• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1116-1120
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• 2010

In this paper we present two refined neighbor selection algorithms for recommender systems and also show how the attributes of the items can be used for higher prediction quality. The refined neighbor selection algorithms adopt the transitivity-based neighbor selection method using virtual neighbors and alternate neighbors, respectively. The experimental results show that the recommender systems with the proposed algorithms outperform other systems and they can overcome the large scale dataset problem as well as the first rater problem without deteriorating prediction quality.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.6
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• pp.477-487
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• 2005

As embedded system grows in size and complexity, the importance of the technique for dynamic memory allocation has increased. The objective of this paper is to measure the performance of dynamic memory allocation by varying both hardware and software design parameters for embedded systems. Unlike torrent performance evaluation studies that have presumed the single threaded system with single address spate without OS support, our study adopts realistic environment where the embedded system runs on Linux OS. This paper contains the experimental performance analyses of dynamic memory allocation method by investigating the effects of each software layer and some hardware design parameters. Our quantitative results tan be used to help system designers design high performance, low power embedded systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.803-805
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• 2022

자율주행의 시대가 도래함에 따라, 딥러닝 모델에 대한 적대적 공격 위험이 함께 증가하고 있다. 카메라 기반 자율주행차량이 공격받을 경우 보행자나 표지판 등에 대한 오분류로 인해 심각한 사고로 이어질 수 있어, 자율주행 시스템에서의 적대적 공격에 대한 방어 및 보안 기술 연구가 필수적이다. 이에 본 논문에서는 GTSRB 표지판 데이터를 이용하여 각종 공격 및 방어 기법을 개발하고 제안한다. 시간 및 정확도 측면에서 성능을 비교함으로써, 자율주행에 최적인 모델을 탐구하고 더 나아가 해당 모델들의 완전자율주행을 위한 발전 방향을 제안한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.901-910
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• 2023

In universities, programming language-based thinking and software education for non-majors are being implemented to cultivate creative and convergent talent capable of leading the digital convergence era in line with the Fourth Industrial Revolution. However, learners face difficulties in acquiring the unfamiliar syntax and programming languages. The purpose of this study is to propose a software education model to alleviate the challenges faced by non-major students during the learning process. By introducing algorithm techniques and diagram techniques based on programming language thinking and using the EZMKER kit as an instructional model, this study aims to overcome the lack of learning about programming languages and syntax. Consequently, a structured software education model has been designed and implemented as a top-down system learning model.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.831-835
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• 2023

In contrast to the global public's interest in the Korean Wave, which has persisted since the early 2000s, our efforts and knowledge on business studies that combine art and technology are limited. This study utilizes a case study methodology to select and analyze notable examples of the integration of various technologies into the performing arts for the growth of Korean performing arts and the continued growth of the Korean Wave. In particular, cases of performing arts utilizing Metaverse have been presented recently, but there is a lack of consideration from the stakeholders' perspective. This study aims to suggest implications for the revitalization of performing arts through the integration of various technologies through case study analysis from these perspectives.

• Development and Reproduction
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• v.15 no.1
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• pp.71-76
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• 2011

Due to its role in maintaining the health of scientific societies, research ethics (or integrity) is notably receiving attention by academia, governments and even individuals who are not engaged in scientific researches. In this paper, I will introduce some valuable papers dealt with plagiarism as a representative research misconduct. In general, researcher's results that will soon be published must meet the crucial scientific criteria: originality, accuracy, reproducibility, precision and research ethics. The definition of plagiarism is "appropriation of another person's ideas, processes, results, or words without giving appropriate credit." Compared to fabrication and falcification, plagiarism is often considered as a minor misconduct. With intentionality, however, plagiarism can be corresponding to 'theft of intellectual product'. The context of plagiarism is not restricted to the stage of publication. It can be extended to prior stages of proposing (i.e. preparing the research proposal) and performing (executing the research), and reviewing (writing the review papers). Duplicate publication is regarded as a self-plagiarism in broad interpretation of plagiarism. To avoid dangers of plagiarism, earnest efforts from all members of scientific community are needed. First of all, researchers should keep 'transparency' and 'integrity' in their scientific works. Editorial board members and reviewers should keep fairness and well-deserved qualification. Government and research foundations must be willing to provide sufficient financial and policy support to the scientific societies; Up-graded editorial services, making good use of plagiarism detection tools, and thorough instruction on how to write a honest scientific paper will contribute to building up a healthy basis for scientific communities.

• The Journal of the Acoustical Society of Korea
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• v.38 no.5
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• pp.593-600
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• 2019

The similarity in tones between speakers can lower the performance of speaker verification. To improve the performance of speaker verification systems, we propose a multi-task learning technique using deep neural network to learn speaker information and age information. Multi-task learning can improve generalization performances, because it helps deep neural networks to prevent hidden layers from overfitting into one task. However, we found in experiments that learning of age information does not work well in the process of learning the deep neural network. In order to improve the learning, we propose a method to dynamically change the objective function weights of speaker identification and age estimation in the learning process. Results show the equal error rate based on RSR2015 evaluation data set, 6.91 % for the speaker verification system without using age information, 6.77 % using age information only, and 4.73 % using age information when weight change technique was applied.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.17-33
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• 2023

This study examined inservice elementary teachers' thoughts on the development of educational apps by preservice elementary teachers and implications for TPACK education for preservice elementary teachers. A case study was conducted in which preservice elementary teachers developed a science education app, and the three teachers were surveyed for their thoughts regarding this. The results regarding the characteristics of the developed app by preservice teachers were as follows. First, "inquiry" had the highest value among educational goals intended by the preservice teachers. In addition, the scores for tool-type apps and apps in which interaction between learners and instructors occurs were relatively high. Second, most of the preservice teachers developed apps to meet curriculum goals, but their apps showed low-level characteristics in terms of the constructive and cooperative dimensions. The results of the analysis of the thinking of elementary school teachers regarding the education development apps are as follows. First, elementary school teachers assigned the lowest scores to the effectiveness of the apps, and to this problem, the achievement standard with respect to the curriculum and the evaluation and modification activities fir the apps were proposed. Second, the teachers indicated that it would be appropriate to provide the experience of making apps to directly improve the TPACK of preservice teachers. Third, the respondents thought that preservice teachers should develop block coding literacy to create apps using App Inventor. Fourth, the teachers considered it necessary to emphasize simulated instructions, as well as the experience of collecting and handling data through apps to improve preservice teachers' TPACK app development for educational use.

• Korean Journal of Cognitive Science
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• v.26 no.4
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• pp.435-452
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• 2015

Recent researches on Entity Linking(EL) have attempted to disambiguate entities by using a knowledge base to handle the semantic relatedness and up-to-date information. However, EL for tweets using a knowledge base is still unsatisfactory, mainly because the tweet data are mostly composed of short and noisy contexts and real-time issues. The EL system the present work builds up links ambiguous entities to the corresponding entries in a given knowledge base via exploring the news articles and the user history. Using news articles, the system can overcome the problem of Wikipedia coverage (i.e., not handling real-time issues). In addition, given that users usually post tweets related to their particular interests, the current system referring to the user history robustly and effectively works with a small size of tweet data. In this paper, we propose an approach to building an EL system that links ambiguous entities to the corresponding entries in a given knowledge base through the news articles and the user history. We created a dataset of Korean tweets including ambiguous entities randomly selected from the extracted tweets over a seven-day period and evaluated the system using this dataset. We use accuracy index(number of correct answer given by system/number of data set) The experimental results show that our system achieves a accuracy of 67.7% and outperforms the EL methods that exclusively use a knowledge base.

• Journal of the Korean Applied Science and Technology
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• v.35 no.3
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• pp.940-947
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• 2018

The purpose of this study was to obtain data to support applied motions of bench press and to provide basic data for the efficient execution of the exercise by analyzing muscular activation through measuring electromyogram of pectoralis major and erector spinae when flat bench pressing with feet on the ground versus feet on the bench. For this study, 4 amateur bodybuilders and 2 health trainers were chosen as subjects. Surface electrodes were attached on the measuring muscles; pectoralis major and erector spinae. Motion phases were defined for the flat bench press and each subject, with a 10RM load, performed a set with feet on the ground and another set with feet on the bench. Data was analyzed in SPSS 20.0 and the following results were obtained. The placement of the feet did not affect the muscular activation of the pectoralis major during the flat bench press. however, the muscular activation of the erector spinae was different between the two positions.