• Journal of information and communication convergence engineering
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• v.14 no.2
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• pp.115-121
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• 2016

Currently there is a lack of literature on SPICE-level models of double-gate (DG) tunnel field-effect transistors (TFETs). A DG TFET compact model is presented in this work that is used to develop a SPICE model for DG TFETs implemented with Verilog-A language. The compact modeling approach presented in this work integrates several issues in previously published compact models including ambiguity about the use of tunneling parameters A_k and B_k, and the use of a universal equation for calculating the surface potential of DG TFETs in all regimes of operation to deliver a general SPICE modeling procedure for DG TFETs. The SPICE model of DG TFET captures the drain current-gate voltage (I_ds-V_gs) characteristics of DG TFET reasonably well and offers a definite computational advantage over TCAD. The general SPICE modeling procedure presented here could be used to develop SPICE models for any combination of structural parameters of DG TFETs.

• Korea Journal of Hospital Management
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• v.2 no.1
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• pp.137-161
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• 1997

This study purports to investigate the determinants of propensity to stay among nursing staff working at Korean hospitals. The independent variables contains three groups of determinants: environmental variables(job opportunity, spouse support, and parent support), psychological variables(met expectations, work involvement, positive affectivity, and negative affectivity), and structural variables(job autonomy, work unit control. routinization, supervisor support, coworker support, role ambiguity, role conflict, workload, resource inadequacy, distributive justice, promotional chances. job security, job hazards, and pay). The sample used in this study consisted of 329 nurses and 175 nurse aides from two university hospitals in Seoul and its surburbs. Data were collected with self-administered questionnaires and analyzed using path analysis. The results of this study indicate that: (1) the following variables, listed in order of size, have significant positive effects on propensity to stay among hospital nursing staff: job satisfaction, met expectations, supervisor support, job security, and positive affectivity, (2) the following variables, listed in order of size, have significant negative total effects on propensity to stay among hospital nursing staff: job opportunity, negative affectivity, and rutinization, (3) the model explains 44.2 percent of the variance in propensity to stay among nursing staff working at two university hospitals, and (4) managerial support for improving the job autonomy, distributive justice, and promotional opportunity for nurse aides are needed.

• Journal of KIISE:Software and Applications
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• v.28 no.5
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• pp.448-448
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• 2001

The definitions in Korean dictionary not only describe meanings of title, but also include various semantic information such as hypernymy/hyponymy, meronymy/holonymy, polysemy, homonymy, synonymy, antonymy, and semantic features. This paper purposes to implement a parser as the basic tool to acquire automatically the semantic information from the definitions in Korean dictionary. For this purpose, first we constructed the part-of-speech tagged corpus and the tree tagged corpus from the definitions in Korean dictionary. And then we automatically extracted from the corpora the frequency of words which are ambiguous in part-of-speech tag and the grammar rules and their probability based on the statistical method. The parser is a kind of the probabilistic chart parser that uses the extracted data. The frequency of words which are ambiguous in part-of-speech tag and the grammar rules and their probability resolve the noun phrase's structural ambiguity during parsing. The parser uses a grammar factoring, Best-First search, and Viterbi search In order to reduce the number of nodes during parsing and to increase the performance. We experiment with grammar rule's probability, left-to-right parsing, and left-first search. By the experiments, when the parser uses grammar rule's probability and left-first search simultaneously, the result of parsing is most accurate and the recall is 51.74% and the precision is 87.47% on raw corpus.

• Journal of Environmental Health Sciences
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• v.46 no.4
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• pp.410-422
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• 2020

Objectives: According to the Act on Registration, Evaluation, Etc. of Chemicals, new and existing chemicals must be registered by 2030. In addition, industries need to submit hazard data as an attachment during the registration process. Therefore, we constructed a nationwide chemical database to support small industry by providing hazard data and original sources. During the process, we developed a new standard procedure for minimizing errors and increasing reliability. Methods: We analyzed the categories of errors and the cause of the errors through the verification results of the 2019 project. We present an improved database construction methodology and system. Results: Errors are categorized according to their causative factors into simple, technical, and structural type errors. Simple errors arise simply because of decreased concentration or negligence in following the instructions. Technical errors are caused by a discrepancy between the professional field and the type of data. Structural errors indicate systemic errors such as incomplete forms on the excel database or ambiguity in the guidelines. Lessons from the errors collected in the 2019 project are used to update the procedures for database authorization and technical guidelines. The main update points are as follows; 'supplementation of review process', 'giving regular training to external reviewers', 'giving additional information to authors, like physico-chemical properties of substances, degradability, etc.', 'amendment of excel form', and 'guideline upgrades'. Conclusions: We conducted this study with the aim of improving the accuracy and reliability of the database of hazard information for chemical substances. The new procedures and guidelines are now being used in the 2020 project for construction of a hazard information database for Korea.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.615-618
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• 2003

The design process of a relational database system consists of requirement analysis, conceptual design using ER diagram, logical design, and physical design. In logical design process, the conceptual schema is transformed to relational schema, and relational schema is normalized. This traditional design process is hard to applied in real database design process, since there is an ambiguity in conceptual design process. In this paper, we suggest a new design process, which provides more structural design steps by removing the conceptual design process. In new approach, we produce the data flow diagram by the structural methodology. From the attributes in the data store of data flow diagram, we construct relational table schema, and we normalize relational schema. Finally we produced table relationship diagram in order to figure out relationships between tables.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.81-92
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• 2003

Generalized LR parsing is one of the enhanced LR parsing methods so that it overcome the limit of one-way linear stack of the traditional LR parser using graph-structured stack, and it has been playing an important role of a firm starting point to generate other variations for NL parsing equipped with various mechanisms. In this paper, we propose a conditional Action Model that can solve the problems of conventional probabilistic GLR methods. Previous probabilistic GLR parsers have used relatively limited contextual information for disambiguation due to the high complexity of internal GLR stack. Our proposed model uses Surface Phrasal Types representing the structural characteristics of the parse for its additional contextual information, so that more specified structural preferences can be reflected into the parser. Experimental results show that our GLR parser with the proposed Conditional Action Model outperforms the previous methods by about 6-7% without any lexical information, and our model can utilize the rich stack information for syntactic disambiguation of probabilistic LR parser.

• Korean Journal of Social Welfare Studies
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• v.42 no.4
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• pp.187-216
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• 2011

This study examined the effects of elderly care facility social workers' work environment (role conflict, role ambiguity, role overload, and adequacy of the reward system) and personal tendency (emotional empathy, cognitive empathy, external attribution, and internal attribution) on their burnout (emotional burnout, low personal achievement, and depersonalization about clients) and suggested strategies for preventing burnout in social workers at elderly care facilities. For this purpose, we conducted a questionnaire survey of social workers working at institutions designated as elderly long-term care facilities and collected a total of 312 questionnaires. According to the results of analyzing the data using a structural equation model, among the sub-factors of work environment, role ambiguity had a significant positive effect on low personal achievement and depersonalization about clients, role conflict on emotional burnout, and role overload on depersonalization about clients. Among the sub-factors of personal tendency, cognitive empathy and internal attribution had a significant negative effect on low personal achievement, and external attribution had a significant positive effect on emotional burnout and depersonalization about clients. This study is meaningful in that it illuminated social workers' burnout not only from the aspect of work environment but also from that of personal tendency.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.369-383
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• 2011

The purpose of this study was to investigate the determinants of intent to leave among IT industry employees, based on the Price's structural model of employee turnover. The sample used in this study were composed of 370 employees from 10 IT firms located in Seoul and Gyeonggi-Do. Data were collected with self-administered questionnaires and analyzed using structural equation modelling technique. This study found that four task reward variables(job variety, job autonomy, job challenge, and role ambiguity), two social reward variables (supervisory support and coworker support), three organizational reward variables(promotional chances, job security, and distributive justice) and one environmental variable(job opportunity), had significant effects on IT industry employees' intent to leave in terms of total effects and his directions of those significant effects were consistent with theoretical predictions; and that two mediating variables, job satisfaction and organizational commitment had the most important effects on IT industry employees' intent to leave in terms of total effects. The theoretical and practical implications of the research findings were discussed and the directions for future research were suggested.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.12 s.148
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• pp.1571-1581
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• 2005

In a highly competitive marketplace, U.S. retailers are challenged to attract, recruit, and retain a skilled workforce. The purpose of our research was to examine the impact of young retail employees' work experiences on their job performance, job satisfaction, and career intention using a comprehensive approach to model development. The model was developed in three phases over a four-year period using both qualitative and quantitative methodologies. During Phase 1, we conducted focus group interviews to guide the development of the questionnaire. Work experience was initially operationalized as role conflict, role ambiguity, supervisory support, and work involvement. Using a student sample(n=470) from U.S. universities, we employed multiple regression to determine the significance of relationships between their work experience, job satisfaction, and retail career intention. During Phase 2, we expanded our investigation to include retail work experiences of teens employed while they were in high school. The teen sample(n=898) was drawn from students enrolled in work-study programs in 16 U.S. high schools, and data were analyzed using structural equation modeling (hereafter SEM). During Phase 3, we expanded our model to include two new variables, job characteristics and job performance. Based on a national sample(n=803) of U.S. university students, we employed SEM to holistically determine if retail employees' work experience impacted their job performance, job satisfaction, and retail career intention. During each phase, job satisfaction consistently was the superior antecedent of retail career intention. Among the work experience variables, supervisory support had a positive impact on job satisfaction, while role conflict, role ambiguity, and work involvement exhibited inconsistent effects on job outcomes. The strong relationship between job satisfaction and retail career intention should make job satisfaction a priority for retailers.

• Journal of Convergence for Information Technology
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• v.10 no.9
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• pp.123-135
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• 2020

Recently organizations are implementing strict security policies and technologies to minimize security incidents. However, strict information security can cause work stress of employees and can make it difficult to achieve security goals. The purpose of this study is to present the preconditions for mitigating the negative impact of security-related work stress. We conducted a questionnaire survey of employees working in the financial industry and secured a total of 266 samples. The test of the research hypothesis was carried out by structural equation modeling. As a result, work stress had a negative effect on compliance intention, and value congruence reduced work stress. Also, security feedback had a moderating effect on the relationship between research factors. The results have theoretical and practical implications for mitigating work stress of employees.