• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2563-2567
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• 2011

Advances in smart sensors, embedded systems, low-power design, ad-hoc networks and MEMS have allowed the development of low-cost small sensor nodes with computation and wireless communication capabilities that can form distributed wireless sensor networks. Time information and time synchronization are fundamental building blocks in wireless sensor networks since many sensor network applications need time information for object tracking, consistent state updates, duplicate detection and temporal order delivery. Various time synchronization protocols have been proposed for sensor networks because of the characteristics of sensor networks which have limited computing power and resources. However, none of these protocols have been designed with time representation scheme in mind. Global time format such as UTC TOD (Universal Time Coordinated, Time Of Day) is very useful in sensor network applications. In this paper we propose network time protocol extension for global time presentation in wireless sensor networks.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.1019-1029
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• 2020

In this paper, we propose a novel knowledge distillation algorithm to create an compressed deep ensemble network coupled with the combined use of local and global features of face images. In order to transfer the capability of high-level recognition performances of the ensemble deep networks to a single deep network, the probability for class prediction, which is the softmax output of the ensemble network, is used as soft target for training a single deep network. By applying the knowledge distillation algorithm, the local feature informations obtained by training the deep ensemble network using facial subregions of the face image as input are transmitted to a single deep network to create a so-called compressed ensemble DCNN. The experimental results demonstrate that our proposed compressed ensemble deep network can maintain the recognition performance of the complex ensemble deep networks and is superior to the recognition performance of a single deep network. In addition, our proposed method can significantly reduce the storage(memory) space and execution time, compared to the conventional ensemble deep networks developed for face recognition.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1041-1044
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• 1998

In this paper the cellular neural networks with annealing capability is designed. The annealing capability helps the networks escape from the local-minimum points and quickly search for the global-minimum point. A 6$\times$6 CNN chip is designed using a $0.8\mu\textrm{m}$ CMOS technology, and the chip area is 2.89mm$\times$2.89mm. The simulation results for hole filling image processing show that the general CNN has a local-minimum problem, but the annealed CNN finds the global-minimum solutions very efficiently.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1327-1335
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• 2011

This paper demonstrates that there is a unique exponentially stable equilibrium state of a class of impulsive cellular neural network with delays. The analysis exploits M-matrix theory and generalized comparison principle to derive some easily verifiable sufficient conditions for the global exponential stability of the equilibrium state. The results extend and improve earlier publications. An example with its simulation is given for illustration of theoretical results.

• Magazine of the Korean Society of Agricultural Engineers
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• v.42
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• pp.9-16
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• 2000

GPS(Global Positioning System) surveying is an effective method using satellite measurement system and can be applied to construction of digital map of irrigation canal networks. In this study, GPS surveying method for irrigation structures was developed. A selected main canal of an irrigation district were surveyed by GPS. The obtained surveying results were corrected by post-processed DGPS (Differential Global Positioning System) and imported to GIS for the digital map construction.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.157-164
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• 2022

The proposed privacy preserving scheme has identified the drawbacks of existing schemes in Vehicular Networks. This prototype enhances the number of nodes by decreasing the cluster size. This algorithm is integrated with the whale optimization algorithm and Block Chain Technology. A set of results are done through the NS-2 simulator in the direction to check the effectiveness of proposed algorithm. The proposed method shows better results than with the existing techniques in terms of Delay, Drop, Delivery ratio, Overhead, throughout under the denial of attack.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.213-226
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• 2021

Given that most of the link prediction algorithms for signed social networks can only complete sign prediction, a novel algorithm is proposed aiming to achieve both link prediction and sign prediction in signed networks. Based on the structural balance theory, the local link tightness and global link tightness are defined respectively by using the structural information of paths with the step size of 2 and 3 between the two nodes. Then the total similarity of the node pair can be obtained by combining them. Its absolute value measures the possibility of the two nodes to establish a link, and its sign is the sign prediction result of the predicted link. The effectiveness and correctness of the proposed algorithm are verified on six typical datasets. Comparison and analysis are also carried out with the classical prediction algorithms in signed networks such as CN-Predict, ICN-Predict, and PSNBS (prediction in signed networks based on balance and similarity) using the evaluation indexes like area under the curve (AUC), Precision, improved AUC', improved Accuracy', and so on. Results show that the proposed algorithm achieves good performance in both link prediction and sign prediction, and its accuracy is higher than other algorithms. Moreover, it can achieve a good balance between prediction accuracy and computational complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.3
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• pp.258-267
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• 2013

Recently, Proxy Mobile IPv6(PMIPv6) networks have been drawing attention as the mobility management protocol that uses limited wireless resources effectively. And the multicast, which is a core technology of the Internet broadcast system such as mobile IPTV, has been widely discussed mainly based on PMIPv6 network. However, PMIPv6-based multicast cannot support the global mobility directly between different PMIPv6 domains because PMIPv6 is basically designed for local mobility in single PMIPv6 domain. Moreover, PMIPv6-based multicast causes the disconnection of services because it does not solve the packet loss problem during binding and group joining procedure. In this paper, we propose a global mobility scheme that supports the seamless multicast service in PMIPv6 networks. The proposed scheme supports the global mobility due to the addition of extra signalling messages between LMAs. Also, it achieves low latency because it performs fast binding and group joining procedure. We present the simulation results which show that the proposed scheme achieves the global mobility with low latency through the NS-2 simulation.

• Journal of the Korean Geographical Society
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• v.51 no.5
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• pp.667-690
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• 2016

This paper reviews the evolution process of global production network(GPN) discourse, from its origin to the recent theorization, namely GPN 2.0. In so doing, the discursive formation of global production networks is introduced in comparison with a competing discourse global commodity/value chains, with particular attention to conceptual and analytical lacunae in the latter. This article also outlines how the global production network perspective has become a useful discursive and practical tool that allows the examination of the nexus of global economy, transnational corporations, and regional development. Subsequently, a theoretical dearth in the approach is discussed in reference to key critiques, and in this context Yeung and Coe's recent theorization GPN 2.0, which is centered on casual mechanisms and network configurations is reviewed. This paper suggests that the theory adequately addresses the problem of casuality lacking in its precedented conceptual framework, and that it helps exploring the formation and evolution processes of varied production networks(including intrafirm coordination, interfirm control, strategic partnership, and extrafirm bargaining) in connection with competitive dynamics and risky environments. As a result of the theorization, the difference between GPN and the chain approaches has become more apparent, and the idea of extrafirm bargaining is particularly important in the differentiation. Extrafirm bargaining is seen to be a comprehensive networking form inclusive of such GPN 1.0 analytical concepts as value, embeddeness, and power, and research attentive to, and engaging with, the extrafirm networks is expected to help transcending the chain governance approaches' analytical excess of interfirm linkages and industry-centeredness.

• Proceedings of the IEEK Conference
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• 2003.11c
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• pp.135-139
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• 2003

Sensor networks consist of sensor nodes with small-size, low-cost, low-power, and multi-functions to sense, to process and to communicate. Minimizing power consumption of sensors is an important issue in sensor networks due to limited power in sensor networks. Clustering is an efficient way to reduce data flow in sensor networks and to maintain less routing information. In this paper, we propose a multi-hop clustering mechanism using global and local ID to reduce transmission power consumption and an efficient routing method for improved data fusion and transmission.