• Genomics & Informatics
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• v.16 no.3
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• pp.52-58
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• 2018

In this report, we present a case study of how pharmacogenomics and pharmacometabolomics can be useful to characterize safety and pharmacokinetic profiles in early phase new drug development clinical trials. During conducting a first-in-human trial for a new molecular entity, we were able to determine the mechanism of dichotomized variability in plasma drug concentrations, which appeared closely related to adverse drug reactions (ADRs) through integrated omics analysis. The pharmacogenomics screening was performed from whole blood samples using the Affymetrix DMET (Drug-Metabolizing Enzymes and Transporters) Plus microarray, and confirmation of genetic variants was performed using real-time polymerase chain reaction. Metabolomics profiling was performed from plasma samples using liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. A GSTM1 null polymorphism was identified in pharmacogenomics test and the drug concentrations was higher in GSTM1 null subjects than GSTM1 functional subjects. The apparent drug clearance was 13-fold lower in GSTM1 null subjects than GSTM1 functional subjects (p < 0.001). By metabolomics analysis, we identified that the study drug was metabolized by cysteinylglycine conjugation in GSTM functional subjects but those not in GSTM1 null subjects. The incidence rate and the severity of ADRs were higher in the GSTM1 null subjects than the GSTM1 functional subjects. Through the integrated omics analysis, we could understand the mechanism of inter-individual variability in drug exposure and in adverse response. In conclusion, integrated multi-omics analysis can be useful for elucidating the various characteristics of new drug candidates in early phase clinical trials.

• Journal of Korean Society for Geospatial Information Science
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• v.9 no.2 s.18
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• pp.29-36
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• 2001

The purpose of this paper is to describe the Disaster Management System Development of Enterprise GIS at the Kangwon Province in Korea. This project is included into 'the Kangwon Enterprise GIS 21 plan'. The Division of Disaster Management is in the middle of the 2-year project of the Disaster Management System development, appropriate for business performed at the Departments of Forestry, Culture, Environment, Tourism, etc. At the 1st phase of CIS implementation, for more than half a year we focused on the necessity of management of disasters. In the planning process, we needed long-term information on the whole area of Kangwon. In the assessment and response processes, we needed real-time data from Korean Meteorological Administration and other agencies. All the above information was carefully studied and referred to. ESRI's new GIS technologies solve the natural hazard/disaster problems. For example, hazardous materials routing often needs to be found the least expensive path through a roadway network. In the circumstances given, we can choose the departure point and destination of the vehicle, which carries the materials. It's also possible to minimize overall risk and costs of disaster problems by making a plan of people and possessions evacuation from the disaster area in short time limits. We can meet all the above goals using the latest ESRI's technologies.

• Journal of the Korea Society for Simulation
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• v.26 no.1
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• pp.21-38
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• 2017

Information Centric Networking is changing the way how content is being transmitted. The shift from IP and host based networking towards content based networking scenario is growing day by day. Many researches have been done about different frameworks of ICN. Caching is an important part of ICN and many researchers have also proposed different ways for caching the data. With caching of data in intermediate devices like the network devices as well the user devices in some cases, the issue of content security as well as the role of the content producer becomes a major concern. A modified ICN architecture based on the current Content Centric Networking (CCN) model is presented in the paper. The architecture mainly focuses on involving the content producer in content delivery in the real time. The proposed architecture provides better security aspects for the CCN architecture. Apart from security the paper will also consider the issue of applicability of CCN architecture to replace the TCP/IP based architecture. The efficiency of the proposed architecture is compared with the previous CCN architecture based on the response time for a content delivery which shows very comparable level of efficiency. The paper than analyzes different beneficial aspects of the proposed architecture over the current architecture.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.11
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• pp.369-382
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(quality of service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to activate only the minimum number of servers needed to handle current user requests. Previous studies on energy aware server cluster put efforts to reduce power consumption or heat dissipation, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management method to improve not only performance per watt but also QoS of the existing server power mode control method based on autonomous learning. Our proposed method is to adjust server power mode based on a hybrid approach of autonomous learning method with multi level thresholds and power consumption prediction method. Autonomous learning method with multi level thresholds is applied under normal load situation whereas power consumption prediction method is applied under abnormal load situation. The decision on whether current load is normal or abnormal depends on the ratio of the number of current user requests over the average number of user requests during recent past few minutes. Also, a dynamic shutdown method is additionally applied to shorten the time delay to make servers off. We performed experiments with a cluster of 16 servers using three different kinds of load patterns. The multi-threshold based learning method with prediction and dynamic shutdown shows the best result in terms of normalized QoS and performance per watt (valid responses). For banking load pattern, real load pattern, and virtual load pattern, the numbers of good response per watt in the proposed method increase by 1.66%, 2.9% and 3.84%, respectively, whereas QoS in the proposed method increase by 0.45%, 1.33% and 8.82%, respectively, compared to those in the existing autonomous learning method with single level threshold.

• Journal of the Korean Institute of Gas
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• v.22 no.6
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• pp.136-143
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• 2018

Cellular automata have been applied to simulations in many fields such as astrophysics, social phenomena, fire spread, and evacuation. Using cellular automata, this study develops a model for consequence analysis of the dispersion of hazardous chemicals, which is required for risk assessments of and emergency responses for frequent chemical accidents. Unlike in cases of detailed plant safety design, real-time accident responses require fast and iterative calculations to reduce the uncertainty of the distribution of damage within the affected area. EPA ALOHA and KORA of National Institute of Chemical Safety have been popular choices for these analyses. However, this study proposes an initiative to supplement the model and code continuously and is different in its development of free software, specialized for small and medium enterprises. Compared to the full-scale computational fluid dynamics (CFD), which requires large amounts of computation time, the relative accuracy loss is compromised, and the convenience of the general user is improved. Using Python open-source libraries as well as meteorological information linkage, it is made possible to expand and update the functions continuously. Users can easily obtain the results by simply inputting the layout of the plant and the materials used. Accuracy is verified against full-scale CFD simulations, and it will be distributed as open source software, supporting GPU-accelerated computing for fast computation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.603-611
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• 2020

Potholes on the road directly affect drivers' safety, satisfaction, and vehicle damage. Thus, real-time detection and response are required. Increasing frequency of patrols allows for potholes to be detected and responded to quickly, but this takes much manpower, money, and time. In addition, potholes have different occurrence characteristics depending on the rain conditions, so it is necessary to consider the optimal frequency from an economic and road-service perspective. Therefore, a quantitative analysis was done on the effects of rainfall on the occurrence characteristics of potholes. Information on the persistence, impact of rainfall intensity, and weather information was collected over a long period. Based on the results, a risk-based, optimized, and changeable road-patrol strategy is presented. The analysis results show that the probability of pothole occurrence increases by 2.4 times in rainy weather. Furthermore, the impact continues for 3 days even after the rain stops. The probability of pothole occurrence increases by 0.46% per 1 mm of rainfall, and the occurrence characteristics react sensitively to even a small amount of rain of around 1 mm. It was concluded that road patrol is required at least once every three days for an effect-free period, while twice a day is needed for the "sphere of influence" period to achieve a 95% reliability level.ys for effect-free period, while twice a day for sphere of influence period to satisfy 95% reliability level.

• Journal of Marine Life Science
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• v.7 no.1
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• pp.29-36
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• 2022

Sea cucumber, Aposticopus japonicus, is a major invertebrate species in the coastal regions of Korea. To evaluate the short-term stress levels according to the releasing methods, this study investigated the gene expression profiles of heat shock protein 90 (HSP90) by real-time quantitative polymerase chain reaction. When the juvenile sea cucumbers were packed in the vinyl bag with oxygen followed by transportation for 30 min or air-exposed for 1 h, the HSP90 gene expression levels in the experimental groups were significantly increased compared to those of the control groups (transported group, p=0.001; air-exposed group, p=0.032). The experimental group at 6 h post-release by seed-spreading method and at 2~6 h post-release by underwater hose-releasing method on board a fishing boat showed that the levels of HSP90 gene expression were not statistically significant but decreased slightly compared to the control group (seed-spreading group, p=0.069; hose-releasing group, p=0.093). On the other hand, the HSP90 gene expression showed an increasing pattern as the time passed (~6 h) after underwater release of juvenile sea cucumbers by divers (p=0.061). These results suggest that HSP90 gene expression can be used to investigate short-term stress response and effective releasing methods of juvenile sea cucumbers.

• Korean Journal of Construction Engineering and Management
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• v.23 no.4
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• pp.3-14
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• 2022

Autonomous equipment requires a large amount of data from various environments. However, it takes a lot of time and cost for an experiment in a real construction sites, which are difficulties in data collection and processing. Therefore, this study aims to develop a virtual environment for autonomous tower cranes technology development and validation. The authors defined automation functions and operation conditions of tower cranes with three performance criteria: operational design domain, object and event detection and response, and minimum functional conditions. Afterward, this study developed a virtual environment for learning and validation for autonomous functions such as recognition, decision making, and control using the Unity game engine. Validation was conducted by construction industry experts with a fidelity which is the representative matrix for virtual environment assessment. Through the virtual environment platform developed in this study, it will be possible to reduce the cost and time for data collection and technology development. Also, it is also expected to contribute to autonomous driving for not only tower cranes but also other construction equipment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.87-96
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• 2022

The traffic vulnerable, including elderly pedestrians, have a relatively low walking speed and slow cognitive response time due to reduced physical ability. Although a smart crossing system has been developed and operated to improve problem, it is difficult to operate a signal that reflects the appropriate walking speed for each pedestrian. In this study, a neural network model and a multiple regression model-based traversing speed estimation model were developed using image information collected in an area with a high percentage of traffic vulnerability. to support the provision of optimal walking signals according to real-time traffic weakness. actual traffic data collected from the urban traffic network of Paju-si, Gyeonggi-do were used. The performance of the model was evaluated through seven selected indicators, including correlation coefficient and mean absolute error. The multiple linear regression model had a correlation coefficient of 0.652 and 0.182; the neural network model had a correlation coefficient of 0.823 and 0.105. The neural network model showed higher predictive power.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.12
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• pp.937-946
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• 2017

Recently, urban structures including buildings are becoming increasingly large and super high-rise in order to make human life more convenient. As the number of super high-rise buildings increases, however, the risk of fire and other disasters is increasing. Especially, it is expected that deaths and injuries will be tremendous than imagined if the evacuation guidance is not provided promptly and precisely for the occupants in case of a fire in super high-rise buildings. Therefore, rapid rescue should be done for those who are in need of residence or rescue in the building. To do this, identification of the size and location of people inside the building should be preceded. To do this, first, we conduct a preliminary study on existing location tracking technologies to identify occupants. Based on this, in this paper, we will study how to improve evacuation time in case of a fire in super high-rise buildings. For this purpose, we utilize the location tracking technology to identify the number of people in real time and improve the density when a disaster such as a fire occurs.