• Current Industrial and Technological Trends in Aerospace
• /
• v.9 no.1
• /
• pp.90-101
• /
• 2011

In this article, we introduce the technologies and trend of technical evolution of Payload Data Handling Unit (PDHU) for Earth Observation Satellites. As well, we review the efforts for the Koreanization of PDHU so far, and conclude with some suggestions for future work.

• Journal of The Korea Institute of Healthcare Architecture
• /
• v.23 no.2
• /
• pp.63-72
• /
• 2017

Purpose: The purpose of this study is to review the material handling system of the Airborne Infection Isolation Hospitals which is the one of the key elements of infection control and to improve the basic data for the planning and design of those facilities. Methods: Research was conducted by literature reviews and case studies for the material handling system of domestic and foreign Isolation hospitals. Results: The result of this study can be summarized into three points. First, a general isolation unit and a high level isolated unit need to be distinguished in terms of efficiency and safety. In particular, it is desirable that a high level isolated unit have to completely separate clean and soiled circulations, and soiled corridor should be installed by those means. By doing this, the medical staff can observe patient rooms and supply clean materials directly in the clean zone without wearing PPE, so that safety and work efficiency can be improved at the same time. Second, for the safe disposal of wastes, it is desirable to install a dedicated sterilizer per ward and sterilize it at least in the ward. In addition, It is desirable to install a central waste treatment room and a dedicated soiled corridor in consideration of the inadequate handling capacity and emergency situation. Third, the characteristics of material flow chart in the negative pressured isolation hospitals and the corresponding material handling system have been presented. Implications: Infection control is very important in safety, but it is necessary to respond to the symptoms of the patient.

• Journal of Radiation Protection and Research
• /
• v.39 no.4
• /
• pp.218-221
• /
• 2014

Nuclear Safety Act had described the three types of licenses on radioisotope handling, such as a general license, a special license and a supervisory license. Applicants should be qualified by careers and qualifications for the education and training to acquire the licenses. In particular, the information on the estimation for the career is notified by Nuclear Safety and Security Commission(NSSC). In this paper, we suggest an improvement by analyzing survey data at the end of the education course on a license for the supervisor of radiation handling. We applied the learning evaluation to improve the education course. The level of satisfaction with the improved curriculum was compared with the existing curriculum. The improved curriculum with the learning evaluation has shown high grades of performance, i.e. above 4.0 points (full mark: 5.0 points) on the level of satisfaction and field application. The learning evaluation should be applied to the basic education course on a general license for radioisotope handling.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.12
• /
• pp.489-498
• /
• 2022

Recently, the textile industry, which is labor-intensive, is attempting to reduce process costs and optimize quality through artificial intelligence. However, the fiber spinning process has a high cost for data collection and lacks a systematic data collection and processing system, so the amount of accumulated data is small. In addition, data imbalance occurs by preferentially collecting only data with changes in specific variables according to the purpose of fiber spinning, and there is an error even between samples collected under the same fiber spinning conditions due to difference in the measurement environment of physical properties. If these data characteristics are not taken into account and used for AI models, problems such as overfitting and performance degradation may occur. Therefore, in this paper, we propose an outlier handling technique and data augmentation technique considering the characteristics of the spinning process data. And, by comparing it with the existing outlier handling technique and data augmentation technique, it is shown that the proposed technique is more suitable for spinning process data. In addition, by comparing the original data and the data processed with the proposed method to various models, it is shown that the performance of the tensile tenacity and elongation prediction model is improved in the models using the proposed methods compared to the models not using the proposed methods.

• Proceedings of the KSR Conference
• /
• 2002.10a
• /
• pp.497-502
• /
• 2002

TGIS(Train General Information System) is monitoring Train status and analyzing fault happened. TGIS informed a lot of Passenger data, Driving data, Status data and Fault data to 'Depot'. For dealing them more properly, TGIS need specified data and specialized data handling method. This paper suggest Optimize data of Train Monitoring System and Apply that to Main Line Car.

• Proceedings of the Korea Database Society Conference
• /
• 2001.11a
• /
• pp.239-256
• /
• 2001

1. 일관성 (Consistency)과 표준화(Standardization) 2. 유용한 피드백의 제공 3 실수에 대한 대응책(Easy Error Handling) 4. 자기 위치정보의 제공(Internal Locus of Control) 5. 단기 기억부담의 최소화(Minimal Memory Load) (중략)

• Proceedings of the Korean Nuclear Society Conference
• /
• 2003.05a
• /
• pp.77.2-77.2
• /
• 2003

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.149-151
• /
• 2005

In this paper, we propose the Optimal Polynomial Neural Networks(PNN) for nonlinear process. The PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to feedforward Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and can be generated. The each node of PNN structure uses several types of high-order polynomial such as linear, quadratic and modified quadratic, and is connected as various kinds of multi-variable inputs. The conventional PNN depends on experience of a designer that select No. of input variable, input variable and polynomial type. Therefore it is very difficult a organizing of optimized network. The proposed algorithm identified and selected No. of input variable, input variable and polynomial type by using Genetic Algorithms(GAs). In the sequel the proposed model shows not only superior results to the existing models, but also pliability in organizing of optimal network. Medical Imaging System(MIS) data is simulated in order to confirm the efficiency and feasibility of the proposed approach in this paper.

• Spatial Information Research
• /
• v.20 no.6
• /
• pp.99-107
• /
• 2012

Recently, various researches have been attempted to connect or integrate BIM handling construction data and GIS handling spatial data. However, it is hard to interoperate by integration between two data models because characteristics and domains of data models between BIM and GIS are very different. In this research, we propose the platform to secure efficient interoperability between BIM and GIS and define the component technologies and functions of the platform proposed in this research by analyzing the existing commercial softwares.

• Journal of Korean Institute of Industrial Engineers
• /
• v.42 no.4
• /
• pp.263-269
• /
• 2016

The purpose of this study is to challenge a computational regression-type problem, that is handling large-size data, in which conventional metamodeling techniques often fail in a practical sense. To solve such problems, regression-type boosting, one of ensemble model techniques, together with bootstrapping-based re-sampling is a reasonable choice. This study suggests weight updates by the amount of the residual itself and a new error decision criterion which constructs an ensemble model of models selectively chosen by rejection limits. Through these ideas, we propose AdaBoost.RMU.R as a metamodeling technique suitable for handling large-size data. To assess the performance of the proposed method in comparison to some existing methods, we used 6 mathematical problems. For each problem, we computed the average and the standard deviation of residuals between real response values and predicted response values. Results revealed that the average and the standard deviation of AdaBoost.RMU.R were improved than those of other algorithms.