• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.309-317
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• 2022

In this paper, we propose a machine learning-based copy-move forgery detection network with dual branches. Because the rotation or scaling operation is frequently involved in copy-move forger, the conventional convolutional neural network is not effectively applied in detecting copy-move tampering. Therefore, we divide the input into rotation-invariant and scaling-invariant features based on the wavelet coefficients. Each of the features is input to different branches having the same structure, and is fused in the combination module. Each branch comprises feature extraction, correlation, and mask decoder modules. In the proposed network, VGG16 is used for the feature extraction module. To check similarity of features generated by the feature extraction module, the conventional correlation module used. Finally, the mask decoder model is applied to develop a pixel-level localization map. We perform experiments on test dataset and compare the proposed method with state-of-the-art tampering localization methods. The results demonstrate that the proposed scheme outperforms the existing approaches.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1657-1664
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• 2018

This paper proposes a decision making scheme for choosing the best move at each state of game in order to implement an artificial intelligence othello game player. The proposed decision making scheme predicts the various possible states of the game when the game has progressed from the current state, evaluates the degree of possibility of winning or losing the game at the states, and searches the best move based on the evaluation. In this paper, we generate learning data by decomposing the records of professional players' real game into states, matching and accumulating winning points to the states, and using the Artificial Neural Network that learned them, we evaluated the value of each predicted state and applied the Minimax search to determine the best move. We implemented an artificial intelligence player of the Othello game by applying the proposed scheme and evaluated the performance of the game player through games with three different artificial intelligence players.

• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.147-155
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• 2015

In this paper, we consider a mobile sensor network for monitoring a polluted area where human beings cannot access. Due to the limited sensing range of individual unmanned vehicles, they need to cooperate to achieve an effective sensing coverage and move to a more polluted region. In order to address the limitations of sensing and communication ranges, we propose a hazardous substance monitoring network based on virtual force algorithms, and develop a testbed. In the considered monitoring network, each unmanned vehicle achieves an optimal coverage and move to the highest interest area based on neighboring nodes sensing values and locations. By using experiments based on the developed testbed, we show that the proposed monitoring network can autonomously move toward a more polluted area and obtain a high weighted coverage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5442-5463
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• 2016

Designing efficient routing protocols for a wireless sensor network with mobile sinks (mWSN) is a challenging task since the network topology and data paths change frequently as sink nodes move. In this paper, we design a novel lightweight reactive ring based routing protocol called R3, which removes the need of proactively maintaining data paths to mobile sinks as they move in the network. To achieve high packet delivery ratio and low transmission cost, R3 combines ring based forwarding and trail based forwarding together. To support efficient ring based forwarding, we build a ring based structure for a network in a way such that each node in the network can easily obtain its ring ID and virtual angle information. For this purpose, we artificially create a virtual hole in the central area of the network and accordingly find a shortest cycled path enclosing the hole, which serves as base ring and is used for generating the remaining ring based structure. We accordingly present the detailed design description for R3, which only requires each node to keep very limited routing information. We derive the communication overhead by ring based forwarding. Extensive simulation results show that R3 can achieve high routing performance as compared with existing work.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1936-1939
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• 2002

Much recent attention on wireless technologies s put on topology-less wireless network, in which all nodes an be mobile and can communicate over wireless links, due to its ease of deployment, high flexibility and low expenses. One key in topology-less wireless network is mobile base stations (MBSs), which provides access points or mobile terminals (MTs) to wireless backbone network. MBSs can move to anywhere in accordance with changes in geographical distribution of MTs. They serve as dynamic odes. However, in order to utilize network resources and take full advantage of this topology-less network, MBSs must move to suitable position according to the current tate of network use. Moreover, MBSs have to consider the distance among them to avoid the crash and gap area of MBSs. Therefore, this paper proposes MBS movement algorithm by implementing push-pull method to fulfill the corporation of MBSs and considering the center of covered MTs or centroid to satisfy the MT coverage. From the simulation results, the proposed algorithm increases the performance of system when comparing with the centroid-based algoriom〔7〕, such as coverage area, MT coverage and call drops rate.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.473-479
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• 2006

A global path planning algorithm using modified self-organizing feature map(SOFM) which is a method among a number of neural network is presented. The SOFM uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors of the 2-dimensional mesh, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the opposite direction of input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.

• Proceedings of the KSRS Conference
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• v.2
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• pp.695-697
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• 2006

Elshayal $Smart{\copyright}$ software is an almost First Arabian GIS $software{\copyright}$ which completely developed by Arabian developers team and independent of any commercial software package. The software current Features are View and Edit shape files, build new layers, add existing layers, remove layers, swap layers, save layers, set layer data sources, layer properties, zoom in & zoom out, pan, identify, selecting features, invert selection, show data table, data query builder, location query builder, build network, find shortest path, print map, save map image, copy map image to clipboard, save project map, edit move vertex, edit move features, snap vertexes, set vertex XY, move settings, converting coordinate system, applying VB script, copy selected features to another layer, move selected features to another layer, delete selected features, edit data table, modify table structure, edit map features, drawing new features, GPS tracking, 3D view, etc... The software expected Features are: Viewing raster image and image geo-referencing, read other map formats such as DXF Format and Tiger Line Format.

• Convergence Security Journal
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• v.11 no.4
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• pp.11-17
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• 2011

In this paper, we propose system design and implementation of FLV Move Picture Solution based on IDC apply to Mini IPTV. IDC of energy minimize and Green Data Center design resources make use of maximization, and Mini IPTV of diverse contents service provider and network provider offer Mini IPTV customers to transmit network. at this time implemented on the improve Move Picture of motion blur and compressibility using FLV solution file format and a compression technique, and reduced traffic cost and solved security question. specially, on the web quickly growing a branch of e-Learning wish to be of help.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.817-822
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• 2004

This paper provides a global path planning method using self-organizing feature map which is a method among a number of neural network. The self-organizing feature map uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.