• Journal of Korean society of Dental Hygiene
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• v.4 no.1
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• pp.119-132
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• 2004

The purpose of this study was to introduce PBL to dental hygienist education in an effort to raise a question about the inauthentic and inappropriate curriculum. PBL is one of learning methods to enhance the problem-solving ability of learners, and it's attempted to develop a PBL package focusing on dental hygienist roles to lay the foundation for producing competent and expert dental hygienists with a good problem- solving ability. The literature concerned was reviewed from November 2002 through January 2003 to determine whether or not PBL was applicable to dental-hygienist course, and that turned out to be effective for dental hygienist education. And then a PBL package was developed to train students to be knowledgeable and have a knowhow and excellent problem-solving skills. The characteristics of the PBL package could be described as follows: First, that focused on dental hygienist roles to serve the purpose of this study to remedy the current unrealistic and improper curriculum and improve the problem-solving skills of learners. Second, time factor was taken into account. In this four-week course for two credits, there are four classes a week, and it's required to take six or eight weeks to apply the PBL package, which is expected to demotivate students. Therefore, it's planned to conduct more weekly classes to make a proper progress. Third, a wide variety of teaching aids were put to use, and learner would be encouraged to be more interactive and utilize teaching aids properly, and eventually, they could have an opportunity to better express themselves. Fourth, online real-time learner discussion would be attended by this researcher. Learners would have a discussion in real time in the Internet cafe chat room, and different discussion time would be allocated to each team. This researcher would take part in each team's discussion once or more. Fifth, learners would prepare one or more journal(s) about four-hour Internet cafe learning. They have to make it twice a week at least, and it would be a good opportunity for learners to look back on themselves and their teams, and their learning effect would be greater. Specific rules were presented to help them make a successful self-examination. Sixth, there are some spaces in the lower part of objective test sheets to have students describe why they make a particular answer choice. They would be asked to depict the reason of their prior evaluation and lecture assessment especially because their responses would be important for more successful discussion and feedback. Seventh, problem-solving approach was designed to attain learning objectives, stimulate the creative thinking of learners and help them share a more systematic discussion. That would serve as a secondhand guide not to make them digress when they discuss by using information they acquire from a scenario presented in class.

• Journal of KIISE
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• v.42 no.5
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• pp.629-636
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• 2015

The types of errors corrected by a Korean spelling and grammar checker can be classified into isolated-term spelling errors and context-sensitive spelling errors (CSSE). CSSEs are difficult to detect and to correct, since they are correct words when examined alone. Thus, they can be corrected only by considering the semantic and syntactic relations to their context. CSSEs, which are frequently made even by expert wiriters, significantly affect the reliability of spelling and grammar checkers. An existing Korean spelling and grammar checker developed by P University (KSGC 4.5) adopts hand-made correction rules for correcting CSSEs. The KSGC 4.5 is designed to obtain very high precision, which results in an extremely low recall. Our overall goal of previous works was to improve the recall without considerably lowering the precision, by generalizing CSSE correction rules that mainly depend on linguistic knowledge. A variety of rule-based methods has been proposed in previous works, and the best performance showed 95.19% of average precision and 37.56% of recall. This study thus proposes a statistics based method using a conditional probability model with dynamic window sizes. in order to further improve the recall. The proposed method obtained 97.23% of average precision and 50.50% of recall.

• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.45-52
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• 2008

As the recent development of the IT services, there is a urgent need of effective diagnosis system to present appropriate solution for the complicated problems of breakdown control, a cause analysis of breakdown and others. So we propose an intelligent diagnosis system that integrates the case-based reasoning and the artificial neural network to improve the system performance and to achieve optimal diagnosis. The case-based reasoning is a reasoning method that resolves the problems presented in current time through the past cases (experience). And it enables to make efficient reasoning by means of less complicated knowledge acquisition process, especially in the domain where it is difficult to extract formal rules. However, reasoning by using the case-based reasoning alone in diagnosis problem domain causes a problem of suggesting multiple causes on a given symptom. Since the suggested multiple causes of given symptom has the same weight, the unnecessary causes are also examined as well. In order to resolve such problems, the back-propagation learning algorithm of the artificial neural network is used to train the pairs of the causes and associated symptoms and find out the cause with the highest weight for occurrence to make more clarified and reliable diagnosis.

• Korean Security Journal
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• no.16
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• pp.47-64
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• 2008

The purpose of this study is to develop the measurement of security needs satisfaction from users of electronic security system, to verify its validity and reliability, and by applying them, to examine the effects between the communities using this system. In 2008, the users of electronic security system in big cities in Seoul(Yong-San, Jong-Lo) and Gyung-Gi Do(Su-Won) for their convenience stores, jewelry shops, communication services, banks, government and public offices, etc. were arranged for a population and 262 of them were used for the final analysis by purposive sampling. This study yields following results. First, the validity of security need satisfaction from users of electronic security system is very high, which means the explanatory adequacy of environmental security need is the highest. Second, the reliability of security need satisfaction from users of electronic security system is very high, in which the reliability value(Cronbach's $\alpha$) of internal consistency is over .765. Third, the security need of electronic security system has the most effects on the group of bank workers. That is, through a close cooperative system between the bank and the service of electronic security system, the more keeping satisfied the environmental, bodily, physical security needs are, the less the in security of this group has. Informational security need has the most effects on convenient store group. It means the service companies of electronic security system offer more services at dawn time and make or supply all sorts of visual information system, which reduces insecurity of the convenient store group.

• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.99-105
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• 2015

Currently robots are widely used in schools for educational purpose. With wide spread of robot-based education, it is known that major advantage of robot-based education is to enhance creativity and logical thinking of students. Although robots can be very useful tools for assisting students' study activities, there have not been lots of teaching-learning models for robot-based education.In this paper, a teaching-learning model is presented for robot-based education. The proposed model is designed based on constructivism. The proposed model consists of 6 stages: preparation, design, assembling, demonstration run, evaluation, and application & extension. The proposed model has the following characteristics. First, the proposed model is designed to enhance creativity and logical thinking ability of learners. Learners are supposed to be involved in self-directed activities and required to provide results based on their own ideas. Teachers are supposed to mediate students only if necessary. Second, learners are encouraged to participate in activity via diverse interaction. The interaction in this model includes learner-to-learner interaction, learner-to-teacher interaction, and learner-to-expert interaction. The proposed model encourages learners to solve the problem with cooperating each other. Also, teachers are supposed to guide students if necessary and observe and monitor behavior of students all the time. Third, motivation is provided in the beginning stage of the instruction. Fourth, in the proposed model, both study results and study process are equally important. In the model, study process is reviewed at the final stage.

• Journal of Internet Computing and Services
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• v.13 no.4
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• pp.45-52
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• 2012

T cells induce immune responses and thereby eliminate infected micro-organisms when peptides from the microbial proteins are bound to HLAs in the host cell surfaces, It is known that the more stable the binding of peptide to HLA is, the stronger the T cell response gets to remove more effectively the source of infection. Accordingly, if peptides (HLA binder) which can be bound stably to a certain HLA are found, those peptieds are utilized to the development of peptide vaccine to prevent infectious diseases or even to cancer. However, HLA is highly polymorphic so that HLA has a large number of alleles with some frequencies even in one population. Therefore, it is very inefficient to find the peptides stably bound to a number of HLAs by testing random possible peptides for all the various alleles frequent in the population. In order to solve this problem, computational methods have recently been developed to predict peptides which are stably bound to a certain HLA. These methods could markedly decrease the number of candidate peptides to be examined by biological experiments. Accordingly, this paper not only introduces a method of machine learning to predict peptides binding to an HLA, but also suggests a new prediction model so called 'knowledge-based genetic algorithm' that has never been tried for HLA binding peptide prediction. Although based on genetic algorithm (GA). it showed more enhanced performance than GA by incorporating expert knowledge in the process of the algorithm. Furthermore, it could extract rules predicting the binding peptide of the HLA alleles common in Koreans.

• Journal of KIISE:Software and Applications
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• v.33 no.6
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• pp.550-563
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• 2006

Software product line engineering is a method that prepares for the future reuse and supports to seamless reuse in application development process. Commonality and variability play central roles in all product line development processes. Reusable assets will become core assets by explicitly representing C&V. Indeed, the variabilities that art identified at each phase of core assets development have different levels of abstraction. In the past, these variabilities have been handled in an implicit manner and without distinguishing the characteristics of each core assets. In addition, previous approaches have depended on the experience and intuition of a domain expert to recognize commonality and variability. In this paper, we suggest a 2-dimensional analyzing method that analyzes the variabilities of core assets in software product line. In horizontal analysis process, the variation types are analyzed in requirements, architecture, and component that are produced at each phase of development process. In vertical analysis process, variations are analyzed in different abstract levels, in which the region of commonality is identified and the variation points are refined. By this method, the traceability of variations between core assets will be possible and core assets can be reused seamlessly.

• Journal of Korean Clinical Nursing Research
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• v.26 no.1
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• pp.117-130
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• 2020

Purpose: This study aimed to develop a bedside nursing shift report protocol and evaluate the effect of the protocol in a tertiary hospital in South Korea. Methods: The bedside nursing handoff protocol with patient engagement was developed based on the literature review and the validation of an expert group. The effect of the protocol on clinical implication was tested in three medical-surgical units in a tertiary hospital. Outcomes were assessed by patient perception, nurse perception, and reporting time. Data collected from June to August in 2018 and analyzed with descriptive statistics and One-way ANOVA using SPSS version 25.0. Results: The bedside nursing shift report protocol with patient engagement consisted of two steps: nurse to nurse report and bedside report with patients. Nurse's perception with patient engagement was significantly increased after applying protocol (F=17.85, p<.001). Patient's perception was significantly improved in the areas of discharge plan (F=7.86, p<.001), health information privacy (F=4.46, p=.012) and identify attending nurse (F=3.19, p=.042). There were no differences in reporting time between the bedside nursing shift report and a traditional shift report (F=0.61, p=.054). Conclusion: Patient perception was significantly increased, while nurse perception was not different after applying this protocol. For the change in the perception of nurses, education may be preceded to improve nurses' competence for the bedside shift report. Furthermore, the support in enough nurse staffing should be needed for encouraging the bedside shift report. The bedside shift report may enhance patient engagement. Therefore it may improve patient safety and health outcome in clinics.

• Anxiety and mood
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• v.14 no.2
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• pp.53-62
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• 2018

Objective : The Korean Association of Anxiety Disorders developed Korean guidelines for treatment of panic disorder (PD) 2018. In this paper, we discussed the consensus among psychiatrists, regarding initial and maintenance treatment strategies for pharmacological treatment of PD in Korea. Methods : Based on current treatment guidelines published by the American Psychiatric Association, the National Institute for Clinical Excellence, and the Canadian Psychiatric Association, we developed questionnaires pertinent to initial and maintenance treatment strategies for pharmacological treatment of PD. Seventy-two experts in PD answered questionnaires. We classified expert opinions into three categories, first, second, and third-line treatment strategies, by analyzing the 95% confidence interval. Results : Antidepressants, benzodiazepine anxiolytics, and cognitive-behavioral therapy (CBT) were recommended as treatments of choice (ToC), and first-line strategies for initial treatment of PD. Escitalopram, paroxetine, sertraline, and venlafaxine were preferred from among many anti-panic drugs. Mean starting dose of anti-panic drugs for initial treatment of PD was relatively lower, than that for other psychiatric illnesses such as major depressive disorder. In the case of maintenance treatment of PD, antidepressants and CBT were selected as ToC and first-line strategies. Patients were typically examined every four weeks during treatment, to review effectiveness and side effects of the drug. Pharmacotherapy was generally continued for one year or more. Conclusion : This study provides information about consensus among Korean experts regarding pharmacological treatment strategies for patients with panic disorder.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2534-2546
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• 2021

Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.