• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.68-78
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• 2013

In this paper, we propose an early spectrum sensing(ESS) as an advance preparation for radio-access trial, which enables multi-mode terminals to access the most appropriate radio-access system in a cloud-conceptual base station system where multiple radio access technologies(RATs) coexist. Prior to a random access to one of RATs, a multi-mode terminal conducts a spectrum sensing over entire frequency bands of whole RATs, then select the RAT with the lowest sensing power, that is likely to have the most available spectrum. Thus, an access failure caused by that the selected RAT has no available radio spectrum could be avoidable in advance. In computer simulation, we consider as various RATs as possible. First, circuit and packet systems are taken into consideration. In addition, the packet systems are classified according to the feasibility of carrier aggregation(CA). In case of terminal, three modes are considered with circuit-only, packet-only, and multi-mode. Subsequently, packet traffic is classified into real-time and non-real-time traffic with three different tolerable delay levels. The simulation includes a call process starting with a call generation and ending up with a resource allocation reflecting individual user's QoS requirements and evaluates the proposed scheme in terms of the successful access probability, system access time, system balancing factor and packet loss probability.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.125-135
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• 2009

Owing to its fast computing capability for fusing images, the FIHS(Fast Intensity Hue Saturation) fusion is widely used for fusion purposes. However, the FIHS fusion also distorts color in the same way such as the IHS(Intensity Hue Saturation) fusion technique. In this paper, a FIHS fusion technique(FIHS-BR) which reduces color distortion by using the ratio of each spectral band and an adaptive FIHS fusion(FIHS-SABR) using spatial information and the ratio of each spectral band are proposed. The proposed FIHS-BR fusion reduces color distortion by adding different spatial detail improvement values for each spectral band. The spatial detail improvement values are derived from the ratio of spectral band. And the proposed FIHS-SABR fusion reduces more color distortion by readjusting the spatial detail improvement values for each spectral band according to the ratio of the spectral bands. The spatial detail improvement values are derived adaptively from the characteristics of spatial information of the local image. To evaluate the performance of the proposed FIHS-BR fusion and FIHS-SABR fusion, a computer simulation is performed for IKONOS remote sensing image. Results from the experiments show that the proposed methods have less color distortion for the forest regions which reveal severe color distortion in the traditional FIHS fusion. From the evaluation results of the characteristics of spectral information for fused image, we show that the proposed methods have best results.

• Korean Journal of Comparative Education
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• v.28 no.3
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• pp.291-307
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• 2018

As the value of lifelong learning becomes important, states are making efforts to build a system of lifelong learning. According to this tendency, this paper intends to compare the participation rate of lifelong learning, learning outcomes, learning support infrastructure, support of learning expenses, and recognition of lifelong learning. For the comparative pedagogical approach, Bray and Thomas' cubes such as geographical / regional level, non - geographical demographic statistics, social and educational aspects were utilized. The participation rate of lifelong learning in Korea is 34.4% in 2017, which is lower than the OECD average of 46%. The competency scores of Korean adults were lower than the OECD national averages of the PIAAC survey which measured adult competence, language ability, numeracy, and computer-based problem solving ability. In order to recognize prior learning, EU countries have developed EQFs to evaluate all non-formal and informal learning outcomes, while Korea recognizes qualification as a credit banking credit under the academic credit banking system. International comparisons of lifelong learning can be used as an important tool for diagnosing the actual conditions of lifelong learning in a country and establishing future lifelong learning policies. Therefore, it is necessary to maintain that the comparative pedagogical approach of lifelong learning differs according to the historical context, socioeconomic characteristics, and population dynamics, including the formation process and characteristics of modern countries.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.57-65
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• 2021

A hyper-connected intelligence information society is emerging that creates new value by converging IoT, AI, and Bigdata, which are new technologies of the fourth industrial revolution, in all industrial fields. Everything is connected to the network and data is exploding, and artificial intelligence can learn on its own and even intellectual judgment functions are possible. In particular, the Internet of Things provides a new communication environment that can be connected to anything, anytime, anywhere, enabling super-connections where everything is connected. Artificial intelligence technology is implemented so that computers can execute human perceptions, learning, reasoning, and natural language processing. Artificial intelligence is developing advanced technologies such as machine learning, deep learning, natural language processing, voice recognition, and visual recognition, and includes software, machine learning, and cloud technologies specialized in various applications such as safety, medical, defense, finance, and welfare. Through this, it is utilized in various fields throughout the industry to provide human convenience and new values. However, on the contrary, it is time to respond as intelligent and sophisticated cyber threats are increasing and accompanied by potential adverse functions such as securing the technical safety of new technologies. In this paper, we propose a new data modeling method to enable IoT integrated security control by utilizing artificial intelligence technology as a way to solve these adverse functions.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.93-98
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• 2022

With the development of new digital technologies, research on various learning tools is being actively conducted. These learning tools are also being developed so that they can be applied to various environments by applying the technology of artificial intelligence or using smart functions to which big data technology is applied. These smart learning tools are contributing a lot to increasing educational effectiveness and learning efficiency. Recently, various learning tools have been applied in universities, and solutions for smart learning from smart attendance are introduced to improve student learning efficiency. This study intends to propose a design for a smart learning tool that can increase the efficiency of project progress and increase the scalability of the results when conducting a company's customized project through such a university's smart learning tool. The proposed smart learning tool is expected to have the advantage of being able to easily adapt to the practical business project as the company-customized projects that can improve practical skills are smoothly used as a learning tool. The proposed project-based smart learning tool model is later built as a related LMS and applied to actual project progress to check its utility, and to revise and supplement the proposed smart learning tool model to provide a project-based smart learning function want to strengthen.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.597-603
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• 2023

The paradigm of military operations has evolved from platform-centric warfare to network-centric warfare and further to information-centric warfare, driven by advancements in information technology. In recent years, with the development of cutting-edge technologies such as big data, artificial intelligence, and the Internet of Things (IoT), military operations are transitioning towards knowledge-centric warfare (KCW), based on artificial intelligence. Consequently, the military places significant emphasis on integrating advanced information and communication technologies (ICT) to establish reliable C4I (Command, Control, Communication, Computer, Intelligence) systems. This research emphasizes the need to apply data mining techniques to analyze and evaluate various aspects of C4I systems, including enhancing combat capabilities, optimizing utilization in network-based environments, efficiently distributing information flow, facilitating smooth communication, and effectively implementing knowledge sharing. Data mining serves as a fundamental technology in modern big data analysis, and this study utilizes it to analyze real-world cases and propose practical strategies to maximize the efficiency of military command and control systems. The research outcomes are expected to provide valuable insights into the performance of C4I systems and reinforce knowledge-centric warfare in contemporary military operations.

• Journal of the Korean Chemical Society
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• v.68 no.3
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• pp.160-175
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• 2024

The purpose of this study is to examine the effects of a Chemistry I class based on an artificial intelligence (AI) classification model. To achieve this, the research investigated the development and application of a class utilizing an AI classification model in Chemistry I classes conducted at D High School in Gyeongbuk during the first semester of 2023. After selecting the curriculum content and AI tools, and determining the curriculum-AI integration education model as well as AI hardware and software, we developed detailed activities for the program and applied them in actual classes. Following the implementation of the classes, it was confirmed that students' self-efficacy improved in three aspects: chemistry concept formation, AI value perception, and AI-based maker competency. Specifically, the chemistry classes based on text and image classification models had a positive impact on students' self-efficacy for chemistry concept formation, enhanced students' perception of AI value and interest, and contributed to improving students' AI and physical computing abilities. These results demonstrate the positive impact of the Chemistry I class based on an AI classification model on students, providing evidence of its utility in educational settings.

• Journal of Korean Home Economics Education Association
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• v.20 no.3
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• pp.179-200
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• 2008

This study is aimed at contributing to the future development of Home Economics Education Department by suggesting basic data of TQM(Total Qualify Management) for evaluating TQM of Home Economics Education Departmeut in education colleges. A survey was conducted involving all junior(3rd year) students of Home Economics Education Department in education colleges either by making a visit to 3 different schools or by sending it in the mail to 10 different schools. Responding answer-sheets, 302 copies(88.3%) out of 342 copies in total were returned. Finally, we used 285 copies(83.3%) as data for analysis. The results of this study are as follows: In terms of Professional Qualification of Home Economics Teachers, the students had passion for their Home Economics Education and also had a great pride and mission to be future Home Economics teachers. However, their ability proved to be poor and low in presenting a vision for Home Economics, in conducting extra-curricular activities, and the computer skills. In the case of college students, their satisfaction showed an average point 3.15 on a scale of 5. Those students who entered school voluntarily or those who hoped for re-entrance showed more satisfaction than those who entered school with good academic records or those who do not hope for re-entrance into school. In terms of professors' leadership, Students are perceived to choose 'Transactional Leadership' instead of 'Transformational Leadership'. Students', who have higher satisfaction and hopes for re-entrance, perception level about their professors' leadership style showed higher satisfaction than average. The students empowerment level showed average point 3.52, which is considered relatively high. Students at the college where professors majored in Home Economics Education are employed showed higher empowerment level than students at the college with professors who did not major in Home Economics Education. The result of evaluating general demand for renovating of Home Economics Education Dept. showed that: they perceived the "Teacher Education Course" of Home Economics Education Dept. as in need of cultivating practical skills in secondary school. They also said, "Teaching Method" is in great need of renovation. In the case of teaching method, they preferred laboratory work, and practical training. In earning credits, they emphasized the importance of faithfully completing the "Study of Content". For the Subject Matter Education, they required a training course to be set up in the secondary school. Finally they claimed that the teachers and students need to take the initiative in developing a Curriculum of Home Economics Education Dept. Based on the findings mentioned above, I would like to suggest further research on how to adopt and evaluate TQM in Home Economics Education, and faculty-centered evaluation methods. I also would like to suggest to vitalize quality research through the form of narrative research.

• Bulletin of the Society of Naval Architects of Korea
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• v.27 no.3
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• pp.131-136
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• 1990

여러해 전부터 선박의 생산실적이나 생산성 관련 자료를 기록하고 보완하는 작업을 꾸준히 개선토록 노력해온 결과중 중요한 것 하나는, 선박의 여러 가지 설계 검토과정에서 충분히 활용할 수 있는 함축성 있고 믿을만한 형태의 생산정보를 제공해줄 수 있게 되었다는 것이라고 말 할 수 있겠다. 이러한 자료들은 생산계획상 각 단계(stage)에서의 작업량, 예상재료비와 인건비의 산출등이 포함될 수 있으며, 선박이나 해상구조물의 전반적인 설계방법론(design methodology)을 개선코자 한다면 ''생산지향적 설계(Design for Production)''의 근간이 되는 선박건조전략(build strategy), 구매정책(purchasing policy)과 생산기술(production technology)에 대한 폭넓은 지식이 한데 어우러져야 한다. 최근에는 CIMS의 일부분에서 보는 바와 같은 경영관리, 설계 및 생산지원 시스템의 도입으로 이와 같은 설계 프로세스의 추진을 가능케하고 있다. 이와 병행하여 설계를 지원하기 위한 전산기술, 특히 대화형 화상처리기술(interactive graphics)의 발달은 설계자가 선박의 형상이나 구조 배치를 여러 가지로 변화시켜 가면서 눈으로 즉시 확인할 수 있도록 설계자의 능력을 배가시키는데 크게 기여하고 있다. 여러 가지의 설계안(alternative design arrangement)을 신속히 만들어내고 이를 즉시 검토 평가할 수 있는 능력을 초기설계 단계에서 가질 수 있다면 이는 분명히 큰 장점일 것이며, 더구나 설계초기 단계에 생산관련인자를 설계에서 고려할 수 있다면 이는 더욱 두드러진 발전일 것이다. 생산공법과 관련생산 비용을 정확히 반영한 각 가지의 설계안을 짧은 시간내에 검토하고 생산소요 비용을 산출하여 비교함으로써, 수주계약단계에서 실제적인 생산공법과 신뢰성있는 생산실적자료를 기준으로 하여 총 건조비(total production cost)를 최소로 하는 최적의 설계를 선택할 수 있도록 해 줄 것이다. 이제 이와 같은 새로운 설계도구(design tool)를 제공해 주므로써 초기설계에 각종 생산관련 정보나 지식 및 실적자료가 반영가능토록 발전되었다. 본 논문은 영국의 뉴카슬대학교(Univ. of Newcastle upon Type)에서 위에 언급한 특징들을 반영하여 새로운 선박구조 설계 방법을 개발한 연구결과를 보여주고 있다. 본 선계연구는 5단계로 구분되는데; (1) 컴퓨터 그라픽스를 이용하고 생산정보 데이타베이스와 연결시켜 구조형상(geometry)을 정의하고 구조부재 칫수(scantling) 계산/결정 (2) 블럭 분할(block division) 및 강재 배치(panel arrangement)의 확정을 위해 생산기술 및 건조방식에 대한 정보 제공 (3) 상기 (1) 및 (2)를 활용하여 아래 각 생산 단계에서의 생산작업 분석(work content assessment) a) 생산 준비 단계(Preparation) b) 가공 조립 단계(Fabrication/Assembly) c) 탑재 단계(Erection) (4) 각각의 설계(안)에 대하여 재료비(material cost), 인건비(labour cost) 및 오버헤드 비용(overhead cost)을 산출키 위한 조선소의 생산시설 및 각종 품셈 정보 (5) 총 건조 비용(total production cost)을 산출하여 각각의 설계안을 비교 검토. 본 설계 방식을 산적화물선(Bulk Carrier) 설계에 적용하여 구조배치(structural geometry), 표준화의 정도(levels of standardisation), 구조생산공법(structural topology) 등의 변화에 따른 설계 결과의 민감도를 분석(sensitivity studies)하였다. 전산장비는 설계자의 대화형 접근을 용이하도록 하기 위해 VAX의 화상 처리장치를 이용하여 각 설계안에 대한 구조형상과 작업분석, 건조비 현황 등을 제시할 수 있도록 하였다. 결론적으로 본 연구는 설계초기 단계에서 상세한 건조비 모델(detailed production cost model)을 대화형 화상 처리방법에 접합시켜 이를 이용하여 여러가지 설계안의 도출과 비교검토를 신속히 처리할 수 있도록 함은 물론, 각종 생산 실적정보를 초기설계에 반영하는 최초의 시도라고 믿으며, 생산지향적(Design for Production) 최적설계분야의 발전에 많은 도움이 되기를 기대해 마지 않는다. 참고로 본 시스템의 설계 적용결과를 부록에 요약 소개하며, 상세한 내용은 참고문헌 [4] 또는 [7]을 참조 요망한다.