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Drying has been widely used to provide a longer shelf life for various agricultural products. The moisture content can be reduced to prevent the spoilage of harvested agricultural products, in order to inhibit the growth of bacteria, yeasts, and molds. Among them, the drying system of solar-assisted air source heat pumps has drawn much attention in recent years, due to excellent energy saving and high dried quality of products. However, solar energy can be badly wasted, when the water tank temperature cannot meet the drying requirement, because of the high drying temperature during the middle and last drying stage. In this study, a solar-assisted multi-heat source heat pump (SMSHP) drying system was proposed to incorporate a watersource evaporator into the existing solar-assisted air source heat pump drying system, in order to improve the economic, and environmental benefit and the utilization rate. The fuzzy analytic hierarchy process was used to develop the optimization model of the SMSHP drying system. The optimization variables were selected as the collector inclination Angle, collector area, water tank volume, heat pump power, water pump flow rate, and airflow rate. The economy, system performance, and energy efficiency were chosen as the optimization objectives of the model. After that, the multi-objective optimization function of the SMSHP drying system was established to obtain a total of 25 groups of optimal combinations after the orthogonal test. Moreover, the simulation model of the SMSHP drying system was developed using the TRNSYS software. The accuracy of the model was verified, according to the experimental platform. Then the 25 groups of optimal combination parameters were introduced into the TRNSYS simulation model of the SMSHP drying system. The optimal parameter group was obtained with the highest system performance. Finally, the optimal and original parameter sets were compared and analyzed to verify the practicability and reliability of the model. The results showed that only 20 groups of 25 optimization parameters met the requirements of the drying process. The relative humidity of the air in the drying room was too high to meet the system requirements in the rest 5 groups. The economy, system performance, and energy efficiency were compared on the 25 groups' optimization. The optimization objective function of the 10th group was the lowest, indicating the optimal objective function. In addition, the TRNSYS simulation also showed that the optimal combination of parameters met the requirement of the drying process. The optimization parameter group 10 was the optimal one. The optimal parameters were obtained: the collector inclination angle was 35 °, the collector area was 40 m², the water tank volume was 1.5 m³, the heat pump power was 10 kW, the water pump flow rate was 2700 kg/h, and the airflow rate was 3500 m³ /h. Compared with the TRNSYS simulation of the original and the optimal parameters, the cost of the SMSHP drying system was reduced by 4.78%, whereas, the system performance and energy saving were improved by 17.08%, and 9.41%, respectively. All indicators were comprehensively improved by 6.27%. The multi-objective optimization of the solar multi-heat source heat pump drying system was carried out using a fuzzy analytic hierarchy process and TRNSYS simulation analysis. The finding has an important guiding significance to improve the performance of solar combined heat pump drying systems. [ABSTRACT FROM AUTHOR]

Cities around the world have reopened from the lockdown caused by the COVID-19 pandemic, and more and more people are planning regional travel. Therefore, it is a practical problem to recommend suitable hotels to travelers amid the COVID-19 pandemic. However, it is also a challenging task since the criteria that affect hotel selection amid the COVID-19 pandemic may be different from those usually considered. From this perspective, a novel fuzzy analytic hierarchy process (FAHP)-fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) approach is proposed in this study for hotel recommendation. The proposed methodology not only considers the criteria affecting hotel selection amid the COVID-19 pandemic, but also establishes a systematic mechanism to simultaneously improve the accuracy and efficiency of the recommendation process. The novel FAHP-fuzzy TOPSIS approach has been successfully applied to recommend suitable hotels to fifteen travelers for regional trips amid the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Due to limitations in traditional concrete gravity dam (CGD) design, a new approach is necessary. In this study, the lean analysis as a novel approach for CGD design, considering the interaction between dam and reservoir was considered. Maximum and minimum stresses at the heel and displacement of the crest were obtained as crucial input values of bubble sorting based on seismic analysis using Finite element analysis (FEA), and the Fuzzy Analytic Hierarchy Process (FAHP). The fuzzy bubble sorting analytic process, aimed at developing a novel method for selecting the best CGD configuration, was developed. Required Criteria, Sub-Criteria and developed models were applied to optimize the body of CGD. The weight of each sub-criterion and models were calculated based on pairwise comparison matrices. The novel approach was designed in MATLAB with the OPT-CGD code to select the best CGD model. The best weight of the Criteria, for selecting the best CGD model, based on the lean construction principles was selected from 60 developed models under implicit dynamic analysis. Statistical analysis reveals a 20% reduction in the concrete mass of the case study's optimal body compared to the traditionally designed dam. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

AbstractThis study explores the factors influencing the cognitive processes of operators in digital nuclear power plants, with a focus on the correlation between these factors and electroencephalogram (EEG) features. Initially, based on expert consultations, seven factors were considered: stress, time, fatigue, procedural complexity, user interface experience, procedural clarity, and efficiency. From these, four were identified as the most crucial for each stage of the cognitive process, highlighting their significant roles in influencing cognitive performance and potentially correlating with distinct EEG characteristics. These were assessed using the fuzzy analytic hierarchy process (FAHP) to determine the weightings of influences across the cognitive stages of monitoring, decision making, and execution.Employing a simulated scenario of a steam generator tube rupture, subjective questionnaires were utilized to gauge participant perceptions of influencer impacts at each stage, calculating human factors fuzzy synthetic values. Concurrently, EEG signals were segmented by operational steps, extracting around 114 features across the time, frequency, and time-frequency domains, which were then dimensionally reduced to 17 principal components via adaptive principal components analysis (APCA). A correlation analysis was performed between the human factors fuzzy synthetic values and the APCA-reduced EEG features of participants. Subsequently, the EEG feature columns of the eight selected participants were used as inputs to construct a transformer-based self-attention network model to evaluate the participants’ human factors fuzzy comprehensive values.The findings confirm the transformer model’s efficacy in assessing these values, evidencing a significant correlation between the EEG features and human factors fuzzy synthetic values. Integrating FAHP with machine learning methodologies, this model proficiently estimated operators’ cognitive states during various cognitive processes, significantly enhancing human-machine interface design and the operational safety and efficiency at nuclear power plants. [ABSTRACT FROM AUTHOR]

Agricultural tourism has been recognized as an opportunity for rural development in recent decades. To promote sustainable agricultural tourism, identifying and prioritizing villages suitable for the development of this activity is essential. This research aims to locate suitable villages for the development of agritourism in rural areas of Semirom County. The method used is a survey-analytical approach. The study population consists of experts and farmers. Data collection was done through questionnaires. Initially, suitable indicators were identified through the opinions of 15 experts using the fuzzy analytic hierarchy process and Super Decision software. Then, using spatial indicators through ArcGIS software and the fuzzy overlay method, areas and villages suitable for agritourism development were determined, ultimately selecting 14 villages based on population size. In the next stage, the social capacity of the local community in the identified villages was assessed. Data were collected from 326 individuals using questionnaires and analyzed with SPSS software. Finally, using the TOPSIS model, villages were ranked based on all indicators influencing agricultural tourism development, including natural and tourism resources, tourism infrastructure, and the social capacity of the local community. The results indicated that Aliabad, Dangzalu, and Khafar have the highest potential for agritourism development. Furthermore, the results showed that planners should consider all factors including agricultural capacity, natural resources, tourist attractions, infrastructure, and local social capacity when identifying suitable villages for agritourism. [ABSTRACT FROM AUTHOR]

Many previous cases have demonstrated that hazardous materials processing industry (HMPI) accidents always result in huge losses and HMPI companies which suffer accidents are difficult to quickly restore. This has demanded an effective way to solve the two problems. Resilience safety culture (RSC) combines conventional safety culture and resilience engineering. It aims at giving an organization the abilities of continually operating or timely recovering during or after a major unexpected event. RSC fits the safety demands of the HMPI well. The present study develops a RSC model for the HMPI. Firstly, through literature review, 12 model elements with 16 hypothesized relationships are developed. These hypothesis are then tested by 618 samples with structural equation modelling. Finally, an HMPI RSC model with 12 elements and 12 relationships is established. Model validity is verified by a comparison study on the proposed model and two existing models with the fuzzy analytic hierarchy process. [ABSTRACT FROM AUTHOR]

Abstract Background Ancient classic prescription play a crucial role in the preservation and advancement of traditional Chinese medicine (TCM) theories. They represent a significant milestone in the ongoing development and transmission of TCM knowledge and practices and are considered one of the breakthroughs in the development of TCM inheritance. In the process of developing ancient classic prescriptions, many problems may still arise in ensuring quality consistency between traditional methods and modern production processes, among which the extraction process poses major challenges. This paper introduces a practical approach extracting an ancient classic prescription using a modern extraction process. The technique is demonstrated through the study of the extraction process of Shenshou Taiyi powder (STP). Methods This study focuses on optimising the STP extraction process to ensure consistency in the quality of the product obtained through ancient and modern processes using the standard relation and fuzzy analytic hierarchical process (FAHP) and criteria importance through intercriteria correlation (CRITIC) method integrated weights combined with the Box-Behnken response surface test. Using the contents of rosmarinic acid, isoimperatorin, puerarin, as well as the extract yield and fingerprint similarity as evaluation indexes of STP, the Box-Behnken response surface method was employed to examine the varying extraction parameters, including water addition ratio, extraction duration, and number of extractions. The weighted coefficients for each parameter were calculated by combining the benchmark correlation and FAHP-CRITIC method, deriving a comprehensive score. Results The optimal extraction process for STP consisted of a two extractions, each using at a tenfold quantity of water, performed for one hour. Process verification across three separate batches yielded a comprehensive score of 94.7, with a relative standard deviation of 0.76%. Conclusions The application of the Box-Behnken response surface method combined with standard relation and FAHP-CRITIC approach proved to be stable and feasible for optimising the extraction process of STP.

Abstract Cities around the world have reopened from the lockdown caused by the COVID-19 pandemic, and more and more people are planning regional travel. Therefore, it is a practical problem to recommend suitable hotels to travelers amid the COVID-19 pandemic. However, it is also a challenging task since the criteria that affect hotel selection amid the COVID-19 pandemic may be different from those usually considered. From this perspective, a novel fuzzy analytic hierarchy process (FAHP)-fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) approach is proposed in this study for hotel recommendation. The proposed methodology not only considers the criteria affecting hotel selection amid the COVID-19 pandemic, but also establishes a systematic mechanism to simultaneously improve the accuracy and efficiency of the recommendation process. The novel FAHP-fuzzy TOPSIS approach has been successfully applied to recommend suitable hotels to fifteen travelers for regional trips amid the COVID-19 pandemic.

Owing to its favorable geographical and climatic conditions, Tunisia offers a great deal of solar potential, making solar energy projects highly feasible. However, to maximize efficiency and return on investment, it is critical to identify the most promising locations to invest in costly solar power plants. Determining the best-suited location for implementing such projects involves various conflicting parameters, including technical, economic, and environmental dimensions. To address the complex nature of the challenges associated with site selection, this study applies an integrated GIS-based MCDM approach to conduct a land suitability analysis to determine the most feasible locations for installing large-scale solar PV power plants in Tunisia. With the aim of achieving maximum power while minimizing costs, the model considers a number of factors, including solar radiation, slope, average cloudy days, land use, soil texture, temperature, orientation, proximity to grid networks, roads, and residential areas, as well as water resources. To this end, we apply the fuzzy analytical hierarchy process (FAHP) to assign weights to the defined criteria and evaluate the potential sites. The findings revealed that 17.6% of the study area is suitable for developing solar PV systems on a large scale. According to the spatial analysis, the most suitable sites covered an area of 5251 km2 (3.31% of the available area) and were densely scattered across the central and southwestern, southeastern, and eastern coastal regions of the country. Furthermore, the technical potential of these sites was estimated at nearly 1060 TWh/yr. An examination of the locations of operational solar farms and planned projects revealed that they were in line with the most suitable sites, which indicated the consistency of the proposed model.

Soil erosion poses a significant problem in the Mediterranean region, posing serious threats to the environment and natural resources. The objective of this study is to identify and evaluate the risks associated with gully erosion in the Medjerda watershed in the northeastern part of Algeria. To accomplish this goal, two models were utilized: the fuzzy analytic hierarchy process (F-AHP) and the frequency ratio (FR). Twelve factors that contribute to soil erosion were considered in the study: slope, elevation, distance to streams, land use and land cover, drainage density (DD), topographic wetness index (TWI), rainfall, soil groups, lineament density, soil power index (SPI), sediment transport index (STI), and plan curvature. The results indicate that sediment transport index (STI), rainfall, and slope are the most influential factors in predicting erosion in the Medjerda Basin. To validate the models used, the area under the receiver operating characteristics curve (AUC) was employed. The AUC values obtained for the FR and F-AHP models were 75.5 and 73.7%, respectively, indicating their excellent accuracy in identifying the erosion susceptibility area. The accuracy ratings of both models demonstrate their outstanding predictive capabilities. Thus, the results of soil erosion susceptibility maps with a better success rate and forecast could be beneficial and effective for implementing various policy measures to safeguard soil. They could be useful for managing gully erosion risks in different parts of the river basin. [ABSTRACT FROM AUTHOR]

On the third-party cloud platform, to help enterprises accurately obtain high-quality and valuable business resources from the massive information resources, a bilateral matching method for business resources, based on synergy effects and incomplete data, is proposed. The method first utilizes a k-nearest neighbor imputation algorithm, based on comprehensive similarity, to fill in missing values. Then, it constructs a satisfaction evaluation index system for business resource suppliers and demanders, and the weights of the satisfaction evaluation indices are determined, based on the fuzzy analytic hierarchy process (FAHP) and the entropy weighting method (EWM). On this basis, a bilateral matching model is constructed with the objectives of maximizing the satisfaction of both the supplier and the demander, as well as achieving the synergy effect. Finally, the model is solved using the linear weighting method to obtain the most satisfactory business resources for both supply and demand. The effectiveness of the method is verified through a practical application and comparative experiments. [ABSTRACT FROM AUTHOR]

Copyright of Nuclear Safety is the property of Nuclear & Radiation Safety Center and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

During the operation of fabricated small box girder bridges, which face safety issues such as structural degradation and failure, there is an urgent need to propose a safety evaluation method to cope with the possible risks. This article quantitatively evaluates the safety state of a fabricated small box girder bridge in Wuhan City based on Fuzzy Analytic Hierarchy Process (FAHP) and structural health monitoring (SHM) data. Firstly, the FAHP model is established, and stress, deformation, and temperature are selected as evaluation factors. The safety thresholds of stress and deformation are determined by combining the industry specifications and the historical statistical patterns of the massive SHM data. The temperature field of the bridge is simulated and analyzed by combining ANSYS, HYPERMESH, and TAITHREM, and the most unfavorable temperature gradient is determined as a threshold for the safety evaluation. Finally, the scores of indexes of the bridge are determined based on the measured SHM data, which in turn provides a quantitative description of the safety state. The results show that the thresholds determined by the joint industry specifications and the massive SHM data are reasonable; the temperature field simulation model established in this article is consistent with the measured results, and can accurately determine the temperature gradient of the bridge. The safety evaluation result from the FAHP model is the same as the field test results, which verifies the effectiveness and applicability of the proposed method to actual bridge projects. [ABSTRACT FROM AUTHOR]

According to a survey regarding indigenous employment, in Taiwan, a high proportion of indigenous people are engaged in construction work compared with the overall population. However, among indigenous construction workers, 56.15% have received no occupational safety or health training, and 9.39% have encountered occupational accidents in their workplaces. Therefore, this study aimed to develop employee assistance programs (EAPs) for indigenous workers in Taiwan by focusing on three dimensions—namely work, life, and health—and by establishing corresponding implementation paths for these EAPs. A modified Delphi method was adopted to screen EAP measures for the workplaces of indigenous workers, and a formal evaluation followed. Subsequently, the analytic hierarchy process was employed to calculate the overall weights among the factors in order to discern the relative importance of each factor in achieving the target goal or to resolve target problems and establish an order of priority. The results indicated that health was the most important of the three dimensions of indigenous EAPs, followed by the life dimension and then the work dimension. Compared with previous studies regarding Han Taiwanese workers, mental health services in the health dimension were particularly important in the present study. Finally, regarding the health dimension, this study suggests developing mental health services that respect indigenous culture and therefore are appropriate for indigenous people, such as the establishment of drug and alcohol addiction support groups and mental health service systems. In addition, corresponding welfare measures can be offered to enhance people's motivation to change. [ABSTRACT FROM AUTHOR]

In the industrial era, production equipment serves as an essential mother machine. In the global manufacturing industry, components such as laptop computers, mobile phones, and automotive parts all strive for aesthetic appearance. Taiwan's machine tool industry plays a significant role globally. Faced with the constantly changing market environment, the development and competitive advantage of CNC machines are crucial topics for manufacturers. Domestic manufacturers of computer numerical control machines should move towards the integration of automated equipment to accommodate various advanced parts processing procedures. Smart manufacturing will become the trend of the industry in the future. This study invited experts from academia, industry, and research institutions to conduct expert interviews. Their opinions were compiled and analyzed, supplemented by fuzzy Delphi analysis to establish the development trends of various modules. The feasibility and demand of the product's functional technology for industrial development were analyzed under three research dimensions and eight technical items. A total of 26 key sub-technical items were identified, achieving an expert consensus level of over 80. Furthermore, the importance ranking was analyzed using the fuzzy analytic hierarchy process, and the consistency tests were passed with C.I. < 0.1 and C.R. < 0.1. Finally, the obtained importance ranking of the hierarchical structure was used to predict the future development of computer numerical control machines through a technology roadmap, helping manufacturers use it as a reference model for future development trends to enhance market competitiveness. [ABSTRACT FROM AUTHOR]

Background: Ancient classic prescription play a crucial role in the preservation and advancement of traditional Chinese medicine (TCM) theories. They represent a significant milestone in the ongoing development and transmission of TCM knowledge and practices and are considered one of the breakthroughs in the development of TCM inheritance. In the process of developing ancient classic prescriptions, many problems may still arise in ensuring quality consistency between traditional methods and modern production processes, among which the extraction process poses major challenges. This paper introduces a practical approach extracting an ancient classic prescription using a modern extraction process. The technique is demonstrated through the study of the extraction process of Shenshou Taiyi powder (STP). Methods: This study focuses on optimising the STP extraction process to ensure consistency in the quality of the product obtained through ancient and modern processes using the standard relation and fuzzy analytic hierarchical process (FAHP) and criteria importance through intercriteria correlation (CRITIC) method integrated weights combined with the Box-Behnken response surface test. Using the contents of rosmarinic acid, isoimperatorin, puerarin, as well as the extract yield and fingerprint similarity as evaluation indexes of STP, the Box-Behnken response surface method was employed to examine the varying extraction parameters, including water addition ratio, extraction duration, and number of extractions. The weighted coefficients for each parameter were calculated by combining the benchmark correlation and FAHP-CRITIC method, deriving a comprehensive score. Results: The optimal extraction process for STP consisted of a two extractions, each using at a tenfold quantity of water, performed for one hour. Process verification across three separate batches yielded a comprehensive score of 94.7, with a relative standard deviation of 0.76%. Conclusions: The application of the Box-Behnken response surface method combined with standard relation and FAHP-CRITIC approach proved to be stable and feasible for optimising the extraction process of STP. [ABSTRACT FROM AUTHOR]

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To move from a traditional end of pipe approach into a more sustainable solid waste management system, the Jordanian Government has recently passed a set of new regulations The National Solid Waste Management Strategy has put a road map to encourage circular economy practices. One of the considered policy instruments is the adoption of the extended producer responsibility (EPR). The current study aimed to adopt a multi-criteria decision-making method to select the most convenient EPR structure within the Jordanian context. The study used analytical hierarchy process (AHP) and fuzzy AHP (FAHP) techniques to select the suitable type of producer responsibility organization (PRO) structure. A four-level hierarchy model was constructed with 4 criteria, 10 sub-criteria and 3 PRO alternatives. The analysis revealed that the legal and administrative criteria is the most important one (0.47) followed by environmental criteria (0.22), whereas the least important ones were socio-economic (0.17) and technical criteria (0.13). The most preferable PRO alternative was found to be PRO with profit. There were slight differences between all weight values under AHP and FAHP. Despite the availability of several laws, there is a need to develop the legal and administrative framework to enable the adoption of EPR in Jordan. Research should be the first step in the process of EPR system design. None of the previous studies conducted used the AHP and FAHP in assessing and selecting the EPR systems. [ABSTRACT FROM AUTHOR]

This research examines the risk of natural disasters for offshore wind turbines together with their potential wind energy capacity to help the site selection of offshore wind power farms. Through evaluations of expert questionnaires, we use the fuzzy analytic hierarchy process to weight how natural disasters damage the sub-assemblies of an offshore wind turbine, then obtain the natural disaster risk assessment model, and finally utilize ArcGIS Pro 3.2 to map the potential wind farm sites for the waters off Taiwan's west coast. We identify that typhoons are the most threatening type of disaster to generators, rotor blades, and rotor hubs; earthquakes are the most threatening to towers; and lightning is the most threatening to transformers. For the whole wind turbine, wind is ironically the most threatening natural disaster, followed by lightning, sea waves, and then earthquakes. Lastly, we examine the results by overlapping the offshore wind farms developed and planned in Taiwan, which coincide with locations in relatively low risk and high wind speed areas. [ABSTRACT FROM AUTHOR]

Background: The relationship between tooth colour and individual satisfaction in oral aesthetics has long been a topic of interest. In this study, we utilized the fuzzy analytic hierarchy process (FAHP) to investigate the impacts of sex and age on tooth colour preference. The findings of this study should provide a scientific basis for oral aesthetic practice. Methods: In the current study, a random selection method was employed, and a survey was completed by 120 patients. To obtain tooth colour data, standard tooth colour charts were used. Smile photos were taken as template images using a single-lens reflex camera. The FAHP was utilized to conduct a weight analysis of tooth colour preferences among patients of different sexes and age groups. Results: There were significant differences in tooth colour preference based on sex and age. Men tend to prefer the B1 colour, while women may prioritize the aesthetic effects of other colours. Additionally, as patients age, their preferences for tooth colour become more diverse. These findings offer valuable insights for oral aesthetics practitioners, enabling them to better address the aesthetic needs of patients across different sexes and ages. This knowledge can aid in the development of more personalized treatment plans that align with patients' expectations. Conclusion: In this study, we utilized scientific analysis methods to quantify the popularity of different tooth colours among various groups of people. By doing so, we established a scientific foundation for clinical practice. The findings of this study offer valuable insights for oral aesthetic research, enhancing our understanding of tooth colour. Additionally, these findings have practical applications in the field of oral medicine, potentially improving patients' quality of life and overall oral health. [ABSTRACT FROM AUTHOR]

Slums are characterized as some of the most impoverished and vulnerable communities within urban areas. They often face a multitude of challenges, including extreme poverty, social marginalization, and inadequate infrastructure. The poor quality of buildings and the lack of adequate infrastructure further exacerbate the vulnerability of slum dwellers to the impacts of flooding. This study focuses on accurate assessment of flood risk in slum area of the Dhaka metropolitan area, the capital of Bangladesh. The manmachine interactive method was utilized to extract slum information from Sentinel-2A satellite imagery. Thirteen evaluation indicators were selected from the aspects of hazard, sensitivity, exposure, and prevention and mitigation capacity. The fuzzy analytic hierarchy process (FAHP) was employed to determine the relative weights of these indicators. A comprehensive evaluation model for flood disaster risk was established, enabling the determination of the spatial distribution of flood risk in slums of Dhaka city. The results indicate that the flood risk distribution in the slums of Dhaka city exhibits an overall high flood risk. The slums with very high flood risk constitute about 22.035% of the total area and are concentrated in Badda, Khilkhet, and Dakshinkhan districts. Slums with high-risk constitute 41.600% of the total area and are located mainly in Turag, Pallabi, Badda, and Gulshan districts. Those areas with abundant rainfall, dense river networks, and flat topography have higher flood risk in slums compared to other regions. These research findings can be a reference for regional flood risk zoning, prevention, and sustainable development planning. [ABSTRACT FROM AUTHOR]

Purpose: Heightened public concerns for the global environment due to human overexploitation have given rise to many green product initiatives by businesses. Green cosmetics (GC) are products developed and marketed based on ecological sustainability and have shown increasing consumer appeal worldwide. The current research investigates the antecedents of green cosmetics consumption among Indian GC users, hitherto un-investigated comprehensively. Design/methodology/approach: The study is a cross-sectional pairwise comparison of green evaluation criteria for cosmetics using an expert panel of thirty Indian cosmetic users using a fuzzy analytic hierarchy process (F-AHP) and investigate the impact of a comprehensive list of antecedents on the multi-criteria category consumption decision. Findings: The study results indicate that perceived consumer effectiveness is the most critical factor for green cosmetics consumption in India, followed by brand trust, behavioural control, and environmental effectiveness. The least important factors are price and social norms. Research limitations/implications: As the GC category is at nascent stage in India the investigation is limited to the GC category innovators – a set of people high in intellectual and financial resources. The study is also limited to women users as the male cosmetic market in the country is still very small. Practical implications: The study results can help marketers in designing and implementing GC related marketing strategies to deliver higher customer value to the target segment. Academicians can use the study results for better prediction of category related behaviour of consumers. Social implications: The study results will help promote GC category adoption and usage which can benefit the environment and consumer health. Originality/value: The study contributes to literature and practice by assessing a comprehensive set of critical antecedents to GC adoption using a novel approach of F-AHP and an expert user panel. The study results offer insights to marketers that can be used to develop suitable strategies to convert non-GC users into GCs in India and similar markets, improving category penetration and benefitting marketers, retailers, users, and the environment. [ABSTRACT FROM AUTHOR]

Over 50% of nuclear power plants (NPPs) worldwide have operated for over three decades, leading to a surge in decommissioning projects. This study addresses the gap in current guidelines by analyzing risks in nuclear decommissioning. Using the fuzzy-AHP technique, tasks within dismantling radioactive concrete structures are prioritized. Findings reveal structural and human-related risks across five main cutting tasks. Collision emerges as a significant concern, particularly during wire saw installation and concrete block hoisting hole creation. Subcategory risk priorities highlight variations in risk across tasks, with jamming, falling, and falling objects identified as top concerns during wire saw transportation. This study emphasizes the importance of comprehensive risk assessment in enhancing safety during decommissioning. It underscores the need to consider both physical risks and risks to personnel throughout the process. By prioritizing safety, stakeholders can ensure worker safety and operational efficiency while minimizing hazards. This research contributes to standardized safety protocols for nuclear decommissioning worldwide, aligning with sustainable energy practices. The outcomes offer practical insights for safety manual development and decision-making processes. This study represents progress in ensuring safety during nuclear decommissioning, paving the way for further refinement of safety protocols and guidelines tailored to decommissioning sites. [ABSTRACT FROM AUTHOR]

Introduction: The development of sustainable animal husbandry plays an important role in establishing food security, improving welfare, increasing the income of rural households, improving productivity, creating job opportunities, creating links with other economic sectors, and rural development. In Iran, the issue of sustainable development of the animal husbandry industry and creating sustainability is one of the most important issues of the country because the animal husbandry industry is one of the most important sub-sectors of the agricultural industry, which produces the most important basic food of the country, i.e., red meat. The main goal of this research is to identify and prioritize the obstacles and problems of sustainable animal husbandry development in Guilan province. The development of the agriculture and animal husbandry industry is necessary to access a sufficient amount of food and energy and to cover the ever-increasing demand due to the increase in the population. Guilan province has a suitable capacity for the development of animal husbandry activities. Paying attention to the existing research gaps, by summarizing findings in this field, using the opinion of animal husbandry industry experts, and the application of the multi-indicator decision-making model, this study identified the obstacles and problems for the development of sustainable animal husbandry in Guilan province. Materials and methods: Various criteria have been introduced in previous research as key factors for the sustainable development of animal husbandry, the most important of which included structural, institutional, economic, cultural, social, environmental, macro goals and strategies, the process and cycles of providing inputs, and selling livestock products. The decision tree was drawn using the findings of similar studies and the opinions of provincial experts in this industry. The data collection tool is a questionnaire for pairwise comparisons of decision tree criteria and sub-criteria. To determine the weight of the criteria and sub-criteria included in the decision tree, the opinions of 10 experts in this field in Guilan province were collected and analyzed using the Fuzzy Hierarchy Process (FAHP). Fuzzy set theory is a mathematical theory designed to model the ambiguity of processes related to human knowledge. The decision maker can freely choose the range of desired values. Also, the uncertain judgment of the expert can be expressed by a fuzzy number. In this method, fuzzy numbers are used for the pairwise comparison of options, and the decision maker can express the pairwise comparisons of the elements of each level in the form of triangular fuzzy numbers. The decision tree for this research has five main criteria including institutional, environmental, social and cultural, structural, and economic factors, and 31 different sub-criteria. FAHP is a systematic method that uses the concepts of fuzzy set theory and hierarchical structure analysis. The calculated weights are a suitable basis for prioritizing the main obstacles and problems in the sustainable animal husbandry industry development of Guilan province. Modeling and obtaining the results were done in the MATLAB software. Results and discussion: The results of the research showed that from the point of view of experts, institutional and economic obstacles with the weights of 29.71% and 19.23%, respectively, are considered to be the most important obstacles to the development of sustainable animal husbandry in Guilan province. On the other hand, the sub-criteria of low attention to the animal husbandry sector in the provincial policies from the institutional criterion, the inappropriateness of the materials used, considering the weather conditions from the environmental criterion, the low status and job position of animal husbandry from the social and cultural criterion, the lack of high-yielding breeds consistent with the conditions of the region from the structural criterion, and the lack of adequate insurance coverage from the economic criterion have the highest rank among the sub-criteria. Conclusions: The obtained results indicated the high level of obstacles and problems for the development of sustainable animal husbandry in Guilan province, which requires the attention of policymakers and the development of a policy package that fits the priorities determined in this study. [ABSTRACT FROM AUTHOR]

Landslide risk assessment in coal mining economic cities faces challenges due to inadequate knowledge of indicator systems and modeling techniques, despite its crucial significance in geological disaster management. This study addresses this gap by proposing a novel framework encompassing data preparation, susceptibility analysis, consequence analysis, and final risk assessment. The primary objective is to reduce the complexity and inherent uncertainties associated with landslide risk assessment in these specific urban environments. First, two comprehensive databases for the indication system were established. One database focuses on landslide susceptibility, considering the region’s mining disturbances and disaster-prone environments. The other evaluates the effect of consequences while accounting for the pertinent risk variables. Second, a hybrid machine learning model called Geo-FR-SVM was developed by combining the GeoDetector, Frequency Ratio method, and Support Vector Machine model to improve landslide susceptibility mapping. Integrating the susceptibility map with the consequence map created using fuzzy set theory and fuzzy analytical hierarchy process methodologies resulted in the final landslide risk map. Our analysis revealed that elevation, distance to rivers and roads, groundwater level, and coal mining subsidence were the key factors influencing landslide occurrence in the Xishan mine area. The majority of the study area exhibits low landslide risk. However, higher consequence zones were primarily concentrated in highly populated residential regions and coal mine industrial zones in the east-central and western urban areas. Additionally, they are mainly distributed along the roads in the center region. With comparatively large percentages of landslide high-risk and extremely high-risk regions (4.596%, 3.855%, 3.625%, and 3.188%, respectively) at Tunlan Mine, Xiqu Mine, Zhenchengdi Mine, and Baijiazhuang Mine, these findings highlight the need for these mines to prioritize potential landslide identification and risk mitigation strategies. This framework offers broad applicability to other coal mining economic cities, serving as a valuable foundation for landslide risk management decision-making.

E-learning approaches have emerged as a prominent method in educational institutions in Malaysia since the Covid-19 outbreak. Moreover, rapid growth in educational technologies with new software and high-end hardware has provided better accessibility for e-learning. To ensure efficient and conducive e-learning environment, the factors and sub-factors that leads towards e-learning success must be recognized and identified. Therefore, this research aims to rank the important factors and sub-factors influencing the success of e-learning in Mathematics from lecturers’ perspectives. Fuzzy Analytic Hierarchy Process (FAHP) is used in analyzing the data collected. The result of this study shows that among the four chosen success factors, Quality of Infrastructure and System is the most important factor (0.3876), followed by Characteristics of Students towards e-learning (0.2428), Quality of Design and Courses (0.1942) and lastly Characteristics of Lecturers Towards e-learning (0.1753). The top four out of 12 e-learning success sub-factors are Design and User Interface System (0.1447), Students’ Attitude Towards e-learning (0.1232), Understanding the Use of Infrastructure (0.1218) and Level of Product Reliability (0.1211). This finding may help to improve the effectiveness of e-learning process to not only for schools and universities but also for corporate and business sectors especially in global training programs. For future studies, students’ perspective towards e-learning success in Mathematics and other subjects should be further studied in order to have a complete view of success factors.

Multi-hazard events have received attention globally due to their increasing frequency and severity in recent years. The coastal region of Bangladesh is particularly vulnerable to multi-hazard events induced by tropical cyclones (TC), including coastal flooding, extreme precipitation, extreme winds, and salinity intrusion. These events inflict substantial damage on human lives and property, yet there has been limited effort to quantitatively assess the associated risks. This study aims to investigate the spatial distribution of multi-hazard risks stemming from TC events, employing a Fuzzy Analytic Hierarchy Process (FAHP) approach. Risk is assessed in relation to hazard, exposure, vulnerability, and mitigation capacities in the study area. Various indicators are selected to define each of these four risk components, with weights determined through expert input for FAHP modeling. The results indicate that more than 50% of the area faces multi-hazard risks, with the hazard component exhibiting the highest degree of risk association, followed by exposure, vulnerability, and adaptive capacity. Storm surge-induced flooding is identified as the most prominent hazard during TC events, followed by intense precipitation, extreme winds, and salinity intrusion. Areas characterized by high population density, a large number of vulnerable populations (e.g., those under 15 years or over 65 years), low elevation, and underdevelopment are found to be the most risk prone. Notably, the presence of hospitals, cyclone centers, and effective warning systems in proximity to an area enhances its potential to withstand multi-hazard impacts. Among the 19 coastal districts, Cox's Bazar and Feni are identified as the most risk prone. The framework and findings presented in this study offer valuable insights for the development and prioritization of multi-hazard risk mitigation policies by identifying the most vulnerable zones and the associated risk factors.

Introduction: Employee assistance programs require resources and manpower of various natures across different types of public sector organization. Methods: This study began by outlining elements for comparing employee assistance programs’ evaluation criteria in four types of public sector organization on the basis of 22 service measures for such programs implemented by the Ministry of Labor in relation to three major aspects: work, life, and health. Elements of the evaluation criteria for public sector employee assistance programs were determined by surveying a panel of experts using the modified Delphi method. Last, the weight associated with the elements of evaluation criteria were calculated using the fuzzy analytic hierarchy process, and the criteria of four types of public sector organization were explored. Results: Data analysis indicated that the weight and priorities associated with elements of evaluation criteria for EAPs implemented by four types of public sector organization were not fully identical. Discussion: The results of this study suggest that, in terms of EAPs, the Directorate-General of Personnel Administration of the Executive Yuan should be pursuant to appropriate employee assistance programs provided by various public sector organizations according to the needs of their employees as well as the diverse objective conditions in which these organizations operate. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Meeting the personalized needs of users is the key to achieving the sustainable success of a product. It depends not only on the product's functionality but also on satisfying users' emotional needs for the product's appearance. Therefore, researchers have been conducting research focusing on Kansei engineering theory to determine users' emotional needs effectively. The initial process involves accurately extracting and filtering emotional data and Kansei words from consumers. Thus, we propose an evaluation model to efficiently obtain, screen, and sort these Kansei words based on Kansei engineering, using household portable air conditioners as research subjects. By integrating techniques for online user comment mining methods, users' Kansei terms related to the product's appearance can be gathered efficiently. These terms are then combined with image samples and filtered to determine a final set of 16 Kansei word pairs. Subsequently, the fuzzy analytic hierarchy process (FAHP) is utilized to prioritize these terms, and the fuzzy comprehensive evaluation (FCE) method is used to validate the results and determine the applicability of the evaluation model. The results showed that Kansei words could be quickly and objectively acquired using existing text mining techniques on online reviews. Moreover, the weights of different Kansei terms of the product's appearance in the consumer's perception are accurately produced through the FAHP. This evaluation model marks a significant advancement in accurately obtaining users' emotional data in Kansei engineering. It offers valuable guidance for designing products that meet users' personalized needs, enhancing design efficiency and reducing resource wastage at the early stages of designing, and improving the sustainability development of Kansei engineering. [ABSTRACT FROM AUTHOR]

With the worldwide recognition of environmental conservation, green production has emerged as a pivotal concern for nearly every manufacturer, and it will be determined for a long time to determine the sustainability of the manufacturer. Therefore, the performance evaluation system must be performed for green suppliers to determine the applicability of the supplier and the company. In a complex transaction and operating environment, suppliers choose to face information asymmetry usually. Fortunately, with the development of computer technology, blockchain technology enhances not only traceability and decentralization in supply chain management, but also boosts the flexibility of the supply chain. Since it is unclear whether the FAHP (Fuzzy Analytic Hierarchy Process) is better than the AHP (Analytic Hierarchy Process) in terms of the quality of decision solution, the method of a mathematical model is first adopted to determine the difference between AHP and FAHP. Then, taking H company's green supplier selection decision as the research object, determine five evaluation criteria, such as quality, delivery, blockchain willingness, costs, and environment protection by literature combing method. Based on FL (Fuzzy logic analysis method), AHP, and FAHP three methods to study the green supplier selection of H company. The result shows that different evaluation methods of FL, AHP, and FAHP have no significant effect on the comprehensive ranking of vendors, and AHP is particularly suitable for a company to select its alternative vendors. [ABSTRACT FROM AUTHOR]

The ever-increasing consumption of electrical energy due to increasing requirements arising in parallel with the developing technology forces manufactures and users to seek new and environmentally compatible energy resources. Due to it endless energy potential and continuity, wind energy, which has been used by humanity for various purposes for centuries, continues its journey, which started with windmills that transform one form of mechanical energy into another, with offshore wind energy turbines. In this study, installation site selection, which is the first step for floating offshore wind turbine installation, is carried out. First, a Fuzzy Analytic Hierarchy Process (F-AHP) is applied to obtain the weights of criteria. Transformed alternatives and criteria in a fuzzy decision matrix through triangular fuzzy numbers are used to obtain a database via a Geographic Information System (GIS). Finally, the installation site and study area are determined. This area is located in the Northeast Aegean Sea, between Çanakkale and Gökçeada, 12 km to the northeast of Gökçeada, and 12 square kilometers. The minimum distance of the area to ship routes is 3000 m, and its minimum distance to fault lines is 2000 m. The average sea depth is 110 m, and the average wind speed is 9.26 m/s (18 knots). With this potential, enough energy can be generated for settlements on Gökçeada and the coastlines. [ABSTRACT FROM AUTHOR]

Copyright of Itobiad: Journal of the Human & Social Science Researches / İnsan ve Toplum Bilimleri Araştırmaları Dergisi is the property of Itobiad: Journal of the Human & Social Science Researches and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Knowing the energy demand guides the future investments of countries. Nuclear power plant (NPP) is an important resource to guide sustainable energy policies in sectoral investments. The first step for the reliable, accurate and energy-demand-based use of this resource is the NPP installation on a suitable site. Therefore, spatial evaluation is required for NPP in terms of planning and management. The purpose of this study was to identify the potential province for NPP installation depending on the energy demand and to select the most suitable sites in this province by using geographic information system integrated with fuzzy analytic hierarchy process from multi-criteria decision making. First of all, the energy demand map for Turkey was produced by considering the demographic and economic criteria. From this map, it was concluded that "Bursa" has a very high energy potential province. Then, the suitability map was created by handling the environmental, social and safety criteria for site selection in Bursa. Results showed that Bursa has a very high suitability site for NPP, which spans 1092 km2 (10%) after deducting the restricted sites, relatively and least suitable sites. Finally, nine candidate sites were selected from among the most suitable sites, and these sites were evaluated in terms of tourism, agricultural activities, sufficient cooling water and area sizes. As a result of the evaluations, two priority sites (CS-7 and CS-9) for NPP were found in Bursa. The examination of NPP site suitability would assist in the country's development and spatial plans. [ABSTRACT FROM AUTHOR]

This study established a comprehensive evaluation model for soil fertility in an open-pit coal mine dump in Jiuxian County of Hequ by drawing on Fuzzy Analytic Hierarchy Process (FAHP) and expert scoring theory. 4 criteria and 25 factors were applied for soil structural stability, water retention capacity, fertility retention capacity, and biological activity. Using the YAAHP calculation software, this study proposed the weights of various influencing factors on the soil fertility restoration ability of the waste dump. The results indicate that soil fertility retention ability bears the highest weight (0.547 7), followed by soil water retention ability (0.198 0), soil biological activity (0.140 8), and soil structural stability (0.113 5) in the evaluation rubric, while organic matter F1 bears the highest weight (0.116 2) among other factors; Based on on-site sampling, results showed that the soil quality in the reclaimed area outperformed the uncultivated area, but still persists at lower to medium levels. The main factor for soil resilience is soil fertility retention capacity, especially the content of soil organic matter. Soil fertility restoration model offers references for improving soil quality in waste dump, accelerating soil reconstruction, and promoting soil ecosystem restoration.

Objective: The progress and emergence of new technologies in the present century have made academic libraries revise, develop, and transform their programs and services. In other words, recent developments have prompted the managers and librarians of libraries around the world to take the changes seriously, think about the horizons of the users’ present and future needs, investigate the challenges they are likely to face on their way to achieving their goals, and devise serious plans, particularly strategic ones, by predicting the trends of future developments. So, systematic future studies need to be conducted on academic libraries to enable them to keep up with modern developments, deal with them effectively, and maintain their status and persistency in current competitive conditions. In this regard, the current article aims to study and design scenarios for the future of academic libraries in Iran in order to help provision of suitable strategies for the promotion and development of these libraries.Methodology: The current research is a survey-applied in which 16 academic libraries have been selected by the quota sampling method and a number of professors and related experts, together with the managers or assistants of the libraries of the selected universities, have formed an expert panel. Besides, four questionnaires were developed to gather the required data. To achieve the research goals, firstly, a comprehensive literature review was conducted to extract the drivers affecting the future of the target academic libraries. These drivers were localized and screened by experts, using the fuzzy Delphi method. After that, the weight of each driver was calculated using the fuzzy Analytic Hierarchy Process method. In the end, the key drivers and final uncertainties were determined by combining the results with Cross Impact Analysis. Findings: In the first step, reviewing the studies led to the extraction of 112 candidate driving forces that can influence the future of academic libraries in eight dimensions, including the political, economic, social, technological, legal, and environmental dimensions (for investigating external environments) in addition to the “structural-managerial” and “the nature and services of libraries” dimensions. After determining the key drivers, and analyzing their mutual effects, the second stage was completed by formulating scenarios facing university libraries by forming a panel of experts, using the Delphi method and future research software.Conclusion: Finally, after analyzing the aspects of the final uncertainties, among the possible candidate scenarios, four plausible scenarios, namely, Utopia, Treasure key, Vicious circle, and Ruins, were drawn as the future possible state of Iranian academic libraries, from which the “Utopia scenario” was picked up as the imagined future.

In order to improve the rationality of the evaluation of water intake methods for large amplitude water level pumping stations, a set of evaluation index system for water intake methods of large amplitude water level pumping stations was established. It combined the Cloud Model (CM) with Analytic Hierarchy Process (AHP) and Entropy Weighting Method (EWM) to assign subjective and objective weights to each evaluation indicator, proposed a comprehensive evaluation method for the water intake mode of large amplitude water level pumping stations based on the combination of CM and Fuzzy Analytic Hierarchy Process (FAHP), and used the cloud model comprehensive similarity comparison method to determine the optimal water intake plan. Taking the comprehensive utilization and replacement of water resources in the First Phase of the Erhai Lake Water Supply Project in Ludila, Yunnan Province as an example, practical application was carried out. The results show that the comprehensive evaluation cloud maps of the four water intake schemes (vertical shaft dry chamber pump room, rack wet chamber pump room, floating boat pump room and cable car pump room) are all located between the evaluation level Ⅲ and level Ⅳ standard cloud maps, the comprehensive evaluation cloud map of the floating boat pump station has the highest similarity with the cloud map of the Grade Ⅳ standard, indicating that the water intake method of the floating boat pump room is the optimal solution. [ABSTRACT FROM AUTHOR]