• KIPS Transactions on Computer and Communication Systems
• /
• v.8 no.8
• /
• pp.191-200
• /
• 2019

In an Ad-hoc network, a method of time synchronizing all the nodes in a network centering on one reference node can be used. A representative algorithm based on a reference node is Flooding Time Synchronization Protocol (FTSP). In the process of sending and receiving messages, predictable and unpredictable delays occur, which should be removed because it hinders accurate time synchronization. In multi-hop communications, hop delays occur when a packet traverses a number of hops. These hop delays significantly degrade the synchronization performance among nodes. Therefore, we need to find a method to reduce these hop delays and increase synchronization performance. In the FTSP scheme, hop delays can be greatly increased depending on the position of a reference node. In addition, in FTSP, a node with the smallest node ID is elected as a reference node, hence, the position of a reference node is actually arbitrarily determined. In this paper, we propose an optimal reference node election algorithm to reduce hop delays, and compare the performance of the proposed scheme with FTSP using the network simulator OPNET. In addition, we verify that the proposed scheme has an improved synchronization performance, which is robust to topology changes.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.1
• /
• pp.679-687
• /
• 2017

This study examines financial factors affecting cash holdings of firms in the domestic capital markets. Specifically, this study focuses on regional firms with headquarters in Chungcheong province, the Republic of Korea, which features little previous research concentrating on the firms in the particular region. Three primary hypotheses were empirically tested utilizing robust econometric models, including static panel data, Tobit regression, and logistic models.Results reveal only five explanatory variables, including DSO, LIQUID, LEVERAGE, PMARGIN, and SIZE, showed statistically significant effects on the level of cash holdings among the nine variables studied. In addition two IDVs, LEVERAGE and FOS, showed significant differentiated effects between firms with headquarters in North and South Chungcheong regions. With continued debate among interested parties on the optimal level of cash reserves, the study provides a new vision for the optimal cash reserves for firms with headquarters in Chungcheong Province, where unprecedented socio-economic factors are driven.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.3 no.3
• /
• pp.63-74
• /
• 1999

A sliding mode fuzzy control (SMFC) algorithm is presented for vibration of large structures. Rule-base of the fuzzy inference engine is constructed based on the sliding mode control, which is one of the nonlinear control algorithms. Fuzziness of the controller makes the control system robust against the uncertainties in the system parameters and the input excitation. Non-linearity of the control rule makes the controller more effective than linear controllers. Design procedure based on the present fuzzy control is more convenient than those of the conventional algorithms based on complex mathematical analysis, such as linear quadratic regulator and sliding mode control(SMC). Robustness of presented controller is illustrated by examining the loop transfer function. For verification of the present algorithm, a numerical study is carried out on the benchmark problem initiated by the ASCE Committee on Structural Control. To achieve a high level of realism, various aspects are considered such as actuator-structure interaction, modeling error, sensor noise, actuator time delay, precision of the A/D and D/A converters, magnitude of control force, and order of control model. Performance of the SMFC is examined in comparison with those of other control algorithms such as $H_{mixed 2/{\infty}}$ optimal polynomial control, neural networks control, and SMC, which were reported by other researchers. The results indicate that the present SMFC is an efficient and attractive control method, since the vibration responses of the structure can be reduced very effectively and the design procedure is simple and convenient.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.3
• /
• pp.451-457
• /
• 2018

We propose an automatic detection and classification system of sewer damage database based on artificial intelligence and deep learning. In order to optimize the performance, we implemented a robust system against various environmental variations such as illumination and shadow changes. In our proposed system, a crack detection and damage classification method using a deep learning based Convolutional Neural Network (CNN) is implemented. For optimal results, 9,941 CCTV images with $256{\times}256$ pixel resolution were used for machine learning on the damaged area based on the CNN model. As a result, the recognition rate of 98.76% was obtained. Total of 646 images of $720{\times}480$ pixel resolution were extracted from various sewage DB for performance evaluation. Proposed system presents the optimal recognition rate for the automatic detection and classification of damage in the sewer DB constructed in various environments.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.9
• /
• pp.1795-1802
• /
• 2009

Motion based serious game is a new style of game and exercise using hands, arms, head and whole body. At that time gamer's reachable movement space is an important game space and interaction happening place. We propose efficient game spatial division and analysis algorithm that gives special information for collision avoidance of game objects. We devide into 9 parts of game space and check the enemy position and upper, down, left and right side movement information of gamer and calculate optimal path for collide avoidance of the enemy. To evaluate the method, we implemented a motion base serious game that consists of a web cam, a player, an enemy, and we obtained some valid results of our method for the collision avoidance. The resole demonstrated that the proposed approach is robust. If movement information is in front of enemy, then the enemy waits and finds the place and runs to avoid collision. This algorithm can be used basic development of level control and effective interaction method for motion based serious game.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.39 no.7
• /
• pp.665-671
• /
• 2015

The performance of fault diagnostics for a planetary gearbox depends on vibration modulation characteristics, which can vary with manufacturing & assembly tolerance, and load condition. In this paper, a fault diagnostics technique that considers vibration modulation characteristics is proposed for the effective fault detection of planetary gearboxes in wind turbines. For identifying the vibration modulation characteristics in practice, re-sampled vibration signals are processed with narrow band-pass filters. Thereafter, the optimal position of the vibration extraction window is identified for effective detection of faulty signals under the varying vibration modulation characteristics. The proposed diagnostics technique makes it possible to perform robust diagnostics of the planetary gearbox with regard to the changeable vibration modulation effect. For demonstrating the proposed fault diagnostics technique, a 2-kW WT testbed is designed with two DC motors and gearboxes. A faulty gear with partial tooth breakage is machined and assembled into the gearbox.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.10
• /
• pp.4411-4417
• /
• 2012

The present study proposes the optimization of wing structure base on reduced model which assures the solution accuracy and computational efficiency. Well-constructed reduced model assures the accurate result in the eigenvalue problem, dynamic analysis or sensitivity of design optimization. Reduced system is classified into the reduce-order model based on structural modes and the reduced system based on degrees of freedom. Because this study uses the reduced system based on degrees of freedom, it is important to select the dominant degrees of freedom properly. For this work, robust selection method, two-level selection scheme, is employed and IRS(Improved Reduced System) is applied to construct the final reduced system. In the optimization process based on the reduced system, all of the equivalent stress, eigenvalue and design sensitivities are calculated from the reduced system. Through a numerical example, it is shown that the present optimization methodology based on the reduction method can provide an optimal results for objective function satisfying constraint condition.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.42 no.7 s.337
• /
• pp.71-78
• /
• 2005

A K-Best algerian is known as optimal for implementing the maximum-likelihood detector (MLD), since it has a fixed maximum complexity compared with the sphere decoding or the maximum-likelihood decoding algorithm. However the computational complexity of the K-Best algrithm is still prohibitively high for practical applications when K is large enough. If small value of K is used, the maximum complexity decreases but error flooring at high SNR is caused by error propagation. In this paper, a K-reduction scheme, which reduces K according to each search level, is proposed to solve error propagation problems. Simulations showed that the proposed scheme provides the improved performance in the bit error rate and also reduces the average complexity compared with the conventional scheme.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.8 no.3
• /
• pp.84-95
• /
• 2005

This paper presents solution heuristics to solving optimal multiple-viewpoint location problems that are based on topographic features. The visibility problem is to maximise the viewshed area for a set of viewpoints on digital elevation models (DEM). For this analysis, five areas are selected, and fundamental topographic features (peak, pass, and pit) are extracted from the DEMs of the study areas. To solve the visibility problem, at first, solution approaches based on the characteristics of the topographic features are explored, and then, a benchmark test is undertaken that solution performances of the solution methods, such as computing times, and visible area sizes, are compared with the performances of traditional spatial heuristics. The feasibility of the solution methods, then, are discussed with the benchmark test results. From the analysis, this paper can conclude that fundamental topographic features based solution methods suggest a new sight of visibility analysis approach which did not discuss in traditional algorithmic approaches. Finally, further research avenues are suggested such as exploring more sophisticated selection process of topographic features related to visibility analysis, exploiting systematic methods to extract topographic features, and robust spatial analytical techniques and optimization techniques that enable to use the topographic features effectively.

• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.200-204
• /
• 2008

In this paper, to solve localization problem for out-door navigation of robotic vehicles, a particle filter based 3D object recognition framework that can estimate the pose of a building or its entrance is presented. A particle filter framework of multiple evidence fusion and model matching in a sequence of images is presented for robust recognition and pose estimation of 3D objects. The proposed approach features 1) the automatic selection and collection of an optimal set of evidences 2) the derivation of multiple interpretations, as particles representing possible object poses in 3D space, and the assignment of their probabilities based on matching the object model with evidences, and 3) the particle filtering of interpretations in time with the additional evidences obtained from a sequence of images. The proposed approach has been validated by the stereo-camera based experimentation of 3D object recognition and pose estimation, where a combination of photometric and geometric features are used for evidences.