• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.29 no.1
• /
• pp.68-76
• /
• 2018

Target prioritization is necessary for a multifunction radar(MFR) to track an important target and manage the resources of the radar platform efficiently. In this paper, we consider an artificial neural network(ANN) model that calculates the priority of the target. Furthermore, we propose a neural network learning algorithm based on the steepest descent method, which is more suitable for target prioritization by combining the conventional gradient descent method. Several simulation results show that the proposed scheme is much more superior to the traditional neural network model from analyzing the training data accuracy and the output priority relevance of the test scenarios.

• The Journal of Korean Association of Computer Education
• /
• v.13 no.6
• /
• pp.9-21
• /
• 2010

Concurrent processes come into conflict with each other when they are competing for the use of the same resources. In the case of competing processes three control problems must be faced: mutual exclusion, deadlock, and starvation. The concurrency is a subject rather difficult to understand. In addition, because concurrent programs included in most of OS texts are described by pseudocode and are not being able to execute directly, almost learners are difficult to understand behaviour of concurrent programs. The purpose of this study is to propose instruction method for mutual exclusion using SDL and MSC base on graphic. In order to verify the effectiveness of the proposed materials, we compare with materials based on pseudocode. The results indicated that the proposed materials is more effective than materials based on pseudocode in teaching-learning for mutual exclusion mechanisms.

• KDI Journal of Economic Policy
• /
• v.18 no.2
• /
• pp.3-61
• /
• 1996

80년대초 이후 기술혁신의 가속으로 중소기업에서도 기술변화에 대한 적응이 경쟁력의 유지를 위한 핵심과제가 되면서, OECD 국가는 중소기업에 대한 과학기술정보(科學技術情報)의 이전(移轉)을 촉진하는 정부지원을 확충하였다. 경제성과의 개선을 위해서는 기술혁신만이 아니라 기술혁신의 성과를 확산시키는 것도 중요하다는 인식으로 중소기업의 경쟁력향상에 기여하는 과학기술정보의 공급확대를 위하여 연구개발사업(硏究開發事業)에 대한 지원을 강화하는 동시에 중소기업에 대한 과학기술정보의 이전을 촉진하기 위하여 과학기술정보의 공급원(供給源)(대학, 시험연구기관 등)과 중소기업을 연결하는 다양한 중개(仲介)(촉매(觸媒))기관(機關)의 설립 운영을 지원하고 있다. 연구개발과 과학기술정보이전에 관한 과학기술공급원과 중소기업간의 인식의 차이를 해소하기 위하여 정보교환(情報交換)과 인적교류(人的交流)를 확대하고 과학기술공급원이 제공하는 지식을 중소기업이 이용하기 쉬운 기술로 변환하기도 한다. 이러한 기능을 중개기관이 효과적으로 수행하기 위해서는 중소기업 사업자와 신뢰관계(信賴關係)를 구축하는 것이 긴요하며, 기술변화를 인지 수용하도록 유도하는 초기단계에서는 중소기업의 네트워크를 통하여 접근하는 것이 효과적이다. 이러한 기술확산과정(技術擴散過程)의 특성으로 인하여 지역혁신체제(地域革新體制)의 구축과 기술혁신정책(技術革新政策)의 지역화(地域化)가 강조되고 있다. 최근에 통상산업부와 과학기술처도 기술혁신정책의 지역화를 시도하고 있다. 연구기반과 산업기반을 고려하여 지역별로 다양한 유형의 산학연 공동연구기반이 구축될 계획이다. 기술혁신정책의 지역화는 시도단계에 불과하며 효율적인 지역혁신체제를 구축하기 위한 여건도 불리하다. 선진국에 비하여 대학과 연구기관의 연구자원(硏究資源)에서도 현격한 차이가 있으나, 네트워크의 혁신성을 좌우하는 지식집약형 중소기업의 비중과 중소기업기술개발의 혁신성에서도 선진국에 비하여 절대열위에 있다. 이러한 불리한 여건을 극복하기 위하여 중소기업의 혁신현장에 밀착된 지역의 전문가집단이 지역경제의 비전과 지역산업의 특수성을 고려하여 지역연구개발사업(地域硏究開發事業)을 전략적으로 기획하고 효율적으로 추진하며, 기획 추진과정에 참여하는 지역대학 지역시험연구기관 지역산업단체 등이 구성하는 지역사회(地域社會)의 협의체(協議體)가 정보공유(情報共有)와 공동학습(共同學習)을 통하여 지역혁신체제의 형성을 주도하고 경쟁과 협력의 조화를 통하여 기술혁신을 가속시키는 지역사회(地域社會)의 규범(規範)과 문화(文化)가 정착되도록 노력하며 중앙정부는 지역연구개발사업에 대한 지원에서 투명하고 합리적인 평가기준을 제시하고 지역산업의 혁신성과에 의하여 지원을 차등화(差等化)하는 경쟁원리를 도입하여 지역사회의 합리적 의사결정을 유도해야 한다.

• The KIPS Transactions:PartD
• /
• v.12D no.4 s.100
• /
• pp.647-656
• /
• 2005

This paper proposes an adaptive resource self-management system that collects system resources, user information, and usage patterns as context information for utilization in self-configuration. This system ill ease the system maintenance burden on users by automation of large part of configuration tasks such as install, reconfiguration and update, and will also decrease cost and errors. Working from the gathered context information, this system allows users to select appropriate components and install them for user's system context. This also offers a more personalized configuration setting by using user's existing application setting and usage pattern. To avoid the overload on central server to transfer and manage related files, we employ Peer-to-Peer method. h prototype was developed to evaluate the system and a comparison study with the conventional methods of manual configuration and MS-IBM systems was conducted to validate the proposed system in terms of functional capacity, install time and etc.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.5
• /
• pp.655-661
• /
• 2020

This study examined community-centered informatization education support measures for empowerment of women with disabilities based on gender perspective.First, the 'Digital Information Gap Survey' conducted by the Ministry of Science and ICT used the 2018 'Digital Information Gap Survey' to find out the current status of the digital information gap between male and female handicapped people. The law on information education support for women with disabilities is presented.Lastly, based on the current status of informatization education support available to women with disabilities, centered on local communities, such as establishing a comprehensive women's disability support center, visiting education considering disability types, developing and supporting customized informatization education considering learning ability, and discovering community resources related to informatization. In this paper, we propose a plan to support informatization education for women with disabilities based on capacity building.

• Journal of Broadcast Engineering
• /
• v.28 no.3
• /
• pp.333-336
• /
• 2023

Recently, the transformer model used in natural language processing is also applied to the image super resolution field, showing good performance. However, these transformer based models have a disadvantage that they are difficult to use in small mobile devices because they are complex and have many learning parameters and require high hardware resources. Therefore, in this paper, we propose a knowledge distillation technique that can effectively reduce the size of a transformer based super resolution model. As a result of the experiment, it was confirmed that by applying the proposed technique to the student model with reduced number of transformer blocks, performance similar to or higher than that of the teacher model could be obtained.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.7
• /
• pp.81-87
• /
• 2018

Problem-based learning (PBL) appears to be a superior and effective strategy to train competent and skilled practitioners and to promote long-term retention of knowledge and skills acquired during the learning experience. This study concerns the implementation of PBL in the online environment and face-to-face PBL. An online environment allows participants to communicate with one another, view presentations or videos, interact with other participants, and engage with resources in work groups. Nowadays, education is accessible everywhere with the use of digital devices. Educational institutions subscribe to GSuite for Education, and Google introduced its Google Classroom as an e-learning platform. This study aims to analyze Google Classroom and to design PBL for Mongolian students taking Korean courses. The main objective of this paper is to identify the usability and evaluation of Google Classroom. The result of this study will be a proposed e-learning platform for Dornod University, Mongolia, which is initially needed in the Natural Science and Business Department.

• Journal of KIISE:Software and Applications
• /
• v.36 no.5
• /
• pp.420-429
• /
• 2009

Patent text is a rich source for discovering technological trends. In order to automate such a discovery process, we attempt to identify phrases corresponding to the problem and its solution method which together form a technology. Problem and solution phrases are identified by a SVM classifier using features based on a combination of a language modeling approach and linguistic clues. Based on the occurrence statistics of the phrases, we identify the time span of each problem and solution and finally generate a trend. Based on our experiment, we show that the proposed semantic phrase identification method is promising with its accuracy being 77% in R-precision. We also show that the unsupervised method for discovering technological trends is meaningful.

• KIISE Transactions on Computing Practices
• /
• v.23 no.5
• /
• pp.310-315
• /
• 2017

In a centralized control structure, the software defined network controller manages all openflow enabled switched in a data plane and controls the telecommunication between all hosts. In addition, the network manager can easily deploy the network function to the application layer with a software defined network controller. For this reason, many methods for network management using a software defined network concept have been proposed. The main policies for network management are related to traffic Quality of Service and resource management. In order to provide Quality of Service and load distribution for network users, we propose an efficient routing method using a naive bayesian algorithm and transmission delay estimation module. In this method, the forwarding path is decided by flow class and estimated transmission delay result in the software defined network controller. With this method, the load on the network node can be distributed to improve overall network performance. The network user also gets better dynamic Quality of Service.

• Journal of IKEEE
• /
• v.14 no.3
• /
• pp.224-231
• /
• 2010

Automatic detection of objects in images has been one of core challenges in the areas such as computer vision and pattern analysis. Especially, with the recent deployment of personal mobile devices such as smart phone, such technology is required to be transported to them. Usually, these smart phone users are equipped with devices such as camera, GPS, and gyroscope and provide various services through user-friendly interface. However, the smart phones fail to give excellent performance due to limited system resources. In this paper, we propose a new scheme to improve object recognition performance based on pre-computation and simple local features. In the pre-processing, we first find several representative parts from similar type objects and classify them. In addition, we extract features from each classified part and train them using regression functions. For a given query image, we first find candidate representative parts and compare them with trained information to recognize objects. Through experiments, we have shown that our proposed scheme can achieve resonable performance.