• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.213-219
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• 2023

In recent years, popularity of deep learning (DL) is increased due to its ability to extract features from Hyperspectral images. A lack of discrimination power in the features produced by traditional machine learning algorithms has resulted in poor classification results. It's also a study topic to find out how to get excellent classification results with limited samples without getting overfitting issues in hyperspectral images (HSIs). These issues can be addressed by utilising a new learning network structure developed in this study.EfficientNet-B4-Based Convolutional network (EN-B4), which is why it is critical to maintain a constant ratio between the dimensions of network resolution, width, and depth in order to achieve a balance. The weight of the proposed model is optimized by Search and Rescue Operations (SRO), which is inspired by the explorations carried out by humans during search and rescue processes. Tests were conducted on two datasets to verify the efficacy of EN-B4, with Indian Pines (IP) and the University of Pavia (UP) dataset. Experiments show that EN-B4 outperforms other state-of-the-art approaches in terms of classification accuracy.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.6
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• pp.179-188
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• 2014

Due to the tremendous amount and its rapid increase of network traffic, the performance of network equipments are becoming an important issue. Network filtering is one of primary functions affecting the performance of the network equipment such as a firewall or a load balancer to process the packet. In this paper, we propose a cache based tri method to improve the performance of the existing tri method of searching for network filtering. When several packets are exchanged at a time between a server and a client, the tri method repeats the same search procedure for network filtering. However, the proposed method can avoid unnecessary repetition of search procedure by exploiting cache so that the performance of network filtering can be improved. We performed network filtering experiments for the existing method and the proposed method. Experimental results showed that the proposed method could process more packets up to 790,000 per second than the existing method. When the size of cache list is 11, the proposed method showed the most outstanding performance improvement (18.08%) with respect to memory usage increase (7.75%).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.1
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• pp.33-41
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• 2011

This paper considers a topological optimization of a network design with mean packet delay and node connectivity constraints. The objective is to find the topological layout of links, at minimal cost. This Problem is known to be NP-hard. To efficiently solve the problem, a scatter search algorithm is proposed. An illustrative example is used to explain and test the proposal approach. Experimental results show evidence that the proposal approach performs more efficiently for finding a good solution or near optimal solution in comparison with a genetic approach.

• ETRI Journal
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• v.34 no.4
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• pp.591-601
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• 2012

Unstructured peer-to-peer (p2p) networks usually employ flooding search algorithms to locate resources. However, these algorithms often require a large storage overhead or generate massive network traffic. To address this issue, previous researchers explored the possibility of building efficient p2p networks by clustering peers into communities based on their social relationships, creating social-like p2p networks. This study proposes a social relationship p2p network that uses a measure based on Hebbian theory to create a social relation weight. The contribution of the study is twofold. First, using the social relation weight, the query peer stores and searches for the appropriate response peers in social-like p2p networks. Second, this study designs a novel knowledge index mechanism that dynamically adapts social relationship p2p networks. The results show that the proposed social relationship p2p network improves search performance significantly, compared with existing approaches.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.1
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• pp.63-68
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• 2015

Pattern layout design is very important to the automation of apparel industry. Until now, the genetic algorithm and Tabu search method have been applied to layout design automation. With the genetic algorithm and Tabu search method, the obtained values are not always consistent depending on the initial conditions, number of iterations, and scheduling. In addition, the selection of various parameters for these methods is not easy. This paper presents a hybrid search method that uses a neural network and simulated annealing to solve these problems. The layout of pattern elements was optimized to verify the potential application of the suggested method to apparel pattern layout design.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.1
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• pp.101-107
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• 2008

This paper considers a topological optimization of a computer network design with a reliability constraint. The objective is to find the topological layout of links, at minimal cost, under the constraint that the network reliability is more than a given reliability. To efficiently solve the problem, a scatter search approach is proposed. Two illustrative examples are used to explain and test the proposed approach. Experimental results show evidence that the proposed approach performs more efficiently for finding a good solution or near optimal solution in comparison with a genetic algorithm approach.

• Journal of The Korean Astronomical Society
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• v.38 no.2
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• pp.81-84
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• 2005

We are undertaking an extra-solar planet search around G-type giant stars by means of Doppler technique using an iodine absorption cell installed to the high dispersion echelle spectrograph for the 188 cm reflector at Okayama Astrophysical Observatory (Okayama Planet Search Program, OPSP). Having detected the first planet candidate (Sato et al. 2003)the search has been proved very promising. Taking advantage of this success, we are trying to develop OPSP to an international collaborative work. We here report the current status of our efforts for establishing such collaborations, namely, those with Chinese and Korean astronomers. We also propose to establish an East-Asian network to search for extra-solar planets around G-type giant stars with the transit detecting technique as well as the Doppler technique, asking other persons/groups to join us to enjoy the planet search.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.109-112
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• 2021

The article considers the state of legislation that regulates the use of public methods of obtaining information by authorized state bodies. The correlation of public investigative (search) actions with operative-search measures as concepts denoting the application of public methods of obtaining information has been studied. In addition, it argues the need for more detailed delineation and legislative regulation of public investigative (search) actions and operational and investigative measures at the legislative and departmental levels. The purpose of the article is to analyze certain provisions of the Law of Ukraine "On operational and investigative activities" to identify inconsistencies in the content of the text of the law in order to correct and prevent ambiguity in the theory and practice of law enforcement.

• Water Engineering Research
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• v.1 no.1
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• pp.63-74
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• 2000

This paper presents a two- phase search scheme for optimal pipe expansion of expansion of existing water distribution systems. In pipe network problems, link flows affect the total cost of the system because the link flows are not uniquely determined for various pipe diameters. The two-phase search scheme based on stochastic optimization scheme is suggested to determine the optimal link flows which make the optimal design of existing pipe network. A sample pipe network is employed to test the proposed method. Once the best tree network is obtained, the link flows are perturbed to find a near global optimum over the whole feasible region. It should be noted that in the perturbation stage the loop flows obtained form the sample existing network are employed as the initial loop flows of the proposed method. It has been also found that the relationship of cost-hydraulic gradient for pipe expansion of existing network affects the total cost of the sample network. The results show that the proposed method can yield a lower cost design than the conventional design method and that the proposed method can be efficiently used to design the pipe expansion of existing water distribution systems.

• ETRI Journal
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• v.37 no.2
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• pp.262-272
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• 2015

In particular, for a practical mobile robot team to perform such a task as that of carrying out a search and rescue mission in a disaster area, the network connectivity and localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a Global Positioning System is unavailable. This paper proposes the new collective intelligence network management architecture of multiple mobile robots supporting seamless network connectivity and cooperative localization. The proposed architecture includes a resource manager that makes the robots move around and not disconnect from the network link by considering the strength of the network signal and link quality. The location manager in the architecture supports localizing robots seamlessly by finding the relative locations of the robots as they move from a global outdoor environment to a local indoor position. The proposed schemes assuring network connectivity and localization were validated through numerical simulations and applied to a search and rescue robot team.