• Journal of Pharmaceutical Investigation
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• v.39 no.5
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• pp.321-325
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• 2009

5-HT$_{2C}$ receptors have been considered as therapeutic targets for the treatment of various central nervous system disorders such as depression, anxiety, epilepsy, schizophrenia and sleep disorders. We chemically synthesized KKHQ80114 (K14) and KKHQ80109 (K09), selective 5-HT$_{2C}$ agonists, with the purpose of developing therapeutic agents for the treatment of obesity. The objective of this work is to investigate analytical methods of these compounds in the plasma and urine of rats by gas chromatography/mass spectrometry. In this experiment, K14 was determined in plasma and urine by using K09 as internal standard. Calibration curves give a good linearity in plasma (r$^2$=0.9993) and urine (r$^2$=0.9988). Among hexane, ethyl acetate and diethyl ether, the highest peak was observed in diethyl ether. However, ethyl acetate was used since more interfering peaks were observed with diethyl ether. Inter-day precision and accuracy were determined in the ranges of 50-500 ng/mL for plasma and 10-500 ng/ml for urine. Quantitation limits were 50 ng/mL plasma and 25 ng/ mL urine. These data may be applicable for further studies of these compounds including absorption and metabolism due to no pharmacokinetic or analytical data available.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.931-940
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• 2021

As information security(IS) is recognized as a critical success factor for organizational growth, organizations are increasing their investment in adopting and operating strict IS policies and technologies. However, when strict IS technology is adopted, IS-related techno-stress may occur in the employees who apply IS technology to their tasks. This study proposes the effect of IS-related techno-stress formed in individuals on IS policy resistance through IS strain and proves that task-technology fit mitigates the negative effect of techno-stress. Research models and hypotheses were presented through previous studies, and the secured samples were used, and structural equation modeling was applied to verify hypothesis. As a result of the study, it was confirmed that IS-related techno-stress (overload, complexity) affected IS policy resistance through IS strain (anxiety, fatigue), and that task-technology fit moderated the relationship between techno-stress and strain. This study suggests a strategic direction for improving the level of internal IS from the viewpoint of suggesting ways to mitigate the stress of employees that may occur when IS policies and technologies are adopted.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.217-225
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• 2021

In this paper, we designed and implemented the integrated system to prevent adverse drug reactions of polypharmacy components in medicine by supporting component-component information and disease-component information, through data queuing algorithm and vast amounts of pharmaceutical big data. In addition, by providing information for drugs, drug components, prohibited drugs, as well as suppliers and distributors, it could help ease anxiety about taking drugs not only for health-care professionals but also for general users. The representative information provided were side effects between two drugs, main components and effectiveness of particular drugs, drugs manufactured by the same pharmaceutical company, and drug component information for patients with chronic diseases. The future work is to update the database by collecting information on rare & new diseases and new drugs.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.199-208
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• 2023

The emergence of COVID-19 virus has shaken almost every aspect of human life including but not limited to social, financial, and economic changes. One of the most significant impacts was obviously healthcare. Now though the pandemic has been over, its aftereffects are still there. Among them, a prominent one is people lifestyle. Work from home, enhanced screen time, limited mobility and walking habits, junk food, lack of sleep etc. are several factors that have still been affecting human health. Consequently, diseases like diabetes, high blood pressure, anxiety etc. have been emerging at a speed never witnessed before and it mainly includes the people at young age. The situation demands an early prediction, detection, and warning system to alert the people at risk. AI and Machine learning has been investigated tremendously for solving the problems in almost every aspect of human life, especially healthcare and results are promising. This study focuses on reviewing the machine learning based approaches conducted in detection and prediction of diabetes especially during and post pandemic era. That will help find a research gap and significance of the study especially for the researchers and scholars in the same field.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.441-452
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• 2022

Training using metacognition in a learning environment is one of the topics that have been continuously studied since the 1990s. Metacognition can be broadly divided into declarative metacognitive knowledge and procedural metacognitive knowledge (metacognitive skills). Accordingly, metacognitive training has also been studied focusing on one of the two metacognitive knowledge. The purpose of this study was to examine the role of metacognitive skills training in the context of mathematical problem solving. Specifically, the learner performed the prediction of problem difficulty, estimation of problem solving time, and prediction of accuracy in the context of a test in which problems of various difficulty levels were mixed within a set, and this was repeated 5 times over a total of 5 weeks. As a result of the analysis, we found that there was a significant difference in all three predictive indicators after training than before training, and we revealed that training can help learners in problem-solving strategies. In addition, we analyzed whether there was a difference between the experiment group and control group in the degree of test anxiety and math achievement. As a result, we found that learners in the experiment group showed less emotional and relationship anxiety at 5 weeks. This effect through metacognitive skill training is expected to help learners improve learning strategies needed for test situations.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.349-359
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• 2022

The purpose of this study is to add and revalidate items of learning cognition and learning emotion factors for online use of the K-LSS for junior college. It is important for self-reflection and improvement of academic achievement to specifically explore and analyze the sub-factors of learning cognition, learning behavior, and learning emotion for each item that can affect the learning strategy of junior college students. The added items are two items for diagnosing the concentration of attention in the learning information processing process of the learning cognitive factor and two questions about the interpersonal anxiety factor for diagnosing the level of anxiety about others in the learning emotional factor. The study area was conducted in 5 areas nationwide, and the subjects of the study were 923 junior college students excluding 327 respondents who answered insincerity. The K-LSS_r scale is a learning strategy diagnosis scale of 52 questions composed of three sub-elements of learning cognition (18 questions), learning emotion (15 questions), and learning behavior (19 questions), and reliability for generalization in this study. As a result of the verification, Cronbach's α coefficient of the entire scale was .896, and Cronbach's α coefficient of the three factors ranged from .876 to .910. The half-segment reliability coefficient of the scale was .858 in total, and the half-segment reliability coefficients of the three factors ranged from .792 to .843. The test-retest reliability verification result for 3 weeks for 350 Junior college Students in 5 regions was .884, and the validity test for generalization also confirmed that the recruitment validity is significant.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.595-604
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• 2022

It is necessary to pay attention to healthy eating habits and attitudes toward health functional foods at a time when the incidence of diseases increases exponentially due to side effects of westernized eating habits. The purpose of this study is to clarify the effect of healthy eating habits and attitudes toward health functional foods on mood states of college students and the elderly. As a result of the analysis, in the elderly, the explanatory power for vitality emotion was lower than that of college students, and only healthy eating habits were factors that significantly explained. For anxiety-depression, it was found that health eating habits could explain the decrease in anxiety-depression emotions even less only in the elderly, and for anger emotions, neither college students nor the elderly showed significant explanatory power. This suggests that it is necessary to further research and analyze the experimental and practical effects based on a wider group and various emotions on how health functional foods and healthy eating habits affect emotions.

• The Journal of Industrial Distribution & Business
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• v.11 no.2
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• pp.33-39
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• 2020

Purpose: The purpose of this study is that victims of technology leaks and people concerned about leaks complain of stress over security concerns. However, there are no psychological treatments among the government's comprehensive plans to prevent technology leaks. Therefore, the government intends to present education methods using the NLP (Neuro Linguistic Program), a collective counseling technique, to heal the psychological injury of the victims. Psychological counseling methods include cognitive behavioral therapy, psychoanalytic behavioral therapy, humanism therapy, art therapy, and other psychological therapies. Among them, NLP (Neuro Linguistic Programming) method was used. NLP has three concepts: neuron, language, and programming, and is used as a general method for group counseling. Research design, data and methodology: In relation to composition, Chapter 1 explained the purpose and necessity of the study, Chapter 2 explained the types of psychological counseling and NLPs to help understand the study, introduced the prior study related to the development of collective counseling programs through NLP, and Chapter 3 developed a security psychological counseling education program. In addition, FGI(Focus Group Interview) was conducted for professionals. Results: Corporate counseling considered most in this study should satisfy client, counselor and manager differently from individual counseling. For this purpose, the result was composed of 11 times. In order to derive personal problems for clients, they consisted of finding, loving, expressing, and emancipating self. And, It solved the leakage anxiety to suggest a professional solution for the counselor. In addition, this course helps them become familiar with counseling techniques for becoming a good security administrator. Lastly, it was configured to leave the result for the manager to suggest the organizational development method through this training. The implication of this study is to derive psychological counseling methods for security officers. Most companies in the field of security counseling complain about technology leakage stress. There is currently no psychotherapy support project under the policy. And It was developed because it can expect sales improvement from security consultation. Conclusions: In conclusion, the results were organized to be left to the manager so that he could suggest how to develop the organization through this time.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.159-172
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• 2018

This study searched and analyzed online tracking technologies. It tried to understand what to consider when establishing policies related to online tracking. Online tracking technologies were classified into 'general cookies', 'super cookies', 'fingerprinting', 'device ID tracking' and 'cross-device tracking'. Political considerations should include the layers of online tracking, the subjects of tracking technology, purpose of use, duration and storage format of information, and development of technology. The implications of this study are as follows: first, policy makers and industry should be aware that the degree of risk perceived by users may vary according to the characteristics of online tracking technology. Secondly, it is necessary to understand factors that affect the classification of online tracking technology. Finally, in the industry, preemptive measures such as building an integrated privacy system are needed to relieve anxiety of users and to build trust.

• Journal of Pharmaceutical Investigation
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• v.39 no.5
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• pp.327-331
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• 2009

5-HT$_{2C}$ receptors have been considered as therapeutic targets for the treatment of various central nervous system disorders such as depression, anxiety, epilepsy, schizophrenia and sleep disorders. We chemically synthesized KKHQ80109 (K09) and KKHQ80114 (K14), selective 5-HT$_{2C}$ agonists, with the purpose of developing therapeutic agents for the treatment of obesity. The objective of this work is to investigate pharmacokinetic parameters and bioavailability of K09 and K14 in rats given orally or intravenously. Oral administration of 20 mg/kg K09 results in 4.11 hr of the terminal half-life and 89.16 ng/mL of C$_{max}$ at 5.00 hr (T$_{max}$). The terminal half-life of K14 was 3.83 hr with 215.81 ng/mL of C$_{max}$ at 3.33 hr (T$_{max}$) after oral dosing of 20 mg/kg K14, indicating that K14 is more rapidly absorbed than K09. Bioavailability showed 0.17-0.21 for K09 and 0.19-0.23 for K14. Urinary excretion of parent K09 and K14 was less than 1%, indicating that K09 and K14 undergo very extensive hepatic metabolism.