Visual Evaluation of Matching Degree between Fisherman Hat and Female Face

By the means of visual evaluation,the matching degree of nine types of fisherman hats and seven face shapes was studied.The characteristics of hats and faces were parameterized,and the images in which seven kinds of faces wore different fisherman hats were processed by Photoshop gray levels.Through a random questionnaire,descriptive analysis,and mean and dispersion analysis,the recommendation table of fisherman hats for different female faces was obtained,and the highly preferred and matching degree types of fisherman hats were obtained.It not only provides reference for virtual hat tests,but also gives references for parameterized hat designs from the collocation aesthetic viewpoint.

Study on the Matching Degree between Essential Drug List and the Provisions on Drug Coverage in Tertiary Hospitals

Objective To study the relationship between essential drug list and the provisions on the drug coverage in tertiary hospitals,and put forward the corresponding countermeasures and suggestions for the adjustment of essential drug list and the improvement of relevant policies.Methods Expert consultation and statistical methods were used to classify the drugs in the list of essential drugs according to different diseases.Besides,the matching degree of basic drug allocation and prescription policy was analyzed.Results and Conclusion Among the 685 drugs in the national essential drug list of 2018 edition,453 drugs were used to treat minor illness,accounting for 66.1%of the total number of essential drug list.232 drugs were for serious illness or fatal illness,accounting for 33.9%of the total number of essential drug list.The current essential drug list does not match the national requirements for drug plan coverage in tertiary hospitals,which needs further adjustment and improvement.

Reasoning Efficiency Research of Expert System for Biomass Soft-Sensor Modeling in Fermentation Process

An expert system for biomass soft-sensor hybrid modeling in fermentation process was decribed in this paper.A production rules representation based on database was presented.The definitions of production rules for biomass soft-sensor hybrid modeling knowledge were proposed.A knowledge base with layered structure was introduced.A breadth-first reasoning approach based on match degree(BFMD) was developed.The definition and calculation method of match degree were illustrated.Compared with the depth-first reasoning approach based on exhaustive method(DFEM),the BFMD needs fewer introduced variables.This expert system could reduce the reasoning steps effectively,and advance reasoning efficiency.Tests shows that reasoning efficiency of the expert system using BFMD in the knowledge base with layered structure is improved 12.9% averagely,compared with using DFEM in the knowledge base with ranking structure.

A novel fault section locating method based on distance matching degree in distribution network

Fault section location of a single-phase grounding fault is affected by the neutral grounding mode of the system, transition resistance, and the blind zone. A fault section locating method based on an amplitude feature and an intelligent distance algorithm is proposed to eliminate the influence of the above factors. By analyzing and comparing the amplitude characteristics of the zero-sequence current transient components at both ends of the healthy section and the faulty section, a distance algorithm with strong abnormal data immune capability is introduced in this paper. The matching degree of the amplitude characteristics at both ends of the feeder section are used as the criterion and by comparing with the set threshold, the faulty section is effectively determined. Finally, simulations using Matlab/Simulink and PSCAD/EMTDC show that the proposed section locating method can locate the faulty section accurately, and is not affected by grounding mode, grounding resistance, or the blind zone.

Approach of fault diagnosis based on similarity degree matching distance function

A new diagnosis method based on the similarity degree matching distance function is proposed.This method solves the problem that the traditional fault diagnosis methods based on transition system model cannot deal with the"special state"which cannot match the target states completely.For evaluating the relationship between the observation and the target states,this paper first defines a new distance function based on the viewpoint of energy to measure the distance between two attribute values.After that,all the distances of the attributes in the state vector are used to synthesize the distance between two states.For calculating the similarity degree between two states,a trend evaluation method is developed.It analyzes the main direction of the trend of the state transfer according to the distances between the observation and each target state and their historical records.Applying the diagnosis method to a primary power subsystem of a satellite,the simulation result shows that it is effective.

A natural language user interface for fuzzy scope queries

This paper presents a two-agent framework to build a natural langua g e query interface for IC information system, focusing more on scope queries in a single English sentence. The first agent, parsing agent, syntactically p rocesses and semantically interprets natural language sentence to construct a fu zzy structured query language (SQL) statement. The second agent, defuzzif ying agent, defuzzifies the imprecise part of the fuzzy SQL statement into its e quivalent executable precise SQL statement based on fuzzy rules. The first agent can also actively ask the user some necessary questions when it manages to disa mbiguate the vague retrieval requirements. The adaptive defuzzification approach employed in the defuzzifying agent is discussed in detail. A prototype interface has been implemented to demonstrate the effectiveness.

Preserving the Efficiency and Quality of Contributed Data in MCS via User and Task Profiling

Mobile crowdsensing is a new paradigm with powerful performance for data collection through a large number of smart devices.It is essential to obtain high quality data in crowdsensing campaign.Most of the existing specs ignore users’diversity,focus on solving complicated optimization problem,and consider devices as instances of intelligent software agents which can make reasonable choices on behalf of users.Thus,the efficiency and quality of contributed data cannot be preserved simultaneously.In this paper,we propose a new scheme for improving the quality of contributed data,which recommends tasks to users based on calculated score that jointly take the matching degree and task’s rationality into account.We design QIM as Quality Investigation Mechanism for profiling tasks’rationality and matching degree,which draw on support vector machine(SVM)to learn it from historical data.Our mechanism is validated against the examination in experiment,and the evaluation demonstrates that the QIM mechanism achieves a better performance while improving efficiency E and quality Q at the same time compared with benchmarks.

Improved Region Energy Based Image Fusion Rule for Multi-focus Image Fusion

In this paper,we propose a novel improved region energy based image fusion rule.The original images are firstly decomposed by using the lifting scheme of wavelet transform into four sub-bands:LL,LH,HL,HH,by studying principles and characteristics of the wavelet subbands,and we put emphasis on the high frequency subbands.Thus HH,HL,LH sub-bands,which represent three direction of high frequency details,are weighted by different size of three direction Gaussian kernel,then the energy based image fusion rule is applied with a optional size of window,thus the activity level of high frequency subbands are obtained,followed by a local region matching degree in the corresponding direction and resolution,an activity level of low frequency subband is calculated,then perform consistency verification on the selected wavelet coefficients,by doing the inverse wavelet transform the fused image is obtained.The performance of the proposed novel image fusion scheme is conducted and compared with a few existing image fusion algorithm,the experimental results show that the proposed method is an effective multi-focus image fusion algorithm.

A REAL-TIME C-V CLUSTERING ALGORITHM FOR WEB-MINING

In this letter, a real-time C-V (Characteristic-Vector) clustering algorithm is put forth to treat with vast action data which are dynamically collected from web site. The algorithm cites the concept of C-V to denote characteristic, synchronously it adopts two-value [0,1]input and self-definition vigilance parameter to design clustering-architecture. Vector Degree of Matching (VDM) plays a key role in the clustering algorithm, which determines the magnitude of typical characteristic. Making use of stability analysis, the classifications are confirmed to have reliably hierarchical structure when vigilance parameter shifts from 0.1 to 0.99. This non-linear relation between vigilance parameter and classification upper limit helps mining out representative classifications from net-users according to the actual web resource, then administering system can map them to web resource space to implement the intelligent configuration effectually and rapidly.

Thermodynamic Evaluation of Transcritical CO_(2) Heat Pump Considering Temperature Matching under the Constraint of Heat Transfer Pinch Point

The non-linear temperature glide in the supercritical CO_(2) cooling process makes the heat transfer pinch point of heat exchanger show multiplicity,like size,location distribution and quantity,which makes the thermodynamic performance of the CO_(2) transcritical cycle more complex and eventually affects the evaluation of the optimal operating state of the system.Based on the second law of thermodynamics and the constraints of heat transfer pinch,a thermodynamic evaluation method of CO_(2) transcritical heat pump system was proposed according to the degree of temperature matching.The influence mechanism of multi-characteristic change of heat transfer pinch point on temperature matching degree and the effect of temperature matching degree on thermodynamic performance of CO_(2) transcritical heat pump system were discussed.The relationship between temperature matching degree,COP and exergy efficiency of the system was analyzed.It is considered that the change of temperature matching index value can clearly characterize the change trends of COP and exergy efficiency.That is,the smaller the temperature matching degree is,the closer the temperature distribution of heat transfer fluids on both sides of the heat exchanger is to Lorenz cycle,and the greater the COP and exergy efficiency are.Furthermore,by monitoring the outlet temperature of the CO_(2) cooler,which has an essential relationship with the temperature matching degree during the heat exchange process,the deviation between actual and optimal working condition can be judged online,which is beneficial to real-time evaluation of the working state of the system.

EFFICIENT SUBSPACE CLUSTERING FOR HIGHER DIMENSIONAL DATA USING FUZZY ENTROPY

In this paper we propose a novel method for identifying relevant subspaces using fuzzy entropy and perform clustering. This measure discriminates the real distribution better by using membership functions for measuring class match degrees. Hence the fuzzy entropy reflects more information in the actual distribution of patterns in the subspaces. We use a heuristic procedure based on the silhouette criterion to find the number of clusters. The presented theories and algorithms are evaluated through experiments on a collection of benchmark data sets. Empirical results have shown its favorable performance in comparison with several other clustering algorithms.

The Reasoning Mechanism Combining Fuzziness and Randomness

This article introduces the developing process, the main idea and the method of FBEST (Fuzzy set theory Based Expert System Tool) reasoning mechanism.The method reasonably solves the problem of various inputting ways and proposition reasoning which possesses both fuzziness and randomness in ES.

Injection performance evaluation for SSRF storage ring

The injection performance of the storage ring is one of the most important factors to consider at a synchrotron radiation facility, especially in the top-up mode. To evaluate the injection performance of the storage ring at the Shanghai Synchrotron Radiation Facility, we have built a bunch-by-bunch position measuring system based on an oscilloscope Input/Output Controller. Accurate assessment of energy mismatching, distribution of residual oscillation, and angle error of injection kickers can be achieved by this system.

Linguistic dynamic systems based on computing with words and their stabilities

Linguistic dynamic systems （LDS） are the systems based on computing with words （CW） instead of computing with numbers or symbols. In this paper, LDS are divided into two types： type-I LDS being converted from conventional dynamical systems （CDS） by using extension principle and type-II LDS by using fuzzy logic rules. For type-I LDS, the method of endograph is provided to discuss the stabilities of type-I LDS and two cases of stabilities of logistic mappings： one is the states being abstracted and the other is parameters also being abstracted. For type-Ⅱ LDS, the method of degree of match is used to discuss the dynamical behavior of arbitrary initial words under fuzzy rule.