• Bulletin of the Korean Chemical Society
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• 제32권1호
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• pp.201-207
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• 2011

Peroxisome proliferator-activated receptors (PPARs) are members of nuclear receptors and their activation induces regulation of fatty acid storage and glucose metabolism. Therefore, the $PPAR\gamma$ is a major target for the treatment of type 2 diabetes mellitus. In order to generate pharmacophore model, 1080 known agonists database was constructed and a training set was selected. The Hypo7, selected from 10 hypotheses, contains four features: three hydrogen-bond acceptors (HBA) and one general hydrophobic (HY). This pharmacophore model was validated by using 862 test set compounds with a correlation coefficient of 0.903 between actual and estimated activity. Secondly, CatScramble method was used to verify the model. Hence, the validated Hypo7 was utilized for searching new lead compounds over 238,819 and 54,620 chemical structures in NCI and Maybridge database, respectively. Then the leads were selected by screening based on the pharmacophore model, predictive activity, and Lipinski's rules. Candidates were obtained and subsequently the binding affinities to $PPAR\gamma$ were investigated by the molecular docking simulations. Finally the best two compounds were presented and would be useful to treat type 2 diabetes.

• Interdisciplinary Bio Central
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• 제4권1호
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• pp.2.1-2.7
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• 2012

Introduction: Histone deacetylases (HDAC) are a class of enzymes that remove acetyl groups from ${\varepsilon}$-N-acetyl lysine amino acids of histone proteins. Their action is opposite to that of histone acetyltransferase that adds acetyl groups to these lysines. Only few HDAC inhibitors are approved and used as anti-cancer therapeutics. Thus, discovery of new and potential HDAC inhibitors are necessary in the effective treatment of cancer. Materials and Methods: This study proposed a method using support vector machine (SVM) to classify HDAC8 inhibitors and non-inhibitors in early-phase virtual compound filtering and screening. The 100 experimentally known HDAC8 inhibitors including 52 inhibitors and 48 non-inhibitors were used in this study. A set of molecular descriptors was calculated for all compounds in the dataset using ADRIANA. Code of Molecular Networks. Different kernel functions available from SVM Tools of free support vector machine software and training and test sets of varying size were used in model generation and validation. Results and Conclusion: The best model obtained using kernel functions has shown 75% of accuracy on test set prediction. The other models have also displayed good prediction over the test set compounds. The results of this study can be used as simple and effective filters in the drug discovery process.

• Nuclear Engineering and Technology
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• 제55권7호
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• pp.2642-2649
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• 2023

A real-time unmeasured dynamic response prediction process for the nuclear power plant pressure pipeline is proposed and its performance is tested in the test-loop system (KAERI). The aim of the process is to predict unmeasurable or unreachable dynamic responses such as acceleration, velocity, and displacement by using a limited amount of directly measured physical responses. It is achieved by combining a well-constructed finite element model and robust inverse force identification algorithm. The pressure pipeline system is described by using the displacement-pressure vibro-acoustic formulation to consider fully filled liquid effect inside the pipeline structure. A robust multiphysics modal projection technique is employed for the real-time sensor synchronized prediction. The inverse force identification method is also derived and employed by using Bathe's time integration method to identify the full-field responses of the target system from the modal domain computation. To validate the performance of the proposed process, an experimental test is extensively performed on the nuclear power plant pressure pipeline test-loop under operation conditions. The results show that the proposed identification process could well estimate the unmeasured acceleration in both frequency and time domain faster than 32,768 samples per sec.

• 드라이브 ㆍ 컨트롤
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• 제10권3호
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• pp.21-26
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• 2013

This paper presents a robust motion tracking control of a cylinder-toggle servomechanism for injection molding machines. Virtual design model has been developed for a five-point type toggle mechanism. A sliding function is defined and combined with PID control to accommodate mismatches between the real plant and the linear model used. From tracking control simulations, it is shown that significant reduction in position tracking error is achieved with clamping force build-up through the use of proposed control scheme.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 춘계학술대회논문집
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• pp.559-564
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• 2002

Cross-talk cancellation, inverse filter design or deconvolution in a generic term, is a vital process for a virtual sound realization in the stereo sound reproduction system. Most, if not all, of the design algorithms available for the inverse filter are based on a linearized model of the real physical plant. The result of such a plant-based design method, which may be referred to here as the indirect method, is biased due to both modelling and inversion errors. This paper presents a novel direct cross-talk cancellation method that may be free from the inversion error. The direct method can directly models the inverse filter by a suitable rearrangement of the input and output ports of the original plant so that no inversion is required here. Advantages are discussed with various experiments in an anechoic chamber using a PC soundcard. Binaural reproduction tests conducted showed that the conventional indirect method yields about 8 % reproduction performance error on both ear positions, whereas the direct method offers about 3 %.

• 자원ㆍ환경경제연구
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• 제30권2호
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• pp.237-268
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• 2021

에너지전환 정책의 가속화로 변동성 재생에너지가 가파르게 증가하면서 계통수용비용이 빠르게 상승하고 있다. 변동성 재생에너지 증가는 기존 전통적 발전자원의 이용률을 하락시켜서 전력공급에 비효율성을 가중시키는데 이에 대한 해결책으로 수요자원이 주목받고 있다. 본 연구에서는 수요자원 중 큰 잠재력을 가지고 있는 전기차 수요가 재생발전에 대한 유연성 자원으로 활용될 경우 전력공급비용을 얼마나 경감시킬 수 있는지 9차 전력수급계획을 반영하여 분석하였다. 분석모형으로 재생발전의 확률적 특성을 사실적으로 반영할 수 있는 확률적 전력시스템 최적화 모형을 적용해서 재생에너지가 유발하는 비용과 전기차 수요자원의 편익을 분석하였다. 분석결과 계시별 요금제보다 가상발전소 기반의 직접제어방식이 편익이 더 높고, 발전구성에서 재생에너지의 비중이 높아질수록 편익이 더 높아지는 것으로 나타났다. 전기차 수요자원의 구현비용인 중개사업자 수수료와 배터리마모비용을 고려한 순편익 추정결과, 충방전이 가능한 가상발전소 방식의 경우 월평균 운행비용의 67~85% 수준으로 나타났다. 이러한 수요자원 순편익이 소비자에게 효과적으로 분배되는 요금체계가 적용될 경우 시장참여유인이 높을 것으로 추정된다.

• 한국전자거래학회지
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• 제14권3호
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• pp.131-151
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• 2009

u-공장이나 u-물류와 같은 유비쿼터스 지능공간에서의 서비스 선택 및 제공을 위해서는 자연스러운 인터페이스가 중요하다. 자연스러운 인터페이스의 실현을 위한 유력한 방법으로 증강현실 기술이 주목받고 있다. 증강현실은 가상현실과 다르게 실제 환경 위에 가상객체를 증강시켜 제공해주는 기술이다. 증강현실을 이용하면 사용자에게 정보를 직관적이고 협력적으로 제공해 줄 수 있는 이점이 있다. 하지만 현재 유비쿼터스 지능공간에서 구동될 전자상거래 도메인에서 활용되는 증강현실 기술은 거의 존재하지 않으며, 있더라도 등록된 마커에 해당하는 사전 정의된 정보와 서비스를 정적으로 제공하는 한계점을 가지고 있다. 따라서 본 연구의 목적은 사용자의 동적 상황을 고려한 증강현실형 전자상거래 방법론을 제안하는 것이다. 이를 실현하기 위해 인지심리학 모형인 Rescorla-Wagner Model과 Galton 자유연상 실험을 기반으로 한 연상 알고리즘을 개발하였으며 개인의 상황에 따라 연상된 서비스와 이미지가 증강현실을 통해 동적으로 제공되도록 하였다.

• Bulletin of the Korean Chemical Society
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• 제33권5호
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• pp.1707-1714
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• 2012

Grb2 is an adapter protein involved in the signal transduction and cell communication. The Grb2 is responsible for initiation of kinase signaling by Ras activation which leads to the modification in transcription. Ligand based pharmacophore approach was applied to built the suitable pharmacophore model for Grb2. The best pharmacophore model was selected based on the statistical values and then validated by Fischer's randomization method and test set. Hypo1 was selected as a best pharmacophore model based on its statistical values like high cost difference (182.22), lowest RMSD (1.273), and total cost (80.68). It contains four chemical features, one hydrogen bond acceptor (HBA), two hydrophobic (HY), and one ring aromatic (RA). Fischer's randomization results also shows that Hypo1 have a 95% significant level. The correlation coefficient of test set was 0.97 which was close to the training set value (0.94). Thus Hypo1 was used for virtual screening to find the potent inhibitors from various chemical databases. The screened compounds were filtered by Lipinski's rule of five, ADMET and subjected to molecular docking studies. Totally, 11 compounds were selected as a best potent leads from docking studies based on the consensus scoring function and critical interactions with the amino acids in Grb2 active site.

• Bulletin of the Korean Chemical Society
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• 제31권1호
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• pp.52-58
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• 2010

Human histamine H1 receptor (HHR1) is a G protein-coupled receptor and a primary target for antiallergic therapy. Here, the ligand-based three-dimensional pharmacophore models were built from a set of known HHR1 inverse agonists using HypoGen module of CATALYST software. All ten generated pharmacophore models consist of five essential features: hydrogen bond acceptor, ring aromatic, positive ionizable and two hydrophobic functions. Best model had a correlation coefficient of 0.854 for training set compounds and it was validated with an external test set with a high correlation value of 0.925. Using this model Maybridge database containing 60,000 compounds was screened for potential leads. A rigorous screening for drug-like compounds unveiled RH01692 and SPB00834, two novel molecules for HHR1 with good CATALYST fit and estimated activity values. The new lead molecules were docked into the active site of constructed HHR1 homology model based on recently crystallized squid rhodopsin as template. Both the hit compounds were found to have critical interactions with Glu177, Phe432 and other important amino acids. The interpretations of this study may effectively be deployed in designing of novel HHR1 inverse agonists.

• 문화기술의 융합
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• 제9권6호
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• pp.245-250
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• 2023

현실공간의 정보를 가상의 공간으로 모사하는 디지털 트윈 기술은 다양한 분야에서 채택되고 있다. 디지털 트윈에 대한 관심은 Industry 4.0 기반의 스마트제조와 같은 첨단 제조 분야를 중심으로 관심이 커지고 있다. 그리고 디지털 트윈의 시스템을 운영하면 수많은 데이터가 발생하며 기술의 분야에 따라 발생하는 데이터는 특성이 다르기때문에 효율적으로 자원을 관리하고, 최적화된 디지털 트윈 플랫폼 기술이 필요하다. 첨단 제조 분야를 중심으로 디지털 트윈의 파이프라인에 대한 연구가 지속적으로 진행되어 왔으나 플랜트 분야의 데이터에 적합한 고속의 파이프라인 연구는 아직 부족하다. 그렇기에 본 논문에서는 Apache Kafka를 통해 고속으로 쏟아지는 플랜트분야의 디지털 트윈 데이터에 특화된 파이프라인 설계 방식을 제안한다. 제안된 모델은 플랜트의 정보를 revit 기반으로 적용하고, 플랜트에 특화된 데이터를 Apache Kafka 통해 수집하며, 경량화된 CFD엔진을 탑재하여 기존의 제조 분야의 디지털 트윈 기술보다 플랜트분야에 적합한 디지털 트윈의 모델을 구현할 수 있다.