• Proceedings of the Korean Fiber Society Conference
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• 1993.06b
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• pp.704-712
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• 1993

• Journal of radiological science and technology
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• v.13 no.1
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• pp.37-52
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• 1990

• Journal of Legislation Research
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• no.53
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• pp.269-310
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• 2017

This article aims at the study on Improvement of legal System which is related to automated vehicles in the era of the 4th industrial revolution. Legal aspects of driving automation have two view points. One is to permit a automated vehicle, the other is to regulate the behavior of driver on the road. Signifying elements of the 4th industrial revolution are IoT, AI, big data, cloud computing etc. Automated vehicles are the imbodiment of those new ICT technologies. The vehicle management act(VMA) rules about vehicle registration and approval of vehicle types. VMA defines a automated vehicle as a vehicle which can be self driven without handling of driver or passenger. Vehicle makers can take temporary driving permission for testing and research the driving automation. Current definition of automated vehicle of VMA is not enough for including all levels of SAE driving automation. In the VMA must be made also a new vehicle safty standard for automated vehicle. In the national assembly is curruntly pending three draft bills about legislation of artificial intelligence. Driving automation and AI technologies must be parallel developed. It is highly expected that more proceeding research of driving automation can be realized as soon as possible.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.2
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• pp.37-48
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• 2007

In order to become a mega hub port, major ports all over the world are making every effort to enhance their productivity through efficiency of internal operation and introduction of the state-of-the-art technologies. They are not only installing various kinds of high-technology equipments but also introducing advanced technologies for the development of an effective gate system. Recently thanks to the appearance of RFID (radio frequency identification) and OCR (optical character recognition) technology, major container terminals are stewing up the automation of truck and container identification at the container luminal gate. This study aim to develop an automated gate system for identification task based on RFID and OCR technology. It will make mn effective gate operations in a container terminal.

• Journal of Biomedical Engineering Research
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• v.38 no.3
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• pp.111-115
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• 2017

Blood pressure is one of the important vital signs for monitoring the medical condition of a patient. Automated NIBP(non-invasive blood pressure) monitoring devices calculate systolic and diastolic blood pressures from the oscillation in cuff pressure caused by a pulsation of an artery. To validate the NIBP devices, we developed a simulator to supply the oscillometric waveforms obtained from human subjects. The simulator provided pressure pulses to device-under-test and device readings were compared to the auscultatory references. Fully automated simulation system including OCR(optical character recognition) were developed and used for NIBP monitoring devices. The validation results using the simulator agreed well with previous clinical validation. More validation studies using the standardized oscillometric waveforms would be required for the replacement of clinical trials to validate a new automated NIBP monitoring device.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.232-249
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• 1998

The first Korean remote sensing satellite, Korea Multi-Purpose Satellite (KOMPSAT-1), is going to be launched in 1999. This will carry a 7m resolution Electro-Optical Camera (EOC) for earth observation. The primary mission of the KOMPSAT-1 is to acquire stereo imagery over the Korean peninsular for the generation of 1:25,000 scale cartographic maps. For this mission, research is being carried out to assess the possibilities of automated or semi-automated mapping of EOC data and to develop, if necessary, such enabling tools. This paper discusses the issue of automated digital elevation model (DEM) generation from EOC data and identifies some important aspects in developing a DEM generation system from EOC data. This paper also presents the current status of the development work for such a system. The development work will be described in three pares of sensor modelling, stereo matching and DEM interpolation. The performance of the system is shown with a SPOT stereo pair. A DEM generated from commercial software is also presented for comparison. The proposed system seems to generate promising results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4345-4363
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• 2021

Deep Learning as a Service (DLaaS), utilizing the cloud-based deep neural network models to provide customer prediction services, has been widely deployed on mobile cloud computing (MCC). Such services raise privacy concerns since customers need to send private data to untrusted service providers. In this paper, we devote ourselves to building an efficient protocol to classify users' images using the convolutional neural network (CNN) model trained and held by the server, while keeping both parties' data secure. Most previous solutions commonly employ homomorphic encryption schemes based on Ring Learning with Errors (RLWE) hardness or two-party secure computation protocols to achieve it. However, they have limitations on large communication overheads and costs in MCC. To address this issue, we present LeHE4SCNN, a scalable privacy-preserving and communication-efficient framework for CNN-based DLaaS. Firstly, we design a novel low-expansion rate homomorphic encryption scheme with packing and unpacking methods (LeHE). It supports fast homomorphic operations such as vector-matrix multiplication and addition. Then we propose a secure prediction framework for CNN. It employs the LeHE scheme to compute linear layers while exploiting the data shuffling technique to perform non-linear operations. Finally, we implement and evaluate LeHE4SCNN with various CNN models on a real-world dataset. Experimental results demonstrate the effectiveness and superiority of the LeHE4SCNN framework in terms of response time, usage cost, and communication overhead compared to the state-of-the-art methods in the mobile cloud computing environment.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.6
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• pp.370-376
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• 2016

Manufacturing data analysis and its applications are getting a huge popularity in various industries. In spite of the fast advancement in the big data analysis technology, however, the manufacturing quality data monitored from the automated inspection system sometimes is not reliable enough due to the complex patterns of product quality. In this study, thus, we aim to define the level of trusty of an automated quality inspection system and improve the reliability of the quality inspection data. By correlation analysis and feature selection, this paper presents a method of improving the inspection accuracy and efficiency in an SVM-based automatic product quality inspection system using thermal image data in an auto part manufacturing case. The proposed method is implemented in the sealer dispensing process of the automobile manufacturing and verified by the analysis of the optimal feature selection from the quality analysis results.

• Biomolecules & Therapeutics
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• v.19 no.1
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• pp.90-96
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• 2011

Automated HPLC/SPE/HPLC coupling experiments using the Sepbox system allowed the rapid identification of four bioactive principles reducing the production of amyloid $\beta$-peptide ($A{\beta}$) from two South African plants, Euclea crispa subsp. crispa and Crinum macowanii. The structures of biologically active compounds isolated from the methanol extract of Euclea crispa subsp. crispa were assigned as 3-oxo-oleanolic acid (1) and natalenone (2) based on their NMR and MS data, while lycorine (3) and hamayne (4) were isolated from the dichloromethane-methanol (1:1) extract of Crinum macowanii. These compounds were shown to inhibit the production of $A{\beta}$ from HeLa cells stably expressing Swedish mutant form of amyloid precursor protein (APPsw).

• Journal of the Society of Disaster Information
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• v.11 no.2
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• pp.269-278
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• 2015

Developed a service platform technology for automated that analyze the fire-fighting vulnerable area and equipped a map online. As a result, it is possible to provide the information necessary for the vulnerable area of the fire-fighting activity online. If progress on the study of the utilized service, it is possible to reduce the Golden Time of the fire fighting field. In this study, Confirmed the technical viability satisfactory to the management and service expansion improvements to fire-fighting vulnerable area.