Automated postoperative blood pressure control

It is very important to maintain the level of mean arterial pressure (MAP) . The MAP control is applied in many clinical situations ,including limiting bleeding during cardiac surgery and promoting healing for patient’s post-surgery. This paper presents a fuzzy controller- based multiple-model adaptive control system for postoperative blood pressure management . Multiple-model adaptive control (MMAC) algorithm is used to identify the patient model ,and it is a feasible system identification method even in the presence of large noise. Fuzzy control (FC) method is used to design controller bank. Each fuzzy controller in the controller bank is in fact a nonlinear proportional- integral (PI) controller ,whose proportional gain and integral gain are adjusted continuously according to error and rate of change of error of the plant output , resulting in better dynamic and stable control performance than the regular PI controller , especially when a nonlinear process is involved. For demonstration , a nonlinear , pulsatile-flow patient model is used for simulation ,and the results show that the adaptive control system can effectively handle the changes in patient’s dynamics and provide satisfactory performance in regulation of blood pressure of hypertension patients.     

Application of TOPSIS Method in Support of Decisions Made in Staff Management Issues

Evaluation model was proposed which refers to fuzzy formalism of the personnel management issues taking account their specific characteristics. Application of TOPSIS （technique for order Performance by similarity to ideal solution） method for evaluation and regulation of alternatives based on hierarchically structured criteria of qualitative character by multiple experts to intellectually support decisions made in staff management issues is reviewed in the article. Candidate selection experiment based on criteria system formed using TOPSIS method for evaluation of candidates during solution of hiring problems reviewed and obtained results were compared with results obtained using Matlab program package.     

Predictive functional control based on fuzzy T-S model for HVAC systems temperature control

In heating, ventilating and air-conditioning （HVAC） systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno （T-S） fuzzy model was proposed to control HVAC systems. The T-S fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from T-S fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc.     

The order structure of fuzzy numbers based on the level characteristics and its application to optimization problems

Ranking and comparing fuzzy numbers is an important part in many fuzzy optimization problems such as intelligent control and manufacturing system production line scheduling with uncertainty environments. In this paper, based on the level characteristic function and α-average of level cut sets of fuzzy number, we establish the IMα-metric method for measuring fuzzy number as a whole, and introduce the concept of IDα-difFerence that describes the reliability of IMα-metric value. Further, the basic properties and the separability of IMα-metric and IDα-difference are discussed. Finally, we give a mathematical model to solve fuzzy optimization problems by means of IMα-metric.     

Analysis of the virtual enterprise partner selection based on multi-agent system

Today, virtual enterprise is regarded as the most competitive management model of enterprises that faces the resource of the globe. This paper proposed an instructor of remote manufacturing system supporting dynamic alliance for virtual enterprises with the multi-agent technology to solve the problem of partner enterprise selection. Grounding on the virtual enterprise＇s cooperation framework, a model was given and in which we analyze the collaboration relation among different agents. The negotiation model will reduce the time and improve the efficiency of negotiation, so the appropriate partner can be selected in a short time.     

Automated postoperative blood pressure control

It is very important to maintain the level of mean arterial pressure （MAP）. The MAP control is applied in many clinical situations, including limiting bleeding during cardiac surgery and promoting healing for patient＇ s post-surgery. This paper presents a fuzzy controller-based multiple-model adaptive control system for postoperative blood pressure management. Multiple-model adaptive control （MMAC） algorithm is used to identify the patient model, and it is a feasible system identification method even in the presence of large noise. Fuzzy control （FC） method is used to design controller bank. Each fuzzy controller in the controller bank is in fact a nonlinear proportional-integral （PI） controller,whose proportional gain and integral gain are adjusted continuously according to error and rate of change of error of the plant output, resulting in better dynamic and stable control performance than the regular PI controller, especially when a nonlinear process is involved. For demonstration, a nonlinear, pulsatile-flow patient model is used for simulation, and the results show that the adaptive control system can effectively handle the changes in patient＇s dynamics and provide satisfactory performance in regulation of blood pressure of hypertension patients.     

Human control model in teleoperation rendezvous

This paper proposes a human control model in teleoperation rendezvous on the basis of human information processing （perception, judgment, inference, decision and response）. A predictive display model is introduced to provide the human operator with predictive information of relative motion. By use of this information, the longitudinal and lateral control models for the operator are presented based on phase plane control method and fuzzy control method, and human handling qualities are analyzed. The integration of these two models represents the human control model. Such a model can be used to simulate the control process of the human operator, which teleoperates the rendezvous with the aid of predictive display. Experiments with human in the loop are carried out based on the semi-Physical simulation system to verify this human control model. The results show that this human control model can emulate human operators＇ performance effectively, and provides an excellent way for the analysis, evaluation and design of the teleoperation rendezvous system.     

An affective model based on fuzzy theory

A new affective model is presented, developed by fuzzy mathematics based on the differential emotions theory, in the model, human emotion and personality trait we defined is presented with fuzzy sets, and an emotion change equation to depict the change of human emotion. The equation includes the factors that affect human emotion, such as stimulus, personality trait and the fading of emotion. The paper develops a model that can simulate the human emotion better, and offers a new thinking for the research of artificial emotion.     

新的基于鼠标行为的持续身份认证方法

With the rapid development of Internet technologies, security issues have always been the hot topics. Continuous identity authentication based on mouse behavior plays a crucial role in protecting computer systems, but there are still some problems to be solved. Aiming at the problems of low authentication accuracy and long authentication latency in mouse behavior authentication method, a new continuous identity authentication method based on mouse behavior was proposed. The method divided the user’s mouse event sequence into corresponding mouse behaviors according to different types, and mined mouse behavior characteristics from various aspects based on mouse behaviors. Thereby, the differences in mouse behavior of different users can be better represented, and the authentication accuracy can be improved. Besides, the importance of mouse behavior features was obtained by the ReliefF algorithm, and on this basis, the irrelevant or redundant features of mouse behavior were removed by combining the neighborhood rough set to reduce model complexity and modeling time. Moreover binary classification was adopted. The algorithm performed the training of the authentication model. During identity authentication, the authentication model was used to obtain a classification score based on the mouse behavior collected each time, and then the user’s trust value was updated in combination with the trust model. When the user’s trust value fell below the threshold of the trust model, it might be judged as illegal user. The authentication effect of the proposed method was simulated on the Balabit and DFL datasets. The results show that, compared with the methods in other literatures, this method not only improves the authentication accuracy and reduces the authentication latency, but also has a certain robustness to the illegal intrusion of external users. © 2022, Beijing Xintong Media Co., Ltd.. All rights reserved.     

A novel intelligent verification platform based on a structured analysis model

An intelligent verification platform based on a structured analysis model is presented.Using an abstract model mechanism with specific signal interfaces for user callback,the unified structured analysis data,shared by the electronic system level design,functional verification,and performance evaluation,enables efficient management review,auto-generation of code,and modeling in the transaction level.We introduce the class tree,flow parameter diagram,structured flow chart,and event-driven finite state machine as structured analysis models.As a sand table to carry maps from different perspectives and levels via an engine,this highly reusable platform provides the mapping topology to search for unintended consequences and the graph theory for comprehensive coverage and smart test cases.Experimental results show that the engine generates efficient test sequences,with a sharp increase in coverage for the same vector count compared with a random test.     

A Customized Framework to Recompress Massive Internet Images

Recently,device storage capacity and transmission bandwidth requirements are facing a heavy burden on account of massive internet images.Generally,to improve user experience and save costs as much as possible,a lot of internet applications always focus on how to achieve appropriate image recompression.In this paper,we propose a novel framework to efficiently customize image recompression according to a variety of applications.First of all,we evaluate the input image’s compression level and predict an initial compression level which is very close to the final output of our system using a prior learnt from massive images.Then,we iteratively recompress the input image to different levels and measure the perceptual similarity between the input image and the new result by a block-based coding quality method.According to the output of the quality assessment method,we can update the target compression level,or switch to the subjective evaluation,or return the final recompression result in our system pipeline control.We organize subjective evaluations based on different applications and obtain corresponding assessment report.At last,based on the assessment report,we set up a series of appropriate parameters for customizing image recompression.Moreover,our new framework has been successfully applied to many commercial applications,such as web portals,e-commerce,online game,and so on.     

一类基于数据的解释性模糊建模方法的研究

An approach to identify interpretable fuzzy models from data is proposed. Interpretability, which is one of the most important features of fuzzy models, is analyzed first. The number of fuzzy rules is determined by fuzzy cluster validity indices. A modified fuzzy clustering algorithm,combined with the least square method, is used to identify the initial fuzzy model. An orthogonal least square algorithm and a method of merging similar fuzzy sets are then used to remove the redundancy of the fuzzy model and improve its interpretability. Next, in order to attain high accuracy, while preserving interpretability, a constrained Levenberg-Marquardt method is utilized to optimize the precision of the fuzzy model. Finally, the proposed approach is applied to a PH neutralization process, and the results show its validity.     

A new approach of fuzzy comprehensive evaluation on rough set

This paper is devoted to some studies on approaches of fuzzy comprehensive estimation of an information system. The redundant or insignificant attributes in fuzzy comprehensive evaluation data sets are removed to reduce knowledge expression of the system based on rough set. The significance of condition attributes is used for setting up a weight distribution of fuzzy evaluation so that some undesirable influences of the weights subjectively defined are eliminated. The precision of the comprehensive evaluation of a system reduced is realized by an approach of fuzzy comprehensive estimation on rough set. The feasibility of fuzzy comprehensive estimation proposed is shown by some of examples of planting rubber here.     

CC与SSE-CMM结合的信息安全评估方法

The information security evaluation is an important part of information field. It is a general method to execute evaluation to the information security products under the instruction of Common Criteria (CC).A new method of information security evaluation, based on the combination of CC and Systems Security Engineering Capability Maturity Model (SSE-CMM),has been proposed in the paper. The basic idea of this method is using the reference of the security system engineer. Based on the experiment of a Target of Evaluation (TOE)in CC, the evaluation result of security assurance by this new method is proved to be more accurate, more comprehensive and more acceptable.     

Surrogate model-assisted interactive genetic algorithms with individual’s fuzzy and stochastic fitness

We propose a surrogate model-assisted algorithm by using a directed fuzzy graph to extract a user’s cognition on evaluated individuals in order to alleviate user fatigue in interactive genetic algorithms with an individual’s fuzzy and stochastic fitness. We firstly present an approach to construct a directed fuzzy graph of an evolutionary population according to individuals’ dominance relations, cut-set levels and interval dominance probabilities, and then calculate an individual’s crisp fitness based on the out-degree and in-degree of the fuzzy graph. The approach to obtain training data is achieved using the fuzzy entropy of the evolutionary system to guarantee the credibilities of the samples which are used to train the surrogate model. We adopt a support vector regression machine as the surrogate model and train it using the sampled individuals and their crisp fitness. Then the surrogate model is optimized using the traditional genetic algorithm for some generations, and some good individuals are submitted to the user for the subsequent evolutions so as to guide and accelerate the evolution. Finally, we quantitatively analyze the performance of the presented algorithm in alleviating user fatigue and increasing more opportunities to find the satisfactory individuals, and also apply our algorithm to a fashion evolutionary design system to demonstrate its efficiency.     

空间数据库磁盘管理器的研究与设计

The disk manager of spatial database provides uniform storage and management for spatial data and attribute data in GIS applications.To investigate it will have effect on creating storage manager of spatial database and SDBMS with lore‘‘s property right for our country.This paper investigates and analyzes the Oracele‘‘s spatial data model,and on the basis of it,it puts forward a new method about disk storage of spatial data and has it designed.     

Decentralized Networked Control System Design Using Takagi-Sugeno (TS) Fuzzy Approach

This paper proposes a new method for control of continuous large-scale systems where the measures and control functions are distributed on calculating members which can be shared with other applications and connected to digital network communications.At first, the nonlinear large-scale system is described by a Takagi-Sugeno(TS) fuzzy model. After that, by using a fuzzy LyapunovKrasovskii functional, sufficient conditions of asymptotic stability of the behavior of the decentralized networked control system(DNCS),are developed in terms of linear matrix inequalities(LMIs). Finally, to illustrate the proposed approach, a numerical example and simulation results are presented.     

Contourlet HMT model with directional feature

According to Shanno’s information theory,the directional feature of texture is defined as the value of directional variable when an image signal attains a singularity of random distribution.In terms of this definition,we calculate the texture’s directional features using Tamura’s method and study the directional probability distribution of Contourlet coefficients.Then we find that the directional features tend to be conveyed across parent and child subbands.Based on this conclusion,we establish a novel probability distribution model of hidden direction variables under the condition of hidden state variable’s distribution,named Contourlet HMT model with directional feature.The structure and training method of the model are presented as well.Moreover,an unsupervised context-based image segmentation algorithm is proposed on the basis of the proposed model.Its effectiveness is verified via extensive experiments carried out on several synthesized images and remote sensing images.     

A provable secure fuzzy identity based signature scheme

To use biometrics identities in an identity based encryption system,Sahai and Waters first introduced the notion of fuzzy identity based encryption(FIBE) in 2005.Yang et al.extended it to digital signature and introduced the concept of fuzzy identity based signature(FIBS) in 2008,and constructed an FIBS scheme based on Sahai and Waters’s FIBE scheme.In this paper,we further formalize the notion and security model of FIBS scheme and propose a new construction of FIBS scheme based on bilinear pairing.The proposed scheme not only provides shorter public parameters,private key and signature,but also have useful structures which result in more efficient verification than that of Yang et al.’s FIBS scheme.The proposed FIBS scheme is proved to be existentially unforgeable under a chosen message attack and selective fuzzy identity attack in the random oracle model under the discrete logarithm assumption.