• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.291-298
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• 2022

In this paper, we present a method for dependency parsing with chunking in Korean. Dependency parsing is a task of determining a governor of every word in a sentence. In general, we used to determine the syntactic governor in Korean and should transform the syntactic structure into semantic structure for further processing like semantic analysis in natural language processing. There is a notorious problem to determine whether syntactic or semantic governor. For example, the syntactic governor of the word "먹고 (eat)" in the sentence "밥을 먹고 싶다 (would like to eat)" is "싶다 (would like to)", which is an auxiliary verb and therefore can not be a semantic governor. In order to mitigate this somewhat, we propose a Korean dependency parsing after chunking, which is a process of segmenting a sentence into constituents. A constituent is a word or a group of words that function as a single unit within a dependency structure and is called a chunk in this paper. Compared to traditional dependency parsing, there are some advantage of the proposed method: (1) The number of input units in parsing can be reduced and then the parsing speed could be faster. (2) The effectiveness of parsing can be improved by considering the relation between two head words in chunks. Through experiments for Sejong dependency corpus, we have shown that the USA and LAS of the proposed method are 86.48% and 84.56%, respectively and the number of input units is reduced by about 22%p.

• Research in Community and Public Health Nursing
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• v.8 no.2
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• pp.277-288
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• 1997

The purpose of this study is to identify the behavioral subsystems of the obese adult and contribute to the utility of Johnson's Behavioral System Model. The subjects were 167 obese adults in out-patients clinics of 2 hospitals and health clinics for 4 companies. These data were collected by a structured questionnaire with 52 items from July 1 to Sep. 30, 1995. The instrument used for this study was modified from the DBSM -self reporting instrument (1983) and Grubbs(1980)'s. The reliability of this method was cronbach's ${\alpha}$=.8476 and the construct validity of it was accepted by using a factor analysis. These data were analyzed by frequency, percentage, mean, standard deviation, factor analysis, pearson's correlation coefficient, Kruskal-Wallis with an SPSS PC+ Program. The results of this study were as follows: 1. The 9 behavioral subsystems of the obese were indentified : sex-related, attachment-affiliative I(social), dependency, ingestive, eliminative, restorative, aggressive-protective, attachment-affiliative and II (familial), an achievement behavioral subsystem. 2. Out of 9 subsystems, the highest significant positive correlation between dependency and acheivement subsystem was found(r=.5357, p<.01), The next, attachment-affiliative I and attachment-affiliative II subsystem was correlated significantly (r=.4526, p<.01). Significant positive correlations among sex-related, achivement, attachment-affiliative I, II, dependency, restorative, and aggressive-protective subsystems were found. But, ingestive and eliminative subsystems were not correlated with the above seven subsystems significantly, only the positive correlation between the ingestive and eliminative subsystems was found. 3. The explained variance of the 9 subsystems was explained as 56.1% out of a total of one. The sex-related subsystem was the first factor explaining 16.3% of the total variance and then the next 8 factors which resulted in 39.8%. According to the results of this study, the suggestions were as follows: 1. In the nursing practice, nursing assessmentand intervention of the obese should be in cluded not only in ingestive and eliminative subsystems but also in sex-related, attachment-affiliative I, dependency, restorative, aggressive-protective, attachment -affiliative II, and achievement behavioral subsystem. 2. Concerning instruments, some items to measure the eliminative, dependency, and aggressive-protective behavioral subsystems with relatively reliability are needed. 3. Johnson's concept of a dependency subsystem should be clarified. 4. Correlation among the 7 subsystems, and the ingestive and eliminative subsystems should be clarified.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.316-321
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• 2007

We propose a quatitative annotation method for edges in Bayesian networks using given sets of condition-specific data. Bayesian network model has been used widely in various fields to infer probabilistic dependency relationships between entities in target systems. Besides the need for identifying dependency relationships, the annotation of edges in Bayesian networks is required to analyze the meaning of learned Bayesian networks. We assume the training data is composed of several condition-specific data sets. The contribution of each condition-specific data set to each edge in the learned Bayesian network is measured using the ratio of likelihoods between network structures of including and missing the specific edge. The proposed method can be a good approach to make quantitative annotation for learned Bayesian network structures while previous annotation approaches only give qualitative one.

• Human Ecology Research
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• v.58 no.4
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• pp.601-611
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• 2020

This study examined the effects of negative parenting attitudes on adolescents' academic helplessness through the mediating effects of social withdrawal and smartphone dependency. Data from the panel study of Korean Children and Youth Panel Survey 2018 (KCYPS 2018) collected by the National Youth Policy Institute (NYPI) was used to examine the research model. The subjects of the study consisted of 2,541 first grade middle school students (1,375 boys and 1,166 girls). Confirmatory factor analysis [CFA], structural equation modeling [SEM], and bootstrapping analysis were conducted by means of SPSS 25.0, AMOS 25.0, and Hayes's PROCESS programs to examine the serial multiple mediating effects. The study results were as follows. First, negative parenting attitude had a direct effect on adolescents' academic helplessness. This implies that adolescents who perceive their parents' attitudes to be high in coercive, rejective, and chaotic levels indicate that they can easily get exhausted in academic settings. Second, negative parenting attitudes had an indirect effect on adolescents' academic helplessness through social withdrawal and smartphone dependency. The results suggest that a high level of negative parenting attitude leads to higher social withdrawal and smartphone dependency that influences adolescents' academic helplessness.

• Journal of Korean Clinical Nursing Research
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• v.28 no.2
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• pp.198-209
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• 2022

Purpose: The purpose of the study was to shorten the KPCS-1 (Korean Patient Classification System-1) for predicting nursing care need level and to explore whether the patients can be clustered by their acuity and dependency. Methods: The participants were inpatients in two surgical wards and two internal medicine wards at a teritory hospital during 14 days investigations. The KPCS-1 was evaluated once a day for all inpatients and 2,082 cases of data from a total of 411 patients were analyzed. Results: The items were reducted from 50 items to 26 items by partial least squares analysis and expert review. Through factor analysis, it was confirmed that hygiene, diet, elimination, and exercise were categorized as dependence factors. Patients were clustered with low acuity/low dependency (average score: 7.68±2.81/1.05±1.33), high acuity/low dependency (average score: 17.20±4.15/1.94±2.40), medium acuity/high dependency (average score: 13.56±5.30/9.66±2.64) through cluster analysis. The total score of the three groups for their nursing care needs was 8.73±3.36, 19.14±5.74, and 23.24±6.31 in order, and the results showed a statistically significant difference (F=1712.12, p<.001). Conclusion: The shortening of the KPCS-1 and the new criteria for categorizing patients according to acuity and dependence will increase clinical utility and be useful for manpower assignment criteria in detail.

• 한국노년학
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• v.29 no.3
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• pp.1183-1196
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• 2009

The purpose of this study was to investigate the influences of characteristics of the long-term care elderly and caregivers on caregivers' stress. The data of this study were collected from 105 long-term care elderly caregivers with 3 grade in Pusan, Daegu, and Gyung-buk area. The results showed that each stress of caregivers was influenced by diverse characteristics in various ways. Time-dependent stress of caregivers was influenced by elderly dependency and caregivers' health. Self-development stress of caregivers was influenced by elderly dependency, caregivers' health, caregivers' age, and relationship quality. Physical stress of caregivers was influenced by elderly dependency and caregivers' health. Social stress of caregivers was influenced by elderly dependency, caregivers' health, and relationship quality. Emotional stress of caregivers was influenced by relationship quality between the elderly and caregivers. These results indicated that the caregivers' stress was influenced not only physical characteristics of the elderly and the caregivers but also relational characteristics.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.79-86
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• 2021

In order to increase the probability of success in big data projects, quantified techniques are required to analyze the root cause of risks from complex causes and establish optimal countermeasures. To this end, this study measures risk factors and relationships through SNA analysis and presents a way to respond to risks based on them. In other words, it derives a dependency network matrix by utilizing the results of correlation analysis between risk groups in the big data projects presented in the preliminary study and performs SNA analysis. In order to derive the dependency network matrix, partial correlation is obtained from the correlation between the risk nodes, and activity dependencies are derived by node by calculating the correlation influence and correlation dependency, thereby producing the causal relationship between the risk nodes and the degree of influence between all nodes in correlation. Recognizing the root cause of risks from networks between risk factors derived through SNA between risk factors enables more optimized and efficient risk management. This study is the first to apply SNA analysis techniques in relation to risk management response, and the results of this study are significant in that it not only optimizes the sequence of risk management for major risks in relation to risk management in IT projects but also presents a new risk analysis technique for risk control.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2196-2203
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• 2000

As processor's operational frequency increases and processors execute multiple instructions per cycle, the processor performance becomes more dependent on the load operand referencing latency and the data dependency. To reduce the operand fetch latency and to increase ILP by breaking the data dependency, we propose a value-address hybrid predictor using a reasonable size prediction buffer and analyse the performance improvement by the proposed predictor. Through the extensive simulation of 5 benchmark programs, the proposed hybrid prediction scheme accurately predicts 62.72% of all loads which are 12.64% higher than the value prediction scheme and show its cost-effectiveness compared to the address predition scheme. In addition, we analyse the performance improvement achieved by the stride management and the history of previous predictions.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.410-415
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• 2005

Recent measurements of local-area and wide-area traffic have shown that network traffic exhibits at a wide range of scales - Self-similarity. Self-similarity is expressed by long term dependency, this is contradictory concept with Poisson model that have relativity short term dependency. Therefore, first of all for design and dimensioning of next generation communication network, traffic model that are reflected burstness and self-similarity is required. Here self-similarity can be characterized by Hurst parameter. In this paper, when different many data traffic being integrated under various environments is arrived to communication network, Hurst Parameter's change is analyzed and compared with simulation results.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1997.11a
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• pp.79-89
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• 1997

Logic programming has many advantages as a paradigm for parallel programming because it offers ease of programming while retaining high expressive power due to its declarative semantics. In parallel logic programming, one of the important issues is the compile-time parallelism detection. Static data-dependency analysis has been widely used to gather some information needed for the detection of AND-parallelism. However, the static data-dependency analysis cannot fully detect AND-parallelism because it does not provide some necessary functions such as the propagation of groundness. As an alternative approach, abstract interpretation provides a promising way to deal with AND-parallelism detection, while a full-blown abstract interpretation is not efficient in terms of computation since it inherently employs some complex operations not necessary for gathering the information on AND-parallelism. In this paper, we propose an abstract domain which can provide a precise and efficient way to use the abstract interpretation for the detection of AND-parallelism of logic programs.