• The Journal of Korean Institute of Information Technology
• /
• v.17 no.12
• /
• pp.29-38
• /
• 2019

A path prediction method using lifelog requires a large amount of training data for accurate path prediction, and the path prediction performance is degraded when the training data is insufficient. The lack of training data can be solved using data of other users having similar user movement patterns. Therefore, this paper proposes a path prediction algorithm based on user similarity. The proposed algorithm learns the path in a triple grid pattern and measures the similarity between users using the cosine similarity technique. Then, it predicts the path with applying measured similarity to the learned model. For the evaluation, we measure and compare the path prediction accuracy of proposed method with the existing algorithms. As a result, the proposed method has 66.6% accuracy, and it is evaluated that its accuracy is 1.8% higher than other methods.

• The Journal of Korea Robotics Society
• /
• v.13 no.2
• /
• pp.121-128
• /
• 2018

Obstacle avoidance is one of the most important parts of autonomous mobile robot. In this study, we proposed safe and efficient local path planning of robot for obstacle avoidance. The proposed method detects and tracks obstacles using the 3D depth information of an RGB-D sensor for path prediction. Based on the tracked information of obstacles, the paths of the obstacles are predicted with probability circle-based spatial search (PCSS) method and Gaussian modeling is performed to reduce uncertainty and to create the cost function of caution. The possibility of collision with the robot is considered through the predicted path of the obstacles, and a local path is generated. This enables safe and efficient navigation of the robot. The results in various experiments show that the proposed method enables robots to navigate safely and effectively.

• Journal of IKEEE
• /
• v.24 no.2
• /
• pp.661-664
• /
• 2020

In this paper, we propose a maritime region segmentation method and a segment-based destination prediction method for vessel path prediction. In order to perform maritime segmentation, clustering on destination candidates generated from the past paths is conducted. Then the segment-based destination prediction is followed. For destination prediction, different prediction methods are applied according to whether the current region is linear or not. In the linear domain, the vessel is regarded to move constantly, and linear prediction is applied. In the nonlinear domain with an uncertainty, we assume that the vessel moves similarly to the most similar past path. Experimental results show that applying the linear prediction and the prediction method using a similar path differently depending on the linearity and the uncertainty of the path is better than applying one of them alone.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.2
• /
• pp.1-12
• /
• 2024

Predicting path loss is one of the important factors for wireless network design, such as selecting the installation location of base stations in cellular networks. In the past, path loss values were measured through numerous field tests to determine the optimal installation location of the base station, which has the disadvantage of taking a lot of time to measure. To solve this problem, in this study, we propose a path loss prediction method based on machine learning (ML). In particular, an ensemble learning approach is applied to improve the path loss prediction performance. Bootstrap dataset was utilized to obtain models with different hyperparameter configurations, and the final model was built by ensembling these models. We evaluated and compared the performance of the proposed ensemble-based path loss prediction method with various ML-based methods using publicly available path loss datasets. The experimental results show that the proposed method outperforms the existing methods and can predict the path loss values accurately.

• Journal of IKEEE
• /
• v.24 no.4
• /
• pp.1176-1179
• /
• 2020

Vessel path prediction methods generally predict the latitude and longitude of a future location directly. However, in the case of direct prediction, errors could be large since the possible output range is too broad. In addition, error accumulation could occur since recurrent neural networks-based methods employ previous predicted data to forecast future data. In this paper, we propose a vessel path prediction method that does not directly predict the longitude and latitude. Instead, the proposed method predicts the acceleration of the vessel. Then the acceleration is employed to generate the velocity and direction, and the values decide the longitude and latitude of the future location. In the experiment, we show that the proposed method makes smaller errors than the direct prediction method, while both methods employ the same model.

• The Journal of the Acoustical Society of Korea
• /
• v.22 no.1E
• /
• pp.33-42
• /
• 2003

Kuo et al proposed an on-line method for an adaptive prediction error filter for improving secondary path modeling performance in the modeling method of the secondary path. This method have some disadvantages, namely having to use additive noise with the result that noise control performance is not good since it is focused on the estimated performance of the secondary path. In this paper, we proposes a modified Kuo model using gain control parameter and delay. It uses a reference signal for additive noise to improve the problems in the existing Kuo model.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.5
• /
• pp.568-574
• /
• 2006

User adaptive services have been important features in many applications. To provide such services, various techniques with various kinds of data are being used. In this paper, we propose a method to analyze user's past moving paths and predict the goal position and the path to the goal by observing the user's current moving path. We develop a spatiotemporal similarity measure between paths. We choose a past path which is the most similar to the current path using the similarity. Based on the chosen path, user's spatiotemporal position is estimated. Through experiments we confirm this method is useful and effective.

• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.298-303
• /
• 2008

User adaptive services have been important features in many applications. To provide such services, various techniques with various kinds of data are being used. In this paper, we propose a method to analyze user's past moving paths for predicting the goal position and the path to the goal by observing the user's current moving path. We develop a spatio-temporal similarity measure between paths. We choose a past path which is the most similar to the current path using the similarity. Based on the chosen path, user's spatio-temporal position is estimated. Through experiments we confirm this method is useful and effective.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.8 no.6
• /
• pp.105-112
• /
• 1999

In this paper we deal with tool interference problem in the case of compound surface machining. A new tool interference detection and correction method based on the envelope of the tool path is suggested to identify and correct the tool interference - not only within the local path of tool movement, but also outside of the tool path. Therefore, the developed strategy can be used to check the possible interference in any region of the surface. In order to analyze quantitatively the milled surface error produced by the tool interference, improved surface prediction model is also suggested in cutting process by general cutters. The effectiveness of the proposed method is demonstrated through simulation study.

• Proceedings of the Acoustical Society of Korea Conference
• /
• autumn
• /
• pp.191-194
• /
• 2004

This study Is an measurement and prediction of transmission loss through dash panel with multi-path in a vehicle. Measurement results of transmission loss are decided by sound power measured using the sound intensity method under locating a sound source in the anechoic room and reverberant room, respectively. Prediction one is decided by multi-path analysis of dash panel composed by a various part of materials and complicated shape. Finally, two results show a great agreement between measured and predicted transmission loss.