• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.7-16
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• 2002

The Post-clustering algorithms, which cluster the results of Web search engine, have several different requirements from conventional clustering algorithms. In this paper, we propose the new post-clustering algorithm satisfying those requirements as many as possible. The proposed Concept ART is the form of combining the concept vector that have several advantages in document clustering with Fuzzy ART known as real-time clustering algorithms. Moreover we show that it is applicable to general-purpose clustering as well as post-clustering

• Korean Journal of Adult Nursing
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• v.19 no.2
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• pp.207-216
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• 2007

Purpose: The purpose of this study was to ascertain the effects of preoperative information on postoperative state anxiety, plasma cortisol, and pain for patients under total knee arthroplasty, and to provide generic data with nursing intervention for total knee arthroplasty. Methods: Data were collected from 34 patients who had total knee arthroplasty from January 3, 2003 to January 15, 2004. An experiment group of 17 patients was provided with pre-operative information prepared by the researchers; a control group of another 17 patients was provided with general information. Data were analyzed through Chi-squared test, t-test, paired t-test and ANCOVA using SPSS WIN 11.0. Results: There was no significant differences between the experiment group and the control group in post operative state anxiety(p=.612). However, there was statistically a significant difference between the above two groups in post operative plasma cortisol(p=.012). There was a statistically significant difference between the above two groups in post operative pain(p=.041). Conclusion: According to the results of the study, the authors concluded that the preoperative information for patients under total knee arthroplasty had the effect on the decrease of postoperative plasma cortisol and pain.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.424-427
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• 2022

본 연구는 도메인 특성이 강한 HR 평가문장을 BERT PLM 모델을통해 4 가지 class 로 구분하는 문제를 다룬다. 다양한 PLM 모델 적용과 training data 수에 따른 모델 성능 비교를 통해 특정 도메인에 언어모델을 적용하기 위해서 필요한 기준을 확인하였다. 또한 Unlabeled 된 HR 분야 corpus 를 활용하여 BERT 모델을 post-training 한 HR-BERT 가 PLM 분석모델 정확도 향상에 미치는 결과를 탐구한다. 위와 같은 연구를 통해 HR 이 가지고 있는 가장 큰 text data 에 대한 활용 기반을 마련하고, 특수한 도메인 분야에 PLM 을 적용하기 위한 가이드를 제시하고자 한다

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.57-67
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• 2024

This research investigates training methods for large language models to accurately identify sentiments and comprehend information about increasing and decreasing fluctuations in the financial domain. The main goal is to identify suitable datasets that enable these models to effectively understand expressions related to financial increases and decreases. For this purpose, we selected sentences from Wall Street Journal that included relevant financial terms and sentences generated by GPT-3.5-turbo-1106 for post-training. We assessed the impact of these datasets on language model performance using Financial PhraseBank, a benchmark dataset for financial sentiment analysis. Our findings demonstrate that post-training FinBERT, a model specialized in finance, outperformed the similarly post-trained BERT, a general domain model. Moreover, post-training with actual financial news proved to be more effective than using generated sentences, though in scenarios requiring higher generalization, models trained on generated sentences performed better. This suggests that aligning the model's domain with the domain of the area intended for improvement and choosing the right dataset are crucial for enhancing a language model's understanding and sentiment prediction accuracy. These results offer a methodology for optimizing language model performance in financial sentiment analysis tasks and suggest future research directions for more nuanced language understanding and sentiment analysis in finance. This research provides valuable insights not only for the financial sector but also for language model training across various domains.

• Informatization Policy
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• v.23 no.2
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• pp.73-97
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• 2016

Social changes due to ICT like Big Data, IoT, Cloud and Mobile is progressing rapidly. Now, we get out of the old-fashioned frame was measured at the level of the information society through the introduction of PC, Internet speed and Internet subscribers etc and there is a need for a new type of diagnostic information society framework. This study is the study for the framework established to diagnose and measure post-information society. The framework and indicators were chosen in accordance with the technological society coevolution theory and information society-related indicators presented from authoritative international organizations. Empirical results utilizing the indicators and framework developed in this study were as follows: First, the three sectors, six clusters (items), 25 nodes (indicators) that make up the information society showed that all strongly connected. Second, it was diagnosed as information society development (50.34%), technology-based expansion (25.03%) and ICT effect (24.63%) through a network analysis (ANP) for the measurement of importance of the information society. Third, the result of calculating the relative importance of the cluster and nodes showed us (1)social development potential (26.04%), (2)competitiveness (15.9%), (3)ICT literacy (15.5%) (4) (social)capital (24.3 %), (5)ICT acceptance(9.54%), (6)quality of life(8.7%). Consequently, We should take into account the effect of the economy and quality of life beyond ICT infrastructure-centric when we measure the post-information society. By applying the weighting we should performs a comparison between countries and we should diagnose the level of Korea and provide policy implications for the preparation of post-information society.

• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.279-311
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• 2020

People collectively understand and often use information and knowledge as terms in a variety of contexts without concern nor discussion of their many competing conceptual and theoretical definitions. The concepts of information and knowledge are intrinsically linked and suffer some of the same problems when scholars try to define them, especially when truth is a prerequisite. This theory paper presents a simple thought experiment that relates the reliabilist and truth-tracking analyses of knowledge with the physical and cognitive paradigms of information, respectively. The results of the thought experiment are discussed within the context of the Post-Truth era, with implications and applications for information literacy.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.120-136
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• 2002

The CRM is the process of integrated customer management to increase the profitability of firm as a maximizing the consumer's value and supplying the high quality product or service. The Post Information Service Headquarter was recognizing the importance of CRM and constructed the customer relationship management system that based on CRM, steadily has made an endeavor for operating to improve the job operation such as posting, banking and insurance. This research analysed the impact of service quality on the customer satisfaction in the Korea Post Office. First of all, we review the existing literature on measurement of service quality and management. As a result of this review and survey of the employer in post office, nineteen factors emerged as important to the service management of The Korea Post Office; Postal Services, Banking Services, Insurance Services. The regression analysis was utilized for analyzing the influence of service quality factors upon the customer satisfaction. Results show that service quality factors have a statistically significant impact on the customer satisfaction of the Korea Post Office.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.197-207
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• 2022

The Naval Combat System operates in multiple software components for efficient functional processing. Data transmission and reception between components is performed in real time using DDS(Data Distribution Service). Reliable Post-Analysis requires the collection of all DDS messages. However, Software workload and development costs increase because common functions for all messages must be developed directly. In the paper, We propose an improved Post-Analysis based on the Feature Model and a new development system using it. Functions for the modified message were applied as variable domains of the Feature Model. When Build Center updates Post-Analysis, it automatically processes all software tasks associated with Post-Analysis. The proposed development system simplified the overall work procedure, and work time was significantly reduced compared to the existing development system.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.1598-1601
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• 2008

We describe the fabrication of transparent conducting single-walled carbon nanotubes (SWCNTs) film on flexible substrate following the conventional spin coating method. The fabricated film was post treated with diluted acid solution and its electrical and optical characterizations were performed. The electrical conductivity of SWCNTs film was enhanced and the film was found to be attached strongly with substrate after the post treatment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1587-1605
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• 2015

Mobile cloud computing (MCC) combines mobile Internet and cloud computing to improve the performance of applications. In MCC, the data processing and storage for mobile devices (MDs) is provided on the remote cloud. However, MCC faces the problem of energy efficiency caused by randomly varying channels. In this paper, by introducing the Lyapunov optimization method, we propose a combined service subscription and delivery (CSSD) algorithm that can guide the users to subscribe to services reasonably. This algorithm can also determine whether to deliver the data and to whom data is sent in the current time unit based on the queue backlog and the channel state. Numerical results validate the correctness and effectiveness of our proposed CSSD algorithm.