• Journal of the Korean Society of Earth Science Education
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• v.13 no.3
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• pp.284-296
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• 2020

This study investigates the effect of SSI debate on first-year high school student's opinions about environmental issue, their judgment grounds, and solutions to regional environmental problems. The SSI debate was about white heron habitats near the village where students live. As the main data of the study, environmental perception questionnaires, and students' workbook including open-ended questions were collected before and after class. The environmental perception questionnaire was analyzed by descriptive statistics, and the response of the open-ended questions was analyzed through inductive qualitative research methods. First, the results of this study shows that the SSI debate has a statistically significant impact on students' environmental attitude. Second, a majority of students agreed on the idea that villagers should drive the birds out of town and they did not change their after the discussion class. However, after the discussion class, students' solutions about the issue were changed in a way that more short-term, feasible, concrete, and less time-consuming solutions to the problem. Based on the results of this study, this study implies that SSI issue debate using local problem should be used more often in science classroom so the students recognize local SSI and improve real world problem solving skills.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.31-39
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• 2018

Recently, there has been active studies to provide a user-friendly interface in a virtual reality environment by recognizing user hand gestures based on deep learning. However, most studies use separate sensors to obtain hand information or go through pre-process for efficient learning. It also fails to take into account changes in the external environment, such as changes in lighting or some of its hands being obscured. This paper proposes a hand gesture recognition method based on deep learning that is strong in external environments without the need for pre-process of RGB images obtained from general webcam. In this paper we improve the VGGNet and the GoogLeNet structures and compared the performance of each structure. The VGGNet and the GoogLeNet structures presented in this paper showed a recognition rate of 93.88% and 93.75%, respectively, based on data containing dim, partially obscured, or partially out-of-sight hand images. In terms of memory and speed, the GoogLeNet used about 3 times less memory than the VGGNet, and its processing speed was 10 times better. The results of this paper can be processed in real-time and used as a hand gesture interface in various areas such as games, education, and medical services in a virtual reality environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.183-190
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• 2011

In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as 'gun', 'scream', 'siren', 'crash', 'bomb' via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.13-21
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• 2020

The Android author identification study can be interpreted as a method for revealing the source in a narrow range, but if viewed in a wide range, it can be interpreted as a study to gain insight to identify similar works through known works. The problem found in the Android author identification study is that it is an important code on the Android system, but it is difficult to find the important feature of the author due to the meaningless codes. Due to this, legitimate codes or behaviors were also incorrectly defined as malicious codes. To solve this, we introduced the concept of survival network to solve the problem by removing the features found in various Android apps and surviving unique features defined by authors. We conducted an experiment comparing the proposed framework with a previous study. From the results of experiments on 440 authors' identified apps, we obtained a classification accuracy of up to 92.10%, and showed a difference of up to 3.47% from the previous study. It used a small amount of learning data, but because it used unique features without duplicate features for each author, it was considered that there was a difference from previous studies. In addition, even in comparative experiments with previous studies according to the feature definition method, the same accuracy can be shown with a small number of features, and this can be seen that continuously overlapping meaningless features can be managed through the concept of a survival network.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.33-39
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• 2021

Speech recognition technology is being combined with deep learning and is developing at a rapid pace. In particular, voice recognition services are connected to various devices such as artificial intelligence speakers, vehicle voice recognition, and smartphones, and voice recognition technology is being used in various places, not in specific areas of the industry. In this situation, research to meet high expectations for the technology is also being actively conducted. Among them, in the field of natural language processing (NLP), there is a need for research in the field of removing ambient noise or unnecessary voice signals that have a great influence on the speech recognition recognition rate. Many domestic and foreign companies are already using the latest AI technology for such research. Among them, research using a convolutional neural network algorithm (CNN) is being actively conducted. The purpose of this study is to determine the non-voice section from the user's speech section through the convolutional neural network. It collects the voice files (wav) of 5 speakers to generate learning data, and utilizes the convolutional neural network to determine the speech section and the non-voice section. A classification model for discriminating speech sections was created. Afterwards, an experiment was conducted to detect the non-speech section through the generated model, and as a result, an accuracy of 94% was obtained.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.55-64
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• 2021

Public libraries are a space where residents learn a wide range of knowledge and ideologies, and as they are directly connected to life, various related studies have been conducted. In most previous studies, variables such as population, traffic accessibility, and environment were found to be highly relevant to library use. In this study, it can be said that the difference from previous studies is that the book borrow demand and relevance were analyzed by reflecting the variables of cultural characteristics based on the book borrow history (1,820,407 cases) and member information (297,222 persons). As a result of the analysis, it was analyzed that as the increase in borrows for social science and literature books compared to technical science books, the demand for book borrows increased. In addition, various descriptive statistical analyzes were used to analyze the characteristics of library book borrow demand, and policy implications and limitations of the study were also presented based on the analysis results. and considering that cultural characteristics change depending on the location and time of day, it is believed that related research should be continued in the future.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.13-21
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• 2021

The purpose of this study is to develop the ship valuation model by utilizing the neural network model. The target of the valuation was secondhand VLCC. The variables were set as major factors inducing changes in the value of ship through prior research, and the corresponding data were collected on a monthly basis from January 2000 to August 2020. To determine the stability of subsequent variables, a multi-collinearity test was carried out and finally the research structure was designed by selecting six independent variables and one dependent variable. Based on this structure, a total of nine simulation models were designed using linear regression, neural network regression, and random forest algorithm. In addition, the accuracy of the evaluation results are improved through comparative verification between each model. As a result of the evaluation, it was found that the most accurate when the neural network regression model, which consist of a hidden layer composed of two layers, was simulated through comparison with actual VLCC values. The possible implications of this study first, creative research in terms of applying neural network model to ship valuation; this deviates from the existing formalized evaluation techniques. Second, the objectivity of research results was enhanced from a dynamic perspective by analyzing and predicting the factors of changes in the shipping. market.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.107-133
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• 2021

This study was performed in order to provide suggestions on how to strengthen librarian competency by evaluating and analyzing the competency value of librarians as information professions. First, the study divided the common competency value of librarians as human capital of libraries into skills, knowledge, behavior and attitude, and analyzed each area of competency value for librarians of the A-library. As a result, the average of the 'librarian's behavior and attitude' area was the highest, followed by the 'librarian's skill' area and the 'librarian's knowledge' area. Second, in terms of 'librarian's skill', A-library librarians' competence values were high in the order of 'communication', 'leadership', 'technology' and in the terms of 'librarian's knowledge' ones were high in the order of 'law and policy', 'marketing', 'learning and growth' and 'finance and accounting'. In addition, in areas of 'librarian's behavior and attitude', the factors were high in the order of 'ethics and values', 'interpersonal relationships' and 'customer service'. Third, the analysis of whether the average difference exists depending on the characteristics of A-library librarians on their evaluation of the competency value shows that only the 'working period' factor in the total competency value and the two factors 'age' and 'working period' were statistically significant in the 'librarian's knowledge' area. Forth, as a result of a regression analysis to identify the characteristics of A-library librarians and their impact on competency value, only the 'final education' factor was statistically significant for the competency value of the 'librarian's skill' area. Fifth, in the survey on problems and desirable improvement measures in increasing the competency value of librarians, the proportion of presenting problems and improvement plan in systemic aspects such as the 'librarian qualification system' and 'librarian training system' was high.

• Journal of Korean Library and Information Science Society
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• v.52 no.1
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• pp.155-178
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• 2021

In the era of the 4th industrial revolution, public libraries need a strategy for promoting intelligent library services in order to actively respond to changes in the external environment such as artificial intelligence. Therefore, in this study, based on the concept of artificial intelligence and analysis of domestic and foreign artificial intelligence related trends, policies, and cases, we proposed the future direction of introduction and development of artificial intelligence services in the library. Currently, the library operates a reference information service that automatically provides answers through the introduction of artificial intelligence technologies such as deep learning and natural language processing, and develops a big data-based AI book recommendation and automatic book inspection system to increase business utilization and provide customized services for users. Has been provided. In the field of companies and industries, regardless of domestic and overseas, we are developing and servicing technologies based on autonomous driving using artificial intelligence, personal customization, etc., and providing optimal results by self-learning information using deep learning. It is developed in the form of an equation. Accordingly, in the future, libraries will utilize artificial intelligence to recommend personalized books based on the user's usage records, recommend reading and culture programs, and introduce real-time delivery services through transport methods such as autonomous drones and cars in the case of book delivery service. Service development should be promoted.

• The Mathematical Education
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• v.60 no.3
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• pp.363-386
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• 2021

To learn statistics meaningfully, we must provide an opportunity to experience the process of solving statistical problems with actual data. In particular, exploration questions at the problem setting stage are important for students to successfully guide them from the beginning to the conclusion of the statistical problem solving process. Therefore, in this study, a mixed research method was carried out for the exploration questions of pre-service mathematics teachers during the problem setting stage. As a result, some pre-service mathematics teachers categorized incorrect statistical questions because they did not clearly define the meaning or variables of the questions in the process of categorizing them from possible questions. In addition, questions that cannot be solved statistically were categorized due to misconceptions about statistical knowledge. Second, only 50% of the pre-service mathematics teachers met all 6 conditions suitable for solving statistical problems, while there maining they met only a few conditions. Therefore, the conclusion of this study is as follows. First of all, they should be given the opportunity to experience all the statistical problem solving processes through teacher education because they do not have enough experience in statistical problem solving. Secondly, since the problem setting stage is very important in the statistical problem solving process, a series of subdivided processes are also required in the problem setting stage.