• Journal of Korean Academy of Nursing Administration
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• v.12 no.2
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• pp.276-286
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• 2006

Purpose: The purpose of this study was to analyze the effects of self-efficacy and collective-efficacy on job stress in the nursing staff. Method: This study surveyed 160 nurses in three general hospitals in the Seoul and Gyung-gi province for two months starting in September 2004. The questionnaire consisted of 54 questions about job stress, 10 questions about self-efficacy, and 7 questions about collective-efficacy. The answers were on a scale rating of 5. The answer sheets were analyzed with descriptive statistics, the t-test, ANOVA, the tukey test, the Pearson correlation coefficients and stepwise multiple regression using SAS version 8.2. Result: The average job stress rating of the nurses was 3.11. The average self-efficacy and the average collective-efficacy were 3.41 and 3.39, respectively. The age, working department, income level, shift-work and hospital have influence on job stress. Efficacies such that self-efficacy and collective-efficacy have influence on job stress. The much efficacy makes the less job stress. The stepwise multiple regression revealed that the significant predictor of job stress was working department and hospital. Conclusion: This study showed that collective-efficacy as well as self-efficacy reduces job stress, so nursing intervention methods should promote collective-efficacy. The collective-efficacy improvement program should be developed to improve job performance, to improve cohesion of nursing units, and to improve satisfaction on the job. The next research could be to develop collective-efficacy improvement programs for nursing units.

• The Journal of Industrial Distribution & Business
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• v.7 no.2
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• pp.13-20
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• 2016

Purpose - The purpose of this research is to discover whether the presence of the product average rating introduces biases or change the way people perceive information. We posit that review's overall rating has a predisposition effect on consumers' perception towards detailed review information. Research design, data, and methodology - To test these hypotheses, we conducted an empirical study on a real-world setting of online shopping platform. We choose the Amazon website to test our results. The data we use were collected by the Stanford Network Analysis Project1 (McAuley et al., 2013). Results - With a dataset containing reviews of seven product categories from amazon.com., our findings could possess more generalizability as they are produced on the typical and influential online market. Second, as our research provides alternative views of consumers' shopping behavior, it is better to test our hypotheses by data from the same source. Conclusions - Our study reveals the impact of the collective rating presence on consumers' diagnosticity perception and sheds light upon some of the conflictive results in prior studies. Our research generates implications to both theories and business practices, and suggests future directions for the research question.

• KIEAE Journal
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• v.15 no.5
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• pp.89-94
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• 2015

Purpose: Various policies to reduce the energy consumption have been carried out to save Earth environment against global warming and environmental pollution in many countries. Energy consumption of buildings in Korea has reached 24% of total energy consumption, and energy consumption of apartment has been continuously increasing. Therefore, Korea government has executed building energy efficiency rating certification system to control energy consumption of buildings. Method: This study was conducted to evaluate the energy performance of apartment unit plans according to the increasement of front width of unit plans, and tried to present the basic data to design more energy conscious unit plans for apartments. For the study, three shapes of unit plans -the 2Bay, 3Bay and 4bay unit- were selected for imput models. They were simulated using ECO2 software to assess building energy efficiency rating certification in Korea. Result: According to the results, in cases that balcony windows were not installed, the primary energy consumption of the 3Bay and 4Bay units were less than 2Bay unit, respectively, 0.1% and 2,5%. The primary energy consumption of the 3Bay and 4Bay units, in cases that balcony windows were installed, was less than 2Bay unit, respectively, 1.7% and 3.2%.

• IE interfaces
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• v.12 no.4
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• pp.496-505
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• 1999

Quality of Service(QoS) is the collective effect of service performances and has a direct impact on customer satisfaction. Although QoS is subjective, network performance parameters contributing to QoS can be measured physically. Therefore overall customer satisfaction for each test condition of the performance parameters is evaluated by asking respondents to indicate his or her opinion on a five-category rating scale i.e., excellent, good, fair, poor, and unsatisfactory. The opinion data resulting from the test can then be used to measure and analyze QoS from the customers' viewpoints. In this papaer, we consider two methods for analyzing the opinion data: MOS method and Cumulative Probability Curve method. The former evaluates an arithmetic mean of the opinion scores which quantify the surveyed opinions of respondents. The latter uses graphical and analytical models which are based on the distribution of the opinions rather than an arithmetic mean. The advantages, disadvantages, and an alternative of each method are discussed, together with future directions of research.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.241-243
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• 2014

In this study, that by applying the algorithm of collective intelligence in helping to select the teaching methods and learning methods of learner and teacher, develop a content recommendation system, the teacher and the learner promote effective learning, I have intended to And for this reason can be applied to education recommended system to be applied to a movie or shopping mall recently, at the time of selection, it is appropriate in accordance with the state, such as the level of the learner, learning environment, learners the theme of teaching and learning, and to provide a teaching method and learning method, the learner can to find the learning method appropriate for the user, and a more efficient, Professor system that can save time to design the teaching learning process I developed, The utility and accuracy of the learning content recommendation system developed finally, after the data is accumulated in the use of a continuous schedule of the learner and a teacher, would need to be validated through the rating.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.49-67
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• 2015

Recently, emerging the notion of big data and social media has led us to enter data's big bang. Social networking services are widely used by people around the world, and they have become a part of major communication tools for all ages. Over the last decade, as online social networking sites become increasingly popular, companies tend to focus on advanced social media analysis for their marketing strategies. In addition to social media analysis, companies are mainly concerned about propagating of negative opinions on social networking sites such as Facebook and Twitter, as well as e-commerce sites. The effect of online word of mouth (WOM) such as product rating, product review, and product recommendations is very influential, and negative opinions have significant impact on product sales. This trend has increased researchers' attention to a natural language processing, such as a sentiment analysis. A sentiment analysis, also refers to as an opinion mining, is a process of identifying the polarity of subjective information and has been applied to various research and practical fields. However, there are obstacles lies when Korean language (Hangul) is used in a natural language processing because it is an agglutinative language with rich morphology pose problems. Therefore, there is a lack of Korean natural language processing resources such as a sentiment lexicon, and this has resulted in significant limitations for researchers and practitioners who are considering sentiment analysis. Our study builds a Korean sentiment lexicon with collective intelligence, and provides API (Application Programming Interface) service to open and share a sentiment lexicon data with the public (www.openhangul.com). For the pre-processing, we have created a Korean lexicon database with over 517,178 words and classified them into sentiment and non-sentiment words. In order to classify them, we first identified stop words which often quite likely to play a negative role in sentiment analysis and excluded them from our sentiment scoring. In general, sentiment words are nouns, adjectives, verbs, adverbs as they have sentimental expressions such as positive, neutral, and negative. On the other hands, non-sentiment words are interjection, determiner, numeral, postposition, etc. as they generally have no sentimental expressions. To build a reliable sentiment lexicon, we have adopted a concept of collective intelligence as a model for crowdsourcing. In addition, a concept of folksonomy has been implemented in the process of taxonomy to help collective intelligence. In order to make up for an inherent weakness of folksonomy, we have adopted a majority rule by building a voting system. Participants, as voters were offered three voting options to choose from positivity, negativity, and neutrality, and the voting have been conducted on one of the largest social networking sites for college students in Korea. More than 35,000 votes have been made by college students in Korea, and we keep this voting system open by maintaining the project as a perpetual study. Besides, any change in the sentiment score of words can be an important observation because it enables us to keep track of temporal changes in Korean language as a natural language. Lastly, our study offers a RESTful, JSON based API service through a web platform to make easier support for users such as researchers, companies, and developers. Finally, our study makes important contributions to both research and practice. In terms of research, our Korean sentiment lexicon plays an important role as a resource for Korean natural language processing. In terms of practice, practitioners such as managers and marketers can implement sentiment analysis effectively by using Korean sentiment lexicon we built. Moreover, our study sheds new light on the value of folksonomy by combining collective intelligence, and we also expect to give a new direction and a new start to the development of Korean natural language processing.

• KIEAE Journal
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• v.16 no.2
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• pp.11-16
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• 2016

Purpose: International efforts to save Earth's environment against global warming and environmental pollution have been made in many countries. Energy consumption of buildings has been continuously increasing, and it has been over 40% of total energy consumption in the world. Energy consumption of buildings in Korea reaches 24% of total energy consumption. So, Korea government has executed building energy rating systems to control energy consumption of buildings. Method: This study was carried out to evaluate the energy performance of apartment unit plans according to converting balconies into living areas. For the study, six types of input models were made. Two input models(SP1 and SP 2) were the standard units that balcony areas were not converted into living areas, and four ones(EP 1, EP 2, EP 3 and EP 4) were the extended unit plans that balcony areas were turned into living areas. All of them were simulated with ECO2 software to assess building energy efficiency. Result: According to the results, the energy performance of the EP 2 and EP 4 models were 21. 8% higher than SP 1 model and 9.2% higher than SP 2 model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.830-860
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• 2022

[Introduction] Nowadays, many companies are shifting their businesses online due to the growing trend among customers to buy and shop online, as people prefer online purchasing products. [Problem] Users share a vast amount of information about products, making it difficult and challenging for the end-users to make certain decisions. [Motivation] Therefore, we need a mechanism to automatically analyze end-user opinions, thoughts, or feelings in the social media platform about the products that might be useful for the customers to make or change their decisions about buying or purchasing specific products. [Proposed Solution] For this purpose, we proposed an automated SentiDecpective approach, which classifies end-user reviews into negative, positive, and neutral sentiments and identifies deceptive crowd-users rating information in the social media platform to help the user in decision-making. [Methodology] For this purpose, we first collected 11781 end-users comments from the Amazon store and Flipkart web application covering distant products, such as watches, mobile, shoes, clothes, and perfumes. Next, we develop a coding guideline used as a base for the comments annotation process. We then applied the content analysis approach and existing VADER library to annotate the end-user comments in the data set with the identified codes, which results in a labelled data set used as an input to the machine learning classifiers. Finally, we applied the sentiment analysis approach to identify the end-users opinions and overcome the deceptive rating information in the social media platforms by first preprocessing the input data to remove the irrelevant (stop words, special characters, etc.) data from the dataset, employing two standard resampling approaches to balance the data set, i-e, oversampling, and under-sampling, extract different features (TF-IDF and BOW) from the textual data in the data set and then train & test the machine learning algorithms by applying a standard cross-validation approach (KFold and Shuffle Split). [Results/Outcomes] Furthermore, to support our research study, we developed an automated tool that automatically analyzes each customer feedback and displays the collective sentiments of customers about a specific product with the help of a graph, which helps customers to make certain decisions. In a nutshell, our proposed sentiments approach produces good results when identifying the customer sentiments from the online user feedbacks, i-e, obtained an average 94.01% precision, 93.69% recall, and 93.81% F-measure value for classifying positive sentiments.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.248-254
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• 2022

Educational innovations are first created, improved or applied educational, didactic, educative, and managerial systems and their components that significantly improve the results of educational activities. The development of pedagogical technology in the global educational space is conventionally divided into three stages. The role of innovative technologies in Higher School practice is substantiated. Factors of effectiveness of the educational process are highlighted. Technology is defined as a phenomenon and its importance is emphasized, it is indicated that it is a component of human history, a form of expression of intelligence focused on solving important problems of being, a synthesis of the mind and human abilities. The most frequently used technologies in practice are classified. Among the priority educational innovations in higher education institutions, the following are highlighted. Introduction of modular training and a rating system for knowledge control (credit-modular system) into the educational process; distance learning system; computerization of libraries using electronic catalog programs and the creation of a fund of electronic educational and methodological materials; electronic system for managing the activities of an educational institution and the educational process. In the educational process, various innovative pedagogical methods are successfully used, the basis of which is interactivity and maximum proximity to the real professional activity of the future specialist. There are simulation technologies (game and discussion forms of organization); technology "case method" (maximum proximity to reality); video training methodology (maximum proximity to reality); computer modeling; interactive technologies; technologies of collective and group training; situational modeling technologies; technologies for working out discussion issues; project technology; Information Technologies; technologies of differentiated training; text-centric training technology and others.

• Korean Journal of Child Education & Care
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• v.19 no.3
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• pp.57-69
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• 2019

Objective: The purpose of this study is to identify the strengths and problems of the current in-service education system, and suggest ways to improve it in the future by looking at the current status of in-service education to strengthen the expertise of teachers and directors of childcare centers. In particular, I would like to search the current status of in-service education, including on-line special job competency education, which is responsible for one of the pillars of in-service education, and present the problems and measures to improve them. Methods: To that end, the present study conducted an analysis of issues based on the previous research on in-service education of childcare teachers' education, and conducted a literature examination focusing on laws, policies, and foreign cases related to in-service education. Results: In-service education for childcare teachers was categorized into educational process diversification and professionalism, educational method diversification, qualification management, and educational support, which were again organized into 14 core tasks. In addition, as a recent phenomenon that has not been discussed in detail in the preceding study, the phenomenon of increased participation in on-line special job competency education at the site of in-service education was analyzed and the problems were presented. Conclusion/Implications: Based on the results of this study, I proposed development measures such as changing the term 'in-service education' and recognizing the diversity of job competency education, the credit rating banking system for job competency education, the provision of on-line job competency education curriculum (basic courses/enhancing courses) for collective education courses, the expansion of education support for promotion to a higher grade courses and the conversion of the mandatory evaluation system for in-service educational institutions.