• Archives of Plastic Surgery
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• v.49 no.4
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• pp.538-542
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• 2022

Performing the first peer review of a plastic surgical research article can be an overwhelming task. However, it is an essential scholarly skill and peer review is used in a multitude of settings: evaluation of journal articles, conference abstracts, and research proposals. Furthermore, peer reviewing provides more than just the opportunity to read and help improve other's work: peer reviewing can improve your own scientific writing. A structured approach is possible and recommended. In these ten tips, we provide guidance on how to successfully conduct the first peer reviews. The ten tips on peer reviewing concern: 1) Appropriateness: are you qualified and prepared to perform the peer review? 2) Familiarization with the journal and its reviewing guidelines; 3) Gathering first impressions of the paper followed by specific tips for reviewing; 4) the abstract and introduction; 5) Materials, methods, and results (including statistical considerations); and 6) discussion, conclusion, and references. Tip 7 concerns writing and structuring the review; Tips 7 and 8 describe how to provide constructive criticism and understanding the limits of your expertise. Finally, Tip 10 details why-and how-you become a peer reviewer. Peer review can be done by any plastic surgeon, not just those interested in an academic career. These ten tips provide useful insights for both the aspiring and the experienced peer reviewer. In conclusion, a systematic approach to peer reviewing is possible and recommended, and can help you getting started to provide quality peer reviews that contribute to moving the field of plastic surgery forward.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.1-9
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• 2024

This paper proposes an integration of the ED-H scheduling algorithm, known for optimal real-time scheduling, with the LoRaEnergySim simulator. This integration facilitates the simulation of interactions between real-time scheduling algorithms for tasks with time constraints in Class-A LoRaWAN Class-A devices using a super-capacitor-based energy harvesting system. The time and energy characteristics of LoRaWAN status and state transitions are extracted in a log format, and the task model is structured to suit the time-slot-based ED-H scheduling algorithm. The algorithm is extended to perform tasks while satisfying time constraints based on CPU executions. To evaluate the proposed approach, the ED-H scheduling algorithm is executed on a set of tasks with varying time and energy characteristics and CPU occupancy rates ranging from 10% to 90%, under the same conditions as the LoRaEnergySim simulation results for packet transmission and reception. The experimental results confirmed the applicability of co-simulation by demonstrating that tasks are prioritized based on urgency without depleting the supercapacitor's energy to satisfy time constraints, depending on the scheduling algorithm.

• Journal of the Korean Society of Physical Medicine
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• v.19 no.1
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• pp.95-105
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• 2024

PURPOSE: This study aimed to utilize the International Classification of Functioning, Disability, and Health (ICF) tool to identify a problem list and explore intervention effects using proprioceptive neuromuscular facilitation (PNF) for improving the crosswalk performance of patients who have undergone a bilateral hip arthroplasty. METHODS: The subject of this study was a 43-year-old male who had undergone a bilateral hip arthroplasty. To address the subject's functional status, a clinical decision-making process was carried out in the order of examination, evaluation, diagnosis, prognosis, intervention, and outcome. Patient information during the examination was collected using the ICF core set. The evaluation involved listing the items of each problem using the ICF assessment sheet and identifying the interaction between activity limitations and the impairment level. The diagnosis explicitly described the causal relationships derived from the evaluation using ICF terminology. The prognosis presented activity goals, body function, and structured goals in terms of the activity and participation levels that needed to be achieved for an individual's functional status. The intervention approached problems through the four components of the PNF philosophy, namely basic principles and procedures, techniques, and patterns, in an indirect-direct-task sequence. Results were compared before and after the intervention using the ICF evaluation display. RESULTS: The results of the study showed that the primary activity limitation, which was the walking time across the crosswalk, showed improvement, and the trunk's counter rotation and the weight-bearing capacity of both the lower limbs, which were impairment level indicators, were enhanced. CONCLUSION: This study suggests that PNF intervention strategies will serve as a positive approach for improving crosswalk walking in patients with bilateral hip arthroplasty.

• Journal of Korean Physical Therapy Science
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• v.31 no.2
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• pp.41-51
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• 2024

Background: The purpose of this study was to identify the effect of home-based exercise program in elderly with chronic diseases on balance, activities of daily living, depression and quality of life. Design: One group pretest-posttest design Methods: The subjects consisted of 21 elderly people over the age of 65 years with chronic diseases lived in seo-gu, Gwangju. Home-based exercise program was performed twice a week, for an hour, during 6 weeks under supervision of an experienced instructor. The home-based exercise program was structured to last a total of 1 hour, consisting of 10 minutes of warm-up, 30 minutes of main exercises, and 20 minutes of concluding exercises. For the warm-up, we performed range of motion, stretching, and flexibility exercises. The main exercises comprised of strength, weight-bearing and balance exercises, and endurance exercises. The concluding exercises were tailored to the individual's home environment and needs, including task-oriented daily living training such as getting up from bed, moving to the restroom, and walking indoors. The subjects were assessed before and after the exercise program with berg balance scale(BBS), Korean-version modified barthel index(K-MBI), euro quality of life questionnaire 5-dimensional classification(EQ-5D), and geriatric depression scale short form-Korea(GDSSF-K). The collected data was analyzed using SPSS Win 18.0 program. Results: The results showed statistically significant difference in all domains of the BBS, K-MBI, EQ-5D, GDSSF-K after the exercise program. Conclusion: These results suggest that Home-based exercise program has resulted in a significant improvement on ADL, depression and quality of life in elderly with chronic diseases.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4404-4415
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• 2014

This study was carried out to verify the relationship between the job satisfaction and turnover intention of nurses working in general hospitals The study included 312 nurses working in three general hospitals located in Gyeoungpook area. The data was collected by a survey using self-administered questionnaires structured from February 25 to March 16, 2013. The level of turnover intention was negatively correlated with job satisfaction and professional position, autonomy, administrative capacity, pay, task requirement. In logistic regression analysis, the adjusted odds ratio of the high risk turnover intention was increased significantly in the lower groups of job satisfaction, job autonomy, administrative capacity and pay than in the higher groups of these items. Hierarchical multiple regression analysis showed that the turnover intention correlated significantly with the education level, subjective sleep evaluation, job career, job position, monthly pay, satisfaction with work, fitness of the job, career choice motives, physical burden of work, and job satisfaction. In addition, there was a negative correlation between the job satisfaction and turnover intention in the studied nurses, which showed that the turnover intention increased with decreasing level of job satisfaction. The variations in the job related characteristics and job satisfaction have a significant influence on the turnover intention.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2469-2475
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• 2015

A structured XML has been widely used to present services on various Web-services. The XML is also used for digital documents and digital signatures and for the representation of multimedia files in email systems. The XML document should be firstly parsed to access elements in the XML. The parsing is the most compute-instensive task in the use of XML documents. Most of the previous work has focused on hardware based XML parsers in order to improve parsing performance, while a little work has studied parsing techniques. We present the high performance parsing technique which can be used all of XML parsers and design hardware based XML parser using an FPGA. The proposed parsing technique uses element analyzers instead of the state machine and performs multibyte-based element matching. As a result, our parsing technique can reduce the number of clock cycles per byte(CPB) and does not need to require any preprocessing, such as loading XML data into memory. Compared to other parsers, our parser acheives 1.33~1.82 times improvement in the system performance. Therefore, the proposed parsing technique can process XML documents in real time and is suitable for applying to all of XML parsers.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.190-205
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• 2011

The purpose of this study was to investigate the effects of the MICE industrial employee's job stressors on intent to leave and test of the mediating role of job satisfaction and job commitment. For the study, job stressors were defined 3 groups with 7 sub-factors, such as role stressors of role ambiguity, role conflict and role overload, task stressors of job routineness and job heteronomy, organizational stressors of job insecurity and distributive injustice. Data were collected from 303 MICE industrial employees in metropolitan area by structured questionnaires. Collected data were analyzed by AMOS 18.0 and findings are as follows. Firstly, on aspect of total effectiveness, the seven job stressors had harmful effect on intent to leave, especially organizational stressors had more serious effect on intent to leave than role stressors. Secondly, not only job satisfaction and job commitment had meditators role but also influenced on intent to leave directly. Thirdly, role ambiguity had effect on intent to leave indirectly through the job satisfaction, while role conflict and role overload had effect on intent to leave directly, and also indirect effectiveness on it through the job commitment. Fourthly, job routineness and job heteronomy had effected on intent to leave only through the meditators. Not only job insecurity and distributive injustice had influenced on intent to leave directly but also effectiveness on it indirectly through the meditators.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1178-1185
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• 2012

The 4th year medical students were randomly divided and designated as group HF and LF, representing high and low fidelity simulations respectfully. Both groups performed OSCE on 2 topics(adult intubation and IV cannulation) with each composed of the same scenario. Each scenario was developed by a faculty in charge of clinical skill education with supervision from 2 other faculty members. High fidelity simulations were designed as in-situ simulations in real OR. Low fidelity simulations had the same scenarios but the environment was simulated only with a simple task trainer in the classroom. All students participated in series of survey using a Likert scale before and after the simulations. The provided data was anlayzed with paired T-test and Mann-Whiteney test(p<0.05). The post simulations self evaluation score for group HF was lower than pre-simulation self confidence score for both topics of adult intubation and IV cannulation where as for group LF, it was lower only for adult intubation(p<0.05). In group HF, the needs for clinical training on both topics increased after the simulation. In group LF, there was no significant change of needs for clinical training between pre and post simulation survey. This suggest that fidelity may be a helpful factor to improve the motivation of the students and further study on economical aspect should be addressed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.497-506
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• 2017

The purpose of this study was to investigate the effects of life stress, depression, and drinking motives on problem drinking among college students. The subjects were 249 college students and data were collected through a self-reported structured questionnaire from Nov to Dec 2016. Collected data were analyzed by descriptive statistics, ANOVA, Pearson's correlation, and stepwise multiple regression. The findings showed that drinking motives were the biggest factor influencing their problem drinking with coping, social, enhancement and conformity motives exerting special effects on it. As for correlations with problem drinking, interpersonal and ongoing task stress of life stress had positive correlations with problem drinking. Coping, social, enhancement, and conformity motives also had positive relations with problem drinking. Drinking motives had critical effects on the problem drinking of college students with coping, social, and enhancement motives strongly impacting on it. The findings necessitate examining the drinking motives of college students to make them choose to drink including negative emotions, social activities, and gatherings in order to prevent their problem drinking. These factors could explain 33% of the problem drinking. It is also required to develop methods for them to utilize resources other than drinking and run drinking education and temperance programs at the school level.