• Smart Structures and Systems
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• v.12 no.3_4
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• pp.363-379
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• 2013

Dynamic displacement of structures is an important index for in-service structural condition and behavior assessment, but accurate measurement of structural displacement for large-scale civil structures such as long-span bridges still remains as a challenging task. In this paper, a vision-based dynamic displacement measurement system with the use of digital image processing technology is developed, which is featured by its distinctive characteristics in non-contact, long-distance, and high-precision structural displacement measurement. The hardware of this system is mainly composed of a high-resolution industrial CCD (charge-coupled-device) digital camera and an extended-range zoom lens. Through continuously tracing and identifying a target on the structure, the structural displacement is derived through cross-correlation analysis between the predefined pattern and the captured digital images with the aid of a pattern matching algorithm. To validate the developed system, MTS tests of sinusoidal motions under different vibration frequencies and amplitudes and shaking table tests with different excitations (the El-Centro earthquake wave and a sinusoidal motion) are carried out. Additionally, in-situ verification experiments are performed to measure the mid-span vertical displacement of the suspension Tsing Ma Bridge in the operational condition and the cable-stayed Stonecutters Bridge during loading tests. The obtained results show that the developed system exhibits an excellent capability in real-time measurement of structural displacement and can serve as a good complement to the traditional sensors.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.521-530
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• 2017

In this paper, we propose a protection solution against intelligent Ransomware attacks by encrypting not only source files but also backup files of external storage. The system is designed to automatically back up to the cloud server at the time of file creation to perform monitoring and blocking in case a specific process affects the original file. When client creates or saves a file, both process identifiers, parent process identifiers, and executable file hash values are compared and protected by the whitelist. The file format that is changed by another process is monitored and blocked to prevent from suspicious behavior. By applying the system proposed in this paper, it is possible to protect against damage caused by the modification or deletion of files by Ransomware.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.3
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• pp.231-238
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• 2020

This paper investigates the soundness of porcelain insulators associated with the acoustic emission (AE) technique. The AE technique is a popular non-destructive method that measures and analyzes the burst energy that occurs mainly when a crack occurs in a high-frequency region. Typical AE methods require continuous monitoring with frequent sensor calibration. However, in this study, the AE technique excites a porcelain insulator using only an impact hammer, and it applies a high-pass filter to the signal frequency range measured only in the AE sensor by comparing the AE and the acceleration sensors. Next, the extracted time-domain signal is analyzed for the damage assessment. In normal signals, the duration is about 2ms, the area of the envelope is about 1,000, and the number of counts is about 20. In the damage signal, the duration exceeds 5ms, the area of the envelope is about 2,000, and the number of counts exceeds 40. In addition, various characteristics in the time and frequency domain for normal and damage cases are analyzed using the short-time Fourier transform (STFT). Based on the results of the STFT analysis, the maximum energy of a normal specimen is less than 0.02, while in the case of the damage specimen, it exceeds 0.02. The extracted high-frequency components can present dynamic behavior of crack regions and eigenmodes of the isolated insulator parts, but the presence, size, and distribution of cracks can be predicted indirectly. In this regard, the characteristics of the surface crack region were derived in this study.

• Journal of the Korean Geosynthetics Society
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• v.5 no.2
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• pp.45-50
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• 2006

Although the discharge capacity of the natural fiber drains are very low compared to that of plastic drain board (PDB), it is found that the conventional fiber drains and the new developed straw drain boards have great potential for use as a substitute for conventional plastic drain boards through several model tests. To verify their field application, a pilot test using environmentally friendly drains is also being carried out to prove their effective discharge capacity in the field. The pilot test site was divided into 5 different areas, with various combinations of vertical and horizontal drains installed for evaluation. Definite characteristics of various drains are still to be found due to the delay in construction of embankment. Consolidation behavior of three types of vertical drains and two types of horizontal drains will be analyzed after the completion of the embankment in the near future.

• Journal of Wetlands Research
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• v.15 no.1
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• pp.59-69
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• 2013

The numerical simulations were performed to analyze the advection-diffusion processes of dredging-induced turbidity plume using RMA2 and RMA4 models in Bunam reservoir, Seosan, Chungnam. Field survey was also performed to measure the turbidity using the multi water quality monitoring system (YSI6600EDS). In the field survey, the vertical and horizontal distributions of the turbidity were measured during the dredging operation in Bunam reservoir. RMA2 model was used to simulate the velocity distributions in both the whole domain and the 2nd part of Bunam reservoir. RMA4 model was also used to simulate the concentration distribution in only the 2nd part of Bunam reservoir, where the dredging work were conducted. The comparison of the simulation results with the field data for the advection-diffusion of the turbidity plume using the concentration ratio concepts shows that the numerical model can be applied to analyze the environmental impact of dredging works.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.604-607
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• 2018

From the last past decade, the Internet of Thing (IoT) area has attracted a lot of attention from researchers. It is said to be a promising technology with great impact in people life, since it redefines the relationship objects have with Human and between themselves. It allows objects to gather data from the real world and communicate with others through the internet. This enabled many opportunities for service providers, companies, factories, environmental monitoring, healthcare, smart cities, and soon. Therefore, today, IoT is densely used in various domains of life, and knows an exponential growth. However, although many advancements have been achieved, several challenges keep causing issues and still need to be overcome. This paper gives an overview on the current trend issues in IoT on which researchers are focusing. It's also explores different proposed frameworks to allow the application of cognitive computing as an integrated process of an Internet of things (IoT) systems, to bring a great advanced in the way machine may communicate with human and their surroundings. This is known as cognitive IoT (CIoT), which allows machines to produce a human-like behavior, then providing enhanced level of capabilities to IoT.

• The KIPS Transactions:PartC
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• v.17C no.2
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• pp.205-214
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• 2010

As network traffic is dramatically increasing due to the popularization of Internet, the need for application traffic classification becomes important for the effective use of network resources. In this paper, we present an application traffic classification method based on fixed IP-port information. A fixed IP-port is a {IP address, port number, transport protocol}triple dedicated to only one application, which is automatically collected from the behavior analysis of individual applications. We can classify the Internet traffic more accurately and quickly by simple packet header matching to the collected fixed IP-port information. Therefore, we can construct a lightweight, fast, and accurate real-time traffic classification system than other classification method. In this paper we propose a novel algorithm to extract the fixed IP-port information and the system architecture. Also we prove the feasibility and applicability of our proposed method by an acceptable experimental result.

• Korean Journal of Social Welfare Studies
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• no.37
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• pp.399-427
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• 2008

The purpose of this study is to examine the moderating effects of protective factors on the relations between deviant peer's influences and delinquent behaviors in adolescence. To investigate the moderating effects, simple slope and region of significance test based on multiple linear regression(MLR) model were used. This study used data from wave 1-2(2003-2004) of the Korea Youth Panel Survey(KYPS). Results showed that for female adolescents, self-esteem, parent monitoring, and attachment to parent moderated the link between best friend's deviancy and delinquent behaviors. For male adolescents, however, best friend's deviancy and protective factors didn't show any significant moderating effects. These results help clarify the conditions under which exposure to deviant best friends can influence delinquent behaviors in adolescence. Practice and policy implications as well as further research topic were discussed to aid the search for highly effective preventive and treatment interventions.

• Ocean and Polar Research
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• v.43 no.4
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• pp.321-334
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• 2021

'Marine mammals-based observations' refers to data acquisition activities from marine mammals by instrumenting CTD (Conductivity-Temperature-Depth) sensors on them for recording vertical profiles of ocean variables such as temperature and salinity during animal diving. It is a novel data collecting platform that significantly improves our abilities in observing extreme environments such as the Southern Ocean with low cost compared to the other conventional methods. Furthermore, the system continues to create valuable information until sensors are detached, expanding data coverage in both space and time. Owing to these practical advantages, the marine mammals-based observations become popular to investigate ocean circulation changes in the Southern Ocean. Although these merits may bring us more opportunities to understand ocean changes, the data should be carefully qualified before we interpret it incorporating shipboard/autonomous vehicles/moored CTD data. In particular, we need to pay more attention to salinity correction due to the usage of an unpumped-CTD sensor tagged on marine mammals. In this article, we introduce quality control methods for the marine mammals-based CTD profiles that have been developed in recent studies. In addition, we discuss strategies of quality control specifically for the seal-tagging CTD profiles, successfully having been obtained near Terra Nova Bay, Ross Sea, Antarctica since February 2021. It is the Korea Polar Research Institute's research initiative of animal-borne instruments monitoring in the region. We anticipate that this initiative would facilitate collaborative efforts among Polar physical oceanographers and even marine mammal behavior researchers to understand better rapid changes in marine environments in the warming world.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.253-262
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• 2018

Objectives: We reviewed digital epidemiological studies to characterize how researchers are using digital data by topic domain, study purpose, data source, and analytic method. Methods: We reviewed research articles published within the last decade that used digital data to answer epidemiological research questions. Data were abstracted from these articles using a data collection tool that we developed. Finally, we summarized the characteristics of the digital epidemiological studies. Results: We identified six main topic domains: infectious diseases (58.7%), non-communicable diseases (29.4%), mental health and substance use (8.3%), general population behavior (4.6%), environmental, dietary, and lifestyle (4.6%), and vital status (0.9%). We identified four categories for the study purpose: description (22.9%), exploration (34.9%), explanation (27.5%), and prediction and control (14.7%). We identified eight categories for the data sources: web search query (52.3%), social media posts (31.2%), web portal posts (11.9%), webpage access logs (7.3%), images (7.3%), mobile phone network data (1.8%), global positioning system data (1.8%), and others (2.8%). Of these, 50.5% used correlation analyses, 41.3% regression analyses, 25.6% machine learning, and 19.3% descriptive analyses. Conclusions: Digital data collected for non-epidemiological purposes are being used to study health phenomena in a variety of topic domains. Digital epidemiology requires access to large datasets and advanced analytics. Ensuring open access is clearly at odds with the desire to have as little personal data as possible in these large datasets to protect privacy. Establishment of data cooperatives with restricted access may be a solution to this dilemma.