Generalized Soft Expert Set and Its Applications

The expert set theory performs an important part in making decisions. It can successfully convey the opinions of every expert since it includes several experts. In this study, generalizations and soft expert sets are combined. First, the generalized soft expert set notion is presented, then follows the definition of operation approaches and characteristics as the complement, union, intersection, AND and OR. The application of the generalized soft expert set concept to decision issues is then presented with an example. The study also introduces the idea of a generalized soft expert matrix and demonstrates how it may be used to solve decision-making issues. The most striking aspect of this paper is to present the concepts of generalized soft expert sets and generalized soft expert matrices and to apply them to the same decision-making scenario.

Fuzzy Soft Expert Matrix Theory and Its Application in Decision-Making

A unique mathematical strategy for dealing with uncertainty is fuzzy soft set theory. In this paper, we propose fuzzy soft expert matrices and describe numerous varieties of fuzzy soft expert matrices, as well as specific operations. Finally, by applying these matrices to decision-making scenarios, we widen our methodology.

正规soft群

提出正规soft群的概念,讨论了正规soft群的一些性质,并给出了soft群的三个同构定理.

Pseudo-Static Elasto-Plastic Cyclic Creep Model and Cyclic Stability of Offshore Soft Foundation

The accumulative shear deformation of soft clays under cyclic loads is considered as pseudo-static creep. A pseudo-static elasto-plastic cyclic creep model is developed based on the visco-elasto-plastic theory. The parameters in the model are determined by cyclic triaxial soil tests. A method for analyzing the stability of offshore soft foundation under wave loads is given by combining the model with pseudo-static creep analysis. An example is analyzed by the method. The results show that the horizontal and vertical stability of foundations under wave loads can be analyzed by it and the analytical results are qualitatively consistent with the observed failure modes of shallow foundations.

SOFT SENSING MODEL BASED ON SUPPORT VECTOR MACHINE AND ITS APPLICATION

Soft sensor is widely used in industrial process control. It plays animportant role to improve the quality of product and assure safety in production. The core of softsensor is to construct soft sensing model. A new soft sensing modeling method based on supportvector machine (SVM) is proposed. SVM is a new machine learning method based on statistical learningtheory and is powerful for the problem characterized by small sample, nonlinearity, high dimensionand local minima. The proposed methods are applied to the estimation of frozen point of light dieseloil in distillation column. The estimated outputs of soft sensing model based on SVM match the realvalues of frozen point and follow varying trend of frozen point very well. Experiment results showthat SVM provides a new effective method for soft sensing modeling and has promising application inindustrial process applications.

Computational dynamics of soft machines

Soft machine refers to a kind of mechanical system made of soft materials to complete sophisticated missions, such as handling a fragile object and crawling along a narrow tunnel corner, under low cost control and actuation. Hence, soft machines have raised great challenges to computational dynamics. In this review article, recent studies of the authors on the dynamic modeling, numerical simulation, and experimental validation of soft machines are summarized in the framework of multibody system dynamics. The dynamic modeling approaches are presented first for the geometric nonlinearities of coupled overall motions and large deformations of a soft component, the physical nonlinearities of a soft component made of hyperelastic or elastoplastic materials, and the frictional contacts/impacts of soft components, respectively. Then the computation approach is outlined for the dynamic simulation of soft machines governed by a set of differential-algebraic equations of very high dimensions, with an emphasis on the efficient computations of the nonlinear elastic force vector of finite elements. The validations of the proposed approaches are given via three case studies, including the locomotion of a soft quadrupedal robot, the spinning deployment of a solar sail of a spacecraft, and the deployment of a mesh reflector of a satellite antenna, as well as the corresponding experimental studies. Finally, some remarks are made for future studies.

Fuzzy Soft Expert Set and Its Application

In 1999, Molodtsov introduced the concept of soft set theory as a general mathematical tool for dealing with uncertainty. Alkhazaleh and Salleh (2011) define the concept of soft expert sets where the user can know the opinion of all experts in one model and give an application of this concept in decision making problem. So in this paper, we generalize the concept of a soft expert set to fuzzy soft expert set, which will be more effective and useful. We also define its basic operations, namely complement, union, intersection, AND and OR. We give an application of this concept in decision making problem. Finally, we study a mapping on fuzzy soft expert classes and its properties.

Improved Soft Cancellation Decoding of Polar Codes

The soft cancellation decoding of polar codes achieves a better performance than the belief propagation decoding with lower computational time and space complexities.However,because the soft cancellation decoding is based on the successive cancellation decoding,the decoding efficiency and performance with finite-length blocks can be further improved.Exploiting the idea of the successive cancellation list decoding,the soft cancellation decoding can be improved in two aspects:one is by adding branch decoding to the error-prone information bits to increase the accuracy of the soft information,and the other is through using partial iterative decoding to reduce the time and computational complexities.Compared with the original method,the improved soft cancellation decoding makes progress in the error correction performance,increasing the decoding efficiency and reducing the computational complexity,at the cost of a small increase of space complexity.

Dislocated Soft Metric Space with Soft Fixed Point Theorems

In the present paper, we define Dislocated Soft Metric Space and discuss about the existence and uniqueness of soft fixed point of a cyclic mapping in soft dislocated metric space. We also prove the unique soft fixed point theorems of a cyclic mapping in the context of dislocated soft metric space. Examples are given for support of the results.

Current management of pediatric soft tissue sarcomas

Pediatric soft tissue sarcomas are a group of malignant neoplasms arising within embryonic mesenchymal tissues during the process of differentiation into muscle, fascia and fat. The tumors have a biphasic peak for age of incidence. Rhabdomyosarcoma(RMS) is diagnosed more frequently in younger children, whereas adult-type non-RMS soft tissue sarcoma is predominately observed in adolescents. The latter group comprises a variety of rare tumors for which diagnosis can be difficult and typically requires special studies, including immunohistochemistry and molecular genetic analysis. Current management for the majority of pediatric sarcomas is based on the data from large multi-institutional trials, which has led to great improvements in outcomes over recent decades. Although surgery remains the mainstay of treatment, the curative aim cannot be achieved without adjuvant treatment. Pre-treatment staging and risk classification are of prime importance in selecting an effective treatment protocol. Tumor resectability, the response to induction chemotherapy, and radiation generally determine the risk-group, and these factors are functions of tumor site, size and biology. Surgery provides the best choice of local control of small resectable tumors in a favorable site. Radiation therapy is added when surgery leaves residual disease or there is evidence of regional spread. Chemotherapy aims to reduce the risk of relapse and improve overall survival. In addition, upfront chemotherapy reduces the aggressiveness of the required surgery and helps preserve organ function in a number of cases. Long-term survival in low-risk sarcomas is feasible, and the intensity of treatment can be reduced. In high-risk sarcoma, current research is allowing more effective disease control.

A study on distributive and modular lattice ordered fuzzy soft group and its duality

Soft set theory has a rich potential application in several fields. A soft group is a parameterized family of subgroups and a fuzzy soft group is a parameterized family of fuzzy subgroups. The concept of fuzzy soft group is the generalization of soft group. Abdulkadir Aygunoglu and Halis Aygun introduced the notion of fuzzy soft groups in 2009[1]. In this paper, the concept of lattice ordered fuzzy soft groups and its duality has been introduced. Then distributive and modular lattice ordered fuzzy soft groups are analysed. The objective of this paper is to study the lattice theory over the collection of fuzzy soft group in a parametric manner. Some pertinent properties have been analysed and hence established duality principle.

The Multi-Interval-Valued Fuzzy Soft Set with Application in Decision Making

In 1999, Molodtsov introduced the concept of soft set theory as a general mathematical tool for dealing with uncertainty. By combining the multi-fuzzy set and soft set models, Y. Yang, X. Tan and C. Meng introduced the concept of multi-fuzzy soft sets and studied some of its operations, such as complement, “AND”, “OR”, Union and Intersection. They also gave an algorithm to analyze a decision problem using multi-fuzzy soft set. In this paper, we introduce the concept of multi-interval-valued fuzzy soft set (M-IVFSS). We also define its basic operations, namely complement, union, intersection, AND and OR. Finally, we give an application of this concept in decision-making problem.

Modeling and control of dynamic soft reduction in continuous slab casting

The centerline segregation in continuous casting steel is known to be formed by the interdendritic enriched liquid flow at the solidification end in strand.At present,several methods,such as thermal soft reduction, electromagnetic stirring and dynamic soft reduction,are available to reduce the center segregation and to improve the internal quality.Although some methods could alleviate center segregation to some extent,they can also give rise to new problems.For instance,thermal soft reduction can lead to surface cracking during casting of some steels and electromagnetic stirring can result in white band.Dynamic soft reduction is an effective technology for the improvement of strand quality in continuous slab casting.In this paper,the key parameters of dynamic soft reduction technology,such as soft reduction region,the total reduction amount,for low carbon steel have been studied based on experimental and theoretical analysis.The soft reduction region was related to the segregation of chemical composition,slab bulging of narrow side and avoiding internal crack of slab.The total reduction amount was composed of natural thermal shrinkage and actual reduction amount depending on critical strain.For low carbon steel with slab dimension of(950 - 1 950) mm×170 mm,the solid fraction range in soft reduction region was recommended from 0.4 to 0.8,the total reduction amount was 2.0 -2.8 mm,and the optimized reduction rate was 0.4 - 1.2 mm/min,respectively.Furthermore,a dynamic soft reduction system in continuous slab casting, Visual Cast-Dynamic,has been developed by multithreading method.It demonstrated that the dynamic soft reduction model in this study was correct with the ability of online control.

Soft Handover Probability Determination Considering New Direction of Motion

This paper presents prior determination of soft handover probability considering new direction of motion of mobile station (MS) coinciding with gravitation point of cells. Our simulation results for 3-cell scenario and considered new direction of MS motion can be potentially used as advance input to soft handover algorithms to minimize number of handovers.

On Soft Pre-Rough Approximation Space with Applications in Decision Making

A soft,rough set model is a distinctive mathematical model that can be used to relate a variety of real-life data.In the present work,we introduce new concepts of rough set based on soft pre-lower and soft pre-upper approximation space.These concepts are soft pre-rough equality,soft pre-rough inclusion,soft pre-rough belonging,soft predefinability,soft pre-internal lower,and soft pre-external lower.We study the properties of these concepts.Finally,we use the soft pre-rough approximation to illustrate the importance of our method in decision-making for Chikungunya medical illnesses.In reality,the impact factors of Chikungunya’s medical infection were determined.Moreover,we develop two new algorithms to address Chikungunya virus issues.Our proposed approach is sensible and effective.

A New Approach to Vague Soft Bi-Topological Spaces

Fuzzy soft topology considers only membership value.It has nothing to do with the non-membership value.So an extension was needed in this direction.Vague soft topology addresses bothmembership and non-membership values simultaneously.Sometimes vague soft topology(single structure)is unable to address some complex structures.So an extension to vague soft bi-topology(double structure)was needed in this direction.To make this situation more meaningful,a new concept of vague soft bi-topological space is introduced and its structural characteristics are attempted with a new definition.In this article,new concept of vague soft bi-topological space(VSBTS)is initiated and its structural behaviors are attempted.This approach is based on generalized vague soft open sets,known as vague softβopen sets.An ample of examples are given to understand the structures.For the non-validity of some results,counter examples are provided to pay the price.Pair-wise vague softβopen and pair-wise vague softβclose sets are alsoaddressedwith examples in(VSBTS).Vague soft separation axioms are initiatedin(VSBTS)concerning soft points of the space.Other separation axioms are also addressed relative to soft points of the space.Vague soft bi-topological properties are studied with the application of vague softβopen sets with respect to soft points of the spaces.The characterization of vague softβclose as well as vague softβopen sets,characteristics of Bolzano Weirstrass property,vague soft compactness and its marriage with sequences,interconnection between sequential compactness and countable compactness in(VSBTS)with respect to softβopen sets are addressed.

Possibility Fuzzy Soft Expert Set

In this paper we introduce the concept of possibility fuzzy soft expert set .We also define its basic operations, namely complement, union, intersection, AND and OR, and study some of their properties. Finally, we give an application of this theory in solving a decision making problem.

A New Attempt to Neutrosophic Soft Bi-Topological Spaces

In this article,new generalized neutrosophic soft∗b open set is introduced in neutrosophic soft bi-topological structurers(NSBTS)concerning soft points of the space.This new set is produced by making the marriage of soft semi-open set with soft pre-open set in neutrosophic soft topological structure.An ample of results are investigated in NSBTS on the basis of this new neutrosophic soft∗b open set.Proper examples are settled for justification of these results.The non-validity of some results is vindicated with examples.