Search results for: type 2 fuzzy control
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16674

Search results for: type 2 fuzzy control

16254 The Use of Artificial Intelligence in the Prevention of Micro and Macrovascular Complications in Type Diabetic Patients in Low and Middle-Income Countries

Authors: Ebere Ellison Obisike, Justina N. Adalikwu-Obisike

Abstract:

Artificial intelligence (AI) is progressively transforming health and social care. With the rapid invention of various electronic devices, machine learning, and computing systems, the use of AI istraversing many health and social care practices. In this systematic review of journal and grey literature, this study explores how the applications of AI might promote the prevention of micro and macrovascular complications in type 1 diabetic patients. This review focuses on the use of a digitized blood glucose meter and the application of insulin pumps for the effective management of type 1 diabetes in low and middle-income countries. It is projected that the applications of AI may assist individuals with type 1 diabetes to monitor and control their blood glucose level and prevent the early onset of micro and macrovascular complications.

Keywords: artificial intelligence, blood glucose meter, insulin pump, low and middle-income countries, micro and macrovascular complications, type 1 diabetes

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16253 FESA: Fuzzy-Controlled Energy-Efficient Selective Allocation and Reallocation of Tasks Among Mobile Robots

Authors: Anuradha Banerjee

Abstract:

Energy aware operation is one of the visionary goals in the area of robotics because operability of robots is greatly dependent upon their residual energy. Practically, the tasks allocated to robots carry different priority and often an upper limit of time stamp is imposed within which the task needs to be completed. If a robot is unable to complete one particular task given to it the task is reallocated to some other robot. The collection of robots is controlled by a Central Monitoring Unit (CMU). Selection of the new robot is performed by a fuzzy controller called Task Reallocator (TRAC). It accepts the parameters like residual energy of robots, possibility that the task will be successfully completed by the new robot within stipulated time, distance of the new robot (where the task is reallocated) from distance of the old one (where the task was going on) etc. The proposed methodology increases the probability of completing globally assigned tasks and saves huge amount of energy as far as the collection of robots is concerned.

Keywords: energy-efficiency, fuzzy-controller, priority, reallocation, task

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16252 Seismic Resistant Mechanism of Two-by-four Wooden Frame with Vibration Control Device

Authors: Takumi Ito, Kurumi Kurokawa, Dong Hang Wu, Takashi Nagumo, Haruhiko Hirata

Abstract:

The structural system of wooden house by two-by-four method is widely adopted in any countries, and a various type of vibration control system for building structures has been developed on country with frequent earthquake. In this study, a vibration control device called “Scaling Frame” (SF) is suggested, and which is applied to wooden two-by-four method structures. This paper performs the experimental study to investigate the restoring force characteristics of two-by-four with SF device installed. The seismic resistant performance is estimated experimentally, and also the applicability and effectiveness are discussing.

Keywords: two-by-four method, seismic vibration control, horizontally loading test, restoring force characteristics

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16251 Material Handling Equipment Selection Using Fuzzy AHP Approach

Authors: Priyanka Verma, Vijaya Dixit, Rishabh Bajpai

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This research paper is aimed at selecting appropriate material handling equipment among the given choices so that the automation level in material handling can be enhanced. This work is a practical case scenario of material handling systems in consumer electronic appliances manufacturing organization. The choices of material handling equipment among which the decision has to be made are Automated Guided Vehicle’s (AGV), Autonomous Mobile Robots (AMR), Overhead Conveyer’s (OC) and Battery Operated Trucks/Vehicle’s (BOT). There is a need of attaining a certain level of automation in order to reduce human interventions in the organization. This requirement of achieving certain degree of automation can be attained by material handling equipment’s mentioned above. The main motive for selecting above equipment’s for study was solely based on corporate financial strategy of investment and return obtained through that investment made in stipulated time framework. Since the low cost automation with respect to material handling devices has to be achieved hence these equipment’s were selected. Investment to be done on each unit of this equipment is less than 20 lakh rupees (INR) and the recovery period is less than that of five years. Fuzzy analytic hierarchic process (FAHP) is applied here for selecting equipment where the four choices are evaluated on basis of four major criteria’s and 13 sub criteria’s, and are prioritized on the basis of weight obtained. The FAHP used here make use of triangular fuzzy numbers (TFN). The inability of the traditional AHP in order to deal with the subjectiveness and impreciseness in the pair-wise comparison process has been improved in the FAHP. The range of values for general rating purposes for all decision making parameters is kept between 0 and 1 on the basis of expert opinions captured on shop floor. These experts were familiar with operating environment and shop floor activity control. Instead of generating exact value the FAHP generates the ranges of values to accommodate the uncertainty in decision-making process. The four major criteria’s selected for the evaluation of choices of material handling equipment’s available are materials, technical capabilities, cost and other features. The thirteen sub criteria’s listed under these following four major criteria’s are weighing capacity, load per hour, material compatibility, capital cost, operating cost and maintenance cost, speed, distance moved, space required, frequency of trips, control required, safety and reliability issues. The key finding shows that among the four major criteria selected, cost is emerged as the most important criteria and is one of the key decision making aspect on the basis of which material equipment selection is based on. While further evaluating the choices of equipment available for each sub criteria it is found that AGV scores the highest weight in most of the sub-criteria’s. On carrying out complete analysis the research shows that AGV is the best material handling equipment suiting all decision criteria’s selected in FAHP and therefore it is beneficial for the organization to carry out automated material handling in the facility using AGV’s.

Keywords: fuzzy analytic hierarchy process (FAHP), material handling equipment, subjectiveness, triangular fuzzy number (TFN)

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16250 Construction Time - Cost Trade-Off Analysis Using Fuzzy Set Theory

Authors: V. S. S. Kumar, B. Vikram, G. C. S. Reddy

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Time and cost are the two critical objectives of construction project management and are not independent but intricately related. Trade-off between project duration and cost are extensively discussed during project scheduling because of practical relevance. Generally when the project duration is compressed, the project calls for an increase in labor and more productive equipments, which increases the cost. Thus, the construction time-cost optimization is defined as a process to identify suitable construction activities for speeding up to attain the best possible savings in both time and cost. As there is hidden tradeoff relationship between project time and cost, it might be difficult to predict whether the total cost would increase or decrease as a result of compressing the schedule. Different combinations of duration and cost for the activities associated with the project determine the best set in the time-cost optimization. Therefore, the contractors need to select the best combination of time and cost to perform each activity, all of which will ultimately determine the project duration and cost. In this paper, the fuzzy set theory is used to model the uncertainties in the project environment for time-cost trade off analysis.

Keywords: fuzzy sets, uncertainty, qualitative factors, decision making

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16249 Integrative-Cyclical Approach to the Study of Quality Control of Resource Saving by the Use of Innovation Factors

Authors: Anatoliy A. Alabugin, Nikolay K. Topuzov, Sergei V. Aliukov

Abstract:

It is well known, that while we do a quantitative evaluation of the quality control of some economic processes (in particular, resource saving) with help innovation factors, there are three groups of problems: high uncertainty of indicators of the quality management, their considerable ambiguity, and high costs to provide a large-scale research. These problems are defined by the use of contradictory objectives of enhancing of the quality control in accordance with innovation factors and preservation of economic stability of the enterprise. The most acutely, such factors are felt in the countries lagging behind developed economies of the world according to criteria of innovativeness and effectiveness of management of the resource saving. In our opinion, the following two methods for reconciling of the above-mentioned objectives and reducing of conflictness of the problems are to solve this task most effectively: 1) the use of paradigms and concepts of evolutionary improvement of quality of resource-saving management in the cycle "from the project of an innovative product (technology) - to its commercialization and update parameters of customer value"; 2) the application of the so-called integrative-cyclical approach which consistent with complexity and type of the concept, to studies allowing to get quantitative assessment of the stages of achieving of the consistency of these objectives (from baseline of imbalance, their compromise to achievement of positive synergies). For implementation, the following mathematical tools are included in the integrative-cyclical approach: index-factor analysis (to identify the most relevant factors); regression analysis of relationship between the quality control and the factors; the use of results of the analysis in the model of fuzzy sets (to adjust the feature space); method of non-parametric statistics (for a decision on the completion or repetition of the cycle in the approach in depending on the focus and the closeness of the connection of indicator ranks of disbalance of purposes). The repetition is performed after partial substitution of technical and technological factors ("hard") by management factors ("soft") in accordance with our proposed methodology. Testing of the proposed approach has shown that in comparison with the world practice there are opportunities to improve the quality of resource-saving management using innovation factors. We believe that the implementation of this promising research, to provide consistent management decisions for reducing the severity of the above-mentioned contradictions and increasing the validity of the choice of resource-development strategies in terms of parameters of quality management and sustainability of enterprise, is perspective. Our existing experience in the field of quality resource-saving management and the achieved level of scientific competence of the authors allow us to hope that the use of the integrative-cyclical approach to the study and evaluation of the resulting and factor indicators will help raise the level of resource-saving characteristics up to the value existing in the developed economies of post-industrial type.

Keywords: integrative-cyclical approach, quality control, evaluation, innovation factors. economic sustainability, innovation cycle of management, disbalance of goals of development

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16248 Islamic Corporate Social Responsibility Disclosure and Financial Performance on Islamic Banking in Indonesia

Authors: Yasmin Umar Assegaf, Falikhatun, Salamah Wahyuni

Abstract:

This study aims to provide empirical evidence about the influence of Islamic Corporate Social Responsibility Disclosures of the financial performance of Islamic banking with the characteristics of the company, as a control variable in Islamic banking in Indonesia. ICSR disclosures are an independent variable, while the Financial Performance is the dependent variable (proxied by Return on Assets (ROA), Return on Equity (ROE), Income Expense Ratio (IER), and Non-net Interest Margin (NIM). The control variables used are firm size, firm age and the type of audit. The population of the study was all Islamic Banks (BUS) operate in Indonesia. The research sample is Islamic Commercial Bank which has existed in Indonesia since 2002 and publishes financial statements between the years of 2007-2011. The sample of the study were include 31 Annual Report published. The results of this study concluded that there are significant influences between the ICSR Disclosures and financial performance. The disclosure is partially effect on ROA, IER and NIM, whereas there is no influence on ROE. Further result shows that all control variables (Firm Size, Age, and Type of Audit Companies) does not have any influence on ICSR Disclosures in Indonesia. This research gives a suggestion for further research to compare these ICSR disclosures in Indonesia with ICSR disclosures in other countries that have Islamic banking, by using other measure variables of financial performance, to get more comprehensive model and real picture.

Keywords: ROA, ROE, IER, NIM, company size, age of the company, audit type, Islamic banking

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16247 The Stability Analysis and New Torque Control Strategy of Direct-Driven PMSG Wind Turbines

Authors: Jun Liu, Feihang Zhou, Gungyi Wang

Abstract:

This paper expounds on the direct-driven PMSG wind power system control strategy, and analyses the stability conditions of the system. The direct-driven PMSG wind power system may generate the intense mechanical vibration, when wind speed changes dramatically. This paper proposes a new type of torque control strategy, which increases the system damping effectively, mitigates mechanical vibration of the system, and enhances the stability conditions of the system. The simulation results verify the reliability of the new torque control strategy.

Keywords: damping, direct-driven PMSG wind power system, mechanical vibration, torque control

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16246 Correlation between Microalbuminuria and Hypertension in Type 2 Diabetic Patients

Authors: Alia Ali, Azeem Taj, Muhammed Joher Amin, Farrukh Iqbal, Zafar Iqbal

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Background: Hypertension is commonly found in patients with Diabetic Kidney Disease (DKD). Microalbuminuria is the first clinical sign of involvement of kidneys in patients with type 2 diabetes. Uncontrolled hypertension induces a higher risk of cardiovascular events, including death, increasing proteinuria and progression to kidney disease. Objectives: To determine the correlation between microalbuminuria and hypertension and their association with other risk factors in type 2 diabetic patients. Methods: One hundred and thirteen type 2 diabetic patients were screened for microalbuminuria and raised blood pressure, attending the diabetic clinic of Shaikh Zayed Hospital, Lahore, Pakistan. The study was conducted from November 2012 to June 2013. Results: Patients were divided into two groups. Group 1, those with normoalbuminuria (n=63) and Group 2, those having microalbuminuria (n=50). Group 2 patients showed higher blood pressure values as compared to Group 1. The results were statistically significant and showed poor glycemic control as a contributing risk factor. Conclusion: The study concluded that there is high frequency of hypertension among type 2 diabetics but still much higher among those having microalbuminuria. So, early recognition of renal dysfunction through detection of microalbuminuria and to start treatment without any delay will confer future protection from end-stage renal disease as well as hypertension and its complications in type 2 diabetic patients.

Keywords: hypertension, microalbuminuria, diabetic kidney disease, type 2 Diabetes mellitus

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16245 Implementation of Inference Fuzzy System as a Valuation Subsidiary is Based Particle Swarm Optimization for Solves the Issue of Decision Making in Middle Size Soccer Robot League

Authors: Zahra Abdolkarimi, Naser Zouri

Abstract:

Nowadays, there is unbelievable growing of Robots created a collection of complex and motivate subject in robotic and intellectual ornate, also it made a mechatronics style base of theoretical and technical way in Robocop. Additionally, robotics system recommended RoboCup factor as a provider of some standardization and testing method in case of computer discussion widely. The actual purpose of RoboCup is creating independent team of robots in 2050 based of FiFa roles to bring the victory in compare of world star team. In addition, decision making of robots depends to environment reaction, self-player and rival player with using inductive Fuzzy system valuation subsidiary to solve issue of robots in land game. The measure of selection in compare with other methods depends to amount of victories percentage in the same team that plays accidently. Consequences, shows method of our discussion is the best way for Particle Swarm Optimization and Fuzzy system compare to other decision of robotics algorithmic.

Keywords: PSO algorithm, inference fuzzy system, chaos theory, soccer robot league

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16244 Representing a Methodology for Refinement of Strategic Objectives in Strategy Map Establishment: Combining Quality Function Deployment and Fuzzy Screening

Authors: Bijan Nahavandi, Navid Jafarinejad, Somayeh Mehrafzad

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Strategy maps represent the way of value creation in in each organization. Nowadays, implementation of strategy is the main concern for all organizations. Strategy map establishment is the start-up point of strategy implementation and this shows the critical importance of this concept. After some years past since emergence of strategy map, there are some shortcomings in its methodology that frequently quoted by many of researchers. One of these shortcomings is the shortage of a mechanism for refinement of objectives candidate for entrance to map. Organizations in practice have obsession and avidity to determine more number of objectives in strategy map. This study wants to represent a step by step approach to help obviate this problem using quality function deployment (QFD) as a helpful tool and fuzzy screening method. Finally, represented approach applies in a practical case and conclusions have been explained.

Keywords: balanced scorecard, fuzzy screening, house of strategic objectives (HoSO), quality function deployment, strategy map

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16243 Multidrug Therapies For HIV: Hybrid On-Off, Hysteresis On-Off Control and Simple STI

Authors: Magno Enrique Mendoza Meza

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This paper deals with the comparison of three control techniques: the hysteresis on-off control (HyOOC), the hybrid on-off control (HOOC) and the simple Structured Treatment Interruptions (sSTI). These techniques are applied to the mathematical model developed by Kirschner and Webb. To compare these techniques we use a cost functional that minimize the wild-type virus population and the mutant virus population, but the main objective is to minimize the systemic cost of treatment and maximize levels of healthy CD4+ T cells. HyOOC, HOOC, and sSTI are applied to the drug therapies using a reverse transcriptase and protease inhibitors; simulations show that these controls maintain the uninfected cells in a small, bounded neighborhood of a pre-specified level. The controller HyOOC and HOOC are designed by appropriate choice of virtual equilibrium points.

Keywords: virus dynamics, on-off control, hysteresis, multi-drug therapies

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16242 A Relative Entropy Regularization Approach for Fuzzy C-Means Clustering Problem

Authors: Ouafa Amira, Jiangshe Zhang

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Clustering is an unsupervised machine learning technique; its aim is to extract the data structures, in which similar data objects are grouped in the same cluster, whereas dissimilar objects are grouped in different clusters. Clustering methods are widely utilized in different fields, such as: image processing, computer vision , and pattern recognition, etc. Fuzzy c-means clustering (fcm) is one of the most well known fuzzy clustering methods. It is based on solving an optimization problem, in which a minimization of a given cost function has been studied. This minimization aims to decrease the dissimilarity inside clusters, where the dissimilarity here is measured by the distances between data objects and cluster centers. The degree of belonging of a data point in a cluster is measured by a membership function which is included in the interval [0, 1]. In fcm clustering, the membership degree is constrained with the condition that the sum of a data object’s memberships in all clusters must be equal to one. This constraint can cause several problems, specially when our data objects are included in a noisy space. Regularization approach took a part in fuzzy c-means clustering technique. This process introduces an additional information in order to solve an ill-posed optimization problem. In this study, we focus on regularization by relative entropy approach, where in our optimization problem we aim to minimize the dissimilarity inside clusters. Finding an appropriate membership degree to each data object is our objective, because an appropriate membership degree leads to an accurate clustering result. Our clustering results in synthetic data sets, gaussian based data sets, and real world data sets show that our proposed model achieves a good accuracy.

Keywords: clustering, fuzzy c-means, regularization, relative entropy

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16241 Prospectivity Mapping of Orogenic Lode Gold Deposits Using Fuzzy Models: A Case Study of Saqqez Area, Northwestern Iran

Authors: Fanous Mohammadi, Majid H. Tangestani, Mohammad H. Tayebi

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This research aims to evaluate and compare Geographical Information Systems (GIS)-based fuzzy models for producing orogenic gold prospectivity maps in the Saqqez area, NW of Iran. Gold occurrences are hosted in sericite schist and mafic to felsic meta-volcanic rocks in this area and are associated with hydrothermal alterations that extend over ductile to brittle shear zones. The predictor maps, which represent the Pre-(Source/Trigger/Pathway), syn-(deposition/physical/chemical traps) and post-mineralization (preservation/distribution of indicator minerals) subsystems for gold mineralization, were generated using empirical understandings of the specifications of known orogenic gold deposits and gold mineral systems and were then pre-processed and integrated to produce mineral prospectivity maps. Five fuzzy logic operators, including AND, OR, Fuzzy Algebraic Product (FAP), Fuzzy Algebraic Sum (FAS), and GAMMA, were applied to the predictor maps in order to find the most efficient prediction model. Prediction-Area (P-A) plots and field observations were used to assess and evaluate the accuracy of prediction models. Mineral prospectivity maps generated by AND, OR, FAP, and FAS operators were inaccurate and, therefore, unable to pinpoint the exact location of discovered gold occurrences. The GAMMA operator, on the other hand, produced acceptable results and identified potentially economic target sites. The P-A plot revealed that 68 percent of known orogenic gold deposits are found in high and very high potential regions. The GAMMA operator was shown to be useful in predicting and defining cost-effective target sites for orogenic gold deposits, as well as optimizing mineral deposit exploitation.

Keywords: mineral prospectivity mapping, fuzzy logic, GIS, orogenic gold deposit, Saqqez, Iran

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16240 Health Assessment of Power Transformer Using Fuzzy Logic

Authors: Yog Raj Sood, Rajnish Shrivastava, Anchal Wadhwa

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Power transformer is one of the electrical equipment that has a central and critical role in the power system. In order to avoid power transformer failure, information system that provides the transformer condition is needed. This paper presents an information system to know the exact situations prevailing within the transformer by declaring its health index. Health index of a transformer is decided by considering several diagnostic tools. The current work deals with UV-Vis, IFT, FP, BDV and Water Content. UV/VIS results have been pre-accessed using separate FL controller for concluding with the Furan contents. It is broadly accepted that the life of a power transformer is the life of the oil/ paper insulating system. The method relies on the use of furan analysis (insulation paper), and other oil analysis results as a means to declare health index. Fuzzy logic system is used to develop the information system. The testing is done on 5 samples of oil of transformers of rating 132/66 KV to obtain the results and results are analyzed using fuzzy logic model.

Keywords: interfacial tension analyzer (ift), flash point (fp), furfuraldehyde (fal), health index

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16239 The Classical Conditioning Effect of Animated Spokes-Characters

Authors: Chia-Ching Tsai, Ting-Hsiu Chen

Abstract:

This paper adopted 2X2 factorial design. One factor was experimental versus control condition. The other factor was types of animated spokescharacter, and one of the two levels was expert type, and the other level is attractive type. In the study, we use control versus experimental conditioning and types of animated spokescharacter as independent variables, and brand attitude as dependent variable to examine the conditioning effect of types of animated spokescharacter on brand attitude. There are 123 subjects participating in the experiment. The results showed conditioning group presents that animated spokescharacter has significantly superior effect of product endorsement in contrast to non-conditioning one, while there is no significant impact of types of animated spokescharacter on brand attitude.

Keywords: classical conditioning, animated spokes-character, brand attitude, factorial design

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16238 Comparative Study Performance of the Induction Motor between SMC and NLC Modes Control

Authors: A. Oukaci, R. Toufouti, D. Dib, l. Atarsia

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This article presents a multitude of alternative techniques to control the vector control, namely the nonlinear control and sliding mode control. Moreover, the implementation of their control law applied to the high-performance to the induction motor with the objective to improve the tracking control, ensure stability robustness to parameter variations and disturbance rejection. Tests are performed numerical simulations in the Matlab/Simulink interface, the results demonstrate the efficiency and dynamic performance of the proposed strategy.

Keywords: Induction Motor (IM), Non-linear Control (NLC), Sliding Mode Control (SMC), nonlinear sliding surface

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16237 Earthquake Identification to Predict Tsunami in Andalas Island, Indonesia Using Back Propagation Method and Fuzzy TOPSIS Decision Seconder

Authors: Muhamad Aris Burhanudin, Angga Firmansyas, Bagus Jaya Santosa

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Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction.

Keywords: earthquake, fuzzy TOPSIS, neural network, tsunami

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16236 Chaos Fuzzy Genetic Algorithm

Authors: Mohammad Jalali Varnamkhasti

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The genetic algorithms have been very successful in handling difficult optimization problems. The fundamental problem in genetic algorithms is premature convergence. This paper, present a new fuzzy genetic algorithm based on chaotic values instead of the random values in genetic algorithm processes. In this algorithm, for initial population is used chaotic sequences and then a new sexual selection proposed for selection mechanism. In this technique, the population is divided such that the male and female would be selected in an alternate way. The layout of the male and female chromosomes in each generation is different. A female chromosome is selected by tournament selection size from the female group. Then, the male chromosome is selected, in order of preference based on the maximum Hamming distance between the male chromosome and the female chromosome or The highest fitness value of male chromosome (if more than one male chromosome is having the maximum Hamming distance existed), or Random selection. The selections of crossover and mutation operators are achieved by running the fuzzy logic controllers, the crossover and mutation probabilities are varied on the basis of the phenotype and genotype characteristics of the chromosome population. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving p-median problems published in the literature.

Keywords: genetic algorithm, fuzzy system, chaos, sexual selection

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16235 The Effect of Radish (Raphanus Sativus L.) Leaves Ethanol Extract on Blood Glucose Levels in Streptozotocin-Nicotinamide-Induced Type-2 Diabetic Rats

Authors: Satria B. Mahathma, Asri Hendrawati

Abstract:

Background: Diabetes mellitus (DM) is a metabolic disorder syndrome characterized by chronic hyperglycemia. The number of people with diabetes rose from 108 million in 1980 to 422 million in 2014. In general, almost 90% of the prevalence of DM is type 2 DM which marked by insulin resistance and decreased receptor sensitivity. Aside from conventional antidiabetic therapy, the utilization of medicinal plants as alternative medicine has beneficial effects in diabetic patients. Flavonoid contents in radish leaves such as quercetin, pelargonidin, and kaempferol are thought to have antidiabetic activity on decreasing blood glucose levels by tricyclic nucleotide modulation of pancreatic beta cells and ameliorating insulin resistance. This study aimed to determine the effect of variant concentration of radish leaves ethanol extract on blood glucose levels in diabetic rats. Method: This study used pretest-posttest control group design by using 16 male Wistar rats which were induced type-2 diabetic by streptozotocin 60 mg/kg BW-nicotinamide 120 mg/kg BW intraperitoneally. Rats who had developed type-2 DM later divided randomly into 4 groups; negative control received placebo, positive control received glibenclamide 5 mg/kg BW/day, rats intervention I and intervention II received 100% and 50% of radish leaves ethanol extract, respectively. Treatments were administered orally for four weeks. The blood glucose levels were measured using the Enzymatic Colorimetric Test “GOD-PAP”. Data were analyzed by the dependent t-test for pretest-posttest intervention difference and one-way ANOVA followed by post hoc test to determine the significant difference of each treatment to obtain the significant data. Result: The result revealed that intervention group had lower blood glucose levels mean than control group which the lowest was intervention II group (negative control: 540,9 ± 191,7 mg/dl, positive control: 494, 97 ± 64,91 mg/dl, intervention I: 301,92 ± 165,70 mg/dl, and intervention II group: 276,1 ± 139,02 mg/dl. Intervention II group had the highest antidiabetic activity, followed by the intervention I group with the amount of decrease in blood glucose levels were -151,85 ± 77,43 mg/dl and -11,08 ± 186,62 mg/dl, however negative and positive control group didn’t have antidiabetic activity. The dependent t-test result showed there is a significant difference in decreasing blood glucose levels in the intervention II pretest-posttest intervention (p=0,03) while the other group didn’t. Data analyzed by one-way ANOVA also revealed the intervention II group significantly declined blood glucose levels compared to the negative and positive control group (p = 0,033 and p=0,032, respectively). Conclusion: There is a significant effect of radish leaves ethanol extract on blood glucose levels in streptozotocin-nicotinamide-induced diabetic rats with the optimal therapeutic effect at a concentration of 50%.

Keywords: blood glucose levels, medicinal plant, radish leaves, type-2 diabetes mellitus

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16234 Optimal Driving Strategies for a Hybrid Street Type Motorcycle: Modelling and Control

Authors: Jhon Vargas, Gilberto Osorio-Gomez, Tatiana Manrique

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This work presents an optimal driving strategy proposal for a 125 c.c. street-type hybrid electric motorcycle with a parallel configuration. The results presented in this article are complementary regarding the control proposal of a hybrid motorcycle. In order to carry out such developments, a representative dynamic model of the motorcycle is used, in which also are described different optimization functionalities for predetermined driving modes. The purpose is to implement an off-line optimal driving strategy which distributes energy to both engines by minimizing an objective torque requirement function. An optimal dynamic contribution is found from the optimization routine, and the optimal percentage contribution for vehicle cruise speed is implemented in the proposed online PID controller.

Keywords: dynamic model, driving strategies, parallel hybrid motorcycle, PID controller, optimization

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16233 A Diurnal Light Based CO₂ Elevation Strategy for Up-Scaling Chlorella sp. Production by Minimizing Oxygen Accumulation

Authors: Venkateswara R. Naira, Debasish Das, Soumen K. Maiti

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Achieving high cell densities of microalgae under obligatory light-limiting and high light conditions of diurnal (low-high-low variations of daylight intensity) sunlight are further limited by CO₂ supply and dissolved oxygen (DO) accumulation in large-scale photobioreactors. High DO levels cause low growth due to photoinhibition and/or photorespiration. Hence, scalable elevated CO₂ levels (% in air) and their effect on DO accumulation in a 10 L cylindrical membrane photobioreactor (a vertical tubular type) are studied in the present study. The CO₂ elevation strategies; biomass-based, pH control based (types II & I) and diurnal light based, were explored to study the growth of Chlorella sp. FC2 IITG under single-sided LED lighting in the laboratory, mimicking diurnal sunlight. All the experiments were conducted in fed-batch mode by maintaining N and P sources at least 50% of initial concentrations of the optimized BG-11 medium. It was observed that biomass-based (2% - 1st day, 2.5% - 2nd day and 3% - thereafter) and well-known pH control based, type-I (5.8 pH throughout) strategies were found lethal for FC2 growth. In both strategies, the highest peak DO accumulation of 150% air saturation was resulted due to high photosynthetic activity caused by higher CO₂ levels. In the pH control based type-I strategy, automatically resulted CO₂ levels for pH control were recorded so high (beyond the inhibition range, 5%). However, pH control based type-II strategy (5.8 – 2 days, 6.3 – 3 days, 6.7 – thereafter) showed final biomass titer up to 4.45 ± 0.05 g L⁻¹ with peak DO of 122% air saturation; high CO₂ levels beyond 5% (in air) were recorded thereafter. Thus, it became sustainable for obtaining high biomass. Finally, a diurnal light based (2% - low light, 2.5 % - medium light and 3% - high light) strategy was applied on the basis of increasing/decreasing photosynthesis due to increase/decrease in diurnal light intensity. It has resulted in maximum final biomass titer of 5.33 ± 0.12 g L⁻¹, with total biomass productivity of 0.59 ± 0.01 g L⁻¹ day⁻¹. The values are remarkably higher than constant 2% CO₂ level (final biomass titer: 4.26 ± 0.09 g L⁻¹; biomass productivity: 0.27 ± 0.005 g L⁻¹ day⁻¹). However, 135% air saturation of peak DO was observed. Thus, the diurnal light based elevation should be further improved by using CO₂ enriched N₂ instead of air. To the best of knowledge, the light-based CO₂ elevation strategy is not reported elsewhere.

Keywords: Chlorella sp., CO₂ elevation strategy, dissolved oxygen accumulation, diurnal light based CO₂ elevation, high cell density, microalgae, scale-up

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16232 Hybrid Fuzzy Weighted K-Nearest Neighbor to Predict Hospital Readmission for Diabetic Patients

Authors: Soha A. Bahanshal, Byung G. Kim

Abstract:

Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

Procedia PDF Downloads 165
16231 Internal Leakage Analysis from Pd to Pc Port Direction in ECV Body Used in External Variable Type A/C Compressor

Authors: M. Iqbal Mahmud, Haeng Muk Cho, Seo Hyun Sang, Wang Wen Hai, Chang Heon Yi, Man Ik Hwang, Dae Hoon Kang

Abstract:

Solenoid operated electromagnetic control valve (ECV) playing an important role for car’s air conditioning control system. ECV is used in external variable displacement swash plate type compressor and controls the entire air conditioning system by means of a pulse width modulation (PWM) input signal supplying from an external source (controller). Complete form of ECV contains number of internal features like valve body, core, valve guide, plunger, guide pin, plunger spring, bellows etc. While designing the ECV; dimensions of different internal items must meet the standard requirements as it is quite challenging. In this research paper, especially the dimensioning of ECV body and its three pressure ports through which the air/refrigerant passes are considered. Here internal leakage test analysis of ECV body is being carried out from its discharge port (Pd) to crankcase port (Pc) when the guide valve is placed inside it. The experiments have made both in ordinary and digital system using different assumptions and thereafter compare the results.

Keywords: electromagnetic control valve (ECV), leakage, pressure port, valve body, valve guide

Procedia PDF Downloads 386
16230 Harmonic Assessment and Mitigation in Medical Diagonesis Equipment

Authors: S. S. Adamu, H. S. Muhammad, D. S. Shuaibu

Abstract:

Poor power quality in electrical power systems can lead to medical equipment at healthcare centres to malfunction and present wrong medical diagnosis. Equipment such as X-rays, computerized axial tomography, etc. can pollute the system due to their high level of harmonics production, which may cause a number of undesirable effects like heating, equipment damages and electromagnetic interferences. The conventional approach of mitigation uses passive inductor/capacitor (LC) filters, which has some drawbacks such as, large sizes, resonance problems and fixed compensation behaviours. The current trends of solutions generally employ active power filters using suitable control algorithms. This work focuses on assessing the level of Total Harmonic Distortion (THD) on medical facilities and various ways of mitigation, using radiology unit of an existing hospital as a case study. The measurement of the harmonics is conducted with a power quality analyzer at the point of common coupling (PCC). The levels of measured THD are found to be higher than the IEEE 519-1992 standard limits. The system is then modelled as a harmonic current source using MATLAB/SIMULINK. To mitigate the unwanted harmonic currents a shunt active filter is developed using synchronous detection algorithm to extract the fundamental component of the source currents. Fuzzy logic controller is then developed to control the filter. The THD without the active power filter are validated using the measured values. The THD with the developed filter show that the harmonics are now within the recommended limits.

Keywords: power quality, total harmonics distortion, shunt active filters, fuzzy logic

Procedia PDF Downloads 455
16229 Integration of Hybrid PV-Wind in Three Phase Grid System Using Fuzzy MPPT without Battery Storage for Remote Area

Authors: Thohaku Abdul Hadi, Hadyan Perdana Putra, Nugroho Wicaksono, Adhika Prajna Nandiwardhana, Onang Surya Nugroho, Heri Suryoatmojo, Soedibjo

Abstract:

Access to electricity is now a basic requirement of mankind. Unfortunately, there are still many places around the world which have no access to electricity, such as small islands, where there could potentially be a factory, a plantation, a residential area, or resorts. Many of these places might have substantial potential for energy generation such us Photovoltaic (PV) and Wind turbine (WT), which can be used to generate electricity independently for themselves. Solar energy and wind power are renewable energy sources which are mostly found in nature and also kinds of alternative energy that are still developing in a rapid speed to help and meet the demand of electricity. PV and Wind has a characteristic of power depend on solar irradiation and wind speed based on geographical these areas. This paper presented a control methodology of hybrid small scale PV/Wind energy system that use a fuzzy logic controller (FLC) to extract the maximum power point tracking (MPPT) in different solar irradiation and wind speed. This paper discusses simulation and analysis of the generation process of hybrid resources in MPP and power conditioning unit (PCU) of Photovoltaic (PV) and Wind Turbine (WT) that is connected to the three-phase low voltage electricity grid system (380V) without battery storage. The capacity of the sources used is 2.2 kWp PV and 2.5 kW PMSG (Permanent Magnet Synchronous Generator) -WT power rating. The Modeling of hybrid PV/Wind, as well as integrated power electronics components in grid connected system, are simulated using MATLAB/Simulink.

Keywords: fuzzy MPPT, grid connected inverter, photovoltaic (PV), PMSG wind turbine

Procedia PDF Downloads 336
16228 A Fuzzy Inference System for Predicting Air Traffic Demand Based on Socioeconomic Drivers

Authors: Nur Mohammad Ali, Md. Shafiqul Alam, Jayanta Bhusan Deb, Nowrin Sharmin

Abstract:

The past ten years have seen significant expansion in the aviation sector, which during the previous five years has steadily pushed emerging countries closer to economic independence. It is crucial to accurately forecast the potential demand for air travel to make long-term financial plans. To forecast market demand for low-cost passenger carriers, this study suggests working with low-cost airlines, airports, consultancies, and governmental institutions' strategic planning divisions. The study aims to develop an artificial intelligence-based methods, notably fuzzy inference systems (FIS), to determine the most accurate forecasting technique for domestic low-cost carrier demand in Bangladesh. To give end users real-world applications, the study includes nine variables, two sub-FIS, and one final Mamdani Fuzzy Inference System utilizing a graphical user interface (GUI) made with the app designer tool. The evaluation criteria used in this inquiry included mean square error (MSE), accuracy, precision, sensitivity, and specificity. The effectiveness of the developed air passenger demand prediction FIS is assessed using 240 data sets, and the accuracy, precision, sensitivity, specificity, and MSE values are 90.83%, 91.09%, 90.77%, and 2.09%, respectively.

Keywords: aviation industry, fuzzy inference system, membership function, graphical user interference

Procedia PDF Downloads 50
16227 Qualitative Measurement of Literacy

Authors: Indrajit Ghosh, Jaydip Roy

Abstract:

Literacy rate is an important indicator for measurement of human development. But this is not a good one to capture the qualitative dimension of educational attainment of an individual or a society. The overall educational level of an area is an important issue beyond the literacy rate. The overall educational level can be thought of as an outcome of the educational levels of individuals. But there is no well-defined algorithm and mathematical model available to measure the overall educational level of an area. A heuristic approach based on accumulated experience of experts is effective one. It is evident that fuzzy logic offers a natural and convenient framework in modeling various concepts in social science domain. This work suggests the implementation of fuzzy logic to develop a mathematical model for measurement of educational attainment of an area in terms of Education Index. The contribution of the study is two folds: conceptualization of “Education Profile” and proposing a new mathematical model to measure educational attainment in terms of “Education Index”.

Keywords: education index, education profile, fuzzy logic, literacy

Procedia PDF Downloads 297
16226 Optimized and Secured Digital Watermarking Using Fuzzy Entropy, Bezier Curve and Visual Cryptography

Authors: R. Rama Kishore, Sunesh

Abstract:

Recent development in the usage of internet for different purposes creates a great threat for the copyright protection of the digital images. Digital watermarking can be used to address the problem. This paper presents detailed review of the different watermarking techniques, latest trends in the field of secured, robust and imperceptible watermarking. It also discusses the different optimization techniques used in the field of watermarking in order to improve the robustness and imperceptibility of the method. Different measures are discussed to evaluate the performance of the watermarking algorithm. At the end, this paper proposes a watermarking algorithm using (2, 2) share visual cryptography and Bezier curve based algorithm to improve the security of the watermark. The proposed method uses fractional transformation to improve the robustness of the copyright protection of the method. The algorithm is optimized using fuzzy entropy for better results.

Keywords: digital watermarking, fractional transform, visual cryptography, Bezier curve, fuzzy entropy

Procedia PDF Downloads 342
16225 The Fuzzy Logic Modeling of Performance Driver Seat’s Localised Cooling and Heating in Standard Car Air Conditioning System

Authors: Ali Ates, Sadık Ata, Kevser Dincer

Abstract:

In this study, performance of the driver seat‘s localized cooling and heating in a standard car air conditioning system was experimentally investigated and modeled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modeling technique. Climate function at automobile is an important variable for thermal comfort. In the experimental study localized heating and cooling performances have been examined with the aid of a mechanism established to a vehicle. The equipment’s used in the experimental setup/mechanism have been provided and assembled. During the measurement, the status of the performance level has been determined. Input parameters revolutions per minute and time; output parameters car seat cooling temperature, car back cooling temperature, car seat heating temperature, car back heating temperature were described by RBMTF if-the rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between experimental data and RBMTF is done by using statistical methods like absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF could be successfully used in standard car air conditioning system.

Keywords: air conditioning system, cooling-heating, RMBTF modelling, car seat

Procedia PDF Downloads 333