Fuzzy Multi-Criteria Decision Support System for the Best Anti-Aging Treatment Selection Process through Normal Wiggly Hesitant Fuzzy Sets

This socialized environment among educated and developed people causes themto focusmore on their appearance and health,which turns them towards medical-related treatments,leading us to discuss anti-aging treatment methods for each age group,particularly for urban people who are interested in this.Some anti-aging therapies are used to address the alterations brought on by aging in human life without the need for surgery or negative effects.Five anti-aging therapies such as microdermabrasion or dermabrasion,laser resurfacing anti-aging skin treatments,chemical peels,dermal fillers for aged skin,and botox injections are considered in this study.Based on the criteria of safety risk,investment cost,customer happiness,and side effects,the optimal alternative is picked.As a result,a NormalWiggly Hesitant Pythagorean Fuzzy Set(NWHPFS)is constructed and used in Multi-Criteria Decision-Making(MCDM)using traditional wavy mathematical approaches.The entropy approach is utilized to determine weight values,and the Normal Wiggly Hesitant Pythagorean-VlseKriterijumska Optimizacija I Kompromisno Resenje(NWHPF-VIKOR)method is utilized to rank alternatives using MCDM methodologies.Sensitivity analysis and comparative analysis were performed to ensure the robustness and reliability of the proposed method.The smart final choice will undoubtedly assist Decision Makers(DM)in making the right judgments,and the MCDM approach will undoubtedly assist individuals in understanding the medicine.

Designing a Protection Scheme in Micro-Grid Systems with DG Using Central Protection Unite and Multiple Setting Group Protection Relays

Distributed generators now is widely used in electrical power networks, in some cases it works seasonally, and some types works at special weather conditions like photo voltaic systems and wind energy, and due to this continuous changes in generation condition, the fault current level in network will be affected, this changes in fault current level will affect in the coordination between protection relays and to keep the coordination at right way, an adaptive protection system is required that can adaptive its setting according to generation changes, the fault current level in each case is evaluated using ETAP software, and the required relay setting in each case is also evaluated using Grey Wolf Optimizer (GWO) algorithm, and to select suitable setting which required in each condition, to select the active setting group of protection relay according to generation capacity, central protection unite can be used, and to improve protection stability and minimizing relays tripping time, a proposed method for selecting suitable backup relay is used, which leads to decrease relays tripping time and increase system stability, output settings for relays in all cases achieved our constrains.

A Synergistic Multi-Attribute Decision-Making Method for Educational Institutions Evaluation Using Similarity Measures of Possibility Pythagorean Fuzzy Hypersoft Sets

Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.

Solid Waste Management:A MADM Approach Using Fuzzy Parameterized Possibility Single-Valued Neutrosophic Hypersoft Expert Settings

The dramatic rise in the number of people living in cities has made many environmental and social problems worse.The search for a productive method for disposing of solid waste is the most notable of these problems.Many scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated ambiguity.The goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site selection.The characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these uncertainties.To tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s method.Following this,an intelligent algorithm is suggested.The steps of the suggested algorithm are explained with an example that explains itself.The compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their viability.This study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,respectively.It uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior literature.It is simpler for the decisionmakers to look at each option separately because the decision is uncertain.Comparing the computed results,it is discovered that they are consistent and dependable because of their preferred properties.

An Intelligent MCGDM Model in Green Suppliers Selection Using Interactional Aggregation Operators for Interval-Valued Pythagorean Fuzzy Soft Sets

Green supplier selection is an important debate in green supply chain management(GSCM),attracting global attention from scholars,especially companies and policymakers.Companies frequently search for new ideas and strategies to assist them in realizing sustainable development.Because of the speculative character of human opinions,supplier selection frequently includes unreliable data,and the interval-valued Pythagorean fuzzy soft set(IVPFSS)provides an exceptional capacity to cope with excessive fuzziness,inconsistency,and inexactness through the decision-making procedure.The main goal of this study is to come up with new operational laws for interval-valued Pythagorean fuzzy soft numbers(IVPFSNs)and create two interaction operators-the intervalvalued Pythagorean fuzzy soft interaction weighted average(IVPFSIWA)and the interval-valued Pythagorean fuzzy soft interaction weighted geometric(IVPFSIWG)operators,and analyze their properties.These operators are highly advantageous in addressing uncertain problems by considering membership and non-membership values within intervals,providing a superior solution to other methods.Moreover,specialist judgments were calculated by the MCGDM technique,supporting the use of interaction AOs to regulate the interdependence and fundamental partiality of green supplier assessment aspects.Lastly,a statistical clarification of the planned method for green supplier selection is presented.

Study on the Influence of Setting Parameters of Tunnel Centralized Smoke Extraction System on Fire Smoke Flow and Temperature Decay

The centralized smoke exhaust system of shield tunnel is an important determinant for tunnel fire safety,and the use of different design parameters of the tunnel smoke exhaust system will affect the smoke exhaust effect in the tunnel,and the influence of different design parameters on the smoke exhaust effect and temperature attenuation of the tunnel can help engineers in designing a more effective centralized smoke exhaust system for the tunnel.In this paper,the Fire Dynamic Simulator(FDS)is utilized to examine smoke exhaust vent settings for a centralized exhaust system in shield tunnel with both flat and sloped conditions,including slopes of+4.5%and−4.5%,under a 30MWfire power with a 150m^(3)/s smoke exhaust rate.The results suggest that maintaining a vent spacing of 60m and a vent size of 4.0 m×1.5 m is a reasonable configuration for centralized smoke exhaust systems in both flat and slope shield tunnels.This choice helpsminimize construction costs and prevent excessive smoke accumulation.It also promotes favorable conditions for maintaining temperature distribution at 2-m height,visibility,smoke spread distance,and temperature below the ceiling,all below the threshold values,while ensuring high smoke extraction efficiency.However,in the slope section,the chimney effect can disrupt exhaust efficiency,visibility,ceiling temperature,and temperature distribution at a height of 2 m.Employing different opening methods,such as having 2 vents up and 4 vents down in a+4.5%slope and 4 vents up and 2 vents down in a−4.5%slope,can help mitigate these effects.Furthermore,the temperature decay formula for shield tunnels follows a bi-exponential decay pattern,and different design parameters of centralized smoke exhaust systems have minimal effects on temperature decay in shield tunnels.

Virtually coupled train set control subject to space-time separation:A distributed economic MPC approach with emergency braking configuration

The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches.

Approximation Maintenance When Adding a Conditional Value in Set-Valued Ordered Decision Systems

The integration of set-valued ordered rough set models and incremental learning signify a progressive advancement of conventional rough set theory, with the objective of tackling the heterogeneity and ongoing transformations in information systems. In set-valued ordered decision systems, when changes occur in the attribute value domain, such as adding conditional values, it may result in changes in the preference relation between objects, indirectly leading to changes in approximations. In this paper, we effectively addressed the issue of updating approximations that arose from adding conditional values in set-valued ordered decision systems. Firstly, we classified the research objects into two categories: objects with changes in conditional values and objects without changes, and then conducted theoretical studies on updating approximations for these two categories, presenting approximation update theories for adding conditional values. Subsequently, we presented incremental algorithms corresponding to approximation update theories. We demonstrated the feasibility of the proposed incremental update method with numerical examples and showed that our incremental algorithm outperformed the static algorithm. Ultimately, by comparing experimental results on different datasets, it is evident that the incremental algorithm efficiently reduced processing time. In conclusion, this study offered a promising strategy to address the challenges of set-valued ordered decision systems in dynamic environments.

Decision Support System Based on Set Pair Analysis and Its Application

The paper has made a comparison among some decision models of G-DSS.Based on Set Pair Analysis,it integrates the advantages and shortcomings of decision models of G-DSS and puts forward SP-DSS.Furthermore,the principle of SP-DSS to make decision as well as its application to diagnose sick systems is expounded,and the program flow chart of SP-DSS is presented.

Rough set based multi-agent system cooperation for industrial supervisory interface system

In this paper, rough set theory is introduced into the interface multi-agent system （MAS） for industrial supervisory system. Taking advantages of rough set in data mining, a cooperation model for MAS is built. Rules for avoiding cooperation conflict are deduced. An optimization algorithm is used to enhance security and real time attributes of the system. An application based on the proposed algorithm and rules are given.

Blow-up Sets to a Coupled Heat System

This paper deals with a heat system coupled via local and localized sources subject to null Dirichlet boundary conditions. In a previous paper of the authors, a complete result on the multiple blow-up rates was obtained. In the present paper, we continue to consider the blow-up sets to the system via a complete classification for the nonlinear parameters. That is the discussion on single point versus total blow-up of the solutions. It is mentioned that due to the influence of the localized sources, there is some substantial difficulty to be overcomed there to deal with the single point blow-up of the solutions.

Psychosocial Group Intervention at a Low-Resource Setting Environment for Women Who Are Diagnosed and Treated for Breast Cancer: A Systematic Review

Africa faces significant challenges in terms of material and personnel resources for oncology interventions. This is particularly evident in South Africa, where resources are divided into high- and low-resource settings. High-resource settings cater to those with financial means to access private oncology facilities. However, many breast cancer patients receive care in South Africa’s low-resource settings, such as public hospital oncology clinics. Unfortunately, these settings have limited service providers and fail to offer comprehensive interventions, resulting in poor outcomes. However, recent research has highlighted the significance of socially supportive relationships in promoting healing and overall individual well-being, and spirituality has been identified as a source of positive outcomes in cancer patients. This systematic review paper explores the feasibility of implementing support group cancer care and interventions that incorporate social support networks available in community settings, and spiritual practices facilitated by traditional healers, and religious/spiritual leaders. These interventions can be provided within low-resource settings to women diagnosed with breast cancer. Inclusive participation of spouses, children, and extended family in the support group cancer care can facilitate healing for the entire system. Focusing on the strengths and resources within communities and incorporating these complementary services, can enhance the well-being and quality of life for Black African women diagnosed with breast cancer, despite low-resource settings. This approach acknowledges the potential of community-based support networks and encourages collaboration between various stakeholders, including community health educators, nurses, lay counselors, and community volunteers, to address the complex needs of these patients.

A Proposal to Set Up a Stable Supply System for Potassic Fertilizer in China

Agriculture is an important foundation of China’s socio-economic development. To secure the sound development of modern agriculture in the 21st century, the supply of fertilizers such as potassium is a key factor. Owing to the limited arable land in China, a vital measure to feed the country’s increasing population is the augmentation of fertilizers so as to gain higher per unit area grain yields. At present, for a fairly long time to come, additional fertilizer resources will mainly come from nitrogen, phosphorus and potassium fertilizers. But there is a severe application disproportion between nitroge-

Set up and validation of Chinese Risk Stratification System for Coronary Artery Bypass Grafting

Objective Our study aims to evaluate the performance of Chinese risk stratification system for coronary artery bypass grafting (CABG) in the prediction of in-hospital mortality and major postoperative complications afterCABG. Methods Clinical information of 9564 consecutive CABG patients was collected in Chinese Coronary Artery Bypass Grafting Registry which recruited 43 centers over China between 2007 and 2008.

SET::NUP214融合基因阳性急性白血病患者3例并文献复习

目的:提高对SET::NUP214融合基因阳性急性白血病的认识。方法:回顾性分析2018年7月至2019年11月广西医科大学第一附属医院收治的3例SET::NUP214融合基因阳性急性白血病患者的临床资料,并结合相关文献进行复习。结果:3例SET::NUP214融合基因阳性急性白血病患者中1例诊断为急性T淋巴细胞白血病(T-ALL),1例为急性髓系白血病(AML),1例为急性淋巴细胞白血病L2(ALL-L2),2例患者诊断时在我院行BCR::ABL荧光原位杂交(FISH)技术检测阳性,按照急性淋巴细胞白血病常规治疗效果欠佳;2例ALL患者均在1年内复发,1例AML患者化疗完全缓解,随后进行异基因移植,移植后10个月复发。结论:SET::NUP214融合基因阳性急性白血病少见,主要见于T-ALL中,染色体可正常,行BCR::ABLFISH有助于早期诊断,确诊需行融合基因检测。含激素化疗方案效果不佳,生存期短,预后差,异基因移植或可改善此类患者的预后。

Note on the Blow-up Set for A Semilinear Parabolic Differential System

This note deals with the blow up set for a non-cooperative noallnear parabolic differential system and generalizes the theorem 3. 2 and 3. 5 of reference [1]. That is, it is proved that the blow up set consists of a single point x=0 without the restriction p】q.

Fault Diagnosis of Vehicle Transmission System Based on Rough Set Theory

Rough set theory is used to treat the data of vehicle transmission system faults. The minimum fault feature vector can be obtained by calculating the importance and dependency of each attribute. Real time diagnosis, as a result, can be actualized. Ultimate decision making can be done by analyzing the consistency of decision information. The result shows that rough set theory is useful and possesses its unique merits in this field.

A Multi-Tuple Rough Set Approach for Information Retrieval

How to deal with the imprecise information retrieval has become more and more important in the present information society. An efficient and effective method of information retrieval based on multi tuple rough set is discussed in this paper. The new approach is considered as a generalization of the original rough set model for flexible information retrieval. The imprecise query results can be obtained by multi tuple approximations.

基于SET-AHP-TRIZ的坐式康复训练器设计研究

为解决现有坐式康复训练器形式与功能单一、操作使用缺乏智能化等问题,文章构建了基于SET-AHP-TRIZ的设计思路。首先,对产品的现状、用户进行市场调研,采用SET分析法确定目标产品的机会缺口;其次,应用AHP法对需求点进行定量计算,以确定创新过程中需要着重改善的问题;最后,通过应用TRIZ理论分析出现的矛盾问题,并总结其矛盾类型,利用发明原理解决问题,进行坐式康复训练器设计实践,减少了设计过程主观因素的影响,使设计结果更为科学合理,以期提高用户的满意度。