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.

Enhanced DDoS Detection Using Advanced Machine Learning and Ensemble Techniques in Software Defined Networking

Detecting sophisticated cyberattacks,mainly Distributed Denial of Service(DDoS)attacks,with unexpected patterns remains challenging in modern networks.Traditional detection systems often struggle to mitigate such attacks in conventional and software-defined networking(SDN)environments.While Machine Learning(ML)models can distinguish between benign and malicious traffic,their limited feature scope hinders the detection of new zero-day or low-rate DDoS attacks requiring frequent retraining.In this paper,we propose a novel DDoS detection framework that combines Machine Learning(ML)and Ensemble Learning(EL)techniques to improve DDoS attack detection and mitigation in SDN environments.Our model leverages the“DDoS SDN”dataset for training and evaluation and employs a dynamic feature selection mechanism that enhances detection accuracy by focusing on the most relevant features.This adaptive approach addresses the limitations of conventional ML models and provides more accurate detection of various DDoS attack scenarios.Our proposed ensemble model introduces an additional layer of detection,increasing reliability through the innovative application of ensemble techniques.The proposed solution significantly enhances the model’s ability to identify and respond to dynamic threats in SDNs.It provides a strong foundation for proactive DDoS detection and mitigation,enhancing network defenses against evolving threats.Our comprehensive runtime analysis of Simultaneous Multi-Threading(SMT)on identical configurations shows superior accuracy and efficiency,with significantly reduced computational time,making it ideal for real-time DDoS detection in dynamic,rapidly changing SDNs.Experimental results demonstrate that our model achieves outstanding performance,outperforming traditional algorithms with 99%accuracy using Random Forest(RF)and K-Nearest Neighbors(KNN)and 98%accuracy using XGBoost.

Report for Type 2 Bayes-Fuzzy Estimation in No-Data Problem

It is well known that the system (1 + 1) can be unequal to 2, because this system has both observation error and system error. Furthermore, we must provide our mustered service within our cool head and warm heart, where two states of nature are existing upon us. Any system is regarded as the two-dimensional variable error model. On the other hand, we consider that the fuzziness is existing in this system. Though we can usually obtain the fuzzy number from the possibility theory, it is not fuzzy but possibility, because the possibility function is as same as the likelihood function, and we can obtain the possibility measure by the maximal likelihood method (i.e. max product method proposed by Dr. Hideo Tanaka). Therefore, Fuzzy is regarded as the only one case according to Vague, which has both some state of nature in this world and another state of nature in the other world. Here, we can consider that Type 1 Vague Event in other world can be obtained by mapping and translating from Type 1 fuzzy Event in this world. We named this estimation as Type 1 Bayes-Fuzzy Estimation. When the Vague Events were abnormal (ex. under War), we need to consider that another world could exist around other world. In this case, we call it Type 2 Bayes-Fuzzy Estimation. Where Hori et al. constructed the stochastic different equation upon Type 1 Vague Events, along with the general following probabilistic introduction method from the single regression model, multi-regression model, AR model, Markov (decision) process, to the stochastic different equation. Furthermore, we showed that the system theory approach is Possibility Markov Process, and that the making decision approach is Sequential Bayes Estimation, too. After all, Type 1 Bays-Fuzzy estimation is the special case in Bayes estimation, because the pareto solutions can exist in two stochastic different equations upon Type 2 Vague Events, after we ignore one equation each other (note that this is Type 1 case), we can obtain both its system solution and its decision solution. Here, it is noted that Type 2 Vague estimation can be applied to the shallow abnormal decision problem with possibility reserved judgement. However, it is very important problem that we can have no idea for possibility reserved judgement under the deepest abnormal envelopment (ex. under War). Expect for this deepest abnormal decision problem, Bayes estimation can completely cover fuzzy estimation. In this paper, we explain our flowing study and further research object forward to this deepest abnormal decision problem.

Mathematical Modeling of Possibility Markov Chains by Possibility Theory

Statistical regression models are input-oriented estimation models that account for observation errors. On the other hand, an output-oriented possibility regression model that accounts for system fluctuations is proposed. Furthermore, the possibility Markov chain is proposed, which has a disidentifiable state (posterior) and a nondiscriminable state (prior). In this paper, we first take up the entity efficiency evaluation problem as a case study of the posterior non-discriminable production possibility region and mention Fuzzy DEA with fuzzy constraints. Next, the case study of the ex-ante non-discriminable event setting is discussed. Finally, we introduce the measure of the fuzzy number and the equality relation and attempt to model the possibility Markov chain mathematically. Furthermore, we show that under ergodic conditions, the direct sum state can be decomposed and reintegrated using fuzzy OR logic. We had already constructed the Possibility Markov process based on the indifferent state of this world. In this paper, we try to extend it to the indifferent event in another world. It should be noted that we can obtain the possibility transfer matrix by full use of possibility theory.

A Blind Spot in the Reframing of a Universe of Possibles: Towards a Suitable Model for Decision-Making Theory and A.I.

Bayesian inference model is an optimal processing of incomplete information that, more than other models, better captures the way in which any decision-maker learns and updates his degree of rational beliefs about possible states of nature, in order to make a better judgment while taking new evidence into account. Such a scientific model proposed for the general theory of decision-making, like all others in general, whether in statistics, economics, operations research, A.I., data science or applied mathematics, regardless of whether they are time-dependent, have in common a theoretical basis that is axiomatized by relying on related concepts of a universe of possibles, especially the so-called universe (or the world), the state of nature (or the state of the world), when formulated explicitly. The issue of where to stand as an observer or a decision-maker to reframe such a universe of possibles together with a partition structure of knowledge (i.e. semantic formalisms), including a copy of itself as it was initially while generalizing it, is not addressed. Memory being the substratum, whether human or artificial, wherein everything stands, to date, even the theoretical possibility of such an operation of self-inclusion is prohibited by pure mathematics. We make this blind spot come to light through a counter-example (namely Archimedes’ Eureka experiment) and explore novel theoretical foundations, fitting better with a quantum form than with fuzzy modeling, to deal with more than a reference universe of possibles. This could open up a new path of investigation for the general theory of decision-making, as well as for Artificial Intelligence, often considered as the science of the imitation of human abilities, while being also the science of knowledge representation and the science of concept formation and reasoning.

Exposure to different severities of famine and subsequent risk of sarcopenia in old age

Background:Poor nutritional status is closely related to the development of sarcopenia and possible sarcopenia.Limited articles have evaluated the impact of undernutrition at different stages of life on the development of sarcopenia or possible sarcopenia in old age.The 1959–1962 Chinese famine provided the possibility for large-scale population studies on the effects of long-term undernutrition or inad-equate intake on various health problems.In this study,we aimed to investigate the effects of long-term reduction of food intake(expo-sure to the 1959–1962 Chinese famine)in early life on the development of sarcopenia and possible sarcopenia in later life.Methods:We used data from the China Health and Retirement Longitudinal Survey(CHARLS)2015 and obtained information on whether participants had experienced famine from the 2014 Life Course Survey of Chinese Residents.After data integration and cleaning,we divided the included participants into five age-exposure cohorts based on birthdate,including cohorts exposed to famine during preschool,midchildhood,young teenage years,teenage years,and adulthood to analyze the long-term effects of exposure to famine on the development of sarcopenia and possible sarcopenia.Results:Exposure to moderate or severe famine did not significantly increase the risk of possible sarcopenia(P>0.05).In a further stratified analysis,moderate famine exposure in adulthood significantly increased the risk of possible sarcopenia(1.475 times;95%CI:1.104–1.969,P=0.009).However,there was no significant association between famine exposure and possible sarcopenia in the preschool,midchildhood,young teenage,or teenage exposure cohorts(P>0.05).Conclusions:Exposure to famine in preadulthood did not increase the risk of possible sarcopenia in older adults.However,the risk of possible sarcopenia in later life was increased about 50%among participants who were exposed to moderate famine in adulthood.

考虑权重因素的非概率可靠性模型

利用区间变量描述参量的不确定性,基于加权平均理论和PDF(possibility degree formula)区间比较法则,依据非概率区间分析方法,建立考虑权重因素的非概率可靠性模型。该模型更进一步地利用数据信息,提高数据积累阶段的可靠性评估精度;将非概率可靠性指标统一到概率可靠度上,有很好的工程应用价值。最后利用算例验证文中提出模型的可行性。

Multiple attribute decision making method based on trapezoid fuzzy linguistic variables

The problem of multiple attribute decision making under fuzzy linguistic environments, in which decision makers can only provide their preferences （attribute values）in the form of trapezoid fuzzy linguistic variables（TFLV）, is studied. The formula of the degree of possibility between two TFLVs is defined, and some of its characteristics are studied. Based on the degree of possibility of fuzzy linguistic variables, an approach to ranking the decision alternatives in multiple attribute decision making with TFLV is developed. The trapezoid fuzzy linguistic weighted averaging （TFLWA） operator method is utilized to aggregate the decision information, and then all the alternatives are ranked by comparing the degree of possibility of TFLV. The method can carry out linguistic computation processes easily without loss of linguistic information, and thus makes the decision results reasonable and effective. Finally, the implementation process of the proposed method is illustrated and analyzed by a practical example.

Approach to obtaining weights of uncertain ordered weighted geometric averaging operator

The ordered weighted geometric averaging（OWGA） operator is extended to accommodate uncertain conditions where all input arguments take the forms of interval numbers. First, a possibility degree formula for the comparison between interval numbers is introduced. It is proved that the introduced formula is equivalent to the existing formulae, and also some desired properties of the possibility degree is presented. Secondly, the uncertain OWGA operator is investigated in which the associated weighting parameters cannot be specified, but value ranges can be obtained and the associated aggregated values of an uncertain OWGA operator are known. A linear objective-programming model is established; by solving this model, the associated weights vector of an uncertain OWGA operator can be determined, and also the estimated aggregated values of the alternatives can be obtained. Then the alternatives can be ranked by the comparison of the estimated aggregated values using the possibility degree formula. Finally, a numerical example is given to show the feasibility and effectiveness of the developed method.

中国高僧与越南“少林寺”

The But Thap Temple in Bac Ninh province of Viet Nam has two Chinese names,one is Ninh Phuc Temple and the other,an alternative one,Thieu Lam Temple.In the middle of17th century,the Chinese Chuyet Cong and Minh Hanh lived and made great contribution to its development.The temple is deeply affected by Chinese culture and the reason for its alˉternative name,the paper argues,is possible related to China’s“North Shao Lin”.

关于锗的必需性问题

在自然界存在的92种元素中,现已在人体中发现81种。根据其生物学作用,可将这些元素分为三类,即必需元素,可能必需元素和非必需元素。目前已知,必需元素共有26种,其中11种是常量元素,15种是微量元素。高等动物必需的微量元素是:Fe、I、Cu、Mn、Zn、Co、Mo、Se、Cr、Sn、V、F、Si、Ni 和 As。随着科学技术的发展,还可能发现一些微量元素对生命活动也是必需的。本文讨论锗的必需性问题。

POSSIBLY用法译评

英语情态副词及其相关的形容词,用法上常常既有相通之处,也有不同之处。本文拟对possibly及其相关的形容词、副词在语义、修饰、句法、位置等方面加以辨析。

佳能广告“Impossible Made Possible”之文体分析

佳能打印机广告"impossible made possible"有着显著的文体特征:一是语音方面,各种押韵被用到,如头韵、尾韵等;音调重音在末尾;元辅音的频繁重复使用。二是词汇方面,形容词占据着极大的比重;反义词possible与impossible强烈的对比效果。三是句法方面,过去简单小句的使用使句子短小精湛。四是语义方面,修辞手法—"重复"的使用。五是语篇方面,情态的精准把握与极性词的使用;语言组织时概念主位与述位精确的定位;口语与书面语的交替使用。基于以上文体特征,该广告大获成功。

可以说“Sb.is lack of sth.”吗?

[问][504]可以说“Sb．is lack of sth．”吗？ [答]关于这个问题我们先看看下面两道相关的英语试题： 1）单选题： We tried to settle the problem with them as soon as possible, but they seemed to __ sincerity.

To be or not to be——College English teacher′s possible roles

Traditionally, in a teacher-centered class, students are deprived of right, for teachers take up the platform and play a “leading” role. What are the college English teacher′s possible roles? The paper tends to shed light on it by kicking the teacher′s traditional roles.

由~*as possible as I can/could引发的思考

中介语研究是二语习得理论的重要内容。传统的观点认为,中介语是与二语习得有关的五种认知过程的产物。按母语是否介入,中介语的成因可分为语际干扰和语内干扰,语内干扰以超度归纳为典型。本文从*as possible as I can/could这一中介语形式入手,借助CLEC语料库,试图分析其成因。分析后发现:*as possible as I can/could主要源自于语内干扰,但不是超度归纳,而是因语内同义形似干扰而形成。因此,本文提出,语内干扰的形式,除了传统的超度归纳,还应包括语内同义形似干扰。这种干扰易错误石化,应予以及时纠正。

品牌重塑的成功之道

2010年6月30日．李宁品牌口号“一切皆有可能”（Everything is possible）及其标识正式“退役”，新口号“Make The Change”（让改变发生）开始启用。富有李宁自创金牌鞍马动作意蕴的“李宁交叉”则成为其新标识。李宁原标识长期以来都被诟病为模仿耐克（Nike），而其口号“Everything is possible”（一切皆有可能）也被认为与阿迪达斯（Adidasl）“Nothing is impossible”（没有什么不可能）雷同。

商品房住宅区公共物业自治管理制度分析 以上海市水仙苑小区为例

The reform of the housing system in Shanghai has unexpectedly given rise to a self-governed property owners’ collective supervisory system, primarily in the form of Property Owners’ Supervisory Council (POSC), which has picked up some of the government’s administrative functions. Although this new, institutionalized management model has theoretically made democratic managerial participation at the grassroots level possible, it has brought about endless problems, overt and covert, shortly after its appearance, some of which are even alarming. A comprehensive analysis of the data collected over a long period of time has led to the conclusion that this system is a failure, attributable to the overt factor related to skills in reality and the covert “priori” factor that is masked by the former. The existence of such “priori” factor once again demonstrates the deep-rooted, traditional managerial logic: Positive operations is society need only to depend upon individuals’ unstable self-disciplined morality rather than to build a system. The current paper points out that any change in the socioeconomic structure that has long been subject to the power of politics is to inevitably incur a corresponding global structural accommodation, including politics itself. To respond to the two factors for the failure, system building in the two overlapping areas is a must.

Effect of Dietary Resistant Starch on Prevention and Treatment of Obesity-related Diseases and Its Possible Mechanisms

Overweight or obesity has become a serious public health problem in the world, scientists are concentrating their efforts on exploring novel ways to treat obesity. Nowadays, the availabilities of bariatric surgery and pharmacotherapy have enhanced obesity treatment, but it should has support from diet, physical exercise and lifestyle modification, especially the functional food. Resistant starch, an indigestible starch, has been studied for years for its beneficial effects on regulating blood glucose level and lipid metabolism. The aim of this review is to summarize the effect of resistant starch on weight loss and the possible mechanisms. According to numerous previous studies it could be concluded that resistant starch can reduce fat accumulation, enhance insulin sensitivity, regulate blood glucose level and lipid metabolism. Recent investigations have focused on the possible associations between resistant starch and incretins as well as gut microbiota. Resistant starch seems to be a promising dietary fiber for the prevention or treatment of obesity and its related diseases.