• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.3-11
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• 2013

In smart healthcare service, the accurate and prompt emergency detection and notification are very critical to patients' lives. Since these detection and notification of emergency situation are usually performed by the medical staffs, it is difficult to simultaneously support many patients in real-time. This article presents a methodology for emergency bio-data transmission for smart healthcare using personalized emergency policy. It consists of three steps: In step 1, the bio-data is collected by wireless body area network. In step 2, the decision on emergency is made using personalized emergency policy. In step 3, the emergency message including the health condition information is converted between IEEE 11073 PHD message and HL7 CDA. By doing this, the emergency status of the individual bio-data collected from wireless body area network is detected automatically using personalized emergency policy. When the emergency is detected, the quick emergency rescue service can be provided to the patient by delivering to the emergency notification and the emergency bio-data. We have verified the service and functions of the proposed system architecture by realizing it.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1655-1665
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• 2014

Dynamic displacements of structures shows general behavior of structures. Generally, It is used to estimate structure condition and trustworthy physical quantity directly. Especially, measuring vertical displacement which is affected by moving load is very important part to find or identify a problem of bridge in advance. However directly measuring vertical displacement of the bridge is difficult because of test conditions and restriction of measuring equipment. In this study, Artificial Neural Network (ANN) is used to suggest estimation method of bridge displacement to overcome constrain conditions, restriction and so on. Horizontal strain and vertical displacement which are measured by appling random moving load on the bridge are applied for learning and verification of ANN. Measured horizontal strain is used to learn ANN to estimate vertical displacement of the bridge. Numerical analysis is used to acquire learning data for axis strain and vertical displacement for applying ANN. Moving load scenario which is made by vehicle type and vehicle distance time using Pearson Type III distribution is applied to analysis modeling to reflect real traffic situation. Estimated vertical displacement in respect of horizontal strain according to learning result using ANN is compared with vertical displacement of experiment and it presents vertical displacement of experiment well.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.327-333
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• 2016

An autonomous vehicle is a convergence of artificial intelligence and a vehicle which can drive itself while analyzing the real-time situation on a road without a driver. A lot of research achievements have been revealed through the media and Google is considered to be the best leading company in this field. The use of patent information which contains various information such as bibliographic data and information about technologies is a good way to find out the R&D direction of a company and develop a reasonable strategy. This study is aimed at investigating the direction to which Google focuses its R&D capabilities and establishing strategies for technology development. Google's patents about autonomous vehicles were collected and the degree of research bias was analyzed using Social Network Analysis based on citations indicating the quality of a patent. Based on the results, the strategies for technology development was eventually proposed. As a result, it was revealed that Google focused its R&D capabilities on the part of hardware control to make up for its lack of hardware-oriented technologies. As of now, Google obtained remarkable achievements, so it seems reasonable that last-movers consider cooperative research with Google.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.278-281
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• 2018

The early Web technology was to show text information through a browser. However, as web technology advances, it is possible to show large amounts of multimedia data through browsers. Web technologies are being applied in a variety of fields such as sensor network, hardware control, and data collection and analysis for big data and AI services. As a result, the standard has been prepared for the Internet of Things, which typically controls a sensor via HTTP communication and provides information to users, by installing a web browser on the interface of the Internet of Things. In addition, the recent development of web-assembly enabled 3D objects, virtual/enhancing real-world content that could not be run in web browsers through a native language of C-class. Factors that evaluate the performance of existing Web applications include performance, network resources, and security. However, since there are many areas in which web applications are applied, it is time to revisit and review these factors. In this thesis, we will conduct an analysis of the factors that assess the performance of a web application. We intend to establish an indicator of the development of web-based applications by reviewing the analysis of each element, its main points, and its needs to be supplemented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1C
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• pp.1-7
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• 2012

At the industrial work site, the manufacturing process is being automated to improve work efficiency. However, it is often difficult to automate the entire manufacturing process, and there are spaces in which workers there are constantly exposed to danger. To protect such workers from the danger, this paper studied a worker safety management system for the industrial work site which uses a location recognition system and which is based on the Ubiquitous-Wireless Sensor Network (U-WSN). Using wireless signals, the distance between two devices can be measured and the location of a worker can be calculated using triangularization in 3-D. But at the industrial work sites where there are a lot of steel and structures, errors occur due to signal reflection and multi-path, etc., which makes it difficult to get the accurate location. To address this problem the following was done: first, a circular polarization patch antenna appropriate to the work site was used to reduce the degree of error that may occur from the antenna emission pattern and the particular Line of Sight (LOS); second, a 3-D localization technique and a filtering algorithm were used to improve the accuracy of location determination. The developed system was tested by using it on a wharf crane to validate its accuracy and effectiveness. The proposed location recognition system is expected to contribute greatly in ensuring the safety of workers at industrial work sites.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.954-961
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• 2010

Stream cipher was worse than block cipher in terms of security, but faster in execution speed as an advantage. However, since so far there have been many algorithm researches about the execution speed of block cipher, these days, there is almost no difference between them in the execution speed of AES. Therefore an secure and fast stream cipher development is urgently needed. In this paper, we propose a 32bit output fast stream cipher, AA32, which is composed of ASR(Arithmetic Shifter Register) and simple logical operation. Proposed algorithm is a cipher algorithm which has been designed to be implemented by software easily. AA32 supports 128bit key and executes operations by word and byte unit. As Linear Feedback Sequencer, ASR 151bit is applied to AA32 and the reduction function is a very simple structure stream cipher, which consists of two major parts, using simple logical operations, instead of S-Box for a non-linear operation. The proposed stream cipher AA32 shows the result that it is faster than SSC2 and Salsa20 and satisfied with the security required for these days. Proposed cipher algorithm is a fast stream cipher algorithm which can be used in the field which requires wireless internet environment such as mobile phone system and real-time processing such as DRM(Digital Right Management) and limited computational environments such as WSN(Wireless Sensor Network).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.149-158
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• 2005

This paper proposed a blind watermarking method for video contents which satisfies both the invisibility and the robustness to attacks to prohibit counterfeiting, modification, illegal usage and illegal re-production of video contents. This watermarking algorithm targets MPEG compression system and was designed to control the amount of watermarking to be inserted according to the adaptive quantization scale code to follow the adaptive quantization of the compression system. The inserting positions of the watermark were chosen by considering the frequency property of an image and horizontal, vertical and diagonal property of a $8{\times}8$ image block. Also the amount of watermarking for each watermark bit was decided by considering the quantization step. This algorithm was implemented by C++ and experimented for invisibility and robustness with MPEG-2 system. The experiment results showed that the method satisfied enough the invisibility of the inserted watermark and robustness against attacks. For the general attacks, the error rate of the extracted watermark was less than $10\%$, which is enough in robustness against the attacks. Therefore, this algorithm is expected to be used effectively as a part in many MPEG systems for real-time watermarking, especially in the sensitive applications to the network environments.

• Journal of IKEEE
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• v.21 no.4
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• pp.388-396
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• 2017

Since there are many variables such as various poses, illuminations and occlusions in a face detection problem, a high performance detection system is required. Although CNN is excellent in image classification, CNN operatioin requires high-performance hardware resources. But low cost low power environments are essential for small and mobile systems. So in this paper, the CPU-FPGA integrated system is designed based on 3-stage cascade CNN architecture using small size FPGA. Adaptive Region of Interest (ROI) is applied to reduce the number of CNN operations using face information of the previous frame. We use a Field Programmable Gate Array(FPGA) to accelerate the CNN computations. The accelerator reads multiple featuremap at once on the FPGA and performs a Multiply-Accumulate (MAC) operation in parallel for convolution operation. The system is implemented on Altera Cyclone V FPGA in which ARM Cortex A-9 and on-chip SRAM are embedded. The system runs at 30FPS with HD resolution input images. The CPU-FPGA integrated system showed 8.5 times of the power efficiency compared to systems using CPU only.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.353-360
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• 2015

The offshore oil production requires a huge amount of cost and time accompanied by multiple variables due to the peculiar nature of 'offshore'. And every process concerned is controlled by elaborate series of plans for reducing loss of lives, environment and property. This paper treats an optimization problem for offshore oil production and transportation. We present an offshore production and transportation network to define scope of the problem and construct a mixed integer linear programming model to tackle it. To demonstrate the validity of the optimization model presented, some computational experiments based on hypothetical offshore oil fields and demand markets are carried out by using MS Office Excel solver. The downstream of the offshore production and transportation network ends up with the maritime transportation problem distributing the crude oil produced from offshore fields to demand markets. We used MoDiSS(Model-based DSS in Ship Scheduling) which was built to resolve this maritime transportation problem. The paper concludes with the remark that the results of the study might be meaningfully applicable to the real world problems of offshore oil production and transportation.

• The KIPS Transactions:PartA
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• v.12A no.6 s.96
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• pp.557-562
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• 2005

Throughput and latency of interconnection network are important factors of the performance of multiprocessor systems. The dual-link CC-NUMA architecture using point-to-point unidirectional link is one of the popular structures in high-end commercial systems. In terms of optimal path between nodes, several paths exist with the optimal hop count by its native multi-path structure. Furthermore, transaction latency between nodes is affected by congestion of links on the transaction path. Hence the transaction latency may get worse if the transactions make a hot spot on some links. In this paper, I propose a dynamic transaction routing algorithm that maintains the balanced link utilization with the optimal path length, and I compare the performance with the fixed path method on the dual-link CC-NUMA systems. By the proposed method, the link competition is alleviated by the real-time path selection, and consequently, dynamic transaction algorithm shows a better performance. The program-driven simulation results show $1{\~}10\%$ improved fluctuation of link utilization, $1{\~}3\%$ enhanced acquirement of link, and $1{\~}6\%$ improved system performance.