• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3798-3807
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• 2021

Tritium extraction from radioactively contaminated cement mortar samples was performed using heating and liquid scintillation counting methods. Tritiated water molecules (HTO) can be present in contaminated water along with water molecules (H₂O). Water is one of the primary constituents of cement mortar dough. Therefore, if tritium is present in cement mortar, the buildings and structures using this cement mortar would be contaminated by tritium. The radioactivity level of the materials in the environment exposed to tritium contamination should be determined for their disposal in accordance with the criteria of low-level radioactive waste disposal facility. For our experiments, the cement mortar samples were heated at different temperature conditions using a high-temperature combustion furnace, and the extracted tritium was collected into a 0.1 M nitric acid solution, which was then mixed with a liquid scintillator to be analyzed in a liquid scintillation counter (LSC). The tritium extraction rate from the cement mortar sample was calculated to be 90.91% and 98.54% corresponding to 9 h of heating at temperatures of 200 ℃ and 400 ℃, respectively. The tritium extraction rate was close to 100% at 400 ℃, although the bulk of cement mortar sample was contaminated by tritium.

• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.289-303
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• 2004

This experimental study proposes a multi-document summarization method that produces optimal summaries in which users can find answers to their queries. In order to identify the most effective method for this purpose, the performance of the three summarization methods were compared. The investigated methods are sentence clustering, passage extraction through spreading activation, and clustering-passage extraction hybrid methods. The effectiveness of each summarizing method was evaluated by two criteria used to measure the accuracy and the redundancy of a summary. The passage extraction method using the sequential bnb search algorithm proved to be most effective in summarizing multiple documents with regard to summarization precision. This study proposes the passage extraction method as the optimal multi-document summarization method.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.97-117
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• 2020

Product evaluation criteria is an indicator describing attributes or values of products, which enable users or manufacturers measure and understand the products. When companies analyze their products or compare them with competitors, appropriate criteria must be selected for objective evaluation. The criteria should show the features of products that consumers considered when they purchased, used and evaluated the products. However, current evaluation criteria do not reflect different consumers' opinion from product to product. Previous studies tried to used online reviews from e-commerce sites that reflect consumer opinions to extract the features and topics of products and use them as evaluation criteria. However, there is still a limit that they produce irrelevant criteria to products due to extracted or improper words are not refined. To overcome this limitation, this research suggests LDA-k-NN model which extracts possible criteria words from online reviews by using LDA and refines them with k-nearest neighbor. Proposed approach starts with preparation phase, which is constructed with 6 steps. At first, it collects review data from e-commerce websites. Most e-commerce websites classify their selling items by high-level, middle-level, and low-level categories. Review data for preparation phase are gathered from each middle-level category and collapsed later, which is to present single high-level category. Next, nouns, adjectives, adverbs, and verbs are extracted from reviews by getting part of speech information using morpheme analysis module. After preprocessing, words per each topic from review are shown with LDA and only nouns in topic words are chosen as potential words for criteria. Then, words are tagged based on possibility of criteria for each middle-level category. Next, every tagged word is vectorized by pre-trained word embedding model. Finally, k-nearest neighbor case-based approach is used to classify each word with tags. After setting up preparation phase, criteria extraction phase is conducted with low-level categories. This phase starts with crawling reviews in the corresponding low-level category. Same preprocessing as preparation phase is conducted using morpheme analysis module and LDA. Possible criteria words are extracted by getting nouns from the data and vectorized by pre-trained word embedding model. Finally, evaluation criteria are extracted by refining possible criteria words using k-nearest neighbor approach and reference proportion of each word in the words set. To evaluate the performance of the proposed model, an experiment was conducted with review on '11st', one of the biggest e-commerce companies in Korea. Review data were from 'Electronics/Digital' section, one of high-level categories in 11st. For performance evaluation of suggested model, three other models were used for comparing with the suggested model; actual criteria of 11st, a model that extracts nouns by morpheme analysis module and refines them according to word frequency, and a model that extracts nouns from LDA topics and refines them by word frequency. The performance evaluation was set to predict evaluation criteria of 10 low-level categories with the suggested model and 3 models above. Criteria words extracted from each model were combined into a single words set and it was used for survey questionnaires. In the survey, respondents chose every item they consider as appropriate criteria for each category. Each model got its score when chosen words were extracted from that model. The suggested model had higher scores than other models in 8 out of 10 low-level categories. By conducting paired t-tests on scores of each model, we confirmed that the suggested model shows better performance in 26 tests out of 30. In addition, the suggested model was the best model in terms of accuracy. This research proposes evaluation criteria extracting method that combines topic extraction using LDA and refinement with k-nearest neighbor approach. This method overcomes the limits of previous dictionary-based models and frequency-based refinement models. This study can contribute to improve review analysis for deriving business insights in e-commerce market.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.205-210
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• 2004

This paper deals with rule extraction from data using rough set theory. We construct the rule base in a hierarchical granulation structure by applying core as a classification criteria at each level. When more than one core exist, the coverage is used for the selection of an appropriate one among them to increase the classification rate and accuracy. In Addition, a probabilistic approach is suggested so that the partially useful information included in inconsistent data can be contributed to knowledge reduction in order to decrease the effect of the uncertainty or vagueness of data. As a result, the proposed method yields more proper and efficient rule base in compatability and size. The simulation result shows that it gives a good performance in spite of very simple rules and short conditionals.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.179-182
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• 2001

In this paper. a key frame extraction algorithm for browsing and searching the summary of a video is proposed. Toward this end, important frames representing a shot are selected according to the correlations among frames. by using the Fourier descriptor which is useful for the shot boundary detection. To quantitatively evaluate the importance of selected frames. a new measure based on correlation coefficients of frames is proposed. If there are several frames with a same importance. another criteria is introduced to break the tie. by computing the partial moment of subframes including each candidate key frame so that the distortion rate is minimized Since a key frame extraction algorithm can be evaluated subjectively. the performance of the proposed algorithm has been verified by a statistical test. Experiments show that more than 20% improvement has been obtained by the proposed algorithm compared to existing methods.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.669-675
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• 1991

Based on process analysis as well as extensive operation experience, two fuzzy expert control algorithms, for startup and control, are proposed for a supercritical fluid extraction process which has high interacting multivariable structure. In the proposed algorithms, a new simple defuzzification method which only requires four fundamental arithmetic rules is also presented. Through numerical simulations, control performance using the proposed control algorithm is compared with that of a different fuzzy algorithm by an other researcher and that of conventional PID-type controllers which are tuned by well-known optimal criteria. Also, the proposed control algorithm has been tested to the bench scale supercritical fluid extraction process. As a consequence, the proposed fuzzy expert controller has shown fast and robust control performance while the other controllers show sluggish and/or highly oscillatory responses.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.304-309
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• 2003

In this study, natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. Feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.

• Journal of the Korean Society of Safety
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• v.22 no.3 s.81
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• pp.13-21
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• 2007

Personal and static sampling for formaldehyde, wood dust and noise monitoring, in accordance to the equipment running on the day, were carried out throughout wood panel manufacturing process. Even though the exposure level of formaldehyde and wood dust were below than exposure criteria, but the personal protective equipment(PPE) for those should be worn to everyone in the process because of its potential characteristics like carcinogenicity. Also a few local air extraction system above the cutting, grinding sections and organic blending room should be required. Most of the exposures of noise exposure were exceeded permitted exposure criteria, in case of Hopper operators, exposed to maximally 94dB(A) as LAeq 8hr, therefore active controls like PPE, monitoring, isolation etc. are necessary. The main sources of noise were caused on compressed air of the machinery, radio sound and operation noise like running machines, conveying, cutting, sawing, moving vehicles, storing and so on. For the comparison of control criteria in each country, the permitted exposure standards for above hazardous materials and noise in Korea, ACGIH and Australia were discussed. We have recognized that the Korean criteria should be discussed urgently to give the right information to employee and modified, if it is necessary.

• Korean Journal of Remote Sensing
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• v.6 no.2
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• pp.135-151
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• 1990

Solid and hazardous waste disposal site selection by using GIS(Geographic Information System) is the purpose of this study. The criteria of site selection are usually defined in accordance with geological, cultural and social characteristics. Unadequate adaptation of these criteria in a site selection may cause serious problem of water and soil pollution. The environmental information for extraction of these criteria consist of a lot of data : geology, geomorphology, hydrogeology, engineering geology, cultural and social information.... GIS could be easily applied to construct of this environmental information data base, and carry out cartography simulation using overlay mapping technique(polygon overlay). ARC/INFO(GIS system) was used for these studies, and AML(ARC/INFO Macro Language) in this system provided more variable and effective methods for cartography simulation. TM(Thematic Mapper) images were used for the evaluation of land cover/use in the studied area, by using ERDAS image processing system.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.717-738
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• 2017

Purpose: This study focused on procedure and methodology for finding the critical design factors in the early stage of product development process. Methods: Firstly, three key criteria, function, affection and usability were defined as the determining factors on customer satisfaction. Secondly, evaluation matrix in terms of each key criteria was proposed for extraction of the critical design factors. Lastly, method of integrating the importance among three key criteria was suggested using structured equation model. Results: As a results of integrating the importance, design factors such as touch sensitiveness and touch method were rated as low in terms of affection. However, these factors were obtained for high ratings with respect to functionality and usability. Thus, touch-related design factors were more facilitated for enhancing customer satisfaction. Conclusion: It is expected that the process suggested in this research could be a considerably useful to maximize customer satisfaction in the early stage of product development process.