• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2006.05a
• /
• pp.573-576
• /
• 2006

Recently, the standard work of the copyright of the Digital content is not completed. And the content providers are developing self's copyright protecting technique. here is some problem such as the confusion existed in the copyright protecting and management system. The reason is that the company using different technique when developing the Digital Contents. Now, there is a standard working leaded by the MPEG. It's called MPEG-21 Multimedia framework and the REL is parted of the Intellectual Property Management and Protection included the framework. And the REL's standard working is completed. The Intellectual Property Management and Protection system contain license server, tool server, metadate server and consume server. In this paper, In order to management and protect the Digital Content copyright, We applying the REL, One of the contents of the MPEG-21 framework to design and implementation the License Server manage the settlement and the consumption information and the Tool Server manage and transport the Tools used from Digital Contents formation to the Digital Contents consumption.

• The KIPS Transactions:PartA
• /
• v.13A no.4 s.101
• /
• pp.275-288
• /
• 2006

Rapid design space exploration is crucial to customizing embedded system design for exploiting the application behavior. As the time-to-market becomes a key concern of the design, the approach based on an application specific instruction-set processor (ASIP) is considered more seriously as one alternative design methodology. In this approach, the instruction set architecture (ISA) for a target processor is frequently modified to best fit the application with regard to code size and speed. Two goals of this paper is to introduce our new retargetable compiler and how it has been used in ASIP-based design space exploration for a popular digital signal processing (DSP) application. Newly developed retargetable compiler provides not only the functionality of previous retargetable compilers but also visualizes the features of the application program and profiles it so that it can help architecture designers and application programmers to insert new application specific instructions into target architecture for performance increase. Given an initial RISC-style ISA for the target processor, we characterized the application code and incrementally updated the ISA with more application specific instructions to give the compiler a better chance to optimize assembly code for the application. We get 32% performance increase and 20% program size reduction using 6 audio codec specific instructions from retargetable compiler. Our experimental results manifest a glimpse of evidence that a higgly retargetable compiler is essential to rapidly prototype a new ASIP for a specific application.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.4
• /
• pp.224-231
• /
• 2019

The current paper was conducted to unravel the influence of affect induction as a background emotion in the process of cognitive task to judge the degree of sequence in groups with or without anxiety symptoms. Four types of affect induction and two sequential task types were used as within-subject variables, and two types of college students groups classified under the Beck Anxiety Inventory (BAI) as a between-subject variable were selected to determine reaction times involving sequential judgment among the lexical relevance information. DmDx5 was used to present a series of stimuli and elicit a response from subjects. Repeated measured ANOVA analyses revealed that reaction times and error rates were significantly larger with anxiety participants compared to the normal group regardless of affect and task types. Within-subject variable effects found that specific affect type (sorrow condition) and number-related task type showed a more rapid response compared to other affect types and magnitude-related task type, respectively. In sum, these findings confirmed the difference in tendency with reaction time and error rates that varied as a function of accompanying affect types as well as anxiety level and task types suggesting the that underlying background affect plays a major role in processing affect-cognitive association tasks.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.9
• /
• pp.362-371
• /
• 2019

The purpose of this study is to recognize kindergarten teachers' experiences of child violence for identifying the site's needs for the implementation of preventive education in early childhood and to provide basic data on child violence. To this end, nine teachers were interviewed in-depth. From the study results, first, child violence-related child behavior, which usually occurs in kindergartens, includes physical assault, aggression, verbal violence, threats and threats, and bullying. Second, teachers usually use direct intervention laws in cases of child violence, but were finding it difficult to intervene properly with many tasks or high teacher-to-child ratios. Teachers recognized the need for lower teacher-to-child ratios and placement of each class burden. Third, teachers were aware of the need for prevention education for child violence targeting infants, and instigated the following appropriate interactions immediately after problem behavior occurred: large group activities, specific multimedia education data and parent education. Fourth, teachers are concerned about the possibility of problem behavior being learned and imitated through education in the implementation of prevention education for children's violence. Therefore, this study proposed the need to develop various teaching methods that could be applied to infant education sites, focusing on the types of child violence-related problem behaviors that occur in kindergartens.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.1
• /
• pp.469-486
• /
• 2021

Vietnam is a country where the largest number of Korean companies have branched out, and calibers who can speak Vietnamese are on great demands. In the multicultural classroom, students of Vietnamese background occupy the first or second largest composition among students with multicultural backgrounds; therefore, if teachers can teach in Vietnamese, the positive effects can be promising. This study presents and evaluates a Vietnamese language class developed and operated for the first time in Korea by a university to raise prospective teachers' global-multicultural competences. Two series of the classes were conducted during two vacations of 2018, and 20 students participated. As a results, the groups showed a significant increase in the global-multicultural competences; About 95 percent of the participants demonstrated improvement in the competences. The participants stated opinions: the classes should expand to offer opportunities for many other students who may want to acquire Vietnamese; the participants had better understandings of the Vietnamese cultures, envisioned their role as a Vietnamese speaker and suggested extended opportunities for contacts with Vietnamese cultures. The study hopes that other universities apply the educational model and the case study and that, as a result, teachers can contribute to building harmonious Korean-Vietnamese relations using Vietnamese.

• Journal of Korea Entertainment Industry Association
• /
• v.13 no.4
• /
• pp.255-262
• /
• 2019

The informatics curriculum which was revised in 2015 presents the growth of creative and convergent talents as a main goal, and what is essential in the growth of creative and convergent talents is Computational Thinking(CT). In this study, in line with the goal of the growth of creative and convergent talents, the subject of IoT technology and liberal arts and natural sciences integration course was combined with the contents of informatics textbook, and the teaching-learning program was developed. In order to verify the effect of the developed teaching-learning program, the experimental research was conducted, and as a result of study, the mean of the experimental group was 10 points higher than that of the control group. Therefore, it could be known that there was an effect in the teaching-learning program suggested in this study. It is expected that the teaching-learning program suggested in this study can induce the learning motive and interest in SW education by directly implementing SW skill to the various fields of a real life through CT education based on Iot as well as a programing language, and improve convergent and scientific thinking through the experience of solving the problems which are blended with many subjects through liberal arts and natural sciences integration course, and designing them creatively.

• The Korean Journal of Applied Statistics
• /
• v.36 no.6
• /
• pp.515-528
• /
• 2023

With the growth of the e-commerce market, consumers increasingly rely on user reviews to make purchasing decisions. Consequently, researchers are actively conducting studies to effectively analyze these reviews. Among the various methods of sentiment analysis, the aspect-based sentiment analysis approach, which examines user reviews from multiple angles rather than solely relying on simple positive or negative sentiments, is gaining widespread attention. Among the various methodologies for aspect-based sentiment analysis, there is an analysis method using a transformer-based model, which is the latest natural language processing technology. In this paper, we conduct an aspect-based sentiment analysis on multilingual user reviews using two real datasets from the latest natural language processing technology model. Specifically, we use restaurant data from the SemEval 2016 public dataset and multilingual user review data from the cosmetic domain. We compare the performance of transformer-based models for aspect-based sentiment analysis and apply various methodologies to improve their performance. Models using multilingual data are expected to be highly useful in that they can analyze multiple languages in one model without building separate models for each language.

• Phonetics and Speech Sciences
• /
• v.15 no.4
• /
• pp.71-80
• /
• 2023

This study primarily aimed to develop an automated stuttering identification and classification method using artificial intelligence technology. In particular, this study aimed to develop a deep learning-based identification model utilizing the convolutional neural networks (CNNs) algorithm for Korean speakers who stutter. To this aim, speech data were collected from 9 adults who stutter and 9 normally-fluent speakers. The data were automatically segmented at the phrasal level using Google Cloud speech-to-text (STT), and labels such as 'fluent', 'blockage', prolongation', and 'repetition' were assigned to them. Mel frequency cepstral coefficients (MFCCs) and the CNN-based classifier were also used for detecting and classifying each type of the stuttered disfluency. However, in the case of prolongation, five results were found and, therefore, excluded from the classifier model. Results showed that the accuracy of the CNN classifier was 0.96, and the F1-score for classification performance was as follows: 'fluent' 1.00, 'blockage' 0.67, and 'repetition' 0.74. Although the effectiveness of the automatic classification identifier was validated using CNNs to detect the stuttered disfluencies, the performance was found to be inadequate especially for the blockage and prolongation types. Consequently, the establishment of a big speech database for collecting data based on the types of stuttered disfluencies was identified as a necessary foundation for improving classification performance.

• Journal of Korean Home Economics Education Association
• /
• v.30 no.3
• /
• pp.19-42
• /
• 2018

The purpose of this study is to analyze the tasks of 'dietary life' in the textbook developed according to the 2015 revised middle school 「Technology·Home economics」 education curriculum based on the multiple intelligence teaching and learning methods. To accomplish this purpose, 12 textbooks of middle school 「Technology·Home economics」 textbooks were titled "Nutrition and Dietary Behavior of Adolescents", "Planning and Choosing Meals", "Choosing Foods and Safe Cooking" except the questions, the tasks that the students can perform are analyzed based on the teaching and learning methods using multiple intelligences. Analysis methods were analyzed by using contents analysis method, focusing on learning activities, and sub-questions of activities were all included in each activity, and the process of preparing activities on a continuous line was grouped into one. Three people analyzed the activities and proceeded to revise and supplement the analysis standard through consultation. The other three researchers confirmed it. As a result of analyzing 12 kinds of textbooks, the number of activity tasks was 25~74 for each kind of textbooks, and the total number of activities was 527. According to the ratio of multiple intelligences, 35% of the tasks were using logical-mathematical intelligence, and 26.8% of linguistic intelligence, 23% of intrapersonal intelligence, 7.2% of interpersonal intelligence, 3.8% of spatial intelligence, bodily-kinesthetic(2.7%) and musical intelligence(1.5%). On the other hand, it was analyzed that there is no activity task using naturalist intelligence. Except to the naturalist intelligence, general intelligence was utilized. This indicates that the home economics curriculum is a convergence of the home economics curriculum in that it is a reorganization by extracting the contents and methods of other curriculum related to dietary life, is interpreted. This study is expected to provide a framework for various teaching and learning methods to activate students' participation classes and to provide an alternative to realize convergence education in home economics curriculum.

• The Korean Society of Law and Medicine
• /
• v.24 no.4
• /
• pp.67-101
• /
• 2023

The utilization of generative AI in the medical field is also being rapidly researched. Access to vast data sets reduces the time and energy spent in selecting information. However, as the effort put into content creation decreases, there is a greater likelihood of associated issues arising. For example, with generative AI, users must discern the accuracy of results themselves, as these AIs learn from data within a set period and generate outcomes. While the answers may appear plausible, their sources are often unclear, making it challenging to determine their veracity. Additionally, the possibility of presenting results from a biased or distorted perspective cannot be discounted at present on ethical grounds. Despite these concerns, the field of generative AI is continually advancing, with an increasing number of users leveraging it in various sectors, including biomedical and life sciences. This raises important legal considerations regarding who bears responsibility and to what extent for any damages caused by these high-performance AI algorithms. A general overview of issues with generative AI includes those discussed above, but another perspective arises from its fundamental nature as a large-scale language model ('LLM') AI. There is a civil law concern regarding "the memorization of training data within artificial neural networks and its subsequent reproduction". Medical data, by nature, often reflects personal characteristics of patients, potentially leading to issues such as the regeneration of personal information. The extensive application of generative AI in scenarios beyond traditional AI brings forth the possibility of legal challenges that cannot be ignored. Upon examining the technical characteristics of generative AI and focusing on legal issues, especially concerning the protection of personal information, it's evident that current laws regarding personal information protection, particularly in the context of health and medical data utilization, are inadequate. These laws provide processes for anonymizing and de-identification, specific personal information but fall short when generative AI is applied as software in medical devices. To address the functionalities of generative AI in clinical software, a reevaluation and adjustment of existing laws for the protection of personal information are imperative.