• Journal of the Korea Safety Management & Science
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• v.13 no.4
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• pp.71-79
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• 2011

The work environment of locomotive cabs has long been an important issue in the design of railload systems since it is quite critical in terms of system's operational safety. It is getting more attention as the running speed of the trains goes up these days. To this end, this paper describes how to systematically construct a DB for the requirements set in the course of the improvement process for the aforementioned cab work environment. As a solution approach, we have adopted the requirement architecture concept to cover the whole activities required to do such as in requirements generation, DB construction, change management, and traceability management. Specifically, based on the requirement architecture framework a requirement process to collect requirements for improvement is discussed, and the guide lines are suggested for verification and validation of the developed requirements. In addition, a base schema and requirements templates are developed, which will be used in generating requirements and constructing a DB. Finally, it is demonstrated how the requirements DB for locomotive cabs can be constructed using a computer-aided tool in an integrated fashion.

• Journal of Convergence for Information Technology
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• v.9 no.1
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• pp.136-141
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• 2019

In this paper, we describe the design of a small size data acquisition system with STM32 processor based on Cortex-M4. The system is used for the sensor devices to collect raw data on production lines at factory and send them to the server computer in real time. Also the system is designed to easily acquisite various kinds of data collected from various sensors with the digital signal input unit, the analog signal input unit, the digital signal output unit and the analog signal output unit This small data acquisition system will contribute to the improvement of the quality of precision products in the industrial field by collecting various data in real time and transmitting data at high speed.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.121-126
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• 2017

EES System support to maximize equipment efficiency by providing real-time information of main equipment which has a significant effect on product quality and productivity, and to prevent equipment failure by detecting equipment abnormality in advance. Smart Equipment Engineering System(S-EES) integrates the activities performed at equipment that are the core of production activities and manages them by system so as to maximize the efficiency of equipment and raise the quality level of products to one level. In other words, when the product is put into the equipment, the recipe is downloaded through the RMS, the recipe is set to the optimal condition through R2R(process control), and the system detects and controls the abnormality of the equipment during operation through the FDC function in real time it means. In this way, we are working with the suitable recipe that matches the lot of product, detecting the abnormality of the equipment during operation, preventing the product from being defective, and establishing a system to maximize the efficiency through real-time equipment management. In this study, we review the present status and problems of equipment management in actual production lines, collect the requirements of the manufacturing line for the PCB line, design and develop the system, The measurement model was studied.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.382-395
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• 2021

In this study, character recognition using deep learning is performed among the various defects in the PCB, the purpose of which is to check whether the printed characters are printed correctly on top of components, or the incorrect parts are attached. Generally, character recognition may be perceived as not a difficult problem when considering MNIST, but the printed letters on the PCB component data are difficult to collect, and have very high redundancy. So if a deep learning model is trained with original data without any preprocessing, it can lead to over fitting problems. Therefore, this study aims to reduce the redundancy to the smallest dataset that can represent large amounts of data collected in limited production sites, and to create datasets through data enhancement to train a flexible deep learning model can be used in various production sites. Moreover, ResNet model verifies to determine which combination of datasets is the most effective. This study discusses how to reduce and augment data that is constantly occurring in real PCB production lines, and discusses how to select coresets to learn and apply deep learning models in real sites.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.37 no.5
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• pp.425-430
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• 1992

This experiment was carried out to collect the Korean red rices and to evaluate them as useful germplasm, 1,113 lines of weedy red rices were collected from farmer's field of the Korean peninsula from 1988 to 1991. The collected red rices were classified into two groups : One was long grain type with length /width ratio of 3.01$\pm$0.11 in paddy rice and the other was short grain type with length /width ratio of 2.28$\pm$0.12. Among the collected red rices 289 lines were long grain type and 824 lines were short. The red rices of long grain type were distributed in Nagdong and Seomjin river vallies of the southern part of the Korean peninsula, and the short ones were distributed all around of the peninsula. Among the collected long grain type red rices, 90.8% was red and 9.2% was white, and among the short grain type 88.8% was red, 10.6% was brown and 0.6% was white in pericarp color. 9.3% of the long grain type and 30.7% of the short grain type of the Korean red rices reacted to phenol solution. In the short grain type, 4.3% was waxy grained, but no waxy line was found in the long grain type. All the long grained Korean red rice showed easy shattering and no awn, however in the short grained red rices, 85.2% showed easy shattering and 49.6% was awned.

• Korean Journal of Medicinal Crop Science
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• v.5 no.4
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• pp.266-275
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• 1997

Anemarrhena asphodeloides BUNGE is one of important medicinal crops, which has been collected or/and cultivated for its rhizomes. The main medicinal ingredient of the A. asphodeloides Bunge rhizomes is a saponin, which is known to have medical values for diaphoresis, sedatives and biuresis. However, studies on cultural methods and breeding works on this plant have not been made in detail. To increase productivity and to improve quality of crops, it is important to collect cultivated and wild lines, to classify them based on morphological and genetic characteristics, and to select superior pure lines at first. Therefore, total 20 A. asphodeloides lines collected were cultivated at the fieldof Chungnam Provincial Administration of Rural Development in 1995 to study the agronomic characteristics and to classify them based on morphological characteristics. Characteristics related with reproductive organ such as the number of spikes per plant and peduncle length showed greater variations than vegetative organrelated characteristics such as leaf length and rhizome length based on the coefficient of variation. Vigorous shoot growth resulted in better development of reproductive organs such as peduncle length and number of spikes per plant. However, the development of spikes was negatively correlated with chlorophyll content. Characteristics of underground parts were more significantly correlated with spike characteristics than aerial part characteristics. A. asphodeloides tested in this study were classified into 2 groups (group A and group B) based on centroid linkage cluster analysis. Group A showed more vigorous shoot growth with more leaves and spikes per plant, longer peduncle length, thicker peduncle diameter and higher shoot dry weight than group B. Group A could be further classified into 2 sub-groups based on leaf size, spike length and peduncle diameter, while group B also could be classified based on number of leaves, number of spikes and shoot dry weight.

• Economic and Environmental Geology
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• v.53 no.5
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• pp.597-608
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• 2020

Even after the Gyeongju earthquake and the Pohang earthquake, hundreds of aftershocks and micro-earthquakes are still occurring in the southeastern part of the Korean Peninsula. These phenomena mean that the stress is constantly working, implying that another huge earthquake may occur in the future. Therefore, the gravity field interpretation method was used to analyze the deep geological structure of the Pohang-Ulsan region in the southeastern Korean Peninsula. First, a gravity survey was performed to collect the insufficient data and to calculate the detailed Bouguer gravity anomaly in the study area. Based on the gravity anomaly data, the location, direction, and maximum depth of deep fault lines were analyzed using the inversion methods "Curvature analysis" and "Euler deconvolution method". As a result, it is interpreted that at least six fault lines(C1~C6) exist in deep depth. The deep fault line C1 is well correlated to the Yeonil Tectonic Line(YTL), suggesting that YTL is extended up to about 4000m deep. The deep fault line C2 consists of several segment faults and well correlated to the fault lines on the surface. Inferred fault lines C3, C4, and C5 have an NW-SE direction, which is parallel to the Ulsan fault. The deep fault line C6 has the direction of NE-SW, and it is interpreted that the eastern boundary fault of Eoil Basin is extended to the deep. Comparing the inferred fault lines with the distribution of micro-earthquakes, the location of the deep fault line C1 is well correlated to the hypocenter of micro-earthquakes. This implies that faults in deep depth are related to the recent earthquakes in the southeastern Korean Peninsula.

• International Commerce and Information Review
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• v.15 no.3
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• pp.87-110
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• 2013

The aim of this study is as follows. The first, What are the most important factors Affecting Global Single Window Usage and its Performance in Korean Trade Related Companies? The factors proposed for this study includes The pressure of trading companies in other country, Support of government, top management support, partnership among (makers distributors, retailers, customs service), education and training We gathered detailed data on our sample companies mainly from publicly available sources : Korea Customs Service. A structured questionnaire was used to collect information about: (1) general fact about the company (size, lines of business, products and services provided, employee, and some financial data about exporting), (2) To investigate the factors of the five contexts described above on korean export-import companies's global single window. The result are as follows. The analysis result revealed that the pressure of trading companies, support of government are influential variables on the affecting global single window in korean trade related companies.

• Journal of the Korean Society for Railway
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• v.19 no.3
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• pp.397-407
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• 2016

This study analyzed the efficiency change and the factors affecting productivity change for the six railway operation corporations that are local public enterprises; study was performed with the DEA-CCR Model and Malmquist Productivity Index, using data collected from 2010 to 2014. Since it was not feasible to collect data on the operating expenses and the number of employees of each of the lines, the efficiencies of each operation corporation were analyzed by integrating the operation corporations, and the Malmquist Productivity Index was used to investigate the trend of the periodical productivity change. Average efficiency for urban railway operation corporations was found to be higher in the case of the bigger corporations. In 2014, the Seoul Metro and the Daejeon Metropolitan Express Transit Corporations were analyzed and found to be the most efficient operation corporations. The Malmquist Productivity Index was used to determine the periodical change; the average MPI was 1.06, with a continuous increase of productivity. The analysis showed that changes of technology were generally more obvious than change of technology efficiency for all six operation corporations.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.92-99
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• 2016

AIS(Automatic Identification System) is an vessel traffic management system which exchanges vessel data with other nearby ships, AIS base stations using VHF band. A domestic AIS base station is located along coast lines or island. So it is difficult to collect vessel data from the ocean. To solve this problem, we adopted AIS payload on the low earth orbit satellite. The AIS payload on the satellite is interfaced with OBC(On-Board Computer) via UART and the FSW(Satellite Flight Software) manages it. The FSW have to receive AIS command from ground station and forward to AIS payload. Similarly FSW have to receive response, OBP, OGP data from AIS payload and it is downlink to the ground station. So in this paper we describe the FSW design & implementation for AIS payload.