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* Jin-Gu Kang received the B.S. and LL.B. degrees from Dongguk University, Seoul, Korea, in 2019. Currently, he has been under the M.S. degree candidate at the Dept. of Computer Science and Engineering, Dongguk University, since 2019. His research areas include Robot AI, Vision and Computer Networks. (From https://orcid.org/0000-0003-4262-7840) [Research Keywords: Robot AI; Vision; Computer Networks]
To solve the problem that sampling-based Rapidly-exploring Random Tree (RRT) method is difficult to guarantee optimality. This paper proposed the Post Triangular Processing of Midpoint Interpolation method minimized the planning time and shorter path length of the sampling-based algorithm. The proposed Post Triangular Processing of Midpoint Interpolation method makes a closer to the optimal path and somewhat solves the sharp path problem through the interpolation process. The experiments were conducted to verify the performance of the proposed method. Applying the method proposed in this paper to the RRT algorithm increases the efficiency of optimization compared to the planning time.
Jin-Gu Kang; Yong-Sik Choi; Jin-Woo Jung. An Enhancement Method of Rapidly-exploring Random Tree Robot Path Planning using Midpoint Interpolation. 2021, 1 .
AMA StyleJin-Gu Kang, Yong-Sik Choi, Jin-Woo Jung. An Enhancement Method of Rapidly-exploring Random Tree Robot Path Planning using Midpoint Interpolation. . 2021; ():1.
Chicago/Turabian StyleJin-Gu Kang; Yong-Sik Choi; Jin-Woo Jung. 2021. "An Enhancement Method of Rapidly-exploring Random Tree Robot Path Planning using Midpoint Interpolation." , no. : 1.
This paper proposed a triangular inequality-based rewiring method for the rapidly exploring random tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm’s performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time.
Jin-Gu Kang; Dong-Woo Lim; Yong-Sik Choi; Woo-Jin Jang; Jin-Woo Jung. Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning. Sensors 2021, 21, 333 .
AMA StyleJin-Gu Kang, Dong-Woo Lim, Yong-Sik Choi, Woo-Jin Jang, Jin-Woo Jung. Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning. Sensors. 2021; 21 (2):333.
Chicago/Turabian StyleJin-Gu Kang; Dong-Woo Lim; Yong-Sik Choi; Woo-Jin Jang; Jin-Woo Jung. 2021. "Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning." Sensors 21, no. 2: 333.
This paper proposed a triangular inequality-based rewiring method for the Rapidly exploring Random Tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm’s performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time.
Jin-Gu Kang; Dong-Woo Lim; Yong-Sik Choi; Woo-Jin Jang; Jin-Woo Jung. Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning. 2020, 1 .
AMA StyleJin-Gu Kang, Dong-Woo Lim, Yong-Sik Choi, Woo-Jin Jang, Jin-Woo Jung. Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning. . 2020; ():1.
Chicago/Turabian StyleJin-Gu Kang; Dong-Woo Lim; Yong-Sik Choi; Woo-Jin Jang; Jin-Woo Jung. 2020. "Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning." , no. : 1.
IBM Watson is one of the representative tools for speech recognition system which can automatically generate not only speech-to-text information but also speaker ID and timing information, which is called as Informatized Caption. However, if there is some noise in the voice signal to the IBM Watson API, the recognition performance is significantly decreased. It can be easily found in movies with background music and special sound effects. This paper aims to improve the inaccuracy problem of current Informatized Captions in noisy environments. In this paper, a method of modifying incorrectly recognized words and a method of enhancing timing accuracy while updating database in real time are suggested based on the original caption and Informatized Caption information. Experimental results shows that the proposed method can give 81.09% timing accuracy for the case of 10 representative animation, horror and action movies.
Yong-Sik Choi; Jin-Gu Kang; Jong Wha J. Joo; Jin-Woo Jung. Real-time Informatized caption enhancement based on speaker pronunciation time database. Multimedia Tools and Applications 2020, 1 -22.
AMA StyleYong-Sik Choi, Jin-Gu Kang, Jong Wha J. Joo, Jin-Woo Jung. Real-time Informatized caption enhancement based on speaker pronunciation time database. Multimedia Tools and Applications. 2020; ():1-22.
Chicago/Turabian StyleYong-Sik Choi; Jin-Gu Kang; Jong Wha J. Joo; Jin-Woo Jung. 2020. "Real-time Informatized caption enhancement based on speaker pronunciation time database." Multimedia Tools and Applications , no. : 1-22.
Environment maps must first be generated to drive mobile robots automatically. Path planning is performed based on the information given in an environment map. Various types of sensors, such as ultrasonic and laser sensors, are used by mobile robots to acquire data on its surrounding environment. Among these, the laser sensor, which has the property of being able to go straight and high accuracy, is used most often. However, the beams from laser sensors are refracted and reflected when it meets a transparent obstacle, thus generating noise. Therefore, in this paper, a state-of-the-art algorithm was proposed to detect transparent obstacles by analyzing the pattern of the reflected noise generated when a laser meets a transparent obstacle. The experiment was carried out using the environment map generated by the aforementioned method and gave results demonstrating that the robot could avoid transparent obstacles while it was moving towards the destination.
Jin-Woo Jung; Jung-Soo Park; Tae-Won Kang; Jin-Gu Kang; Hyun-Wook Kang. Mobile Robot Path Planning Using a Laser Range Finder for Environments with Transparent Obstacles. Applied Sciences 2020, 10, 2799 .
AMA StyleJin-Woo Jung, Jung-Soo Park, Tae-Won Kang, Jin-Gu Kang, Hyun-Wook Kang. Mobile Robot Path Planning Using a Laser Range Finder for Environments with Transparent Obstacles. Applied Sciences. 2020; 10 (8):2799.
Chicago/Turabian StyleJin-Woo Jung; Jung-Soo Park; Tae-Won Kang; Jin-Gu Kang; Hyun-Wook Kang. 2020. "Mobile Robot Path Planning Using a Laser Range Finder for Environments with Transparent Obstacles." Applied Sciences 10, no. 8: 2799.
Yeji Shin; Youngone Cho; Hyun Wook Kang; Jin-Gu Kang; Jin-Woo Jung. Neural Network-based Efficient Measurement Method on Upside Down Orientation of a Digital Document. Advances in Science, Technology and Engineering Systems Journal 2020, 5, 697 -702.
AMA StyleYeji Shin, Youngone Cho, Hyun Wook Kang, Jin-Gu Kang, Jin-Woo Jung. Neural Network-based Efficient Measurement Method on Upside Down Orientation of a Digital Document. Advances in Science, Technology and Engineering Systems Journal. 2020; 5 (2):697-702.
Chicago/Turabian StyleYeji Shin; Youngone Cho; Hyun Wook Kang; Jin-Gu Kang; Jin-Woo Jung. 2020. "Neural Network-based Efficient Measurement Method on Upside Down Orientation of a Digital Document." Advances in Science, Technology and Engineering Systems Journal 5, no. 2: 697-702.
ECD (Exact Cell Decomposition) based path planning is not applicable in curvilinear obstacles environment. Therefore, after the curvilinear obstacles are approximated to the polygons by using DP (Douglas-Peucker) algorithm, which is a polygon approximation algorithm, the ECD method is applied. However, there is a case of not including all the existing obstacles' area and ignoring the outer area, when it comes to the curvilinear obstacles, approximated to the polygons by using the DP algorithm. In this case, path planning of ECD method cannot guarantee the clearance. This paper proposes a CDP (Circumscribed DP) algorithm to solve this problem. The CDP algorithm has a disadvantage of having more inner area than the DP algorithm, but it can guarantee the clearance because of the fact the algorithm always has 0(%) of outer area (OA). In order to confirm this, the polygonal approximation of DP and CDP algorithms was compared in the same curvilinear obstacles and the result was as the following: When each ε value is 0.05, 0.08, 0.11(m), each result of the inner area ratio (IA) was 2.45, 4.89, 7.19(%) by DP algorithm, 16.3, 18.39, 32.58(%) by CDP algorithm, and result of the outer area ratio (OA) was 0.7, 1.17, 1.54(%) by DP Algorithm, 0, 0, 0(%) by CDP Algorithm. Also, it can be confirmed that the CDP algorithm has always guaranteed for clearance.
Jin-Woo Jung; Byung-Chul So; Jin-Gu Kang; Woo-Jin Jang. Circumscribed Douglas-Peucker Polygonal Approximation for Curvilinear Obstacle Representation. 2019 7th International Conference on Robot Intelligence Technology and Applications (RiTA) 2019, 237 -241.
AMA StyleJin-Woo Jung, Byung-Chul So, Jin-Gu Kang, Woo-Jin Jang. Circumscribed Douglas-Peucker Polygonal Approximation for Curvilinear Obstacle Representation. 2019 7th International Conference on Robot Intelligence Technology and Applications (RiTA). 2019; ():237-241.
Chicago/Turabian StyleJin-Woo Jung; Byung-Chul So; Jin-Gu Kang; Woo-Jin Jang. 2019. "Circumscribed Douglas-Peucker Polygonal Approximation for Curvilinear Obstacle Representation." 2019 7th International Conference on Robot Intelligence Technology and Applications (RiTA) , no. : 237-241.
This paper proposes a new protocol that can be used to reduce transmission delay and energy consumption effectively. This will be done by adjusting the duty-cycle (DC) ratio of the receiver node and the contention window size of the sender node according to the traffic congestion for various devices in the Internet of Things (IoT). In the conventional duty-cycle MAC protocol, the data transmission delay latency and unnecessary energy consumption are caused by a high collision rate. This is because the receiver node cannot sufficiently process the data of the transmitting node during the traffic peak time when the transmission and reception have the same duty-cycle ratio. To solve this problem, this paper proposes an algorithm that changes the duty-cycle ratio of the receiver and broadcasts the contention window size of the senders through Early Acknowledgment (E-ACK) at peak time and off/peak time. The proposed algorithm, according to peak and off/peak time, can transmit data with fewer delays and minimizes energy consumption.
Gayoung Kim; Jin-Gu Kang; MinJoong Rim. Dynamic Duty-Cycle MAC Protocol for IoT Environments and Wireless Sensor Networks. Energies 2019, 12, 4069 .
AMA StyleGayoung Kim, Jin-Gu Kang, MinJoong Rim. Dynamic Duty-Cycle MAC Protocol for IoT Environments and Wireless Sensor Networks. Energies. 2019; 12 (21):4069.
Chicago/Turabian StyleGayoung Kim; Jin-Gu Kang; MinJoong Rim. 2019. "Dynamic Duty-Cycle MAC Protocol for IoT Environments and Wireless Sensor Networks." Energies 12, no. 21: 4069.
The Expanded Douglas–Peucker (EDP) polygonal approximation algorithm and its application method for the Opposite Angle-Based Exact Cell Decomposition (OAECD) are proposed for the mobile robot path-planning problem with curvilinear obstacles. The performance of the proposed algorithm is compared with the existing Douglas–Peucker (DP) polygonal approximation and vertical cell decomposition algorithm. The experimental results show that the path generated by the OAECD algorithm with EDP approximation appears much more natural and efficient than the path generated by the vertical cell decomposition algorithm with DP approximation.
Jin-Woo Jung; Byung-Chul So; Jin-Gu Kang; Dong-Woo Lim; Yunsik Son. Expanded Douglas–Peucker Polygonal Approximation and Opposite Angle-Based Exact Cell Decomposition for Path Planning with Curvilinear Obstacles. Applied Sciences 2019, 9, 638 .
AMA StyleJin-Woo Jung, Byung-Chul So, Jin-Gu Kang, Dong-Woo Lim, Yunsik Son. Expanded Douglas–Peucker Polygonal Approximation and Opposite Angle-Based Exact Cell Decomposition for Path Planning with Curvilinear Obstacles. Applied Sciences. 2019; 9 (4):638.
Chicago/Turabian StyleJin-Woo Jung; Byung-Chul So; Jin-Gu Kang; Dong-Woo Lim; Yunsik Son. 2019. "Expanded Douglas–Peucker Polygonal Approximation and Opposite Angle-Based Exact Cell Decomposition for Path Planning with Curvilinear Obstacles." Applied Sciences 9, no. 4: 638.
Hyun Mo Yang; Ng Woo Lim; Yong Sik Choi; Jin-Gu Kang; In Hwan Kim; Ailing Lin; Jin Woo Jung. Image-based human sperm counting method. International Journal of Social and Humanistic Computing 2019, 3, 148 .
AMA StyleHyun Mo Yang, Ng Woo Lim, Yong Sik Choi, Jin-Gu Kang, In Hwan Kim, Ailing Lin, Jin Woo Jung. Image-based human sperm counting method. International Journal of Social and Humanistic Computing. 2019; 3 (2):148.
Chicago/Turabian StyleHyun Mo Yang; Ng Woo Lim; Yong Sik Choi; Jin-Gu Kang; In Hwan Kim; Ailing Lin; Jin Woo Jung. 2019. "Image-based human sperm counting method." International Journal of Social and Humanistic Computing 3, no. 2: 148.
This paper proposes an adaptive duty-cycled hybrid X-MAC (ADX-MAC) protocol for energy-efficient forest fire prediction. The Asynchronous sensor network protocol, X-MAC protocol, acquires additional environmental status details from each forest fire monitoring sensor for a given period, and then changes the duty-cycle sleep interval to efficiently calculate forest fire occurrence risk according to the environment. Performance was verified experimentally, and the proposed ADX-MAC protocol improved throughput by 19% and was 24% more energy efficient compared to the X-MAC protocol. The duty-cycle was shortened as forest fire probability increased, ensuring forest fires were detected at faster cycle rate.
Jin-Gu Kang; Dong-Woo Lim; Jin-Woo Jung. Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol. Sensors 2018, 18, 2960 .
AMA StyleJin-Gu Kang, Dong-Woo Lim, Jin-Woo Jung. Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol. Sensors. 2018; 18 (9):2960.
Chicago/Turabian StyleJin-Gu Kang; Dong-Woo Lim; Jin-Woo Jung. 2018. "Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol." Sensors 18, no. 9: 2960.
In this paper, we propose an adaptive duty-cycled hybrid X-MAC (ADX-MAC) protocol for energy-efficient forest fire prediction. The X-MAC protocol acquires the additional environmental status collected by each forest fire monitoring sensor for a certain period. And, based on these values, the length of sleep interval of duty-cycle is changed to efficiently calculate the risk of occurrence of forest fire according to the mountain environment. The performance of the proposed ADX-MAC protocol was verified through experiments the proposed ADX-MAC protocol improves throughput by 19% and was more energy-efficient by 24% compared to X-MAC protocol. As the probability of forest fires increases, the length of the duty cycle is shortened, confirming that the forest fires are detected at a faster cycle.
Jin-Gu Kang; Dong-Woo Lim; Jin-Woo Jung. Energy-Efficient Forest Fire Prediction Model based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol. 2018, 1 .
AMA StyleJin-Gu Kang, Dong-Woo Lim, Jin-Woo Jung. Energy-Efficient Forest Fire Prediction Model based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol. . 2018; ():1.
Chicago/Turabian StyleJin-Gu Kang; Dong-Woo Lim; Jin-Woo Jung. 2018. "Energy-Efficient Forest Fire Prediction Model based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol." , no. : 1.