• 정보관리학회지
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• 제38권4호
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• pp.153-171
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• 2021

이 연구는 데이터세트를 관리, 보존, 서비스하기 위해 DDI 메타데이터를 기반으로 METS를 활용하는 방안을 제시하였다. DDI는 통계 데이터 처리를 위한 표준으로 현재 DDI Codebook(DDI-C)과 DDI Lifecycle(DDI-L) 두 가지 버전이 존재한다. 본 연구에서는 DDI-C의 주요 요소를 주로 하였다. 이를 위해 우선 METS와 DDI-C의 구조와 요소를 분석하였다. 그리고 METS와 DDI-C의 주요 요소들에 대한 매핑작업을 수행하였다. 여기서 기준은 최종적으로 이를 표현할 형식인 METS로 삼았다. METS와 DDI-C가 완벽하게 1:1의 매핑을 보이지 않기 때문에 기준인 METS의 각 요소들에 가장 적합하게 부합하는 DDI-C 요소를 선택하였다. 그 결과 DDI-C 메타데이터요소를 활용한 새로운 데이터세트 관리전송 표준 METS를 설계하여 제시하였다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.2444-2448
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• 2007

The multi channel of DDI which is the core part of the LCD-TV has been propelled. When multi channel in DDI is introduced, it brings a thermal problem because of the increased power. To solve the thermal problem of the DDI it needs to be investigated each at the package level and module level. It is important to extract the junction temperature(Tj) of DDI clearly from the system level. The objective of this research is to construct a compact model. The compact model is to reduce LCD module including DDI. When the compact model is used, it will be able to easily handle the boundary condition and accurately predict the temperature. Consequently, the temperature of DDI can be calculated easily at the system level. Through this research,we also proposed the cooling plan of DDI for a protection of overheating. The cooling plan was utilized in DDI design.

• 한국임상약학회지
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• 제19권1호
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• pp.1-17
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• 2009

Adverse drug reactions (ADR) caused by inappropriate prescription are responsible for major socioeconomic loss. Drug-drug interactions (DDI) has been recognized as a major part of ADRs and, therefore, healthcare professionals should prevent possible DDIs to minimize preventable ADRs. This study aimed to examine DDI information in drug information references and Korea Food & Drug Administration (KFDA) drug labeling information. Drug ingredients from the formulary of Health Insurance Review and Assessment Service in Korea (HIRA) were included for the study. DDI information source used for the study were Micromedex Drugdex and Drug Information Facts (DIF) with the DDI severity level of "moderate" or more. The DDI information in KFDA drug labeling were collected and compared. Drug ingredients were classified with KFDA Drug Classification and ATC Classification of WHO for the analysis. Among the total 1,355 drug ingredients satisfying inclusion criteria, 738 ingredients involved at least one DDI, which was described in Micromedex and/or DIF. Drug Ingredients of 176 involved DDI only described in KFDA drug labeling, but not Micromedex nor DIF. Drug ingredients of 35 which DDIs were described in Micromedex or DIF did not have DDI based on KFDA drug labeling. Micromedex and DIF retrieved 7,582 and 3,071 DDIs, respectively 57.6% and 58.5% of DDIs were also described in KFDA drug labeling. Central nervous system (CNS) drugs, cardiovascular system (CVS) drugs and the antiinfectives appeared to have higher frequency of DDIs among all drug classes. The highest number of DDIs with high severity level ("contraindicated" or "major") were the DDIs of CNS drugs. The antiinfectives are the second drug group having serious DDIs. The DDI pairs of the CNS drug and the antiinfective had the highest contraindication risk (13.6%). DDI information from Micromedex and DIF were not consistent with the result that only 465 ingredients' DDIs are common in both literature (total DDI numbers were 715 vs 488, respectively). And 1,652 DDI information are common in both references among 7,582 vs 3,071 DDIs, respectively. Only 55.2% of DDI information in the database contained in the KFDA drug labeling. Prescribers and pharmacists should pay attention to the drugs for CV system, CNS and infections because of higher risk of possible DDIs compared to other drug classes. KFDA drug labeling is not likely to be recommended as a good information source for DDI due to significant inconsistency of information. Drug information providers should be aware that DDI information from different sources are not consistent and therefore multiple references should be used.

• International Journal of Computer Science & Network Security
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• 제21권6호
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• pp.319-328
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• 2021

Parallel administration of numerous drugs increases Drug-Drug Interaction (DDI) because one drug might affect the activity of other drugs. DDI causes negative or positive impacts on therapeutic output. So there is a need to discover DDI to enhance the safety of consuming drugs. Though there are several DDI system exist to predict an interaction but nowadays it becomes impossible to maintain with a large number of biomedical texts which is getting increased rapidly. Mostly the existing DDI system address classification issues, and especially rely on handcrafted features, and some features which are based on particular domain tools. The objective of this paper to predict DDI in a way to avoid adverse effects caused by the consumed drugs, to predict similarities among the drug, Drug pair similarity calculation is performed. The best optimal weight is obtained with the support of KHA. LSTM function with weight obtained from KHA and makes bets prediction of DDI. Our methodology depends on (LSTM-KHA) for the detection of DDI. Similarities among the drugs are measured with the help of drug pair similarity calculation. KHA is used to find the best optimal weight which is used by LSTM to predict DDI. The experimental result was conducted on three kinds of dataset DS1 (CYP), DS2 (NCYP), and DS3 taken from the DrugBank database. To evaluate the performance of proposed work in terms of performance metrics like accuracy, recall, precision, F-measures, AUPR, AUC, and AUROC. Experimental results express that the proposed method outperforms other existing methods for predicting DDI. LSTMKHA produces reasonable performance metrics when compared to the existing DDI prediction model.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제21권3호
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• pp.215-222
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• 2015

사물인터넷을 이용한 디지털 도어락, DDiT를 소개한다. DDiT에서는 기존의 디지털 도어락을 제어하기 위하여 통합 마이크로 컨트롤러 플랫폼인 아두이노를 이용하였으며 모바일 플랫폼으로는 안드로이드 스마트폰을 사용하였다. DDiT의 장점 중 하나는 기존의 디지털 도어락에 부착해서 사용할 수 있는 형태로 스마트폰 애플리케이션을 열쇠로 활용하는 방식이라는 점이다. 더구나, 스마트폰 애플리케이션을 사용하므로 이를 통해서 여러 가지 부가적인 기능도 수행할 수 있다. 따라서, 사물인터넷을 이용한 디지털 도어락은 일반 가정집 도어락은 물론 호텔, 연구실, 및 회사와 같은 높은 보안을 필요로 하는 장소에까지 다양한 분야에서 효과적이고 편리하게 활용될 수 있을 것이다.

• Tuberculosis and Respiratory Diseases
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• 제72권2호
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• pp.124-131
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• 2012

Background: DNA damage-inducible 1 (Ddi1), one of the ubiquitin-like and ubiquitin-associated family of proteins, may function in the regulation of the ubiquitin-proteasome pathway, which has been validated as a target for antineoplastic therapy. We investigated Ddi1 expression in human lung cancer tissues and evaluated the relationship of this expression pattern with clinicopathological factors in patients with non-small-cell lung cancer (NSCLC). Methods: Ddi1 expression was examined by immunohistochemistry in tumor tissues from 97 patients with stage I NSCLC, who had undergone curative surgical resection at two tertiary referral hospitals from 1993~2004. None of the patients received preoperative chemotherapy and/or radiation therapy. Results: Thirty-nine (40.2%) of the 97 cases were positive for Ddi1. Ddi1 expression was dominantly seen in cytoplasm rather than in the nuclei of cancer cells in all histological types, whereas adjacent nontumoral lung tissue showed negative Ddi1 staining in most cases. Ddi1 expression tended to increase in well-differentiated tumors but without statistical significance. Positive Ddi1 expression was associated with a tendency for better disease-free survival and disease-specific survival, although the difference was not significant. Conclusion: Ddi1 expression is a property of NSCLC. Because Ddi1 could be a potential target for cancer therapy, more research is needed to evaluate its role in NSCLC.

• 대한지역사회영양학회지
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• 제16권5호
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• pp.580-591
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• 2011

This research was performed to investigate the effects of NEP (Nutritional Education Practice) program developed by KHyDDI (Korea Hypertension Diabetes Daegu Initiative) for hypertension and diabetes patients. The subjects were 116 patients (hypertension 70, diabetes 46) who had completed basic education program at the education information center and four-session program was implemented for them. Nutrient intake was analyzed and compared before and after the program by 24-hr recall method and evaluate weight, waist circumference, body fat, blood pressure and eating habits in terms of nutrition knowledge, eating behavior, salty taste assessment. The improved results after the program were observed in weight, waist circumference, body fat ratio, blood pressure, slightly salty taste in salty taste assessment, nutrition knowledge, eating behavior, sodium, energy, carbohydrate and protein intake ratio to total energy (p < 0.001). Therefore, this program is effective in the improvement of weight, waist circumference and eating behavior, and the continued management would lead to the prevention of cardio-cerebrovascular diseases in the community.

• 한국산학기술학회논문지
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• 제11권2호
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• pp.485-490
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• 2010

본 논문에서는 버팅 콘택(butting contact) 구조를 갖는 DDI DRAM소자의 감지 증폭기의 입력 게이트 단의 모든 기생 성분을 포함한 등가 회로를 제안 하였다. 제안한 모델을 이용하여 기생 쇼트키 다이오드가 감지 증폭기 동작에 어떤 영향을 미치는지 분석하였다. 각각의 불량 가능성에 대해 감지 증폭기가 어떻게 동작하는지 분석하여 단측 불량 특성의 원인을 규명하였다. DDI DRAM에서 단측 불량 원인과 불량률의 온도 의존성은 감지 증폭기의 입력 게이트 단에 형성된 기생 쇼트키 다이오드 형성에 기인한 것으로 판단된다. 이러한 기생 쇼트키 다이오드는 게이트 입력에 기생 전압 강하를 야기하게 되고 결국 감지 증폭기의 노이즈 마진을 감소시켜 단측 불량률을 증가시킨다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 추계학술발표대회
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• pp.63-65
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• 2022

DDI(Drug-Drug Interaction)는 병원에서 발생하는 약물이상반응의 30%를 유발하는 부작용이지만, 현실적으로 모든 약물쌍의 DDI 를 기존 in vivo, in vitro 방식으로 예측하는 것은 불가능하다. 그렇기에, 다양한 in silico 방식의 DDI 예측 모델이 연구되고 있다. 본 연구에서는, 단백질 네트워크 상에서 RWR(Random Walk with Restart) 알고리즘을 통해 약물과 직접적으로 상호작용하는 단백질과 간접적으로 상호작용하는 단백질의 정보를 사용하여 DDI 를 예측하는 모델을 개발하였다. 이 모델을 통하여 기존에 발견하지 못한 DDI 를 새롭게 발견하고, 신약 개발 시에도, 신약과 함께 복용 시 문제를 일으킬 수 있는 약물을 예측하여 약물 이상반응을 방지하고자 한다.

• 한국임상약학회지
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• 제21권3호
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• pp.249-255
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• 2011

Objective: To examine the drug use (prescribing) pattern of serious drug-drug interactions (DDIs, contraindicated drug interactions) using real world data. Prescription patterns were examined in terms of dispensing types. Method: Retrospective drug utilization review (DUR) study was performed. One hundred and six datasets of serious DDIs (DDI pairs) were determined among DDI datasets that Ministry of Health & Welfare announced for the DUR system from 2004 to 2005. Electronically transacted ambulatory patients' prescription database to Health Insurance Assessment and Review Services (HIRA) from July, 2005 to June, 2006 was collected with personal information deidentified and analyzed in terms of types of dispensing as a contributing factor. Results: After prescription data analysis per each patient, total number of DDI cases using 95 DDI pairs was 5,511, which accounted for 2.6 cases per patients. DDI cases between two drugs from each of community pharmacy dispensing- type prescription were considerable (63% vs. 24% in those from each of in-institutional dispensing-type prescription and vs. 13% in those from a community pharmacy dispensing-type prescription and an in-institutional dispensingtype prescription). Conclusions: DDI cases from different prescribers were found to be significant. Thus, the concurrent DUR process between prescriptions from different physicians and institutions should be implemented for the safe drug use.