New Approaches to the Prognosis and Diagnosis of Breast Cancer Using Fuzzy Expert Systems

Breast cancer remains a significant global health challenge, necessitating effective early detection and prognosis to enhance patient outcomes. Current diagnostic methods, including mammography and MRI, suffer from limitations such as uncertainty and imprecise data, leading to late-stage diagnoses. To address this, various expert systems have been developed, but many rely on type-1 fuzzy logic and lack mobile-based applications for data collection and feedback to healthcare practitioners. This research investigates the development of an Enhanced Mobile-based Fuzzy Expert system (EMFES) for breast cancer pre-growth prognosis. The study explores the use of type-2 fuzzy logic to enhance accuracy and model uncertainty effectively. Additionally, it evaluates the advantages of employing the python programming language over java for implementation and considers specific risk factors for data collection. The research aims to dynamically generate fuzzy rules, adapting to evolving breast cancer research and patient data. Key research questions focus on the comparative effectiveness of type-2 fuzzy logic, the handling of uncertainty and imprecise data, the integration of mobile-based features, the choice of programming language, and the creation of dynamic fuzzy rules. Furthermore, the study examines the differences between the Mamdani Inference System and the Sugeno Fuzzy Inference method and explores challenges and opportunities in deploying the EMFES on mobile devices. The research identifies a critical gap in existing breast cancer diagnostic systems, emphasizing the need for a comprehensive, mobile-enabled, and adaptable solution by developing an EMFES that leverages Type-2 fuzzy logic, the Sugeno Inference Algorithm, Python Programming, and dynamic fuzzy rule generation. This study seeks to enhance early breast cancer detection and ultimately reduce breast cancer-related mortality.

Fuzzy Set-Membership Filtering for Discrete-Time Nonlinear Systems

In this article,the problem of state estimation is addressed for discrete-time nonlinear systems subject to additive unknown-but-bounded noises by using fuzzy set-membership filtering.First,an improved T-S fuzzy model is introduced to achieve highly accurate approximation via an affine model under each fuzzy rule.Then,compared to traditional prediction-based ones,two types of fuzzy set-membership filters are proposed to effectively improve filtering performance,where the structure of both filters consists of two parts:prediction and filtering.Under the locally Lipschitz continuous condition of membership functions,unknown membership values in the estimation error system can be treated as multiplicative noises with respect to the estimation error.Real-time recursive algorithms are given to find the minimal ellipsoid containing the true state.Finally,the proposed optimization approaches are validated via numerical simulations of a one-dimensional and a three-dimensional discrete-time nonlinear systems.

Life-cycle cost model and evaluation system for power grid assets based on fuzzy membership degree

Life-cycle cost(LCC)theory can be effectively applied to improve the efficiency and quality of power plant equipment and asset management.However,specific aspects of the LCC calculation and evaluation model require further research for practical application.This paper proposes an LCC assessment model for the management of electric power plant equipment during its service life.A membership function method based on fuzzy logic is used to improve the allocation of modernization and overhaul projects to multiple equipment assets.An LCC assessment model and evaluation system for power equipment are proposed and successfully applied to the equipment and project management of a Guangzhou power plant in the China Southern Power Grid,providing a decision-making mechanism that facilitates efficient operation and optimal utilization of power plant equipment and assets.

The Theory of Membership Degree of Γ-Conclusion in Several n-Valued Logic Systems

Based on the analysis of the properties of Γ-conclusion by means of deduction theorems, completeness theorems and the theory of truth degree of formulas, the present papers introduces the concept of the membership degree of formulas A is a consequence of Γ (or Γ-conclusion) in Lukasiewicz n-valued propositional logic systems, Godel n-valued propositional logic system and the R0 n-valued propositional logic systems. The condition and related calculations of formulas A being Γ-conclusion were discussed by extent method. At the same time, some properties of membership degree of formulas A is a Γ-conclusion were given. We provide its algorithm of the membership degree of formulas A is a Γ-conclusion by the constructions of theory root.

Asymptotically Necessary and Sufficient Quadratic Stability Conditions of T-S Fuzzy Systems Using Staircase Membership Function and Basic Inequality

Asymptotically necessary and sufficient quadratic stability conditions of Takagi-Sugeno (T-S) fuzzy systems are obtained by utilizing staircase membership functions and a basic inequality. The information of the membership functions is incorporated in the stability analysis by approximating the original continuous membership functions with staircase membership functions. The stability of the T-S fuzzy systems was investigated based on a quadratic Lyapunov function. The asymptotically necessary and sufficient stability conditions in terms of linear matrix inequalities were derived using a basic inequality. A fuzzy controller was also designed based on the stability results. The derivation process of the stability results is straightforward and easy to understand. Case studies confirmed the validity of the obtained stability results.

Fuzzy logic controller design with unevenly-distributed membership function for high performance chamber cooling system

Fuzzy logic controller adopting unevenly-distributed membership function was presented with the purpose of enhancing performance of the temperature control precision and robustness for the chamber cooling system.Histogram equalization and noise detection were performed to modify the evenly-distributed membership functions of error and error change rate into unevenly-distributed membership functions.Then,the experimental results with evenly and unevenly distributed membership functions were compared under the same outside environment conditions.The experimental results show that the steady-state error is reduced around 40% and the noise disturbance is rejected successfully even though noise range is 60% of the control precision range.The control precision is improved by reducing the steady-state error and the robustness is enhanced by rejecting noise disturbance through the fuzzy logic controller with unevenly-distributed membership function.Moreover,the system energy efficiency and lifetime of electronic expansion valve(EEV) installed in chamber cooling system are improved by adopting the unevenly-distributed membership function.

Output Linearization of Single-Input Single-Output Fuzzy System to Improve Accuracy and Performance

For fuzzy systems to be implemented effectively,the fuzzy membership function(MF)is essential.A fuzzy system(FS)that implements precise input and output MFs is presented to enhance the performance and accuracy of single-input single-output(SISO)FSs and introduce the most applicable input and output MFs protocol to linearize the fuzzy system’s output.Utilizing a variety of non-linear techniques,a SISO FS is simulated.The results of FS experiments conducted in comparable conditions are then compared.The simulated results and the results of the experimental setup agree fairly well.The findings of the suggested model demonstrate that the relative error is abated to a sufficient range(≤±10%)and that the mean absolute percentage error(MPAE)is reduced by around 66.2%.The proposed strategy to reduceMAPE using an FS improves the system’s performance and control accuracy.By using the best input and output MFs protocol,the energy and financial efficiency of every SISO FS can be improved with very little tuning of MFs.The proposed fuzzy system performed far better than other modern days approaches available in the literature.

Comprehensive Evaluation of New Maize Varieties for Grain and Fodder Based on Membership Function Method

To screen new maize(Zea mays L.)varieties suitable for food and fodder dual-purpose in Du'an Yao Autonomous County of Guangxi,the agronomic characters,yield and quality indexes of 12 new maize varieties were measured,and the correlation between various indexes were analyzed,and the comprehensive performance of tested varieties was evaluated by membership function method.The results showed that Guidan 671 had the highest grain yield and whole-plant biomass at 10908 and 49965 kg/hm^(2),respectively,and the second was Zhaoyu 215 with a grain yield and whole-plant biomass of 10086 and 47175 kg/hm^(2),respectively.Grain yield was highly significantly positively correlated with ear diameter and 100-grain weight(P<0.01),and significantly correlated with whole-plant biomass,starch content,ear length and grain number per row(P<0.05);and the whole-plant biomass was highly significantly correlated with the number of grains per row(P<0.01),and significantly correlated with starch content,panicle length,plant height and panicle height(P<0.05).The comprehensive performance scores of the tested varieties from high to low were Guidan 671,Zhaoyu 215,Guidan 669,Guidan 6208,Guidan 666,Guidan 6205,Guidan 660,Guidan 6203,Guidan 6206,Guidan 162,Guidan 668 and Guidan 673.According to the values of membership function and combined with various indexes,Guidan 671 and Zhaoyu 215 had good comprehensive performance,and could be used as the first choice for food and fodder dual-purpose maize varieties in Du'an Yao Autonomous County.

农村集体经济组织成员资格认定的逻辑脉络及其展开

农村集体经济组织成员资格认定是农村集体产权制度改革的基础性工作,集体所有权主体的确定是该问题研究的逻辑起点。集体所有权不具有共有和总有等所有权构造类型的特征,同时投资关系说和类比国有资本授权经营体制论都不能对农村集体经济组织的产生渊源进行合理解释。在民法规范语境下,应将农村集体经济组织确定为集体所有权主体。就成员资格和成员权利的关系而言,两者相伴而生,成员资格实质上是从权利主体角度对成员权的描述,为成员权在主体面向的表达。基于此,集体成员资格认定的法律实质是对农民所享有的集体经济组织成员权予以确权。我国农村传统经营方式决定了农户是基本经营单位,从逻辑上应当将家庭成员与以家庭为单位取得权益的关系确定为按份共有,集体经济组织成员权主体应为集体经济组织成员而非农户。城乡二元体制导致户籍这一本质上与成员权利取得不具因果关系的因素被纳入认定标准之中,其证明作用不应被忽视。在传统路径下,应构建以出生事实为核心、其他亲缘关系为辅助的主体判断路径,同时明确列举其他除外情形,形成正反双向的认定机制。在农村集体产权制度改革背景下,基于股权类型设置,集体固有成员与股份经济合作社股东在范围上并非完全一致,未来应以恢复农村集体经济组织和集体成员权的私法属性为目标,分阶段对农村集体经济组织成员权制度进行渐进性改革。

基于模糊理论的桥梁监测设备评估方法研究

针对桥梁监测设备运行状态难以量化评估的问题,提出一种基于模糊理论的综合评估方法,构建监测设备运行状态自诊断服务系统。基于现行规范建立监测设备运行状态评估指标体系,采用正态分布隶属度函数,并引入Pearson相关系数和信息熵确定各评估指标权重;采用基于混合算子的模糊评估模型,实现监测设备运行状态量化评估;通过自诊断服务系统,实时监测设备运行状态并进行报警。将该方法应用于某悬索桥监测设备评估,工程应用结果表明:该方法与规范方法和概率分析法评估结果相同,但该方法基于模糊理论“自下而上”逐级综合加权分析,全面量化评估桥梁监测设备体系各等级运行状态隶属度,评估结果简单直观,所构建的自诊断服务系统有助于科学指导桥梁健康监测系统运维。

基于GRU的仪表着陆系统故障预测方法研究

故障预测技术在保障仪表着陆系统的可靠运行、提高空管效能等方面具有重要应用价值。结合仪表着陆系统运行特征和实际运行维护工作,提出一种基于GRU的仪表着陆系统故障预测方法。以航向信标为研究对象,在分析其监控参数与设备运行状态之间的关系后,将监控参数作为故障特征参数;根据监控参数时间步长、时变性特征显著的特点,采用GRU预测监控参数的未来变化趋势;根据监控参数的隶属函数计算出参数未来时刻可能发生“故障”的概率,实现对航向信标故障的预测。结果表明:基于GRU的仪表着陆系统预测方法的相对预测精度在95%以上。

Decision Making Based on Valued Fuzzy Superhypergraphs

This paper explores the defects in fuzzy (hyper) graphs (as complex (hyper) networks) and extends the fuzzy(hyper) graphs to fuzzy (quasi) superhypergraphs as a new concept.We have modeled the fuzzy superhypergraphsas complex superhypernetworks in order to make a relation between labeled objects in the form of details andgeneralities. Indeed, the structure of fuzzy (quasi) superhypergraphs collects groups of labeled objects and analyzesthem in the form of the part to part of objects, the part of objects to the whole group of objects, and the whole tothe whole group of objects at the same time.We have investigated the properties of fuzzy (quasi) superhypergraphsbased on any positive real number as valued fuzzy (quasi) superhypergraphs, considering the complement of valuedfuzzy (quasi) superhypergraphs, the notation of isomorphism of valued fuzzy (quasi) superhypergraphs based onthe permutations, and we have presented the isomorphic conditions of (self complemented) valued fuzzy (quasi)superhypergraphs. The concept of impact membership value of fuzzy (quasi) superhypergraphs is introducedin this study and it is applied in designing the real problem in the real world. Finally, the problem of businesssuperhypernetworks is presented as an application of fuzzy valued quasi superhypergraphs in the real world.

Limb Lengthening and Reconstruction Society orthopedic surgeons in the United States:An analysis of geographical distribution,academic,leadership,and demographic characteristics

BACKGROUND The Limb Lengthening and Reconstruction Society(LLRS)is a premier orthopedic specialty organization that promotes limb reconstruction for all ages.LLRS membership characteristics,however,are poorly reported.This study delineates orthopedic surgeon LLRS members’demographic traits,academic achievement,leadership attainment,and geographical distribution across the United States.AIM To inform aspiring orthopedic professionals,as well as to promote growth and diversity in both the LLRS organization and overarching field.METHODS This cross-sectional study examined United States LLRS members’academic,leadership,demographic,and geographical attributes.After reviewing the 2023 LLRS member directory,Google search results were matched to the listings and appended to the compiled data.Sex and ethnicity were evaluated visually utilizing retrieved images.The Hirsch index(H-index)of academic activity,residency and fellowship training,other graduate degrees,leadership positions,practice type(academic or non-academic),and spoken languages were categorized.LLRS members per state and capita determined geographic distribution.The Mann Whitney U test was applied to compare H-index between males and females,as well as to assess member differences pertaining to affiliation with academic vs non-academic practice facilities.RESULTS The study included 101 orthopedic surgeons,78(77.23%)Caucasian and 23(22.77%)non-Caucasian,79(78.22%)male and 22(21.78%)female.Surgeons with DO degrees comprised only 3.96%(4)of the cohort,while the vast majority held MDs[96.04%(97)].Mean H-index was 10.55,with male surgeons having a significantly higher score(P=0.002).Most orthopedic surgeons(88.12%,)practiced in academic centers.Of those professionals who occupied leadership positions,14%were women,while 86%were men.Additionally,19(37.25%)United States regions and the District of Columbia lacked an LLRS-member orthopedic surgeon.Total per capita rate across the United States was 0.30 LLRS orthopedic surgeons per 1 million people.CONCLUSION Over 21%of LLRS members are women,surpassing prior benchmarks noted in orthopedic faculty reporting.LLRS members’high research productivity scores imply field dedication that can refine expertise in the limb lengthening and reconstruction space.Gender disparities in leadership remain,however,necessitating greater equity efforts.A low rate of LLRS representation per capita must be addressed geographically as well,to affect improvements in regional care access.This study can serve to support aspiring orthopedic professionals,inform diversity,leadership,and field advancement strategies,and maintain the continued goal of enhanced patient care worldwide.

Are You Willing to Pay to Go to the Supermarket?

In recent yea rs,t raditiona l offline supermarkets are facing big challenges,and warehouse membership superma rkets(hereinafter referred to as membership supermarkets)are quickly gaining p opu l a r it y.Ma ny t r ad it iona l supermarkets have become membership supermarkets,and even many retail enterprises have entered this field.

The New Year Ushers in New Members to BRICS

At the beginning of this year,the BRICS countries welcomed a wave of new members.On New Year’s Day,Saudi Arabia,Egypt,the United Arab Emirates,Iran and Ethiopia became full members,doubling the number of BRICS members from five to ten.At present,BRICS,as a multilateral cooperation organization of developing countries,is on the road towards substantial expansion and rapid development.In both historical and practical terms,the expansion of BRICS membership has profound historical logic and contemporary implications,which will have a significant impact on the world’s pattern and international order.

广义二型模糊系统的自组织规则生成方法

针对广义二型模糊系统在复杂情况中因缺乏专家经验而难以构建合适模糊规则的问题,提出了一种基于输入数据的激活强度来生成广义二型模糊集以及模糊规则的方法。通过数据驱动自组织构建广义二型模糊系统模糊规则,并且使用迭代最小二乘法和梯度下降法优化系统前后件参数。最后,分别在无扰动和施加噪声情况下进行了非线性系统的跟踪仿真,实验结果证明了自组织规则生成的广义二型模糊系统的有效性,并能够以较高精度跟踪参考轨迹。

Evaluating Privacy Leakage and Memorization Attacks on Large Language Models (LLMs) in Generative AI Applications

The recent interest in the deployment of Generative AI applications that use large language models (LLMs) has brought to the forefront significant privacy concerns, notably the leakage of Personally Identifiable Information (PII) and other confidential or protected information that may have been memorized during training, specifically during a fine-tuning or customization process. We describe different black-box attacks from potential adversaries and study their impact on the amount and type of information that may be recovered from commonly used and deployed LLMs. Our research investigates the relationship between PII leakage, memorization, and factors such as model size, architecture, and the nature of attacks employed. The study utilizes two broad categories of attacks: PII leakage-focused attacks (auto-completion and extraction attacks) and memorization-focused attacks (various membership inference attacks). The findings from these investigations are quantified using an array of evaluative metrics, providing a detailed understanding of LLM vulnerabilities and the effectiveness of different attacks.

基于广电融合业务的会员管理系统建设与应用

5G业务的落地拓展为广电运营商补齐移动业务短板的同时,也加剧了同质竞争。依托新的融合业务架构,广电运营商亟需构建一套会员体系来提升用户服务和黏性。本文主要介绍分析了基于“5G+宽带+电视+X”融合业务的会员管理系统建设和应用实践。

药店个性化药品推荐系统的深度学习方法

本研究开发了一种基于深度学习技术的药店个性化药品推荐系统,旨在提高药品推荐的准确度和个性化程度。系统通过收集和预处理药店会员数据,利用深度学习模型分析用户的健康状况和药物相互作用。结果显示,该系统在准确率和召回率方面均优于传统方法。通过顾客反馈和调查,验证了系统的有效性和顾客满意度,展示了深度学习在药品推荐领域的应用潜力,为相关行业从业者提供了新的技术途径。

基于Membership的高可用性Linux集群

介绍了Ｌｉｎｕｘ集群高可用性（ＨＡ）技术的应用背景和体系结构，重点讲述了集群Ｍｅｍｂｅｒｓｈｉｐ技术可以显著提高集群系统的可用性，并且提出了可配置的Ｍｅｍｂｅｒｓｈｉｐ服务（ＭＢＬＣ）来实现Ｌｉｎｕｘ集群的高可用性的方案。