• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.125-130
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• 2011

This paper investigates the possibility of exploiting haptic force-feedback technology for interacting with Nanta music. We use VR technologies including touch processing technologies and haptic devices to offer touch of cylinder objects and cup object to users. Haptic device is used to implement touch model in VR space. Matlab/Simulink and proSENCE Virtual Touch Toolbox of Handshake Inc. for experiment, are used as programing tools. Function needed to describe the movement of x, y, and z axis respectively are applied to delineate the natural movement of water in cup object modeled with 3D. A certain amount of water in cup object has the difference of sounds. In experiment, to perceive the appearance of 3D object by touch and to feel the tactile by touch are conducted with the effect of sound on Haptic perception. We also verify that it is possible to develop games or contents in VR space by using point.

• The KIPS Transactions:PartD
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• v.16D no.4
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• pp.527-540
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• 2009

State diagrams describe the dynamic behavior of an individual object as a number of states and transitions between these states. In this paper, we propose an automated technique to the generation of a state diagram from class operations with pre/post conditions. And I also develop a supporting tool, SDAG (State Diagram Automatic Generation tool). Additionally, we propose a complexity metric and a state diagram generation approach concerning types of each operation for decreasing complexity of generated state diagram.

• Electronics and Telecommunications Trends
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• v.33 no.4
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• pp.23-32
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• 2018

Object detection is a challenging field in the visual understanding research area, detecting objects in visual scenes, and the location of such objects. It has recently been applied in various fields such as autonomous driving, image surveillance, and face recognition. In traditional methods of object detection, handcrafted features have been designed for overcoming various visual environments; however, they have a trade-off issue between accuracy and computational efficiency. Deep learning is a revolutionary paradigm in the machine-learning field. In addition, because deep-learning-based methods, particularly convolutional neural networks (CNNs), have outperformed conventional methods in terms of object detection, they have been studied in recent years. In this article, we provide a brief descriptive summary of several recent deep-learning methods for object detection and deep learning architectures. We also compare the performance of these methods and present a research guide of the object detection field.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.839-846
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• 2016

Bin picking is a task of picking a small object from a bin. For accurate bin picking, the 3D pose information, position, and orientation of a small object is required because the object is mixed with other objects of the same type in the bin. Using this 3D pose information, a robotic gripper can pick an object using exact distance and orientation measurements. In this paper, we propose a 3D vision technique for accurate measurement of 3D position and orientation of small objects, on which a paper label is stuck to the surface. We use a maximally stable extremal regions (MSERs) algorithm to detect the label areas in a left bin image acquired from a stereo camera. In each label area, image features are detected and their correlation with a right image is determined by a stereo vision technique. Then, the 3D position and orientation of the objects are measured accurately using a transformation from the camera coordinate system to the new label coordinate system. For stable measurement during a bin picking task, the pose information is filtered by averaging at fixed time intervals. Our experimental results indicate that the proposed technique yields pose accuracy between 0.4~0.5mm in positional measurements and $0.2-0.6^{\circ}$ in angle measurements.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.6-9
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• 2021

The 3D industry is drawing attention for its applications in various markets, including architecture, media, VR/AR, metaverse, imperial broadcast, and etc.. The current feature of the architecture we are introducing is to make 3D models more easily created and modified than conventional ones. Existing methods for generating 3D models mainly obtain values using specialized equipment such as RGB-D cameras and Lidar cameras, through which 3D models are constructed and used. This requires the purchase of equipment and allows the generated 3D model to be verified by the computer. However, our framework allows users to collect data in an easier and cheaper manner using cell phone cameras instead of specialized equipment, and uses 2D data to proceed with 3D modeling on the server and output it to cell phone application screens. This gives users a more accessible environment. In addition, in the 3D modeling process, object classification is attempted through deep learning without user intervention, and mesh and texture suitable for the object can be applied to obtain a lively 3D model. It also allows users to modify mesh and texture through requests, allowing them to obtain sophisticated 3D models.

• Journal of Sensor Science and Technology
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• v.10 no.6
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• pp.286-294
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• 2001

In this study, 3-D underwater object recognition using the self-made 3-3 type composite ultrasonic transducer and modified SOFM(Self Organizing Feature Map) neural network are investigated. Properties of the self-made 3-3 type composite specimens are satisfied considerably with requirements as an underwater ultrasonic transducer's materials. 3-D underwater all object's recognition rates obtained from both the training data and testing data in different objects, such as a rectangular block, regular triangular block, square block and cylinderical block, were 100% and 94.0%, respectively. All object's recognition rates are obtained by utilizing the self-made 3-3 type composite transducer and SOFM neural network. From the object recognition rates, it could be seen that an ultrasonic transducer fabricated with the self-made 3-3 type composite resonator will be able to have application for the underwater object recognition.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.4 s.181
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• pp.183-190
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• 2006

Digital 3D Real Object Duplication System (RODS) consists of 3D Scanner and Solid Freeform Fabrication System (SFFS). It is a device to make three-dimensional objects directly from the drawing or the scanning data. In this research, we developed an office type SFFS based on Three Dimensional Printing Process and an industrial SFFS using Dual Laser. An office type SFFS applied sliding mode control with sliding perturbation observer (SMCSPO) algorithm for control of this system. And we measured process variables about droplet diameter measurement and powder bed formation etc. through experiments. In case of industrial type SFFS, in order to develop more elaborate and speedy system for large objects than existing SLS process, this study applies a new Selective Dual-Laser Sintering (SDLS) process and 3-axis Dynamic Focusing Scanner for scanning large area instead of the existing f lens. In this process, the temperature has a great influence on sintering of the polymer. Also the laser parameters are considered like that laser beam power, scan speed, and scan spacing. Now, this study is in progress to evaluate the effect of experimental parameters on the sintering process.

• Ceramist
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• v.23 no.1
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• pp.27-37
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• 2020

Recently, 4D printing technology has received considerable attention in various industries and research fields including soft robotics, tissue engineering, electronics. In 4D printing process, 3D printed object transforms itself into programmed structure by the input of external energy. Thus, this process requires not only smart materials, capable of changing their properties or features in response to external stimuli such as electricity, temperature, light, etc., but also smart structures, multi-material 3D printing, simulation and so on. In this review, the concept, technical elements and potential of 4d printing are presented.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.139-142
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• 2008

Construction Management by using 4D CAD system analyzes operations information based on 3D and 4D objects. But it is difficult to provide a variety of documents linked by 4D objects in a lump from 4D CAD system based on visual object, and to get an optimal decision-making information to conduct business. Therefore, it is necessary to construct effective construction information management systems and to organize integrated information through linking non-objects to objects. This study suggests methodologies of effective construction management for railway facilities through building of framework for practical application and methodologies to link 4D objects to IETM documents. Accordingly, it is possible to establish a systematic decision-making for an effective construction management of railway facilities, and this provide integrated methodology for linking non-objects to objects.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.494-499
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• 2012

In this paper, a new method for detecting various objects that can be risks to safety navigation in sea environment is proposed. By analysing Infrared(IR) images obtained from various sea environments, we could find out that object regions include both horizontal and vertical direction edges while background regions of sea surface mainly include vertical direction edges. Therefore, we present an approach to detecting object regions considering horizontal and vertical edges. To this end, in the first step, image enhancement is performed by suppressing noises such as sea glint and complex clutters using a statistical filter. In the second step, a horizontal edge map and a vertical edge map are generated by 1-D Discrete Cosine Transform technique. Then, a combined map integrating the horizontal and the vertical edge maps is generated. In the third step, candidate object regions are detected by a adaptive thresholding method. Finally, exact object regions are extracted by eliminating background and clutter regions based on morphological operation.