• International conference on construction engineering and project management
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• 2017.10a
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• pp.121-123
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• 2017

The widespread dissemination of the green building certification system has led to the ongoing development of information management technologies with the aim to effectively utilize construction product information. Among them, a data crawling technology enables to collect the data conveniently and to manage large volumes of construction product information in Korea and overseas. However, without a standardized classification system, it is difficult to efficiently utilize information, and problems such as an additional work for classifying information or information-sharing errors. Therefore, this study suggests to present a necessity for the standardization of the information classification system through expert interviews, and to compare construction product classification systems in Korea and overseas. This study is expected to present a necessity for the effective management of construction product information and the standardization of information-sharing with regard to various construction certifications.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.4
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• pp.592-598
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• 2015

Stress adversely affects the wellbeing of commercial chickens, and comes with an economic cost to the industry that cannot be ignored. In this paper, we first develop an inexpensive and non-invasive, automatic online-monitoring prototype that uses sound data to notify producers of a stressful situation in a commercial poultry facility. The proposed system is structured hierarchically with three binary-classifier support vector machines. First, it selects an optimal acoustic feature subset from the sound emitted by the laying hens. The detection and classification module detects the stress from changes in the sound and classifies it into subsidiary sound types, such as physical stress from changes in temperature, and mental stress from fear. Finally, an experimental evaluation was performed using real sound data from an audio-surveillance system. The accuracy in detecting stress approached 96.2%, and the classification model was validated, confirming that the average classification accuracy was 96.7%, and that its recall and precision measures were satisfactory.

• Journal of the Korean Society for information Management
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• v.19 no.1
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• pp.135-161
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• 2002

This study presents a multilingual integrated ontological approach that enables linking classification systems. thesauri. and terminology databases in science and technology for more effective indexing and information retrieval online. In this integrated system, we designed a thesaurus model with concept as a unit and designated essential data elements for a terminology database on the basis of ISO 12620 standard. The classification system for science and technology adopted in this study provides subject access channels from other existing classification systems through its mapping table. A prototype system was implemented with the field of nuclear energy as an application area.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09b
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• pp.1138-1140
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• 2005

• Archives of design research
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• v.16 no.1
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• pp.5-14
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• 2003

As the digital technology has improved, the numbers of Hangul font users have increased and their individual needs and taste are diversified. Therefore new and various Hangul fonts out of traditional form are developed and used. But under the present font classification system, it is hard to compare and analyze these various fonts. And the present classification system is hard to be the font user's guide for proper use of various Hangul fonts. For the better use of Hangul font, to diversify the font classification system is needed. So we propose the development of these thru classification standards. First, structural classification based on the structural character of Hangul. Second, image classification based on the visual images of each font. And third, usage classification based on the fonts proper usage in various media. For the development of various typographically balanced fonts and for the suitable and effective use of the various font, we must try to build the font classification system based on the diversified classification standards and build Hangul font database based on this classification system. Through these studies, we can expect the development of good quality fonts and the better use of these fonts.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.830-839
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• 2017

Support vector machine (SVM) is introduced as an effective fault diagnosis technique based on dissolved gases analysis (DGA) for oil-immersed transformers with maximum generalization ability; however, the applicability of the SVM is highly affected due to the difficulty of selecting the SVM parameters appropriately. Therefore, a novel approach combing SVM with improved imperialist competitive algorithm (IICA) for fault diagnosis of oil-immersed transformers was proposed in the paper. The improved ICA, which is proved to be an effective optimization approach, is employed to optimize the parameters of SVM. Cross validation and normalizations were applied in the training processes of SVM and the trained SVM model with the optimized parameters was established for fault diagnosis of oil-immersed transformers. Three classification benchmark sets were studied based on particle swarm optimization SVM (PSOSVM) and IICASVM with four multiple classification schemes to select the best scheme for transformer fault diagnosis. The results show that the proposed model can obtain higher diagnosis accuracy than other methods. The comparisons confirm that the proposed model is an effective approach for classification problems.

• Journal of Korean Library and Information Science Society
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• v.31 no.4
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• pp.111-138
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• 2000

The lxnpose of this study is to pmvide the basic data for developing rational classification scheme of intemet resources in the fields of the information & telecommunications technology. The coverage of this study is, kt, to dehe the concept of informtion & telecommunications, and also to investigate the division of information & telecommunications technology through the literature, seumd, to analyze the using library classification schemes for internet resources, and thud, to review classi6cation system of the directory search engines. In this study, I w new

• Journal of Information Management
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• v.27 no.2
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• pp.33-64
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• 1996

The systematic classification of database technologies is being much debated issue currently in the telecommunication and database industry. Such a rapid requirement toward standard classification model will enable many experts to characterize database technologies. The purpose of this study is to obtain a general overview and suggest a draft for the development of standard model associated with classification. This presented model is concentrating on information and database system. This presentation is catalogued by 5 subjects such as : general overview, information distribution, information retrieval systems, database systems, peripheral aspects related to database.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1060-1071
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• 2014

Signals of the Electroencephalogram (EEG) can reflect the electrical background activity of the brain generated by the cerebral cortex nerve cells. This has been the mostly utilized signal, which helps in effective analysis of brain functions by supervised learning methods. In this paper, an approach for improving the accuracy of EEG signal classification is presented to detect epileptic seizures. Moreover, Independent Component Analysis (ICA) is incorporated as a preprocessing step and Short Time Fourier Transform (STFT) is used for denoising the signal adequately. Feature extraction of EEG signals is accomplished on the basis of three parameters namely, Standard Deviation, Correlation Dimension and Lyapunov Exponents. The Artificial Neural Network (ANN) is trained by incorporating Levenberg-Marquardt(LM) training algorithm into the backpropagation algorithm that results in high classification accuracy. Experimental results reveal that the methodology will improve the clinical service of the EEG recording and also provide better decision making in epileptic seizure detection than the existing techniques. The proposed EEG signal classification using feed forward Backpropagation Neural Network performs better than to the EEG signal classification using Adaptive Neuro Fuzzy Inference System (ANFIS) classifier in terms of accuracy, sensitivity, and specificity.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.403-413
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• 2022

Classification and analysis are improved factors for the realtime automation system. In the field of agriculture, the cultivation of different paddy crop depends on the atmosphere and the soil nature. We need to analyze the moisture level in the area to predict the type of paddy that can be cultivated. For this process, Ensemble Modulation Pattern system and Block Probability Neural Network based classification models are used to analyze the moisture and temperature of land area. The dataset consists of the collections of moisture and temperature at various data samples for a land. The Ensemble Modulation Pattern based feature analysis method, the extract of the moisture and temperature in various day patterns are analyzed and framed as the pattern for given dataset. Then from that, an improved neural network architecture based on the block probability analysis are used to classify the data pattern to predict the class of paddy crop according to the features of dataset. From that classification result, the measurement of data represents the type of paddy according to the weather condition and other features. This type of classification model assists where to plant the crop and also prevents the damage to crop due to the excess of water or excess of temperature. The result analysis presents the comparison result of proposed work with the other state-of-art methods of data classification.