• Korean Journal of Adult Nursing
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• v.27 no.4
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• pp.449-458
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• 2015

Purpose: The aims of this study were to identify the reported attitudes of older patients with cancer toward advance directives (ADs) and the factors associated with their attitudes toward ADs. Methods: The design was a cross-sectional survey. The age mean of the 130 participants were 70.8, and 66.2% of the participants were male. The data were collected at one university hospital in Seoul, South Korea during the period from October $1^{st}$ to December $5^{th}$ in 2013. The data collecting instruments were the Advance Directives Attitude Survey (ADAS) and questionnaires including socio-demographic and disease-related characteristics, family function. Results: 30.0% of the participants were aware of ADs, only 9% of them had been informed by healthcare providers. Most participants (93.1%) intended to complete ADs. The mean score of ADAS was 48.29. The stepwise linear regression analysis indicated that family function, perceived health status, period of education, and age accounted for a significant percentage (52.0%, p<.001) of the variance in participants' ADAS. The variable with the greatest effect was family function. Conclusion: The findings suggest that family function and attitude of older cancer patients need to be considered for adapting ADs to Korean health care systems. Healthcare providers should include family members in advanced care planning discussions.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.7-13
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• 2020

We describes V2X technology, a connectivity-based recognition technology that is attracting attention as a key technology for implementing autonomous driving technology, and autonomous communication modules that implement ADAS technology, a sensor-based recognition technology. It also explains the trends in V2X technology standardization centered on IEEE 802.11p, which is a WAVE technology standard based on Wi-Fi/DSRC. Finally, we will discuss the market growth trend of V2X communication modules in the United States, the leading V2X technology module, and the development of technology development trends of major domestic and international companies that are leading the global technology market related to V2X communication modules. V2X and ADAS technologies will be the biggest influence on automotive purchasing decisions. In recent years, V2I mandates have been promoted beyond V2V, mainly in developed countries such as the United States. The related industry needs to focus on the development of information transmission network technology that can support high frequency high efficiency(transmission rate) and sophisticated positioning accuracy beyond conventional vehicle communication.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1002-1015
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• 2018

The advent of Internet of Things (IoT) and the evident inadequacy of Cloud networks concerning management of numerous end nodes have brought about a shift of paradigm giving birth to Fog computing. Fog computing is an extension of Cloud computing that extends Cloud resources at the edge of the network, closer to the user. Cloud computing has become one of the essential needs of people over the Internet but with the emerging concept of IoT, traditional Clouds seem inadequate. IoT entails extremely low latency and for that, the Cloud servers that are distant and unknown to the user appear to be unsuitable. With the help of Fog computing, the Fog devices installed would be closer to the user that will provide an immediate storage for the frequently needed data. This paper discusses data migration between different storage types especially between Cloud devices and then presents a mechanism to migrate data between Cloud and Fog Layer. We call this mechanism Adaptive Deadline-Aware Scheme (ADAS) for Data migration between Cloud and Fog. We will demonstrate that we can access and process latency sensitive "hot" data through the proposed ADAS more efficiently than with a traditional Cloud setup.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.684-685
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• 2017

FMCW radar, which is widely used as a front collision warning system for vehicles, is now being commercialized. In this study we develope the radar signal processing system using MPC5775K that is specialized for high performance ADAS. That has special features for ADAS such as 10Msps 12bit ADC, 50MHz Radix-4 FFT, CTE(Cross Triggering Engine) for synchronized triggering between DAC and ADC. The baseband processing board is implemented and shows the result in Matlab.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.60-65
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• 2021

The event data recorders (EDR) have been used as a device to help understand traffic accidents. With the recent development of autonomous vehicle (AV), it has become important to prepare the new EDR for AV. Therefore, the purpose of this study is to propose the direction of EDR-AV recording. First of all, the recent EDR data elements and the data elements of AV under discussion at UNECE WP29 EDR/DSSAD (Data Storage System for Automated Driving) were analyzed. The consumer complaint database in Motor Vehicle Recall Center in Korea was analyzed in order to utilize cases of domestic traffic accidents related to advanced driver assistance systems (ADAS). Consequently, problems with existing EDR were identified through unclear accident cases related to ADAS. In the future, it was proposed to record images in which the ADAS perception systems recognize the surroundings of the accident site as an EDR-AV recording item.

• Journal of Auto-vehicle Safety Association
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• v.10 no.4
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• pp.40-49
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• 2018

Currently, a lot of researches about high risk test scenarios for autonomous vehicle and advanced driver assistance systems have been carried out to evaluate driving safety. This study proposes new type of test scenario that evaluate the driving safety for autonomous vehicle by reconstructing accident database of national automotive sampling system crashworthiness data system (NASS-CDS). NASS-CDS has a lot of detailed accident data in real fields, but there is no data of accurate velocity in accident moments. So in order to propose scenario generation method from accident database, we try to reconstruct accident moment from accident sketch diagram. At the same step, we propose an accident of occurrence frequency which is based on accident codes and road shapes. The reconstruction paths from accident database are integrated into evaluation of simulation environment. Our proposed methods and processor are applied to MILS (Model In the Loop Simulation) and VILS (Vehicle In the Loop Simulation) test environments. In this paper, a reasonable method of accident reconstruction typology for autonomous vehicle evaluation of feasibility is proposed.

• Childhood Kidney Diseases
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• v.26 no.1
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• pp.31-39
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• 2022

Alport syndrome (AS) is a progressive hereditary nephritis that is often accompanied by sensorineural hearing loss and ocular abnormalities. It is inherited in three modes of X-linked AS (XLAS), autosomal recessive AS (ARAS), and autosomal dominant AS (ADAS). XLAS is caused by pathogenic variants in COL4A5, while ARAS and ADAS are caused by those in COL4A3 or COL4A4. There is currently no curative treatment for AS; however, angiotensin-converting enzyme inhibitors (ACEi) can improve the outcome of AS. In the past decade, multiple studies have shown that early intervention with ACEi upon isolated microscopic hematuria or microalbuminuria could delay disease progression, and early diagnosis is crucial for early treatment. Therefore, a new classification of AS based on molecular diagnoses has been proposed, including the paradigm shift of re-classifying female "carriers" to "patients" and "thin basement membrane nephropathy" to "ADAS." In addition, with the detection of COL4A mutations in some patients with biopsy-confirmed IgA nephropathy, focal segmental glomerulosclerosis, and chronic kidney disease of unknown origin, it is suggested that the phenotype of AS should be expanded. In this review, we highlight the landmark studies and guidelines published over the past decade and introduce strategies for early diagnosis and treatment to improve the outcomes of AS.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.81-90
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• 2016

As an autonomous driving vehicle (AV) need to cope with external road conditions by itself, its perception performance for road environment should be better than that of a human driver. A vision sensor, one of AV sensors, performs lane detection function to percept road environment for performing safe vehicle steering, which relates to define vehicle heading and lane departure prevention. Performance standards for a vision sensor in an ADAS(Advanced Driver Assistance System) focus on the function of 'driver assistance', not on the perception of 'independent situation'. So the performance requirements for a vision sensor in AV may different from those in an ADAS. In assuming that an AV keep previous steering due to lane detection failure, this study calculated lane departure distances between the AV location following curved road alignment and the other one driving to the straight in a curved section. We analysed lane departure distance and time with respect to the allowance of lane detection malfunction of an AV vision sensor. With the results, we found that an AV would encounter a critical lane departure situation if a vision sensor loses lane detection over 1 second. Therefore, it is concluded that the performance standards for an AV should contain more severe lane departure situations than those of an ADAS.

• Journal of Sensor Science and Technology
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• v.26 no.1
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• pp.1-6
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• 2017

The advanced driver assistant system (ADAS) requires the collection of a large amount of information including road conditions, environment, vehicle status, condition of the driver, and other useful data. In this regard, large-scale sensor networks can be an appropriate solution since they have been designed for this purpose. Recent advances in sensor network technology have enabled the management and monitoring of large-scale tasks such as the monitoring of road surface temperature on a highway. In this paper, we consider the estimation and fusion problems of the large-scale sensor networks used in the ADAS. Hierarchical fusion architecture is proposed for an arbitrary topology of the large-scale sensor network. A robust cluster estimator is proposed to achieve robustness of the network against outliers or failure of sensors. Lastly, a robust hierarchical data fusion scheme is proposed for the communication channel between the clusters and fusion center, considering the non-Gaussian channel noise, which is typical in communication systems.

• Journal of Auto-vehicle Safety Association
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• v.12 no.3
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• pp.34-42
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• 2020

ADAS (Advanced Driver Assistance Systems) uses sensors such as camera, radar, lidar and GPS (Global Positioning System). Among these sensors, the camera has many advantages compared with other sensors. The reason is that it is cheap, easy to use and can identify objects. In this paper, therefore, a theoretical formula was proposed to obtain the distance from the vehicle's front wheel to the lane using a monocular camera. And the validity of the theoretical formula was verified through the actual vehicle test. The results of the actual vehicle test in scenario 4 resulted in a maximum error of 0.21 m. The reason is that it is difficult to detect the lane in the curved road, and it is judged that errors occurred due to the occurrence of significant yaw rates. The maximum error occurred in curve road condition, but the error decreased after lane return. Therefore, the proposed theoretical formula makes it possible to assess the safety of the LKA system.