홀로그래픽 디지털 정보 저장장치에서의 이차원 인터리빙 구조

김민승,한승훈,양병춘,이병호,Kim, Min-Seung,Han, Seung-Hun,Yang, Byeong-Chun,Lee, Byeong-Ho 대한전자공학회 2001 電子工學會論文誌-SD (Semiconductor and devices) Vol.38 No.10

본 논문에서 우리는 홀로그래픽 디지털 정보 저장 장치를 위한 2차원 인터리빙 구조를 제안한다. 이 저장장치에서는 다량의 디지털이진 정보를 2차원 정보 영상(1000×1000 bits) 안에 실어서 기록 및 재생, 처리하게 된다. 따라서, 저장 장치에서 발생하는 연집 오류(burst error) 또한 2차원의 형태를 띄게 되며, 이를 극복하기 위해 정보 영상 안에서 효율적인 2차원 인터리빙을 해야 할 필요가 있다. 연집 오류의 형태와 위치가 불규칙적임을 감안하여 각 부호어의 bit들을 2차원 상으로 흩뜨리면, 각 부호어의 bit들은 정삼각 격자 구조를 이루며 분포해야 한다. 이러한 정삼각 격자 형태의 인터리빙을 구현하기 위한 요소와 알고리즘을 제안한다. In this paper, we propose a two-dimensional interleaving structure of holographic digital data storage. In this storage, many of the digital binary data are recorded, retrieved and processed in a two-dimensional data image (1000$\times$1000 bits). Therefore, burst errors in this digital device also have two-dimensional characteristics and it is required to use effective two-dimensional interleaving to overcome them. Bits of every code word should be distributed in an equilateral triangular lattice structure when they are scattered considering the random shape and occurrence of burst errors. We deal with factors and algorithm to construct this interleaving structure of equilateral triangular lattice.

딥러닝 기반 지능형 기술가치평가에 관한 연구: 심층신경망 학습을 통한 정성평가 지표 예측 모형

김민승(Kim, Min-Seung),이재식(Lee, Jaesik),오은식(Oh, Eun-Sik),이찬호(Lee, Chan-Ho),최지혜(Choi, Ji-Hye),장용주(Jang, Yong-Ju),이정희(Lee, Jeong-Hee),성태응(Sung, Tae-Eung) 한국기술혁신학회 2021 기술혁신학회지 Vol.24 No.6

최근 전 세계적으로 주목받고 있는 기술금융 지원정책은 저성장 기조의 경제 현황을 극복하기 위한 정부 부처 및 유관기관의 기업혁신 지원전략으로 부상하고 있다. 이에 힘입어 최근에는 기술가치 평가체계의 한계(장기간 · 고비용)를 개선한 웹 기반 지능형 평가시스템이 일부 평가기관을 중심으로 제공 중에 있으나, 여전히 사용자에게 전문적인 평가 지식을 요구한다는 점에서 한계가 존재한다. 본 논문에서는 기존 시스템의 정성평가 항목에 딥러닝 기반 추정을 적용, 현금흐름 산출로직에 연계하는 방안을 제시한다. 이는 일반적으로 준용되는 기술가치평가 방법론을 기반으로 이론적 타당성은 유지하되, 전문적 지식을 요구하는 세부지표점수들을 딥러닝 기반 추정을 적용함으로써 비전문가 수준에서도 손쉽게 보유 기술의 가치를 확인할 수 있는 수요자 편의성을 제공한다. 최종적으로 본 논문에서는 제안하는 인공신경망 기반 알고리즘을 통해 기업이 보유하고 있는 특허 또는 기술에 대해 객관적이고 신속한 평가를 수행할 수 있도록 하며, 기존 방법론이 내포하고 있던 장시간 · 고비용의 한계를 최소화하고 적시에 기술 기반 금융 활동에 대한 의사 결정을 지원할 수 있다는 점에서 그 활용성이 기대된다. The technology finance is emerging as a corporate innovation support strategy of government sectors in line with the low-growth economic trends. Therefore, some evaluation agencies are providing a web-based intelligent technology valuation framework, but there still exist limitations. In this study, we propose how to associate deep learning-based estimation results with cash flow calculation logics and how to automate them, without waiting until scoring qualitative factors among experts group. While holding theoretical validity based on technology valuation methodology generally accepted, it provides the demanders" convenience in that it enables commercialization support non-experts to easily identify the values of a technology, by deep learning-based estimation and automated calculation which required expertise knowledge regarding technology assessment. Ultimately, by deep learning-based algorithms we propose the objective, prompt valuation for a firm"s technologies or patents will be feasible and it is expected that they minimize the limitations in terms of long-term and high-cost in valuation and support decision-making for technology-driven finance activities.

Checking Degree of Related Information When Purchasing Food, and Evaluation and Purchasing Behavior of Environment-friendly agricultural products

Kim, Min-Seung(김민승),Park, Sun-Young(박선영) 한국소비문화학회 2010 소비문화연구 Vol.13 No.4

본 논문은 환경문제와 함께 중요한 사회적 이슈인 유전자재조합기술에 대한 소비자 의 태도에 따른 식품안전정보의 확인 정도 차이와 친환경농산물에 대한 소비자의 인식과 구매행동의 관련성에 관한 분석을 시도하였다. 본 연구의 주요결과는 다음과 같다. 첫째, 소비자의 환경문제 및 유전자재조합 기술에 대한 태도를 유형화 시키는 요인은 환경문제관심 요인, 유전자재조합 기술 부정적 인식요인, 유전자재조합기술 혜택추구요인 환경비용 지불의사요인의 4가지로 분리되었다. 이 요인들을 이용하여 군집분석을 수행한 결과 5유형의 소비자들로 분류되었다. 서로 다른 소비자유형은 식품안전정보 확인정도에 통계적으로 유의미한 차이를 보였다. 둘째, 친환경농산물에 대한 인식과 구매행동에 있어서 5개 소비자 집단 모두 차이를 보였다. 전체 조사대상자들의 친환경농산물에 대한 인식은 높은 편인 것으로 나타났으며, 구매행동은 이와 같은 인식수준에는 못 미치는 것으로 나타났다. 본 연구 결과를 종합하면, 친환경 농산물의 판매를 촉진시키기 위해서는 친환경 농산물의 우수성을 알리는데 좀 더 환경 관련 정보를 제공해주는 것이 중요한 것으로 나타났다. 또한 친환경 농산물의 구매가능성이 높은 혜택 추구형 환경 개선집단과 보수적 환경개선 집단이 추구하는 최적화된 환경관련 주요 정보를 적절히 제공하는 것이 필요한 것으로 나타났다. In this study, checking degree of related information when purchasing food, and evaluation and purchasing behavior of environment-friendly agricultural products were analyzed. The followings are the results of the study. First, consumers' attitude toward environmental problem and GMO technology were classified as four factors. they were "interest in environmental problem", "Negative attitudes toward GMO technology", "Benefit seeking from GMO technology", and "Accepting environmental expense", and these factors combined explained 60.25% of variance. Second, consumers clustered into five groups which are "advantage seeker with interests in environment improvement(104, 22%)", "unconcern(51, 11%)", "conservatives with interests in environment improvement(87, 18%)", "advantage seeker maintaining environment(147, 31%)", and "individualist with no concern(84, 18%)", depending on the characteristics of each group. Consumers in different groups showed significant differences in age, living expense, food expense, educational level, and occupation. Third, expiration date, manufactured date, price and country of origin in order were checked more frequently, while license number for business & item was the least checked information when purchasing food. Consumers in "advantage seeker with interests in environment improvement" group showed the highest checking degree of information. Fourth, there were differences in evaluation and purchasing behavior of environment-friendly agricultural products among five groups. Evaluations of environment-friendly agricultural products were fairly good. However, purchasing behavior of environment-friendly agricultural products were not as good, considering evaluation scores. In conclusion, to promote sales of environment-friendly agricultural products, it is important to inform consumers superiority the of environment-friendly agricultural products in environmental aspects, and provide the information accurately which were mostly checked by consumers in "advantage seeker with interests in environment improvement" group and "conservatives with interests in environment improvement" group. More follow-up studies on consumers' attitudes, recognition, and preparations about factors which threaten food safety, like importation of american beef, beef traceability, pesticides, and GMO technology, and so on, are needed.

머신러닝을 이용한 와인 품질 예측분석

김민승(Min-Seung Kim),정재현(Jae-hyeon Jeong),김종민(Jong-min Kim) 한국정보통신학회 2022 한국정보통신학회 종합학술대회 논문집 Vol.26 No.1

본 연구는 와인 데이터를 활용하여 와인 품질에 영향을 미치는 요인에 대해 상관관계 분석을 실시하였고, 그 결과를 토대로 와인 품질의 기준을 예측 하였다. 본 연구에서 사용된 데이터셋은 포르투갈의 비뉴베르드(Vinho verde)에서 생산된 레드와인의 1599개, 화이트와인 4898개의 관측지의 데이터로 총 6497개를 사용하였다. 변수 항목은 물리적, 화학적 분석 테스트를 통해 와인 성분을 나타내는 12가지 성분 변수, 총 1599개의 관측지, 세계 와인 3대 생산지국가(프랑스, 이탈리아, 스페인)들의 대표와인 한 개씩 총 3개를 추가하였고, 그 국가들의 기후변화 데이터를 적용하여 분석하였다. In this study, we used wine data to perform correlation analysis on factors that affect wine quality, and predicted wine quality standards based on the results. The dataset used in this study used data from 1599 red wines and 4898 white wines produced in Vinho verde, Portugal, for a total of 6497. The variable items are 12 kinds of component variables that represent wine components through physical and chemical analysis tests, a total of 1599 observations, and a total of one of the representative wines of the three major wine producing regions in the world (France, Italy, Spain). Added 3 pieces. Analysis was made by applying national climate change data.

Arthrospira platensis 추출물의 항산화 및 UVB에 의해 유도된 활성산소 생성에 미치는 영향

김민승(Min Seung Kim),양재찬(Jae-Chan Yang),김보애(Bo-Ae Kim) 한국응용과학기술학회 (구.한국유화학회) 2020 한국응용과학기술학회지 Vol.37 No.2

지구상에서 가장 오래된 해양 미세조류로 알려진 스피룰리나는 인체에 필요한 영양성분을 대부분 함유하고 있는 것으로 알려져 있다. 그 구성성분으로는 phycocyanin, chlorophyll, β-carotene 과 같은 다양한 물질을 다량 함유한다고 보고되고 있으며, 노화 및 미백효과가 있다고 알려져 있다. 본 연구에서는 스피룰리나 정제수 추출물의 UVB로 유도된 활성산소종 ROS (reactive oxygen species) 소거능과 항산 화능을 확인하였다. 스피룰리나 정제수 추출물 0.05, 0.10, 0.50 1.0 mg/mL의 DPPH 라디칼 소거능, FRAP 환원능 및 ABTS + 라디칼 소거능을 측정하여 항산화효과를 확인하였다. 대체실험동물모델인 Zebrafish를 이용하여 스피룰리나 정제수 추출물을 0.05, 0.10, 0.50 mg/mL 농도로 처리하여 응고율, 부화율, 심장독성을 측정하였으며, 스피룰라나 추출물을 0.05, 0.10, 0.50 mg/mL 농도로 처리한 후, DCFH-DA로 염색하여 UVB로 유도된 ROS 저해효과를 확인하였다. 항산화효과 측정 결과 양성대조군인 ascorbic acid와 비교시 DPPH, Frpa, ABTS 모두 농도 의존적으로 항산화 효과가 있음을 확인하였다. 대체 실험동물인 Zebrafish를 이용하여 응고율과 부화율, 심박수를 측정한 결과 0.5 mg/mL을 제외한 0.05, 0.10 mg/mL에서는 대조군과 비교 시 독성이 없음을 확인 하였다. UVB로 유도된 Zebrafish의 ROS 소거 능은 양성대조군에 비해 높은 ROS 감소 효과를 나타내었다. 본 연구의 결과는 스피룰라나 정제수 추출물이 자외선 및 피부 보호 화장품 소재로 사용가치가 있음을 시사한다. Arthrospira platensis is the oldest marine microalgae on the planet, is said to contain most of the nutrients needed by the human body. It‘s components are reported to contain a large amount of various substances such as phycocyanin, chlorophyll and β-carotene, and are known to have an aging and whitening effect. In this study, UVB-induced reactive oxygen species reduction efficacy and antioxidant activity of spirulina purified water extract were investigated. effect was confirmed by measuring DPPH radical scavenging activity, FRAP reducing power and ABTS + radical scavenging activity of 0.05, 0.10, 0.50 1.0 mg/mL of spirulina purified water extract. The coagulation rate, hatching rate and heart rate toxicity were measured by treating spirulina purified water extract with 0.05, 0.10, 0.50 mg/mL concentration using Zebrafish, an alternative experimental animal model. UVB-induced ROS measurement was treated with spirulina extract at 0.05, 0.10, 0.50 mg/mL concentration, and then stained with DCFH-DA to confirm the inhibitory effect of ROS. As a result of measuring antioxidant effect, DPPH, FRAP and ABTS + showed concentration-dependent antioxidant effects in comparison with ascorbic acid. and measuring the coagulation rate, hatching rate, and heart rate using Zebrafish, an alternative experimental animal, it was confirmed that there was no toxicity in 0.05 and 0.10 mg/mL except 0.5 mg/mL compared to the control group. The ROS scavenging activity of UVB-induced zebrafish showed higher ROS reduction than the positive control. The results of this study suggest that spirulina and purified water extracts are valuable for UV and skin protection cosmetics.

이산요소법을 활용한 점성토 환경에서의 토양 입자 크기에 따른 몰드보드 플라우 견인력 예측 시뮬레이션

김민승(Min Seung Kim),배보민(Bo Min Bae),정대위(Dae Wi Jung),안장현(Jang Hyeon An),최세오(Se O Choi),성시원(Si Won Sung),김연수(Yeon Soo Kim),김용주(Yong Joo Kim),Sang Hyeon Lee 유공압건설기계학회 2024 드라이브·컨트롤 Vol.21 No.3

In the agricultural machinery field, load analysis is mostly done through field tests. However, field tests are time-consuming and costly. There are also limitations in test conditions due to weather conditions. To overcome these environmental limitations, research on load analysis through simulation in a virtual environment is actively being conducted. This study aimed to select the most appropriate soil particle size for modeling by analyzing the effect of soil particle size on the prediction of draft force of the implement using simulation and soil particle modeling in a virtual environment with the discrete element method (DEM) software. The accuracy was verified by simulating the draft force for the same moving speed by soil particle size. For soil particle modeling, DEM soil modeling was performed by designing soil property measurement procedure. Soil particle correction was performed with a virtual vane shear test. Average DEM simulation results showed an error of 27.39% (19.43~40.66%) compared to actual measured data. The possibility of improvement was confirmed through additional research. Results of this study provide useful information for selecting soil particle size in soil modeling using DEM from the perspective of agricultural machinery research.

지도학습 기반의 다중회귀분석을 이용한 실업률 결정요인에 관한 연구

김민승(Min-Seung Kim),이찬호(Chan-Ho Lee),이정희(Jeong-Hee Lee),성태응(Tae-Eung Sung) 한국정보과학회 2019 한국정보과학회 학술발표논문집 Vol.2019 No.6

석면 해체 작업의 위험성평가모델 비교 분석

김동규 ( Kim Dong-gyu ),김민승 ( Kim Min-seung ),이수민 ( Lee Su-min ),김유진 ( Kim Yu-jin ),한승우 ( Han Seung-woo ) 한국건축시공학회 2022 한국건축시공학회 학술발표대회 논문집 Vol.22 No.2

As the danger of exposure to the asbestos has been revealed, the importance of demolition asbestos in existing buildings has been raised. Extensive body of study has been conducted to evaluate the risk of demolition asbestos, but there were confined types of variables caused by not reflecting categorical information and limitations in collecting quantitative information. Thus, this study aims to derive a model that predicts the risk in workplace of demolition asbestos by collecting categorical and continuous variables. For this purpose, categorical and continuous variables were collected from asbestos demolition reports, and the risk assessment score was set as the dependent variable. In this study, the influence of each variable was identified using logistic regression, and the risk prediction model methodologies were compared through decision tree regression and artificial neural network. As a result, a conditional risk prediction model was derived to evaluate the risk of demolition asbestos, and this model is expected to be used to ensure the safety of asbestos demolition workers.

오토 북 스크롤

김승재(Seung-Jae Kim),김건두(Geon-Du Kim),김민승(Min-Seung Kim),박동일(Dong-Il Park),변황우(Hwang-Woo Byun),고영진(Yeong-Jin Goh) 대한전기학회 2023 대한전기학회 학술대회 논문집 Vol.2023 No.11

Hybrid CNN-LSTM 알고리즘을 활용한 도시철도 내 피플 카운팅 연구

최지혜(Ji-Hye Choi),김민승(Min-Seung Kim),이찬호(Chan-Ho Lee),최정환(Jung-Hwan Choi),이정희(Jeong-Hee Lee),성태응(Tae-Eung Sung) 한국지능정보시스템학회 2020 지능정보연구 Vol.26 No.2

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens or commuters’ convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4x4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5°C, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4x4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4x4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of publi