• Journal of IKEEE
• /
• v.23 no.1
• /
• pp.280-288
• /
• 2019

In the CR-enabled MANET, routing paths can be easily destroyed due to node mobility and channel unavailability (due to the emergence of the PU of a channel), resulting in significant overhead to maintain/recover the routing path. In this paper, network caching is actively used for route maintenance, taking into account the properties of the CR. In the proposed scheme, even if a node detects that a path becomes unavailable, it does not generate control messages to establish an alternative path. Instead, the node stores the packets in its local cache and 1) waits for a certain amount of time for the PU to disappear; 2) waits for a little longer while overhearing messages from other flow; 3) after that, the node applies local route recovery process or delay tolerant forwarding strategy. According to the simulation study using the OPNET simulator, it is shown that the proposed scheme successfully reduces the amount of control messages for path recovery and the service latency for the time-sensitive traffic by 13.8% and 45.4%, respectively, compared to the existing scheme. Nevertheless, the delivery ratio of the time-insensitive traffic is improved 14.5% in the proposed scheme.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.6
• /
• pp.773-781
• /
• 2018

In recent years, a study of power-line inspection using an unmanned aerial vehicle (UAV) has been actively conducted. However, relevant studies have been conducting power-line inspection with an UAV operated by manual control, and they have developed just power-line detection algorithm on aerial images. To overcome limitations of existing research, we propose a drone-based power-line tracking system in this paper. The main contributions of this paper are to operate developed system under configured environment and to develop a power-line detection algorithm in real-time. Developed system is composed of the power-line detection and the image-based tracking control. To detect a power-line in real-time, a region of interest (ROI) image is extracted. Furthermore, clustering algorithm is used in order to discriminate the power-line from background. Finally, the power-line is detected by using the Hough transform, and a center position and a tilt angle are estimated by using the Kalman filter to control a drone smoothly. We design a position controller and an attitude controller for image-based tracking control, and both controllers are designed based on the proportional-derivative (PD) control method. The interaction between the position controller and the attitude controller makes the drone track the power-line. Several experiments were carried out in environments where conditions are similar to actual environments, which demonstrates the superiority of the developed system.

• Journal of Internet Computing and Services
• /
• v.20 no.6
• /
• pp.11-20
• /
• 2019

Numerous enterprises, organizations and individual users are exposed to large DDoS (Distributed Denial of Service) attacks. DDoS attacks are performed through a BotNet, which is composed of a number of computers infected with a malware, e.g., zombie PCs and a special computer that controls the zombie PCs within a hierarchical chain of a command system. In order to detect a malware, a malware detection software or a vaccine program must identify the malware signature through an in-depth analysis, and these signatures need to be updated in priori. This is time consuming and costly. In this paper, we propose a botnet detection scheme that does not require a periodic signature update using an artificial neural network model. The proposed scheme exploits Word2Vec and accelerated hierarchical density-based clustering. Botnet detection performance of the proposed method was evaluated using the CTU-13 dataset. The experimental result shows that the detection rate is 99.9%, which outperforms the conventional method.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.1
• /
• pp.17-34
• /
• 2022

This paper develops a model for dynamic station assignment to optimize the Demand Responsive Transit (DRT) operation. In the process of optimization, we use the bus travel time as a variable for DRT management. In addition, walking time, waiting time, and delay due to detour to take other passengers (detour time) are added as optimization variables and entered for each DRT passenger. Based on a network around Anaheim, California, reserved origins and destinations of passengers are assigned to each demand responsive bus, using K-means clustering. We create a model for selecting the dynamic station and bus route and use Non-dominated Sorting Genetic Algorithm-III to analyze seven scenarios composed combination of the variables. The result of the study concluded that if the DRT operation is optimized for the DRT management, then the bus travel time and waiting time should be considered in the optimization. Moreover, it was concluded that the bus travel time, walking time, and detour time are required for the passenger.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.10
• /
• pp.822-831
• /
• 2003

A computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and the radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation is introduced for line detection. The dimension of inner and outer radius of pipe is calculated by the proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified and removed.

• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.7
• /
• pp.72-84
• /
• 2001

This paper proposes a design methodology for customer, assembly and disassembly considering recycling. The disign process starts with the identification of customer needs, which are in turn converted into functional requirements. The concepts of Design for Customer(DFC), Design for Assembly(DFA), Design for Variety(DFV) and Design for Disassembly(DFD) are considered in the product design phases in order to decreas production variety and mass customization. And, a new module generation approach is developed for rearranging and clustering parts and subassemblies for disassembly and recycling. Based on the result of the module generation, a new configuration methodology is suggested to minimize the disassembly time or number of disassembly operations for recycling.

• International journal of advanced smart convergence
• /
• v.6 no.1
• /
• pp.39-43
• /
• 2017

As the industry grows, the amount of data grows exponentially, and data analysis using these serves as a predictable solution. As data size increases and processing speed increases, it has begun to be applied to new fields by combining artificial intelligence technology as well as simple big data analysis. In this paper, we propose a method to quickly apply a machine learning based algorithm through efficient resource allocation. The proposed algorithm allocates memory for each attribute. Learning Distinct of Attribute and allocating the right memory. In order to compare the performance of the proposed algorithm, we compared it with the existing K-means algorithm. As a result of measuring the execution time, the speed was improved.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.99.1-99
• /
• 2002

In this paper, a computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplacian operator with input image which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along t...

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.946-950
• /
• 2003

In this paper, a computer-vision based pipe shape inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle. by which pipes with wrong end-shape can be classified removed.

• International Journal of Contents
• /
• v.4 no.1
• /
• pp.16-19
• /
• 2008

In this paper, we propose to new dispatcher method, which doesn't depend on an operating system of the server, and the direct routing method, by which a server answers a client's request at first hand. And, propose new web clustering scheme based on the contents on the web where web servers composed of cluster, with each different contents, answer client's request. The other purposes are to reduce overhead of the dispatcher through load balance, and to minimize the time to take in responding to a client's request. The performance of new web cluster scheme was improved by about 39% than that of the existing RR method. It was identified that the performance of the proposed web cluster method was extraordinary improved comparing with that of the existing RR method as a whole.