• Title/Summary/Keyword: Co-occurrence probability

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

  • Kim, Youngchul;An, Ik-Sung;Kang, Min-Gi
    • Journal of Korean Society on Water Environment
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    • v.21 no.2
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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
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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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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Autonomous Ship's Remote Operation Situation Occurrence Probability Estimation Model based on Navigation Areas (운항 해역별 자율운항선박 원격운항 상황 발생 확률 추산 시뮬레이션 모델)

  • Taewoong Hwang;Taemin Hwang;Dain Lee;Hyeinn Park;Ik-Hyun Youn
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.7
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    • pp.910-914
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    • 2023
  • With the technological innovation owing to the 4th industrial revolution, the maritime transportation is rapidly being developed with autonomous ships and systems. Particularly, autonomous ships will partially replace the manned ships and navigation among them remotely upon the degree of autonomy suggested by IMO. Accordingly, the remote operator and related research have increased as well. However, the data on the minimum required manpower for remote operators are lacking such as considering engage required situations and their co-occurrence probability. Therefore, this study proposes a simulation model that calculates the number of remote engage required situations by defining restricted water area and remote engage required situation as close-quarter situations based on accumulated trajectory data of actual ships. The findings are expected to be used as background materials to establish the appropriate manpower distribution of remote operators in remote operation centers.

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

  • Woo, Qui-Hee;Lee, Hae-Yeoun
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.12
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    • pp.889-898
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    • 2013
  • Due to the popularization of high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy to make high-quality counterfeit money. However, the probability of detecting counterfeit money to the general public is extremely low and the detection device is expensive. In this paper, a counterfeit money detection algorithm using a general purpose scanner and computer system is proposed. First, the printing features of color printers are calculated using morphological operations and gray-level co-occurrence matrix. Then, these features are used to train a support vector machine classifier. This trained classifier is applied for identifying either original or counterfeit money. In the experiment, we measured the detection rate between the original and counterfeit money. Also, the printing source was identified. The proposed algorithm was compared with the algorithm using wiener filter to identify color printing source. The accuracy for identifying counterfeit money was 91.92%. The accuracy for identifying the printing source was over 94.5%. The results support that the proposed algorithm performs better than previous researches.

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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    • 2014.05a
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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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    • v.37 no.4
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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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    • v.10 no.2
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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
    • Proceedings of the Korean Society for Language and Information Conference
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    • 2002.02a
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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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    • v.9 no.7
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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.

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

  • Lee, Sang Min;Park, Jeonghun;Nam, Kanghyun;Yoo, Chang-Hee;Park, Sang-Shin
    • Tribology and Lubricants
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    • v.34 no.2
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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.