• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.85-92
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• 2022

In this study, we aim to design an action game that increases the user experience. In order to increase the immersion of the game, the characteristics of the game used by the user were analyzed, and the systemic and visual characteristics of the game were designed with reference to each characteristic. The proposed method uses Unity 3D to implement an interaction system between objects in the game and is designed in a way that allows users to immerse themselves in the game. To induce immersion through the visual elements of the game, 2D objects and players are placed in a 3D space, and a 2D dynamic light shader is added. It is composed of inter-combat rules and monster behavior pattern collision detection and event detection. The proposed method contained the user experience with the implementation thesis, and showed the game's possibility of leading the user's affordance.

• Journal of Biosystems Engineering
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• v.22 no.2
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• pp.237-246
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• 1997

Shucking(removing the meat from the shell) an oyster requires that the muscle attachments to the two shell valves and the hinge be severed. Described here is the computer vision software needed to locate the oyster hinge line so it can be automatically severed, one step in development of an automated oyster shucker. Oysters are first prepared by washing and trimming off a small shell piece on the oyster hinge end to provide access to the outer hinge surface. A computer vision system employing a color video comera then gabs an image of the hinge end of the oyster shell. This image is Processed by the computer using software. The software is a combination of commercially available and custom written routines that locate the oyster hinge. The software uses four feature variables, circularity, rectangularity, aspect-ration, and Euclidian distance, to distinguish the hinge object from other dark colored objects on the hinge end of the oyster. Several techniques, including shrink-expand, thresholding, and others, were used to secure an image that could be reliably and efficiently processed to locate the oyster hinge line.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.197-205
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• 2024

Development of AI and big data-based algorithms to advance and optimize the recognition and detection performance of various static/dynamic vehicles in front and around the vehicle at a time when securing driving safety is the most important point in the development and commercialization of autonomous vehicles. etc. are being studied. However, there are many research cases for recognizing the same vehicle by using the unique advantages of radar and camera, but deep learning image processing technology is not used, or only a short distance is detected as the same target due to radar performance problems. Therefore, there is a need for a convergence-based vehicle recognition method that configures a dataset that can be collected from radar equipment and camera equipment, calculates the error of the dataset, and recognizes it as the same target. In this paper, we aim to develop a technology that can link location information according to the installation location because data errors occur because it is judged as the same object depending on the installation location of the radar and CCTV (video).

• Journal of the Health Care and Life Science
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• v.10 no.2
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• pp.361-367
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• 2022

This study provides several methods to minimize dead zone and to detect missing person using combined DRONE and AI especially called 4 th Industrial Revolution. That is composed of image acquisition for a person who is in needed of support. The procedure is DRONE that is made of image acquisition and transfer system. after that can be shown GPS information. Currently representative AI algorithm is YOLO (You Only Look Once) that can be adopted to find manikin or real image by learning with dataset. The output was reached in reliable and efficient results. As the trends of DRONE is expanded widely that will provide various roll. This paper was composed of three parts. the first is DRONE specification, the second is the definition of AI and procedures, the third is the methods of image acquisition using DRONE, the last is the future of DRONE with AI.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.233-247
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• 2023

Recently, research on detecting objects in hidden spaces beyond the direct line-of-sight of observers has received attention. Most studies use optical equipment that utilizes the directional of light, but sound that has both diffraction and directional is also suitable for non-line-of-sight(NLOS) research. In this paper, we propose a novel method of detecting objects in non-line-of-sight (NLOS) areas using acoustic signals in the audible frequency range. We developed a deep learning model that extracts information from the NLOS area by inputting only acoustic signals and predicts the properties and location of hidden objects. Additionally, for the training and evaluation of the deep learning model, we collected data by varying the signal transmission and reception location for a total of 11 objects. We show that the deep learning model demonstrates outstanding performance in detecting objects in the NLOS area using acoustic signals. We observed that the performance decreases as the distance between the signal collection location and the reflecting wall, and the performance improves through the combination of signals collected from multiple locations. Finally, we propose the optimal conditions for detecting objects in the NLOS area using acoustic signals.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.135-141
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• 2018

In this paper, we describe design and implementation of optimal smart home control system. Recent developments in technologies such as sensors and communication have enabled the Internet of Things to control a wide range of objects, such as light bulbs, socket-outlet, or clothing. Many businesses rely on the launch of collaborative services between them. However, traditional IoT systems often support a single protocol, although data is transmitted across multiple protocols for end-to-end devices. In addition, depending on the manufacturer of the Internet of things, there is a dedicated application and it has a high degree of complexity in registering and controlling different IoT devices for the internet of things. ARIoT system, special marking points and edge extraction techniques are used to detect objects, but there are relatively low deviations depending on the sampling data. The proposed system implements an IoT gateway of object based on OneM2M to compensate for existing problems. It supports diverse protocols of end to end devices and supported them with a single application. In addition, devices were learned by using deep learning in the artificial intelligence field and improved object recognition of existing systems by inference and detection, reducing the deviation of recognition rates.

• Journal of Aerospace System Engineering
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• v.16 no.1
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• pp.49-55
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• 2022

The role of drones has been expanded to various fields such as agriculture, construction, and logistics. In particular, agriculture drones are emerging as an effective alternative to solve the problem of labor shortage and reduce the input cost. In this study therefore, we proposed the fruit recognition algorithm and harvesting mechanism for fruit harvesting drone system that can safely harvest fruits at high positions. In the fruit recognition algorithm, we employ "You-Only-Look-Once" which is a deep learning-based object detection algorithm and verify its feasibility by establishing a virtual simulation environment. In addition, we propose the fruit harvesting mechanism which can be operated by a single driving motor. The rotational motion of the motor is converted into a linear motion by the scotch yoke, and the opened gripper moves forward, grips a fruit and rotates it for harvesting. The feasibility of the proposed mechanism is verified by performing Multi-body dynamics analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.245-247
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• 2022

Backscattered x-ray imaging is a technology capable of acquiring an image inside an irradiated object by measuring X-rays scattered from an object. For image acquisition, the system must include an X-ray generator and a detection system for measuring scattered x-rays. The imaging device must acquire a real-time signal at sampling intervals for x-rays generated by passing through a high-speed rotating collimator, and for this purpose, a high-speed signal acquisition device is required. We developed a high-speed multi-channel signal acquisition device for converting and transmitting signals generated by the sensor unit composed of a large-area plastic scintillator and a photomultiplier tube. The developed detector is a system capable of acquiring signals at intervals of at least 15u seconds and converting and transmitting signals of up to 6 channels. And a system includes remote control functions such as high voltage, signal gain, and low level discrimination for individual calibration of each sensor. Currently, we are conducting an application test for image acquisition under various conditions.

• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.611-619
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• 2010

This paper presents an efficient modeling system of virtual pottery in which the user can deform a body of virtual clay with a haptic tool for E-learning. We propose a Circular Sector Element Method (CSEM) which represents the virtual pottery with a set of circular sector elements based on the cylindrical symmetry of pottery. Efficient algorithms for collision detection and response, interactions between adjacent elements, and GPU-based visual-haptic synchronization are designed and implemented for the CSEM. Empirical evaluation showed that the modeling system is computationally efficient with finer details and provides convincing model deformation and force feedback. The developed system, if combined with educational contents, is expected to be used as an effective E-learning platform for elementary school students.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.12
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• pp.630-640
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• 2007

As the range of sensor network's applicability is getting wider, it creates new application areas which is required real-time operation, such as military and detection of radioactivity. However, existing researches are focused on effective management for resources, existing sensor network operating system cannot support to real-time areas. In this paper, we propose the ${\mu}TMO$ model which is lightweight real-time distributed object model TMO. We design the real-time sensor network operation system ${\mu}TMO-NanoQ+$ which is based on ETRI's sensor network operation system Nano-Q+. We modify the Nano-Q+'s timer module to support high resolution and apply Context Switch Threshold, Power Aware scheduling techniques to realize lightweight scheduler which is based on EDF. We also implement channel based communication way ITC-Channel and periodic thread management module WTMT.