Picture模糊数的改进得分函数在多属性群决策中的应用

针对picture模糊环境下专家权重和属性权重信息未知的多属性群决策问题进行研究.首先,针对现有picture模糊数的得分函数存在一些不足问题,提出了一种新的得分函数.通过分析其相关性质,并与现有得分函数进行比较,说明其更具合理性,能更好地处理模糊决策信息.其次,提出了基于得分函数的picture模糊环境下的多属性群决策方法,根据每位专家给出的picture模糊评价信息的不精确程度及不同专家给出信息的差异程度,从个体和群体两方面综合得到决策者权重;利用得分函数构造不同属性的灰靶贡献度,从而确定属性权重.最后,通过实例比较分析验证了所提方法的可行性和有效性.

Picture最小二乘模糊推理算法在模式识别中的应用

目的:由于picture模糊推理全蕴涵算法和picture模糊推理五蕴涵算法所满足的还原性是有条件的还原性,我们寻找一种满足无条件还原性的picture模糊推理算法。方法:将picture模糊集转化为三维模糊集,结合最小二乘模型的思想,构建最小二乘模型的picture模糊推理算法。结果:给出基于最小二乘模型的picture模糊推理算法及其解的表示形式。结论:我们将基于最小二乘模型的picture模糊推理算法应用到模式识别,实验结果表明,本文提出的算法是合理和有效的。

An Integrated Bipolar Picture Fuzzy Decision Driven System to Scrutinize Food Waste Treatment Technology through Assorted Factor Analysis

Food Waste(FW)is a pressing environmental concern that affects every country globally.About one-third of the food that is produced ends up as waste,contributing to the carbon footprint.Hence,the FW must be properly treated to reduce environmental pollution.This study evaluates a few available Food Waste Treatment(FWT)technologies,such as anaerobic digestion,composting,landfill,and incineration,which are widely used.A Bipolar Picture Fuzzy Set(BPFS)is proposed to deal with the ambiguity and uncertainty that arise when converting a real-world problem to a mathematical model.A novel Criteria Importance Through Intercriteria Correlation-Stable Preference Ordering Towards Ideal Solution(CRITIC-SPOTIS)approach is developed to objectively analyze FWT selection based on thirteen criteria covering the industry’s technical,environmental,and entrepreneurial aspects.The CRITIC method is used for the objective analysis of the importance of each criterion in FWT selection.The SPOTIS method is adopted to rank the alternative hassle-free,following the criteria.The proposed model offers a rank reversal-free model,i.e.,the rank of the alternatives remains unaffected even after the addition or removal of an alternative.In addition,comparative and sensitivity analyses are performed to ensure the reliability and robustness of the proposed model and to validate the proposed result.

NFHP-RN:AMethod of Few-Shot Network Attack Detection Based on the Network Flow Holographic Picture-ResNet

Due to the rapid evolution of Advanced Persistent Threats(APTs)attacks,the emergence of new and rare attack samples,and even those never seen before,make it challenging for traditional rule-based detection methods to extract universal rules for effective detection.With the progress in techniques such as transfer learning and meta-learning,few-shot network attack detection has progressed.However,challenges in few-shot network attack detection arise from the inability of time sequence flow features to adapt to the fixed length input requirement of deep learning,difficulties in capturing rich information from original flow in the case of insufficient samples,and the challenge of high-level abstract representation.To address these challenges,a few-shot network attack detection based on NFHP(Network Flow Holographic Picture)-RN(ResNet)is proposed.Specifically,leveraging inherent properties of images such as translation invariance,rotation invariance,scale invariance,and illumination invariance,network attack traffic features and contextual relationships are intuitively represented in NFHP.In addition,an improved RN network model is employed for high-level abstract feature extraction,ensuring that the extracted high-level abstract features maintain the detailed characteristics of the original traffic behavior,regardless of changes in background traffic.Finally,a meta-learning model based on the self-attention mechanism is constructed,achieving the detection of novel APT few-shot network attacks through the empirical generalization of high-level abstract feature representations of known-class network attack behaviors.Experimental results demonstrate that the proposed method can learn high-level abstract features of network attacks across different traffic detail granularities.Comparedwith state-of-the-artmethods,it achieves favorable accuracy,precision,recall,and F1 scores for the identification of unknown-class network attacks through cross-validation onmultiple datasets.

顺应论视域下The Picture of Dorian Gray中译本的对比研究

The Picture of Dorian Gray是王尔德唯一一部长篇小说,小说语言唯美自然。本文从顺应论的角度出发,从语境顺应、结构顺应以及动态顺应三个方面分析孙宜学译本与荣如德译本的差异。文章发现,两译者对于自己的定位不同,即前者是源语文化的传播者,后者则是文学作品的传播者,译者的意识程度以及自身定位影响着译者采取的翻译方法,只有找准定位才能更好地翻译,获得更大的阅读价值以及参考价值。

A Study on the Values and Strategies of English Picture Book Reading for Improving Pupils’ English Reading Literacy

Reading is one of the core skills in English learning.It is indispensable for EFL learners to develop good English reading literacy in primary schools.English picture books are consistent with pupils’cognitive and thinking modes,which is valuable to improve their English reading literacy.However,at present,most Chinese pupils have some problems in English reading.The paper aims at analyzing the current problems in Chinese pupils’English reading and digging out the values and strategies of English picture book reading,so as to stimulate their reading interests,cultivate their intercultural awareness,and improve their English reading literacy.

区间值Picture模糊参数集结算子及其应用

针对决策信息为区间值Picture模糊数的多属性群决策问题,在充分考虑属性间相互关联的情况下,将区间值Picture模糊数与广义Heronian均值函数和Heronian平均算子结合,定义了区间值Picture模糊参数广义加权Heronian平均算子,并研究了其性质。该信息集结算子能够反映信息的完整性、属性相关性和决策者的风险偏好。然后,提出了一种基于区间值Picture模糊参数广义加权Heronian平均算子的多属性群决策模型。最后,运用本文提出的群决策模型对信息系统进行了最优选择,并与其它模型进行比较,说明所提模型的有效性和优越性。

Floyd-Warshall Algorithm Based on Picture Fuzzy Information

The Floyd-Warshall algorithm is frequently used to determine the shortest path between any pair of nodes.It works well for crisp weights,but the problem arises when weights are vague and uncertain.Let us take an example of computer networks,where the chosen path might no longer be appropriate due to rapid changes in network conditions.The optimal path from among all possible courses is chosen in computer networks based on a variety of parameters.In this paper,we design a new variant of the Floyd-Warshall algorithm that identifies an All-Pair Shortest Path(APSP)in an uncertain situation of a network.In the proposed methodology,multiple criteria and theirmutual associationmay involve the selection of any suitable path between any two node points,and the values of these criteria may change due to an uncertain environment.We use trapezoidal picture fuzzy addition,score,and accuracy functions to find APSP.We compute the time complexity of this algorithm and contrast it with the traditional Floyd-Warshall algorithm and fuzzy Floyd-Warshall algorithm.

Picture Fuzzy Relations over Picture Fuzzy Sets

Nowadays, picture fuzzy set theory is a flourishing field in mathematics with uncertainty by incorporating the concept of positive, negative and neutral membership degrees of an object. A traditional crisp relation represents the satisfaction or the dissatisfaction of relationship, connection or correspondence between the objects of two or more sets. However, there are some problems that can’t be solved through classical relationships, such as the relationship between two objects being vague. In those situations, picture fuzzy relation over picture fuzzy sets is an important and powerful concept which is suitable for describing correspondences between two vague objects. It represents the strength of association of the elements of picture fuzzy sets. It plays an important role in picture fuzzy modeling, inference and control system and also has important applications in relational databases, approximate reasoning, preference modeling, medical diagnosis, etc. In this article, we define picture fuzzy relations over picture fuzzy sets, including some other fundamental definitions with illustrations. The max-min and min-max compositions of picture fuzzy relations are defined in the light of picture fuzzy sets and discussed some properties related to them. The reflexivity, symmetry and transitivity of a picture fuzzy relation are described over a picture fuzzy set. Finally, various properties are explored related to the picture fuzzy relations over a picture fuzzy set.

Cayley Picture Fuzzy Graphs and Interconnected Networks

Theory of the Cayley graphs is directly linked with the group theory.However,if there are uncertainties on the vertices or edges or both then fuzzy graphs have an extraordinary importance.In this perspective,numbers of generalηizations of fuzzy graphs have been explored in the literature.Among the others,picture fuzzy graph(PFG)has its own importance.A picture fuzzy graph(PFG)is a pair G=(C,D)defined on a H^(*)=(A,B),where C=(ηC,θ_(C),■_(C))is a picture fuzzy set on A and D=(ηD,θ_(D),■_(D))is a picture fuzzy set over the set B∈A×A such that for any edge mn∈ B with ηD(m,n)≤min(ηC(m),ηC(n)),θD(m,n)≤min(θC(m),θC(n))and ■_(D)(m,n)≥max(■_(C)(m),■_(C)(n)).In this manuscript,we introduce the notion of the Cayley picture fuzzy graphs on groups which is the generalization of the picture fuzzy graphs.Firstly,we discuss few important characteristics of the Cayley picture fuzzy graphs.We show that Cayley picture fuzzy graphs are vertex transitive and hence regular.Then,we investigate different types of Cayley graphs induced by the Cayley picture fuzzy graphs by using different types of cuts.We extensively discuss the term connectivity of the Cayley picture fuzzy graphs.Vertex connectivity and edge connectivity of the Cayley picture fuzzy graphs are also addressed.We also investigate the linkage between these two.Throughout,we provide the extensions of some characηteristics of both the PFGs and Cayley fuzzy graphs in the setting of Cayley picture fuzzy graphs.Finally,we provide the model of interconnected networks based on the Cayley picture fuzzy graphs.

Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering for Noisy Data

Clustering is a crucial method for deciphering data structure and producing new information.Due to its significance in revealing fundamental connections between the human brain and events,it is essential to utilize clustering for cognitive research.Dealing with noisy data caused by inaccurate synthesis from several sources or misleading data production processes is one of the most intriguing clustering difficulties.Noisy data can lead to incorrect object recognition and inference.This research aims to innovate a novel clustering approach,named Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering(PNTS3FCM),to solve the clustering problem with noisy data using neutral and refusal degrees in the definition of Picture Fuzzy Set(PFS)and Neutrosophic Set(NS).Our contribution is to propose a new optimization model with four essential components:clustering,outlier removal,safe semi-supervised fuzzy clustering and partitioning with labeled and unlabeled data.The effectiveness and flexibility of the proposed technique are estimated and compared with the state-of-art methods,standard Picture fuzzy clustering(FC-PFS)and Confidence-weighted safe semi-supervised clustering(CS3FCM)on benchmark UCI datasets.The experimental results show that our method is better at least 10/15 datasets than the compared methods in terms of clustering quality and computational time.

Arithmetic Operations of Generalized Trapezoidal Picture Fuzzy Numbers by Vertex Method

In this article, we define the arithmetic operations of generalized trapezoidal picture fuzzy numbers by vertex method which is assembled on a combination of the (α, γ, β)-cut concept and standard interval analysis. Various related properties are explored. Finally, some computations of picture fuzzy functions over generalized picture fuzzy variables are illustrated by using our proposed technique.

Not one thing at a time:When concomitant multiple stressors produce a transdiagnostic clinical picture

A condition of exposure to multiple stressors resulting in a mixed clinical picture spanning conventional categories without meeting any of them in full,encompasses a risk for a list of comorbidities preventing appropriate prevention and treatment.New transformative transdiagnostic approaches suggest changes spanning conventional categories.They base their systems of classification on biomarkers as well as on brain structural and functional dysregulation as associated with behavioral and emotional symptoms.These new approaches received critiques for not being specific enough and for suggesting a few biomarkers for psychopathology as a whole.Therefore,they put the value of differential diagnosis at risk of avoiding appropriate derived prevention and treatment.Multiplicity of stressors has been considered mostly during and following catastrophes,without considering the resulting mixed clinical picture and life event concomitant stressors.We herewith suggest a new category within the conventional classification systems:The Complex Stress Reaction Syndrome,for a condition of multiplicity of stressors,which showed a mixed clinical picture for daily life in the post coronavirus disease 2019 era,in the general population.We argue that this condition may be relevant to daily,regular life,across the lifespan,and beyond conditions of catastrophes.We further argue that this condition may worsen without professional care and it may develop into a severe mental health disorder,more costly to health systems and the suffering individuals.Means for derived prevention and treatment are discussed.

Oxbridge Pictures in Woolf’s A Room of One’s Own

A Room of One’s Own is a masterpiece by Virginia Woolf, which describes her understanding of literary creation and the issue of women and fiction. The content of this book is based on Woolf’s two speeches at Cambridge, with the theme of “Women and fiction.” Through the analysis of the history and current situation of female literary creation, the paper points out that women should have the courage and right to fight for independent economic power and social status. “Oxbridge” is a combined term of Oxford and Cambridge, and Oxbridge pictures dominate the first chapter of A Room of One’s Own, which are the focus of this paper. Through a detailed analysis of the different indoor and outdoor pictures of Oxbridge, including nature, landscape, humanistic architecture and the “pictures” imagined in the narrator’s mind, this paper discusses the existence of Victorian women and Woolf’s feminist thoughts so as to provide possible implications for the social survival of contemporary women. The study is also concerned with Woolf’s Eco-feminism, stream of consciousness and other artistic skills.

The Tantou New Year Picture

Tantou is an ancient town in Longhui,Hunan.And the Tantou New Year Picture is a famous traditional art form.It first appeared in the Tang Dynasty.And it is mostly used for the Spring Festival.There are more than 20 steps to make it.All these steps,from making paper by hand to producing the New Year Picture,are finished in one place.That s amazing.It's very popular for its special features--bright colors,old and exagge-rated images,ordinary materials and special skills.

基于FANUC PICTURE软件的人机界面二次开发及应用

通过FANUC PICTURE软件人机界面设计流程、数控机床典型界面(报警界面、润滑界面、横梁界面)制作实例等方面叙述,开发出了操作简单、快捷的数控机床人机界面并在实践中得到了验证,受到了广大机床操作者的喜爱和高度评价。

属性权重未知picture模糊多属性决策方法及其应用

针对属性权重未知的picture模糊多属性决策问题,提出一种基于picture模糊熵和picture模糊加权对称交叉熵的多属性决策方法。首先,基于余弦函数提出一类新的picture模糊熵,并验证该熵值满足picture模糊熵的公理化定义;其次,针对标准化处理后的picture模糊决策矩阵,以picture模糊熵确定各属性权重,同时确定正、负理想方案;再次,分别计算各方案与正、负理想方案的picture模糊加权对称交叉熵,考虑决策者的主观评价倾向以模糊折中值得到各备选方案的排序结果;最后,将所提多属性决策方法应用于河南自贸试验区郑州片区创新型项目遴选,并通过对比分析验证该决策方法的有效性与合理性。

基于FANUC PICTURE椭圆内孔加工人机界面开发及应用

在研究FANUC PICTURE强大图形显示和贴图功能的基础上,提出基于FANUC PICTURE椭圆内孔加工的人机界面开发。根据人机界面开发方法,开发出椭圆内孔加工人机界面,并与宏程序手工编程、CAD/CAM软件编程对比分析。结果表明:采用椭圆内孔加工人机界面大大缩短了编程时间,有效提高了编程效率,比宏程序手工编程效率提高40%左右,比CAD/CAM软件编程效率提高1.5倍以上。这为其他复杂形面的人机界面开发提供了参考。

基于FANUC PICTURE轴类零件加工专用人机界面开发与应用

为解决数控机床加工操作者培训周期长,加工出错率高,且加工质量不稳当的问题,本文以FANUC PICTURE为开发工具,开发一种面向FANUC数控系统的轴类零件加工专用人机界面,使用该人机界面能大幅降低对数控操作者的技能要求。操作者根据加工图纸,可直接在人机界面中快速选取所需加工轴类零件的特征尺寸信息,对该特征尺寸要素进行编辑修改,即可直接进行数控加工。经实际加工验证,操作者上手快,效率高,且加工产品质量稳定,符合产品技术要求。

基于FANUC PICTURE椭圆型腔人机界面开发及应用

针对二次曲线类零件宏程序编程参数不清和不直观的问题,以椭圆型腔零件为例,利用FANUC PICTURE开发软件的强大图像处理功能,开发了椭圆型腔人机交互界面模块。经检验,实现了二次曲线零件数控编程简单化、方便化、快捷化、模块化及操作界面友好化。对其他复杂型面二次曲线类零件人机界面开发具有借鉴意义。