructed from implemented database. An algorithm also suggests steps leading to optimization of implemented database. The proposed algorithm is verified by an implemented prototype. The paper also describes a fuzzy system which works with the vague requirements for a database of an information system, procedure for creating conceptual from vague requirements and an algorithm for reconstructing a conceptual model from implemented database.

Keywords: testing, database, relational database, information system, conceptual model, fuzzy, uncertain information, database testing, reconstruction, requirements, optimization

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Authors: C. Ardil

Abstract:

Fuzzy set theory and its extensions (intuitionistic fuzzy sets, picture fuzzy sets, and neutrosophic sets) have been widely used to address imprecision and uncertainty in complex decision-making. However, they may struggle with inherent indeterminacy and inconsistency in real-world situations. This study introduces uncertainty sets as a promising alternative, offering a structured framework for incorporating both types of uncertainty into decision-making processes.This work explores the theoretical foundations and applications of uncertainty sets. A novel decision-making algorithm based on uncertainty set-based proximity measures is developed and demonstrated through a practical application: selecting the most suitable stealth combat aircraft.

The results highlight the effectiveness of uncertainty sets in ranking alternatives under uncertainty. Uncertainty sets offer several advantages, including structured uncertainty representation, robust ranking mechanisms, and enhanced decision-making capabilities due to their ability to account for ambiguity.Future research directions are also outlined, including comparative analysis with existing MCDM methods under uncertainty, sensitivity analysis to assess the robustness of rankings,and broader application to various MCDM problems with diverse complexities. By exploring these avenues, uncertainty sets can be further established as a valuable tool for navigating uncertainty in complex decision-making scenarios.

Keywords: Uncertainty set, stealth combat aircraft selection multiple criteria decision-making analysis, MCDM, uncertainty proximity analysis

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Authors: Raghad Alhusari, Farag Omar, Moustafa Fadel

Abstract:

A traditional greenhouse is a metal frame agricultural building used for cultivation plants in a controlled environment isolated from external climatic changes. Using greenhouses in agriculture is an efficient way to reduce the water consumption, where agriculture field is considered the biggest water consumer world widely. Controlling greenhouse environment yields better productivity of plants but demands an increase of electric power. Although various control approaches have been used towards greenhouse automation, most of them are applied to traditional greenhouses with ventilation fans and/or evaporation cooling system. Such approaches are still demanding high energy and water consumption. The aim of this research is to develop a fuzzy control system that minimizes water and energy consumption by utilizing outside weather conditions and underground heat exchanger to maintain the optimum climate of the greenhouse. The proposed control system is implemented on an experimental model of thermally isolated greenhouse structure with dimensions of 6x5x2.8 meters. It uses fans for extracting heat from the ground heat exchanger system, motors for automatic open/close of the greenhouse windows and LED as lighting system. The controller is integrated also with environmental condition sensors. It was found that using the air-to-air horizontal ground heat exchanger with 90 mm diameter and 2 mm thickness placed 2.5 m below the ground surface results in decreasing the greenhouse temperature of 3.28 ˚C which saves around 3 kW of consumed energy. It also eliminated the water consumption needed in evaporation cooling systems which are traditionally used for cooling the greenhouse environment.

Keywords: Automation, earth-to-air heat exchangers, fuzzy control, greenhouse, sustainable buildings.

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Authors: M. Ramezani, Gh. Amin, E. Jalili

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In present study the effects of anti-inflammatory and antinociceptive of vitex hydro-alcoholic extract were evaluated on male mice. In inflammatory test mice were divided into 7 groups: first group was control. The second group, positive control group, received dexamethasone (15 mg/kg) and the other five groups received different doses of hydroalcohol extract of Vitex fruit (265, 365, 465, 565, and 665 mg/kg). The inflammation was caused by xylene-induced ear edema. Formalin test was used for evaluation of antinociceptive effect of extract. In this test, mice were divided into 7 groups: control, morphine (10mg/kg) as positive control group, and Vitex extract groups ((265, 365, 465, 565, and 665 mg/kg). All drugs were administered intrapritoneally, 30 min before each test. The data were analyzed using one-way ANOVA followed by Tukey-kramer multiple comparison test. Results have shown significant antiinflammatory effects of extract at all dosed as compared with control (P<0.05). In the first phase of formalin test (0-5 min) none doses of extract could inhibit acute pain, but in the second phase (15-30 min) chronic pain decreased at 265, 365, 465, and 565 mg/kg doses (P<0.05). The results of this research indicated that Vitex extract remarkably inhibited inflammation and second phase of nociception (inflammatory pain) and can be used for treatment of inflammatory diseases.

Keywords: Anti-inflammatory, Antinociceptive, Mice, Vitexagnus castus.

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Authors: Abdalla Kablan, Joseph Falzon

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This paper is motivated by the aspect of uncertainty in financial decision making, and how artificial intelligence and soft computing, with its uncertainty reducing aspects can be used for algorithmic trading applications that trade in high frequency. This paper presents an optimized high frequency trading system that has been combined with various moving averages to produce a hybrid system that outperforms trading systems that rely solely on moving averages. The paper optimizes an adaptive neuro-fuzzy inference system that takes both the price and its moving average as input, learns to predict price movements from training data consisting of intraday data, dynamically switches between the best performing moving averages, and performs decision making of when to buy or sell a certain currency in high frequency.

Keywords: Financial decision making, High frequency trading, Adaprive neuro-fuzzy systems, moving average strategy.

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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: D. Garg, S. Luthra, A. Haleem

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Reverse logistics (RL) is supposed to be a systematic procedure that helps in improving the environmental hazards and maintain business sustainability for industries. Industries in Indian are now opting for adoption of RL techniques in business. But, RL practices are not popular in Indian industries because of many barriers for its successful implementation. Therefore, need arises to identify and evaluate the barriers to implement RL practices by taking an Indian industries perspective. Literature review approach and case study approach have been adapted to identify relevant barriers to implement RL practices. Further, Fuzzy Decision Making Trial and Evaluation Laboratory methodology has been brought into use for evaluating causal relationships among the barriers to implement RL practices. Seven barriers out of ten barriers have been categorized into the cause group and remaining into effect group. This research will help Indian industries to manage these barriers towards effective implementing RL practices.

Keywords: Barriers, decision making trial and evaluation laboratory, fuzzy set theory, Indian industries, reverse logistics.

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Authors: M. Padmavathi, R. M. Suresh

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Every machine plays roles of client and server simultaneously in a peer-to-peer (P2P) network. Though a P2P network has many advantages over traditional client-server models regarding efficiency and fault-tolerance, it also faces additional security threats. Users/IT administrators should be aware of risks from malicious code propagation, downloaded content legality, and P2P software’s vulnerabilities. Security and preventative measures are a must to protect networks from potential sensitive information leakage and security breaches. Bit Torrent is a popular and scalable P2P file distribution mechanism which successfully distributes large files quickly and efficiently without problems for origin server. Bit Torrent achieved excellent upload utilization according to measurement studies, but it also raised many questions as regards utilization in settings, than those measuring, fairness, and Bit Torrent’s mechanisms choice. This work proposed a block selection technique using Fuzzy ACO with optimal rules selected using ACO.

Keywords: Ant Colony Optimization (ACO), Bit Torrent, Download time, Peer-to-Peer (P2P) network, Performance.

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Authors: Anusua Ghosh, Andrew Nafalski, Jeffery Tweedale, Maureen Dollard

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This paper presents anapproach of hybridizing two or more artificial intelligence (AI) techniques which arebeing used to fuzzify the workstress level ranking and categorize the rating accordingly. The use of two or more techniques (hybrid approach) has been considered in this case, as combining different techniques may lead to neutralizing each other-s weaknesses generating a superior hybrid solution. Recent researches have shown that there is a need for a more valid and reliable tools, for assessing work stress. Thus artificial intelligence techniques have been applied in this instance to provide a solution to a psychological application. An overview about the novel and autonomous interactive model for analysing work-stress that has been developedusing multi-agent systems is also presented in this paper. The establishment of the intelligent multi-agent decision analyser (IMADA) using hybridized technique of neural networks and fuzzy logic within the multi-agent based framework is also described.

Keywords: Fuzzy logic, intelligent agent, multi-agent systems, neural network, workplace stress.

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Authors: Chunshien Li, Jhao-Wun Hu, Tai-Wei Chiang, Tsunghan Wu

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Time series forecasting is an important and widely popular topic in the research of system modeling. This paper describes how to use the hybrid PSO-RLSE neuro-fuzzy learning approach to the problem of time series forecasting. The PSO algorithm is used to update the premise parameters of the proposed prediction system, and the RLSE is used to update the consequence parameters. Thanks to the hybrid learning (HL) approach for the neuro-fuzzy system, the prediction performance is excellent and the speed of learning convergence is much faster than other compared approaches. In the experiments, we use the well-known Mackey-Glass chaos time series. According to the experimental results, the prediction performance and accuracy in time series forecasting by the proposed approach is much better than other compared approaches, as shown in Table IV. Excellent prediction performance by the proposed approach has been observed.

Keywords: forecasting, hybrid learning (HL), Neuro-FuzzySystem (NFS), particle swarm optimization (PSO), recursiveleast-squares estimator (RLSE), time series

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Authors: Hai Xu, Yiwei Wang, Xi Bao, Bihua Deng, Pengcheng Li, Yu Lu

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T7 phage could be used as a perfect vector for peptides expression and haptens presentation. T7-3GnRH recombinant phage was constructed by inserting three copies of Gonadotrophin Releasing Hormone (GnRH) gene into the multiple cloning site of T7 Select 415-1b phage genome. The positive T7-3GnRH phage was selected by using polymerase chain reaction amplification, and the p10B-3GnRH fusion protein was verified by SDS-PAGE and Western-blotting assay. T7-3GnRH vaccine was made and immunized with 10¹⁰ pfu in 0.2 ml per dose in mice. Blood samples were collected at an interval in weeks, and anti-GnRH antibody and testosterone concentrations were detected by ELISA and radioimmunoassay, respectively. The results show that T7-3GnRH phage particles confer a high immunogenicity to the GnRH-derived epitope. Moreover, the T7-3GnRH vaccine induced higher level of anti-GnRH antibody than ImproVac^®. However, the testosterone concentrations in both immunized groups were at a similar level, and the testis developments were significantly inhibited compared to controls. These findings demonstrated that the anti-GnRH antibody could neutralize the endogenous GnRH to down regulate testosterone level and limit testis development, highlighting the potential value of T7-3GnRH in the immunocastration vaccine research.

Keywords: Gonadotrophin releasing hormone, GnRH, immunocastration, T7 phage, phage vaccine.

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Authors: Grouz Faten, Sbita Lassaâd

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In this paper, Speed Sensorless Indirect Field Oriented Control (IFOC) of a Permanent Magnet Synchronous machine (PMSM) is studied. The closed loop scheme of the drive system utilizes fuzzy speed and current controllers. Due to the well known drawbacks of the speed sensor, an algorithm is proposed in this paper to eliminate it. In fact, based on the model of the PMSM, the stator currents and rotor speed are estimated simultaneously using adaptive Luenberger observer for currents and MRAS (Model Reference Adaptive System) observer for rotor speed. To overcome the sensivity of this algorithm against parameter variation, adaptive for on line stator resistance tuning is proposed. The validity of the proposed method is verified by an extensive simulation work.

Keywords: PMSM, Indirect Field Oriented Control, fuzzy speed and currents controllers, Adaptive Luenberger observer, MRAS.

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Authors: P. Thongmuang, Y. Sudjaroen

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The methanolic extracts from seeds of tamarind (Tamarindus indica) was prepared by Soxhlet apparatus extraction and evaluated for total phenolic content by Folin-Ciocalteu method. Then, methanolic extract was screened biological activities (In vitro) for anti-melanogenic activity by tyrosinase inhibition test, antiinflammation activity by cyclooxygenase 1 (COX-1) and cyclooxygenase 2 (COX-2) inhibition test, and cytotoxic screening test with Vero cells. The results showed that total phenolic content, which contained in extract, was contained 27.72 mg of gallic acid equivalent per g of dry weight. The ability to inhibit tyrosinase enzyme, which exerted by Tamarind seed extracts (1 mg/ml) was 52.13 ± 0.42 %. The extract was not possessed inhibitory effect to COX-1 and COX-2 enzymes and cytotoxic effect to Vero cells. The finding is concludes that tested seed extract was possessed antimelanogenic activity with non-toxic effects. However, there was not exhibited anti-inflammatory activity. Further studies include the use of advance biological models to confirm this biological activity, as well as, the isolation and characterization of the purified compounds that it was contained.

Keywords: Tamarindus indica, anti-melanogenic, antiinflammatotion, cytotoxicity, seed, phenolic compounds.

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Authors: J. Menčík

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Actual load, material characteristics and other quantities often differ from the design values. This can cause worse function, shorter life or failure of a civil engineering structure, a machine, vehicle or another appliance. The paper shows main causes of the uncertainties and deviations and presents a systematic approach and efficient tools for their elimination or mitigation of consequences. Emphasis is put on the design stage, which is most important for reliability ensuring. Principles of robust design and important tools are explained, including FMEA, sensitivity analysis and probabilistic simulation methods. The lifetime prediction of long-life objects can be improved by long-term monitoring of the load response and damage accumulation in operation. The condition evaluation of engineering structures, such as bridges, is often based on visual inspection and verbal description. Here, methods based on fuzzy logic can reduce the subjective influences.

Keywords: Design, fuzzy methods, Monte Carlo, reliability, robust design, sensitivity analysis, simulation, uncertainties.

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Authors: Georgia C. Kosta, Christos S. Nicolaidis

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The present paper discusses the role of teams’ climate in the intrapreneurial process. Intrapreneurship, which corresponds for entrepreneurship in existing organizations, puts special emphasis on climate as an influential factor of the intrapreneurial behavior. Although climate exists at every level and in every subgroup of the organizational structure, research focuses mainly on the study of climate that characterizes organization as a whole. However, the climate of a work team may differ radically from the organizational climate, and in fact it can be far more influential. The paper provides a conceptual analysis of organizational climate from the intrapreneurial point of view, and sheds light upon teams’ climate role in the intrapreneurial posture.

Keywords: Entrepreneurship, innovation, intrapreneurship, organizational climate, teams’ climate.

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Authors: Dulal Acharjee, Punyaban Patel

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For collecting data from all sensor nodes, some changes in Dynamic Source Routing (DSR) protocol is proposed. At each hop level, route-ranking technique is used for distributing packets to different selected routes dynamically. For calculating rank of a route, different parameters like: delay, residual energy and probability of packet loss are used. A hybrid topology of DMPR(Disjoint Multi Path Routing) and MMPR(Meshed Multi Path Routing) is formed, where braided topology is used in different faulty zones of network. For reducing energy consumption, variant transmission ranges is used instead of fixed transmission range. For reducing number of packet drop, a fuzzy logic inference scheme is used to insert different types of delays dynamically. A rule based system infers membership function strength which is used to calculate the final delay amount to be inserted into each of the node at different clusters. In braided path, a proposed 'Dual Line ACK Link'scheme is proposed for sending ACK signal from a damaged node or link to a parent node to ensure that any error in link or any node-failure message may not be lost anyway. This paper tries to design the theoretical aspects of a model which may be applied for collecting data from any large hanging iron structure with the help of wireless sensor network. But analyzing these data is the subject of material science and civil structural construction technology, that part is out of scope of this paper.

Keywords: Metallic corrosion, Multi Path Routing, DisjointMPR, Meshed MPR, braided path, dual line ACK link, route rankingand Fuzzy Logic.

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Authors: K. Sakthivel, R. Nallusamy, C. Kavitha

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The goal of image segmentation is to cluster pixels into salient image regions. Segmentation could be used for object recognition, occlusion boundary estimation within motion or stereo systems, image compression, image editing, or image database lookup. In this paper, we present a color image segmentation using support vector machine (SVM) pixel classification. Firstly, the pixel level color and texture features of the image are extracted and they are used as input to the SVM classifier. These features are extracted using the homogeneity model and Gabor Filter. With the extracted pixel level features, the SVM Classifier is trained by using FCM (Fuzzy C-Means).The image segmentation takes the advantage of both the pixel level information of the image and also the ability of the SVM Classifier. The Experiments show that the proposed method has a very good segmentation result and a better efficiency, increases the quality of the image segmentation compared with the other segmentation methods proposed in the literature.

Keywords: Image Segmentation, Support Vector Machine, Fuzzy C–Means, Pixel Feature, Texture Feature, Homogeneity model, Gabor Filter.

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Authors: Brigita Altenbaher

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In recent years there has been a continuous increase of axle loads, tonnage, train speed and train length which has increased both the productivity in the rail sector and the risk of rail breaks and derailments. On the other hand, the environmental requirements (e.g. noise reduction) for railway operations will become tighter in the future. In our research we developed a new composite material which does not change braking properties, is capable of taking extremely high pressure loads, reduces noise and is environmentally friendly. Part of our research was also the development of technology which will be able to apply this material to the rail. The result of our research was the system which reduces the wear out significantly and almost completely eliminates the squealing noise at the same time, and by using only one special material.

Keywords: Active protection, composite material, lubrication, noise reduction, reduction at source, railway.

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Authors: Nasim Ullah, Shaoping Wang

Abstract:

ELS is an important ground based hardware in the loop simulator used for aerodynamics torque loading experiments of the actuators under test. This work focuses on improvement of the transient response of torque controller with parameters uncertainty of Electrical Load Simulator (ELS).The parameters of load simulator are estimated online and the model is updated, eliminating the model error and improving the steady state torque tracking response of torque controller. To improve the Transient control performance the gain of robust term of SMC is updated online using fuzzy logic system based on the amount of uncertainty in parameters of load simulator. The states of load simulator which cannot be measured directly are estimated using luenberger observer with update of new estimated parameters. The stability of the control scheme is verified using Lyapunov theorem. The validity of proposed control scheme is verified using simulations.

Keywords: ELS, Observer, Transient Performance, SMC, Extra Torque, Fuzzy Logic.

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Authors: A. Galashev

Abstract:

Absorption spectra of infra-red (IR) radiation of the disperse water medium absorbing the most important greenhouse gases: CO2 , N2O , CH4 , C2H2 , C2H6 have been calculated by the molecular dynamics method. Loss of the absorbing ability at the formation of clusters due to a reduction of the number of centers interacting with IR radiation, results in an anti-greenhouse effect. Absorption of O3 molecules by the (H2O)50 cluster is investigated at its interaction with Cl- ions. The splitting of ozone molecule on atoms near to cluster surface was observed. Interaction of water cluster with Cl- ions causes the increase of integrated intensity of emission spectra of IR radiation, and also essential reduction of the similar characteristic of Raman spectrum. Relative integrated intensity of absorption of IR radiation for small water clusters was designed. Dependences of the quantity of weight on altitude for vapor of monomers, clusters, droplets, crystals and mass of all moisture were determined. The anti-greenhouse effect of clusters was defined as the difference of increases of average global temperature of the Earth, caused by absorption of IR radiation by free water molecules forming clusters, and absorption of clusters themselves. The greenhouse effect caused by clusters makes 0.53 K, and the antigreenhouse one is equal to 1.14 K. The increase of concentration of CO2 in the atmosphere does not always correlate with the amplification of greenhouse effect.

Keywords: Greenhouse gases, infrared absorption and Raman spectra, molecular dynamics method, water clusters.

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Authors: Yuan-Jye Tseng, Yi-Shiuan Chen

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In this paper, a new concept of closed-loop design for a product is presented. The closed-loop design model is developed by integrating forward design and reverse design. Based on this new concept, a closed-loop design model for sustainable manufacturing by integrated evaluation of forward design, reverse design, and green manufacturing using a fuzzy analytic network process is developed. In the design stage of a product, with a given product requirement and objective, there can be different ways to design the detailed components and specifications. Therefore, there can be different design cases to achieve the same product requirement and objective. Subsequently, in the design evaluation stage, it is required to analyze and evaluate the different design cases. The purpose of this research is to develop a model for evaluating the design cases by integrated evaluating the criteria in forward design, reverse design, and green manufacturing. A fuzzy analytic network process method is presented for integrated evaluation of the criteria in the three models. The comparison matrices for evaluating the criteria in the three groups are established. The total relational values among the three groups represent the total relational effects. In applications, a super matrix model is created and the total relational values can be used to evaluate the design cases for decision-making to select the final design case. An example product is demonstrated in this presentation. It shows that the model is useful for integrated evaluation of forward design, reverse design, and green manufacturing to achieve a closed-loop design for sustainable manufacturing objective.

Keywords: Design evaluation, forward design, reverse design, closed-loop design, supply chain management, closed-loop supply chain, fuzzy analytic network process.

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Authors: Danijela Tuljak-Suban, Valter Suban

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Food as perishable goods represents a specific and sensitive part in the supply chain theory, since changing physical or chemical characteristics considerably influence the approach to stock management. The most delicate phase of this process is transportation, where it becomes difficult to ensure the stable conditions which limit deterioration, since the value of the deterioration rate could be easily influenced by the mode of transportation. The fuzzy definition of variables allows one to take these variations into account. Furthermore, an appropriate choice of the defuzzification method permits one to adapt results to real conditions as far as possible. In this article those methods which take into account the relationship between the deterioration rate of perishable goods and transportation by ship will be applied with the aim of (a) minimizing the total cost function, defined as the sum of the ordering cost, holding cost, disposing cost and transportation costs, and (b) improving the supply chain sustainability by reducing environmental impact and waste disposal costs.

Keywords: Perishable goods, fuzzy reasoning, transport by ship, supply chain sustainability.

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Authors: Adeolu O. Dairo

Abstract:

Getting the consumer marketing strategy right is a crucial and complex task for firms with a large customer base such as mobile operators in a competitive mobile market. While empirical studies have made efforts to identify key constructs, no geospatial model has been developed to comprehensively assess the viability and interdependency of ground realities regarding the customer, competition, channel and the network quality of mobile operators. With this research, a geo-analytic framework is proposed for strategy formulation and allocation for mobile operators. Firstly, a fuzzy analytic network using a self-organizing feature map clustering technique based on inputs from managers and literature, which depicts the interrelationships amongst ground realities is developed. The model is tested with a mobile operator in the Nigeria mobile market. As a result, a customer-centric geospatial and visualization solution is developed. This provides a consolidated and integrated insight that serves as a transparent, logical and practical guide for strategic, tactical and operational decision making.

Keywords: Geospatial, geo-analytics, self-organizing map, customer-centric.

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Authors: M. M. Mon, S. S. Maw, Z. K. Oo

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Antioxidant activities of ethanolic extracts of Ardisia japonica Blume., Ageartum conyzoides Linn., and Cocculus hirsutus Linn Diels. leaves was determined qualitatively and quantitatively in this research. 1, 1-diphenyl-2-picrylhydrazyl (DPPH) free radical solution was used to investigate free radical scavenging activity of these leaves extracts. Ascorbic acid (Vitamin C) was used as the standard. In the present investigation, it is found that all of these extracts have remarkable antioxidant activities. The EC50 values of these ethanolic extracts were 12.72 μg/ml for A. japonica, 15.19 μg/ml for A. conyzoides, 10.68 μg/ml for C. hirsutus respectively. Among these Myanmar medicinal plants, C. hirsutus showed higher antioxidant activities as well as free radical scavenging activity than black tea (Camellia sinensis), the famous antioxidant, and A. japonica and A. conyzoides showed a rather lower antioxidant activity than tea extracts. According to results from bioassay with carrot discs infected with Agrobacterium tumefaciens, all extracts showed anti-tumor activity after 3 weeks of incubation. No gall was detected in carrot disks treated with C. hirsutus and A. japonica extracts in the dose of 100ppm and in carrot discs treated with A. conyzoides extract in the dose of 1000 ppm. Therefore, the research clearly indicates that these weedy plants of dry farm land are exceptionally advantageous for human health.

Keywords: Antioxidant, Anti-tumor activity, Carrot-discbioassay, DPPH

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Authors: Ali Ghaffari, Mansour Nikkhah Bahrami, Hesam Parsa

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In this paper a comprehensive model of a fossil fueled power plant (FFPP) is developed in order to evaluate the performance of a newly designed turbine follower controller. Considering the drawbacks of previous works, an overall model is developed to minimize the error between each subsystem model output and the experimental data obtained at the actual power plant. The developed model is organized in two main subsystems namely; Boiler and Turbine. Considering each FFPP subsystem characteristics, different modeling approaches are developed. For economizer, evaporator, superheater and reheater, first order models are determined based on principles of mass and energy conservation. Simulations verify the accuracy of the developed models. Due to the nonlinear characteristics of attemperator, a new model, based on a genetic-fuzzy systems utilizing Pittsburgh approach is developed showing a promising performance vis-à-vis those derived with other methods like ANFIS. The optimization constraints are handled utilizing penalty functions. The effect of increasing the number of rules and membership functions on the performance of the proposed model is also studied and evaluated. The turbine model is developed based on the equation of adiabatic expansion. Parameters of all evaluated models are tuned by means of evolutionary algorithms. Based on the developed model a fuzzy PI controller is developed. It is then successfully implemented in the turbine follower control strategy of the plant. In this control strategy instead of keeping control parameters constant, they are adjusted on-line with regard to the error and the error rate. It is shown that the response of the system improves significantly. It is also shown that fuel consumption decreases considerably.

Keywords: Attemperator, Evolutionary algorithms, Fossil fuelled power plant (FFPP), Fuzzy set theory, Gain scheduling

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Authors: Ali Asadian, Behzad Moshiri, Ali Khaki Sedigh, Caro Lucas

Abstract:

Most integrated inertial navigation systems (INS) and global positioning systems (GPS) have been implemented using the Kalman filtering technique with its drawbacks related to the need for predefined INS error model and observability of at least four satellites. Most recently, a method using a hybrid-adaptive network based fuzzy inference system (ANFIS) has been proposed which is trained during the availability of GPS signal to map the error between the GPS and the INS. Then it will be used to predict the error of the INS position components during GPS signal blockage. This paper introduces a genetic optimization algorithm that is used to update the ANFIS parameters with respect to the INS/GPS error function used as the objective function to be minimized. The results demonstrate the advantages of the genetically optimized ANFIS for INS/GPS integration in comparison with conventional ANFIS specially in the cases of satellites- outages. Coping with this problem plays an important role in assessment of the fusion approach in land navigation.

Keywords: Adaptive Network based Fuzzy Inference System (ANFIS), Genetic optimization, Global Positioning System (GPS), Inertial Navigation System (INS).

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Authors: N. Drir, L. Barazane, M. Loudini

Abstract:

It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.

Keywords: Maximum power point tracking, neural networks, photovoltaic, P&O.

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Authors: Kulaya Wimolwat, Panlop Chakravitthamrong, Neti Waranuch

Abstract:

Background: Seborrheic dermatitis is a common chronic skin condition affecting the face, scalp, chest, and trunk. The cause of seborrheic dermatitis is still unknown. Sebum production, lipid composition, hormone levels, and Malassezia species have been suggested as important factors in the development of seborrheic dermatitis. Curcuma aeruginosa Roxb. extract-containing cream with anti-inflammatory and anti-androgenic properties may be beneficial for treating mild to moderate facial seborrheic dermatitis. Objectives: We evaluated the efficacy and safety of 2% C. aeruginosa Roxb. extract-containing cream in the treatment of mild to moderate seborrheic dermatitis. Methods: This was a prospective, open-label, and non-comparative study. Ten adult patients clinically diagnosed with mild to moderate seborrheic dermatitis were enrolled in a four-week study. The 2% C. aeruginosa Roxb. cream was applied twice daily to a lesional area on the face for four weeks. The Scoring Index (SI) ranking system on days 14 and 28 was compared with that at baseline to determine the efficacy of treatment. The adverse events (burning sensation and erythema) were evaluated on days 14 and 28 to determine the safety of the treatment. Results: Significant improvement was observed in the reduction of the mean SI at day 14 (2.9) and 28 (1.4) compared to that at baseline (4.9). An adverse reaction was observed on day 14 (mild erythema 20% and mild burning sensation 10%) and was resolved by the end of the study. Conclusion: This open-label pilot study has shown that there was a significant improvement in the severity in these seborrheic patients and most reported they were satisfied with it. Reported adverse events were all mild.

Keywords: Anti-androgenic, antifungals, anti-inflammatory, Curcuma aeruginosa, seborrheic dermatitis, efficacy, safety.

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