In order to safeguard the safety of passengers and reducemaintenance costs, it is necessary to analyze and evaluate the security risk ofthe Railway Signal System. However, the conventional Fuzzy Analytical HierarchyProcess (FAHP) can not describe the fuzziness and randomness of the judgment,accurately, and once the fuzzy sets are described using subjection degreefunction, the concept of fuzziness will be no longer fuzzy. Thus Fuzzy-FMECAmethod based on cloud model is put forward. Failure Modes Effects andCriticality Analysis (FMECA) method is used to identify the risk and FAHP basedon cloud model is used for determining the subjection degree function in fuzzymethod, finally the group decision can be gained with the syntheticallyaggregated cloud model, the method’s feasibility and effectiveness are shown inthe practical examples. Finally Fuzzy-FMECA based on cloud model and theconventional FAHP are used to assess the risk respectively, evaluation resultsshow that the cloud model which is introduced into the risk assessment ofRailway Signal System can realize the transition between precise value andquality value by combining the fuzziness and randomness and provide moreabundant information than subjection degree function of the conventional FAHP.
The present paper introduces a parametric generalized exponential measure of fuzzy divergence of order α with the proof of its validity. A particular case of proposed fuzzy divergence measure is studied. Some properties of the new divergence measure between different fuzzy sets are proved. We establish a relation between exponential fuzzy entropy of order α and our fuzzy divergence measure. Further, a numerical example is given for the comparative study of the new divergence measure with some of existing measures. Finally, application of the measure to strategic decision-making is discussed and a comparative study of the method of strategic decision-making with the existing methods is presented. It is noted that the new measure of fuzzy divergence and the method of strategic decision-making comprise greater simplicity, consistency and flexibility in applications due to the presence of the parameter.
This paper aims to introduce the theory of imprecise soft sets which is a hybrid model of soft sets and imprecise sets. It has been established that two independent laws of randomness are necessary and sufficient to define a law of fuzziness. Further, in case of fuzzy sets, the set theoretic axioms of exclusion and contradiction are not satisfied. Accordingly, the theory of imprecise sets has been developed where these mistakes arising in the literature of fuzzy sets are absent. Our work is an endeavor to combine imprecise sets with soft sets resulting in imprecise soft sets. We have put forward a matrix representation of imprecise soft sets. Finally we have studied the notion of similarity of two imprecise soft sets and put forward an application of similarity in a decision problem.
Molecular recognition by intrinsically disordered proteins (IDPs) commonly involves specific localized contacts and target-induced disorder to order transitions. However, some IDPs remain disordered in the bound state, a phenomenon coined “fuzziness”, often characterized by IDP polyvalency, sequence-insensitivity and a dynamic ensemble of disordered bound-state conformations. Besides the above general features, specific biophysical models for fuzzy interactions are mostly lacking. The transcriptional activation domain of the Ewing's Sarcoma oncoprotein family (EAD) is an IDP that exhibits many features of fuzziness, with multiple EAD aromatic side chains driving molecular recognition. Considering the prevalent role of cation-π interactions at various protein-protein interfaces, we hypothesized that EAD-target binding involves polycation- π contacts between a disordered EAD and basic residues on the target. Herein we evaluated the polycation-π hypothesis via functional and theoretical interrogation of EAD variants. The experimental effects of a range of EAD sequence variations, including aromatic number, aromatic density and charge perturbations, all support the cation-π model. Moreover, the activity trends observed are well captured by a coarse-grained EAD chain model and a corresponding analytical model based on interaction between EAD aromatics and surface cations of a generic globular target. EAD-target binding, in the context of pathological Ewing's Sarcoma oncoproteins, is thus seen to be driven by a balance between EAD conformational entropy and favorable EAD-target cation-π contacts. Such a highly versatile mode of molecular recognition offers a general conceptual framework for promiscuous target recognition by polyvalent IDPs.
The data mining is to discover knowledge from the database, quantitative association rules mining method is difficult for their values are too large. The usual means is dividing quantitative Data to discrete conception. The Cloud model combines fuzziness and randomness organically, so it fits the real world objectively, a new method to mine association rules from quantitative data based on the cloud model was proposed, which first take the original data distribution in the database into account, and then use the trapezoidal cloud model to complicate concepts division, and transforms qualitative data to the quantitative concept, in the conversion take account of the basic characteristics of human behavior fully, divides quantitative Data with trapezium Cloud model to create discreet concepts, the concept cluster within one class, and separated with each other. So the quantitative Data can be transforms to Boolean data well, the Boolean data can be mined by the mature Boolean association rules mining method to find useful knowledge.
“Rule number explosion” in fuzzy controller and “uncertainty” in the model are two main issues in the design of fuzzy control systems. To overcome these problems, we have applied a method in which a linear sensory fusion function has been used to reduce the number of dimensions of fuzzy controller’s inputs and simultaneously use the features of LQR control. Since, in type-2 fuzzy control, the degree of fuzziness increased and it can better handle the uncertainty in the model compared to conventional fuzzy, so the method of sensory fusion with type-2 fuzzy control scheme has been combined to make the controller more robust w.r.t. the parameter variation, perturbance and uncertainty in the model. Performance criteria like IAE, ISE and ITAE have been used to compare the control performance obtained from conventional fuzzy and type-2 fuzzy controller.
Beibuwan Economical Zone of Guangxi Province has the necessary basis and conditions to develop the madicine manufacturing industry.It is significant to select products which ficilitate the development of madicine manufacturing industry from the prospective of promoting the development of the industry smoothly. The feature of selection of essential products of medicine manufacturing can be summarized as multi-objectiveness, multi-layer, fuzziness and the interaction and penetration of different objectives. Due to these characteristics, analysis is made through analytic hierarchy process (AHP) by this thesis. The paper put forward the developmental sequence of madicine manufacturing industry in Beibuwan Economical Zone of Guangxi Province by adopting analytic hierarchy process, and pointed out that, among others, the technical competence is the most influnctial factor of a company. The appropriate developmental sequence of the products selected is biological and biochemical products, medicinal chemicals, chemical medicine and preparations. This research is in favor of speeding up the development of competitive products and creating industry competition.
Background Dizziness is a common complaint among older adults and has been linked to a wide range of health conditions, psychological and social characteristics in this population. However a profile of dizziness is still uncertain which hampers clinical decision-making. We therefore sought to explore the relationship between dizziness and a comprehensive range of demographic data, diseases, health and geriatric conditions, and geriatric syndromes in a representative sample of community-dwelling older people. Methods This is a cross-sectional, population-based study derived from FIBRA (Network for the Study of Frailty in Brazilian Elderly Adults), with 391 elderly adults, both men and women, aged 65 years and older. Elderly participants living at home in an urban area were enrolled through a process of random cluster sampling of census regions. The outcome variable was the self-report of dizziness in the last year. Several feelings of dizziness were investigated including vertigo, spinning, light or heavy headedness, floating, fuzziness, giddiness and instability. A multivariate logistic regression analysis was conducted to estimate the adjusted odds ratios and build the probability model for dizziness. Results The complaint of dizziness was reported by 45% of elderly adults, from which 71.6% were women (p=0.004). The multivariate regression analysis revealed that dizziness is associated with depressive symptoms (OR = 2.08; 95% CI 1.29–3.35), perceived fatigue (OR = 1.93; 95% CI 1.21-3.10), recurring falls (OR = 2.01; 95% CI 1.11-3.62) and excessive drowsiness (OR = 1.91; 95% CI 1.11–3.29). The discrimination of the final model was AUC = 0.673 (95% CI 0.619-0.727) (p< 0.001). Conclusions The prevalence of dizziness in community-dwelling elderly adults is substantial. It is associated with other common geriatric conditions usually neglected in elderly adults, such as fatigue and drowsiness, supporting its possible multifactorial manifestation. Our findings demonstrate the need to expand the design in future studies, aiming to estimate risk and identify possible causal relations.
Purpose The aim of this paper is to develop a mean-entropy-skewness stock portfolio selection model with transaction costs in an uncertain environment. Methods Since entropy is free from reliance on symmetric probability distributions and can be computed from nonmetric data, it is more general than others as a competent measure of risk. In this work, returns of securities are assumed to be uncertain variables, which cannot be estimated by randomness or fuzziness. The model in the uncertain environment is formulated as a nonlinear programming model based on uncertainty theory. Also, some other criteria like short-and long-term returns, dividends, number of assets in the portfolio, and the maximum and minimum allowable capital invested in stocks of any company are considered. Since there is no efficient solution methodology to solve the proposed model, assuming the returns as some special uncertain variables, the original portfolio selection model is transformed into an equivalent deterministic model, which can be solved by any state-of-the-art solution methodology. Results The feasibility and effectiveness of the proposed model is verified by a numerical example extracted from Bombay Stock Exchange, India. Returns are considered in the form of trapezoidal uncertain variables. A genetic algorithm is used for simulation. Conclusions The efficiency of the portfolio is evaluated by looking for risk contraction on one hand and expected return and skewness augmentation on the other hand. An empirical application has served to illustrate the computational tractability of the approach and the effectiveness of the proposed algorithm.
The catch 22 situation in psychiatry is that for precise diagnostic categories/criteria, we need precise investigative tests, and for precise investigative tests, we need precise diagnostic criteria/categories; and precision in both diagnostics and investigative tests is nonexistent at present. The effort to establish clarity often results in a fresh maze of evidence. In finding the way forward, it is tempting to abandon the scientific method, but that is not possible, since we deal with real human psychopathology, not just concepts to speculate over. Search for clear-cut definitions/diagnostic criteria in psychiatry must be relentless. There is a greater need to be ruthless and blunt in this, rather than being accommodative of diverse opinions. Investigative tests - psychological, serum, CSF, or neuroimaging - are only corroborative at present; they need to become definitive.Medicalisation appears most prominent in psychiatry; so, diagnostic proliferation and fuzziness appear inevitable. And yet, the established diagnostic entities need to forward greater and conclusive precision. Also, the need for clarity and precision must outweigh pandering to and mollifying diverse interests, moreso in the upcoming revision of diagnostic manuals. This is specially because the DSM-5, being an Association manual, may need to accommodate powerful member lobbies; and ICD-11 may similarly need to cater to diverse country lobbies. Finding precise biological correlates of psychiatric phenomena, whether through neuroimaging, molecular neurobiology and/or neurogenomics, is the right way forward. It is in the 1.5-kg structure in the cranium that all secrets of psychiatric conditions lie. Social forces, behavioural modification, psychosocial restructuring, study of intrapsychic processes, and philosophical insights are not to be discounted, but they are supplementary to the primary goal - studying and deciphering those brain processes that result in psychiatric malfunction. Experimental breakthroughs, both in psychiatric aetiology and therapeutics, will come mainly from biology and its adjunct, psychopharmacology; while supplementary and complementary breakthroughs will come from the psychosocial, cognitive and behavioural approaches; the support base will come from phenomenology, epidemiology, nosology and diagnostics; while insights and leads can hopefully come from many fields, especially the psychosocial, the behavioural, the cognitive and the philosophical.Major energies must now be marshalled towards finding biomarkers and deciphering the precise phenotype-genotype-endophenotype axis of psychiatric disorders. Energies also need to be focussed on unravelling those critical processes in the brain that tip the scale towards psychiatric disorders. At how those critical processes are set into motion by forces de novo, in utero, in the genes and their expression, by the environment's psychopathological social forces - stress, peer pressure, poverty, deprivation, alienation, malnutrition, discrimination of various types (caste, gender, race, etc.), mass conflicts (war, terror attacks, etc.), disasters (natural and man-made), religious/ideological fascism - or social institutions like marriage, family, work place, political governance, etc. Ultimately, we must decipher how the brain goes into malfunction when such varied forces impinge on it, which precise cortical areas and neuronal cellular and molecular processes are involved in such malfunction and its manifestation, as also which of these are involved when malfunction ceases and health is restored, and the psychosocial processes and institutions which aid such health restoration, as also those which promote well-being and help in primary prevention. Emphasis on the brain and its intimate neurological and molecular mechanisms will not impinge on, or nullify, importance of the 'mind,' wherein subtle and gross brain functions in the form of behaviour, thought and emotions in all their ramifications will continue to be the focus of psychological, cognitive, sociological, psychopharmacological, behavioural and philosophical research. Progress in brain research must move in tandem with progress in 'mind' research.