• 제목/요약/키워드: Co-occurrence probability

검색결과 37건 처리시간 0.023초

우리나라 하수처리장 방류수 수질현황 및 특성 (Survey of the Secondary Effluents from Municipal Wastewater Treatment Plants in Korea)

  • 김영철;안익성;강민기
    • 한국물환경학회지
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    • 제21권2호
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    • pp.158-168
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    • 2005
  • In this study, the discharging effluents from have been 9 municipal wastewater treatment plants surveyed for 1 year-period. Statistics including probability distribution, cumulative occurrence concentration and other statistical parameters were presented. In addition, treatment performance and its stability were also discussed. Most of the plants, have an operational problem of high soluble organic content in the secondary effluent which may be associated with the integrated treatment of human and livestock manures. Nitrogen concentration in the effluents were usually higher during the period of summer and winter. It was found that this is mainly due to lack of the proper C/N ratio during the summer, or/and the effects of low temperature and less dilution by dry weather during the winter. Phosphorus concentration is sharply increased in June. Discussion with plant operators told that it is due to the dissolution of phosphate from the sludge accumulated in the primary settling tanks from the early spring to june. During this period, usually, sludge treatment line is highly overloaded with flush-outs of the sediments also stored in the bottom of combined sewer due to the low flow during winter season. Most of the plants can meet new effluent discharge limits of the nitrogen and phosphorus, and total coliform without further treatment.

Evaluation of the relationship between maximum tsunami heights and fault parameters in Korea

  • Song, Min-Jong;Kim, Chang Hee;Cho, Yong-Sik
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.275-275
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    • 2022
  • Tsunamis triggered by undersea earthquakes have the characteristic of longer wavelengths and can propagate a very long distance. Although the occurrence frequency of tsunami is low, it can cause casualties and properties. Historically, tsunamis that occurred on the western coast of Japan attacked the eastern coast of the Korean Peninsula and damaged the property and the loss of human life in 1983 and 1993. By tsunami in 1983 especially, 2 people were killed, and more than 200 casualties occurred. In addition, it caused 2 million dollars in property damage at Imwon Port. In 2011, The eastern cities of Japan: Iwate, Miyagi, Ibaraki, and Fukushima were damaged by a tsunami that occurred near onshore along the Pacific ocean and caused more than 300 billion dollars in property damage, and 20,000 casualties occurred. Moreover, those provoked nuclear power plant meltdown at Fukushima. In this study, it was carried out a relationship between maximum tsunami heights and fault parameters of earthquake: strike angle, dip angle, and slip angle at Imwon port. Those fault parameters are known that it does not relate to the magnitude of earthquake directly. Virtual tsunamis, which could be triggered by probable undersea earthquakes in the future, were investigated and mutual information based on probability and information theory was introduced to figure out the relationship between maximum tsunami height and fault parameters. Fault parameters were evaluated according to the strong relationship with maximum tsunami heights finally.

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운항 해역별 자율운항선박 원격운항 상황 발생 확률 추산 시뮬레이션 모델 (Autonomous Ship's Remote Operation Situation Occurrence Probability Estimation Model based on Navigation Areas)

  • 황태웅;황태민;이다인;박혜인;윤익현
    • 해양환경안전학회지
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    • 제29권7호
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    • pp.910-914
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    • 2023
  • 4차 산업혁명의 도래로 인한 기술혁신은 자율운항선박을 중심으로 해상 운송분야까지 활발한 발전을 불러왔다. 특히, 현재의 선원이 직접 운항하는 방식인 유인선박 사이에서 운항하게 될 자율운항선박은 자율도에 따라 원격제어를 통해 운항을 수행하며, 육상에서 이를 제어할 원격운항자에 대한 관심 또한 늘어나고 있다. 하지만 아직 원격운항자가 개입이 필요한 상황이 동시에 발생하는 등을 고려한 원격운항자 최소 인력 요구사항에 대한 연구는 부족한 상황이다. 본 연구는 특정 해역 구간의 누적된 항적데이터를 활용하여 선박간에 발생할 수 있는 조우상황에서 원격운항자의 개입이 필요한 상황을 정의하고, 해당 구간을 특정 규모의 자율운항선박 선대로 운항하였을 때, 원격운항자의 개입이 동시에 필요한 상황이 얼마나 발생하는지를 시뮬레이션을 통해 확인하였다. 연구의 결과는 향후 실제 자율운항선박 선대를 운행할 원격운항센터의 원격운항자의 적정인력 배치 등의 계획 또는 정책 수립에 활용될 기초 자료로 활용될 것으로 기대한다.

컬러 프린터 영상의 모폴로지 특징과 지도 학습 모델 분류기를 활용한 위변조 지폐 판별 알고리즘 (Counterfeit Money Detection Algorithm based on Morphological Features of Color Printed Images and Supervised Learning Model Classifier)

  • 우귀희;이해연
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제2권12호
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    • pp.889-898
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    • 2013
  • 고성능 영상 장비의 대중화와 강력한 이미지 편집 소프트웨어의 출현으로 인해 지폐 및 유가 증권 등을 고품질로 위변조가 가능해졌다. 특히 컬러 레이저 프린터의 범용화로 인하여 화폐 위변조 범죄는 급격히 증가하고 있지만, 일반인이 이를 판별하는 비율은 낮은 수준이며 판별 기기도 고가이다. 본 연구에서는 범용 스캐너와 컴퓨터 시스템을 활용하여 화폐의 위변조를 탐지하기 위한 알고리즘을 제안하였다. 먼저 지폐의 인쇄방식과 다른 컬러 프린터의 인쇄 특징을 계산하기 위하여 모폴로지 기술과 명암도 동시 발생 행렬을 활용하였다. 그 후 계산된 특징들을 지도학습 모델 분류기에 적용하여 훈련을 시켰다. 이렇게 훈련된 분류기에 판별을 위한 지폐를 입력하고 위변조 여부에 대한 분석을 수행한다. 제안한 알고리즘의 성능을 분석하기 위하여 위변조 지폐의 판별률과 인쇄에 사용한 프린터의 판별률로 나누어 평가를 하였다. 또한 기존의 컬러 프린터 판별에 사용되었던 위너필터를 사용한 기술과 비교를 수행하였다. 그 결과 제안한 알고리즘이 위변조 지폐 식별에 있어서 91.92%, 위변조기기의 식별에 있어서 94.5% 이상 정확도를 보여 기존 컬러 프린터의 특징 추출 방법을 활용한 것보다 우수한 것으로 나타났다.

Species Diversity Analysis of Mushrooms Collected in Mt. Chiak

  • Lee, Byung-Kook;Kim, Kyoung Su;Eom, Ki-Cheol;Seok, Soon-Ja
    • 한국균학회소식:학술대회논문집
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    • 한국균학회 2014년도 춘계학술대회 및 임시총회
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    • pp.19-19
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    • 2014
  • This study included the analysis of mushroom data collected from Mt. Chiak in Gangwon-do using various methods. Former studies of Korean mushrooms are limited by regional characters and there is less species diversity among the regions. This study tried to find a way for the forecast of mushroom distribution and appearance by indexes of species diversity. The indexes used in this study include the number of fungi (N), the number of species (S), similarity index (C), richness index (R1, R2), variety index (V1, V2), evenness index (E1, E2, E3, E4, E5), and dominance index (D1) to analyze variety of species diversity. Analyses of data of fungi using a multistage cluster sampling indicate that the average value of C for years was higher than the average value of C for areas. The mushrooms consisted of 208 species in 686 individuals in limited fungal collection from 2002 to 2003. One hundred thirty nine species in 393 individuals were collected in 2002, and 122 species 293 individuals were collected in 2003. The individuals collected in 2003 were smaller than 2002's individuals. Similarity, richness, and variety indexes' values of 2003 were reduced than 2002's values but dominance index of 2003 was increased than 2002's value. Generally the species diversity of the environment to evaluate the index of similarity, richness, and variety was a higher index; dominance index was lower than that of the surrounding environment, suggesting a good diversity. As a result, the occurrence of mushrooms in the surrounding environment and the various factors seem fell in 2002 compared to 2003. The majority genus of the limited fungal collection was Mycena genus in 63 individuals; the majority species was Laccaria laccata in 34 individuals. Ninety three species in 106 individuals were collected by the extended collection and the majority genus of the extended collection was Amanita genus in 17 individuals; the majority species was Amanita citrina (Schaeff.) Pers. which was found in 5 individuals. This demonstrates that periodical similarity's value was 0.159 is higher than special similarity's 0.119. This indicates that the probability of the appearance of same mushrooms in the same area in following year is higher than the probability of the appearance of same mushrooms in the surrounding area in same year. The value of coefficient of variation (CV), in which the amount of change is much or less by N is higher than the CV value by S. CV value of dominance index(D) was the highest r point among other indexes, and evenness index (E) was the lowest point among other indexes. The correlation matrix with 66 combinations between the indexes, the combinations with correlations was 46 combinations. These results revealed that indexes of R1, V2, and E1 were proper to represent species diversity of fungi based on the correlation matrix and the theory of statistical independence which means there is no or less mutual association. This research would contribute to the study about variable living creature by measuring method and in the future this would be used to figure out regulation about fungi with their correlation, values in ecosystem, develop improving new models about agricultural fungi species and numbers by investigating agricultural variable species.

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Estrus Detection in Sows Based on Texture Analysis of Pudendal Images and Neural Network Analysis

  • Seo, Kwang-Wook;Min, Byung-Ro;Kim, Dong-Woo;Fwa, Yoon-Il;Lee, Min-Young;Lee, Bong-Ki;Lee, Dae-Weon
    • Journal of Biosystems Engineering
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    • 제37권4호
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    • pp.271-278
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    • 2012
  • Worldwide trends in animal welfare have resulted in an increased interest in individual management of sows housed in groups within hog barns. Estrus detection has been shown to be one of the greatest determinants of sow productivity. Purpose: We conducted this study to develop a method that can automatically detect the estrus state of a sow by selecting optimal texture parameters from images of a sow's pudendum and by optimizing the number of neurons in the hidden layer of an artificial neural network. Methods: Texture parameters were analyzed according to changes in a sow's pudendum in estrus such as mucus secretion and expansion. Of the texture parameters, eight gray level co-occurrence matrix (GLCM) parameters were used for image analysis. The image states were classified into ten grades for each GLCM parameter, and an artificial neural network was formed using the values for each grade as inputs to discriminate the estrus state of sows. The number of hidden layer neurons in the artificial neural network is an important parameter in neural network design. Therefore, we determined the optimal number of hidden layer units using a trial and error method while increasing the number of neurons. Results: Fifteen hidden layers were determined to be optimal for use in the artificial neural network designed in this study. Thirty images of 10 sows were used for learning, and then 30 different images of 10 sows were used for verification. Conclusions: For learning, the back propagation neural network (BPN) algorithm was used to successful estimate six texture parameters (homogeneity, angular second moment, energy, maximum probability, entropy, and GLCM correlation). Based on the verification results, homogeneity was determined to be the most important texture parameter, and resulted in an estrus detection rate of 70%.

Predicting PM2.5 Concentrations Using Artificial Neural Networks and Markov Chain, a Case Study Karaj City

  • Asadollahfardi, Gholamreza;Zangooei, Hossein;Aria, Shiva Homayoun
    • Asian Journal of Atmospheric Environment
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    • 제10권2호
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    • pp.67-79
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    • 2016
  • The forecasting of air pollution is an important and popular topic in environmental engineering. Due to health impacts caused by unacceptable particulate matter (PM) levels, it has become one of the greatest concerns in metropolitan cities like Karaj City in Iran. In this study, the concentration of $PM_{2.5}$ was predicted by applying a multilayer percepteron (MLP) neural network, a radial basis function (RBF) neural network and a Markov chain model. Two months of hourly data including temperature, NO, $NO_2$, $NO_x$, CO, $SO_2$ and $PM_{10}$ were used as inputs to the artificial neural networks. From 1,488 data, 1,300 of data was used to train the models and the rest of the data were applied to test the models. The results of using artificial neural networks indicated that the models performed well in predicting $PM_{2.5}$ concentrations. The application of a Markov chain described the probable occurrences of unhealthy hours. The MLP neural network with two hidden layers including 19 neurons in the first layer and 16 neurons in the second layer provided the best results. The coefficient of determination ($R^2$), Index of Agreement (IA) and Efficiency (E) between the observed and the predicted data using an MLP neural network were 0.92, 0.93 and 0.981, respectively. In the MLP neural network, the MBE was 0.0546 which indicates the adequacy of the model. In the RBF neural network, increasing the number of neurons to 1,488 caused the RMSE to decline from 7.88 to 0.00 and caused $R^2$ to reach 0.93. In the Markov chain model the absolute error was 0.014 which indicated an acceptable accuracy and precision. We concluded the probability of occurrence state duration and transition of $PM_{2.5}$ pollution is predictable using a Markov chain method.

A Korean Homonym Disambiguation System Based on Statistical, Model Using weights

  • Kim, Jun-Su;Lee, Wang-Woo;Kim, Chang-Hwan;Ock, Cheol-young
    • 한국언어정보학회:학술대회논문집
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    • 한국언어정보학회 2002년도 Language, Information, and Computation Proceedings of The 16th Pacific Asia Conference
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    • pp.166-176
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    • 2002
  • A homonym could be disambiguated by another words in the context as nouns, predicates used with the homonym. This paper using semantic information (co-occurrence data) obtained from definitions of part of speech (POS) tagged UMRD-S$^1$), In this research, we have analyzed the result of an experiment on a homonym disambiguation system based on statistical model, to which Bayes'theorem is applied, and suggested a model established of the weight of sense rate and the weight of distance to the adjacent words to improve the accuracy. The result of applying the homonym disambiguation system using semantic information to disambiguating homonyms appearing on the dictionary definition sentences showed average accuracy of 98.32% with regard to the most frequent 200 homonyms. We selected 49 (31 substantives and 18 predicates) out of the 200 homonyms that were used in the experiment, and performed an experiment on 50,703 sentences extracted from Sejong Project tagged corpus (i.e. a corpus of morphologically analyzed words) of 3.5 million words that includes one of the 49 homonyms. The result of experimenting by assigning the weight of sense rate(prior probability) and the weight of distance concerning the 5 words at the front/behind the homonym to be disambiguated showed better accuracy than disambiguation systems based on existing statistical models by 2.93%,

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Bag of Visual Words Method based on PLSA and Chi-Square Model for Object Category

  • Zhao, Yongwei;Peng, Tianqiang;Li, Bicheng;Ke, Shengcai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권7호
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    • pp.2633-2648
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    • 2015
  • The problem of visual words' synonymy and ambiguity always exist in the conventional bag of visual words (BoVW) model based object category methods. Besides, the noisy visual words, so-called "visual stop-words" will degrade the semantic resolution of visual dictionary. In view of this, a novel bag of visual words method based on PLSA and chi-square model for object category is proposed. Firstly, Probabilistic Latent Semantic Analysis (PLSA) is used to analyze the semantic co-occurrence probability of visual words, infer the latent semantic topics in images, and get the latent topic distributions induced by the words. Secondly, the KL divergence is adopt to measure the semantic distance between visual words, which can get semantically related homoionym. Then, adaptive soft-assignment strategy is combined to realize the soft mapping between SIFT features and some homoionym. Finally, the chi-square model is introduced to eliminate the "visual stop-words" and reconstruct the visual vocabulary histograms. Moreover, SVM (Support Vector Machine) is applied to accomplish object classification. Experimental results indicated that the synonymy and ambiguity problems of visual words can be overcome effectively. The distinguish ability of visual semantic resolution as well as the object classification performance are substantially boosted compared with the traditional methods.

브레이크 마찰력 증가를 위한 상용차용 전기-기계식 브레이크의 쐐기 설계 (Design of Wedge in the Electro-Mechanical Brakes for Commercial Vehicles to Boost Braking Friction Forces)

  • 이상민;박정훈;남강현;유창희;박상신
    • Tribology and Lubricants
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    • 제34권2호
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    • pp.55-59
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    • 2018
  • This paper proposes a new type of electro-mechanical wedge brake for commercial vehicles. The brake operates on a novel mechanism for self-boosting braking friction forces using eccentric shafts, and involves wedges that are inserted between the rampbridge and traverse; this self-boosting mechanism is explained herein. A dynamic analysis using ADAMS was conducted, and the findings are reported. The constraint and contact conditions are explained to verify the precision of the dynamic analysis. The dynamic analysis shows that in the proposed mechanism, the self-boosting effect occurs as desired. However, it is also noted that the system has a limitation in terms of the production of unlimited braking forces that can jam the roller inside the wedges. After demonstrating the self-boosting effect, dynamic analyses are performed for several values of the wedge angles and friction coefficients between the brake pads and disks. Conventionally, a lower wedge angle has been suggested owing to its provision of a larger clamping force for given friction coefficients. However, it is noted that lower wedge angles can lead to a higher probability of occurrence of undesirable high braking forces, which can jam the roller into the wedge; thus, a larger wedge angle is preferable for avoiding the undesirable jamming phenomena. These analysis results are presented and discussed herein.