• The Journal of Sustainable Design and Educational Environment Research
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• v.16 no.2
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• pp.44-53
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• 2017

Facility management is to maintain and develop the primary structural, functional, aesthetic performance of facility in order to guaranty the users' daily convenience and safety. However it is hard to maintain and serve their intended function and safe environment from the beginning as times go by. As present educational government of city and local area has been performing formally facility check and management as well as maintenance of school facility, it is hard to respond a dangerous situation at the suitable time and safety prevention plans are delayed. In addition, educational environment improving budget have been unreasonably decided not according to the allocating criteria. Therefore, this research developed a same, simple, and quantitative evaluation method of deterioration level of elementary, middle, and high School in Korea and verified usability of the method through the case study.

• Journal of KIISE:Software and Applications
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• v.36 no.10
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• pp.861-873
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• 2009

There are many reasons that fail to get appropriate information in information retrieval. Allomorph is one of the reasons for search failure due to keyword mismatch. This research proposes a method to construct alternative word candidates automatically in order to minimize search failure due to keyword mismatch. Assuming that two words have similar meaning if they have similar co-occurrence words, the proposed method uses the concept of concentration, association word set, cosine similarity between association word sets and a filtering technique using confidence. Performance of the proposed method is evaluated using a manually extracted alternative list. Evaluation results show that the proposed method outperforms the context window overlapping in precision and recall.

• Geophysics and Geophysical Exploration
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• v.23 no.3
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• pp.149-156
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• 2020

The genesis of ore bodies is a very diverse and complex process, and the target depth of mineral exploration increases. These create a need for predictive mineral exploration, which may be facilitated by the advancement of machine learning and geological database. In this study, we confirm that the faults and igneous rocks distributions and magnetic data can be used as input data for potential mapping using deep neural networks. When the input data are constructed with faults, igneous rocks, and magnetic data, we can build a potential mapping model of the metal deposit that has a predictive accuracy greater than 0.9. If detailed geological and geophysical data are obtained, this approach can be applied to the potential mapping on a mine scale. In addition, we confirm that the magnetic data, which provide the distribution of the underground igneous rock, can supplement the limited information from the surface igneous rock distribution. Therefore, rather than simply integrating various data sets, it will be more important to integrate information considering the geological correlation to genesis of minerals.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.9
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• pp.110-117
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• 2016

Applying the contrast enhancement algorithms to luminance values of color images is a widely used approach to enhance the contrast of color images. The results obtained by this approach have reduced saturation compared with that of the original images in spite of contrast enhancement without color degradation. Applying the contrast enhancement algorithm to each channel of color images is another approach for the contrast enhancement of color images. This method produces improved images in terms of contrast and saturation while the hue of original images is changed. In this paper, main cause of color degradation is analyzed and then solving the problem based on the analysis. The channel adaptive contrast enhancement method considering characteristics of each channel is also proposed to deal with color degradation. As a result, the proposed method enhances the contrast and saturation simultaneously without color degradation. Experimental results show that the proposed method outperforms the conventional methods not only on subjective evaluation but on objective criteria.

• Journal of KIISE
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• v.44 no.7
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• pp.674-679
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• 2017

In big-data environments wherein large amounts of text documents are produced daily, titles are very important clues that enable a prompt catching of the key ideas in documents; however, titles are absent for numerous document types such as blog articles and social-media messages. In this paper, a title-generation model for which sequence-to-sequence RNNs with attention and copying mechanisms are employed is proposed. For the proposed model, input sentences are encoded based on bi-directional GRU (gated recurrent unit) networks, and the title words are generated through a decoding of the encoded sentences with keywords that are automatically selected from the input sentences. Regarding the experiments with 93631 training-data documents and 500 test-data documents, the attention-mechanism performances are more effective (ROUGE-1: 0.1935, ROUGE-2: 0.0364, ROUGE-L: 0.1555) than those of the copying mechanism; in addition, the qualitative-evaluation radiative performance of the former is higher.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.269-276
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• 2012

The objective of this short communication is to introduce several evaluation methods to crop model users because the evaluation of crop model performance is an important step to develop or select crop model. In this paper, mean error, mean absolute error, index of agreement, root mean square error, efficiency of model, accuracy factor and bias factor were explained and compared in terms of dimension and observed number. Efficiency of model and index of agreement are dimensionless and independent of number of observation. Relative root mean square, accuracy factor and bias factor are dimensionless and not independent of number of observation. Mean error and mean absolute error are affected by dimension and number of observation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.727-736
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• 2009

Many of the researchers have tried to enhance the satisfaction of both users and owners of social infrastructures by applying the asset management methodology. This study is to develop more efficient asset management framework for bridge management. Based on various literature review, an asset management procedure for bridge management was suggested, and appropriate practices at each step were given. The suggested procedures include the determination of operation and maintenance strategy, level of service, performance measure, valuation of assets, and decision-makings. In addition, this study suggests an applicable decision-making process for the resource distribution based on the management strategy.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.761-766
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• 2023

In this paper, TI was measured to classify the presence or absence of mild left ventricular diastolic dysfunction. Of the total 306 data, 206 were used as training data and 100 were used as test data, and the machine learning models used for classification used SVM and KNN. As a result, it was confirmed that SVM showed relatively higher accuracy than KNN and was more useful in diagnosing the presence of left ventricular diastolic dysfunction. In future research, it is expected that classification performance can be further improved by adding various indicators that evaluate not only TI but also cardiac function and securing more data. Furthermore, it is expected to be used as basic data to predict and classify other diseases and solve the problem of insufficient medical manpower compared to the increasing number of tests.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.3
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• pp.348-356
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• 2007

Statistical and probabilistic method was used in the analysis of data, which is the most effective one in describing the various natures, and the methodology relating the results with the design was developed. Influents and effluents of three treatment plants were analyzed and the focus was made on BOD, COD, SS, IN, TP The fluctuations of influent such as BOD, COD, SS were extremely large and their standard deviations(st.dev) were more than 10 mg/L. but those of TN, TP were small; the st.dev was 6.6 mg/L for TN, 0.6 mg/L for TP, respectively. But, effluent concentration showed consistent pattern regardless of the influent fluctuations, the st.dev was ranged between 0.28 and 4.48 mg/L. Effluent distributional characteristics were as follows; BOD, COD were distributed normally, but SS, TN, and TP, log-normally; unsymmetric and skewed to the right. The coefficient of reliability(COR) based on the results of statistics of data was introduced to evaluate the process performance an4 to reflect the process performance to the process design. The coefficient of reliability relates the design value(the goal) with the standards and it can be used in operating treatment facilities under a certain reliability level and/or in evaluating the reliability of the treatment facilities on operation. Each treated water quality of effluent showed the half of water quality standards in the level of 50% percentile and all treatment plant was achieved 100% probability of water quality standards. It was concluded that the variability of the process performance should be reflected to the design procedure and the standards through the analysis based on the statistics and the probability.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.1
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• pp.36-42
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• 2018

This paper considers the Marine Traffic Risk Assessment for fixed and moving targets, which threaten officers during a voyage. The Collision Risk Assessment Formula was calculated based on a dynamic ship domain considering the length, speed and maneuvering capability of a vessel. In particular, the Navigation Risk Assessment Model that is used to quantitatively index the effect of a ship's size, speed, etc. has been reviewed and improved using a hybrid combination of a vessel's dynamic area and the Collision Risk Assessment Formula. Accordingly, a new type of Marine Traffic Risk Assessment Model has been suggested giving consideration to the Speed Length Ratio, which was not sufficiently reflected in the existing Risk Assessment Model. The larger the Speed Length Ratio (dimensionless speed), the higher the CJ value. That is, the CJ value is presented well by the Speed Length Ratio. When the Speed Length Ratio is large, states ranging from [Caution], [Warning], [Dangerous] or [Very Dangerous] are presented from a greater distance than when the Speed Length Ratio is small. The results of this study, can be used for route and port development, including dangerous route avoidance, optimum route planning, breakwater width, bridge span, etc. as well as the development of costal navigation safety charts. This research is also applicable for the selection of optimum ship routing and the prevention of collisions for smart ships such as autonomous vessels.