• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.1-6
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• 2022

Scene change detection is an important topic because of the wide and growing range of its applications. Streaming services from many providers are increasing their capacity which causes the industry growth. The method for the scene change detection is described here and compared with the State-of-the-Art methods over the Open Video Scene Detection (OVSD) - an open dataset of Creative Commons licensed videos freely available for download and use to evaluate video scene detection algorithms. The proposed method is based on scene analysis using threshold values and smooth scene changes. A comparison of the presented method was conducted in this research. The obtained results demonstrated the high efficiency of the scene cut localization method proposed by authors, because its efficiency measured in terms of precision, recall, accuracy, and F-metrics score exceeds the best previously known results.

• Journal of the Korean Regional Science Association
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• v.13 no.2
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• pp.55-74
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• 1997

This paper investigates the spatial characteristics of networks, which arise as a firm's strategy to enhance its competitiveness to cope with the changing economic environments characterized by technological changes and increasing competitiveness. The theoretical framework in this study proposes that networks emerge as a firm's strategies to promote its competitiveness through the vertical/horizontal disintegration of the production system. Futhermore, regional industries of networks. The study examines the types of cooperation and the spatial boundary of the computer industry networks in Korea. Questionnaire survey was conducted on 1, 128 computer companies which had more than 10 employees, with 126 questionnaires being used for analysis. In addition, newpaper articles were used to supplement the foregoing work on network characteristics. The review of these articles covers the period from Jan. 1994 to June 1996. Major findings of this study are as follows: The spatial range of cooperative networks varies according to the specific characters of cooperation(R & D, production, and seles). Intralocal networks are being developed in Kangnam and Youido area, the computer industry agglomeration clusres of Seoul. There are the regional differnces in the agents and contents of cooperation. In intra-national R & D and production networks, regional differnces in agglomeratins and non-agglomerations are not detercted. Most networks of this type are found between large firms and small firms. In contrast, foregn R & D and production networks, which are operated mostly by large firms, are found in Kangnam, Youido, and CBD. Intra-national and foreign productino networks are also focused in Kangnam, Youido, and CBD. Small firms are playing an active role in making this type of cooperation possible. In the perspective of localization-globalization, Korean computer industry can be analyzed in two respects: industrial and regional. The localization of small firms and the localization-globalization of large firms' networks are being developed in industrial contexts, while the localization-globalization of agglomerations and the localization of non-agglomerations networks are being developed in regional contexts. As networks for the localization-globalization of industry are growing in agglomerations, interfirm networks could be related to trends in the formation or intensification of industrial agglomerations. industrial agglomeration areas function as a facilitator of localization through subcontracts, intraregional network and interregional network. They also facilitate globalization via foregn networks. In non-agglomeratin areas, localization networks, which are connected with agglomeration areas via subcontracting, interregional R & D. or production cooperation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.204-211
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• 2020

In this paper, we propose an optimal deep learning network architecture for main object location detection through weak supervised learning. The proposed network adds convolution blocks for improving the localization accuracy of the main object through weakly-supervised learning. The additional deep learning network consists of five additional blocks that add a composite product layer based on VGG-16. And the proposed network was trained by the method of weakly-supervised learning that does not require real location information for objects. In addition, Grad-CAM to compensate for the weakness of GAP in CAM, which is one of weak supervised learning methods, was used. The proposed network was tested through the CUB-200-2011 data set, we could obtain 50.13% in top-1 localization error. Also, the proposed network shows higher accuracy in detecting the main object than the existing method.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.81-86
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• 2013

In this paper, the parameter identification for localization scheme for the optics-based micro sensor node is conducted. We analyzed short measurement range problem which can be occurred in optical based micro sensor node localization method using a time of flight. And we set up the theory for distance and maximum reflected laser power to overcome the problem by identifying hardware parameters like laser power, effective area of MEMS CCR, sensitivity of photodetector, and so on. Experimental results of measurement of maximum reflected laser power were compared with results of the theory. By using the theory, we can identify hardware parameters of localization scheme to measure particular position of the optics-based micro sensor node.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.1
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• pp.197-203
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• 2010

The problem of location awareness in wireless sensor networks where nodes use GPS (Global Positioning System), remains challenging problem, when considering the required large energy consumption during the localization phase. In this paper we designed hardware for GPS based localization and propose a framework, called ELS, to consume low cost energy. In the ELS framework, sensor nodes are equipped with GPS. Because GPS spends large energy for position awareness, conventional localization algorithms cannot use GPS-device. We try to find a solution for efficient energy expenditure of GPS. Finally, we derive optimal transmission power of GPS data and a scheme of localization through experiment and simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.925-930
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• 2008

Many sensor network applications require that each node's sensor data stream be annotated with its physical location in some coordinate system. Equipping GPS on every sensor node is often expensive and does not work in indoor deployments. Recently, cricket-based localization system is often used for indoor localization system. It is very important to know the exact position of beacons in cricket-based localization system for identifying moving sensor node's position. In this paper, a new method, Mobile Listener Detect Algorithm (MLD) which can automatically calculate the unknown newly installed beacons is proposed. For the verification of the feasibility of the proposed scheme, we have conducted several experiments.

• Annual Conference of KIPS
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• 2016.10a
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• pp.168-171
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• 2016

In recent years, indoor localization in Wi-Fi environment has been researched for its location determining capability. The fingerprint and RF propagation models has been the main approach in determining indoor positioning. With the use of fingerprint, a low-cost, versatile localization system can be achieved without the use of external hardware. However, only a few research have been made on virtual access points (VAPs) among indoor localization models. In this paper, the idea of indoor localization system using fingerprint with the addition of VAP in Wi-Fi environment is discussed. The idea is to virtually add APs in the existing indoor Wi-Fi system, this would mean additional virtually APs in the network. The experiments of the proposed algorithm shows the positive results when 2VAPs are used compared with only APs. A combination of 3APs and 2VAPs had the lowest average error in all 4 scenarios with 3.99 meters.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.156-164
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• 2011

This paper propose a localization system of indoor mobile robots. The localization system includes camera and artificial landmarks for global positioning, and encoders and gyro sensors for local positioning. The Kalman filter is applied to take into account the stochastic errors of all sensors. Also we develop a dead reckoning system to estimate the global position when the robot moves the blind spots where it cannot see artificial landmarks, The learning engine using modular networks is designed to improve the performance of the dead reckoning system. Experimental results are then presented to verify the usefulness of the proposed localization system.

• Annual Conference of KIPS
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• 2010.11a
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• pp.829-832
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• 2010

Wireless Sensor Networks have been proposed for several location-dependent applications. For such systems, the cost and limitations of the hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point to point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we proposed a modified DV-Hop (range-free localization) algorithm which reduces node's location error and cumulated distance error by minimizing localization error. Simulation results have verified the high estimation accuracy with our approach which outperforms the classical DV-Hop.

• Asian Journal of Innovation and Policy
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• v.4 no.2
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• pp.242-262
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• 2015

The relationship between geographical proximity and academics' formal and informal knowledge-transfer activities in the network is analyzed with a mixed research method. With social network analysis as a basis, we have explored the networks between academics and firms in the 16 regions of South Korea. The result shows Seoul and Gyunggi are identified as central nodes, meaning that the academics in other regions tend to collaborate with firms in these regions. An econometric analysis is performed to confirm the localization of knowledge-transfer activities. The intensity of formal channels measured by the number of academic papers is negatively, but significantly associated with the geographical proximity. However, we have not found any significant relationship between the formality of the channels and geographical proximity. Possibly, the regional innovation systems in South Korea are neither big enough nor strong enough to show a localization effect.