• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.550-560
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• 2018

Many countries have provided support for research and development and implemented policies for Advanced Driver Assistance Systems (ADAS) for enhancing the safety of vehicles. With such efforts, the toll of casualties due to traffic accidents has decreased gradually. Korea has exhibited the lowest toll of casualties due to traffic accidents and is ranked 32nd in mortality among the 35 OECD members. Traffic accidents typically fall into three categories depending on the cause of the accident: vehicle to vehicle (V2V), vehicle to pedestrian (V2P), and vehicle independent. Most accidents are caused by drivers' mistakes in recognition, judgment, or operation. ADAS has been proposed to prevent and reduce accidents from such human errors. Moreover, the global automobile industry has recently been developing various safety measures, but on-road tests are still limited and contain various risks. Therefore, this study investigated the international standards for evaluation tests with regard to the assessment techniques in braking capability to cope with the limitations of on-road tests. A theoretical formula for braking force and a control algorithm are proposed, which were validated by comparing the results with those from an on-road test. These results verified the braking force depending on the functions of ADAS. The risks of on-road tests can be reduced because the proposed theoretical formula allows a prediction of the tendencies.

• Journal of the Korean Society for Environmental Technology
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• v.19 no.6
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• pp.576-585
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• 2018

Systematic management during the whole life cycle from construction to operation and maintenance is very important for the seven underground pipelines (waterworks, sewerage, electricity, telecommunications, gas, heating, oil including waterworks and sewerage). Especially, it is the construction process that affects the whole life cycle of underground buried pipeline. In order to construct a new city or to maintain different underground pipes, it is always necessary to dig the ground and carry out construction and related work. There is a possibility that secondary and tertiary breaks frequently occur in the pipeline construction process after the piping constructed first in this process. To solve this problem, a system is needed which can monitor damage in real time. However, the supply of electric power for continuous operation of the system is limited according to the environment of underground buried pipelines, so it is necessary to develop a stable electric power supply system using natural energy rather than existing electric power. In this study, we developed a system that can operate the pipeline monitoring system for long time (24 hours and 15 days) using natural energy using wind and solar light.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.483-494
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• 2020

With the advent of the 4th Industrial Revolution, interest in AI education is increasing. In order to cultivate talented people with AI competencies who will lead the future, AI education must be conducted in a sound manner at the school site. Although AI education is being conducted at home and abroad, it was determined that the role of the AI education platform is important to implement better AI education, so this study investigated the perception of experts on the AI education platform. A perception survey was conducted based on five criteria: teaching and learning management, educational contents, accessibility, performance of AI education platform, and level suitability of elementary school students. As a results, the number of 103 educational experts selected 'Entry' as the most proper platform among the eight platforms - 'Machine learning for Kids', 'Teachable Machine', 'AI Oceans(code.org)', 'Entry', 'Genie Block', 'Elice', 'mBlock' and etc. Analysis shows that this is because 'Entry' provides quality educational content, has convenient accessibility, is easy to manage teaching and learning, as well as an AI education platform suitable for the level of elementary school. In order to apply various AI education platforms to the school field, it is necessary to train teachers in AI-related training to train them as AI education experts, and to continuously provide opportunities to experience AI education platforms. In this study, there are limitations to what is called 'a population perception survey'. because only 103 people were surveyed, and most of the experts are working in a specific area(Gyeonggi-do). In the future, it is judged that research targeting experts at the national level should be conducted to supplement these limitations.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.922-930
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• 2020

Marine accidents involving fishing boats, caused by a loss of stability, have been increasing over the last decade. One of the main reasons for these accidents is a sudden wind attacks. In this regard, the wind loads acting on the ship hull need to be estimated accurately for safety assessments of the motion and maneuverability of the ship. Therefore, this study aims to develop a computational model for the inlet boundary condition and to numerically estimate the wind load acting on a fishing boat. In particular, wind loads acting on a fishing boat at the wind speed profile boundary condition were compared with the numerical results obtained under uniform wind speed. The wind loads were estimated at intervals of 15° over the range of 0° to 180°, and i.e., a total of 13 cases. Furthermore, a numerical mesh model was developed based on the results of the mesh dependency test. The numerical analysis was performed using the RANS-based commercial solver STAR-CCM+ (ver. 13.06) with the k-ω turbulent model in the steady state. The wind loads for surge, sway, and heave motions were reduced by 39.5 %, 41.6 %, and 46.1 % and roll, pitch, and yaw motions were 48.2 %, 50.6 %, and 36.5 %, respectively, as compared with the values under uniform wind speed. It was confirmed that the developed inlet boundary condition describing the wind speed gradient with respect to height features higher accuracy than the boundary condition of uniform wind speed. The insights obtained in this study can be useful for the development of a numerical computation method for ships.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.383-390
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• 2021

The experiments in coastal engineering are very complex and a lot of components should be concerned. The experience has an important role in the successful execution. Hydraulic model experiments have been improved with the development of the wave generator and the advanced measuring apparatus. The hydraulic experiments have the advantage, that is, the stability of coastal structures and the hydraulic characteristics could be observed more intuitively rather than the numerical modelings. However, different experimental results can be drawn depending on the model scale, facilities, apparatus, and experimenters. In this study, two-dimensional hydraulic experiments were performed to suggest the guide of the test wave(random wave) generation, which is the most basic and important factor for the model test. The techniques for generating the random waves with frequency energy spectrum and the range for the incident wave height [(H_S)_M/(H_S)_T = 1~1.05] were suggested. The proposed guide for the test wave generation will contribute to enhancing the reliability of the experimental results in coastal engineering.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.85-100
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• 2023

Corporate ESG performance (environmental, social, and corporate governance) reflecting a company's strategic sustainability has emerged as one of the main factors in today's investment decisions. The traditional ESG performance rating process is largely performed in a qualitative and subjective manner based on the institution-specific criteria, entailing limitations in reliability, predictability, and timeliness when making investment decisions. This study attempted to predict the corporate ESG rating through automated machine learning based on quantitative and disclosed corporate financial information. Using 12 types (21,360 cases) of market-disclosed financial information and 1,780 ESG measures available through the Korea Institute of Corporate Governance and Sustainability during 2019 to 2021, we suggested a deep neural network prediction model. Our model yielded about 86% of accurate classification performance in predicting ESG rating, showing better performance than other comparative models. This study contributed the literature in a way that the model achieved relatively accurate ESG rating predictions through an automated process using quantitative and publicly available corporate financial information. In terms of practical implications, the general investors can benefit from the prediction accuracy and time efficiency of our proposed model with nominal cost. In addition, this study can be expanded by accumulating more Korean and international data and by developing a more robust and complex model in the future.

• The Journal of Bigdata
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• v.8 no.2
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• pp.149-163
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• 2023

Due to the continuous growth of the E-commerce market, the volume of orders that fulfillment centers have to process has increased, and various customer requirements have increased the complexity of order processing. Along with this trend, the operational efficiency of fulfillment centers due to increased labor costs is becoming more important from a corporate management perspective. Using historical performance data as training data, this study focused on real-time box recommendations applicable to packaging areas during fulfillment center shipping. Four types of data, such as product information, order information, packaging information, and delivery information, were applied to the machine learning model through pre-processing and feature-engineering processes. As an input vector, three characteristics were used as product specification information: width, length, and height, the characteristics of the input vector were extracted through a feature engineering process that converts product information from real numbers to an integer system for each section. As a result of comparing the performance of each model, it was confirmed that when the Gradient Boosting model was applied, the prediction was performed with the highest accuracy at 95.2% when the product specification information was converted into integers in 21 sections. This study proposes a machine learning model as a way to reduce the increase in costs and inefficiency of box packaging time caused by incorrect box selection in the fulfillment center, and also proposes a feature engineering method to effectively extract the characteristics of product specification information.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.4
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• pp.275-282
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• 2024

A recently proposed rapid-disassembly , carbon-minimized dismantle connection was tested using cyclic loading. To better understand the behavior of the test specimen, three-dimensional finite element (3D-FE) analyses were conducted using a "tied model" (bolted contact surfaces are tied together) and a "bolt-slip model" (contact surfaces slip and separate). The tied model suggests that plastic hinging of the beam occurs if the proposed connection behaves rigidly. The bolt-slip model suggests that the proposed connection, if manufactured and assembled properly, can dissipate energy to about 0.5 times that experienced by a rigid connection. However, when compared in a test, its moment-rotation hysteresis curve does not match well, which suggests that the low performance of the test specimen is attributable to a manufacturing deficiency. Regardless, the results corroborate the pinching phenomenon observed in the experimental hysteresis and fracture failure of the test specimen.

• The Magazine of the IEIE
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• v.29 no.6
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• pp.76-80
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• 2002

'Liquid Crystal의 상전이(相轉移)와 광학적 이방성(異方性)이 1888년과 1889년 F. Reinitzer와 O. Lehmann에 의해 Monatsch Chem.과 Z.Physikal.Chem.에 각각 보고된 후 부터 제2차 세계대전이 끝난 뒤인 1950년대 까지는 Liquid Crystal을 단지실험실에서의 기초학문 차원의 연구 대상으로만 다루어 왔다. 1963년 Williams가 Liquid Crystal Device로는 최초로 특허 출원을 하였으며, 1968년 RCA사의 Heilmeier등은 Nematic 액정(液晶)에 저주파(低周波) 전압(電壓)을 인가하면 투명한 액정이 혼탁(混濁)상태로 변화하는 '동적산란(動的散亂)'(Dynamic Scattering) 현상을 이용하여 최초의 DSM(Dynamic Scattering Mode) LCD(Liquid Crystal Display)를 발명하였다. 비록 150V 이상의 높은 구동전압과 과소비전력의 특성 때문에 실용화에는 실패하였지만 Guest-Host효과와 Memory효과 등을 발견하였다. 1970년대에 이르러 실온에서 안정되게 사용 가능한 액정물질들이 합성되고(H. Kelker에 의해 MBBA, G. Gray에 의한 Cyano-Biphenyl 액정의 합성), CMOS 트랜지스터의 발명, 투명도전막(ITO), 수은전지등의 주변기술들의 발전으로 인하여 LCD의 상품화가 본격적으로 이루어지게 되었다. 1971년에는 M. Shadt, W. Helfrich, J.L. Fergason등이 TN(Twisted Nematic) LCD를 발명하여 전자 계산기와 손목시계에 응용되었고, 1970년대 말에는 Sharp에서 Dot Matrix형의 휴대형 컴퓨터를 발매하였다. 이러한 단순 구동형의 TN LCD는 그래픽 정보를 표시하는 데에는 품질의 한계가 있어 1979년 영국의 Le Comber에 의해 a-Si TFT(amorphous Silicon Thin Film Transistor) LCD의 연구가 시작되었고, 1983년 T.J. Scheffer, J. Nehring, G. Waters에 의해 STN(Super Twisted Nematic) LCD가 창안되었고, 1980년 N. Clark, S. Lagerwall 및 1983년 K.Yossino에 의해 Ferroelectric LCD가 등장하여 LCD의 정보 표시량 증대에 크게 기여하였다. Color화의 진전은 1972년 A.G. Ficher의 셀 외부에 RGB(Red, Green, Blue) filter를 부착하는 방안과, 1981년 T. Uchida 등에 의한 셀 내부에 RGB filter를 부착하는 방법에 의해 상품화가 되었다. 1985년에는 J.L. Fergason에 의해 Polymer Dispersed LCD가 발명되었고, 1980년대 중반에 이르러 동화상(動畵像) 표시가 가능한 a-Si TFT LCD의 시제품(試製品) 개발이 이루어지고 1990년부터는 본격적인 양산 시대에 접어들게 되었다. 1990년대 초에는 STN LCD의 Color화 및 대형화(大型化) 고(高)품위화에 힘입어 Note-Book PC에 LCD가 본격적으로 적용이 되었고, 1990년대 후반에는TFT LCD의 표시품질 대비 가격경쟁력 확보로 인하여 Note-Book PC 시장을 독점하기에 이르렀다. 이후로는 TFT LCD의 대형화가 중요한 쟁점으로 부각되고 있고, 1995년 삼성전자는 당시 세계최대 크기의 22' TFT LCD를 개발하였다. 또한 LCD의 고정세(高情細)화를 위해 Poly Si TFT LCD의 개발이 이루어졌고, 디지타이져 일체형 LCD의 상품화가 그 응용의 폭을 넓혔으며, LCD의 대형화를 위해 1994년 Canon에 의해 14.8', 21' 등의 FLCD가 개발되었다. 대형화 방안으로 Tiled LCD 기술이 개발되고 있으며, 1995년에 Sharp에 의해 21' 두장의 Panel을 이어 붙인 28' TFT LCD가 전시되었고 1996년에는 21' 4장의 Panel을 이어 붙인 40'급 까지의 개발이 시도 되었으며 현재는 LCD의 특성향상과 생산설비의 성능개선과 안정적인 공정관리기술을 바탕으로 삼성전자에서 단패널 40' TFT LCD가 최근에 개발되었다. Projection용 디스플레이로는 Poly-Si TFT LCD를 이용하여 $25'{\sim}100'$사이의 배면투사형과 전면투사형 까지 개발되어 대형 TV시장을 주도하고 있다. 21세기 디지털방송 시대를 맞아 플라즈마디스플레이패널(PDP) TV, 액정표시장치 (LCD)TV, 강유전성액정(FLCD) TV 등 2005년에 약 1500만대 규모의 거대 시장을 형성할 것으로 예상되는 이른바 '벽걸이TV'로 불리는 차세대 초박형 TV 시장을 선점하기 위하여 세계 가전업계들이 양산에 총력을 기울이고 있다. 벽걸이TV 시장이 본격적으로 형성되더라도 PDP TV와 LCD TV가 직접적으로 시장에서 경쟁을 벌이는 일은 별로 없을 것으로 보인다. 향후 디지털TV 시장이 본격적으로 열리면 40인치 이하의 중대형 시장은 LCD TV가 주도하고 40인치 이상 대화면 시장은 PDP TV가 주도할 것으로 보는 시각이 지배적이기 때문이다. 그러나 이러한 직시형 중대형(重大型)디스플레이는 그 가격이 너무 높아서 현재의 브라운관 TV를 대체(代替)하기에는 시일이 많이 소요될 것으로 추정되고 있다. 그 대안(代案)으로는 비교적 저가격(低價格)이면서도 고품질의 디지털 화상구현이 가능한 고해상도 프로젝션 TV가 유력시되고 있다. 이러한 고해상도 프로젝션 TV용으로 DMD(Digital Micro-mirror Display), Poly-Si TFT LCD와 LCOS(Liquid Crystals on Silicon) 등의 상품화가 진행되고 있다. 인터넷과 정보통신 기술의 발달로 휴대형 디스플레이의 시장이 예상 외로 급성장하고 있으며, 요구되는 디스플레이의 품질도 단순한 문자표시에서 그치지 않고 고해상도의 그래픽 동화상 표시와 칼라 표시 및 3차원 화상표시까지 점차로 그 영역이 넓어지고 있다. <표 1>에서 보여주는 바와 같이 LCD의 시장규모는 적용분야 별로 지속적인 성장이 예상되며, 새로운 응용분야의 시장도 성장성을 어느 정도 예측할 수 있다. 따라서 LCD기술의 연구개발 방향은 크게 두가지로 분류할 수 있으며 첫째로는, 현재 양산되고 있는 LCD 상품의 경쟁력강화를 위하여 원가(原價) 절감(節減)과 표시품질을 향상시키는 것이며 둘째로는, 새로운 타입의 LCD를 개발하여 기존 상품을 대체하거나 새로운 시장을 창출하는 분야로 나눌 수 있다. 이와 같은 관점에서 현재 진행되고 있는 LCD기술개발은 다음과 같이 분류할 수 있다. 1) 원가 절감 2) 특성 향상 3) New Type LCD 개발.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.28-35
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• 2006

Statistical models of shape variability based on active shape models (ASMs) have been successfully utilized to perform segmentation and recognition tasks in two-dimensional (2D) images. Three-dimensional (3D) model-based approaches are more promising than 2D approaches since they can bring in more realistic shape constraints for recognizing and delineating the object boundary. For 3D model-based approaches, however, building the 3D shape model from a training set of segmented instances of an object is a major challenge and currently it remains an open problem in building the 3D shape model, one essential step is to generate a point distribution model (PDM). Corresponding landmarks must be selected in all1 training shapes for generating PDM, and manual determination of landmark correspondences is very time-consuming, tedious, and error-prone. In this paper, we propose a novel automatic method for generating 3D statistical shape models. Given a set of training 3D shapes, we generate a 3D model by 1) building the mean shape fro]n the distance transform of the training shapes, 2) utilizing a tetrahedron method for automatically selecting landmarks on the mean shape, and 3) subsequently propagating these landmarks to each training shape via a distance labeling method. In this paper, we investigate the accuracy and compactness of the 3D model for the human liver built from 50 segmented individual CT data sets. The proposed method is very general without such assumptions and can be applied to other data sets.