260 research outputs found
Transforming medical equipment management in digital public health: a decision-making model for medical equipment replacement
IntroductionIn the rapidly evolving field of digital public health, effective management of medical equipment is critical to maintaining high standards of healthcare service levels and operational efficiency. However, current decisions to replace large medical equipment are often based on subjective judgments rather than objective analyses and lack a standardized approach. This study proposes a multi-criteria decision-making model that aims to simplify and enhance the medical equipment replacement process.MethodsThe researchers developed a multi-criteria decision-making model specifically for the replacement of medical equipment. The model establishes a system of indicators for prioritizing and evaluating the replacement of large medical equipment, utilizing game theory to assign appropriate weights, which uniquely combines the weights of the COWA and PCA method. In addition, which uses the GRA method in combination with the TOPSIS method for a more comprehensive decision-making model.ResultsThe study validates the model by using the MRI equipment of a tertiary hospital as an example. The results of the study show that the model is effective in prioritizing the most optimal updates to the equipment. Significantly, the model shown a higher level of differentiation compared to the GRA and TOPSIS methods alone.DiscussionThe present study shows that the multi-criteria decision-making model presented provides a powerful and accurate tool for optimizing decisions related to the replacement of large medical equipment. By solving the key challenges in this area as well as giving a solid basis for decision making, the model makes significant progress toward the field of management of medical equipment
Natural and Technological Hazards in Urban Areas
Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events
Multi-criteria decision making with fuzzy TOPSIS:a case study in Bangladesh for selection of facility location
Abstract. The choice of an ideal facility location becomes essential as businesses work to streamline their processes and increase efficiency. In this study, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is applied to choose the best facility location for Rokomari.com, a well-known Bangladeshi online book seller. The goal is to compare Fuzzy TOPSIS’ effectiveness and efficiency to expert judgment when choosing a facility location. The research begins by examining the existing fulfillment center of Rokomari.com located in Motijheel, south Dhaka, and the company’s desire to establish a new branch in north Dhaka for faster service expansion. Eleven potential alternatives are evaluated using the Fuzzy TOPSIS method, which incorporates fuzzy set theory to represent criteria values and preferences as fuzzy numbers. This approach enables the consideration of uncertainty and vagueness in decision-making, offering a more comprehensive evaluation of the facility location alternatives. The study incorporates the expert opinion of four managerial experts from Rokomari.com in addition to the Fuzzy TOPSIS analysis. To gain a thorough understanding of the decision-making process, their observations and viewpoints are contrasted with the Fuzzy TOPSIS findings. The study aims to compare the analyses produced by Fuzzy TOPSIS and expert judgment in order to assess the efficacy and efficiency of each method for choosing a facility location. The results of this study offer insightful information about the use of Fuzzy TOPSIS in the context of choosing a facility location. Additionally, it adds to the body of knowledge by contrasting the results of Fuzzy TOPSIS with professional judgment, highlighting the advantages and drawbacks of each method. The outcomes can help decision-makers at Rokomari.com and other comparable organizations choose a facility location in a knowledgeable and efficient manner
Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5
This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered.
First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes.
Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification.
Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well
Tradition and Innovation in Construction Project Management
This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings
Enhancing the cosmetics industry sustainability through a renewed sustainable supplier selection model
The cosmetics industry requires a long-term sustainable strategy to balance its continuously growing trend worldwide and its resources consumption. In this view, the suppliers' selection process is gaining more attention affecting products' overall sustainability. The objective of this contribution is hence to develop and validate the Cosmetics Sustainable Supplier Selection (C-SSS) model allowing the selection of sustainable suppliers for the cosmetic industry, evaluating them in an objective and balanced manner. The model was built relying on both scientific and grey literature, by incorporating the characteristics of existing SSS models usually used separately. The C-SSS enabled to integrate the EMM approach (to reduce the subjectivity), the ANP approach (to evaluate criteria interconnections), and the TOPSIS and ELECTRE models (to create a hybrid compensation model) to support managers in objectively selecting the most sustainable suppliers. The C-SSS model was applied and validated through an industrial use case in a cosmetics Italian company
Investigating the Relationship between Resilience and the Situation of Risk in the Face of Natural Disasters
Creating cities resilient in multiple dimensions could be appropriate and economic thanks to strengthening town structure to alter crises and natural and unnatural hazards. Therefore, the aim of this study is to investigate the connection between the resilience in the city of Sari and the risk situation towards natural disasters. Data analysis with geographic information system (GIS), Decision making trial and evaluation laboratory (DEMATEL), and analytic network process (ANP) is carried out. The variables studied to explain the resilience of the city of Sari are the conditions of open spaces, incompatible land uses, land bed, building resistance, access, property, density, which are evaluated in the presented paradigm. After collecting the scores and multiplying the scores by the coefficients obtained from the statistical procedures of an urban resilience model, the final computation of urban resilience in Sari was performed. The results show that its value has been calculated as 5.44398, which shows that there is an urgent need to develop programs and reform structures to increase the level of resilience in this urban area. One of the effective factors in urban resilience is the high level of social participation in crisis, which is necessary in this area. It is suggested to create educational programs in the community, so that they can maximize the level of communication and participation of employees
Evaluation of Metaverse Traffic Safety Implementations using fuzzy Einstein based logarithmic methodology of additive weights and TOPSIS method
As the Metaverse’s popularity grows, its effect on everyday problems is beginning to be discussed. The upcoming Metaverse world will influence the transportation system as cross-border lines blur due to rapid globalization. The purpose of this paper is to investigate the capabilities of the Metaverse and its alternatives to traffic safety, as well as to prioritize its advantages. The case study is based on a densely populated metropolis with an extensive education system. The city’s decision-makers will have to weigh the pros and cons of the Metaverse’s effect on traffic safety. To illustrate the complex forces that drive the decision-making process in traffic safety, we create a case study with four alternatives to Metaverse’s integration into the traffic system. Alternatives are evaluated using twelve criteria that reflect the decision problem’s rules and regulations, technology, socioeconomic, and traffic aspects. In this study, fuzzy Einstein based logarithmic methodology of additive weights (LMAW) is applied to calculate the weights of the criteria. We present a new framework that combines Einstein norms and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank the alternatives. The findings of this study show that public transportation is the most appropriate area for implementing the Metaverse into traffic safety because of its practical opportunities and broad usage area
Unveiling the nexus of digital conversion and clean energy: An ISM-MICMAC and DEMATEL perspective
Our aim is to develop a hierarchical framework that assesses the interdependence of digital metrics impacting clean energy in the European energy market. The framework is evaluated to determine its applicability to clean energy and implementation. We utilize a taxonomy of digital metrics with the MICMAC ("Matrice d'Impacts Croisés-Multiplication Appliquée à un Classement") methodology and a questionnaire-based survey using DEMATEL to validate the framework. This results in an efficient hierarchy and contextual relationship between key metrics in the European energy industry. We investigate and simulate ten key metrics of digital conversion for clean energy in the energy domain, identifying the most significant effects, including the "decision-making process" the "sustainable value chain" the "sustainable supply chain", "sustainable product life cycle", and the "interconnection of diverse equipment". The MICMAC methodology is used to classify these parameters for a better understanding of their structure, and DEMATEL is employed to examine cause-and-effect relationships and linkages. The practical implications of this framework can assist institutions, experts, and academics in forecasting essential metrics and can complement existing studies on digital conversion and clean energy. By prioritizing these key parameters, improvements in convenience, efficiency, and the reduction of product fossilization can be achieved. The value and originality of this study lie in the novel advancements in analyzing digital conversion metrics in the European energy industry using a cohesive ISM, MICMAC, and DEMATEL framework
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