• Proceedings of the Korea Society for Simulation Conference
• /
• 2003.06a
• /
• pp.179-184
• /
• 2003

HLA-RTI is middleware for the distribute simulation that developed in the US Department of Defense. This provides fast accomplishment speed and reliability than distribute simulation Middleware by transfer. However, DDM(Data Distribution Management) service is used as data filtering technology in the existing HLA-RTI. As for this, the problem that network traffic increases in data exchange between the mobility simulation objects is generated. it proposes applying agent technology to the mobility simulation object in order to solve these problems in this paper in this. And this paper applies that to practical simulation and analyzes performance between each data filtering technology with comparison.

• Structural Engineering and Mechanics
• /
• v.77 no.2
• /
• pp.167-177
• /
• 2021

Due to various benefits such as unlimited degrees of freedom, environment adaptability, and safety for humans, engineers have used soft materials with hyperelastic behavior in various industrial, medical, rescue, and other sectors. One of the applications of these materials in the fabrication of bending soft actuators (SA) is that they have eliminated many problems in the actuators such as production cost, mechanical complexity, and design algorithm. However, SA has complexities, such as predicting and monitoring behavior despite the many benefits. The first part of this paper deals with the prediction of SA behavior through mathematical models such as Ogden and Darijani, and its comparison with the results of experiments. At first, by examining different geometric models, the cubic structure was selected as the optimal structure in the investigated models. This geometrical structure at the same pressure showed the most significant bending in the simulation. The simulation results were then compared with experimental, and the final gripper model was designed and manufactured using a 3D printer with silicone rubber as for the polymer part. This geometrical structure is capable of bending up to a 90-degree angle at 70 kPa in less than 2 seconds. The second section is dedicated to monitoring the bending behavior created by the strain sensors with different sensitivity and stretchability. In the fabrication of the sensors, silicon is used as a soft material with hyperelastic behavior and carbon fiber as a conductive material in the soft material substrate. The SA designed in this paper is capable of deforming up to 1000 cycles without changing its characteristics and capable of moving objects weigh up to 1200 g. This SA has the capability of being used in soft robots and artificial hand making for high-speed objects harvesting.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.40 no.3
• /
• pp.265-271
• /
• 2020

Automotive radar that is one of the most important equipment in high-tech vehicles, is commonly used to detect the speed and range of objects such as cars. In this paper, in addition to objects detection, a method of retrieving precipitation information using the automotive radar data is proposed. The proposed method is based on the fact that the degree of attenuation of the returned radar signal differs depending on the precipitation intensity and the assumption that the distribution of precipitation is constant in short spatial and temporal observation. The purpose of this paper is to assesses the possibility of retrieving precipitation information using a vehicle radar. To verify the feasibility of the proposed method during actual driving, a method of estimating precipitation information for each time segment of various precipitation events was applied. From the results of driving field experiments, it was found that the proposed method is suitable for estimating precipitation information in various rainfall types.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.3
• /
• pp.86-99
• /
• 2021

This research proposes the Accident Prevention System to prevent collision accident that can occur due to blind spots such as crossway or school zone using V2I communication. Vision sensor and LiDAR sensor located in the infrastructure of crossway somewhere like that recognize objects and warn vehicles at risk of accidents to prevent accidents in advance. Using deep learning-based YOLOv4 to recognize the object entering the intersection and using the Manhattan Distance value with LiDAR sensors to calculate the expected collision time and the weight of braking distance and secure safe distance. V2I communication used ROS (Robot Operating System) communication to prevent accidents in advance by conveying various information to the vehicle, including class, distance, and speed of entry objects, in addition to collision warning.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.2
• /
• pp.595-598
• /
• 2005

MPEG-4 Visual is, and international standard for the object-based video compression, designed for supporting a wide range of applications from multimedia communication to HDTV. To control the minimum decoding complexity required at the decoder, the MPEG-4 Visual standard defines the co-called video buffering mechanism, which includes three video buffer models. Among them, the VCV(Video Complexity Verifier) defines the control of the processing speed for decoding of a macroblock, there are two models: VCV and B-VCV distinguishing the boundary and non-boundary MB. This paper presents the evaluation results of decoding complexity by measuring decoding time of a MB for rectangular, arbitrarily shaped video objects and the various types of objects supporting the resolution of HDTV using the optimized MPEG-4 Reference Software. The experimental results shows that decoding complexity varies depending on the coding type and more effective usage of decoding resources may be possible.

• Journal of the Institute of Convergence Signal Processing
• /
• v.23 no.3
• /
• pp.150-159
• /
• 2022

This paper presents an implementation of detecting whether a helmet is worn and there is a fall accident through individual image analysis in real-time from extracting the image objects of several workers active in the industrial field. In order to detect image objects of workers, YOLO, a deep learning-based computer vision model, was used, and for whether a helmet is worn or not, the extracted images with 5,000 different helmet learning data images were applied. For whether a fall accident occurred, the position of the head was checked using the Pose real-time body tracking algorithm of Mediapipe, and the movement speed was calculated to determine whether the person fell. In addition, to give reliability to the result of a falling accident, a method to infer the posture of an object by obtaining the size of YOLO's bounding box was proposed and implemented. Finally, Telegram API Bot and Firebase DB server were implemented for notification service to administrators.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.3
• /
• pp.580-585
• /
• 2009

Real Time Locating Systems (RTLS) are used to track and identify the location of objects in real time using simple, inexpensive tags attached to or embedded in objects and readers that receive the wireless signals from these tags to determine their locations. A tag is powered an internal source such as a battery. The blink frequency of a tag affects the energy efficiency and the locating accuracy of RTLS. The mobility of a tag also affects the locating accuracy. In this paper, we introduce a RTLS tag design which improves the locating accuracy and the power efficiency. We propose an adaptive transmission-rate control algorithm using a motion sensor. By analyzing the signal pattern of the motion sensor, we can build a model to estimate the speed of the motion. Using this model, our algorithm can achieve better locating accuracy and lower power consumption than those of the conventional method. In our experiments, the number of transmission reduced as 40%, keeping similar locating accuracy.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.168-173
• /
• 2003

In this paper, we will present a deeper look on optimal design methods that are related to path-planning for a mobile robot. To control the motion of a mobile robot in a clustered environment, it's necessary to know a suitable trajectory assuming certain start and goal point. Up to now, there are many literatures that concern optimal path planning for an obstacle avoided mobile robot. Among those literatures, we have chosen 2 novel methods for our further analysis. The first approach [4] is based on HJB(Hamilton-Jacobi-Bellman) equation whose solution is the return-function that helps to generate a shortest path to the goal. The later [5] is called polynomial-path-planning approach, in this method, a shortest polynomial-shape path would become a solution if it was a collision-free path. The camera network plays the role as sensors to generate updated map which locates the static and dynamic objects in the space. Therefore, the exhibition of both path planning and dynamic obstacle avoidance by the updated map would be accomplished simultaneously. As we mentioned before, our research will include the motion control of a true mobile robot on those optimal planned paths which were generated by above algorithms. Base on the kinematic and dynamic simulation results, we can realize the affection of moving speed to the stable of motion on each generated path. Also, we can verify the time-optimal trajectory through velocity tuning. To simplify for our analysis, we assumed the obstacles are cylindrical circular objects with the same size.

• International Journal of Computer Science & Network Security
• /
• v.23 no.10
• /
• pp.37-43
• /
• 2023

The hospital situation, timing, and patient restrictions have become obstacles to an optimum therapy session. The crowdedness of the hospital might lead to a tight schedule and a shorter period of therapy. This condition might strike a post-stroke patient in a dilemma where they need regular treatment to recover their nervous system. In this work, we propose an in-house and uncomplex serious game system that can be used for physical therapy. The Kinect camera is used to capture the depth image stream of a human skeleton. Afterwards, the user might use their hand gesture to control the game. Voice recognition is deployed to ease them with play. Users must complete the given challenge to obtain a more significant outcome from this therapy system. Subjects will use their upper limb and hands to capture the 3D objects with different speeds and positions. The more substantial challenge, speed, and location will be increased and random. Each delegated entity will raise the scores. Afterwards, the scores will be further evaluated to correlate with therapy progress. Users are delighted with the system and eager to use it as their daily exercise. The experimental studies show a comparison between score and difficulty that represent characteristics of user and game. Users tend to quickly adapt to easy and medium levels, while high level requires better focus and proper synchronization between hand and eye to capture the 3D objects. The statistical analysis with a confidence rate(α:0.05) of the usability test shows that the proposed gaming is accessible, even without specialized training. It is not only for therapy but also for fitness because it can be used for body exercise. The result of the experiment is very satisfying. Most users enjoy and familiarize themselves quickly. The evaluation study demonstrates user satisfaction and perception during testing. Future work of the proposed serious game might involve haptic devices to stimulate their physical sensation.

• Journal of KIISE:Databases
• /
• v.32 no.4
• /
• pp.405-415
• /
• 2005

Indexing techniques are used to implement selective tuning in wireless environments Indices are broadcast together with data to help mobile clients locate the required information. As a result, clients stay in doze mode most of the time. The drawback of this solution is that broadcast cycles are lengthened due to additional index information. In location-aware mobile services(LAMSs), it is important to reduce the query response time, since a late query response nay contain out-of-date information. In this paper, we present a broadcast-based spatial query processing method (BBS) designed to support k-NN query processing. In the BBS, broadcasted data objects are sorted sequentially based on their locations, and the server broadcasts the location dependent data along with an index segment. The performance of this scheme is investigated in relation to various environmental variables, such as the distributions of the data objects, the average speed of the clients and the size of the service area.