• Journal of Radiation Industry
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• v.5 no.4
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• pp.313-316
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• 2011

[$^{18}F$]FDG (2-[$^{18}F$] Fluoro-2-deoxy-D-Glucose), which is required Automated Synthetic Module for production, is most often used Radiopharmaceuticals in nuclear medicine. In this study, an Automated Synthesis Module was developed to produce FDG in two consecutive time when F-18 feds continuously by modifying a domestic FDG Automated Synthetic Module on structural geometry and control system. The results were showed that the Average Synthesis Yields on the developed Automated Synthetic Module were $45{\pm}3%$ (n=20), $50{\pm}3%$ (n=20) respectively. The Quality Control results, such as Radio TLC, Radiochemical purity, Gamma-counter, pH, LAL Test, Micro bacteria test, showed in same level with domestic [$^{18}F$]FDG Auto-Synthetic modules. Therefore, if some features were improved by considering the components life time and appearance, commercial sales can be expected because of low price and easy maintenance compared with foreign products.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.2
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• pp.118-125
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• 2017

In this paper, we propose a smart transformer for a smart transformer miniature model, which can replace a 60 [Hz] single-phase transformer installed in an electric vehicle. The proposed smart transformer is lighter than a conventional transformer, can control instantaneous voltage, and can be expected to improve power quality through harmonic compensation. The proposed intelligent transformer consists of an incoming part, an AC/DC converter, and a dual active bridge. Only the incoming part and the AC/DC converter are described in this paper. The proposed intelligent transformer has 75 kVA 3.3 kV input and 750 V DC output, which are verified by simulation and experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.938-958
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• 2024

Unsupervised Video Object Segmentation (UVOS) is a highly challenging problem in computer vision as the annotation of the target object in the testing video is unknown at all. The main difficulty is to effectively handle the complicated and changeable motion state of the target object and the confusion of similar background objects in video sequence. In this paper, we propose a novel deep Dual-stream Co-enhanced Network (DC-Net) for UVOS via bidirectional motion cues refinement and multi-level feature aggregation, which can fully take advantage of motion cues and effectively integrate different level features to produce high-quality segmentation mask. DC-Net is a dual-stream architecture where the two streams are co-enhanced by each other. One is a motion stream with a Motion-cues Refine Module (MRM), which learns from bidirectional optical flow images and produces fine-grained and complete distinctive motion saliency map, and the other is an appearance stream with a Multi-level Feature Aggregation Module (MFAM) and a Context Attention Module (CAM) which are designed to integrate the different level features effectively. Specifically, the motion saliency map obtained by the motion stream is fused with each stage of the decoder in the appearance stream to improve the segmentation, and in turn the segmentation loss in the appearance stream feeds back into the motion stream to enhance the motion refinement. Experimental results on three datasets (Davis2016, VideoSD, SegTrack-v2) demonstrate that DC-Net has achieved comparable results with some state-of-the-art methods.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.6
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• pp.578-583
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• 2016

In this paper, we propose a multi-mode wireless power transfer (WPT) system with a dual loop structure. The proposed multi-mode WPT system consist of outer loop module which can operate at two different frequency bands including 6.78 MHz magnetic resonance WPT mode and 13.56 MHz near field communication (NFC) mode and inner loop module connected with outer loop which can operate at two different frequency bands including WPC mode and PMA mode based on inductive coupling standards. In order to be able to embed this system into smartphone battery back cover, the electrical designs are optimized and then the size was fixed $45{\times}90{\times}0.35mm3$ (including ferrite sheet) which is the same commercial smartphone. The proposed multi-mode WPT module can cover WPC and PMA mode based on inductive coupling. Moreover, it has more than 20 dB return loss characteristics at two different frequency bands including 6.78 MHz and 13.56 MHz, and shows more than 70 % transfer efficiency between resonant coils at 6.78 MHz in magnetic resonant charging environment.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.1
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• pp.95-102
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• 2018

This paper proposes a dual lifting and its cooperative control system with two different kinds of floating cranes. The Mega-erection and Giga-erection in the ship building are used to handle heavier and wider blocks and modules as ships and off-shore platforms are enlarged. However, there is no equipment to handle such Tera-blocks. In order to overcome the limit on performance of existing floating cranes, the dual lifting is proposed in this research. In the dual lifting, two floating cranes are well-coordinated to add up the lift capabilities of both cranes without any loss such that virtually a single crane is lifting, maneuvering and unloading. Two main constraints for the dual lifting are as follows: First, two barges of floating cranes should be constrained as a rigid body not to cause a relative motion between two barges and main hooks of the two cranes should be controlled as main hooks of a single crane. In order words, it is necessary to develop the cooperative control of two floating cranes in order to sustain a center of gravity of the module and minimize the tilting angle during the lifting and unloading by the two floating cranes. Two floating cranes are handled as a master-slave system. The master crane is able to gather information about all working conditions and make a decision to control the individual hook speed, which communicates the slave crane by TCP/IP. The developed control system has been embedded in the real floating crane systems and the dual lifting has been demonstrated five times at SHI shipyard in 2015. The moving angles of the lifting module are analyzed and verified to be suitable for hoisting control. It is verified that the dual lifting can be applied for many heavier and wider blocks and modules to shorten the construction time of ships and off-shore platforms.

• The Journal of Korea Robotics Society
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• v.12 no.4
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• pp.441-447
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• 2017

Robot arms are being increasingly used in various fields with special attention given to unmanned systems. In this research, we developed a high payload dual-arm robot, in which the forearm module is replaceable to meet the assigned task, such as object handling or lifting humans in a rescue operation. With each forearm module specialized for an assigned task (e.g. safety for rescue and redundant joints for object handling task), the robot can conduct various tasks more effectively than could be done previously. In this paper, the design of the high payload dual-arm robot with replaceable forearm function is described in detail. Two forearms are developed here. Each of forearm has quite a different goal. One of the forearms is specialized for human rescue in human familiar flat aspect and compliance parts. Other is for general heavy objects, more than 30 kg, handling with high degree of freedom more than 7.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.16-37
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• 2022

Accurate liver segment segmentation based on radiological images is indispensable for the preoperative analysis of liver tumor resection surgery. However, most of the existing segmentation methods are not feasible to be used directly for this task due to the challenge of exact edge prediction with some tiny and slender vessels as its clinical segmentation criterion. To address this problem, we propose a novel deep learning based segmentation model, called Boundary-Aware Dual Attention Liver Segment Segmentation Model (BADA). This model can improve the segmentation accuracy of liver segments with enhancing the edges including the vessels serving as segment boundaries. In our model, the dual gated attention is proposed, which composes of a spatial attention module and a semantic attention module. The spatial attention module enhances the weights of key edge regions by concerning about the salient intensity changes, while the semantic attention amplifies the contribution of filters that can extract more discriminative feature information by weighting the significant convolution channels. Simultaneously, we build a dataset of liver segments including 59 clinic cases with dynamically contrast enhanced MRI(Magnetic Resonance Imaging) of portal vein stage, which annotated by several professional radiologists. Comparing with several state-of-the-art methods and baseline segmentation methods, we achieve the best results on this clinic liver segment segmentation dataset, where Mean Dice, Mean Sensitivity and Mean Positive Predicted Value reach 89.01%, 87.71% and 90.67%, respectively.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.3
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• pp.177-184
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• 2017

High performance non-volatile memory system can mitigate the gap between main memory and storage. However, no single memory devices fulfill the requirements. Non-volatile Dual In-line Memory Module (NVDIMM) consisted of DRAMs and NAND Flashes has been proposed to achieve the performance and non-volatility simultaneously. When power outage occurs, data in DRAM is backed up into NAND Flash using a small-size external energy storage such as a supercapacitor. Backup and restore operations of NVDIMM do not cooperate with the operating system in the NVDIMM standard, thus there is room to optimize its operation. This paper analysis the operation of NVDIMM and proposes a method to reduce backup and restore time. Particularly, data compression is introduced to reduce the amount of data that to be backed up and restored. The simulation results show that the proposed method reduces up to 72.6% of backup and restore time.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.6
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• pp.62-68
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• 1983

We suggest a Quasi- dual graph model in consideration of dynamic module assignment and relocation to assign task optimally to two processors that have different processing abilities. An optimal module partitioning and allocation to minimize total processing cost can be achieved by applying shortest-path algorithm with time complexity 0(n2) on this graph model.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.501-503
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• 2013

This project presents a concept of mobile robots using prototypes, computing proposal oriented to embedded systems implementation. We implement our system using GPS module, Ultrasonic sensor(range sensors), H-bridge dual stepper control, DTMF(Dual-tone Multi-Frequency ) and LCD module. In this paper we construct a mechanical simple mobile robot model, which can measure the distance from obstacle with the aid of sensor and should able to control the speed of motor accordingly. Modules were interfaced with FPGA(Field Programmable Gate Array) controller for hardware implementation.