• Title/Summary/Keyword: Multiple regression model

Search Result 2,523, Processing Time 0.03 seconds

The Relationship of Dental Hygienists' Performance of Dental Infection Control with Their Health Beliefs and Importance (치과위생사의 건강신념 및 감염관리에 대한 중요도와 치과 감염관리 수행도와의 관련요인)

  • Moon, Sang-Eun;Hong, Sun-Hwa;Lee, Bo-Ram
    • The Journal of the Korea Contents Association
    • /
    • v.21 no.2
    • /
    • pp.227-235
    • /
    • 2021
  • The purpose of this study was to investigate the association factors of dental infection control by applying the health belief model in the dental hygienists. This study subject was 142 dental hygienists from 15 to July 5, 2020. Data were analyzed by chi-square test ANOVA, correlation analysis, and multiple regression analysis using SPSS version 23.0. The performance of dental infection control in accordance with the general characteristics of research subjects was high in case when they had educational experiences of infection control, and when they 'always' did medical examinations by interview about infectious diseases(p<0.01). The group of dental hygienists working for dental clinics with less than average 50 patients a day showed the highest rate of wearing a mask and latex gloves as personal protective gears(p<0.05),(p<0.01). When the wearing of protective goggles(face shield) and the frequency of exchanging masks after the outbreak of COVID-19 were more, the performance for infection control was increasing(p<0.05),(p<0.01),(p<0.001). In this study, it is difficult to generalize the results of the study because the research area and the subject are limited by selecting the subjects by convenience extraction, and focusing on the degree of awareness of infection control by dental hygienists, the actual status of infection control in dentistry is carefully illuminated. What you didn't do can be seen as a limitation. Considering the results of this study, the performance of infection control could be increased by removing obstacles and increasing the importance and perceived benefits of infection control of dental hygienists.

Possibility of Estimating Daily Mean Temperature for Improving the Accuracy of Temperature in Forage Yield Prediction Model (풀사료 수량예측모델의 온도 정밀도 향상을 위한 일평균온도 추정 가능성 검토)

  • Kang, Shin Gon;Jo, Hyun Wook;Kim, Ji Yung;Kim, Kyeong Dae;Lee, Bae Hun;Kim, Byong Wan;Sung, Kyung Il
    • Journal of The Korean Society of Grassland and Forage Science
    • /
    • v.41 no.1
    • /
    • pp.56-61
    • /
    • 2021
  • This study was conducted to determine the possibility of estimating the daily mean temperature for a specific location based on the climatic data collected from the nearby Automated Synoptic Observing System (ASOS) and Automated Weather System(AWS) to improve the accuracy of the climate data in forage yield prediction model. To perform this study, the annual mean temperature and monthly mean temperature were checked for normality, correlation with location information (Longitude, Latitude, and Altitude) and multiple regression analysis, respectively. The altitude was found to have a continuous effect on the annual mean temperature and the monthly mean temperature, while the latitude was found to have an effect on the monthly mean temperature excluding June. Longitude affected monthly mean temperature in June, July, August, September, October, and November. Based on the above results and years of experience with climate-related research, the daily mean temperature estimation was determined to be possible using longitude, latitude, and altitude. In this study, it is possible to estimate the daily mean temperature using climate data from all over the country, but in order to improve the accuracy of daily mean temperature, climatic data needs to applied to each city and province.

The Influence of Teacher-Librarians' Autonomy Support on Middle School Library Users' Satisfaction and Continuance Intention: The Mediating Role of Three Basic Psychological Needs (사서교사의 자율성 지지가 중학생의 학교도서관 만족도와 지속의도에 미치는 영향 - 기본심리욕구의 매개효과를 중심으로 -)

  • Kim, Jiwon;Park, Ji-Hong
    • Journal of the Korean BIBLIA Society for library and Information Science
    • /
    • v.32 no.1
    • /
    • pp.59-87
    • /
    • 2021
  • The purpose of this study is to investigate the influence of teacher-librarians' autonomy support on the school library users' satisfaction and continuance intention. Based on SDT(self-determination theory), it focuses on the mediating effect of BPN(basic psychological needs) between the autonomy supports and the satisfaction of the school library users. A survey was administered to 331 middle school students and the research model was examined by using regression analysis and Hayes' parallel multiple mediator model. The findings show that the teacher-librarians' support for autonomy directly and indirectly has a positive effect on the students' satisfaction with the school library, and perceived autonomy and competence among the sub-factors of basic psychological needs are found to have a significant mediating effect between the support of the librarian's autonomy and satisfaction with the school library. In addition, students' satisfaction with the school library shows a significant effect on the continuance intention. This study is meaningful in that it presents the role of teacher-librarians as a factor affecting students' motivation to use school libraries and provides implications for revitalizing school libraries.

Applying the Theory of Planned Behavior to Digital Gaming: Focusing on the Balance Relationship with Significant Others (디지털 게임에 대한 계획행동이론의 적용: 중요한 타인과 균형관계를 중심으로)

  • Gyu Hyun Ho;Eun Yeong Na
    • Korean Journal of Culture and Social Issue
    • /
    • v.29 no.3
    • /
    • pp.275-304
    • /
    • 2023
  • This study aimed to examine the mechanisms underlying digital game usage behavior by applying the Theory of Planned Behavior and the Balance Theory. It investigated the influences of attitude, subjective norms, and perceived behavioral control on the intention to use digital games, as well as the differences in the application of the Theory of Planned Behavior model based on the balance state among individuals, significant others, and digital games. A total of 315 responses from adult PC game users were collected through an online survey conducted from October 21 to 25, 2021, and were analyzed using multiple regression analysis. The results revealed that attitude and perceived behavioral control had a significant positive impact on the intention to continue using digital games, while subjective norms did not exert a significant influence. By categorizing groups into balanced, unbalanced, and imbalance states based on the balance relationship, the application of the Theory of Planned Behavior model showed that in the unbalanced and imbalance groups, both perceived behavioral control and attitude had a positive impact on the intention to continue using digital games. However, in the balanced group, attitude only had a positive impact on the intention to continue game usage. This study contributes to understanding digital game users by examining both individual psychological factors and the influence of others on digital game usage behavior.

Development of Driving Evaluation model of a truck for UBI (화물자동차 UBI 도입을 위한 운행 평가 모델 구축)

  • Yoo, GeonGeun;Won, Jong-Un;Lee, Suk;Kwon, YongJang
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
    • /
    • v.6 no.12
    • /
    • pp.469-481
    • /
    • 2016
  • Freight car accidents occur frequently and have a high mortality. In this reason, freight can insurance fee has been raised drastically. But speeding and overloading of trucks are still not decreased. We need to consider a measure about voluntary safe driving of truck drivers. We select UBI(Usage-Based insurance) as a measure for safe driving of truck drivers. UBI is a car insurance system and insurance fee is flexible. If vehicle drivers drive safely, insurance fee is discounted. The other way, if vehicle drivers drive dangerously, insurance fee is increased. In now, very high insurance fee for truck drivers, UBI is a effective way for leading a truck driver to safe driving. The most important thing in UBI is to evaluate truck driver rationally and accurately. In this paper, we select the reasons of truck accidents and develop driving evaluation model from multiple regression analysis and correlation analysis with accident reasons and truck accidents.

Association between a Genetic Variant of CACNA1C and the Risk of Schizophrenia and Bipolar I Disorder Across Diagnostic Boundaries (조현병과 제1형 양극성장애의 진단 경계를 넘어선 공통적 후보유전자로서의 CACNA1C에 대한 단일염기다형성 연합 연구)

  • Lee, Bora;Baek, Ji Hyun;Cho, Eun Young;Yang, So-Yung;Choi, Yoo Jin;Lee, Yu-Sang;Ha, Kyooseob;Hong, Kyung Sue
    • Korean Journal of Schizophrenia Research
    • /
    • v.21 no.2
    • /
    • pp.43-50
    • /
    • 2018
  • Objectives : Genome-wide association studies (GWASs) and meta-analyses indicate that single-nucleotide polymorphisms (SNPs) in the a-1C subunit of the L-type voltage-dependent calcium channel (CACNA1C) gene increase the risk for schizophrenia and bipolar disorders (BDs). We investigated the association between the genetic variants on CACNA1C and schizophrenia and/or BDs in the Korean population. Methods : A total of 582 patients with schizophrenia, 336 patients with BDs consisting of 179 bipolar I disorder (BD-I) and 157 bipolar II disorder (BD-II), and 502 healthy controls were recruited. Based on previous results from other populations, three SNPs (rs10848635, rs1006737, and rs4765905) were selected and genotype-wise association was evaluated using logistic regression analysis under additive, dominant and recessive genetic models. Results : rs10848635 showed a significant association with schizophrenia (p=0.010), the combined schizophrenia and BD group (p=0.018), and the combined schizophrenia and BD-I group (p=0.011). The best fit model was dominant model for all of these phenotypes. The association remained significant after correction for multiple testing in schizophrenia and the combined schizophrenia and BD-I group. Conclusion : We identified a possible role of CACNA1C in the common susceptibility of schizophrenia and BD-I. However no association trend was observed for BD-II. Further efforts are needed to identify a specific phenotype associated with this gene crossing the current diagnostic categories.

Comparison of Deep Learning Frameworks: About Theano, Tensorflow, and Cognitive Toolkit (딥러닝 프레임워크의 비교: 티아노, 텐서플로, CNTK를 중심으로)

  • Chung, Yeojin;Ahn, SungMahn;Yang, Jiheon;Lee, Jaejoon
    • Journal of Intelligence and Information Systems
    • /
    • v.23 no.2
    • /
    • pp.1-17
    • /
    • 2017
  • The deep learning framework is software designed to help develop deep learning models. Some of its important functions include "automatic differentiation" and "utilization of GPU". The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsoft's deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google's Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Google's Tensorflow, Microsoft's CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.

A study on the interrelation of influential factors in organizational conflict and organizational commitment (병원종사자의 조직갈등 및 조직몰입에 영향을 미치는 요인에 관한 연구)

  • Kim, Young-Hoon;Kim, Han-Joong;Cho, Woo-Hyun;Lee, Hae-Jong;Park, Chong-Yon;Lee, Sun-Hee
    • Korea Journal of Hospital Management
    • /
    • v.7 no.1
    • /
    • pp.41-63
    • /
    • 2002
  • The purpose of this study is to analyze the interrelation of influential factors in organizational conflict and organizational commitment. The data for this study were collected through a self-administered survey with a structured Questionnaire to 1,167 subjects from several nursing staff members, administration staff members and medical technicians of six hospitals. In this analysis frequency test, t-test, ANOVA, hierarchical multiple regression and structural equation model were used. The main findings of this study are as follows. 1. Factors which influence organizational conflict were analyzed. The type of occupation and the year of service were socio-demographic variables which influenced organizational conflict positively. Adjusted R square was 0.03. Perceptions on organizational structure and organizational culture were analyzed with two- level variables that were added. The findings were as follows. Adjusted R square increased to 0.25. The year of service, internal process culture and rational goal culture were positive variables. The design of organizational structure, human relations culture and open system culture were negative variables. 2. Variables which influence organizational commitment were analyzed. Age and the year of service were positive variables, while academic background based on high school education was a negative variable. Adjusted R square was 0.16. Perceptions on organizational structure and organizational culture were analyzed with two-level variables that were added. The findings were as follows. The characteristics of organizational structure, human relations culture and organizational culture were positive variables. Adjusted R square increased to 0.55. The variables of organizational conflict were added in 3 steps. Findings were as follows. The variables of hierarchical conflict showed negative influence and were included in two-level influential variables. Adjusted R square increased to 0.56. 3. Structural equation model was analyzed in order to examine the relation between organizational structure and the variables of organizational culture, organizational conflict and organizational commitment. Thirteen path coefficients out of seventeen path coefficients were significant. Age had negative influence on organizational conflict and positive influence on organizational commitment. The year of service had positive influence on organizational conflict and organizational commitment. The design of organizational structure, human relations culture and open system culture had negative influence on organizational. conflict. They had positive influence on organizational commitment. Internal process culture and rational goal culture had positive influence on organizational conflict. Organizational conflict had negative influence on organizational commitment. The squared multiple correlation of this model was 25.1% in organizational conflict and 52.7% in organizational commitment. The conclusion of this study is as follows. Factors in organizational structure and organizational culture, rather than socio-demographic factors, had a stronger influence on the organizational conflict and organizational commitment of hospitals. In order to decrease organizational conflict, to increase organizational commitment and to maximize the effectiveness of hospital management, it is necessary to understand the overall relation between organizational structure, organizational culture, organizational conflict and organizational commitment, with the effort of improving personalized factors and individual factors of organization management.

  • PDF

An Empirical Study on the Determinants of Supply Chain Management Systems Success from Vendor's Perspective (참여자관점에서 공급사슬관리 시스템의 성공에 영향을 미치는 요인에 관한 실증연구)

  • Kang, Sung-Bae;Moon, Tae-Soo;Chung, Yoon
    • Asia pacific journal of information systems
    • /
    • v.20 no.3
    • /
    • pp.139-166
    • /
    • 2010
  • The supply chain management (SCM) systems have emerged as strong managerial tools for manufacturing firms in enhancing competitive strength. Despite of large investments in the SCM systems, many companies are not fully realizing the promised benefits from the systems. A review of literature on adoption, implementation and success factor of IOS (inter-organization systems), EDI (electronic data interchange) systems, shows that this issue has been examined from multiple theoretic perspectives. And many researchers have attempted to identify the factors which influence the success of system implementation. However, the existing studies have two drawbacks in revealing the determinants of systems implementation success. First, previous researches raise questions as to the appropriateness of research subjects selected. Most SCM systems are operating in the form of private industrial networks, where the participants of the systems consist of two distinct groups: focus companies and vendors. The focus companies are the primary actors in developing and operating the systems, while vendors are passive participants which are connected to the system in order to supply raw materials and parts to the focus companies. Under the circumstance, there are three ways in selecting the research subjects; focus companies only, vendors only, or two parties grouped together. It is hard to find researches that use the focus companies exclusively as the subjects probably due to the insufficient sample size for statistic analysis. Most researches have been conducted using the data collected from both groups. We argue that the SCM success factors cannot be correctly indentified in this case. The focus companies and the vendors are in different positions in many areas regarding the system implementation: firm size, managerial resources, bargaining power, organizational maturity, and etc. There are no obvious reasons to believe that the success factors of the two groups are identical. Grouping the two groups also raises questions on measuring the system success. The benefits from utilizing the systems may not be commonly distributed to the two groups. One group's benefits might be realized at the expenses of the other group considering the situation where vendors participating in SCM systems are under continuous pressures from the focus companies with respect to prices, quality, and delivery time. Therefore, by combining the system outcomes of both groups we cannot measure the system benefits obtained by each group correctly. Second, the measures of system success adopted in the previous researches have shortcoming in measuring the SCM success. User satisfaction, system utilization, and user attitudes toward the systems are most commonly used success measures in the existing studies. These measures have been developed as proxy variables in the studies of decision support systems (DSS) where the contribution of the systems to the organization performance is very difficult to measure. Unlike the DSS, the SCM systems have more specific goals, such as cost saving, inventory reduction, quality improvement, rapid time, and higher customer service. We maintain that more specific measures can be developed instead of proxy variables in order to measure the system benefits correctly. The purpose of this study is to find the determinants of SCM systems success in the perspective of vendor companies. In developing the research model, we have focused on selecting the success factors appropriate for the vendors through reviewing past researches and on developing more accurate success measures. The variables can be classified into following: technological, organizational, and environmental factors on the basis of TOE (Technology-Organization-Environment) framework. The model consists of three independent variables (competition intensity, top management support, and information system maturity), one mediating variable (collaboration), one moderating variable (government support), and a dependent variable (system success). The systems success measures have been developed to reflect the operational benefits of the SCM systems; improvement in planning and analysis capabilities, faster throughput, cost reduction, task integration, and improved product and customer service. The model has been validated using the survey data collected from 122 vendors participating in the SCM systems in Korea. To test for mediation, one should estimate the hierarchical regression analysis on the collaboration. And moderating effect analysis should estimate the moderated multiple regression, examines the effect of the government support. The result shows that information system maturity and top management support are the most important determinants of SCM system success. Supply chain technologies that standardize data formats and enhance information sharing may be adopted by supply chain leader organization because of the influence of focal company in the private industrial networks in order to streamline transactions and improve inter-organization communication. Specially, the need to develop and sustain an information system maturity will provide the focus and purpose to successfully overcome information system obstacles and resistance to innovation diffusion within the supply chain network organization. The support of top management will help focus efforts toward the realization of inter-organizational benefits and lend credibility to functional managers responsible for its implementation. The active involvement, vision, and direction of high level executives provide the impetus needed to sustain the implementation of SCM. The quality of collaboration relationships also is positively related to outcome variable. Collaboration variable is found to have a mediation effect between on influencing factors and implementation success. Higher levels of inter-organizational collaboration behaviors such as shared planning and flexibility in coordinating activities were found to be strongly linked to the vendors trust in the supply chain network. Government support moderates the effect of the IS maturity, competitive intensity, top management support on collaboration and implementation success of SCM. In general, the vendor companies face substantially greater risks in SCM implementation than the larger companies do because of severe constraints on financial and human resources and limited education on SCM systems. Besides resources, Vendors generally lack computer experience and do not have sufficient internal SCM expertise. For these reasons, government supports may establish requirements for firms doing business with the government or provide incentives to adopt, implementation SCM or practices. Government support provides significant improvements in implementation success of SCM when IS maturity, competitive intensity, top management support and collaboration are low. The environmental characteristic of competition intensity has no direct effect on vendor perspective of SCM system success. But, vendors facing above average competition intensity will have a greater need for changing technology. This suggests that companies trying to implement SCM systems should set up compatible supply chain networks and a high-quality collaboration relationship for implementation and performance.

The Relationship Between DEA Model-based Eco-Efficiency and Economic Performance (DEA 모형 기반의 에코효율성과 경제적 성과의 연관성)

  • Kim, Myoung-Jong
    • Journal of Environmental Policy
    • /
    • v.13 no.4
    • /
    • pp.3-49
    • /
    • 2014
  • Growing interest of stakeholders on corporate responsibilities for environment and tightening environmental regulations are highlighting the importance of environmental management more than ever. However, companies' awareness of the importance of environment is still falling behind, and related academic works have not shown consistent conclusions on the relationship between environmental performance and economic performance. One of the reasons is different ways of measuring these two performances. The evaluation scope of economic performance is relatively narrow and the performance can be measured by a unified unit such as price, while the scope of environmental performance is diverse and a wide range of units are used for measuring environmental performances instead of using a single unified unit. Therefore, the results of works can be different depending on the performance indicators selected. In order to resolve this problem, generalized and standardized performance indicators should be developed. In particular, the performance indicators should be able to cover the concepts of both environmental and economic performances because the recent idea of environmental management has expanded to encompass the concept of sustainability. Another reason is that most of the current researches tend to focus on the motive of environmental investments and environmental performance, and do not offer a guideline for an effective implementation strategy for environmental management. For example, a process improvement strategy or a market discrimination strategy can be deployed through comparing the environment competitiveness among the companies in the same or similar industries, so that a virtuous cyclical relationship between environmental and economic performances can be secured. A novel method for measuring eco-efficiency by utilizing Data Envelopment Analysis (DEA), which is able to combine multiple environmental and economic performances, is proposed in this report. Based on the eco-efficiencies, the environmental competitiveness is analyzed and the optimal combination of inputs and outputs are recommended for improving the eco-efficiencies of inefficient firms. Furthermore, the panel analysis is applied to the causal relationship between eco-efficiency and economic performance, and the pooled regression model is used to investigate the relationship between eco-efficiency and economic performance. The four-year eco-efficiencies between 2010 and 2013 of 23 companies are obtained from the DEA analysis; a comparison of efficiencies among 23 companies is carried out in terms of technical efficiency(TE), pure technical efficiency(PTE) and scale efficiency(SE), and then a set of recommendations for optimal combination of inputs and outputs are suggested for the inefficient companies. Furthermore, the experimental results with the panel analysis have demonstrated the causality from eco-efficiency to economic performance. The results of the pooled regression have shown that eco-efficiency positively affect financial perform ances(ROA and ROS) of the companies, as well as firm values(Tobin Q, stock price, and stock returns). This report proposes a novel approach for generating standardized performance indicators obtained from multiple environmental and economic performances, so that it is able to enhance the generality of relevant researches and provide a deep insight into the sustainability of environmental management. Furthermore, using efficiency indicators obtained from the DEA model, the cause of change in eco-efficiency can be investigated and an effective strategy for environmental management can be suggested. Finally, this report can be a motive for environmental management by providing empirical evidence that environmental investments can improve economic performance.

  • PDF