Search results for: fuzzy deterioration rate

Authors: Yousfi Abdelkader, Chaker Abdelkader, Bot Youcef

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This article proposes a five-level shunt active power filter for power quality improvement using a interval type-2 fuzzy logic controller (IT2 FLC). The reference compensating current is extracted using the P-Q theory. The majority of works previously reported are based on two-level inverters with a conventional Proportional integral (PI) controller, which requires rigorous mathematical modeling of the system. In this paper, a IT2 FLC controlled five-level active power filter is proposed to overcome the problem associated with PI controller. The IT2 FLC algorithm is applied for controlling the DC-side capacitor voltage as well as the harmonic currents of the five-level active power filter. The active power filter with a IT2 FLC is simulated in MATLAB Simulink environment. The simulated response shows that the proposed shunt active power filter controller has produced a sinusoidal supply current with low harmonic distortion and in phase with the source voltage.

Keywords: power quality, shunt active power filter, interval type-2 fuzzy logic controller (T2FL), multilevel inverter

Procedia PDF Downloads 176

Authors: Manish Kumar

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Reinforced cement concrete is getting extensively used for construction of different type of structures for the last one century. During this period, we have constructed many structures like buildings, bridges, industrial structures, pavement, water tanks etc. using this construction material. These structures have been created with huge investment of resources. It is essential to maintain those structures in functional condition. Since deterioration in RCC Structures is a common and natural phenomenon it is required to have a detailed plan, methodology for structural repair and rehabilitation shall be in place for dealing such issues. It is important to know exact reason of distress, type of distress and correct method of repair concrete structures. The different methods of repair are described in paper according to distress category which can be refereed for repair. Major finding of the study is that to protect our structure we need to have maintenance frequency and correct material to be chosen for repair. Also workmanship during repair needs to be taken utmost care for quality repair.

Keywords: deterioration, functional condition, reinforced cement concrete, resources

Procedia PDF Downloads 250

Authors: Murat Gunduz, Mustafa Ozdemir

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In this research, a framework is to be proposed to model the safety performance in construction sites. Determinants of safety performance are to be defined through extensive literature review and a multidimensional safety performance model is to be developed. In this context, a questionnaire is to be administered to construction companies with sites. The collected data through questionnaires including linguistic terms are then to be defuzzified to get concrete numbers by using fuzzy set theory which provides strong and significant instruments for the measurement of ambiguities and provides the opportunity to meaningfully represent concepts expressed in the natural language. The validity of the proposed safety performance model, relationships between determinants of safety performance are to be analyzed using the structural equation modeling (SEM) which is a highly strong multi variable analysis technique that makes possible the evaluation of latent structures. After validation of the model, a safety performance index assessment tool is to be proposed by the help of software. The proposed safety performance assessment tool will be based on the empirically validated theoretical model.

Keywords: Fuzzy set theory, safety performance assessment, safety index, structural equation modeling (SEM), construction sites

Procedia PDF Downloads 521

Authors: Jonqlan Lin, C. Y. Tasi, K. H. Lin

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This paper addresses the issue of the autonomous mobile robot (AMR) navigation task based on the hybrid control modes. The novel hybrid control mode, based on multi-sensors information by using the fuzzy approach, has been presented in this research. The system operates in real time, is robust, enables the robot to operate with imprecise knowledge, and takes into account the physical limitations of the environment in which the robot moves, obtaining satisfactory responses for a large number of different situations. An experiment is simulated and carried out with a pioneer mobile robot. From the experimental results, the effectiveness and usefulness of the proposed AMR obstacle avoidance and navigation scheme are confirmed. The experimental results show the feasibility, and the control system has improved the navigation accuracy. The implementation of the controller is robust, has a low execution time, and allows an easy design and tuning of the fuzzy knowledge base.

Keywords: autonomous mobile robot, obstacle avoidance, MEMS, hybrid control mode, navigation control

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Authors: Wann-Ming Wey

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

Keywords: green TOD, built environment, fuzzy delphi technique, quality function deployment, fuzzy analytic network process

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Authors: Katarina Rogulj, Ivana Racetin, Jelena Kilic

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In this study, the fuzzy logic approach (FLA) was developed for construction project management (CPM) under uncertainty and duality. The focus was on decision making in selecting the type of the glass facade for a residential-commercial building in the main design. The adoption of fuzzy sets was capable of reflecting construction managers’ reliability level over subjective judgments, and thus the robustness of the system can be achieved. An α-cuts method was utilized for discretizing the fuzzy sets in FLA. This method can communicate all uncertain information in the optimization process, taking into account the values of this information. Furthermore, FLA provides in-depth analyses of diverse policy scenarios that are related to various levels of economic aspects when it comes to the construction projects' valid decision making. The developed approach is applied to CPM to demonstrate its applicability. Analyzing the materials of glass facades, variants were defined. The development of the FLA for the CPM included relevant construction projec'ts stakeholders that were involved in the criteria definition to evaluate each variant. Using fuzzy Decision-Making Trial and Evaluation Laboratory Method (DEMATEL) comparison of the glass facade was conducted. This way, a rank, according to the priorities for inclusion into the main design, of variants is obtained. The concept was tested on a residential-commercial building in the city of Rijeka, Croatia. The newly developed methodology was then compared with the existing one. The aim of the research was to define an approach that will improve current judgments and decisions when it comes to the material selection of buildings facade as one of the most important architectural and engineering tasks in the main design. The advantage of the new methodology compared to the old one is that it includes the subjective side of the managers’ decisions, as an inevitable factor in each decision making. The proposed approach can help construction projects managers to identify the desired type of glass facade according to their preference and practical conditions, as well as facilitate in-depth analyses of tradeoffs between economic efficiency and architectural design.

Keywords: construction projects management, DEMATEL, fuzzy logic approach, glass façade selection

Procedia PDF Downloads 136

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

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

Keywords: defuzzification, floating search, fuzzy clustering, Zernike moments

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Authors: Ejazulhaq Rahimi

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The development of techniques evaluating deterioration on concrete structures is vital for structural health monitoring (SHM). One of the main reasons for reinforced concrete structure's deterioration is the corroding of embedded rebars. It is a natural process that begins when the rebar starts to rust. It occurs when the protective layer on the rebar is destroyed. The rebar in concrete is usually protected against corrosion by the high pH of the surrounding cement paste. However, there are chemicals that can destroy the protective layer, making it susceptible to corrosion. It is very destructive for the lifespan and durability of the concrete structure. Corrosion products which are 3 to 6 times voluminous than the rebar stress its surrounding concrete and lead to fracture as cracks even peeling off the cover concrete over the rebar. As is clear that concrete shows limit elastic behavior in its stress strain property, so corrosion product stresses can be detected as strains from the concrete surface. It means that surface strains have a relation with the situation and amount of corrosion products and related concrete fractures inside reinforced concrete. In this paper, a comparative study of surface strains due to corrosion products detected by strain gauges and acoustic emission (AE) testing under periodic accelerated corrosion in the salty environment with 3% NaCl is reported. From the results, three different stages of strains were clearly observed based on the type and rate of strains in each corrosion situation and related fracture types. AE parameters which mostly are related to fracture and their shapes, describe the same phases. It is confirmed that there is a great agreement to the result of each other and describes three phases as generation and expansion of corrosion products and initiation and propagation of corrosion-induced cracks, and surface cracks. In addition, the strain on the concrete surface was rapidly increased before the cracks arrived at the surface of the concrete.

Keywords: acoustic emission, monitoring, rebar corrosion, reinforced concrete, strain

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Authors: Aman Berhe, Camille Guinaudeau, Claude Barras

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In order to facilitate information seeking in large collections of multimedia documents with long and progressive content (such as broadcast news or TV series), one can extract the semantic links that exist between semantically coherent parts of documents, i.e., scenes. The links can then create a coherent collection of scenes from which it is easier to perform content analysis, topic extraction, or information retrieval. In this paper, we focus on TV series structuring and propose two approaches for scene linking at different levels of granularity (episode and season): a fuzzy online clustering technique and a graph-based community detection algorithm. When evaluated on the two first seasons of the TV series Game of Thrones, we found that the fuzzy online clustering approach performed better compared to graph-based community detection at the episode level, while graph-based approaches show better performance at the season level.

Keywords: multimedia collection structuring, progressive content, scene linking, fuzzy clustering, community detection

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Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih

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In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level.

Keywords: inventory optimization, soft computing, safety stock optimization, dairy industries inventory optimization

Procedia PDF Downloads 123

Authors: Sittampalam Manoharan, Gary Chai, Sanaul Chowdhury, Andrew Golding

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The primary objective of this paper is to present a simplified approach to develop the structural deterioration model using traffic speed deflectometer data for flexible pavements. Maintaining assets to meet functional performance is not economical or sustainable in the long terms, and it would end up needing much more investments for road agencies and extra costs for road users. Performance models have to be included for structural and functional predicting capabilities, in order to assess the needs, and the time frame of those needs. As such structural modelling plays a vital role in the prediction of pavement performance. A structural condition is important for the prediction of remaining life and overall health of a road network and also major influence on the valuation of road pavement. Therefore, the structural deterioration model is a critical input into pavement management system for predicting pavement rehabilitation needs accurately. The Traffic Speed Deflectometer (TSD) is a vehicle-mounted Doppler laser system that is capable of continuously measuring the structural bearing capacity of a pavement whilst moving at traffic speeds. The device’s high accuracy, high speed, and continuous deflection profiles are useful for network-level applications such as predicting road rehabilitations needs and remaining structural service life. The methodology adopted in this model by utilizing time series TSD maximum deflection (D0) data in conjunction with rutting, rutting progression, pavement age, subgrade strength and equivalent standard axle (ESA) data. Then, regression analyses were undertaken to establish a correlation equation of structural deterioration as a function of rutting, pavement age, seal age and equivalent standard axle (ESA). This study developed a simple structural deterioration model which will enable to incorporate available TSD structural data in pavement management system for developing network-level pavement investment strategies. Therefore, the available funding can be used effectively to minimize the whole –of- life cost of the road asset and also improve pavement performance. This study will contribute to narrowing the knowledge gap in structural data usage in network level investment analysis and provide a simple methodology to use structural data effectively in investment decision-making process for road agencies to manage aging road assets.

Keywords: adjusted structural number (SNP), maximum deflection (D0), equant standard axle (ESA), traffic speed deflectometer (TSD)

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Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

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Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: short term load forecasting, prediction interval, type 2 fuzzy logic systems, electric, computer systems engineering

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Authors: Atakan Aral Ormancı, Tuğçe Arslantaş, Murat Özcü

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This study presents the design and implementation of an experimental chassis-level system for various control applications. Specifically, the height level of the chassis is controlled using proportional integrated derivative, fuzzy logic, and deep learning control methods. Real-time data obtained from height and pressure sensors installed in a 6x2 truck chassis, in combination with pulse-width modulation signal values, are utilized during the tests. A prototype pneumatic system of a 6x2 truck is added to the setup, which enables the Smart Pneumatic Actuators to function as if they were in a real-world setting. To obtain real-time signal data from height sensors, an Arduino Nano is utilized, while a Raspberry Pi processes the data using Matlab/Simulink and provides the correct output signals to control the Smart Pneumatic Actuator in the truck chassis. The objective of this research is to optimize the time it takes for the chassis to level down and up under various loads. To achieve this, proportional integrated derivative control, fuzzy logic control, and deep learning techniques are applied to the system. The results show that the deep learning method is superior in optimizing time for a non-linear system. Fuzzy logic control with a triangular membership function as the rule base achieves better outcomes than proportional integrated derivative control. Traditional proportional integrated derivative control improves the time it takes to level the chassis down and up compared to an uncontrolled system. The findings highlight the superiority of deep learning techniques in optimizing the time for a non-linear system, and the potential of fuzzy logic control. The proposed approach and the experimental results provide a valuable contribution to the field of control, automation, and systems engineering.

Keywords: automotive, chassis level control, control systems, pneumatic system control

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Authors: Said Baadel, Fadi Thabtah, Joan Lu

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

Keywords: data mining, k-means, MCOKE, overlapping

Procedia PDF Downloads 571

Authors: Takashi Mitsuishi

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Fuzzy logic has gained acceptance in the recent years in the fields of social sciences and humanities such as psychology and linguistics because it can manage the fuzziness of words and human subjectivity in a logical manner. However, the major field of application of the fuzzy logic is control engineering as it is a part of the set theory and mathematical logic. Mamdani method, which is the most popular technique for approximate reasoning in the field of fuzzy control, is one of the ways to numerically represent the control afforded by human language and sensitivity and has been applied in various practical control plants. Fuzzy logic has been gradually developing as an artificial intelligence in different applications such as neural networks, expert systems, and operations research. The objects of inference vary for different application fields. Some of these include time, angle, color, symptom and medical condition whose fuzzy membership function is a periodic function. In the defuzzification stage, the domain of the membership function should be unique to obtain uniqueness its defuzzified value. However, if the domain of the periodic membership function is determined as unique, an unintuitive defuzzified value may be obtained as the inference result using the center of gravity method. Therefore, the authors propose a method of circular-polar-coordinates transformation and defuzzification of the periodic membership functions in this study. The transformation to circular polar coordinates simplifies the domain of the periodic membership function. Defuzzified value in circular polar coordinates is an argument. Furthermore, it is required that the argument is calculated from a closed plane figure which is a periodic membership function on the circular polar coordinates. If the closed plane figure is continuous with the continuity of the membership function, a significant amount of computation is required. Therefore, to simplify the practice example and significantly reduce the computational complexity, we have discretized the continuous interval and the membership function in this study. In this study, the following three methods are proposed to decide the argument from the discrete polygon which the continuous plane figure is transformed into. The first method provides an argument of a straight line passing through the origin and through the coordinate of the arithmetic mean of each coordinate of the polygon (physical center of gravity). The second one provides an argument of a straight line passing through the origin and the coordinate of the geometric center of gravity of the polygon. The third one provides an argument of a straight line passing through the origin bisecting the perimeter of the polygon (or the closed continuous plane figure).

Keywords: defuzzification, fuzzy membership function, periodic function, polar coordinates transformation

Procedia PDF Downloads 362

Authors: Matar Celine, Gaucel Sebastien, Gontard Nathalie, Guilbert Stephane, Guillard Valerie

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To increase the very short shelf life of fresh fruits and vegetable, Modified Atmosphere Packaging (MAP) allows an optimal atmosphere composition to be maintained around the product and thus prevent its decay. This technology relies on the modification of internal packaging atmosphere due to equilibrium between production/consumption of gases by the respiring product and gas permeation through the packaging material. While, to the best of our knowledge, benefit of MAP for fresh fruits and vegetable has been widely demonstrated in the literature, its effect on shelf life increase has never been quantified and formalized in a clear and simple manner leading difficult to anticipate its economic and environmental benefit, notably through the decrease of food losses. Mathematical modelling of mass transfers in the food/packaging system is the basis for a better design and dimensioning of the food packaging system. But up to now, existing models did not permit to estimate food quality nor shelf life gain reached by using MAP. However, shelf life prediction is an indispensable prerequisite for quantifying the effect of MAP on food losses reduction. The objective of this work is to propose an innovative approach to predict shelf life of MAP food product and then to link it to a reduction of food losses and wastes. In this purpose, a ‘Virtual MAP modeling tool’ was developed by coupling a new predictive deterioration model (based on visual surface prediction of deterioration encompassing colour, texture and spoilage development) with models of the literature for respiration and permeation. A major input of this modelling tool is the maximal percentage of deterioration (MAD) which was assessed from dedicated consumers’ studies. Strawberries of the variety Charlotte were selected as the model food for its high perishability, high respiration rate; 50-100 ml CO₂/h/kg produced at 20°C, allowing it to be a good representative of challenging post-harvest storage. A value of 13% was determined as a limit of acceptability for the consumers, permitting to define products’ shelf life. The ‘Virtual MAP modeling tool’ was validated in isothermal conditions (5, 10 and 20°C) and in dynamic temperature conditions mimicking commercial post-harvest storage of strawberries. RMSE values were systematically lower than 3% for respectively, O₂, CO₂ and deterioration profiles as a function of time confirming the goodness of model fitting. For the investigated temperature profile, a shelf life gain of 0.33 days was obtained in MAP compared to the conventional storage situation (no MAP condition). Shelf life gain of more than 1 day could be obtained for optimized post-harvest conditions as numerically investigated. Such shelf life gain permitted to anticipate a significant reduction of food losses at the distribution and consumer steps. This food losses' reduction as a function of shelf life gain has been quantified using a dedicated mathematical equation that has been developed for this purpose.

Keywords: food losses and wastes, modified atmosphere packaging, mathematical modeling, shelf life prediction

Procedia PDF Downloads 180

Authors: Wajahat Ali, Shakeel Javaid

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In this study, we have developed a mathematical programming model for a solid transportation problem with three objective functions arranged in hierarchical order. The mathematical programming models with more than one objective function to be solved in hierarchical order is termed as a multi-level programming model. Our study explores a Multi-Level Solid Transportation Problem with Uncertain Parameters (MLSTPWU). The proposed MLSTPWU model consists of three objective functions, viz. minimization of transportation cost, minimization of total transportation time, and minimization of deterioration during transportation. These three objective functions are supposed to be solved by decision-makers at three consecutive levels. Three constraint functions are added to the model, restricting the total availability, total demand, and capacity of modes of transportation. All the parameters involved in the model are assumed to be uncertain in nature. A solution method based on fuzzy logic is also discussed to obtain the compromise solution for the proposed model. Further, a simulated numerical example is discussed to establish the efficiency and applicability of the proposed model.

Keywords: solid transportation problem, multi-level programming, uncertain variable, uncertain environment

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Authors: Vladimir A. Todiras

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Spatio-temporal models provide new possibilities for real-time action in pest risk analysis. It should be noted that estimation of the possibility and probability of introduction of a pest and of its economic consequences involves many uncertainties. We present a new mapping technique that assesses pest invasion risk using online BioClass software. BioClass is a GIS tool designed to solve multiple-criteria classification and optimization problems based on fuzzy logic and level set methods. This research describes a method for predicting the potential establishment and spread of a plant pest into new areas using a case study: corn rootworm (Diabrotica spp.), tomato leaf miner (Tuta absoluta) and plum fruit moth (Grapholita funebrana). Our study demonstrated that in BioClass we can combine fuzzy logic and geographic information systems with knowledge of pest biology and environmental data to derive new information for decision making. Pests are sensitive to a warming climate, as temperature greatly affects their survival and reproductive rate and capacity. Changes have been observed in the distribution, frequency and severity of outbreaks of Helicoverpa armigera on tomato. BioClass has demonstrated to be a powerful tool for applying dynamic models and map the potential future distribution of a species, enable resource to make decisions about dangerous and invasive species management and control.

Keywords: classification, model, pest, risk

Procedia PDF Downloads 281

Authors: Vasileiou Apostolos, Theodosiou Chrysa, Tsitroulis Ioannis, Maris Fotios

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The severity of extreme phenomena is due to their ability to cause severe damage in a small amount of time. It has been observed that floods affect the greatest number of people and induce the biggest damage when compared to the total of annual natural disasters. The detection of potential flood-prone areas constitutes one of the fundamental components of the European Natural Disaster Management Policy, directly connected to the European Directive 2007/60. The aim of the present paper is to develop a new methodology that combines geographical information, fuzzy logic and multi-criteria evaluation methods so that the most vulnerable areas are defined. Therefore, ten factors related to geophysical, morphological, climatological/meteorological and hydrological characteristics of the basin were selected. Afterwards, two models were created to detect the areas pronest to flooding. The first model defined the gravitas of each factor using Analytical Hierarchy Process (AHP) and the final map of possible flood spots were created using GIS and Boolean Algebra. The second model made use of the fuzzy logic and GIS combination and a respective map was created. The application area of the aforementioned methodologies was in Ardas basin due to the frequent and important floods that have taken place these last years. Then, the results were compared to the already observed floods. The result analysis shows that both models can detect with great precision possible flood spots. As the fuzzy logic model is less time-consuming, it is considered the ideal model to apply to other areas. The said results are capable of contributing to the delineation of high risk areas and to the creation of successful management plans dealing with floods.

Keywords: analytical hierarchy process, flood prone areas, fuzzy logic, geographic information system

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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: Mohamed Ahmed Abd El Kader

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This paper describes the conservation processes of an Ancient Egyptian wooden coffin dating back to the Middle Kingdom, ancient Egypt, using several scientific and analytical methods in order to provide a deeper understanding of the deterioration status and a greater awareness of how well preserved the object is. Visual observation and 2D Programs, as well as Optical Microscopy (OM), Environmental scanning Electron Microscopy (ESEM), X-ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FTIR) were used in our study. The identification of wood species and the composition of the pigments and previous restoration materials were made. The coffin was previously conserved and stored in improper conditions, which led to its further deterioration; the surface of the lid dust, which obscured the decorations as well as all necessary restoration work was promptly carried out as soon as the coffin was transferred from the display hall from the Egyptian Museum to the Wood Conservation Laboratory of the Grand Egyptian Museum-Conservation Center (GEM-CC). The analyses provided detailed information concerning the original materials and the materials added during the previous treatment interventions, which was considered when applying the conservation plan. Conservation procedures have been applied with high accuracy to conserve the coffin including cleaning, consolidation of fragile painted layers, and the wooden boards forming the sides of the coffin were reassembled in their original positions. The materials and methods that were applied were extremely effective in stability and reinforcement of the coffin without harmfulness to the original materials and the coffin was successfully conserved and ready to display in the Grand Egyptian Museum (GEM).

Keywords: coffin, middle kingdom, deterioration, 2d program

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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: 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: Mohd Izzat Md. Nor, Norfazlina Jaffar, Noor Zaitulakma Md. Zain, Nur Izyanti Mohd Suppian, Subhashini Balakrishnan, Geetha Kandavello

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During the Coronavirus (COVID-19) pandemic, Malaysia has been focusing on building herd immunity by introducing vaccination programs into the community. Hospital Standard Operating Procedures (SOP) were developed to prevent inpatient transmission. Objective: In this study, we focus on the positivity rate of inpatient Person Under Surveillance (PUS) becoming COVID-19 positive and compare this to the National rate in order to see the outcomes of the patient who becomes COVID-19 positive in relation to their vaccination status. Methodology: This is a retrospective observational study carried out from 1 January until 30 March 2022 in Institut Jantung Negara (IJN). There were 5,255 patients admitted during the time of this study. Pre-admission Polymerase Chain Reaction (PCR) swab was done for all patients. Patients with positive PCR on pre-admission screening were excluded. The patient who had exposure to COVID-19-positive staff or patients during hospitalization was defined as PUS and were quarantined and monitored for potential COVID-19 infection. Their frequency and risk of exposure (WHO definition) were recorded. A repeat PCR swab was done for PUS patients that have clinical deterioration with or without COVID symptoms and on their last day of quarantine. The severity of COVID-19 infection was defined as category 1-5A. All patients' vaccination status was recorded, and they were divided into three groups: fully immunised, partially immunised, and unvaccinated. We analyzed the positivity rate of PUS patients becoming COVID-positive, outcomes, and correlation with the vaccination status. Result: Total inpatient PUS to patients and staff was 492; only 13 became positive, giving a positivity rate of 2.6%. Eight (62%) had multiple exposures. The majority, 8/13(72.7%), had a high-risk exposure, and the remaining 5 had medium-risk exposure. Four (30.8%) were boostered, 7(53.8%) were fully vaccinated, and 2(15.4%) were partial/unvaccinated. Eight patients were in categories 1-2, whilst 38% were in categories 3-5. Vaccination status did not correlate with COVID-19 Category (P=0.641). One (7.7%) patient died due to COVID-19 complications and sepsis. Conclusion: Within the first quarter of 2022, our institution's positivity rate (2.6%) is significantly lower than the country's (14.4%). High-risk exposure and multiple exposures to positive COVID-19 cases increased the risk of PUS becoming COVID-19 positive despite their underlying vaccination status.

Keywords: COVID-19, boostered, high risk, Malaysia, quarantine, vaccination status

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

Abstract:

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

Abstract:

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

Abstract:

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

Abstract:

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

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

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Authors: Ghada Elshafei, A. Elazim Negm

Abstract:

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

Procedia PDF Downloads 474