Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.

Contribution of the MERISE-Type Conceptual Data Model to the Construction of Monitoring and Evaluation Indicators of the Effectiveness of Training in Relation to the Needs of the Labor Market in the Republic of Congo

This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.

Mining Weights of Land Evaluation Factors Based on Cloud Model and Correlation Analysis

The veracity of land evaluation is tightly related to the reasonable weights of land evaluation fac- tors. By mapping qualitative linguistic words into a fine-changeable cloud drops and translating the uncertain factor conditions into quantitative values with the uncertain illation based on cloud model, and then, inte- grating correlation analysis, a new way of figuring out the weight of land evaluation factors is proposed. It may solve the limitations of the conventional ways.

Evaluation and classification of residential greenbelt quality based on factor analysis & clustering analysis:An example of Xinxiang City,China

Five factors expressing greenbelt quality and one factor expressing quantity were adopted for evaluation of the residential greenbelt, and the AHP （Analytical Hierarchy Process） method was used to determine the value of factors. Thirty residential areas were selected as the samples. Two principal components were extracted and their expression was constructed by method of factor anlysis, therefore, quality evaluation of residential greenbelt was obtained. The accuracy of the function and implement quality classification toward the residential greenbelts in Xinxiang City were validated by clustering analysis method. The results showed that the greenbelt quality of fourteen residential areas was higher than the average level, of which eleven were newly-built residential areas. The 30 residential areas were classified into three types according to their greenbelt features and their formation by clustering analysis method. Finally rational proposal basing on aforesaid evaluating results was proposed for construction and renewal of residential greenbelt, upon which directive basis was provided for construction and renewal of residential greenbelt.

Comprehensive Evaluation on the Regional Economy of Commodity Grain Base in Heilongjiang Province Based on Factor Analysis Method

Taking a total of 13 areas in Heilongjiang commodity grain base as the research objects,9 indices are selected,which are regional GDP(X1),per capita GDP(X2),total value of tertiary industry(X3),financial revenue(X4),urban fixed assets investment(X5),average salary(X6),gross industrial output value(X7),total output value of farming,forestry,husbandry and fishing(X8),and retail sales of social consumer goods(X9).Based on this,evaluation index system of regional economy is established.According to the 2006-2008 Heilongjiang Statistical Yearbook,average values within 3 years are used as analytical data.Factor Analysis Method is adopted to establish regression model and to carry out comprehensive analysis.Result shows that Heilongjiang commodity grain base has extremely uneven regional economic development in different areas.According to the score order and actual situation,the 13 areas are divided into 4 types.The first and second types are Harbin and Daqing,respectively.The third type is Qiqihaer,Suihua,Mudanjiang and Jiamusi.And the forth type is Jixi,Shuangyashan,Heihe,Yichun,Qitaihe,Hegang and Daxinganling.Suggestions for the development of these areas are put forward.

Comprehensive Evaluation of Processing Quality of Tibetan Native Hulless Barley Variety by Factor Analysis

The purpose of this study was to explore the quality of the Tibetan native hulless barley variety in depth and to evaluate the characteristics of its processing quality using ratio analysis.For this study,10 native barley varieties were chosen with the detection of 24 quality indexes in order to build a system of comprehensive evaluation.The results of the factor analysis indicated that seven common factors with an eigenvalue greater than 1 were extracted,cumulatively accounting for 96.21%of the total variance.The first common factor,including ASP,GLU,SER,GLY,ARG,TYR and CYS contents,accounted for 33.82% of the variance.The second common factor,including ash,the total starch,soluble fiber,VB_(3),Cu,Mn,Na and beta-glucan contents,accounted for 19.46%of the variance.The third common factor,including the total dietary fiber,α-VE,K,Zn and glutelin.The fourth common factor,including B,Ba and prolamin,explained the barley starch character of the rheological property.The fifth common factor included crude fiber.The sixth and the seventh common factors did not account for a substantial amount of variance.According to the comprehensive evaluation model,the score consequence was as the following:Zangqing25>Pengnaigabu>Lhasa changhei>2004Qing21>Lhasa duanbai>Liangamu>Zhikonggaxia>lianmubai>Jiangreejiu>Longzihei.

Factor Analysis Based on the Level of Urban Facilities in Different Regions

With the rapid growth of economy in China, people＇s living standard has been generally improved, and people＇s requirements on the quality and quantity of infrastructures like transportation convenience, city greening have become higher and higher, which requires the government to attach importance to these livelihood is- sues. Based on the China Statistical Yearbook, 6 target factors of 31 provinces and cities in China were conducted with factor analysis, and the conditions of the infras- tructures in the 31 provinces and cities were judged and evaluated through the ex- traction of common factors and the calculation of these common factors, and corre- sponding suggestions were proposed with the aim to improve the infrastructures in China.

Spatial analysis and evaluation of a coal deposit by coupling AHP & GIS techniques

Nowadays,the evaluation of coal deposits becomes crucial,due to many uncontrollable factors,which affect the energy sector.A comparative evaluation of coal deposits is essential for their hierarchical classification regarding their sustainable exploitation,when compared to other coal deposits or competitive fuels,which may be used as alternative solutions for electricity generation.In this paper,a method for spatial analysis and evaluation of a lignite deposit is proposed,by creating four spatial key indicators via GIS analysis,which are then aggregated by applying a weighted linear combination.The analytical hierarchy process is applied to estimate the relative weights of the indicators,in order to perform a weighted cartographic overlay.Through the synthesis of the indicators,an overall,total spatial quality indicator is calculated.The weighted analysis was shown to be more effective compared to the unweighted one,because it can provide more reliable results regarding the exploitation of the examined lignite deposit.The implementation of GIS-based analytical hierarchy process in spatial analysis and evaluation of lignite deposits,in terms of sustainable exploitation,demonstrates that this method can be extensively applied for evaluating the economic potential of mineral deposits.

Comprehensive security risk factor identification for small reservoirs with heterogeneous data based on grey relational analysis model

Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.

Main Controlling Factors and Dominant Reservoir Series Analysis of Es_3 in the Qibei Area of Qikou Sag

Based on analysis of geophysical data such as core observation, rock slices identification, physical property, scanning electron microscope, X-ray diffraction, logging data etc., 16 factors of sedimentation, diagenesis, fluid pressure, and their relationships with reservoir physical property were analyzed, and the results indicate sedimentation is the internal factor controlling the reservoir property, diagenesis is the external and final decisive factor and abnormal fluid pressure is an important factor preserving the deep reservoir property. Quantitative characterization of diagenesis indicates that compaction and dissolution are more important than cementation and they respectively cause porosity change of-23.6% and 7.7% and -6.2%. Through optimizing 11 main controlling factors and constructing reservoir evaluation index （REI） according to the hierarchical cluster and principal component analysis, reservoir classification standard was established and reservoirs were divided into four classes. The studies show that Es~ SQ4 consists mainly of class I and II, while Es~ SQ6 is mainly of class III and II; the favorable zone is the north and south slope of Qibei sub-sag and the Liujianfang fault-nose. The successful application of the quantitative and comprehensive evaluation in the Qibei area verifies the advanced, practicable method of less artificial factor is suitable for the low porosity and permeability reservoir.

A nonparametric spectrum estimation method for dispersion and attenuation analysis of borehole acoustic measurements

Dispersion and attenuation analysis can be used to determine formation anisotropy induced by fractures,or stresses.In this paper,we propose a nonparametric spectrum estimation method to get phase dispersion characteristics and attenuation coefficient.By designing an appropriate vector filter,phase velocity,attenuation coefficient and amplitude can be inverted from the waveform recorded by the receiver array.Performance analysis of this algorithm is compared with Extended Prony Method(EPM)and Forward and Backward Matrix Pencil(FBMP)method.Based on the analysis results,the proposed method is capable of achieving high resolution and precision as the parametric spectrum estimation methods.At the meantime,it also keeps high stability as the other nonparametric spectrum estimation methods.At last,applications to synthetic waveforms modeled using finite difference method and real data show its efficiency.The real data processing results show that the P-wave attenuation log is more sensitive to oil formation compared to S-wave;and the S-wave attenuation log is more sensitive to shale formation compared to P-wave.

Comprehensively evaluate the short outcome of small bowel obstruction:A novel medical-economic score system

BACKGROUND Small bowel obstruction(SBO)still imposes a substantial burden on the health care system.Traditional evaluation systems for SBO outcomes only focus on a single element.The comprehensive evaluation of outcomes for patients with SBO remains poorly studied.Early intensive clinical care would effectively improve the short-term outcomes for SBO,however,the full spectrum of the potential risk status regarding the high complication-cost burden is undetermined.AIM We aim to construct a novel system for the evaluation of SBO outcomes and the identification of potential risk status.METHODS Patients who were diagnosed with SBO were enrolled and stratified into the simple SBO(SiBO)group and the strangulated SBO(StBO)group.A principal component(PC)analysis was applied for data simplification and the extraction of patient characteristics,followed by separation of the high PC score group and the low PC score group.We identified independent risk status on admission via a binary logistic regression and then constructed predictive models for worsened management outcomes.Receiver operating characteristic curves were drawn,and the areas under the curve(AUCs)were calculated to assess the effectiveness of the predictive models.RESULTS Of the 281 patients,45 patients(16.0%)were found to have StBO,whereas 236 patients(84.0%)had SiBO.Regarding standardized length of stay(LOS),total hospital cost and the presence of severe adverse events(SAEs),a novel principal component was extracted(PC score=0.429×LOS+0.444×total hospital cost+0.291×SAE).In the multivariate analysis,risk statuses related to poor results for SiBO patients,including a low lymphocyte to monocyte ratio(OR=0.656),radiological features of a lack of small bowel feces signs(OR=0.316)and mural thickening(OR=1.338),were identified as risk factors.For the StBO group,higher BUN levels(OR=1.478)and lower lymphocytes levels(OR=0.071)were observed.The AUCs of the predictive models for poor outcomes were 0.715(95%CI:0.635-0.795)and 0.874(95%CI:0.762-0.986)for SiBO and StBO stratification,respectively.CONCLUSION The novel PC indicator provided a comprehensive scoring system for evaluating SBO outcomes on the foundation of complication-cost burden.According to the relative risk factors,early tailored intervention would improve the short-term outcomes.

Energy efficiency evaluation based on DEA integrated factor analysis in ethylene production

Energy efficiency evaluation plays an important role in energy efficiency improvement of the ethylene production. It is observed from the actual production data that the ethylene production energy efficiency often varies with the complex production working conditions. In the favored methods for energy efficiency evaluation,DEA models may show poor resolution when directly used to evaluate the efficiency values. Therefore, a new energy efficiency evaluation method for ethylene production is proposed based on DEA integrated factor analysis with respect to operation classification. Three key factors, including raw material composition, cracking depth and load rate, are taken into account in determining the production working conditions by means of k-means algorithm. Based on the multi-working conditions mode the energy efficiency evaluation of the ethylene production is made by using DEA model, where the most related energy data are screened by factor analysis.Furthermore, the supporting decision of energy efficiency improvement is provided to the operators. The accuracy and effectiveness of the proposed method are illustrated by applying in a practical ethylene production,which gives more effective energy efficiency evaluation in the complicated working conditions of ethylene production with declined dimension of input indicators.

An intelligent prediction model of epidemic characters based on multi-feature

The epidemic characters of Omicron(e.g.large-scale transmission)are significantly different from the initial variants of COVID-19.The data generated by large-scale transmission is important to predict the trend of epidemic characters.However,the re-sults of current prediction models are inaccurate since they are not closely combined with the actual situation of Omicron transmission.In consequence,these inaccurate results have negative impacts on the process of the manufacturing and the service industry,for example,the production of masks and the recovery of the tourism industry.The authors have studied the epidemic characters in two ways,that is,investigation and prediction.First,a large amount of data is collected by utilising the Baidu index and conduct questionnaire survey concerning epidemic characters.Second,theβ-SEIDR model is established,where the population is classified as Susceptible,Exposed,Infected,Dead andβ-Recovered persons,to intelligently predict the epidemic characters of COVID-19.Note thatβ-Recovered persons denote that the Recovered persons may become Sus-ceptible persons with probabilityβ.The simulation results show that the model can accurately predict the epidemic characters.

Construction of an evaluation system for information openness of local governments

Evaluating government openness is important in monitoring government performance and promoting government transparency. Therefore, it is necessary to develop an evaluation system for information openness of local governments. In order to select evaluation indicators, we conducted a content analysis on current evaluation systems constructed by researchers and local governments and the materials of a case study on a local government. This evaluation system is composed of 5 first-tier indicators, 30 secondtier indicators and 69 third-tier indicators. Then Delphi Method and Analytic Hierarchy Process(AHP) Method are adopted to determine the weight of each indicator. At last, the practicability of the system is tested by an evaluation of the local government of Tianjin Binhai New Area, which has been undergoing administrative reform and attempting to reinvent itself in the past 5 years.

The hot issues of studies in China on digital information resources: Based on co-word analysis

With the SPSS and the help of factor method and hierarchical clustered method,journal articles on digital information resources(DIR) from CNKI in the past ten years are analyzed with a co-word analytical method in this paper. The hot issues of studies on DIR and the relationship between those subjects are analyzed in this investigation as well.

Turning Research into Action: Using Factor Analysis to Enhance Program Evaluation

Purpose: Sexual activity among adolescents in the United States remains high. Nearly 46% of students grades 9-12 have engaged in sexual intercourse. One of the more recent statistical tools employed in evaluation efforts includes factor analysis. The objective of this study was to investigate the underlying dimensions of a survey instrument that assesses a youth character development program, which focuses on avoiding high-risk behaviors. Method: The 76-item survey instrument was administered to adolescents (age 12-18). During the 2009-2010 school year, 652 participants in the intervention group and 1110 participants in the comparison group completed the pre-, post-, and 6-month follow-up survey. Results: Using Ajzen’s theory of planned behavior groupings, 27 survey items were selected. Through iterative principal axis factoring, four factors were extracted and rotated. A visual scree plot was generated to determine the number of acceptable factors. The extracted factors accounted for 52.53% of the total variance. Factors were subjected to Equimax rotation with Kaiser normalization and converged after six iterations. Variables with patterned weights less than 0.44 were excluded. A reliability analysis demonstrated internal consistency. Conclusions: Identified factors included: 1) Teenagers’ attitudes toward sexual health behaviors;2) Teenagers’ perceptions of the consequences of sexual health behaviors;3) Parental or guardian expectations;and 4) Teenagers’ relationships with parents or guardians. This study’s results indicated that all factors can be described within Ajzen’s theoretical framework consistent with previous research findings. Results may be used to enhance delivery of the intervention.

Site Suitability Evaluation for Sustainable Distribution of Hospital Using Spatial Information Technologies and AHP: A Case Study of Upper Egypt, Aswan City

Site selection for location of a hospital is one of the crucial policy-related decisions taken by the government. In upper Egypt, the cities suffer from a shortage and bad distribution of hospital site. The selection of the appropriate hospital site requires consideration of multiple alternative solutions and evaluation factor. We develop a Multi-Criteria Decision Support System (MCDSS) process that combines Geographical Information System (GIS) analysis with Analytical Hierarchy Process (AHP) and use this process to determine the optimum site for a new hospital in the Aswan urban area. Based on actual conditions Aswan city, we used three main factors and seven sub-factors. The main factors are urban, environmental and economic factors. An application adopting AHP process was developed to calculate weights of every factor. Spatial analysis in GIS was used to overlay and generate factors maps and suitability evaluation map. All maps are classified from 1 (low suitable) to 5 (high suitable) using spatial information technologies. The candidate sites are divided by best, good and unsuitable hospital areas. Best hospital site represents optimal sites;good hospital site can be used as back-up candidate sites. The study was found that best area (S3) is about 30%, and most of these are located in the south part of the study area;good area (S2) is about 58%, and most of these are located in the central part of the study area;unsuitable area (S1) is about 12%, and most of these are located in the Eastern and Western parts of the study area. Finally, the study ends with an assessment of proposed sites.

Multivariant statistical analysis for diagenetic information of chert from southern Tibet,China

There are large scale chert formations of different ages exposed widely in southern Tibet, along Yarlung-Zangbo suture zone. The typical chert specimens were sampled from Pengcuolin, Xialu and Zongzhuo profiles. Multivariate statistical analysis is applied for effectively extracting the geochemical information of the chert, and the raw data are processed by R-factor analysis. The first, second and third factors representing terrigenous, authigenic and hydrothermal constituents are extracted from the analysis results. From Pengcuolin, Xialu to Zongzhuo chert profiles, the variance ratios of continental and authigenetic factors become higher （ 51. 1% →62.9 % →91.6 % ）, while hydrothermal factor rapidly decrease （ 40. 9 % →32.2 % →0 ）. This tend- eney also present in the analysis for traee elements, indicating that Pengeuolin chert is hydrothermal origin, The Zongzhuo chert belong to normal sedimentation and the Xialu chert exhibit normal deposition interacted with hydrothermal sedimentation. The facts provide significant implications for understanding the diagenetic and palaeomineralization information of southern Tibet.

Survey of Data Value Evaluation Methods Based on Open Source Scientific and Technological Information

It is important to effectively identify the data value of open source scientific and technological information and to help intelligence analysts select high-value data from a large number of open-source scientific and technological information. The data value evaluation methods of scientific and technological information is proposed in the open source environment. According to the characteristics of the methods, the data value evaluation methods were divided into the following three aspects: research on data value evaluation methods based on information metrology, research on data value evaluation methods based on economic perspective and research on data value assessment methods based on text analysis. For each method, it indicated the main ideas, application scenarios, advantages and disadvantages.