基于论据系统的带权定性概率推理机

定性概率推理是不确定性推理领域的一种重要方法。将定性概率推理的论据系统方法和抽象系统方法二者合而为一,在定性概率推理机(QPR)的基础上提出基于论据系统的带权定性概率推理机(WQPR)。首先扩展了带权定性概率网的定义,讨论了带权定性影响的对称性;其次将带权定性概率推理融入到论据系统中,提出WQPR推理系统,相比QPR能够在更精确的尺度进行不确定性推理,并证明了系统的正确性与完备性。

APPLICATION OF GREY SYSTEM THEORY TO PROCESSING OF MEASURING DATA IN REVERSE ENGINEERING

The processing of measuri ng data plays an important role in reverse engineering. Based on grey system the ory, we first propose some methods to the processing of measuring data in revers e engineering. The measured data usually have some abnormalities. When the abnor mal data are eliminated by filtering, blanks are created. The grey generation an d GM(1,1) are used to create new data for these blanks. For the uneven data sequ en ce created by measuring error, the mean generation is used to smooth it and then the stepwise and smooth generations are used to improve the data sequence.

Application of data fusion method to fault diagnosis of nuclear power plant

The work condition of nuclear power plant (NPP) is very bad, which makes ithas faults easily. In order to diagnose (he faults real time, the fusion diagnosis system is built.The data fusion fault diagnosis system adopts data fusion method and divides the fault diagnosisinto three levels, which are data fusion level, feature level and decision level. The feature leveluses three parallel neural networks whose structures are the same. The purpose of using neuralnetworks is mainly to get basic probability assignment ( BPA) of D-S evidence theory, and the neuralnetworks in feature level are used for local diagnosis. D-S evidence theory is adopted to integratethe local diagnosis results in decision level. The reactor coolant system is the study object andwe choose 2# steam generator U-tubes break of the reactor coolant system as a diagnostic example.The experiments prove that the fusion diagnosis system can satisfy the fault diagnosis requirementof complicated system, and verify that the fusion fault diagnosis system can realize the faultdiagnosis of NPP on line timely.

Evaluation of Training Program for New Nurses to Enhance Caring Behavior

This research was aimed to evaluate the training program enhancing caring behaviors of new nurses by Kirkpatrick＇s four level for evaluation model： reaction, learning, behavior, and result of the program. The participants were new nurses, preceptors of new nurses, administrators, patients and members of the patients＇ family cared by new nurses. The research instruments were： （1） five questionnaires toward program suitability, knowledge, attitude, caring expression, and result to organization. The mean, standard deviation and dependent sample t-test were used for data analysis; （2） guidelines for focus group discussion and semi-structural questionnaire analyzed by content analysis. The study revealed that： （1） the mean of suitability was at the very high level （X = 4.49, SD. = .30）; （2） the knowledge and attitude after training were significantly higher than before training at .000 level, [t =-21.65, p = .000 and t = -19.30, p = .000）; {3} caring behavior after training was significantly higher than before training at the .000 level; and {4} the result of the program was at the high level { X = 4.25, SD. = .17}, related to the result of semi-structured interview and focus group discussion. These evaluation research finding suggested that administrators can use for improving the preparation of any project and apply to evaluate other training programs, developing human resource system.

Review of pre-processing technologies for ice cores

High-resolution ice core records covering long time spans enable reconstruction of the past climatic and environmental conditions allowing the investigation of the earth system's evolution. Preprocessing of ice cores has direct impacts on the data quality control for further analysis since the conventional ice core processing is time-consuming, produces qualitative data, leads to ice mass loss, and leads to risks of potential secondary pollution. However, over the past several decades, preprocessing of ice cores has received less attention than the improvement of ice drilling, the analytical methodology of various indices, and the researches on the climatic and environmental significance of ice core records. Therefore, this papers reviews the development of the processing for ice cores including framework, design as well as materials, analyzes the technical advantages and disadvantages of the different systems. In the past, continuous flowanalysis(CFA) has been successfully applied to process the polar ice cores. However, it is not suitable for ice cores outside polar region because of high level of particles, the memory effect between samples, and the filtration before injection. Ice core processing is a subtle and professional operation due to the fragility of the nonmetallic materials and the random distribution of particles and air bubbles in ice cores, which aggravates uncertainty in the measurements. The future developments of CFA are discussed in preprocessing, memory effect, challenge for brittle ice, coupling with real-time analysis and optimization of CFA in the field. Furthermore, non-polluting cutters with many different configurations could be designed to cut and scrape in multiple directions and to separate inner and outer portions of the core. This system also needs to be coupled with streamlined operation of packaging, coding, and stacking that can be implemented at high resolution and rate, avoiding manual intervention. At the same time, information of the longitudinal sections could be scanned andidentified, and then classified to obtain quantitative data. In addition, irregular ice volume and weight can also be obtained accurately. These improvements are recorded automatically via user-friendly interfaces. These innovations may be applied to other paleomedias with similar features and needs.

DISCUSSION ON AVERAGE GENERATION OF TWODIMENSIONAL DATA SEQUENCE IN GREY SYSTEM THEORY

An unequal time interval sequence or a sequence with blanks is usually completed with average generation in grey system theory. This paper discovers that there exists obvious errors when using average generation to generate internal points of non-consecutive neighbours. The average generation and the preference generation of the sequence are discussed, the concave and convex properties show the status of local sequence and propose a new idea for using the status to build up the criteria of choosing generation coefficient. Compared with the general average method of the one-dimensional data sequence, the two-dimensional data sequence is defined and its average generation is discussed, and the coefficient decision method for the preference generation is presented.

Neural Network Applications in Petroleum Exploration Based on Statistical Space Mapping

In this paper, we propose the statistical space mapping thought and classify the seismic body space throughlithology space clustering combining to the actual application background of petroleum exploration. A new method ofstratum petroleum recognition based on neural network was set up through the foundation of the data mapping relationbetween log and seismic body. It can break a new path for recognition petroleum using both log and seismic data. Andthis method has been validated in the practical data analysis in Liaohe oil field.

Full Diversity Reception Based on Dempster-Shafer Theory for Network Coding with Multiple-Antennas Relay

In this paper,a two-way relay system which achieves bi-directional communication via a multiple-antenna relay in two time slots is studied.In the multiple access(MA) phase,the novel receive schemes based on Dempster-Shafer(D-S) evidence theory are proposed at the relay node.Instead of traditional linear detection,the first proposed MIMO-DS NC scheme adopts D-S evidence theory to detect the signals of each source node before mapping them into network-coded signal.Moreover,different from traditional physical-layer network coding(PNC) based on virtual MIMO model,the further proposed MIMO-DS PNC comes from the vector space perspective and combines PNC mapping with D-S theory to obtain network-coded signal without estimating each source node signal.D-S theory can appropriately characterize uncertainty and make full use of multiple evidence source information by Dempster's combination rule to obtain reliable decisions.In the broadcast(BC) phase,the space-time coding(STC) and antenna selection(AS) schemes are adopted to achieve transmit diversity.Simulation results reveal that the STC and AS schemes both achieve full transmit diversity in the BC phase and the proposed MIMO-DS NC/PNC schemes obtain better end-to-end BER performance and throughputs compared with traditional schemes with a little complexity increasing and no matter which scheme is adopted in the BC phase,MIMO-DS PNC always achieves full end-to-end diversity gain as MIMO-ML NC but with a lower complexity and its throughput approaches the throughput of MIMO-ML NC in high SNR regime.

A Digital Evidence Fusion Method in Network Forensics Systems with Dempster-Shafer Theory

Network intrusion forensics is an important extension to present security infrastructure,and is becoming the focus of forensics research field.However,comparison with sophisticated multi-stage attacks and volume of sensor data,current practices in network forensic analysis are to manually examine,an error prone,labor-intensive and time consuming process.To solve these problems,in this paper we propose a digital evidence fusion method for network forensics with Dempster-Shafer theory that can detect efficiently computer crime in networked environments,and fuse digital evidence from different sources such as hosts and sub-networks automatically.In the end,we evaluate the method on well-known KDD Cup1999 dataset.The results prove our method is very effective for real-time network forensics,and can provide comprehensible messages for a forensic investigators.

AN INTRUSION DETECTION SYSTEM BASED ON EVIDENCE THEORY AND ROUGH SET THEORY

In this paper,we propose a novel Intrusion Detection System (IDS) architecture utilizing both the evidence theory and Rough Set Theory (RST). Evidence theory is an effective tool in dealing with uncertainty question. It relies on the expert knowledge to provide evidences,needing the evidences to be independent,and this make it difficult in application. To solve this problem,a hybrid system of rough sets and evidence theory is proposed. Firstly,simplification are made based on Variable Precision Rough Set (VPRS) conditional entropy. Thus,the Basic Belief Assignment (BBA) for all evidences can be calculated. Secondly,Dempster’s rule of combination is used,and a decision-making is given. In the proposed approach,the difficulties in acquiring the BBAs are solved,the correlativity among the evidences is reduced and the subjectivity of evidences is weakened. An illustrative example in an intrusion detection shows that the two theories combination is feasible and effective.

Properties of A=7-9 Drip-Line Nuclei in RMF Theory

The relativistic mean-field （RMF） theory is used to calculate the properties of A =7-9 drip-line nuclei ^7Li, ^7;9Be, ^8;9B, and ^9C. Systematic deviations between experimental and theoretical binding energies are found. Possible reasons of these systematic deviations are discussed in terms of pairing energy. The root-mean-square （rms） radii of matter distributions for these nuclei agree with the experimental data quite well. The one-proton halo structure in ^8B is reproduced well, and the two-proton halo in ^9C is predicted. The calculations show that the RMF theory is valid in studying the properties of light drip-line nuclei.

Theoretical predictions of viscosity of methane under confined conditions

Density functional theory has been confirmed as a reliable approach in the descriptions of inhomogeneous fluids.By integrating the density functional theory into the revised local average density model, a theoretical approach is constructed to investigate the local shear viscosity in the confined conditions. In the density functional theory,the weighted density approximation for attractive part and the modified fundamental measure theory for repulsion contribution are adopted to accurately describe the inhomogeneous systems. By comparing with simulation data, the theoretical model is tested. In this work, the shear viscosities of methane are calculated in different external fields(on a hard wall, a solvophobic wall and in slit pores with different widths). In addition, the effects of temperature on the local density and viscosity are also considered. It shows that the effect of temperature on the shear viscosity is more obvious on solid surfaces. The calculation provides an approach to determine the viscosity under confined conditions, which is extremely significant in real industrial applications.

不完全信息条件下的非单调推理技术集成决策框架研究

非单调推理技术在决策支持领域的应用,主要困难在于理论本身的容错性并不满足决策制定过程对决策结果的要求,对此,文章试图通过将非单调逻辑形式和信念修正工具进行集成来解决这一应用问题.基于决策流程要求,在设计和改进支持工具的基础上,给出了一个基于非单调技术的普遍集成决策框架,设定相应的运行机制,解决非单调推理过程中不可避免的不动点选择问题,且为不完全信息条件下的决策行为提供有效的支持.

Injections of ginkgo in the treatment of cerebral infarction: a systematic review and network Meta-analysis

OBJECTIVE： To assess the clinical effectiveness and safety of injections of ginkgo （GI） combined with Western Medicine （WM） for cerebral infarction （C/）. METHODS; Randomized controlled trials （RCTs） of C/treated by GI were searched in China National Knowledge Infrastructure Database, Wanfang, China Science and Technology Journal Database, Web of Science, Cochrane library, Embase, PubMed and Chinese Biomedical Literature Database, with the publication data no later than April, 2016. The Co- chrane risk of bias method was used to evaluate the methodological quality of the RCTs. The data were analyzed by Review Manager 5.3, Stata 13.0, and WinBUGS 14 software.RESULTS： Totally 37 RCTs involving 4330 patients were included. By direct comparison, the results of GI group were significantly superior to the routine WM group in the total effective rates [OR = 3.61, 95% CI （2.93, 4.44）, P 〈 0.0001], the neural function defect score （NFDS） [MD = - 4.39, 95% CI （- 5.47, - 3.32）, P 〈 0.0001]. Network Meta-analysis （NMA） results showed that, between S GIs in efficacy, the difference comparing ginaton injections （GbE） to ginkgo-dipyidamolum injections （GD） [OR = 1.74, 95% CI （0.73, 3.65）], shuxuening injections （SXN） [OR = 1.06, 95% CI （0.609, 1.697）] or ginkgolides in- jections （GK） [OR = 4.711, 95% CI （1.178, 13.21）] reach statistical significance; the difference compar- ing GD to GK reach statistical significance [OR = 2.791, 95% CI （0.866, 6.908）]; the difference com- paring SXN to GK reach statistical significance [OR = 4.537, 95% CI （1.203, 12.41）]. Besides, there was no difference between 4 GIs in NFDS. Proba- bility ranking result showed a great possibility for GK [Surface under the Cumulative Ranking curve （SUCRA） = 80.3%] in improving the total effective rates, which were followed by GD （SUCRA = 73.34%）, SXN （SUCRA = 46.59%）, GbE （SUCRA = 45.46%）, floium ginkgo extract and tertram ethy- pyrazine sodium chloride injections （FT） （SU- CRA = 35.64%）. However, GK （SUCRA = 80.3%） or GbE （SUCRA = 69.4%） was better than other GIs in reducing NFDS.GK ＋ WM is the best treatment measures to reduce NFDS in cerebral infarction, which were followed by SXN ＋ WM （SUCRA = 51.6%）, GD ＋ WM （SUCRA = 48.1%）. CONCLUSION： GIs was more effectiveness on CI than the routine Western Medicine. But based on the limitations of the study, more high-quality ran- domized controlled trials will be necessary.

Meta-analysis on randomized controlled trials for scalp acupuncture treatment of stroke：A systematic review

OBJECTIVE:To conduct a systematic review to assess the clinical effectiveness of scalp acupuncture(SA) for stroke.METHODS:Literature searches were performed in7 databases up to 16 August 2014,and all the randomized controlled trials(RCTs) in which SA therapy was administered to stroke patients were selected.Methodological quality was assessed using the Jadad score,the Cochrane risk of bias assessment,and the Standards for Reporting Interventions in Clinical Trials of Acupuncture.RESULTS:Of a total of 2086 papers,21 RCTs were selected.Meta-analysis revealed significant differences in the total efficacy rates of the SA group and the body acupuncture(BA) group vs the medication group(P < 0.002,P < 0.000 001,respectively),the SA plus BA group vs the BA group(P < 0.001);in the motor function of the SA plus BA group vs the BA group(P = 0.077);and in the nerve function of the SA group vs the SA plus BA group(P < 0.0001).CONCLUSION:The results of our systematic review showed that SA therapy may exhibit effects in treatment efficacy and in the recovery of motor and nervous functions in patients with acute to chronic stroke.However,because of the lack of methodological quality,the thoroughly planned clinical studies are still required.

Separability criteria via some classes of measurements

Mutually unbiased bases (MUBs) and symmetric informationally complete (SIC) positive operator-valued measurements (POVMs) are two related topics in quantum information theory. They are generalized to mutually unbiased measurements (MUMs) and general symmetric informationally complete (GSIC) measurements, respectively, that are both not necessarily rank 1. We study the quantum separability problem by using these measurements and present separability criteria for bipartite systems with arbitrary dimensions and multipartite systems of multi-level subsystems. These criteria are proved to be more effective than previous criteria especially when the dimensions of the subsystems are different. Furthermore, full quantum state tomography is not needed when these criteria are implemented in experiment.