Search results for: fuzzy inference model

Authors: Shihab-Uz-Zaman Shah, Sanjeeb Roy, Habiba Akter

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Keeping the high impact of the Ready-Made Garments (RMG) on the country’s economic growth in mind, this research paves a way for the implementation of Industry 4.0 in the garments industry of Bangladesh. At present, Industry 4.0 is a common buzzword representing the adoption of digital technologies in the production process to transform the existing industries into smart factories and create a great change in the global value chain. The RMG industry is the largest industrial sector of Bangladesh which provides 12.26% to its National GDP (Gross Domestic Product). The work starts with identifying possible enablers of Industry 4.0. To evaluate the enablers, a Multiple-Criteria Decision-Making (MCDM) procedure named Fuzzy Analytical Hierarchy Process (FAHP) was used. A questionnaire was developed as a part of a survey for collecting and analyzing expert opinions from relevant academicians and industrialists. The responses were eventually used as the input for the FAHP which helped to assign weight matrices to the enablers. This weight matrix indicated the level of importance of these enablers. The full paper will discuss the way of a successful evaluation of the enablers and implementation of Industry 4.0 by using these enablers.

Keywords: enablers, fuzzy AHP, industry 4.0, RMG sector

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Authors: M. De Iuliis, O. Kammouh, G. P. Cimellaro, S. Tesfamariam

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Community Resilience has gained a significant attention due to the recent unexpected natural and man-made disasters. Resilience is the process of maintaining livable conditions in the event of interruptions in normally available services. Estimating the resilience of systems, ranging from individuals to communities, is a formidable task due to the complexity involved in the process. The most challenging parameter involved in the resilience assessment is the 'downtime'. Downtime is the time needed for a system to recover its services following a disaster event. Estimating the exact downtime of a system requires a lot of inputs and resources that are not always obtainable. The uncertainties in the downtime estimation are usually handled using probabilistic methods, which necessitates acquiring large historical data. The estimation process also involves ignorance, imprecision, vagueness, and subjective judgment. In this paper, a fuzzy-based approach to estimate the downtime of building structures following earthquake events is proposed. Fuzzy logic can integrate descriptive (linguistic) knowledge and numerical data into the fuzzy system. This ability allows the use of walk down surveys, which collect data in a linguistic or a numerical form. The use of fuzzy logic permits a fast and economical estimation of parameters that involve uncertainties. The first step of the method is to determine the building’s vulnerability. A rapid visual screening is designed to acquire information about the analyzed building (e.g. year of construction, structural system, site seismicity, etc.). Then, a fuzzy logic is implemented using a hierarchical scheme to determine the building damageability, which is the main ingredient to estimate the downtime. Generally, the downtime can be divided into three main components: downtime due to the actual damage (DT1); downtime caused by rational and irrational delays (DT2); and downtime due to utilities disruption (DT3). In this work, DT1 is computed by relating the building damageability results obtained from the visual screening to some already-defined components repair times available in the literature. DT2 and DT3 are estimated using the REDITM Guidelines. The Downtime of the building is finally obtained by combining the three components. The proposed method also allows identifying the downtime corresponding to each of the three recovery states: re-occupancy; functional recovery; and full recovery. Future work is aimed at improving the current methodology to pass from the downtime to the resilience of buildings. This will provide a simple tool that can be used by the authorities for decision making.

Keywords: resilience, restoration, downtime, community resilience, fuzzy logic, recovery, damage, built environment

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Authors: Alaba M. Dare, Idris A. Ayinde, Adebayo M. Shittu, Sam O. Sam-Wobo

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Households' source of water is one of the core development indicators recently gaining pre-eminence in Nigeria. This study examined rural households' sources of water, Willingness to Pay (WTP) and factors influencing mean WTP. A cross-sectional survey which involved the use of questionnaire was used. A dichotomous choice (DC) with follow up was used as elicitation method. A multi-stage random sampling technique was used to select 437 rural households. Descriptive statistics and Tobit model were used for data estimation. The result revealed that about 70% fetched from unimproved water sources. Most (74.4%) respondents showed WTP for improved water sources. Age (p < 0.01), sex (p < 0.01), education (p < 0.01), occupation (p < 0.01), income (p < 0.01), price of water (P < 0.01), quantity of water (p < 0.01), household size (p < 0.01) and distance (p < 0.01) to existing water sources significantly influenced rural households' WTP for these services. The inference from this study showed that rural dweller sources of water is highly primitive and deplorable. Governments and stakeholders should prioritize the provision of rural water at an affordable price by rural dwellers.

Keywords: households, source of water, willingness to pay (WTP), tobit model

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Authors: Roseline Oghogho Osaseri, Osaseri E. I.

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Lassa fever is an epidemic hemorrhagic fever caused by the Lassa virus, an extremely virulent arena virus. This highly fatal disorder kills 10% to 50% of its victims, but those who survive its early stages usually recover and acquire immunity to secondary attacks. One of the major challenges in giving proper treatment is lack of fast and accurate diagnosis of the disease due to multiplicity of symptoms associated with the disease which could be similar to other clinical conditions and makes it difficult to diagnose early. This paper proposed an Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Lass Fever. In the design of the diagnostic system, four main attributes were considered as the input parameters and one output parameter for the system. The input parameters are Temperature on admission (TA), White Blood Count (WBC), Proteinuria (P) and Abdominal Pain (AP). Sixty-one percent of the datasets were used in training the system while fifty-nine used in testing. Experimental results from this study gave a reliable and accurate prediction of Lassa fever when compared with clinically confirmed cases. In this study, we have proposed Lassa fever diagnostic system to aid surgeons and medical healthcare practictionals in health care facilities who do not have ready access to Polymerase Chain Reaction (PCR) diagnosis to predict possible Lassa fever infection.

Keywords: anfis, lassa fever, medical diagnosis, soft computing

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Authors: Henry Lau, Dilupa Nakandala, Li Zhao

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All along the length of the supply chain, fresh food firms face the challenge of managing both product quality, due to the perishable nature of the products, and product cost. This paper develops a method to assist logistics managers upstream in the fresh food supply chain in making cost optimized decisions regarding transportation, with the objective of minimizing the total cost while maintaining the quality of food products above acceptable levels. Considering the case of multiple fresh food products collected from multiple farms being transported to a warehouse or a retailer, this study develops a total cost model that includes various costs incurred during transportation. The practical application of the model is illustrated by using several computational intelligence approaches including Genetic Algorithms (GA), Fuzzy Genetic Algorithms (FGA) as well as an improved Simulated Annealing (SA) procedure applied with a repair mechanism for efficiency benchmarking. We demonstrate the practical viability of these approaches by using a simulation study based on pertinent data and evaluate the simulation outcomes. The application of the proposed total cost model was demonstrated using three approaches of GA, FGA and SA with a repair mechanism. All three approaches are adoptable; however, based on the performance evaluation, it was evident that the FGA is more likely to produce a better performance than the other two approaches of GA and SA. This study provides a pragmatic approach for supporting logistics and supply chain practitioners in fresh food industry in making important decisions on the arrangements and procedures related to the transportation of multiple fresh food products to a warehouse from multiple farms in a cost-effective way without compromising product quality. This study extends the literature on cold supply chain management by investigating cost and quality optimization in a multi-product scenario from farms to a retailer and, minimizing cost by managing the quality above expected quality levels at delivery. The scalability of the proposed generic function enables the application to alternative situations in practice such as different storage environments and transportation conditions.

Keywords: cost optimization, food supply chain, fuzzy sets, genetic algorithms, product quality, transportation

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Authors: C. L. Wu, W. W. Tseng

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From the National Health Insurance (NHI) system was introduced in Taiwan in 2000, there have been some problems in transformed small-scale hospitals, such as mobility of patients, shortage of nursing staff, medical pipelines breaking fire compartments and insufficient fire protection systems. Due to shrinking of the funding scale and the aging society, fire safety in small-scale hospitals has recently given cause for concern. The aim of this study is to determine fire risk index for small-scale hospital through a systematic approach The selection of fire safety mitigation methods can be regarded as a multi-attribute decision making process which must be guaranteed by expert groups. First of all, identify and select safety related factors and identify evaluation criteria through literature reviews and experts group. Secondly, application of the Fuzzy Analytic Hierarchy Process method is used to ascertain a weighted value which enables rating of the importance each of the selected factors. Overall, Sprinkler type and Compartmentation are the most crucial indices in mitigating fire, that is to say, structural approach play an important role to decrease losses in fire events.

Keywords: Fuzzy Delphi Method, fuzzy analytic hierarchy, process risk assessment, fire events

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Authors: Jianhua Wang, Ying Zhou, Xi Zhang

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To establish the influential mechanism of learning engagement on interpreter’s performance, the present study submitted a questionnaire to a sample of 927 English major students with 804 valid ones and used the structural equation model as the basis for empirical analysis and statistical inference on the sample data. In order to explore the mechanism for interpreting learning engagement on student interpreters’ performance, a path model of interpreting processes with three variables of ‘input-environment-output’ was constructed. The results showed that the effect of each ‘environment’ variable on interpreting ability was different from and greater than the ‘input’ variable, and learning engagement was the greatest influencing factor. At the same time, peer interaction on interpreting performance has significant influence. Results suggest that it is crucial to provide effective guidance for optimizing learning engagement and interpreting teaching research by both improving the environmental support and building the platform of peer interaction, beginning with learning engagement.

Keywords: learning engagement, interpreting performance, interpreter training, English major students

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Authors: Shreya Pare, Parvin Akhter

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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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Authors: Hossein Gitinavard, Mohammad Hossein Fazel Zarandi

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

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

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Authors: Ghada Elshafei, A. Elazim Negm

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Recently, Green architecture becomes a significant way to a sustainable future. Green building designs involve finding the balance between comfortable homebuilding and sustainable environment. Moreover, the utilization of the new technologies such as artificial intelligence techniques are used to complement current practices in creating greener structures to keep the built environment more sustainable. The most common objectives are green buildings should be designed to minimize the overall impact of the built environment on ecosystems in general and particularly on human health and on the natural environment. This will lead to protecting occupant health, improving employee productivity, reducing pollution and sustaining the environmental. In green building design, multiple parameters which may be interrelated, contradicting, vague and of qualitative/quantitative nature are broaden to use. This paper presents a comprehensive critical state of art review of current practices based on fuzzy and its combination techniques. Also, presented how green architecture/building can be improved using the technologies that been used for analysis to seek optimal green solutions strategies and models to assist in making the best possible decision out of different alternatives.

Keywords: green architecture/building, technologies, optimization, strategies, fuzzy techniques, models

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Authors: Alex Vakaloudis, Juan Manuel Escano-Gonzalez

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Setting up a system to broadcast live lectures on the web is a procedure which on the surface does not require any serious technical skills mainly due to the facilities provided by popular learning management systems and their plugins. Nevertheless, producing a system of outstanding quality is a multidisciplinary and by no means a straightforward task. This complicatedness may be responsible for the delivery of an overall poor experience to the learners, and it calls for a formal rating framework that takes into account the diverse aspects of an architecture for synchronous video e-learning systems. We discuss the specifications of such a framework which at its final stage employs fuzzy logic technique to transform from qualitative to quantitative results.

Keywords: synchronous video, fuzzy logic, rating framework, e-learning

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Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

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Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

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Authors: Mehrdad Abkenari, Orod Zarrinkafsh, Mohsen Ramezan Shirazi

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Construction projects initiate in complicated dynamic environments and, due to the close relationships between project parameters and the unknown outer environment, they are faced with several uncertainties and risks. Success in time, cost and quality in large scale construction projects is uncertain in consequence of technological constraints, large number of stakeholders, too much time required, great capital requirements and poor definition of the extent and scope of the project. Projects that are faced with such environments and uncertainties can be well managed through utilization of the concept of risk management in project’s life cycle. Although the concept of risk is dependent on the opinion and idea of management, it suggests the risks of not achieving the project objectives as well. Furthermore, project’s risk analysis discusses the risks of development of inappropriate reactions. Since evaluation and prioritization of construction projects has been a difficult task, the network structure is considered to be an appropriate approach to analyze complex systems; therefore, we have used this structure for analyzing and modeling the issue. On the other hand, we face inadequacy of data in deterministic circumstances, and additionally the expert’s opinions are usually mathematically vague and are introduced in the form of linguistic variables instead of numerical expression. Owing to the fact that fuzzy logic is used for expressing the vagueness and uncertainty, formulation of expert’s opinion in the form of fuzzy numbers can be an appropriate approach. In other words, the evaluation and prioritization of construction projects on the basis of risk factors in real world is a complicated issue with lots of ambiguous qualitative characteristics. In this study, evaluated and prioritization the risk parameters and factors with fuzzy logy method by combination of three method DEMATEL (Decision Making Trial and Evaluation), ANP (Analytic Network Process) and TOPSIS (Technique for Order-Preference by Similarity Ideal Solution) on Construction Management.

Keywords: fuzzy logy, risk, prioritization, assessment

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Authors: T. Wanyama, B. Far

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

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

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Authors: Saleem Z. Ramadan

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This paper discusses the effects of using progressive Type-I right censoring on the design of the Simple Step Accelerated Life testing using Bayesian approach for Weibull life products under the assumption of cumulative exposure model. The optimization criterion used in this paper is to minimize the expected pre-posterior variance of the PTH percentile time of failures. The model variables are the stress changing time and the stress value for the first step. A comparison between the conventional and the progressive Type-I right censoring is provided. The results have shown that the progressive Type-I right censoring reduces the cost of testing on the expense of the test precision when the sample size is small. Moreover, the results have shown that using strong priors or large sample size reduces the sensitivity of the test precision to the censoring proportion. Hence, the progressive Type-I right censoring is recommended in these cases as progressive Type-I right censoring reduces the cost of the test and doesn't affect the precision of the test a lot. Moreover, the results have shown that using direct or indirect priors affects the precision of the test.

Keywords: reliability, accelerated life testing, cumulative exposure model, Bayesian estimation, progressive type-I censoring, Weibull distribution

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Authors: Wided Bakari, Patrice Bellot, Omar Trigui, Mahmoud Neji

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This article constitutes an opening to think of the modeling and analysis of Arabic texts in the context of a question-answer system. It is a question of exceeding the traditional approaches focused on morphosyntactic approaches. Furthermore, we present a new approach that analyze a text in order to extract correct answers then transform it to logical predicates. In addition, we would like to represent different levels of information within a text to answer a question and choose an answer among several proposed. To do so, we transform both the question and the text into logical forms. Then, we try to recognize all entailment between them. The results of recognizing the entailment are a set of text sentences that can implicate the user’s question. Our work is now concentrated on an implementation step in order to develop a system of question-answering in Arabic using techniques to recognize textual implications. In this context, the extraction of text features (keywords, named entities, and relationships that link them) is actually considered the first step in our process of text modeling. The second one is the use of techniques of textual implication that relies on the notion of inference and logic representation to extract candidate answers. The last step is the extraction and selection of the desired answer.

Keywords: NLP, Arabic language, question-answering, recognition text entailment, logic forms

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Authors: Ahmed A. D. Sarhan, Mum Wai Yip, M. Sayuti, Lim Siew Fen

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Ti6Al4V alloy is highly used in the automotive and aerospace industry due to its good machining characteristics. Micro EDM drilling is commonly used to drill micro hole on extremely hard material with very high depth to diameter ratio. In this study, the parameters of micro-electrical discharge machining (EDM) in drilling of Ti6Al4V alloy is optimized for higher machining accuracy with less hole-dilation and hole taper ratio. The micro-EDM machining parameters includes, peak current and pulse on time. Fuzzy analysis was developed to evaluate the machining accuracy. The analysis shows that hole-dilation and hole-taper ratio are increased with the increasing of peak current and pulse on time. However, the surface quality deteriorates as the peak current and pulse on time increase. The combination that gives the optimum result for hole dilation is medium peak current and short pulse on time. Meanwhile, the optimum result for hole taper ratio is low peak current and short pulse on time.

Keywords: Micro EDM, Ti-6Al-4V alloy, fuzzy logic based analysis, optimization, machining accuracy

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Authors: M. Doumi, A. Miloudi, A.G. Aissaoui, K. Tahir, C. Belfedal, S. Tahir

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The studies on the photovoltaic system are extensively increasing because of a large, secure, essentially exhaustible and broadly available resource as a future energy supply. However, the output power induced in the photovoltaic modules is influenced by an intensity of solar cell radiation, temperature of the solar cells and so on. Therefore, to maximize the efficiency of the photovoltaic system, it is necessary to track the maximum power point of the PV array, for this Maximum Power Point Tracking (MPPT) technique is used. These algorithms are based on the Perturb-Observe, Conductance-Increment and the Fuzzy Logic methods. These techniques vary in many aspects as: simplicity, convergence speed, digital or analogical implementation, sensors required, cost, range of effectiveness, and in other aspects. This paper presents a comparative study of three widely-adopted MPPT algorithms; their performance is evaluated on the energy point of view, by using the simulation tool Simulink®, considering different solar irradiance variations. MPPT using fuzzy logic shows superior performance and more reliable control to the other methods for this application.

Keywords: photovoltaic system, MPPT, perturb and observe (P&O), incremental conductance (INC), Fuzzy Logic (FLC)

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Authors: Oluwayemisi O. Alaba, John O. Olaomi

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The 2013 Nigerian Demographic Health Survey (NDHS) data was used to investigate the determinants of family size in Nigeria using the geo-additive model. The fixed effect of categorical covariates were modelled using the diffuse prior, P-spline with second-order random walk for the nonlinear effect of continuous variable, spatial effects followed Markov random field priors while the exchangeable normal priors were used for the random effects of the community and household. The Negative Binomial distribution was used to handle overdispersion of the dependent variable. Inference was fully Bayesian approach. Results showed a declining effect of secondary and higher education of mother, Yoruba tribe, Christianity, family planning, mother giving birth by caesarean section and having a partner who has secondary education on family size. Big family size is positively associated with age at first birth, number of daughters in a household, being gainfully employed, married and living with partner, community and household effects.

Keywords: Bayesian analysis, family size, geo-additive model, negative binomial

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Authors: Abdullah Eqal Al Mazrooei

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In this work, a new nonlinear model will be introduced. The model is in the state-space form. The nonlinearity of this model is in the state equation where the state vector is multiplied by its self. This technique makes our model generalizes many famous models as Lotka-Volterra model and Lorenz model which have many applications in the real life. We will apply our new model to estimate the wind speed by using a new nonlinear estimator which suitable to work with our model.

Keywords: nonlinear systems, state-space model, Kronecker product, nonlinear estimator

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Authors: Elahe Memari, Ahmad Aslizadeh, Ahmad Memari

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Today strategic planning is counted as the most important duties of senior directors in each organization. Strategic planning allows the organizations to implement compiled strategies and reach higher competitive benefits than their competitors. The present research work tries to prepare and rank the strategies form effective factors on strategic planning in fulfillment of the State Road Management and Transportation Organization in order to indicate the role of organizational factors in efficiency of the process to organization managers. Connection between six main factors in fulfillment of State Road Management and Transportation Organization were studied here, including Improvement of Strategic Thinking in senior managers, improvement of the organization business process, rationalization of resources allocation in different parts of the organization, coordination and conformity of strategic plan with organization needs, adjustment of organization activities with environmental changes, reinforcement of organizational culture. All said factors approved by implemented tests and then ranked using fuzzy multivariate decision-making technique.

Keywords: Fuzzy TOPSIS, improvement of organization business process, multivariate decision-making, strategic planning

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: Kamalendu Pal

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This paper describes the main features of a knowledge-based system evaluation method. System evaluation is placed in the context of a hybrid legal decision-support system, Advisory Support for Home Settlement in Divorce (ASHSD). Legal knowledge for ASHSD is represented in two forms, as rules and previously decided cases. Besides distinguishing the two different forms of knowledge representation, the paper outlines the actual use of these forms in a computational framework that is designed to generate a plausible solution for a given case, by using rule-based reasoning (RBR) and case-based reasoning (CBR) in an integrated environment. The nature of suitability assessment of a solution has been considered as a multiple criteria decision making process in ASHAD evaluation. The evaluation was performed by a combination of discussions and questionnaires with different user groups. The answers to questionnaires used in this evaluations method have been measured as a combination of linguistic variables, fuzzy numbers, and by using defuzzification process. The results show that the designed evaluation method creates suitable mechanism in order to improve the performance of the knowledge-based system.

Keywords: case-based reasoning, fuzzy number, legal decision-support system, linguistic variable, rule-based reasoning, system evaluation

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Authors: Talha Ali Khan

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This paper presents an adaptive neuro-fuzzy interference system (ANFIS), which is applied to a hybrid stepper motor (HSM) to regulate its speed. The dynamic response of the HSM with the ANFIS controller is studied during the starting process and under different load disturbance. The effectiveness of the proposed controller is compared with that of the conventional PI controller. The proposed method solves the problem of nonlinearities and load changes of the HSM drives. The proposed controller ensures fast and precise dynamic response with an excellent steady state performance. Matlab/Simulink program is used for this dynamic simulation study.

Keywords: stepper motor, hybrid, ANFIS, speed control

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Authors: Germán Díaz Flórez, Carlos Alberto Olvera Olvera, Domingo José Gómez Meléndez, Francisco Eneldo López Monteagudo

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In recent decades, population growth has exerted great pressure on natural resources. Two of the most scarce and difficult to obtain resources, arable land, and water, are closely interrelated, to the satisfaction of the demand for food production. In Mexico, the agricultural sector uses more than 70% of water consumption. Therefore, maximize the efficiency of current production systems is inescapable. It is essential to utilize techniques and tools that will enable us to the significant savings of water, labor and fertilizer. In this study, we present a production module of hydroponic green forage (HGF), which is a viable alternative in the production of livestock feed in the semi-arid and arid zones. The equipment in addition to having a forage production module, has a climate and irrigation control system that operated with photovoltaics. The climate control, irrigation and power management is based on fuzzy control techniques. The fuzzy control provides an accurate method in the design of controllers for nonlinear dynamic physical phenomena such as temperature and humidity, besides other as lighting level, aeration and irrigation control using heuristic information. In this working, firstly refers to the production of the hydroponic green forage, suitable weather conditions and fertigation subsequently presents the design of the production module and the design of the controller. A simulation of the behavior of the production module and the end results of actual operation of the equipment are presented, demonstrating its easy design, flexibility, robustness and low cost that represents this equipment in the primary sector.

Keywords: fuzzy, climate control system, hydroponic green forage, forage production module

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Authors: Md. Moniruzzaman, Thirayoot Limanond

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Being the most visible indicator, the transport system of a city points out how developed the city is. Dhaka megacity holds a mixed composition of motorized and non-motorized modes of transport and the number of vehicle figure is escalating over times. And this obviously poses associated environmental costs like air pollution, noise etc. which is degrading the quality of life in the city. Eventually sustainable transport or more importantly green transport from environmental point of view has become a prime choice to the transport professionals in order to cope up the crisis. Currently the city authority is planning to execute such sustainable transport systems that could serve the pressing demand of the present and meet the future needs effectively. This study focuses on the selection and evaluation of green transportation systems among potential alternatives on a priority basis. In this paper, Fuzzy TOPSIS - a multi-criteria decision method is presented to find out the most prioritized alternative. In the first step, Twenty-one individual specific criteria for sustainability assessment are selected. In the following step, experts provide linguistic ratings to the potential alternatives with respect to the selected criteria. The approach is used to generate aggregate scores for sustainability assessment and selection of the best alternative. In the third step, a sensitivity analysis is performed to understand the influence of criteria weights on the decision making process. The key strength of fuzzy TOPSIS approach is its practical applicability having a generation of good quality solution even under uncertainty.

Keywords: green transport, multi-criteria decision approach, urban transportation system, sustainability assessment, fuzzy theory, uncertainty

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Authors: Mohammad Vahed, Ana Sadeghitohidi, Majid Vahed, Hiroki Takahashi

Abstract:

In the genomics field, the huge amounts of data have produced by the next-generation sequencers (NGS). Data volumes are very rapidly growing, as it is postulated that more than one billion bases will be produced per year in 2020. The growth rate of produced data is much faster than Moore's law in computer technology. This makes it more difficult to deal with genomics data, such as storing data, searching information, and finding the hidden information. It is required to develop the analysis platform for genomics big data. Cloud computing newly developed enables us to deal with big data more efficiently. Hadoop is one of the frameworks distributed computing and relies upon the core of a Big Data as a Service (BDaaS). Although many services have adopted this technology, e.g. amazon, there are a few applications in the biology field. Here, we propose a new algorithm to more efficiently deal with the genomics big data, e.g. sequencing data. Our algorithm consists of two parts: First is that BDaaS is applied for handling the data more efficiently. Second is that the hybrid method of MapReduce and Fuzzy logic is applied for data processing. This step can be parallelized in implementation. Our algorithm has great potential in computational analysis of genomics big data, e.g. de novo genome assembly and sequence similarity search. We will discuss our algorithm and its feasibility.

Keywords: big data, fuzzy logic, MapReduce, Hadoop, cloud computing

Procedia PDF Downloads 275

Authors: Jirarat Teeravaraprug, Usawadee Inklay

Abstract:

This paper gave an attempt in prioritizing information technologies that organizations should give concentration. The case study was organizations in the automotive assembly industry in Thailand. Data were first collected to gather all information technologies known and used in the automotive assembly industry in Thailand. Five experts from the industries were surveyed based on the concept of fuzzy DEMATEL. The information technologies were categorized into six groups, which were communication, transaction, planning, organization management, warehouse management, and transportation. The cause groups of information technologies for each group were analysed and presented. Moreover, the relationship between the used and the significant information technologies was given. Discussions based on the used information technologies and the research results are given.

Keywords: information technology, automotive assembly industry, fuzzy DEMATEL

Procedia PDF Downloads 316

Authors: N. Ould cherchali, M. S. Boucherit, L. Barazane, A. Morsli

Abstract:

Photovoltaic power is widely used to supply isolated or unpopulated areas (lighting, pumping, etc.). Great advantage is that this source is inexhaustible, it offers great safety in use and it is clean. But the dynamic models used to describe a photovoltaic system are complicated and nonlinear and due to nonlinear I-V and P–V characteristics of photovoltaic generators, a maximum power point tracking technique (MPPT) is required to maximize the output power. In this paper, two online techniques of maximum power point tracking using robust controller for photovoltaic systems are proposed, the first technique use fuzzy logic controller (FLC) and the second use sliding mode controller (SMC) for photovoltaic systems. The two maximum power point tracking controllers receive the partial derivative of power as inputs, and the output is the duty cycle corresponding to maximum power. A Photovoltaic generator with Boost converter is developed using MATLAB/Simulink to verify the preferences of the proposed techniques. SMC technique provides a good tracking speed in fast changing irradiation and when the irradiation changes slowly or is constant the panel power of FLC technique presents a much smoother signal with less fluctuations.

Keywords: fuzzy logic controller, maximum power point, photovoltaic system, tracker, sliding mode controller

Procedia PDF Downloads 521

Authors: Chih-Chieh Yang, Chung-Neng Huang

Abstract:

In power system, how to improve the fault diagnosis technology of transmission line has always been the primary goal of power grid operators. In recent years, due to the rise of green energy, the addition of all kinds of distributed power also has an impact on the stability of the power system. Because the smart meters are with the function of data recording and bidirectional transmission, the adaptive Fuzzy Neural inference system, ANFIS, as well as the artificial intelligence that has the characteristics of learning and estimation in artificial intelligence. For transmission network, in order to avoid misjudgment of the fault type and location due to the input of these unstable power sources, combined with the above advantages of smart meter and ANFIS, a method for identifying fault types and location of faults is proposed in this study. In ANFIS training, the bus voltage and current information collected by smart meters can be trained through the ANFIS tool in MATLAB to generate fault codes to identify different types of faults and the location of faults. In addition, due to the uncertainty of distributed generation, a wind power system is added to the transmission network to verify the diagnosis correctness of the study. Simulation results show that the method proposed in this study can correctly identify the fault type and location of fault with more efficiency, and can deal with the interference caused by the addition of unstable power sources.

Keywords: ANFIS, fault diagnosis, power system, smart meter

Procedia PDF Downloads 121