• Journal of Biosystems Engineering
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• v.17 no.4
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• pp.363-369
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• 1992

The aim of this study was to examine the blurring effects on performance of the experimental fruit grader in grading Fuji apples by size and coloration of the whole surface of individual apples. The grader consisted of a black/white image prcessing system, one camera, and utilized the algorithm developed for high speed sorting in the previous study. The results are summarized as follows : 1. With the algorithm developed in the previous study, it took 0.27~0.33 second in analyzing the size and coloration of an apple, and relative errors were within 3% for size and 1.3% for coloration. 2. The effect of blurring increased linearly with the conveying speed of apple and showed more significant effect on detection of coloration than on determining of size. 3. Considering the blurring effect, capacity of the experimental fruit grader was estimated to 7,500 apples per hour.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.9-9
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• 2017

입자거동해석소프트웨어(EDEM)은 DEM(Discrete Element Method)기법을 이용한 입자 거동 전용 해석툴로 입자 유입량, 위치 등을 조절하여 입자거동과 관련된 제품 개발, 프로세스 최적화를 위한 비용 및 시간 절감에 활용도가 뛰어난 소프트웨어이다. EDEM을 활용하기 위해선 적용대상에 대한 물성치를 적용하여야 한다. 따라서 본 연구에서는 EDEM를 이용하여 현재 연구개발 중인 카드클리너 방식의 고추 선별기의 성능을 분석을 수행하기 위해 고추 물성측정 실험을 수행 하였다. EDEM을 이용한 입자거동해석에 필요한 개인 물성치에는 포아송비, 전단탄성계수, 밀도가 있다. 또한 입자-입자, 입자-Geometry 간의 상호관계를 위한 물성치인 반발계수, 정지마찰계수, 구름마찰계수가 필요하다. 공시 시료인 고추는 광주광역시 남구 승촌동 소재의 개인농가 Plastic 온실로 재배된 '천상'품종을 사용하였다. 푸아송 비와, 전단 탄성계수를 측정하기 위한 인장시험기기로는 만능인장시험기(TA-XT2, Stable Micro, 영국)를 이용하였으며, 인장에 의한 고추의 변형량 축정은 초고속카메라(NX4-SI, IDT, 미국)을 이용하였다. 밀도는 비중병법에 기초하여 질량과 부피를 측정하여 밀도를 계산하였다. 반발계수는 고추의 충돌 실험을 통해 변화한 높이를 이용하여 계산하였고, 충동 실험을 통해 변화한 높이는 초고속카메라를 이용하여 측정하였다. 정지마찰계수와 구름마찰계수는 고추의 미끄러짐이 시작하는 각도와 등속도 운동으로 구르는 각도를 초고속카메라를 이용하여 측정 후 계산하였다. 모든 실험은 3번 반복을 통해 평균값을 시험 결과 값으로 이용하였다. 고추의 대한 물성치 실험결과 고추의 푸아송 비는 0.294(std : 0.2), 전단탄성계수 4.624E+06 Pa, 밀도 $600kg/m^3$로 나타났다. 또한 입자-입자 간의 물성치인 반발계수는 0.383, 정지마찰계수는 0.455, 구름마찰 계수는 0.043로 나타났다. 추후 본 연구에서 측정한 고추의 물성치를 적용한 EDEM 입자거동해석 시뮬레이션을 통해 카드클리너 방식의 고추 선별기의 성능에 대한 분석을 하고자 한다.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.164-172
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• 2004

For a local search algorithm to find a bettor quality solution it is required to generate and evaluate a sufficiently large number of candidate solutions as neighbors at each iteration, demanding quite an amount of CPU time. This paper presents a method of selectively generating only good-looking candidate neighbors, so that the number of neighbors can be kept low to improve the efficiency of search. In our method, a newly generated candidate solution is probabilistically selected to become a neighbor based on the quality estimation determined heuristically by a very simple evaluation of the generated candidate. Experimental results on the problem of load balancing for production scheduling have shown that our candidate selection method outperforms other random or greedy selection methods in terms of solution quality given the same amount of CPU time.

• Resources Recycling
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• v.26 no.1
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• pp.69-77
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• 2017

Used small household appliances(small e-waste) consists of a variety of complex materials and components. The small e-waste is mainly composed of plastics and an important potential source of waste plastic. The black plastics, particularly are very difficult to separate by resin type and therefore these are mainly recycled in the form of a mixtures. In the present study, the sorting technologies such as gravity and electro static separation, near-infrared ray(NIR) and IR/Raman optical sorting separation on mixture of black plastics were analyzed and their limitations on sorting process were also investigated. The Laser Induced Breakdown Spectroscopy(LIBS) spectrum of each black plastics was used for identification of black plastics by resin type, and after analyzing the normalization operation, Principal Component Analysis(PCA) was carried out. The spectrum data was optimized through PCA process. In order to improve the identification accuracy and sorting efficiency of black plastics, it is necessary to design a classifier with high efficiency and to improve the performance and reliability of the classifier by applying the field of intelligent algorithms.

• Microbiology and Biotechnology Letters
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• v.3 no.3
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• pp.117-122
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• 1975

In order to develop an activated sludge which can be used for both waste treatment and protein source of animal feed, microorganisms were isolated from sewages of various wheat or sweet potato starch processing plants and their activities were tested. Out of 32 isolates which composed of two protozoan genera and 13 bacterial strains, were screened and three bacterial stranis were found to be most effective in both floe-formation and wheat starch waste liquid stabilization.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2341-2347
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• 2016

In this paper, we implement monitoring system for grain sorting using a high-speed FPGA and embedded LINUX. The proposed system is designed by base on web server and web-based applications while existing system was designed by base on stand-alone mode.The interface the Web server with high speed hardware of FPGA is designed on the implemented monitoring system. The proposed system has the advantages of multi-tasking on Linux web server and real-time high speed on FPGA also. The control logic of a high speed rate line-scan CCD camera, the method of center of gravity, HSL decoding and the interface on the Web server are implemented in FPGA. The implemented monitoring system has the advantage of being able to control the grain monitoring, system failure and recovery remotely by web application. As a result, we can upgrade the performance of sorting quality compared by existing system.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.541-548
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• 2016

The use of social media is already essential as a source of information for listening user's various opinions and monitoring. We define social 'risks' that issues effect negative influences for public opinion in social media. This paper aims to discriminate various linguistic features and reveal their effects for building an automatic classification model of social risks. Expecially we adopt a word embedding technique for representation of linguistic clues in risk sentences. As a preliminary experiment to analyze characteristics of individual features, we revise errors in automatic linguistic analysis. At the result, the most important feature is NE (Named Entity) information and the best condition is when combine basic linguistic features. word embedding, and word clusters within core predicates. Experimental results under the real situation in social bigdata - including linguistic analysis errors - show 92.08% and 85.84% in precision respectively for frequent risk categories set and full test set.

• Resources Recycling
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• v.19 no.3
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• pp.24-32
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• 2010

In the present work, a new separation system with rotating rakes has been developed to separate the film-based plastics from the recyclable materials, and environment assessment is also carried out during operation of the device. Capacity of the device was about 5.3 ton/hr at a rakes rotation speed of 26.0 rpm (the number of rakes in the 1st, 2nd and 3rd trials were 39, 52 and 48, respectively) and a belt conveyor speed of 38.5m/min, which satisfied the initial design capacity (5.0 ton/hr). Recovery ratio and purity of the plastic films were 92.6% and 96.5%, respectively at a rotation speed of 28 rpm. The levels of noise, vibration and particulate emission were below material standard regulatory limits. Plastic refused fuel (RPF) was also prepared with the recovered films. The calorific value and chlorine content of the prepared RPF were 9,740 kcal/kg and 0.18%, respectively which satisfy the first grade quality specification of the Korean RPF standard. As a result of this work, recovery of energy resources from the municipal solid waste is possible by adopting the developed separation device.

• Korean Journal of Food Science and Technology
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• v.39 no.3
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• pp.315-322
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• 2007

This study was carried out to investigate the functional activities of microorganisms isolated from kochujang, such as fibrinolytic, immunostimulating, and cytotoxical activities, and to apply these microorganisms to kochujang products. Ninety-one microbial strains with proteolytic activity were selected from 294 strains isolated from traditional and commercial kochujang. Three strains (TPP 0014, TPP 6013, and TPP 6015) with high fibrinolytic activity were tested for their immunostimulating and cytotoxical activities. For the assessment of macrophage activation, cytokines such as tumor necrosis factor, $interleukin-1{\alpha}$ and nitrogen oxide were measured with the murine macrophage cell line RAW 264.7. In addition, the cytotoxical activities of the three strains were examined by MTT assay on the colon cancer cell line SNU-C4 and normal cell line CHO-K1. Using an API identifying kit, two of the microbial strains (TPP 0014 and TPP 6015) were identified as Bacillus stearothermophilus and the other strain (TPP 6013) was identified as B. amyloliquefacience.

• The Journal of Engineering Geology
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• v.33 no.4
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• pp.673-687
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• 2023

Exploratory data analysis is the process of observing and understanding data collected from various sources to identify their distributions and correlations through their structures and characterization. This process can be used to identify correlations among conditioning factors and select the most effective factors for analysis. This can help the assessment of landslide susceptibility, because landslides are usually triggered by multiple factors, and the impacts of these factors vary by region. This study compared two stages of exploratory data analysis to examine the impact of the data exploration procedure on the landslide prediction model's performance with respect to factor selection. Deep-learning-based landslide susceptibility analysis used either a combinations of selected factors or all 23 factors. During the data exploration phase, we used a Pearson correlation coefficient heat map and a histogram of random forest feature importance. We then assessed the accuracy of our deep-learning-based analysis of landslide susceptibility using a confusion matrix. Finally, a landslide susceptibility map was generated using the landslide susceptibility index derived from the proposed analysis. The analysis revealed that using all 23 factors resulted in low accuracy (55.90%), but using the 13 factors selected in one step of exploration improved the accuracy to 81.25%. This was further improved to 92.80% using only the nine conditioning factors selected during both steps of the data exploration. Therefore, exploratory data analysis selected the conditioning factors most suitable for landslide susceptibility analysis and thereby improving the performance of the analysis.