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It is of great significance to study how to assess the railway tunnel damage loss quickly after earthquake for the earthquake relief and post-disaster reconstruction work. Hierarchical weighted synthesis method is the theoretical foundation of the system of earthquake disaster loss assessment. The system is based on windows operation system and VB language is selected as integrated development environment. Access is as external database, the automotive conversion of the earthquake damage reduction value without manual entering and automotive computing of Loss Assessment will be achieved. The computing outcome will be saved in excel. The software can provide scientific evidence and improve the efficiency of the loss assessment.

This thesis, as part of the creation of a text-mining-based sentiment dictionary to be applied in the Korean grammar structure, solves the problem of the enhancement of accuracy of opinion mining data by applying the filtering model of candidate sentiment vocabularies. The fact that the reliability of sensitive vocabularies shows huge variances according to the filtering modeling method applied has become a decreasing factor for the accuracy of the vocabularies in the opinion mining process, which is attributable to the fact there isn’t a success factor in the filtering modeling standard for precise selection of vocabularies. In this thesis, a filtering model of positive and negative vocabularies on candidate Korean sentiment vocabularies and a reliability scale for accuracy were suggested to solve such problems by applying the semi-structured data filtering model for the selection of candidate sentiment vocabularies of the Korean grammar. The study has confirmed through relevant performance assessment when filtering were applied in relation to 30%, 50% and 60% respectively with regard to candidate sentiment vocabularies upon collecting vocabularies obtained via sentence segmentation and classification into positive and negative vocabularies that exceptional accuracy of the opinion sentiment dictionary was shown via the 60% filtering.

This paper uses fuzzy mathematics theory, and the fuzzy comprehensive evaluation method is applied to the research on admission professional warning fuzzy comprehensive evaluation, combined with the actual situation of the professional warning and admission professional warning evaluation system will be divided into a number of indicators according to the need, establishing the factor set, evaluation set, membership function and weight set, and the comprehensive evaluation of admission professional warning level will be realized. This paper also uses hierarchical analysis method to calculate and evaluate the weight set, and improves the max-min algorithm and the maximum membership degree principle of the evaluation results, proposes a new improved algorithm, and verifies by experiment, and achieves good results. Examples show that the hierarchical analysis improved algorithm based on weighted average fuzzy math has strong operation and good effect, which can be widely used in professional warning.

Business intelligence approach is adopted for data mining analysis on the customer transaction data and basic customer information of securities companies. Decision tree algorithm is used to create the customer loss warning model, which is then used to analyze and design the securities data mining system. This system based on Weka source code, realized by JSP language and takes the classification analysis in the business intelligent core technology as the core algorithm. Analyzing this system can assist to mine the customers with potential loss trend and help establish specific detainment strategy to prevent great loss due to customer loss.

Based on a two-stage analysis of a panel of data for 25 Korean accounting firm for 16 years from 1997 to 2012, the researcher investigates how non-audit services affect accounting firm productivity. In the first stage, the researchers employ Data Envelopment Analysis (DEA) to compute the relative productivity of accounting firms in using their human resources to generate firm revenues. In the second stage, the researcher estimate regression models that relate the logarithm of DEA productivity scores to the mix of services provided and control variables. Empirical results support my research hypotheses that accounting firm productivity, in terms of revenue generation based on human resources utilized, decreases with greater provision of taxation services and increases with greater provision of management advisory services.

Most recommender systems based on collaborative filtering aim to provide recommendations for a user in one domain. But data sparsity is a major problem for collaborative filtering techniques. Recently, many scholars have proposed recommendation models to alleviate the sparsity problem by transferring rating matrix in other domains. But different domains have different rating scales (e.g., rating scale may be 1-5 or 1-10). Simple process for the rating scale does not reflect the real situation. The diversity of rating scales may cause the opposite effect, making the recommendation results more imprecise. In this paper, we propose a transfer model which learning the common feature tags from other domain. This model ignores the difference of rating scales between two domains, and focus on studying the feature tags. Using its own rating values to fill the missing value. We first get the different types of users (items) based on non-negative matrix tri-factorization from auxiliary domain. The process we call the user (item) clustering. Than we can get a BP neural network which can judge the type of user according to user's feature tags by studying the features of different types of users (items). And we classify the user (items) which from target domain by exploiting the trained neural network and the users’ feature tags of target domain. Use the average rating values of the same type of users (items) to fill the missing value of target domain. We perform extensive experiments to show that our proposed model outperforms the state-of-the-art CF methods for the cross-domain recommendation task.

In numerous epidemiological data, complex sample survey including stratification variables and cluster variables is used as a sampling method. This study compared the differences in mean and significant probability depending on the application method of weights when a chi-square test is performed using Complex Sample Survey Data. Multiple regression and complex sample regression analysis were used as analyzing methods. Youth Risk Behavior Web-based Survey (KYRBS) 2012 was used as data source. As a result of multiple regression and complex sample regression analysis, there were differences in mean and significant probability. The result of this study confirmed that in the analysis of data from complex sample surveys, biased variance (standard error) may be drawn out when using Simple Random Sampling Design. When using complex sampling survey data, in order to minimize the error for samples and to have study results that represent overall population, Complex Sampling Design is required.

Based on field trials of different nitrogen levels, rice canopy chlorophyll content and canopy spectrum of its booting stage were respectively measured using the nitrogen balance index meter and the hyperspectral imager, in the Northeast of china. Analyzing the rice canopy spectral response characteristics under nitrogen gradient after canopy reflectance spectra were first extracted and filtered for noise, then the original reflectance spectra were transformed into the first derivative reflectance for further analysis. Stepwise analysis was carried out to select sensitive bands for canopy chlorophyll content by making correlation analysis and to build spectral indexes, and then chlorophyll content prediction models were generated and tested. After comparing, the two models with better estimation precision were the model with reflectivity at 572nm as a variable and the model with the index DSI(572,682) constructed the reflectivity at 572 and 682nm as a variable, the coefficients of determination R2 were 0.733 and 0.694, the root mean square errors RMSE were 2.9656 and 3.0346, and the relative errors RE% were 7.07% and 7.43%.

This study aimed to assess whether gum chewing affects bowel motility, including time to first passage of flatus, time to first feces, time to tolerance of oral fluid, and length of hospi-tal stay after laparoscopic colorectal surgery. The current study had a non-equivalent con-trol group and non-synchronized design. Sixty-four patients who underwent laparoscopic colorectal surgery were assigned to either a gum chewing group (n = 32; experimental group) or a control group (n = 32). The patients in the experimental group chewed gum for 1 hour, 3 times a day, until they passed gas. Chewing gum led to significant differences in the first passage of flatus (t = 7.716, p < .001) and feces (t = 2.216, p = .030), time to toler-ance of oral fluid (t = 4.404, p < .001), and length of hospital stay (t = 2.829, p = .006) between groups. This research concluded that chewing gum can be a useful intervention to shorten the time to the first passage of flatus and feces as well as to reduce the time to tol-erance of oral fluid and length of hospital stay.

The traditional recommendation algorithms of image tagging ignore the diversity between the visual content information and the tags recommended, which causes the recommended results have the problem of tag ambiguity, tag redundancy and so on. Therefore, this paper proposes the recommendation algorithm of image tagging based on relevance and diversity. The algorithm defines the relevance and diversity of a label set, and selects a label set which can reasonably balance the relevance and diversity to recommend to the user. The experimental results show that this algorithm improves the relevance between the recommended results and the image, and makes the recommended results be able to reflect the image content thoroughly at the same time.

China’s traditional industry clusters meet challenges and opportunities as the global economy goes ups and downs. Following the trend of industry upgradation is a highlight in both theoretical and practical domain. This paper focuses on the principles of dynamic evolution of China’s industry clusters in order to pursuit and establish its enduring growing drive and competitive advantages. This paper gives research into dynamic evolution of cluster network, centering on its inherent relationship with the core enterprise transformation and the restructure flexibility of cluster members and defines “the transformation and up gradation of the core enterprises in cluster network”, finds out the dynamic and persistent effect of transformation and upgradation of the core enterprises on network resources and puts forward the dilemma of the dynamic evolution and upgradation of China’s cluster network.

The popularization of smart devices and SNS as a new communication way promotes positive changes such as the user’s participation in the communication with others and the knowledge sharing. Meanwhile, it also facilitates negative social problems such as the formation of unexpected social relations, the intrusion of privacy, the cyber violence and the polarization of communication. These negative changes go toward a new viewpoint that the excessive SNS use may cause the SNS user’s fatigue. The purpose of this study is to invest how the SNS use motives and use patterns influence on the SNS user’s fatigue and ambivalent attitude. Therefore this study intended to develop a model about the SNS user’s social stress and ambivalent attitude influencing on the continual SNS use, and will empirically research this model in future studies.

Adverse drug reactions (ADRs) are a serious threat to people's lives and property safety. Currently, drug instructions are the main way for people to obtain information on ADRs. Due to drugs’ limited pre-market clinical trials, adverse reactionsstated in drug instructions are often not sufficient. Avisualization platform for ADRs isput forward to address this problem. Adverse drug events (ADEs) data include actual clinical adverse reactions of drugs detected by drug monitoring administrationand can compensate for the insufficiency of drug instructions. Based on drug instructions and ADEs data, ADRVis isrealized by data analysis, model design and JAVA programming. ADRVis presentsthe relationship of 656 common drugs and their respective ADRs. Three case studies show that the platform has the capacities of visual presentation of ADRs and early warning of drug risks.The platform can provide people more rich information about drugs and help them understand ADRs more accurately and comprehensively.

The purpose of this study was to measure post-dialysis fatigue in patients on hemodialysis and identifies clinical variables that are associated with post-dialysis fatigue. The subjects for this study were 103 patients who were receiving chronic hemodialysis in outpatient dialysis clinics in Seoul between April 12th and April 23th, 2010 and consented to participate in the study. The collected data were analyzed by the SPSS WIN 12.0 program. The mean score of fatigue were 63.4, 86.8 and 60.8 before hemodialysis, after hemodialysis and next day, respectively. There was a statistically significant (F=5.16, p<.001). All these indicators but ‘tired’, ‘not energetic’, ‘difficult to move’, ‘would like to lie’ did not significantly differ over time after hemodilaysis. ‘Would like to lie’ was strongest after hemodialysis (F=12.52, p<.001). There were significantly positive correlations between post-dialysis fatigue and weight gain (r=.18, p=.038). There were significantly positive correlations between weight gain and ‘tired’, ‘ difficult to move’, and ‘would like to lie’. There were also significantly positive correlations between post-dialysis fatigue and age (r=.19, p=.035), comorbidities (r=.14, p=.031), post dialysis blood pressure (r=-.17, p =.024), weight change (r=.14, p=.034), and hemoglobin (r=-.27, p=.005). Also, Age, comorbidities post-dialysis blood pressure, weight change, and hemoglobin predicted value accounted for 16.8% of the variance on post-dialysis fatigue (F=13.08, p<.001). It is considered that dialysis providers care to recognize post-dialysis fatigue as an important nursing issue for hemodialysis patients. It is also necessary to develop a nursing intervention for improving their post-dialysis fatigue.

With analyzing usual collaborative filtering algorithm , a modified collaborative filtering algorithm which fuses with fashion attributes is researched .Firstly , using fuzzy mathematics processes fashion attributes, which include style , color , material , quality , brand , and seasonality , to produce fashion attributes function . Secondly, using fashion attributes function adjusts users appraising matrix parameters of collaborative filtering algorithm to improve fashion recommendation system performance. Lastly, to use experiment proves that performance of modified collaborative filtering algorithm is better than performance of usual filtering algorithm performance in personalized fashion recommendation system.

There is an increasing recognition that the organizations must address the issues of environmental protection with the development of the economy and society, and it is becoming a matter of obligation rather than choice to adopt more environmentally friendly behavior. It is known to all that China is one of the global manufacturing countries. However the Chinese government has realized the responsibility of reducing the pollution and the protection of the environment is one of the basic state policies. This paper is an attempt to testify the improvement of reducing environment pollution and identify the current issues in environmental pollution of the companies from the supply chain perspective in China. Grey approach is employed to evaluate the improvement of the product supply chains in terms of reducing environmental pollution in China. The managerial implications and suggestions for future research are discussed in this paper.

Today, there are many important factors which enterprises should consider to innovate. When there is an organizational change, the employees’ understanding of the change and individual readiness that measures the state of readiness are also important factors. Studies have been conducted focusing on the roles of leaders to make a change but for true innovation, all employees should prepare for changes. This study examined 9 domains focusing on the K Company to find out key factors in change readiness. In addition to key factors, this study suggested a plan for employees’ effective change management activities by analyzing a perception gap in different positions by factors.

In order to analyze the premise condition of logistics cloud service discovery and composition and provide the basis for subsequent research, the logistics cloud service cooperation system framework was constructed from the perspective of modern logistics Virtual Enterprise Alliance. Base on this, extracts the preconditions of the logistics cloud service discovery and combination were extracted, then the game models were built and analyzed. Finally, reasonable countermeasures were proposed, which have a certain practical significance for carrying out the cloud logistics and developing the modern logistics.

Recently, with the rapid development of science and cultural areas, the written and electronic amount of books in the university libraries increases sharply. When readers use the traditional searching system which is based on the collaborative filtering method, it is usually difficult for them to find out their interested books due to a large number of results from the system. Aiming at this problem, the paper points out a sort of personalized recommending system. This system optimizes the collaborative filtering method based on the information of the users, uses the new collaborative filtering method based on the classification of users and books, and analyzes and orders a variety of recommending information after filter. From the experiment, it concludes that compared with the traditional recommending system the personalized system targets towards different types of readers. The numbers of books which feed back to readers have decreased a lot. What’s more, after a comprehensive analysis and order of the various recommending information, the average recommending accuracy will make further improvement.

Since the establishment of cyber universities in South Korea in 2001, there have been high societal expectations for these new institutions of higher learning. However, as the dropout rate for cyber universities is higher than standard four-year universities, matters of quality control are increasingly becoming an issue. This study analyses the factors that influence the expansion and maintenance of student numbers in cyber universities. Of the four-year cyber universities that conferred bachelor's degrees in 2013 and 2014, 17 universities were selected in analyzing the factors influencing academic continuity of cyber university students. This study analyzed cyber universities’ offline study halls and study support facilities’ locations, the level of university recognition, the rate of expanding teacher facilities, scale of enrolled students, level of competitiveness for university entrance for freshmen students, cost of education per student, scholarships per student, and the proportion of lectures appointed to full-time faculty against the enrollment rate of new students, the proportion of standard high school graduates which indicates the academic continuity of the freshmen enrollment rate, and the enrollment rate of the entire student body and dropout rate. The results show that the level of competitiveness for university entrance for first year students and the proportion of lectures appointed to full-time faculty are factors with a positive effect, with the level of competitiveness for university entrance for first year students having the greatest influence. Such analysis results show that the factors related to the decision making when students select a university have a significant effect on cyber universities' enrollment and continued learning, suggesting that after enrollment, academic experience has a relatively small influence on continued learning. Therefore, there is a need for cyber universities to improve the quality of learning and teaching as well as increase the information available to students for students to choose cyber universities. There is a need for these two policy directions to be promoted simultaneously to improve the relevancy of programs offered by and demanded of cyber universities.

As an important initiative of comprehensively deepening reform in China, how to promote government purchase public service actively and steadily is the common focus of academic and practical departments. Two typical modes of government purchase public service which are purchase service from producer and purchase service from integrator are analyzed. According to the contract theory, the two optimal models are set up through adding heterogeneity of public service variables to the classical incentive model. The rent of the two modes paid by government is compared and analyzed. The conclusion indicates that the heterogeneity of public service can influence mode selection of government purchase public service. It should choose multi-agent when the heterogeneity of public service is low; otherwise, it should select service integrator to undertake public service.

This study is a descriptive correlation study to determine the factors that affect immigrant women depression. In this study, migrant known factors on the impact of depression on women on the basis of previous studies acculturation stress, family stress, marital satisfaction, life satisfaction by focusing on variables such as the impact on immigrant women depression and depression check the effects of factors previously mentioned, and to provide a basis for early detection of depression and the prevention of immigrant women. The participants were 665 immigrant women who married Korean men. Data collection for this study was conducted between February to June 2010. Data collection methods to meet immigrant women in Seoul, Gyeonggi (Hanam, Yongin), Gyeongsangnam-do (Jinju), and migrant women who are based in Busan Center, Health Center, etc., were chosen as the place of data collection. The major findings were as follows; 1) Depression is generally characteristic of the separation group and was significantly higher than the married group in marital status (F =5.063, p =.001). In in areas like “my husband’s educational level” (F = 3.522, p = .007), “the religion of subjects” (F = 3.200, p = .002), “husband religion” (F = 2.562, p = .013), and “family monthly income” (F = 4.421, p = 0.005), there was a statistically significant difference. 2) Immigrant women's depression and marital satisfaction (r = -. 112, p <.01), Korean life satisfaction (r = -. 124, p <.01), than was the inverse correlation is significant and acculturation stress (r = .231, p <.01) were significantly correlated net. 3) Depression was predictive, the regression model of migrant women appeared to be significant (F = 10.12, p <.001), indicating a revised explanatory power of the model coefficient of determination (Adj R2) was 0.17 with 17% explanatory power. Based upon the findings, this study provides useful information that could assist in reducing depression among married immigrant women and indicates that depression prevention programs are needed.

Due to the multi-objective process of complex product scheme design, the multi-objective design optimization method of product scheme design is studied, an improved decision-making method of multi-objective extension design based on the extension theory is put forward, and a decision-making method of multi-objective extension design model based on the extensible relational degree is presented. By using the method and the model, the characteristic indexes are processed integrated, the computation model of extension degree of association is founded to process the uncertainty design information, and the decision design is achieved based on the optimum degree of the multi-objective design scheme. Finally, a case is provided to prove its feasibility.

Work-related musculoskeletal disorders are known as chronic health hazards in the musculoskeletal system, resulting from minute injuries mainly in the joint regions and caused by repetitive manual work, inconvenient and awkward working postures, high labor intensity, excessive force, insufficient rest, cold working environments, or vibrations. The purpose of the present study is to judge whether low back pain and other musculoskeletal symptoms appear more significantly in sedentary work or standing work. The present study was conducted with 109 production workers of an electronic product manufacturing business that implement assembling processes along the flow of conveyor belts with typical sedentary work for eight working hours per day. In addition, it also included 116 production workers of a car component manufacturing business located in Gyeonggi-do that implement assembling processes in cell lines with typical standing work for eight working hours per day. More sedentary workers were shown to be pain complainants (21.1%) and management targets (54.1%) that felt pain in at least one region. Many complained of pain in the shoulder (15.6%) and the percentage of management targets among them was shown to be higher than standing workers were. As almost 70% of standing workers experiencing many physical burdens were shown to be healthy, except for those who were shown to be pain complainants, standing work is assumed to have healthy effects. As well, given that only 24.8% of sedentary workers were shown to be normal, sedentary workers should be managed through appropriate exercise therapy or health management.

Aiming at high nonlinear problem of special transmission gear invalidation analysis, provided a method which based on Meshless local Petrov-Galerkin method coupled with finite element method and method to solve fracture problem of special transmission gear. Simulation calculation has been done to non-involute beveloid gear developed by project team. Calculation result verified efficiency of the simulation method. The method has important meaning to novel gear development and research.

This study attempted to determine the practice of various powers of life that penetrate the discourses on health and pursue the direction that must be followed by nurses. Florence Nightingale expanded nursing, which traditionally was the role of women at home, to the society; since then, nursing has secured its place as a specialized profession in health. Can nursing continue to grow as a powerful profession? Foucault disclosed the concept of power not in the sense of force or coercion, but in the sense of discourse domination that induces people to naturally practice in daily life. Accordingly, this study verified the implications in the perspective and strategies of nursing science by discussing the power of discourse that penetrates body and health through analysis of health-related texts.

Business Process Management (BPM) has gained great success in business and industry. However, business processes and workflow has been greatly changed by the emergence of social network media in recent years. It is necessary to study a mechanism of the seamless integration of BPM tools with existing social network platforms. This paper aims at building a social BPM system at the minimum cost on multiple existing popular public social networks. An integrated social BPM mechanism is proposed and implemented through abstract social network definition, abstract definition of BPM with Event-Driven Process Chains (EPC) model and open platforms of the social networks. The mechanism has the merits of stand-alone design, seamless integration and crossing platforms. Under the support of the mechanism people achieve seamless collaboration on public social networks.

Educational courses for preschoolers are important in developing their perceptive ability. Recently, many educational programs have been performed under digital environments. It is very innovative compared to traditional educational programs. However, sometimes such new methodology may impede children’s emotional exchanges and physical interactions. On the other hand, physical interface through physical senses such as traditional plays may maintain emotional exchanges of a high level. Therefore, children may nurture positive cognitive ability through physical experiences. Accordingly, Preschoolers’ education aims for strengthening physical activities and perceptual ability rather than mere obtaining of knowledge. The current digital education environment does not fully satisfy such goals. In order to resolve this, first of all, changes in the interface of digital education are necessary. Educational courses should be formed with a physical interface operated based on children’s physical activities. This study intends to present an educational platform appropriate for such a goal.