• Journal of Preventive Medicine and Public Health
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• 제34권4호
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• pp.417-426
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• 2001

Objectives : To analyse the psychosocial factors associated with hypertension management(drug treatment and life style modification) of newly detected cases and to understand and assess their behavioral intention or behaviors. Methods : The survey area was a combined urban and rural area in Chungnam province, Korea, and the sampling method was cluster sampling. Study subjects included 541 newly detected cases of hypertension rated above stage 2 by JNC-VI from a community survey. The first survey was applied to 383 of these patients in order to discern their psychosocial characteristics. A follow-up survey was given to 345 persons with an 11-month interval following monthly telephone counseling concerning medication and life style modification by trained nurses. The final study subjects for analysis comprised 271 persons after excluding cases of incomplete data and change of address. Results : Among the 85(33.2%) new patients who had intended to undergo drug treatment, 30(35.3%) persons were treated with antihypertensive agent after 11 - month interval, while among the patients with no intention to receive treatment, only 36(21.1%) persons were treated. Hypertensive patients with a high intention score revealed a high score in life style modification compliance as well. Seventy three percent of the variance of behavioral intention to undergo hypertension management was explained by the patients attitude toward performing the behavior and subjective norm associated with behaviors related to the theory of reasoned action in structural modeling. Actual behaviors related positively with behavioral intention. The coefficient of determination was 0.255. Conclusion : Improving the compliance level of hypertensive patients in respect to drug treatment or life style modification requires a build up of positive behavioral intention, and caregivers must pay more attention to eventually converting behavioral intention to actual behaviors.

• Archives of Pharmacal Research
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• 제27권7호
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• pp.806-810
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• 2004

Metformin is a biguanide antihyperglycemic agent often used for the treatment of non-insulin dependent diabetics (NIDDM). In this study, the pharmacokinetics and pharmacodynamics of metformin were investigated in Korean healthy volunteers during a fasting state for over 10 h. In order to evaluate the amount of glucose-lowering effect of metformin, the plasma concentrations of glucose were measured for a period of 10 h followed by the administration of metformin (oral 500 mg) or placebo. In addition, the concentration of metformin in blood samples was determined by HPLC assay for the drug. All volunteers were consumed with 12 g of white sugar 10 minutes after drug intake to maintain initial plasma glucose concentration. The time courses of the plasma concentration of metformin and the glucose-lowering effect were analyzed by nonlinear regression analysis. The estimated $C_{max}$, $T_{max}$, $CL_{t}$/F (apparent clearance), V/F(apparent volume of distribution), and half-life of metformin were 1.42$\{pm}$0.07 $\mu\textrm{g}$/mL, 2.59$\{pm}$0.18h, 66.12$\{pm}$4.6 L/h, 26.63 L, and 1.54 h respectively. Since a significant counterclock-wise hysteresis was found for the metformin concentration in the plasma-effect relationship, indirect response model was used to evaluate pharmacodynamic parameters for metformin. The mean concentration at half-maximum inhibition $IC_{50}$, $k_{in}$, $k_{out}$ were 2.26 $\mu\textrm{g}$/mL, 83.26 $H^{-1}$, and 0.68 $H^{-1}$, respectively. Therefore, the pharmacokinetic-pharmacodynamic model may be useful in the description for the relationship between plasma concentration of metformin and its glucose-lowering effect.

• Genomics & Informatics
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• 제19권1호
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• pp.11.1-11.8
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• 2021

For the novel coronavirus disease 2019 (COVID-19), predictive modeling, in the literature, uses broadly susceptible exposed infected recoverd (SEIR)/SIR, agent-based, curve-fitting models. Governments and legislative bodies rely on insights from prediction models to suggest new policies and to assess the effectiveness of enforced policies. Therefore, access to accurate outbreak prediction models is essential to obtain insights into the likely spread and consequences of infectious diseases. The objective of this study is to predict the future COVID-19 situation of Korea. Here, we employed 5 models for this analysis; SEIR, local linear regression (LLR), negative binomial (NB) regression, segment Poisson, deep-learning based long short-term memory models (LSTM) and tree based gradient boosting machine (GBM). After prediction, model performance comparison was evelauated using relative mean squared errors (RMSE) for two sets of train (January 20, 2020-December 31, 2020 and January 20, 2020-January 31, 2021) and testing data (January 1, 2021-February 28, 2021 and February 1, 2021-February 28, 2021) . Except for segmented Poisson model, the other models predicted a decline in the daily confirmed cases in the country for the coming future. RMSE values' comparison showed that LLR, GBM, SEIR, NB, and LSTM respectively, performed well in the forecasting of the pandemic situation of the country. A good understanding of the epidemic dynamics would greatly enhance the control and prevention of COVID-19 and other infectious diseases. Therefore, with increasing daily confirmed cases since this year, these results could help in the pandemic response by informing decisions about planning, resource allocation, and decision concerning social distancing policies.

• Biomolecules & Therapeutics
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• 제30권3호
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• pp.232-237
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• 2022

Autism spectrum disorder (ASD) having core characteristics of social interaction problems and repetitive behaviors and interests affects individuals at varying degrees and comorbidities, making it difficult to determine the precise etiology underlying the symptoms. Given its heterogeneity, ASD is difficult to treat and the development of therapeutics is slow due to the scarcity of animal models that are easy to produce and screen with. Based on the theory of excitation/inhibition imbalance in the brain with ASD which involves glutamatergic and/or GABAergic neurotransmission, a pharmacologic agent to modulate these receptors might be a good starting point for modeling. N-methyl-D-aspartic acid (NMDA) is an amino acid derivative acting as a specific agonist at the NMDA receptor and therefore imitates the action of the neurotransmitter glutamate on that receptor. In contrast to glutamate, NMDA selectively binds to and regulates the NMDA receptor, but not other glutamate receptors such as AMPA and kainite receptors. Given this role, we aimed to determine whether NMDA administration could result in autistic-like behavior in adolescent mice. Both male and female mice were treated with saline or NMDA (50 and 75 mg/kg) and were tested on various behavior experiments. Interestingly, acute NMDA-treated mice showed social deficits and repetitive behavior similar to ASD phenotypes. These results support the excitation/inhibition imbalance theory of ASD and that NMDA injection can be used as a pharmacologic model of ASD-like behaviors.

• 한국기록관리학회지
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• 제23권2호
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• pp.95-115
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• 2023

본 연구는 세계기록유산으로 등재된 국채보상운동 디지털 아카이브 기록물의 활용성을 높이기 위한 방안으로 위키데이터와 연계하는 데이터 모델을 설계하고, 적용가능성을 검토하였다. 국채보상운동 기록물 메타데이터, 시소러스, 시맨틱 네트워크 그래프를 분석하여 시사점을 도출하고, 기록물의 내용 분석을 통해 위키데이터와 연계를 위한 데이터 모델의 클래스인 기록물건, 행위주체, 시간, 장소, 사건을 도출하였다. 또한 클래스 간 연결을 위한 관계 속성들을 파악하여, 설계한 데이터 모델을 실제 기록물 사례에 적용해봄으로써, 속성을 중심으로 한 객체 간의 이동을 통해 풍부한 관련 정보들을 획득할 수 있는 가능성을 확인하였다. 본 연구의 결과는 소규모 로컬 아카이브에서 위키데이터를 활용한 데이터의 공유와 활용 체계 마련에 활용될 수 있을 것이다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권7호
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• pp.1726-1748
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• 2024

Trajectory planning is vital for autonomous systems like robotics and UAVs, as it determines optimal, safe paths considering physical limitations, environmental factors, and agent interactions. Recent advancements in trajectory planning and future location prediction stem from rapid progress in machine learning and optimization algorithms. In this paper, we proposed a novel framework for Spatial-temporal transformer-based feed-forward neural networks (STTFFNs). From the traffic flow local area point of view, skip-gram model is trained on trajectory data to generate embeddings that capture the high-level features of different trajectories. These embeddings can then be used as input to a transformer-based trajectory planning model, which can generate trajectories for new objects based on the embeddings of similar trajectories in the training data. In the next step, distant regions, we embedded feedforward network is responsible for generating the distant trajectories by taking as input a set of features that represent the object's current state and historical data. One advantage of using feedforward networks for distant trajectory planning is their ability to capture long-term dependencies in the data. In the final step of forecasting for future locations, the encoder and decoder are crucial parts of the proposed technique. Spatial destinations are encoded utilizing location-based social networks(LBSN) based on visiting semantic locations. The model has been specially trained to forecast future locations using precise longitude and latitude values. Following rigorous testing on two real-world datasets, Porto and Manhattan, it was discovered that the model outperformed a prediction accuracy of 8.7% previous state-of-the-art methods.

• 한국프랜차이즈경영연구
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• 제15권3호
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• pp.1-15
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• 2024

Purpose: The insurance market is steadily growing, with General Agencies (GA) experiencing rapid sales increases. GAs need marketing strategies to boost contract renewal intentions by effectively managing customer relationships. This study examines the impact of perceived customer orientation and sales orientation on customer trust, identification, and renewal intentions with GA insurance planners. Research design, data, and methodology: The study surveyed customers who subscribe to insurance products from GA-affiliated insurance planners. Out of 615 respondents, 251 valid responses were analyzed using frequency analysis, measurement models, and structural equation modeling (SEM) with SmartPLS 4.0. Result: The study revealed that customer orientation positively affects cognitive trust and sense of identification. In contrast, sales orientation did not significantly impact customer trust or identification. Additionally, customer trust positively influences sense of identification, and both trust and identification positively affect the intention to renew the contract. Conclusions: Implementing a customer-oriented marketing strategy is essential for providing tailored customer management services and maintaining or improving the quality of customer relationships for insurance planners. Given that insurance products require long-term management, it is crucial for planners to build trust, enhance customer identification, and offer continuous customer management to meet customers' needs effectively.

• 한국유통학회지:유통연구
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• 제17권4호
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• pp.55-80
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• 2012

다른 기업과 거래관계를 형성하고 유지하는 것은 빠르게 변화하는 치열한 환경에서 대부분의 기업에게 불가피한 전략적 선택이다. 유통망 안의 모든 기업들도 결국 독립적 기업 간의 이러한 거래 계약으로 맺어져 있다. 하지만 모든 기업 간의 거래가 하나의 목표를 가지고 공동의 이익 창출을 위해 노력하여, 모두 효과적이고 효율적인 성과만을 낼 수는 없다. 대리인 이론에 따르면, 기업들은 모두 독립적 주체로서 각자의 이해를 추구하고, 위험을 회피하려하며, 제한된 합리성을 가지고 불충분한 정보를 처리하게 된다. 즉, 기업 간 거래관계는 그 속에서 신뢰와 협력을 기대하는 동시에, 갈등과 기회주의적 행위도 예측해야 한다. 이에 본 연구는 기업 간 거래의 갈등 원인을 확인하고, 실제 기업이 주로 활용하는 거래조정 방식의 갈등관리 효과를 밝히고자 한다. 이를 위해 관련된 기존 연구와 대리인 이론을 활용하여, 제조업자와 공급업자 간 갈등이 관계성과에 미치는 영향과 거래 위험요인(환경동태성, 자산특유화 수준)의 갈등 유발 효과, 그리고 국내 기업거래 연구에서 잘 다루어지지 않은 거래 조정방식의 갈등관리 효과를 가정하였다. 더불어 국내 중소기업 데이터 329개를 대상으로 연구모델을 검증하였다. 연구 결과, 구매기업(제조업자)의 환경 동태성과 자산 특유화 수준이 높을수록 더 큰 갈등이 유발되었으며, 이러한 B2B 갈등은 기업 간 관계질과 재무성과에 부정적 영향을 끼쳤다. 또한 사회적 조정방식과 법적 조정방식은 갈등의 관계질에 대한 부정적 영향을 매우 유의한 수준에서 완화시키는 조절효과가 검증되었다. 이러한 결과를 바탕으로 본 연구는 B2B갈등의 원인과 관리기법에 대하여 실증적으로 확인하였다는 의의가 있으며, 특히 국내 거래관리 연구에서 소홀히 다루어졌던 법적 계약 방식의 긍정적이고 유의한 효과를 확인하였다는 의의가 있다.

• Bulletin of the Korean Chemical Society
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• 제31권3호
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• pp.606-610
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• 2010

Aminoacyl-tRNA synthetases (aaRSs) play vital roles in protein biosynthesis of living organisms and are interesting antibacterial drug targets. In order to find out new inhibitor candidate molecules as antibacterial agent, the binding modes of the candidate molecules were investigated at the active sites of aaRSs by molecular docking study. The docking simulations were performed with 48 compounds from four different scaffolds into the eight different aaRSs. The results show that scaffolds 3 and 4 compounds have consistently better binding capabilities, specifically for HisRS (E. coli) and IleRS (S. aureus). The binding modes of the best compounds with the proteins were well compatible with those of two ligands in crystal structures. Therefore, we expect that the final compounds we present may have reasonable aaRS inhibitory activity.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제6권4호
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• pp.421-429
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• 2000

현재 ATM(Asynchronous Transfer Mode) 기반 통합 서비스 교환 시스템 개발 추세는 복합 교환 시스템에서의 운용, 보전 기능 및 ATM 기반 인터넷/협대역 통합 서비스 등을 수용하기 위하여 워크스테이션에 멀티플러그-인 개념을 도입하여 시스템이 설계, 구현되고 있다. 한편, 기존 워크스테이션에서는 교환 시스템을 운용하기 위해 HMI(Human Machine Interface) 운용 시스템 기능과 함께 파일 관리 기능, 시간 관리 기능, 그래픽 처리 기능 및 TMN(Telecommunication Management Network)의 에이전트 기능 등이 설정되어 교환 시스템과의 많은 인터페이스를 통하여 기능들이 수행되고 있다. 이러한 기능들은 프로세스 혹은 프로세서간 많은 메시지 통신을 필요로 하고 있으며, 워크스테이션내 입출력 장치 파일, 일반 파일, 그리고 메시지 전송을 위한 메시지 큐, 소켓 자원 등을 사용하고 있다. 따라서, 현재 개발 중인 시스템의 정상 동작 여부를 확인하고 파악된 문제점들에 대한 성능 개선과 함께 추후 지속적인 기능 추가 시에도 시스템의 정상 동작을 보장하기 위해서는 사전에 개발될 교환 시스템에 대한 성능 평가가 선행되어야 한다. 본 논문은 이러한 ATM 기반 통합 서비스 교환 시스템 개발 작업에서 사전에 시스템의 성능 평가를 했다. 성능 평가는 MVA(Mean Value Analysis) 알고리즘을 이용한다. 모델은 큐잉 네트워크 모델을 사용하고 모델링된 시스템을 이용하여 PDQ(Pretty Damn Quick) 시뮬레이션 패키지와 C 언어를 사용하여 시뮬레이션 하였다.