• Journal of Preventive Medicine and Public Health
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• v.47 no.5
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• pp.258-265
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• 2014

Objectives: To examine whether the nursing practice environment at the hospital-level affects the job satisfaction and turnover intention of hospital nurses. Methods: Among the 11 731 nurses who participated in the Korea Health and Medical Workers' Union's educational program, 5654 responded to our survey. Data from 3096 nurses working in 185 general inpatient wards at 60 hospitals were analyzed using multilevel logistic regression modeling. Results: Having a standardized nursing process (odds ratio [OR], 4.21; p<0.001), adequate nurse staffing (OR, 4.21; p<0.01), and good doctor-nurse relationship (OR, 4.15; p<0.01), which are hospital-level variables based on the Korean General Inpatients Unit Nursing Work Index (KGU-NWI), were significantly related to nurses' job satisfaction. However, no hospital-level variable from the KGU-NWI was significantly related to nurses' turnover intention. Conclusions: Favorable nursing practice environments are associated with job satisfaction among nurses. In particular, having a standardized nursing process, adequate nurse staffing, and good doctor-nurse relationship were found to positively influence nurses' job satisfaction. However, the nursing practice environment was not related to nurses' turnover intention.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5244-5259
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• 2019

With the continuous development of LBS (Location Based Service) applications, privacy protection has become an urgent problem to be solved. Differential privacy technology is based on strict mathematical theory that provides strong privacy guarantees where it supposes that the attacker has the worst-case background knowledge and that knowledge has been applied to different research directions such as data query, release, and mining. The difficulty of this research is how to ensure data availability while protecting privacy. Spatial multidimensional data are usually released by partitioning the domain into disjointed subsets, then generating a hierarchical index. The traditional data-dependent partition methods need to allocate a part of the privacy budgets for the partitioning process and split the budget among all the steps, which is inefficient. To address such issues, a novel two-step partition algorithm is proposed. First, we partition the original dataset into fixed grids, inject noise and synthesize a dataset according to the noisy count. Second, we perform IH-Tree (Improved H-Tree) partition on the synthetic dataset and use the resulting partition keys to split the original dataset. The algorithm can save the privacy budget allocated to the partitioning process and obtain a more accurate release. The algorithm has been tested on three real-world datasets and compares the accuracy with the state-of-the-art algorithms. The experimental results show that the relative errors of the range query are considerably reduced, especially on the large scale dataset.

• Journal of Convergence for Information Technology
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• v.10 no.7
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• pp.1-6
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• 2020

A new resource management algorithm is proposed for 5G networks which have a coordinated network architecture. By sharing the contol information among multiple neighbor cells and managing in centralized structure, the propsed algorithm fully utilizes the benefits of network coordination to increase fairness and throughput at the same time. This optimization of network performance is achieved while operating within a tolerable amount of signaling overhead and computational complexity. Simulation results confirm that the proposed scheme improve the network capacity up to 40% for cell edge users and provide network-wise fairness as much as 23% in terms of the well-knwon Jain's Fainess Index.

• The Journal of Korean Society for School & Community Health Education
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• v.18 no.3
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• pp.45-53
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• 2017

Objectives: This study aimed to analyze the association between adolescent depression and personal factors such as interpersonal relationship and personal characteristics. Methods: The data used for this study was taken from the 2014 Korean Children and Youth Panel Survey. Of those 2,351 subjects in a data set, data of 1,938 subjects were analyzed after excluding 413 subjects with missing information. Hierarchical regression analysis was conducted for multi-variate analysis. In addition, controlling effects of ego-resiliency was analyzed. SPSS 22.0. was utilized for statistical analyses. Results: The study found that the depressive index was higher in women than men, and lower in adolescent who has a good relationship with parents and friends. This study also found that adolescents with high ego-resiliency are more vulnerable to depression. Conclusions: It is recommended to understand and to utilize ego-resiliency of adolescents, in order to reduce adolescents depression. Promoting good relationship with parents and friends will also positively impact to lower adolescents depression.

• Safety and Health at Work
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• v.10 no.3
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• pp.341-346
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• 2019

Background: Although the concept of workload is important to nursing practice, only a few nursing researchers have focused on the issue of workload within the nursing context. Knowledge of how the dynamics of workload affects the job stress of nurses working in a specific unit or department in a hospital setting, and the influence of coworker support on this relationship, still remains limited. This study, therefore examined the effect of workload on job stress of Ghanaian outpatient department nurses and the moderating effect of coworker support on this relationship. Methods: A cross-sectional survey design was used, and questionnaire was used to collect data from a sample of 216 outpatient department nurses from four major hospitals in Ghana. The data collected measured workload, job stress, and coworker support using National Aeronautics and Space Administration (NASA) Task Load Index, job stress scale, and coworker support scale, respectively. Data were analysed using descriptive statistics, correlation, and hierarchical regression. Results: High levels of workload were associated with high levels of job stress of the nurses. Also, higher levels of workload were related to higher levels of job stress for nurses who received high levels of coworker support, but this was not the case for those who received low levels of coworker support (reserve buffering effect). Conclusion: The finding reiterates the adverse effect of workloads on employees' health, and the reverse buffering effect implies that supporting a colleague at work should be conveyed in a positive manner devoid of negative appraisal.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.63-77
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• 2011

The World Wide Web is a very large distributed digital information space. From its origins in 1991, the web has grown to encompass diverse information resources as personal home pasges, online digital libraries and virtual museums. Some estimates suggest that the web currently includes over 500 billion pages in the deep web. The ability to search and retrieve information from the web efficiently and effectively is an enabling technology for realizing its full potential. With powerful workstations and parallel processing technology, efficiency is not a bottleneck. In fact, some existing search tools sift through gigabyte.syze precompiled web indexes in a fraction of a second. But retrieval effectiveness is a different matter. Current search tools retrieve too many documents, of which only a small fraction are relevant to the user query. Furthermore, the most relevant documents do not nessarily appear at the top of the query output order. Also, current search tools can not retrieve the documents related with retrieved document from gigantic amount of documents. The most important problem for lots of current searching systems is to increase the quality of search. It means to provide related documents or decrease the number of unrelated documents as low as possible in the results of search. For this problem, CiteSeer proposed the ACI (Autonomous Citation Indexing) of the articles on the World Wide Web. A "citation index" indexes the links between articles that researchers make when they cite other articles. Citation indexes are very useful for a number of purposes, including literature search and analysis of the academic literature. For details of this work, references contained in academic articles are used to give credit to previous work in the literature and provide a link between the "citing" and "cited" articles. A citation index indexes the citations that an article makes, linking the articleswith the cited works. Citation indexes were originally designed mainly for information retrieval. The citation links allow navigating the literature in unique ways. Papers can be located independent of language, and words in thetitle, keywords or document. A citation index allows navigation backward in time (the list of cited articles) and forwardin time (which subsequent articles cite the current article?) But CiteSeer can not indexes the links between articles that researchers doesn't make. Because it indexes the links between articles that only researchers make when they cite other articles. Also, CiteSeer is not easy to scalability. Because CiteSeer can not indexes the links between articles that researchers doesn't make. All these problems make us orient for designing more effective search system. This paper shows a method that extracts subject and predicate per each sentence in documents. A document will be changed into the tabular form that extracted predicate checked value of possible subject and object. We make a hierarchical graph of a document using the table and then integrate graphs of documents. The graph of entire documents calculates the area of document as compared with integrated documents. We mark relation among the documents as compared with the area of documents. Also it proposes a method for structural integration of documents that retrieves documents from the graph. It makes that the user can find information easier. We compared the performance of the proposed approaches with lucene search engine using the formulas for ranking. As a result, the F.measure is about 60% and it is better as about 15%.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.864-881
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• 2021

Purpose: This study aims is to provide a total care solution preventing disaster based on Big Data and AI technology and to service safety considered by individual situations and various risk characteristics. The purpose is to suggest a method that customized comprehensive index services to prevent and respond to safety accidents for calculating the living safety index that quantitatively represent individual safety levels in relation to daily life safety. Method: In this study, we use method of mixing AHP(Analysis Hierarchy Process) and Likert Scale that extracted from consensus formation model of the expert group. We organize evaluation items that can evaluate life safety prevention services into risk indicators, vulnerability indicators, and prevention indicators. And We made up AHP hierarchical structure according to the AHP decision methodology and proposed a method to calculate relative weights between evaluation criteria through pairwise comparison of each level item. In addition, in consideration of the expansion of life safety prevention services in the future, the Likert scale is used instead of the AHP pair comparison and the weights between individual services are calculated. Result: We obtain result that is weights for life safety prevention services and reflected them in the individual risk index calculated through the artificial intelligence prediction model of life safety prevention services, so the comprehensive index was calculated. Conclusion: In order to apply the implemented model, a test environment consisting of a life safety prevention service app and platform was built, and the efficacy of the function was evaluated based on the user scenario. Through this, the life safety index presented in this study was confirmed to support the golden time for diagnosis, response and prevention of safety risks by comprehensively indication the user's current safety level.

• Journal of Environmental Impact Assessment
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• v.26 no.2
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• pp.160-170
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• 2017

The purpose of this study is to perform clustering of the habitat types and to identify the characteristics of species in the habitat types using mammal data (70,562) of the 3rd National Ecosystem Survey conducted from 2006 to 2012. The 15 habitat types recorded in the field-paper of the 3rd National ecosystem survey were reclassified, which was followed by the statistical analysis of mammal habitat types. In the habitat types cluster analysis, non-hierarchical cluster analysis (k-means cluster analysis), hierarchical cluster analysis, and non-metric multidimensional scaling method were applied to 14 habitat types recorded more than 30 times. A total of 7 Orders, 16 Families, and 39 Species of mammals were identified in the 3rd National Ecosystem Survey collected nationwide. When 11 clusters were classified by habitat types, the simple structure index was the highest (ssi = 0.07). As a result of the similarities and hierarchies between habitat types suggested by the hierarchical clustering analysis, the residential areas were the most different habitat types for mammals; the next following type was a cluster together with rivers and coasts. The results of the non-metric multidimensional scaling analysis demonstrated that both Mus musculus and Rattus norvegicus restrictively appeared in a residential area, which is the most discriminating habitat type. Lutra lutra restrictively appeared in coastal and river areas. In summary, according to our results, the mammalian habitat can be divided into the following four types: (1) the forest type (using forest as the main habitat and migration route); (2) the river type (using water as the main habitat); (3) the residence habitat (living near residential area); and (4) the lowland type (consuming grain or seeds as the main feeding resource).

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.399-406
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• 2002

The goal of this research has been to develop an adaptive user agent for web surfing. To achieve this goal, the research has concentrated on three issues: collection of user data, construction and improvement of user profile, and adaptation by applying the user profile. The main outcome from the research is a prototype system that provides the functional definition and componential design scheme for an adaptive user agent for the web environment. Internally, the system achieves its operational goal from the cooperation of two independent agents. They are IIA (Interactive Interface Agent) and UPA (User Profiling Agent). As a tool for providing a user-friendly interface environment, the IIA employs the Keyword Index, which is a list of index terms of a webpage as well as a keyword menu for subsequent queries, and the Suggest Link, which is a hierarchical list of URLs showing the past browsing procedure of the user. The UPA reflects in the User Profile, both the static and the dynamic information obtained from the user's browsing behavior. In particular, a user's interests are represented in the form of Interest Vectors which, based on the similarity of the vectors, is subject to update and creation, thus dynamically profiling the user's ever-shifting interests.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.7078-7088
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• 2015

This study examined effects of health behaviors and sleep related factor on cognitive function in the elderly hypertensive patients. Data were collected through a face to face interview survey with structured questionnaire form 140 elderly with hypertension ($age{\geq}65years$) from February 5 to May 1, 2013. Research instruments included Pittsburgh Sleep Quality Index(PSQI), Epworth Sleepiness Scale(ESS) and Korean version the Mini-Mental State Examination(MMSE-K). Cognitive function was negatively related to degradation in quality of sleep(r=-.29, p<.001). Sleep duration were negatively related to body mass index(r=-.18, p=.032) and degradation in quality of sleep(r=-.59, p<.001). Sleep duration was positively related to daytime sleepiness(r=.22, p=.008). Hierarchical multiple regression showed that age, education levels and living arrangement were associated with cognitive function(F=8.56, p<.001, Adjusted $R^2=.14$). After controlling for demographic characteristics and health behaviors, degradation in quality of sleep(${\beta}=-.27$, p=.008) was identified as significant predictors of cognitive function. This final model explained 17.0% of the cognitive function in the elderly hypertensive patients(F=4.09, p<.001). Therefore, as a strategy improving cognitive function of the elderly with hypertension, therapeutic intervention should be developed to improve quality of sleep considering age, education levels and living arrangement.