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Background: The hospital ward system is the core service unit of a hospital and an important aspect of hospital management. The maturity of the hospital ward system represents the level of development and improvement in ward management and services. In order to improve the quality of hospital services, it is significant to assess the maturity of the ward system. Although various assessment methods have been proposed in existing studies, there are some issues such as a single-dimensional factor system, subjectivity in qualitative factor values, and insufficient objectivity in the evaluation methods., Methods: Therefore, based on the data collection of the factors used in the existing literature, this study made correlation analysis, determined the similarity of factors, and established a maturity assessment factor system satisfying distinctiveness and comprehensiveness. Furthermore, an evaluation method for the weights of each factor was proposed based on the fuzzy analytic hierarchy process, while taking account of the ambiguity of expert information. In addition, through the technique for order of preference by similarity to ideal solution method, an objective evaluation method for the maturity of the hospital ward system was established. Finally, a case study involving 6 hospitals in a specific location was conducted., Results: There are a total of 16 factors used to assess the maturity of the hospital ward system, among which the most important is Doctor service. The maturity degree of the 6 researched hospitals are 0.4517, 0.0035, 0.4254, 0.8681, 0.6636, 0.1586, and the maturity degree of the 6 researched hospitals are II, I, II, IV, III, I., Conclusion: The factor system constructed in this study effectively reflected the importance of human-related factors in the development process of ward system. The evaluation results were consistent with the actual situation, demonstrating the effectiveness of the proposed method., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.)

It is a multi-criteria decision issue to conduct a risk assessment of the tunnel. In this paper, a tunnel collapse risk assessment model based on the improved theory of quantification III and the fuzzy comprehensive evaluation method is proposed. According to the geological conditions and the construction disturbance classification method, the evaluation factors are selected, and the tunnel collapse risk level is divided into 5 levels according to the principle of maximum membership degree. The three groups of scores with the largest correlation ratio are calculated by the theory of quantification III to form the X, Y, and Z axes of the spatial coordinate system, The spatial distance of each evaluation factor is optimized by the Kendall correlation coefficient combined with the empirical formula, so that it can be used to judge the probability of the occurrence of the evaluation factor; taking the coupling of the objective entropy weight method (EW) and the subjective analytic hierarchy process (AHP) as the weight. Finally, the fuzzy comprehensive evaluation method is used to determine the possibility classification of tunnel collapse. Taking the Ka-Shuang water diversion tunnel as a case study, the comparison between the evaluation results of 10 tunnel samples and the status quo of the actual engineering area verifies the reliability of the method., (© 2022. The Author(s).)

Risks exist in medicine related fields, which cannot be defined and quantified precisely. It is necessary to adopt a method for the risk assessment of uncertain and fuzzy phenomenon. This paper summarizes the thinking, procedure, advantage and application of fuzzy analytic hierarchy process in the risk assessment in medicine related fields for the purpose of providing reference for its further application.

The field of occupational health and safety (OHS) focuses on reducing occupational accidents to an acceptable level. OHS covers systematic efforts aimed at providing employee health, safety and welfare in the workplace. This study proposes a new approach for risk assessment in the field of OHS. It integrates the Pythagorean fuzzy analytic hierarchy process (PFAHP) and fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (FVIKOR) into a risk assessment process. The PFAHP is used in weighting the risk parameters. FVIKOR is then applied to prioritize the hazards. To demonstrate the applicability and validity of the proposed approach, a case study of a barrel external surface oxidation and colouring unit of a gun and rifle production facility is performed. A comparison is also provided between the proposed approach and an intuitionistic fuzzy sets-based approach. The proposed approach is found to produce reliable outcomes that better represent the vagueness of the decision-making process.

Objective: The present study aimed to identify and prioritize control measures of violence against health care workers (HWs) using the fuzzy analytical hierarchy process (FAHP) and fuzzy additive ratio assessment (ARAS-F)., Background: Occupational violence is a pervasive problem in health care centres. Reducing violence against staff is one of the challenges for health care managers., Method: At the first stage, the most common criteria and control options for violence against HWs were identified and extracted using a review of previous studies. At the next stage, criteria for selection of control measures were prioritized using the FAHP. Finally, control measures of workplace violence were prioritized using the ARAS-F method., Results: Results of the FAHP indicated that safety and efficiency were the most important criteria. Results of the ARAS-F also revealed that 'increasing number of security personnel' and 'training staff' were the best recommendations for controlling violence against HWs., Conclusion: Based on expert's opinions, administrative measures are the optimal ways to control violence at health centres; therefore, it is suggested that violence control programmes should be more focused on administrative measures., Implications for Nursing Management: These results could assist nursing management to take best strategies for controlling occupational violence based on multi-criteria decision-making methods., (© 2020 John Wiley & Sons Ltd.)

With the rapid development of social economy and the increasing environmental pollution in China, the government's environmental investment has been gradually increasing, and an effective evaluation system is required to study the benefits from environmental investment. Based on the literature review and current situation analysis of the benefits from environmental investment, the selection of indicators was determined after the analysis of the economic, environmental, and social benefits of environmental investment. The gray relation analysis (GRA) method was adopted to test the correlation between each indicator and environmental investment, the combination of analytic hierarchy process (AHP) and Delphi method was used to determine the relative weight of each indicator, and a fuzzy comprehensive evaluation model was established for benefits from environmental investment. The study found that benefits from environmental investment in China had been improving over years but still not satisfying, and several suggestions had been proposed according to the analysis.

The primary goal in project portfolio management is to select and manage the optimal set of projects that contribute the maximum in business value. However, selecting Information Technology (IT) projects is a difficult task due to the complexities and uncertainties inherent in the strategic-operational nature of the process, and the existence of both quantitative and qualitative criteria. We propose a two-stage process to select an optimal project portfolio with the aim of maximizing project benefits and minimizing project risks. We construct a two-stage hybrid mathematical programming model by integrating Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Inference System (FIS). This hybrid framework provides the ability to consider both the quantitative and qualitative criteria while considering budget constraints and project risks. We also present a real-world case study in the cybersecurity industry to exhibit the applicability and demonstrate the efficacy of our proposed method., (Copyright © 2019. Published by Elsevier Ltd.)

Based on the noninvasive detection indeices and fuzzy mathematics method, this paper studied the noninvasive, convenient and economical cardiovascular health assessment system. The health evaluation index of cardiovascular function was built based on the internationally recognized risk factors of cardiovascular disease and the noninvasive detection index. The weight of 12 indexes was completed by the analytic hierarchy process, and the consistency test was passed. The membership function, evaluation matrix and evaluation model were built by fuzzy mathematics. The introducted methods enhanced the scientificity of the evaluation system. Through the Kappa consistency test, McNemer statistical results ( P = 0.995 > 0.05) and Kappa values (Kappa = 0.616, P < 0.001) suggest that the comprehensive evaluation results of model in this paper are relatively consistent with the clinical, which is of certain scientific significance for the early detection of cardiovascular diseases.

The Yellow River Delta (YRD), located in Yellow River estuary, is characterized by rich ecological system types, and provides habitats or migration stations for wild birds, all of which makes the delta an ecological barrier or ecotone for inland areas. Nevertheless, the abundant natural resources of YRD have brought huge challenges to the area, and frequent human activities and natural disasters have damaged the ecological systems seriously, and certain ecological functions have been threatened. Therefore, it is necessary to determine the status of the ecological environment based on scientific methods, which can provide scientifically robust data for the managers or stakeholders to adopt timely ecological protection measures. The aim of this study was to obtain the spatial distribution of the ecological vulnerability (EV) in YRD based on 21 indicators selected from underwater status, soil condition, land use, landform, vegetation cover, meteorological conditions, ocean influence, and social economy. In addition, the fuzzy analytic hierarchy process (FAHP) method was used to obtain the weights of the selected indicators, and a fuzzy logic model was constructed to obtain the result. The result showed that the spatial distribution of the EV grades was regular, while the fuzzy membership of EV decreased gradually from the coastline to inland area, especially around the river crossing, where it had the lowest EV. Along the coastline, the dikes had an obviously protective effect for the inner area, while the EV was higher in the area where no dikes were built. This result also showed that the soil condition and groundwater status were highly related to the EV spatially, with the correlation coefficients &minus;0.55 and &minus;0.74 respectively, and human activities had exerted considerable pressure on the ecological environment.

Innovation is key to gaining a sustainable edge in an increasingly competitive global manufacturing landscape. For Bangladesh's manufacturing sector to survive and thrive in today's cutthroat business environment, adopting transformative technologies such as the Internet of Things (IoT) is not a luxury but a necessity. This article tackles the formidable task of identifying and comprehensively evaluating the impediments to IoT adoption in the Bangladeshi manufacturing industry. We delve deeply into the complex terrain of IoT adoption challenges by synthesizing expert insights and a meticulously selected body of contemporary literature. We employ a robust methodology combining the Delphi method with the fuzzy Analytical Hierarchy Process to systematically analyze and prioritize these challenges. Using this methodology, we leveraged the combined expertise of domain specialists and subsequently employed fuzzy logic techniques to address the inherent ambiguities and uncertainties within the data. Our findings highlight this clear path. They reveal that among the myriad barriers, "Lack of top management commitment to implementing new technology" (B10), "High initial implementation investment costs" (B9), and "Risks associated with switching to a new business model" (B7) loom most extensive, demanding immediate attention. These insights are not confined to academia but serve as a pragmatic guide for industrial managers. Armed with the knowledge gleaned from this study, managers can craft tailored strategies, set well-informed priorities, and embark on a transformational journey toward harnessing the vast potential of IoT in the Bangladeshi industrial sector. This article provides a comprehensive understanding of IoT adoption challenges and industry leaders with the tools necessary to navigate these challenges effectively. This strategic navigation, in turn, contributes significantly to enhancing the competitiveness and sustainability of Bangladeshi manufacturing in the IoT era. [ABSTRACT FROM AUTHOR]

Development of urban transport facilities via analysing indicators has become one of the new domains explored worldwide, as cities are growing with no control. The present state of sustainability testing practices feels that technical analysis is rather very complex collaboratively and comprehensively met with local statements. As a result, developing indicators assessment techniques has become inevitable to deal with these challenges. In this study, a comprehensive transport assessment index such as trustworthiness, Amenity, Receptivity, Assurance and Affinity for the cities through passenger response can be useful for the researchers in the city. A set of 5 indicators has been formulated among 500 respondents that might influence and shape urban public transport performance. For finding the Key Performance Indicator (KPI) of the Urban transport system, the hybrid Complex Proportional Assessment (COPRAS)—Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to measure the quantitative weight to analyze the complex process of perceived service quality. This model is validated by different Multi-Criteria Decision Making (MCDM) such as Analytic Hierarchy Process (AHP) and Fuzzy-AHP by comparing performance measures for randomly selected elements, which is new to mixed traffic flow conditions. The performance obtained such as computational complexity and agility in decision making by the hybrid COPRAS-TOPSIS are 132 and 1245. Hence, the proposed approach was more accurate than conventional ones, thus used to support decision-makers for long-term designing and planning of transport networks based on priority. Based on these factors, the present study successfully develops and applies KPI analysis prediction of the general transport approach in the background of India. [ABSTRACT FROM AUTHOR]

Failure mode effects and criticality analysis (FMECA) is widely employed across industries to recognize and reduce possible failures. Despite its extensive usage, FMECA encounters challenges in decision‐making. In this paper, a new fuzzy resilience‐based RPN model is created to develop the FMECA method. The fuzzy model transcends the limitations associated with traditional risk priority number calculations by incorporating factors beyond frequency, severity, and detection. This extension includes considerations impacting system cost, sustainability, and safety, providing a more comprehensive risk assessment. In addition, to create trust in decision‐makers, a robust assessment approach is suggested, integrating three methodologies. In the initial phase, the fuzzy analytical hierarchy process and the grey relation analysis method are used to determine the subjective weights of different risk factors and resolve the flaws associated with the deficiency of constructed fuzzy inference rules. In the second phase, an entropy method is applied to handle the uncertainty of individual weightage calculated and capture different conflicting experts' views. The suggested approach is validated through a case study involving a gas turbine. The results demonstrate significant differences in failure mode prioritization between different approaches. The introduction of MTTR addresses critical shortcomings in traditional FMECA, enhancing predictive capabilities. Furthermore, the hybrid approach improved criticality assessment and failure mode ranking, classifying failure modes into fifteen categories, aiding decision‐making, and applying appropriate risk mitigation measures. Overall, the findings validate the efficacy of the proposed approach in addressing uncertainties and divergent expert judgments for risk assessment in complex systems. [ABSTRACT FROM AUTHOR]

The combined use of the Analytical Hierarchy Process (AHP) and Fuzzy Inference Systems (FISs) can significantly enhance the effectiveness of transformative projects in organizations by better managing their complexities and uncertainties. This work develops a novel multicriteria model that integrates both methodologies to assist organizations in these projects. To demonstrate the value of the proposed approach, we present an illustrative example focused on the implementation of Industry 4.0 in SMEs. First, through a review of relevant literature, we identify the key barriers to improving SMEs' capability to implement Industry 4.0 effectively. Subsequently, the AHP, enhanced through Dong and Saaty's methodology, establishes a consensus-based assessment of the importance of these barriers, using the judgments of five experts. Next, a FIS is utilized, with rule bases automatically derived from the preceding weights, eliminating the need for another round of expert input. This paper shows and discusses how SMEs can use this model to self-assess their adaptability to the Industry 4.0 landscape and formulate improvement strategies to achieve deeper alignment with this transformative paradigm. [ABSTRACT FROM AUTHOR]

Given the increasing demand for proteinaceous food products, aquaculture production of fish is on the rise. Due to its attractiveness, marine cage culture has gained attention in the aquaculture industry and has become profitable. This study focuses on the hydrodynamic variables to determine suitable areas for establishing fish cage sites in the waters surrounding Qeshm Island. Hydrodynamic variables were estimated through oneyear numerical modeling using Mike 21. By applying the Analytic Hierarchy Process (AHP) and fuzzy logic to the variables, suitable areas in four sections were identified: east of Qeshm Channel, south of Hormuz Island - between Qeshm City and Larak Island - north of Larak, the coast from Ramchah to Hengam Island, and Dayerstan bay to Salakh. The results indicate that, in addition to the previously identified areas in similar studies, the northern part of Larak Island and the center of eastern Qeshm Channel are also suitable and could be options for expanding this industry in the future with the development of cage technology and infrastructure. Areas identified in previous studies, such as the coasts from Souza to Shibderaz and Dayerstan Bay, may face significant wave height threats in severe storm conditions. However, areas like Dargahan can be less risky regarding hydrodynamic conditions due to limited fetch exposure in weather conditions. It is beneficial to conduct studies on cage deployment for development and planning of the maritime economy. By incorporating water quality indicators alongside hydrodynamic variables, more accurate results can be obtained, thereby reducing investment risks in this industry. [ABSTRACT FROM AUTHOR]

The rapidly expanding Internet of Medical Things (IoMT) landscape fosters enormous opportunities for personalized healthcare, yet it also exposes patients and healthcare systems to diverse security threats. Heterogeneous IoMT devices present challenges that need comprehensive risk assessment due to their varying functionality, protocols, and vulnerabilities. Hence, to achieve the goal of having risk-free IoMT devices, the authors used a hybrid approach using fuzzy logic and the Fuzzy Analytical Hierarchy Process (FAHP) to evaluate risks, providing effective and useful results for developers and researchers. The presented approach specifies qualitative descriptors such as the frequency of occurrence, consequence severity, weight factor, and risk level. A case study with risk events in three different IoMT devices was carried out to illustrate the proposed method. We performed a Bluetooth Low Energy (BLE) attack on an oximeter, smartwatch, and smart peak flow meter to discover their vulnerabilities. Using the FAHP method, we calculated fuzzy weights and risk levels, which helped us to prioritize criteria and alternatives in decision-making. Smartwatches were found to have a risk level of 8.57 for injection attacks, which is of extreme importance and needs immediate attention. Conversely, jamming attacks registered the lowest risk level of 1, with 9 being the maximum risk level and 1 the minimum. Based on this risk assessment, appropriate security measures can be implemented to address the severity of potential threats. The findings will assist healthcare industry decision-makers in evaluating the relative importance of risk factors, aiding informed decisions through weight comparison. [ABSTRACT FROM AUTHOR]

Introduction: The electricity generated from nuclear plants and petroleum- based products has a negative influence on the environment as a whole. It has shown the utility to search out and promote the utilization of renewable, environmentally friendly, and sustainable energy sources such as solar, wind, and geothermal. Nowadays, Wind energy resource has quickly emerged as the world's fastest-growing energy source. Methods: However, the selection of the most suitable places for developing a wind farm is a crucial challenge that can be seen as a problem of site selection, which involves numerous conflicting variables. Therefore, it is classified as an MCDM (multi-criteria decision-making) problem. The main objective of this research is to determine the best locations in Burundi for the installation of wind farms. The Fuzzy Analytic Hierarchy Process (FAHP) was used to weigh the criteria considering their relative importance. This study considers several key factors when determining the optimal location for a wind farm. These factors include wind speed, slope, proximity to the grid network, distance to roads, and land use/land cover (LULC). Furthermore, a geographic information system (GIS) is utilized to generate the final suitability wind farm locations map. Results and Discussion: The obtained results indicate that 20.91% of the whole study area is suitable nevertheless, only 1.96% is tremendously suitable for wind turbine placement. The western part of Burundi is the optimal area for constructing a wind farm, and the most is in Lake Tanganyika. [ABSTRACT FROM AUTHOR]

A slew of economic, environmental, and social concerns has pushed policymakers and governments to embrace renewable energy (RE) technologies in order to ensure a sustainable energy future. RE technologies have a beneficial effect on the environment and social well-being. Therefore, this study presents a method for systematically determining and ranking the benefits of adopting RE technologies in remote areas and possible solutions. The present analysis is structured into four distinct levels. The benefits of RE technologies were identified through a comprehensive review of relevant literature. The Delphi technique was employed to reach a consensus and classify the advantages. Fourteen benefits were determined and classified according to seven primary criteria. Furthermore, the Fuzzy Analytic Hierarchy Process was employed to determine the weights and rankings. The Fuzzy VIekriterijumsko KOmpromisno Rangiranje method was ultimately used to evaluate the potential alternatives. The integrated method result significantly reveals that the environmental criteria are the most critical factor, with a weight of (0.1727), and are followed by the quality of energy aspect, with a weight of (0.1617). Moreover, the global weights show that Sustainability is ranked highest, followed by Skill development, then the other sub-benefits within different categories. These two benefits have relative weights of (9.9164%) and (9.4924%), respectively. Furthermore, the most effective solution facilitating local and foreign investors was the most promising among the four recommended alternatives. The quote has proven that it benefits the government and policymakers in deploying RE technologies and resolving energy challenges in remote areas of developing nations like Pakistan. [ABSTRACT FROM AUTHOR]

In an evolving defense landscape with persistent security threats, enhancing Wireless Sensor Networks (WSN) for border security and advancing Intrusion Detection Systems (IDS) are vital for national defense and data integrity. In this research, we present a structured and innovative Analytical Hierarchy Process (AHP) Multi attribute Decision Making (MADM) Aggregated Multiple Type 3 Fuzzy Logic (IT3FLS) approach for the accurate prediction of the number of k-barriers for fast intrusion detection and prevention within WSN. Four possible features—the rectangular region, the detecting sensors range, the transmission range of the sensors, and the number of sensors for uniform sensor distribution—were used in the training and evaluation of the suggested model. Using Monte Carlo simulation, these traits are retrieved. This methodology outlined in four-stages. In Stage 1, it constructs Multiple IT3FLS through data collected from simulations. Stage 2 rigorously evaluates IT3FLS models using statistical measures, culminating in a performance matrix. Stage 3 integrates this matrix, enhancing understanding via the AHP-MADM to assign weights. In Stage 4, these weights optimize predictions through a weighted aggregation method. The system's results significantly enhance the accuracy of k-barrier predictions in intrusion detection. The model demonstrates its proficiency with a remarkable correlation coefficient (R) of 0.997, a minimal root mean square error (RMSE) of 5.36 and low bias of 1.7. Furthermore, the research assesses the proposed system's performance against multiple benchmark methods, confirming its superior accuracy and computational efficiency. [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 Biomedical Engineering Maintenance Services (BEMS) is a comprehensive maintenance program that ensures the safety and reliability of medical devices. Significant and crucial devices are identified and prioritized for best practice prior to the equipment life cycle to mitigate functional problems, alarmed by the Fourth Industrial Revolution (4IR) underlying the modernization agenda. A model of multi‐criteria decision‐making (MCDM) to prioritize medical devices according to their criticality is presented in this paper, with the utilization of quality function deployment (QFD) and fuzzy logic in the development of the model through a quantitative survey of experts from all regions in Malaysia. As a result, a customized version of the Asset Criticality Assessment (ACA) is developed and is recommended for use in more than 144 Ministry of Health (MOH) hospitals. Subsequently, real data of four selected devices are pulled from the Asset and Services Information System (ASIS) to demonstrate a relevant and comparable end‐result using the QFD and fuzzy logic. In essence, the key contribution of the customized ACA model is that it assesses a promising evaluation with a broader range on both the performance of medical devices and the appropriate asset replacement choices. This leads to an effective maintenance strategy for each device and the modernization of reliability computation metrics. [ABSTRACT FROM AUTHOR]

Small and Medium Enterprises SME play a crucial role in the global economy through their contribution in countries economy and creation of employment opportunities, and their success heavily relies on the implementation of efficient manufacturing systems like Lean Production(LP). LP is a continuous improvement philosophy based on various lean activities for improving enterprise lean performance. A fuzzy model that integration Fuzzy Consistency Algorithm (FCA) and Fuzzy Analytical Hierarchy Process (FAHP) was proposed as a comprehensive framework to assess the levels of importance and priority of nineteen SME lean activities that categorized into the related five related lean dimensions. FCA was used to construct the fuzzy pairwise comparison matrix to ensure obtaining consistent experts judgment, whereas FAHP was applied to identify the level of importance and priority of lean activities. Identifying the level of importance of lean activities will be contributed in focuses SME efforts in the improvement process on the most important lean activities to ensure effective resource allocation and foster continuous improvement process and offer a practical tool for enhancing their competitiveness and sustainability. The proposed model was applied in Iraqi SME. The result showed that FCA is an efficient approach to construct a consistent judgment matrix. Efficient manger, Kaizen team, supplier relationship, execution customer suggestions and customer satisfaction job rotation are the most important lean activities with level of importance 58.90%, 21.30%, 49.80%, 38.50%, 41.20% respectively. The proposed model can be used for small or medium size enterprise for various production industries. [ABSTRACT FROM AUTHOR]

Dimensional stones classification models are efficient to particular aspects of these stones production. However, there are two main problems with these models. Initially, these models focus on specific types of dimensional stones, lacking a comprehensive model encompassing all stone types. Additionally, these systems classify stones based on a singular or limited set of features that affect stone quality. In addition, stones usage is an important factor, which determines the type of stone properties need to be considered in stone quality evaluation. To address these issues, this paper introduces a comprehensive classification model for dimensional stones. This model enables the identification of the optimal stone application and helps prevent the inappropriate use of stones in various contexts. To achieve this objective, an index called Stone Quality Point (SQP) is established, which is utilized within the classification model. Coefficients of the model are calculated by the Analytic Hierarchy Process (AHP) technique, and the Variables of the model are determined based on Fuzzy Logic. Stones are then categorized into three classes (good, moderate, and weak) using the SQP index, taking into account their suitability for various construction applications. Ultimately, the SQP is calculated to categorize the granite used in the construction of building facades. The values range from 1 to 2 for the weak group, 2 to 2.5 for the moderate group, and 2.5 to 3 for the good group. The SQP model and its scoring procedure remain consistent for various types of stones. [ABSTRACT FROM AUTHOR]

In this research, we present a supporting tool for decision making by designing a distribution system for a trading company of supplies for the welding industry in Mexico. The case study encompasses a distribution system with shortage problems and poor fleet capacity. To address these problems, improvement options were grouped into three possible scenarios through a third-party logistics (3PL) service. Furthermore, for the evaluation and selection of one of the scenarios, the Analytic Hierarchy Process (AHP) methodology was proposed integrating fuzzy logic as a tool for decision making, including factors of uncertainty and subjectivity as well as a comparison with traditional AHP obtaining the best scenario, meeting the requirements of the company, and showing potential improvements in the desired service level for its distribution system. [ABSTRACT FROM AUTHOR]

Issues related to stable microgrid (MG) operation often pose challenges for engineers and researchers, including energy management, power quality maintenance, and the effect of perturbations. Therefore, continuous measurement and monitoring of the system's stability level require special attention. Thus, motivated and focused on addressing these issues, this paper presents a novel decision-making methodology for determining the MG stability index (MGSI) to comprehensively measure the MG stability level. The proposed index is based on continuously measuring fundamental MG parameters, including voltage, frequency, battery state of charge (SOC), and total harmonic distortion. The influence of these parameters on system stability is considered using 256 rules in a Mamdani-based fuzzy inference system. The proposed methodology is evaluated through seven case studies considering different modes of MG operation, types of loads, and availability of power sources and simulated using MATLAB Simulink software. The results demonstrate variations in MGSI for different investigated scenarios, such that a grid-connected MG system with high renewable output and high battery SOC, along with critical/noncritical load, exhibits the best MGSI compared to an islanded MG system with low renewable output, low battery SOC, and an inductive load that shows least MGSI. Additionally, to demonstrate the credibility of the fuzzy-based controller in complex decision-making, a comparative analysis is performed with the analytic hierarchy process under the multi-criteria decision-making technique. The paper also includes sensitivity analysis that reflects the system's sensitivity to different input sources and robustness analysis of the controller. [ABSTRACT FROM AUTHOR]

Flooding has become a devastating natural hazard worldwide, posing a substantial hazard to civilization and leading to socioeconomic losses. Urban flooding in India is on the rise due to unplanned urbanization, uncontrolled population growth, and changes in land use. For this analysis, the urban region of Dhanera (Gujarat state, India) has been chosen as a study area to prepare a flood hazard map in a geographic information system (GIS) environment using a multiple-criteria decision making (MCDM) technique. This study includes qualitative analysis compound factor (CF) and analytical hierarchy process (AHP), and quantitative analysis (fuzzy logic) using eight flood-affected criteria (slope, distance from the main river, land-use land cover (LULC), soil, drainage density, elevation, geomorphology, and proximity to stream confluence). MCDM techniques examined the weight of each criterion. The historical flood depth data have been collected via field visits or published articles for validation. Flood hazard maps have been classified into very high, high, moderate, low, and very low hazard zones. In each MCDM method, Ward 1 and Ward 2 are very highly and highly hazardous, respectively. The flood hazard map using fuzzy logic and inundation map matches very high, high, and very low categories. So, fuzzy logic is the best method to quantify flood hazards for Dhanera. This study provides a low-cost and time-efficient tool that assists local administration in prioritizing the preservation and control of floods, further helping the decision makers in mitigation planning to reduce damages. [ABSTRACT FROM AUTHOR]

Water erosion in general is considered a natural danger that worsens with passing of years, and this is in the absence of human awareness and taking the necessary preventive measures to manage areas exposed to erosion. Most studies on water erosion have been subject to one framework, which is the evaluation of water erosion. This research contributed to the identification of soil erosion-prone areas in the sub-watershed of Boussellam and K'sob, Algeria, through the use of the Analytical Hierarchy Process (AHP), Fuzzy Boolean Modeling and the Modified Global Soil Loss Equation (RUSLE). A group of factors that affect soil erosion were used (Curvature, Slope, Aspect, Elevation, Rainfall Erosivity, Land use land cover, Drainage Density, K factor/Soil, Lithology, NDWI, Factor Ls, NDVI, Factor P, C Factor). Water erosion conditioning factors were integrated and erosion risk maps were extracted using the Geographic Information System. The study results, after using the RUSLE, fuzzy and AHP models, indicate areas with very high erosion risks occupied 12.91%, 12.98% and 9.49%, respectively, of the study area, and with the help of Receiver Operating Characteristics curves the risk maps were validated. Water erosion under the curve (AUC) and the results revealed that the models showed good predictive capabilities in determining soil erosion susceptibility zones with AUC values of 0.783, 0.806, and 0.644 for the AHP, fuzzy logic and RUSLE models, respectively. This study contributed to identifying the area's most vulnerable to water erosion to help decision-makers to intervene quickly and take the essential strategies to reduce this problem in the research area. [ABSTRACT FROM AUTHOR]

This study presents the implementation of Multi-Criteria Decision-Making (MCDM) methodologies, particularly the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS), in prioritizing technosignatures (TSs) for the search for extraterrestrial intelligence (SETI). By incorporating expert opinions and weighted criteria based on the established Axes of Merit, our analysis offers insights into the relative importance of various TSs. Notably, radio and optical communications are emphasized, in contrast to dark side illumination and starshades in transit. We introduce a new axis, Scale Sensitivity, designed to assess the variability of TS metrics. A sensitivity analysis confirms the robustness of our approach. Our findings, especially the highlighted significance of artifacts orbiting Earth, the Moon, or the Sun, indicate a need to broaden evaluative criteria within SETI research. This suggests an enhancement of the Axes of Merit, with a focus on addressing the plausibility of TSs. As the quest to resolve the profound question of our solitude in the cosmos continues, SETI efforts would benefit from exploring innovative prioritization methodologies that effectively quantify TS search strategies. [ABSTRACT FROM AUTHOR]

To solve the problems of low-ratio high-contribution stages in the horizontal well initial fracturing and complex factors affecting refracturing effects in tight reservoirs, analytic hierarchy process, grey correlation, BP neural network, and fuzzy logic methods are comprehensively applied to establish a multi-level Type-2 fuzzy logic system (T2-FLS): Based on the improved analytic hierarchy process–grey relational method, the weight of different geological engineering factors on the productivity contribution of the candidate refracturing stages was calculated. The BP neural network system was used to establish the refracturing productivity prediction model, and the value of each influencing factor was divided into four grades in the T2-FLS. The membership function of the T2-FLS and comprehensive quantitative evaluation criterion of candidate well interval for refracturing is established. The productivity improvement in different refracturing candidate wells and different refracturing candidate stages of the same horizontal well after refracturing was compared and analyzed. For relatively heterogeneous reservoirs, the incomplete fracturing stage with high contribution rate of primary fracturing to productivity has the highest refracturing potential. For relatively homogeneous reservoirs, the stimulation potential of refracturing in the unstimulated section is higher than that in the simulated section. The high and sub-high potential stages of the high comprehensive potential candidate wells should first be selected for refracturing, and then select the high potential stages in the low comprehensive potential candidate wells. After reasonable refracturing stage selection, the productivity of some refractured horizontal wells can even be increased by more than 10% compared with the initial production. [ABSTRACT FROM AUTHOR]

Anatolia has been used as a settlement area by many civilizations throughout history due to its geopolitical and geographical features. Traditional houses in Anatolia convey the thousands of years of culture and identity of the region where they are located, with their unique architectural style. In this respect, traditional houses appear as the most important cultural heritage values that convey information such as the social, cultural, economic and architectural style of the period. Historical textures have been in change and transformation in the Malatya region, as in every region of Anatolia. However, Malatya has largely lost its traditional houses and texture due to many reasons such as rapid urbanization, unconsciousness, rent, and the destructive effect of time. In this study, which was prepared by addressing this problem, Fuzzy Logic and AHP (Analytical Hierarchy Process) analysis system was used in order to evaluate the authenticity of civil architectural examples located in traditional tissue pieces in the urban area of Malatya and to protect these structures. Thus, it is aimed to develop an authenticity assessment method together with the experts of the subject (conservation experts, architectural historians, art historians). It is aimed to determine the authenticity of the buildings numerically and proportionally with the authenticity evaluation model developed with a systematic setup. Ahmet Kökçü House, located in Yakınca Neighborhood, was chosen as the study area due to reasons such as the fact that it largely preserved its traditional texture as a field study and faced extinction as a result of the rapid urbanization of Malatya's central city wall reaching the border of Yeşilyurt district. With the authenticity assessment model developed in this context, the authenticity of the building was determined by experts and suggestions were made for the preservation of the building. [ABSTRACT FROM AUTHOR]

To enhance profitability of production cycle, any manufacturer needs effective product design and evaluation procedures. This study proposed a novel approach combining fuzzy analytic hierarchy process (FAHP) and multi-layer fuzzy inference system (MFIS). It is based on consumer online comments to improve product design. This method possesses several advantages over traditional design evaluation methods. It can quickly acquire consumer preferences, effectively handle multi-criteria decision problems and integrate uncertain and fuzzy information. The Fuzzy Analytic Hierarchy Process–Multi-layer Fuzzy Inference System (FAHP-MFIS) involves the following steps: screening of factors, hierarchical modeling, quantification of qualitative factors, and conversion of these factors into quantitative values. It is a knowledge-based system that uses logical rules. The quantity and levels of input variables directly correlates with the quantity of logical rules. However, with multi-factor and multi-level inference, the establishment of a rule base becomes impractical due to the overwhelming number of rules. To address this issue, the Taguchi orthogonal table is applied to reduce the number of logical rules. Taking a household oxygen generator for medical devices as an example, the proposed model is applied in real-time. In the first stage, web crawlers are used to collect user reviews of the household oxygen generators on large e-commerce platforms. Latent Dirichlet Allocation (LDA) models are used to screen for principal and sub-factors in the second stage. Then, sub-factors of the FAHP screening are used as inputs, and the principal factors are used as outputs. In the third stage, priority indicators are established based on principal factors such as Appearance, Basic Function, and Advanced Function. Established evaluation models are then used to rank the selected designs. The results show that the higher the priority index value of the product design scheme, the better the scheme, and vice versa. This study holds significant reference value in aiding enterprises to enhance the efficiency of their manufacturing cycle and determining the direction of product design and innovation with improved pace and accuracy. Moreover, it can be applied to other fields such as supply chain management, risk assessment, and investment decisions. [ABSTRACT FROM AUTHOR]

This article shows the evaluation of the Integrated Real-time Energy Management Framework (IREMF), a cutting-edge system designed to develop energy management practices. The framework leverages real-time data collection, advanced visualization techniques, and fuzzy logic to optimize energy consumption patterns. To assess the performance and importance of each layer and main factor within IREMF, we employ a multi-step methodology. First, the Fuzzy Delphi Method is utilized to harness expert insights and collective intelligence, providing a holistic understanding of the framework's functionality. Researchers used a fuzzy analytic hierarchy process (AHP) to determine the relative importance of each component of the energy system (first stage). This careful evaluation process helps ensure that resources are allocated effectively and that strategic decisions are made based on sound data. The findings of the study not only improve our understanding of the capabilities of the IREMF platform but also pave the way for future developments in energy system management. The study highlights the critical role of real-time data, visualization, fuzzy logic, and advanced decision-making methods in shaping a sustainable energy future. [ABSTRACT FROM AUTHOR]

Focusing on problem-based learning (PBL) and the multi-disciplinary teaching of science, technology, engineering, arts, and mathematics (STEAM), we developed the evaluation tool of teaching aids in STEAM education to help students practice creative thinking and solution-finding. The fuzzy theory and the analytical hierarchy process were integrated for the evaluation of the acceptance of using robots in STEAM education. The fuzzy analytical hierarchy process (FAHP) was developed with the help of experts in education and industry who defined the goal, criteria, and alternatives (factors) of using teaching aids in STEAM education. FAHP was applied to the evaluation of three robots designed for STEAM education in this study. The result of the evaluation showed that the use of the designed robots in STEAM education was important in five criteria (structure, function, economy, aesthetic, and creativity). Among the alternatives, logic, creativity, simpleness, Avant-garde, and innovation were important for robots to be used for STEAM education. This indicated that artistic elements were important in the integration of them in STEAM education. The developed FAHP and questionnaire were useful in evaluating the acceptance of teaching aids in STEAM education. For the evaluation of the use of other teaching aids, the result of this study provides a basis and a reference for how teaching aids can be used for STEAM education. [ABSTRACT FROM AUTHOR]

Maritime transport has a significant share in world trade. The unsafe operation of ships causes loss of life, loss of cargo, and marine environmental pollution. Commercial ships are equipped with advanced types of equipment. The nautical charts as aids to navigation are used on commercial ships to navigate safely between ports. The officer of the watch can see the risks in the navigation area by checking these charts. The risks indicated on the chart should be taken into account during the navigation of ships, and if the correct calculations are not made, serious accidents may occur. These calculations are based on both sufficient maritime experience and knowledge. This research studied the category zone of confidence (CATZOC) areas in ECDIS on ships, the limitations of the system, and their solutions. Recommendations received from experts for the solutions to the identified problems were determined and explained according to the priorities with the Fuzzy Analytical Hierarchy Process (FAHP) method. [ABSTRACT FROM AUTHOR]

Crafting a comprehensive strategy to mitigate the impact of droughts, a complex geo-hazard profoundly affecting socio-economic aspects, entails the creation of a drought vulnerability map as a primary step. This study harmonizes geospatial techniques and the Fuzzy Analytical Hierarchy Process (fuzzy AHP) to formulate such a map for northwestern Odisha, India. From six principal drought-induced vulnerability parameters, namely physical attributes, water demand and usage, agriculture, land use, groundwater and population/development, 22 sub-parameters were selected. Spatial layers were generated for each sub-parameter, followed by their fuzzification using a fuzzy membership approach. Subsequently, AHP was employed to establish parameter weights through pair-wise comparisons. By applying the weighted overlay method, drought vulnerability maps were generated, classifying regions into five vulnerability levels: very high, high, moderate, low, and very low. The outcomes indicate that roughly 33% of the area is classified as having high drought vulnerability. Validation of the approach using statistical metrics, including accuracy, root mean square error and mean absolute error, demonstrates its efficacy in gauging drought vulnerability, thereby aiding planners in devising effective drought mitigation strategies. [ABSTRACT FROM AUTHOR]

The primary goal of this research paper is to develop a tool for screening for Asperger Syndrome (AS). The "multi-criteria decision-making (MCDM)" method, an extensively used approach for making decisions involving several criteria, has been used to create this screening tool. The amount of knowledge available to a person is vast, ambiguous, and uncertain; fuzzy logic has been used to deal with ambiguity and confusion. Due to the opulence of symptoms that may cause AS, to know which symptoms affect more and which affect less, a "fuzzy analytic hierarchy process (FAHP)" algorithm has been used with the "If-Then" rule-based approach for determining whether or not an individual has an AS. The developed tool uses a hierarchy approach called "Fuzzy Tree" to reduce the huge number of rules. Efforts are being made to develop a less complex tool that can assess a person in a short period and provide accurate results. The validity of the design was verified by the two groups of individuals consisting of the AS group (N = 25) and the Typically Developed (TD) group (N = 25). It was confirmed that the method created efficiently differentiated AS participants from TD and has a precision of 99%. [ABSTRACT FROM AUTHOR]

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Objectives. Hospitals provide direct and indirect employment benefits to medical professionals. Accidents in hospitals often lead to disastrous consequences such as fatalities, property damage and economic losses. It is, therefore, imperative to have an occupational health and safety (OHS) policy that aims to reduce work-related accidents to acceptable levels. This study aims to investigate health risks to staff from various hazards and suggest control measures to prevent recurrence of accidents. Methods. A two-stage fuzzy multi-criteria decision-making (MCDM) approach incorporating the fuzzy analytical hierarchical process (FAHP) and fuzzy technique for order preference for similarity to ideal solution (TOPSIS) was applied to assess the hazards in a leading multi-speciality hospital in Chennai. Results. The top three hazards identified in the workplace were electrical hazards, faulty medical equipment, and ventilation and air conditioning hazards. Subsequently, control measures were suggested to reduce the recurrence of hazards. Finally, a survey of hospital accidents occurring in India between 2010 and 2020 was conducted and compared with the results of this study. Conclusions. The survey findings show similarity to the hazard rankings obtained in this work, thus validating the methodology used for the assessment of hazards in hospitals. Electrical hazards and faulty medical equipment should be monitored. [ABSTRACT FROM AUTHOR]

The concept of the circular city is gaining more and more attention nowadays due to its reuse/recover/recycle applications for circulating the resource. The authorities need decision support tools to determine which sources can be recovered and what are the best applicable technologies. This study proposes a decision-making approach that calculates sustainability ındex (SI) for wastewater resource recovery strategies. The resource recovery plan consists of the preliminary steps to determine the wastewater streams to be recovered and their alternative technologies to implement. Analytical hierarchy process (AHP) is used for the composition of SI, which provides a systematic evaluation by listing the criteria that contribute to sustainability. Lastly, the fuzzy ınference engine combines the fundamental components of sustainability defined with AHP. It quantifies the SI, which is reported as an index value with the sustainability class and its membership degree. Therefore, the novelty of this study is providing a holistic approach for the sustainability assessment of wastewater recovery technologies due to including a resource recovery plan and allowing the evaluation of symbiosis strategies and quantification of SI by using fuzzy logic. The proposed approach is demonstrated with a scenario for nutrient recovery technologies from wastewater, and according to the scenario, membrane technology has the highest SI with 8.36. The numerical value for SI and priority weights communicates between stakeholders of the circular city while deciding on the resource recovery technologies for wastewater recovery. The proposed approach was easily applied and was convenient for handling uncertain data and linguistic expert opinions. [ABSTRACT FROM AUTHOR]

Adoption of the Paris Agreement in December 2015 and its subsequent ratification through Nationally Determined Contribution (NDC) marked, among other things, India's commitment to reduce the emission intensity of its GDP by 33–35 per cent by 2030 from 2005 level. The transport sector, being the prime conduit of production value-chain, has been a major contributor to global energy-related greenhouse gas (GHG) emissions. In this context, it is critical production research study that needs to evaluate the linkage of NDC with freight transport. The proposed framework consists of goal setting, seeking expert opinion and driving insights into the field of freight transport. First, goal and criteria or attribute for achieving NDC through the freight sector are identified. Next, expert opinions from transport and climate change specialists are sought. Lastly, results and insights related to the most feasible alternatives, such as heavy road, heavy rail, hybrid, heavy waterborne, and heavy air with regard to the select attributes and its sub-attributes viz, slower growth, structural changes in sector and economy, strategic and operational choices, technology and innovation and regulatory and economic instruments with the help of fuzzy analytic hierarchy process (FAHP) are drawn. The strength of the proposed methodology is that it uses FAHP to prescribe definitive solutions to climate change policymakers and logistics and supply chain managers who otherwise would have found difficulties with such an arcane subject having partial and little quantified information. [ABSTRACT FROM AUTHOR]

Due to the irruption of new technologies in cities such as mobile applications, geographic information systems, internet of things (IoT), Big Data, or artificial intelligence (AI), new approaches to citizen management are being developed. The primary goal is to adapt citizen services to this evolving technological environment, thereby enhancing the overall urban experience. These new services can enable city governments and businesses to offer their citizens a truly immersive experience that facilitates their day-to-day lives and ultimately improves their standard of living. In this arena, it is important to emphasize that all investments in infrastructure and technological developments in Smart Cities will be wasted if the citizens for whom they have been created eventually do not use them for whatever reason. To avoid these kinds of problems, the citizens' level of adaptation to the technologies should be evaluated. However, although much has been studied about new technological developments, studies to validate the actual impact and user acceptance of these technological models are much more limited. This work endeavors to address this deficiency by presenting a new model of personalized recommendations based in the technology acceptance model (TAM). To achieve the goal, this research introduces an assessment system for tourists' digital maturity level (DMT) that combines a fuzzy 2-tuple linguistic model and the analytic hierarchy process (AHP). This approach aims to prioritize and personalize the connection and communication between tourists and Smart Cities based on the digital maturity level of the tourist. The results have shown a significant correlation between technology usage and the potential for personalized experiences in the context of tourism and Smart Cities. [ABSTRACT FROM AUTHOR]

The Assaka watershed is one of the largest watersheds in the Guelmim region in southern Morocco. It is frequently exposed to the many flooding events that can be responsible for many costly human and material damages. This work illustrates a decision-making methodology based on Analytical Hierarchy Process (AHP) and Fuzzy Logic Modelling (FLM), in the order to perform a useful flood susceptibility mapping in the study area. Seven decisive factors were introduced, namely, flow accumulation, distance to the hydrographic network, elevation, slope, LULC, lithology, and rainfall. The susceptibility maps were obtained after normalization and weighting using the AHP, while after Fuzzification as well as the application of fuzzy operators (OR, SUM, PRODUCT, AND, GAMMA 0.9) for the fuzzy logic methods. Thereafter, the flood susceptibility zones were distributed into five flood intensity classes with very high, high, medium, low, and, very low susceptibility. Then validated by field observations, an inventory of flood-prone sites identified by the Draa Oued Noun Hydraulic Watershed Agency (DONHBA) with 71 carefully selected floodprone sites and GeoEye-1 satellite images. The assessment of the mapping results using the ROC curve shows that the best results are derived from applying the fuzzy SUM (AUC = 0.901) and fuzzy OR (AUC = 0.896) operators. On the other hand, the AHP method (AUC = 0.893) shows considerable mapping results. Then, a comparison of the two methods of SUM fuzzy logic and AHP allowed considering the two techniques as complementary to each other. They can accurately model the flood susceptibility of the Assaka watershed. Specifically, this area is characterized by a high to very high risk of flooding, which was estimated at 67% and 30% of the total study area coverage using the fuzzy logic (SUM operator) and the AHP methods, respectively. Highly susceptible flood areas require immediate action in terms of planning, development, and land use management to avoid any dramatic disaster. [ABSTRACT FROM AUTHOR]

The main objective of this research was to create a robust hierarchical model to evaluate the power generation technologies in the energy mix of any country, with particular emphasis on its use in the case study of Spain. An exhaustive literature review allowed to identify a balanced number of the most relevant criteria that the model should consider to evaluate the seven alternatives that cover most of the Spanish energy demand. Through expert knowledge, the Analytic Hierarchy Process (AHP) methodology allowed to obtain the local and global weights of the criteria used in the model. Using these weights and the assessments of alternatives for each criterion, their ranking was determined through both AHP and a novel fuzzy inference system (FIS), whose inference rules were automatically constructed based on the weights of the criteria and a distance minimization method. The design of this FIS constitutes the main contribution of the work, firstly, because it avoids a second round of experts consultations and, secondly, because it systematically conceptualises the knowledge base that allows to infer the individual evaluation of any alternative, without the risk of rank reversal that may occur if using only AHP. The results of the case study of Spain showed that environmental was the most important criterion. In terms of the comparative AHP merit order, Photovoltaic (PV) was ranked first and Coal last. In addition, the individual assessment of the technologies through FIS yielded results consistent with the previous AHP ranking. Finally, a sensitivity analysis was performed, which showed good stability in the results obtained. [ABSTRACT FROM AUTHOR]

Purpose: Studies on textile upcycling in Africa are rare, particularly in Liberia, where extensive upcycling designs are appreciated throughout the country. This study aims to contribute to the upcycling literature from the perspective of Liberia's fashion upcyclers by assessing their coping strategies and understanding the challenges confronting fashion upcycling in Monrovia's four largest markets. Design/methodology/approach: A fuzzy analytical hierarchy process and data envelopment analysis (DEA) models were used to assess labor input, delivery and flexibility, technological and innovation capability, financial capability, pricing of finished products, customer service and quality outputs of upcycled fashions. The fuzzy inference system model assessed upcyclers' loaning eligibility. Findings: The results highlight that Liberia's fashion upcycling is expanding with varying innovative designs. The quality of upcycled fashions was deemed most important in the proposed AHP model. However, many upcycling businesses lack sufficient capital to make long-term investments. With the necessary investment, the innovation of these upcyclers could be a new line of fashion brands with great potential. In addition, using a fair judgment in assessing the little loaning funds available is paramount to enhancing their growth. Research limitations/implications: Only 34 decision-making units were assessed. Future research could expand this scope using other models with more practical loaning strategies. Originality/value: This study presents a wealth of managerial and policy implications. The proposed hybrid model is adequate for developing managerial decisions for fashion upcyclers. The proposed framework can manage ambiguity, inaccuracy and the complexity of making decisions based on numerous criteria, making it applicable in unearthing robust strategies for enhancing the fashion upcycling sectors and other industries in developing countries. In addition, the proposed fuzzy Mamdani system could also be extended to other sectors, such as agriculture, for a more transparent allocation of resources. [ABSTRACT FROM AUTHOR]

Diabetes mellitus is a disease that plagues all countries in the world. One of the affectations caused by this chronic disease is damage to peripheral nervous tissues. This is the cause of ulcers and amputations in parts of the foot of the diabetic patient. In this paper, we propose a method to evaluate the patient's degree of preventive management of peripheral diabetic neuropathy. For this purpose, the Neutrosophic Analytic Hierarchy Process (AHP) method is used to assess the importance of factors influencing the prevention of peripheral neuropathic complications associated with diabetes mellitus in some patients. For the final evaluation, the aggregator called neutrosophic uninorm is used; especially, the operator based on the combining function utilized in the Prospector expert system. [ABSTRACT FROM AUTHOR]

Flood risk assessment is an important tool for urban planning, land development, and hydrological analysis. The flood risks are very high in arid countries due to the nature of the rainfall resulting from thunderstorms and the land cover, which comprises mostly very dry arid soil. Several methods have been used to assess the flood risk, depending on various factors that affect the likelihood of occurrence. However, the selection of these factors and the weight assigned to them remain rather arbitrary. This study assesses the risk of flood occurrence in arid regions based on land cover, soil type, precipitation, elevation, and flow accumulation. Thematic maps of the aforementioned factors for the study area were prepared using GIS. The Fuzzy Analytic Hierarchy Process (F-AHP) was used to calculate the likelihood of the flood occurrence, and land use was used to assess the exposure impact. Using the likelihood map (i.e., probability) from the Fuzzy-AHP and an exposure map, the flood risk was assessed. This method was applied to Qatar as a case study. Results were compared with those produced by fuzzy logic. To explore the pairwise importance of the F-AHP, equal weight analysis was performed. The resulting risk map shows that the majority of urbanized areas in Qatar are within the high-risk zone, with some smaller parts within the very high flood-risk area. The majority of the country is within the low-risk zone. Some areas, especially land depressions, are located within the intermediate-risk category. Comparison of Fuzzy logic and the F-AHP showed that both have similarities in the low-risk and differences in the high-risk zones. This reveals that the F-AHP is probably more accurate than other methods as it accounts for higher variability. [ABSTRACT FROM AUTHOR]

In the digital era, companies have experienced a progressive change in their business models, which has led them to develop greater agility to adapt to changing environments, and the necessity to properly manage the group decision making in these companies is patent. This paper shows how fuzzy models are utilized in group decision making. In this context, one of the most important group decisions to be adopted is how to manage the digital transformation of the company, drawing up the best possible roadmap. To achieve this goal, this paper proposes a new methodology improvement of group decision making based on a fuzzy 2-tuple linguistic model and the analytic hierarchy process (AHP) method. The suggested methodology proposes the calculation of the digital maturity level (DML) of companies based on five of the most cited and agreed upon criteria in the existing literature. The methodology proposed in this paper was tested and validated for the business case of Spanish SMEs through three different clusters to derive global recommendations tailored to each specific cluster and company segments, using a sample of 1428 companies. The main fundings reveal that the digital maturity level directly impacts on the size of the company and its digital mindset in the sense of driving change management processes. As future works, authors recommend extending the model to any industry using the proposed methodology and evaluate disruptive technologies such as artificial intelligence (AI) in supporting the digital transformation of SMEs. [ABSTRACT FROM AUTHOR]

Energy management is important for choosing the right software recommendation to reduce the cost of service utilization. Time factor and CPU performance will be the challenges for feature analysis in smart devices like smartphones, tabs, and computers. The energy makes highly desirable needs for Priority Software which contains the recommendation for choosing right features to make the right choice of execution software. Different techniques are used to reduce the energy for considering software, but they are insufficient to recordation in which they are not used to prioritize the software utilization to make better device-driven hardware. The recommendations are considered to choose good quality software based on feature analysis from risk, cost, and requirement of the stakeholders' which needs the priority of the requirements. To overcome this problem, an analytical hierarchy process of identifying software requirement prioritization based on optimized fuzzy logic social spider optimization (FLSP) is proposed to reduce energy consumption. By utilizing the software feature evaluation, the decision rule is attained to make priority using finite decision ranking (FDR). Initially, social spider optimization is intended to evaluate the spectral weight which is selected from the customer behavioral features and strategies to provide priority processing through fitness evaluation. The efficiency of these features depend on software factors which are evaluated to communal weight and rule with fuzzy logic mapping function (FLMF). Then the logical regression creates a stack to assign weights based on software features to make ranking to prioritize the utilization of software. The contrast of these approaches proves that measurement performance leads to higher efficiency and accuracy in software recommendation to use with best energy consumption. [ABSTRACT FROM AUTHOR]

Environmental vulnerability refers to the susceptibility of a region to damage when it is subjected to natural or anthropogenic actions. The assessment of environmental vulnerability in lakes is an important tool to assist managers in planning and intervening for sustainable production and environmental preservation. The combination of geotechnologies, fuzzy logic and the analytic hierarchy process (AHP) has been applied by professionals and researchers to improve the work and research conducted in various areas and environments. In this context, the objective of this work was to map the environmental vulnerability of a lake and its surroundings through fuzzy logic and the AHP method. The study area comprises the Juparanã Lagoon Drainage Surface (JLDS), Espírito Santo state, Brazil. A survey of the physical characteristics of the watershed (drainage surface) that feeds the Juparanã Lagoon was carried out and also of the land use of this surface. To achieve the proposed objectives, the following methodological steps were implemented: (a) delimitation of watersheds, (b) spatialization of Permanent Preservation Areas (APP) based on the Brazilian Forestry Code (Law nº 12,651/2012), (c) application of logic fuzzy and AHP to spatialize the environmental vulnerability and (d) application of an evaluation of environmental vulnerability to the Preservation Areas (APP). Environmental vulnerability was modeled using Euclidean distance analysis, fuzzy logic and the AHP method, as proposed by Saaty (1977). For the development of this work, geotechnologies were used, with special emphasis on the use of the free software QGIS. The analysis revealed that 31.20%, 32.86% and 20.93% of the JLDS have very high, high and medium vulnerability, respectively. The evaluation of the environmental vulnerability of the APP showed that there is protection in the APP of the JLDS at rates of 47.35%, 34.05% and 14.5% for very high, high and medium vulnerability classes, respectively. The difficulties encountered were related to the lack of studies in the area of environmental vulnerability with a particular focus on lagoons. Here, for the first time, we perform a photointerpretation of the surroundings of Juparanã Lagoon. An important improvement measure would be the application of a temporal analysis to assess the dynamics of environmental vulnerability over time, considering socioeconomic, climatic and environmental changes. This would provide a more complete understanding of the distribution of environmental vulnerability in the study area. The methodology can be adapted to consider different scales of analysis, from local to regional, national and global scales, to assess environmental vulnerability at various scopes and levels of complexity. It can also be adapted to include local communities and governments. [ABSTRACT FROM AUTHOR]