• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.12
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• pp.1486-1491
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• 1999

This paper presents a method of recognizing high impedance fault(HIF) of electrical power systems and classifying fault patterns based on chaos attractors. Two dimensional chaos attractors are reconstructed from neutral point current waveforms. Reliable features for HIF pattern classification are obtained from the chaos attractors. Radial basis function network, trained with two types of HIF data generated by the electromagnetic transient program and measured form actual faults. The RBFN successfully classifies normal and the three types of fault patterns according to the features generated from the chaos attractors.

• Asia pacific journal of information systems
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• v.12 no.2
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• pp.197-216
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• 2002

Cooperativeness within an organization can be conceptualized as the degree of members' willingness to work with others. The simulation study investigates the relationships of cooperativeness with team performance at different levels of information redundancy by using a multi-agents model called Team-Soar. The model consists of a group of four individual Al agents situated in a network, which models a naval command and control team consisting of four members. The study used a $9{\times}3$ design in which agent cooperativeness was manipulated at nine levels by gradually replacing selfish team members with increasing numbers of neutral and cooperative members, while information redundancy was controlled at three different levels(i.e., low, medium, and high). Results of the Team-Soar simulation show that cooperation has positive impacts on team performance. Further, the results reveal that the impact of agent cooperativeness on team performance depends on the amount of information needed to be processed during the decision making process.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.309-312
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• 2001

A primitive gas classification system which can classify limited species of gas was designed and simulated. The 'electronic nose' consists of an array of 4 metal oxide gas sensors with different selectivity patterns, signal collecting unit and a signal pattern recognition and decision Part in PLD(programmable logic device) chip. Sensor array consists of four commercial, tin oxide based, semiconductor type gas sensors. BP(back propagation) neutral networks with MLP(Multilayer Perceptron) structure was designed and implemented on CPLD of fifty thousand gate level chip by VHDL language for processing the input signals from 4 gas sensors and qualification of gases in air. The network contained four input units, one hidden layer with 4 neurons and output with 4 regular neurons. The 'electronic nose' system was successfully classified 4 kinds of industrial gases in computer simulation.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1977-1983
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• 2009

This paper described partial discharge(PD) patterns depending on types of insulation defects in CNCO-W cable(Concentric Neutral Closs-linked Polyethylene Insulated Polyolefin-Water Proof Sheathed Power Cable). The PD measurement system consists of a coupling network, a detection impedance, and a low noise amplifier. A 16 bit, 250 MS/s data acquisition system was used to analyze PD patterns. To simulate insulation defects in a power cable, a needle with the curvature radius of $10{\mu}m$ was inserted into the insulation part. We measured phase ($\Phi$), magnitude (q), and counts (n) of PD pulse for the defects, and classified PD patterns using the PRPD (phase Resolved Partial Discharge) method. From the analysis of acquired PD signals, we could find that a unique PD pattern is formed according to the types of defect.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.131-138
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• 2013

In this paper, I propose and evaluate the method that classifies emotional type of characters with their emotional words. Emotional types are classified as three types such as positive, negative and neutral. They are selected by classification of emotional words that characters speak. I propose the method to extract emotional words based on WordNet, and to represent as emotional vector. WordNet is thesaurus of network structure connected by hypernym, hyponym, synonym, antonym, and so on. Emotion word is extracted by calculating its emotional distance to each emotional category. The number of emotional category is 30. Therefore, emotional vector has 30 levels. When all emotional vectors of some character are accumulated, her/his emotion of a movie can be represented as a emotional vector. Also, thirty emotional categories can be classified as three elements of positive, negative, and neutral. As a result, emotion of some character can be represented by values of three elements. The proposed method was evaluated for 12 characters of four movies. Result of evaluation showed the accuracy of 75%.

• CELLMED
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• v.4 no.1
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• pp.6.1-6.12
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• 2014

Anthrax is the deadly disease for human being caused by Bacillus anthracis. Instantaneous research work on the mode of infection of the organism revealed that different proteases are involved in different steps of pathogenesis. Present study reports the in silico characterization and the detection of pathogenic proteases involved in anthrax infection through protein-protein interaction. A total of 13 acid, 9 neutral, and 1 alkaline protease of Bacillus anthracis were selected for analysing the physicochemical parameter, the protein superfamily and family search, multiple sequence alignment, phylogenetic tree construction, protein-protein interactions and motif finding. Among the 13 acid proteases, 10 were found as extracellular enzymes that interact with immune inhibitor A (InhA) and help the organism to cross the blood brain barrier during the process of infection. Multiple sequence alignment of above acid proteases revealed the position 368, 489, and 498-contained 100% conserved amino acids which could be used to deactivate the protease. Among the groups analyzed, only acid protease were found to interact with InhA, which indicated that metalloproteases of acid protease group have the capability to develop pathogenesis during B. anthracis infection. Deactivation of conserved amino acid position of germination protease can stop the sporulation and germination of B anthracis cell. The detailed interaction study of neutral and alkaline proteases could also be helpful to design the interaction network for the better understanding of anthrax disease.

• Journal of Environmental Health Sciences
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• v.43 no.5
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• pp.393-400
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• 2017

This study was investigated on pH, heavy metals, oils and solvents in 34 surface soil samples and the samples are collected at two times for 17 farmland sites around 7 industrial areas in Northern Gyeonggi Province. As a result of pH for soil contamination monitoring network, the range of pH showed 4.4~8.4 and average was 6.3. The range of pH for Agricultural land around industrial area was 6.7~7.5 and average indicated 7.1 that mostly showed neutral condition in this area. he average concentrations of Cu, Pb, Ni, As and $Cr^{6+}$ are lower than Korea soil contamination worrisome levels at region 1 and the mean levels of farmland from the soil quality monitoring network. The average concentrations of Zn, Cd and Hg didn't exceed the soil contamination worrisome levels at region 1 but slightly higher than the mean levels of farmland from the soil quality monitoring network. The heavy metal levels of all samples are within Korea soil contamination worrisome levels at region 1. The results showed that the detected heavy metal concentrations ranged from N.D. to ~32.7% of Korea soil contamination worrisome levels at region 1. BTEX, TPH, TCE and PCE were not detected in all samples and thus the farmland around the industrial areas were free from oils and solvents contamination.

• Journal of the Korean Chemical Society
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• v.55 no.2
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• pp.199-203
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• 2011

The title one-dimensional hydrogen-bonded coordination compound $[Cu^{II}(C_{13}H_{17}N_3OBr)(C_8H_5O_4)]{\cdot}2H_2O.CH_3OH$ has been synthesized and characterized by single crystal X-ray diffraction study. The monomeric unit contains a square-planar $Cu^{II}$ centre. The four coordination sites are occupied by a tridentate anionic Schiff base ligand (4-bromo-2-[(2-piperazin-1-yl-ethylimino)-methyl]-phenol) which furnishes an $N_2O$-donor set, with the fourth position being occupied by the oxygen atom of an adjacent terephthalate unit. Two adjacent neutral molecules are linked through intermolecular N-H---O and O-H---N hydrogen bonds and generate a dimeric pair. Each dimeric pair is connected with each other via discrete water and methanol molecules by hydrogen bonding to form a one-dimensional supramolecular network.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.421-431
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• 2018

The purpose of this study is to analyze the trends of 'traditional' terminology in Korea. We focus on an empirical investigation of how media reports are conveying 'tradition' terminology in our society by applying text mining and social network analysis techniques. The analysis covered 2,481,143 news articles related to 'tradition' terminology that appeared in the media since the 1920's. In this research, frequency analysis, association analysis and social network analysis were used on articles related to 'tradition' terminology from 1920 to 2017 by decade. By applying these data science techniques, we can grasp the meaning of social culture phenomenon related 'tradition' with objective and value-neutral position and understand the social symbolism which contains the tradition of the times.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.97-106
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• 2023

Sentiment analysis using social network platforms such as Twitter has achieved tremendous results. Twitter is an online social networking site that contains a rich amount of data. The platform is known as an information channel corresponding to different sites and categories. Tweets are most often publicly accessible with very few limitations and security options available. Twitter also has powerful tools to enhance the utility of Twitter and a powerful search system to make publicly accessible the recently posted tweets by keyword. As popular social media, Twitter has the potential for interconnectivity of information, reviews, updates, and all of which is important to engage the targeted population. In this work, numerous methods that perform a classification of tweet sentiment in Twitter is discussed. There has been a lot of work in the field of sentiment analysis of Twitter data. This study provides a comprehensive analysis of the most standard and widely applicable techniques for opinion mining that are based on machine learning and lexicon-based along with their metrics. The proposed work is helpful to analyze the information in the tweets where opinions are highly unstructured, heterogeneous, and polarized positive, negative or neutral. In order to validate the performance of the proposed framework, an extensive series of experiments has been performed on the real world twitter dataset that alter to show the effectiveness of the proposed framework. This research effort also highlighted the recent challenges in the field of sentiment analysis along with the future scope of the proposed work.