Search results for: intuitionistic fuzzy cycle

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: Heeba A. Gurku

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Introduction: Cone Beam CT(CBCT) images play an integral part in proper patient positioning in cancer patients undergoing radiation therapy treatment. But these images are low in quality. The purpose of this study is to generate high-quality synthetic CT images from CBCT using generative models. Material and Methods: This study utilized two datasets from The Cancer Imaging Archive (TCIA) 1) Lung cancer dataset of 20 patients (with full view CBCT images) and 2) Pancreatic cancer dataset of 40 patients (only 27 patients having limited view images were included in the study). Cycle Generative Adversarial Networks (GAN) and its variant Attention Guided Generative Adversarial Networks (AGGAN) models were used to generate the synthetic CTs. Models were evaluated by visual evaluation and on four metrics, Structural Similarity Index Measure (SSIM), Peak Signal Noise Ratio (PSNR) Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), to compare the synthetic CT and original CT images. Results: For pancreatic dataset with limited view CBCT images, our study showed that in Cycle GAN model, MAE, RMSE, PSNR improved from 12.57to 8.49, 20.94 to 15.29 and 21.85 to 24.63, respectively but structural similarity only marginally increased from 0.78 to 0.79. Similar, results were achieved with AGGAN with no improvement over Cycle GAN. However, for lung dataset with full view CBCT images Cycle GAN was able to reduce MAE significantly from 89.44 to 15.11 and AGGAN was able to reduce it to 19.77. Similarly, RMSE was also decreased from 92.68 to 23.50 in Cycle GAN and to 29.02 in AGGAN. SSIM and PSNR also improved significantly from 0.17 to 0.59 and from 8.81 to 21.06 in Cycle GAN respectively while in AGGAN SSIM increased to 0.52 and PSNR increased to 19.31. In both datasets, GAN models were able to reduce artifacts, reduce noise, have better resolution, and better contrast enhancement. Conclusion and Recommendation: Both Cycle GAN and AGGAN were significantly able to reduce MAE, RMSE and PSNR in both datasets. However, full view lung dataset showed more improvement in SSIM and image quality than limited view pancreatic dataset.

Keywords: CT images, CBCT images, cycle GAN, AGGAN

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Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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Authors: Mehran Fadaeinasab, Hamed Karimian, Najihah Mohd Hashim, Hapipah Mohd Ali

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In this study, three indole alkaloids namely; rauvolfine B, macusine B, and isoreserpiline have been isolated from the dichloromethane crude extract of Rauvolfia reflexa bark (Apocynaceae). The structural elucidation of the isolated compounds has been performed using spectral methods such as UV, IR, MS, 1D, and 2D NMR. Rauvolfine B showed anti proliferation activity on HCT-116 cancer cell line, its cytotoxicity induction was observed using MTT assay in eight different cell lines. Annexin-V is serving as a marker for apoptotic cells and the Annexin-V-FITC assay was carried out to observe the detection of cell-surface Phosphatidylserine (PS). Apoptosis was confirmed by using caspase-8 and -9 assays. Cell cycle arrest was also investigated using flowcytometric analysis. rauvolfine B had exhibited significantly higher cytotoxicity against HCT-116 cell line. The treatment significantly arrested HCT-116 cells in the S phase. Together, the results presented in this study demonstrated that rauvolfine B inhibited the proliferation of HCT-116 cells and programmed cell death followed by cell cycle arrest.

Keywords: apocynacea, indole alkaloid, apoptosis, cell cycle arrest

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Authors: Yusri Yusof, Chen Wong Keong

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This paper presents the implementation details of a Relational Database Management System of a STEP-technology product model repository. It is able support the implementation of any EXPRESS language schema, although it has been primarily implemented to support mechanical product life cycle applications. This database support the input of STEP part 21 file format from CAD in geometrical and topological data format and support a range of queries for mechanical product life cycle applications. This proposed relational database management system uses entity-to-table method (R1) rather than type-to-table method (R4). The two mapping methods have their own strengths and drawbacks.

Keywords: RDBMS, CAD, ISO 10303, part-21 file

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Authors: Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini

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In vapor cycle systems, the mass flow sensor plays a key role for different monitoring and control purposes. However, physical sensors can be inaccurate, heavy, cumbersome, expensive, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor, based on other standard sensors, is a good alternative. This paper has two main objectives. Firstly, a data-driven model using a convolutional neural network is proposed to estimate the mass flow of the compressor. We show that it significantly outperforms the standard polynomial regression model (thermodynamic maps) in terms of the standard MSE metric and engineer performance metrics. Secondly, a semi-automatic segmentation method is proposed to compute the engineer performance metrics for real datasets, as the standard MSE metric may pose risks in analyzing the dynamic behavior of vapor cycle systems.

Keywords: deep learning, convolutional neural network, vapor cycle system, virtual sensor

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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: Sharon Yunger, Liat Altman, Yuval Garini, Yaron Shav-Tal

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Understanding the dynamics of transcription in living cells has improved since the development of quantitative fluorescence-based imaging techniques. We established a method for following transcription from a single copy gene in living cells. A gene tagged with MS2 repeats, used for mRNA tagging, in its 3' UTR was integrated into a single genomic locus. The actively transcribing gene was detected and analyzed by fluorescence in situ hybridization (FISH) and live-cell imaging. Several cell clones were created that differed in the promoter regulating the gene. Thus, comparative analysis could be obtained without the risk of different position effects at each integration site. Cells in S/G2 phases could be detected exhibiting two adjacent transcription sites on sister chromatids. A sharp reduction in the transcription levels was observed as cells progressed along the cell cycle. We hypothesized that a change in chromatin structure acts as a general mechanism during the cell cycle leading to down-regulation in the activity of some genes. We addressed this question by treating the cells with chromatin decondensing agents. Quantifying and imaging the treated cells suggests that chromatin structure plays a role both in regulating transcriptional levels along the cell cycle, as well as in limiting an active gene from reaching its maximum transcription potential at any given time. These results contribute to understanding the role of chromatin as a regulator of gene expression.

Keywords: cell cycle, living cells, nucleus, transcription

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Authors: Grzegorz Baranski, Piotr Kacejko, Konrad Pietrykowski, Mariusz Duk

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This paper discusses a model of a bus-driving scheme. Rapid changes in speed result in a constantly changing kinetic energy accumulated in a bus mass and an increased fuel consumption due to hardly recuperated kinetic energy. The model is based on the results achieved from chassis dynamometer, airport and city street researches. The verified model was applied to simulate the mechanical energy recuperation during the Japanese JE05 Emission Test Cycle. The simulations were performed for several values of vehicle mass. The research results show that fuel economy is impacted by kinetic energy recuperation.

Keywords: heavy duty vehicle, city bus, Japanese JE05 test cycle, kinetic energy, simulations

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Authors: Ohud Alharbi, Emily Baines

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The animation industry is one of the creative industries that have attracted recent historiographical attention. However, there has been very limited research on Saudi Arabian and wider Arabian animation industries, while there are a large number of studies that have covered this issue for North America, Europe and East Asia. The existing studies show that developed countries such as USA, Japan and the UK have reached the Maturity stage in their animation industry life-cycle. On the other hand, developing countries that are still in the Introduction phase of the industry life-cycle face challenges to improve their industry. Saudi Arabia is one of the countries whose animation industry is still in its infancy. Thus, the aim of this paper is to address the main barriers that hinder the evolution of the industry life-cycle for Saudi animation – challenges that are also relevant to many other early stage industries in developing countries. These barriers have been analysed using the early mobility barriers defined by Porter, to provide a conceptual structure for defining recommendations to enable the transition to a strong Growth phase industry. This study utilized qualitative methods to collect data, which involved in-depth interviews, document analysis and observations. It also undertook a comparative case study approach to investigate the animation industry life-cycle, with three selected case studies that have a more developed industry than Saudi animation. Case studies include: the United Kingdom, which represents a Mature animation industry; Egypt, which represents an established Growth stage industry; and the United Arab of Emirates, which is an early Growth stage industry. This study suggests adopting appropriate strategies that arise as findings from the comparative case studies, to overcome barriers and facilitate the growth of the Saudi animation industry.

Keywords: barriers, industry life-cycle, Saudi animation, industry

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Authors: Onur Özdemir, M.Erhan ORHAN

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Knowledge Development (KD) is just one of the important phases of Knowledge Management (KM). KD is the phase in which intelligence is used to see the big picture. In order to understand whether information is important or not, we have to use the intelligence cycle that includes four main steps: aiming, collecting data, processing and utilizing. KD also needs these steps. To make a precise decision, the decision maker has to be aware of his subordinates’ ideas. If the decision maker ignores the ideas of his subordinates or participants of the organization, it is not possible for him to get the target. KD is a way of using wisdom to accumulate the puzzle. If the decision maker does not bring together the puzzle pieces, he cannot get the big picture, and this shows its effects on the battlefield. In order to understand the battlefield, the decision maker has to use the intelligence cycle. To convert information to knowledge, KD is the main means for the intelligence cycle. On the other hand, the “Z Generation” born after the millennium are really the game changers. They have different attitudes from their elders. Their understanding of life is different - the definition of freedom and independence have different meanings to them than others. Decision makers have to consider these factors and rethink their decisions accordingly. This article tries to explain the relation between KD and Generation Z. KD is the main method of target managing. But if leaders neglect their people, the world will be seeing much more movements like the Arab Spring and other insurgencies.

Keywords: knowledge development, knowledge management, generation Z, intelligence cycle

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Authors: Halimi Mohamed Taher, Kordoghli Bassem, Ben Hassen Mohamed, Sakli Faouzi

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Textile and clothing manufacturing industry is based largely on subcontracting system. Choosing the right subcontractor became a strategic decision that can affect the financial position of the company and even his market position. Subcontracting firms in Tunisia are lead to define an appropriate selection process which takes into account several quantitative and qualitative criteria. In this study, a methodology is proposed that includes a Fuzzy Analytic Hierarchy Process (AHP) in order to incorporate the ambiguities and uncertainties in qualitative decision. Best subcontractors for two Tunisian firms are determined based on model results.

Keywords: AHP, subcontractor, multicriteria, selection

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Authors: Pathinathan Theresanathan, Ajay Minj

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Ignatian Discernment Process (IDP) is an intense decision-making tool to decide on life-issues. Decisions are influenced by various factors outside of the decision maker and inclination within. This paper develops IDP in the context of Fuzzy Multi-criteria Decision Making (FMCDM) process. Extended VIKOR method is a decision-making method which encompasses even conflict situations and accommodates weightage to various issues. Various aspects of IDP, namely three ways of decision making and tactics of inner desires, are observed, analyzed and articulated within the frame work of fuzzy rules. The decision-making situations are broadly categorized into two types. The issues outside of the decision maker influence the person. The inner feeling also plays vital role in coming to a conclusion. IDP integrates both the categories using Extended VIKOR method. Case studies are carried out and analyzed with FMCDM process. Finally, IDP is verified with an illustrative case study and results are interpreted. A confused person who could not come to a conclusion is able to take decision on a concrete way of life through IDP. The proposed IDP model recommends an integrated and committed approach to value-based decision making.

Keywords: AHP, FMCDM, IDP, ignatian discernment, MCDM, VIKOR

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Authors: Ketseas Dimitris

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In this work, we investigate the effect of noise on a classical two-degree-of-freedom pitch-plunge aeroelastic system. The inlet velocity of the flow is modelled as a stochastically varying parameter by the Ornstein-Uhlenbeck (OU) stochastic process. The system is a 2D airfoil, and the elastic problem is simulated using linear springs. We study the manifestation of Limit Cycle Oscillations (LCO) that correspond to the varying fluid velocity under the dynamic stall regime. We aim to delve into the unexplored facets of the classical pitch-plunge aeroelastic system, seeking a comprehensive understanding of how parametric noise influences the occurrence of LCO and expands the boundaries of its known behavior.

Keywords: aerodynamics, aeroelasticity, computational fluid mechanics, stall flutter, stochastical processes, limit cycle oscillation

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Authors: Michelle Zeyuan Ma, Hermann Heilmeier

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Recently, meat production ecosystem impacts initiated many hot discussions and researchers, and it is a difficult implementation to reduce such impacts due to the demand of meat products. It calls for better management and control of ecosystem impacts from every aspects of meat production. This article analyzes the ecosystem impacts of meat production based on meat products life cycle. The analysis shows that considerable ecosystem impacts are caused by different meat production steps: initial establishment phase, animal raising, slaughterhouse processing, meat consumption, and wastes management. Based on this analysis, the impacts are summarized as: leading factor for biodiversity loss; water waste, land use waste and land degradation; greenhouse gases emissions; pollution to air, water, and soil; related major diseases. The article also provides a discussion on a solution-sustainable food system, which could help in reducing ecosystem impacts. The analysis method is based on the life cycle level, it provides a concept of the whole meat industry ecosystem impacts, and the analysis result could be useful to manage or control meat production ecosystem impacts from investor, producer and consumer sides.

Keywords: eutrophication, life cycle based analysis, sustainable food, waste management

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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: 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: R Palson Kennedy, P.Kiran Sai

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This article introduces machine learning (ML) researchers to the hurdles that geoscience problems present, as well as the opportunities for improvement in both ML and geosciences. This article presents a review from the data life cycle perspective to meet that need. Numerous facets of geosciences present unique difficulties for the study of intelligent systems. Geosciences data is notoriously difficult to analyze since it is frequently unpredictable, intermittent, sparse, multi-resolution, and multi-scale. The first half addresses data science’s essential concepts and theoretical underpinnings, while the second section contains key themes and sharing experiences from current publications focused on each stage of the data life cycle. Finally, themes such as open science, smart data, and team science are considered.

Keywords: Data science, intelligent system, machine learning, big data, data life cycle, recent development, geo science

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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: Richard Madanda, Paul Isaac Musasizi, Sandy Stevens Tickodri-Togboa, Doreen Orishaba, Victor Tumwine

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New vehicle concepts targeting specific geographical markets are designed to satisfy a unique set of road and load requirements. The KIIRA-EV SMACK (KES) hybrid vehicle is designed in Uganda for the East African market. The engine and generator added to the KES electric power train serve both as the range extender and the power assist. In this paper, the design consideration taken to achieve the proper management of the on-board power from the batteries and engine-generator based on the specific drive cycle are presented. To harness the fuel- efficiency benefits of the power train, a specific control philosophy operating the engine and generator at the most efficient speed- torque and speed-power regions is presented. By using a suitable model developed in MATLAB using Simulink and Stateflow, preliminary results show that the steady-state response of the vehicle for a particular hypothetical drive cycle mimicking the expected drive conditions in the city and highway traffic is sufficient.

Keywords: control strategy, drive cycle, hybrid vehicle, simulation

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Authors: Seon Tae Kim, Robert Hegner, Goksel Ozuylasi, Panagiotis Stathopoulos, Eberhard Nicke

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High-temperature heat pumps (HTHP) that can supply heat at temperatures above 200°C can enhance the energy efficiency of industrial processes and reduce the CO₂ emissions connected with the heat supply of these processes. In the current work, the thermodynamic performance of 3 different vapor compression cycles, which use R-718 (water) as a working medium, have been evaluated by using a commercial process simulation tool (EBSILON Professional). All considered cycles use two-stage vapor compression with intercooling between stages. The main aim of the study is to compare different intercooling strategies and study possible heat recovery scenarios within the intercooling process. This comparison has been carried out by computing the coefficient of performance (COP), the heat supply temperature level, and the respective mass flow rate of water for all cycle architectures. With increasing temperature difference between the heat source and heat sink, ∆T, the COP values decreased as expected, and the highest COP value was found for the cycle configurations where both compressors have the same pressure ratio (PR). The investigation on the HTHP capacities with optimized PR and exergy analysis has also been carried out. The internal heat exchanger cycle with the inward direction of secondary flow (IHX-in) showed a higher temperature level and exergy efficiency compared to other cycles. Moreover, the available operating range was estimated by considering mechanical limitations.

Keywords: high temperature heat pump, industrial process, vapor compression cycle, R-718 (water), thermodynamic analysis

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Authors: Aldona Kluczek

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In recent years, manufacturing processes have interacted with sustainability issues realized in the cost-effective ways that minimalize energy, decrease negative impacts on the environment and are safe for society. However, the attention has been on separate sustainability assessment methods considering energy and material flow, energy consumption, and emission release or process control. In this paper, the energy-led sustainability assessment approach combining the methods: energy Life Cycle Assessment to assess environmental impact, Life Cycle Cost to analyze costs, and Social Life Cycle Assessment through ‘energy LCA-based value stream map’, is used to assess the energy sustainability of the hardwood lumber manufacturing process in terms of technologies. The approach integrating environmental, economic and social issues can be visualized in the considered energy-efficient technologies on the map of an energy LCA-related (input and output) inventory data. It will enable the identification of efficient technology of a given process to be reached, through the effective analysis of energy flow. It is also indicated that interventions in the considered technology should focus on environmental, economic improvements to achieve energy sustainability. The results have indicated that the most intense energy losses are caused by a cogeneration technology. The environmental impact analysis shows that a substantial reduction by 34% can be achieved with the improvement of it. From the LCC point of view, the result seems to be cost-effective, when done at that plant where the improvement is used. By demonstrating the social dimension, every component of the energy of plant labor use in the life-cycle process of the lumber production has positive energy benefits. The energy required to install the energy-efficient technology amounts to 30.32 kJ compared to others components of the energy of plant labor and it has the highest value in terms of energy-related social indicators. The paper depicts an example of hardwood lumber production in order to prove the applicability of a sustainability assessment method.

Keywords: energy efficiency, energy life cycle assessment, life cycle cost, social life cycle analysis, manufacturing process, sustainability assessment

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Authors: Yaw-Ling Lin

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A de Bruijn graph of order k is a graph whose vertices representing all length-k sequences with edges joining pairs of vertices whose sequences have maximum possible overlap (length k−1). Every Hamiltonian cycle of this graph defines a distinct, minimum length de Bruijn sequence containing all k-mers exactly once. A Kautz sequence is the minimal generating sequence so as the sequence of minimal length that produces all possible length-k sequences with the restriction that every two consecutive alphabets in the sequences must be different. A collection of de Bruijn/Kautz sequences are orthogonal if any two sequences are of maximally differ in sequence composition; that is, the maximum length of their common substring is k. In this paper, we discuss how such a collection of (maximal) orthogonal de Bruijn/Kautz sequences can be made and use the algorithm to build up a web application service for the synthesized DNA and other related biomolecular sequences.

Keywords: biomolecular sequence synthesis, de Bruijn sequences, Eulerian cycle, Hamiltonian cycle, Kautz sequences, orthogonal sequences

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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: C. G. Shashi Kumar, G. Arun Maiya, H. Manjunath Hande, K. V. Rajagopal

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Background: Diabetes mellitus (DM) is a metabolic disorder with involvement of neurovascular and muscular system. Studies have documented that the gait parameter is altered in type 2 diabetes mellitus with peripheral neuropathy. However, there is a dearth of literature regarding the gait characteristics in type 2 diabetes mellitus (T2DM) without peripheral neuropathy. Therefore, the present study is focused on identifying gait changes in early type 2 diabetes mellitus without peripheral neuropathy. Objective: To analyze the gait characteristics in Type 2 diabetes mellitus without peripheral neuropathy. Methods: After obtaining ethical clearance from Institutional Ethical Committee (IEC), 36 T2DM without peripheral neuropathy and 32 matched healthy subjects were recruited. Gait characteristics (step duration, gait cycle length, gait cycle duration, stride duration, step length, double stance duration) of all the subjects were analyzed using Windtrack dynamic foot scanner. Data were analyzed using Independent‘t’ test to find the difference between the groups (step duration, gait cycle length, gait cycle duration) and Mann-Whitney test was used to analyze the step length and double stance duration to find difference between the groups. Level of significance was kept at P<0.05. Results: Result analysis showed significant decrease in step duration, gait cycle length, gait cycle duration, step length, double stance duration in T2DM subjects as compared to healthy subjects. We also observed a mean increase in stride duration in T2DM subjects compared to healthy subjects.

Keywords: type 2 diabetes mellitus, dynamic foot scan, gait characteristics, medical and health sciences

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

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

Keywords: behavior of winds, wind power, fuzzy logic, sustainable development

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Authors: E. Moradimaram, H. Sayehvand

Abstract:

In recent years the increasing use of fossil fuels has led to various environmental problems including urban pollution, ozone layer depletion and acid rains. Moreover, with the increased number of industrial centers and higher consumption of these fuels, the end point of the fossil energy reserves has become more evident. Considering the environmental pollution caused by fossil fuels and their limited availability, renewable sources can be considered as the main substitute for non-renewable resources. One of these resources is the Organic Rankine Cycles (ORCs). These cycles while having high safety, have low maintenance requirements. Combining the ORCs with other systems, such as ejector and reheater will increase overall cycle efficiency. In this study, ejector and reheater are used to improve the thermal efficiency (ηth), exergy efficiency (η_ex) and net output power (w_net); therefore, the ORCs with reheater (RORCs) are proposed. A computational program has been developed to calculate the thermodynamic parameters required in Engineering Equations Solver (EES). In this program, the analysis of the first and second law in RORC is conducted, and a comparison is made between them and the ORCs with Ejector (EORC). R245fa is selected as the working fluid and water is chosen as low temperature heat source with a temperature of 95 °C and a mass transfer rate of 1 kg/s. The pressures of the second evaporator and reheater are optimized in terms of maximum exergy efficiency. The environment is at 298.15 k and at 101.325 kpa. The results indicate that the thermodynamic parameters in the RORC have improved compared to EORC.

Keywords: Organic Rankine Cycle (ORC), Organic Rankine Cycle with Reheater (RORC), Organic Rankine Cycle with Ejector (EORC), exergy efficiency

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Authors: Hong Dongchen, Chen Qiuxiao, Wu Shuang

Abstract:

Systematic science reveals the complex nonlinear mechanisms of behaviour in urban system. However, in China, when the current city planners face with the system, most of them are still taking simple linear thinking to consider the open complex giant system. This paper introduces the hyper-cycle theory, which is one of the basis theories of systematic science, based on the analysis of the reasons why the current urban planning failed, and proposals for optimization ideas that urban planning compilation should change, from controlling quantitative to the changes of relationship, from blueprint planning to progressive planning based on the nonlinear characteristics and from management control to dynamically monitor feedback.

Keywords: systematic science, hyper-cycle theory, urban planning, urban management

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Authors: R. Akbari, M. A. Ehyaei, R. Shahi Shavvon

Abstract:

Nowadays, solar energy is used for energy purposes such as the use of thermal energy for domestic, industrial and power applications, as well as the conversion of the sunlight into electricity by photovoltaic cells. In this study, the thermodynamic simulation of the solar Rankin cycle with phase change material (paraffin) was first studied. Then energy and exergy analyses were performed. For optimization, a single and multi-objective genetic optimization algorithm to maximize thermal and exergy efficiency was used. The parameters discussed in this paper included the effects of input pressure on turbines, input mass flow to turbines, the surface of converters and collector angles on thermal and exergy efficiency. In the organic Rankin cycle, where solar energy is used as input energy, the fluid selection is considered as a necessary factor to achieve reliable and efficient operation. Therefore, silicon oil is selected for a high-temperature cycle and water for a low-temperature cycle as an operating fluid. The results showed that increasing the mass flow to turbines 1 and 2 would increase thermal efficiency, while it reduces and increases the exergy efficiency in turbines 1 and 2, respectively. Increasing the inlet pressure to the turbine 1 decreases the thermal and exergy efficiency, and increasing the inlet pressure to the turbine 2 increases the thermal efficiency and exergy efficiency. Also, increasing the angle of the collector increased thermal efficiency and exergy. The thermal efficiency of the system was 22.3% which improves to 33.2 and 27.2% in single-objective and multi-objective optimization, respectively. Also, the exergy efficiency of the system was 1.33% which has been improved to 1.719 and 1.529% in single-objective and multi-objective optimization, respectively. These results showed that the thermal and exergy efficiency in a single-objective optimization is greater than the multi-objective optimization.

Keywords: exergy analysis, genetic algorithm, rankine cycle, single and multi-objective function

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