• Transactions of the Korean Society of Automotive Engineers
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• v.25 no.2
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• pp.219-226
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• 2017

This paper addresses the effective and quantitative image DB construction for the development of front looking camera systems. The automotive industry has expanded the capability of front camera solutions that will help ADAS(Advanced Driver Assistance System) applications targeting Euro NCAP function requirements. These safety functions include AEB(Autonomous Emergency Braking), TSR(Traffic Signal Recognition), LDW(Lane Departure Warning) and FCW(Forward Collision Warning). In order to guarantee real road safety performance, the driving image DB logged under various real road conditions should be used to train core object classifiers and verify the function performance of the camera system. However, the driving image DB would entail an invalid and time consuming task without proper guidelines. The standard working procedures and design factors required for each step to build an effective image DB for reliable automotive front looking camera systems are proposed.

• Journal of Korea Multimedia Society
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• v.24 no.7
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• pp.860-867
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• 2021

Lane detection is important technology for implementing ADAS or autonomous driving. Although edge detection has been typically used for the lane detection however, false detections occur frequently. To improve this problem, a deep learning based lane detection algorithm is proposed in this paper. This algorithm is mounted on an ARM-based embedded system to implement a LDW(lane departure warning). Since the embedded environment lacks computing power, the VGG-11, a lightweight model based on VGG-13, has been proposed. In order to evaluate the performance of the LDW, the test was conducted according to the test scenario of NHTSA.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.172-177
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• 2021

The HUD (Head-up Display) device for vehicles has gradually been advanced in connection with ADAS (Advanced Driver Assistant System) for the safety and the convenience of driving. In this paper, the major features (e.g. speed, RPM, etc.) of vehicles is received through the ECU and the route information is received through the navigating API, configurating the integrated GUI. And, the optical system is configured based on DLP (Digital Light Processing) to evaluate the visibility depending on the resolution change of the GUI. The IoT HUD system proposed in this paper has the scalability to flexibly add not only the ECU but also various cloud-based driving-related information.

• Journal of Auto-vehicle Safety Association
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• v.9 no.1
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• pp.6-12
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• 2017

Regulation for the testing and operation of automated vehicles on public roadways has been recently developed all over the world. For example, the licensing standards and the evaluation technology for automated vehicles have been proposed in California, Nevada and EU. But specific safety evaluation scenarios for automated vehicles have not been proposed yet. This paper presents safety evaluation scenarios for extraordinary service permission of automated vehicles on highways. A total of seven scenarios are selected in consideration of safety priority and real traffic situation. Six scenarios are relevant with lane keeping and one scenario is relevant with lane change. All scenarios are developed based on existing ADAS evaluation scenarios and repeated simulation of automated vehicle algorithm. Safety evaluation factors as well as scenarios are developed. The safety factors are based on existing ADAS ISO requirements, ADAS safety factors and current traffic regulations. For the scenarios, a hunter vehicle is needed in addition to automated vehicle evaluated. The hunter vehicle performs multiple roles like preceding vehicle, cut-in vehicle and so on. The hunter vehicle is also automated vehicle equipped with high performance GPS, radar and Lidar. All the scenarios can be implemented by driving a lap on a KATRI ITS test track. These scenarios and safety evaluation factors are investigated via both a computer simulation and an experimental vehicle test on the test track. The experimental vehicle test was conducted with two automated vehicles, which are the evaluated vehicle and the hunter vehicle.

• Journal of IKEEE
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• v.20 no.4
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• pp.351-360
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• 2016

Recently, machine learning algorithms, especially deep learning-based algorithms, have been receiving attention due to its high classification performance. Among the algorithms, Convolutional Neural Network(CNN) is known to be efficient for image processing tasks used for Advanced Driver Assistance Systems(ADAS). However, it is difficult to achieve real-time processing for CNN in vehicle embedded software environment due to the repeated operations contained in each layer of CNN. In this paper, we propose a hardware accelerator which enhances the execution time of CNN by parallelizing the repeated operations such as convolution. Xilinx ZC706 evaluation board is used to verify the performance of the proposed accelerator. For $36{\times}36$ input images, the hardware execution time of CNN is 2.812ms in 100MHz clock frequency and shows that our hardware can be executed in real-time.

• Journal of Life Science
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• v.9 no.2
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• pp.9-14
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• 1999

Pseudomonas iodinum IFO 3558 adenosine deaminase(ADA) gene was cloned by the polymerase chain reaction and deduced the amino acid sequence of the enzyme. DNA sequence homology of Pseudomonas iodinum IFO 3558 ADA gene was compared to those of E. coli, human and mouse ADA genes. Unambiguous sequence from both strands of pM21 was obtained for the region believed to encode ADA. The sequence included a 804-nucleotide open reading frame, bounded on one end by sense primer and on the other end by two antisense primer. This open reading frame encodes a protein of 268 amino acids having a molecular weight of 29,448. The deduced amino acid sequence shows considerable similarity to those of E. coli, mouse and human ADA. Pseudomonas iodinum IFO 3558 nucleotide sequence shows 98.5% homology with that of the E. coli ADA sequence and 51.7% homology with that of the mouse ADA sequence and 52.5% homology with that of the human ADA sequence. The ADA protein sequence of Pseudomonas iodinum IFO 3558 shows 96.9% homology with that of the E. coli and 40.7% homology with that of the mouse and 41.8% homology with that of the human. The distance between two of the conserved elements, TVHAGE and SL(1)NTDDP has veen exactly conserved at 76 amino acids for all four ADAs. Two of the four conserved sequence elements shared among the four ADAs are also present in the yeast, rat, human (M), and Human(L) AMP deaminase. The SLSTDDP sequence differs only in the conservative substitution of a serine for an asparagine. A conserved cysteine with conserved spacing between these two regions is also found. Thus, sequence analysis of four ADAs and four AMP deaminases revealed the presence of a highly conserved sequence motif, SLN(S)TDDP, a conserved dipeptide, HA, and a conserved cysteine residue.

• Journal of IKEEE
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• v.20 no.3
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• pp.241-250
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• 2016

AVM(Around View Monitoring) is a function of ADAS(Advanced Driver Assistance Systems), which provides a bird's eye view of the surroundings of a vehicle to the user. AVM systems require large bandwidth since they are composed of four input images and require real-time processing for vehicle-embedded environments. Also, the memory bandwidth requirement increases greatly when the resolution of the input data is higher. In this paper, we propose four basic hardware models of AVM systems. The models are decided by whether or not there is a valid data extraction module and an image processing purpose LUT generation module. We analyze the required bandwidth and hardware resource for each model. For verification of the proposed models, we implemented an AVM system using XC7Z045 FPGA and DDR3 memory for VGA and FHD resolution. All four of the proposed hardware model is executed below 33ms, which shows that it can operate in real-time.

• Journal of IKEEE
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• v.21 no.4
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• pp.358-367
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• 2017

Advanced Driver Assistance Systems(ADAS), such as Front Collision Warning System (FCWS) are currently being developed. FCWS require high processing speed because it must operate in real time while driving. In addition, a low-power system is required to operate in an automobile embedded system. In this paper, FCWS is implemented in CPU-FPGA architecture in embedded system to enable real-time processing. The lane detection enabled the use of the Inverse Transform Perspective (IPM) and sliding window methods to operate at fast speed. To detect the vehicle, a Convolutional Neural Network (CNN) with high recognition rate and accelerated by parallel processing in FPGA is used. The proposed architecture was verified using Intel FPGA Cyclone V SoC(System on Chip) with ARM-Core A9 which operates in low power and on-board FPGA. The performance of FCWS in HD resolution is 44FPS, which is real time, and energy efficiency is about 3.33 times higher than that of high performance PC enviroment.

• Journal of Auto-vehicle Safety Association
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• v.13 no.3
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• pp.78-85
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• 2021

Recently a traffic accident of heavy duty vehicles under the mandatory installation of ADAS (Advanced Driver Assistance System) is often reported in the media. Heavy duty vehicle accidents are normally occurring a high number of passenger's injury. According to report of Insurance Institute for Highway Safety, FCW (Forward Collision Warning) and AEB (Automatic Emergency Braking) were associated with a statistically significant 12% reduction in the rate of police-reportable crashes per vehicle miles traveled, and a significant 41% reduction in the rear-end crash rate of large trucks. Also many countries around the world, including Korea, are studying the effects of ADAS installation on accident reduction. Traffic accident statistics of passenger vehicle for business purpose in TMACS (Traffic safety information Management Complex System in Korea) tends to remarkably reduce the number of deaths due to the accident (2017(211), 2018(170), 2019(139)), but the number of traffic accidents (2017(8,939), 2018(9,181), 2019(10,095)) increases. In this paper, it is introduced a traffic accident case that could lead to high injury traffic accidents by being equipped with AEB in a bus. AEB reduces accidents and damage in general but malfunction of AEB could occur severe accident. Therefore, proper education is required to use AEB system, simply instead of focusing on developing and installing AEB to prevent traffic accidents. Traffic accident of AEB equipped vehicle may arise a new dispute between a driver's fault and vehicle defect. It is highly recommended to regulate an advanced event data recorder system.

• Korean Journal of Clinical Pharmacy
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• v.33 no.4
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• pp.290-304
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• 2023

Background: Innovative Alzheimer's disease drugs received approval in the United States in 2021 and 2023. This study aims to assess the safety and efficacy of these novel treatments, elucidate their mechanisms of action, and compare their impact on cognitive function improvement with approved drugs. Methods: We conducted a comprehensive search of pivotal clinical studies related to Alzheimer's disease treatments in PubMed/Medline, Embase, and the Cochrane Library databases from January 1st, 2020 to December 31st, 2022. Meta-analysis was performed using RevMan 5.4 software. Results: A total of 14 studies were included in this systematic review. When compared to the placebo, the new drugs did not exhibit a statistically significant effect on MMSE (Mini-Mental State Examination) (mean difference= -0.04, 95% confidence intervals [CIs]: -0.31, 0.23, N=3662, I²=0%). However, they demonstrated a significant impact on ADAS-cog (Alzheimer's Disease Assessment Scale-Cognitive Subscale) (standardized mean difference= -0.15, 95% CIs: -0.2, -0.1, N=6710, I²=17%). When compared to the approved drugs, the new drugs showed a statistically significantly lower effect on MMSE (test for subgroup difference Chi²=23.13, N = 5870, p<0.00001) but showed only a trend of decreased efficacy on ADAS-cog (Chi²=1.16, N = 8670, p=0.28). Conclusion: New drugs yielded diverse clinical endpoint results compared to the placebo, and in comparison to existing approved drugs, they exhibited lower efficacy in improving cognitive function. The safety profile of these new drugs, as reported in clinical trials, was generally well-tolerated.