• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.26 no.2
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• pp.61-69
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• 2020

As post-harvest processes of onions are carried by a 20 kg-net package which results in high-cost and low-efficiency, especially, the insufficient drying and physical damage of onions after harvesting leads to a huge second loss in storage, we had developed a low-cost, high-efficiency post-harvest bulk handling machinery system by collecting onions on a farm using ton-bags, drying with forced air circulation, and sorting/packaging. The post-harvest bulk handling machinery system consisted of 6 devices, and this study designed an automatic feed hopper with a feeding rate control device, an inclined belt conveyor with a two-step chute, and an automatic pallet unloading device for feeding onions into the sorting/packing line. This study also analyzed the performance and control of the total system. The device had 1-ton handling capacity, but the operational condition was set to increase the capacity. The three-step filling method of pallet by the velocity control of the inclined belt conveyor was applied in the post-harvest bulk handling machinery system for the prevention of physical damage. If one worker was set to operate the total system, the time required to complete one palletized load was approximately 5 minutes and 5 seconds. The calculated daily handling capacity was approximately 94 tons, when the daily actual working time was 8 hours. When the developed system was applied to the managerial size of 2,000 ton, the processing cost per ton of the system was decreased by 19.5%, compared with the existing 20 kg-net package-based handling. The developed post-harvest bulk handling machinery system would be a good substitute for the rapid decline and aging of rural labor.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.1
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• pp.25-31
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• 2003

This paper addresses an oil supply enhancement device to resolve a shortage of oil supply or no oil supply at all encountered at low speed operation for a variable speed reciprocating compressor used for household refrigerators. The oil supply enhancement device comprises a moving cylinder attached to the lower end of crankshaft and two of fluid diodes, each one at the inlet and outlet of the cylinder. Up-and-down movement of the cylinder against the lower end of the crankshaft together with the functioning of the two fluid diodes produces net oil flow from oil reservoir to inside the crankshaft. The experiment on the test bench has shown that enough oil supply into the oil feeding hole cu be made by using this device even at low speed range. Some analytical study has also been carried out to under-stand its oil supply mechanism.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.10 no.2
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• pp.62-67
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• 2011

Embedded device that can support mobile computing environment has been popular recently. In this study, we propose a new robot application based on embedded device to control a mobile robot using a touch-based remote interface with information display of robot trajectory and sensors. We developed the robot application using Microsoft's.Net Compact Framework and Zigbee data communication with Windows CE kernel based embedded device. In experiment, we evaluated the feasibility and the effectiveness of the proposed system by showing a remote robot control using touch interface and a information display of the robot.

• KIISE Transactions on Computing Practices
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• v.23 no.7
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• pp.417-423
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• 2017

Recently, many embedded devices that have the computing capability required for deep learning have become available; hence, many new applications using these devices are emerging. However, these embedded devices have an architecture different from that of PCs and high-performance servers. In this paper, we propose a method that improves the performance of deep-learning framework by considering the architecture of an embedded device that shares memory between the CPU and the GPU. The proposed method is implemented in Caffe, an open-source deep-learning framework, and is evaluated on an NVIDIA Jetson TK1 embedded device. In the experiment, we investigate the image recognition performance of several state-of-the-art deep-learning networks, including AlexNet, VGGNet, and GoogLeNet. Our results show that the proposed method can achieve significant performance gain. For instance, in AlexNet, we could reduce image recognition latency by about 33% and energy consumption by about 50%.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.28 no.4
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• pp.360-370
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• 1992

In order to analyse the mesh selectivity for the trawl net, the fishing experiment was carried out by the training ship Saebada belonging to the National Fisheries University, in the Southern Korea Sea and the East China Sea from June 1991 to August 1992. The trawl net used in the experiment has the trouser type of cod-end with cover net and the mesh selectivity in the cod-end part. In this report, the species of fishes caught and the catch rate for them in accordance with different mesh sizes were analysed, and the result obtained are summarized as follows: 1) 145 species of aquatic animals were caught in totally 138 times of trawl operations. 2) The number of species mostly not to escape are 28, 22, 19, 16 and 11 respectively, in each opening mesh size, 51.2mm, 70.2mm, 77.6mm, 88.0mm and 111.3mm of cod-end. 3) In view that the use of the opening mesh size above 54mm in cod-end of trawl net in Korea, it is necessary to device a counterplan against the overfishing, for the 22 species of aquatic animals mostly not to escape in the cod-end of the large mesh sizes more than 70.2mm.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2606-2613
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• 2022

Spent resin often exceeds radiation limits for safe disposal, creating a need for commercial-scale treatment techniques to reduce resin radioactivity. In this study, the radiological safety of a commercialized spent resin treatment device with a treatment capacity of 1 ton/day was evaluated. The results confirm that the device is radiologically safe in the event of an accident. This device desorbs ¹⁴C from the spent resin, allowing disposal as low-level waste instead of intermediate-level waste. The device also reduces overall waste by recycling the extracted ¹⁴C. Potential accident scenarios were explored to enable dose assessments for both internal and external exposure while preventing further spillage of the device and processing the spilled resin. The scenarios involved the development of a surface fracture on the resin mixture separator and microwave systems, which were operated under pressure and temperature of 0-6 bar and 0-150 ℃, respectively. In the case of accidents with separator and microwave device, the maximum allowable working time of worker were derived, respectively, considering external and internal exposures. When wearing the respirator corresponding to APF 50, in the case of the microwave device accident scenario, the radiological safety was confirmed when the maximum worker worked within 132.1 h.

• JSTS:Journal of Semiconductor Technology and Science
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• v.5 no.2
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• pp.136-147
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• 2005

A theoretical design evaluation based on a hydrodynamic transport simulation of strained Si-SiGe on insulator (SSOI) type nMOSFETs is reported. Although, the net performance improvement is quite limited by the short channel effects, simulation results clearly show that the strained Si-SiGe type nMOSFETs are well-suited for gate lengths down to 20 nm. Simulation results show that the improvement in the transconductance with decreasing gate length is limited by the long-range Coulomb scattering. An influence of lateral and vertical diffusion of shallow dopants in the source/drain extension regions on the device performance (i.e., threshold voltage shift, subthreshold slope, current drivability and transconductance) is quantitatively assessed. An optimum layer thickness ($t_{si}$ of 5 and $t_{sg}$ of 10 nm) with shallow Junction depth (5-10 nm) and controlled lateral diffusion with steep doping gradient is needed to realize the sub-50 nm gate strained Si-SiGe type nMOSFETs.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.191-194
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• 1999

Switching behaviour of the ferroelectric thin film and device characteristics of the MFSFET (Metal-Ferroelectric-Semiconductor FET) are simulated with taking into account the accumulation of oxygen vacancies near interface between the ferroelectric thin film and the bottom electrode caused by the progress of fatigue. We show net switching current decreases due fatigue in the switching model. It indicates that oxygen vacancy strongly suppresses polarization reversal. The difference of saturation drain current of the device before fatigue is shown by the dual threshold voltages in I$_{D}$-V$_{D}$ curve as 6㎃/$\textrm{cm}^2$ and decreases as much as 50% after fatigue. Our simulation model is expected to play an important role in estimation of the behavior of MFSFET device with various ferroelectric thin films.lms.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.3114-3120
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• 2023

A high-accuracy magnetic field measurement device based on a cyclotron is being developed for accelerator mass spectrometry (AMS). In this study, a magnetic field measurement device consisting of a Hall probe sensor, piezo-motor, and step motor was developed to measure the magnetic field of the AMS cyclotron magnet. The Hall probe sensor was calibrated to achieve positional accuracy by using polar coordinates. The measurement results between the ratchet gear and piezo-motor, which are the instruments used for driving the measurement device, were analyzed. The measurement result of the device with a piezo-motor exhibits a difference of 5 Gauss (0.04%) as compared with the simulation result.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1165-1171
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• 2018

CNN requires a large amount of computation and memory in the process of extracting the feature of the object. Also, It is trained from the network that the user has configured, and because the structure of the network is fixed, it can not be modified during training and it is also difficult to use it in a mobile device with low computing power. To solve these problems, we apply a pruning method to the pre-trained weight file to reduce computation and memory requirements. This method consists of three steps. First, all the weights of the pre-trained network file are retrieved for each layer. Second, take an absolute value for the weight of each layer and obtain the average. After setting the average to a threshold, remove the weight below the threshold. Finally, the network file applied the pruning method is re-trained. We experimented with LeNet-5 and AlexNet, achieved 31x on LeNet-5 and 12x on AlexNet.