• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.117-122
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• 2005

The purpose of this study is to analyze a correlation between lithology, rock physical property and fracture zone by multiple-logging method, which includes optic borehole image, suspension type PS, resistivity, SP, natural gamma, density, caliper logging located in Ogar test area, Changsu, Pocheon-gun, Gyunggi Province. The outstanding geophysical logging responses particularly shown from lithology pattern, fracture zone, dike zone. in result, the depth of fracture zone which enable groundwater flow estimated at $67{\sim}69m$.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.328-334
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• 2004

Recently, Software DSMs continue to improve its performance and scalability As Software DSMs become attractive on larger clusters, the focus of attention is likely to move toward improving the reliability of a system. A popular approach to tolerate failures is message logging with checkpointing, and so many log-based rollback recovery schemes have been proposed. In this work, we propose a remote logging scheme which uses the volatile memory of a remote node assigned to each node. As our remote logging does not incur frequent disk accesses during failure-free execution, its logging overhead is not significant especially over high-speed communication network. The remote logging tolerates multiple failures if the backup nodes of failed nodes are alive. It makes the reliability of DSMs grow much higher. We have designed and implemented the FT-KDSM(Fault Tolerant KAIST DSM) with the remote logging and showed the logging overhead and the recovery time.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.253-258
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• 2021

In this paper, we developed a hardware and software platform of the real-time data logging system to verify radar FEM (Front-end Module) and signal-processing algorithms. We developed a hardware platform based on FPGA (Field Programmable Gate Array) and DSP (Digital Signal Processor) and implemented firmware software to verify the various FEMs. Moreover, we designed PC based software platform to control radar logging parameters and save radar data. The developed platform was verified using 24 GHz multiple channel FMCW (Frequency Modulated Continuous Wave) in an environment of stationary and moving targets of chamber room.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.4
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• pp.169-178
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• 2018

Currently, various sensors have been used for advanced driver assistance systems. In order to overcome the limitations of individual sensors, sensor fusion has recently attracted the attention in the field of intelligence vehicles. Thus, vision and radar based sensor fusion has become a popular concept. The typical method of sensor fusion involves vision sensor that recognizes targets based on ROIs (Regions Of Interest) generated by radar sensors. Especially, because AVM (Around View Monitor) cameras due to their wide-angle lenses have limitations of detection performance over near distance and around the edges of the angle of view, for high performance of sensor fusion using AVM cameras and radar sensors the exact ROI extraction of the radar sensor is very important. In order to resolve this problem, we proposed a sensor fusion scheme based on commercial radar modules of the vendor Delphi. First, we configured multiple radar data logging systems together with AVM cameras. We also designed radar post-processing algorithms to extract the exact ROIs. Finally, using the developed hardware and software platforms, we verified the post-data processing algorithm under indoor and outdoor environments.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.09a
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• pp.11-18
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• 2005

Filament inversion routines are highly effective for target definition whenever total-field DHTEM vectors can be obtained using three-component logging tools. However most cross-hole components contain significant noise related to sensor design and errors in observation of probe rotation. Standard stacking methods can be used to improve data quality but additional statistical methods based on cross-correlation and spatial averaging of orthogonal components may be required to ensure a consistent vector migration path. Apart from assisting with spatial averaging, multiple filaments generated for successive time-windows can provide additional imaging information relating to target geometry and current migration. New digital receiver systems provide additional time-windows to provide better tracking options necessary for high-resolution imaging of this type.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.10
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• pp.1194-1205
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• 1999

인과적 메시지 로깅은 정상수행시 낙관적 메시지 로깅의 장점을 가지고, 회복시 비관적 메시지 로깅의 장점을 가지고 있다. 본 논문에서는 회복 프로세스들간의 비동기성을 향상시키기 위한 인과적 메시지 로깅에 기반한 새로운 회복 알고리즘을 제안하고자 한다. 기존의 인과적 메시지 로깅 기반 회복 알고리즘들은 살아있는 프로세스들의 수행을 대기시키거나, 회복 프로세스들간의 높은 동기성을 요구한다. 본 논문에서 제안하는 회복 알고리즘은 각 회복 프로세스가 자신의 회복만을 책임지게 함으로써, 여러 개의 프로세스들이 동시적으로 고장이 발생하더라도 회복시 살아있는 프로세스들의 수행을 대기시키지 않고, 회복 프로세스들 중 하나의 회복 프로세스에게만 과부하가 발생하지 않도록 한다. 또한, 제안하는 알고리즘은 각 회복 프로세스의 회복 과정이 다른 회복 프로세스의 연속적인 고장들에 의해 지연되지 않도록 한다. 본 논문에서는 제안하는 회복 알고리즘의 정당성을 증명하고, 시뮬레이션을 통해서 제안하는 회복 알고리즘이 기존 회복 알고리즘에 비해 고장난 프로세스의 평균회복시간을 단축시킨다는 것을 보여준다.Abstract Causal message logging has the advantages of optimistic message logging during failure-free execution and pessimistic message logging during recovery. In this paper, we present a new recovery algorithm based on causal message logging for improving asynchrony among recovering processes. Existing recovery algorithms based on causal message logging block the execution of live processes or require high synchronization among recovering processes. As each recovering process is responsible for only its recovery in our algorithm, the algorithm avoids blocking the execution of live processes during recovery even in concurrently multiple failures and overloading only one among recovering processes. Moreover, it allows the recovery of each recovering process not to be delayed by the continuous failures of other recovering processes. We prove the correctness of our recovery algorithm, and our simulation results show that our algorithm reduces the average recovery time of a failed process compared with the existing recovery algorithms.

• The Journal of Engineering Geology
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• v.8 no.1
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• pp.87-98
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• 1998

Multiple logging techniques consisting of geophysical logs, care logs, physical property measurements on core samples have been adopted on a test borehole drilled in the Pungam basin ; a small Cretaceous sedimentary basin located in Sosok area, Hongchon-gun, Kangwon Province, Korea. This study has been made to solve the problem of mismatches between the results of geophysical log and core log analyses. And the cause and range of depth errors as well as logging responses were studied. The result shows that the depth error caused by geophysical log is so small that it can be used as a reliable depth criterion in the borehole. The analysis of physical property measurements is also shown as very effective in determining the real depth and the geology of the borehole.

• Journal of the Korean Geotechnical Society
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• v.19 no.5
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• pp.319-326
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• 2003

In site investigation for tunnel designs, nowadays, geophysical exploration such as seismic exploration and electric resistivity exploration as well as drilling logging is frequently carried out. A method which can systematically make the utmost use of all available data obtained from investigation, therefore, is strongly required for the optimal evaluation of ground conditions in terms of rock mass class, etc. Many researchers have proposed using qualitative data to cope with the lack of quantitative data. In this study, an evaluation technique of rock mass classes in undrilled region was proposed based upon multiple indicator kriging method which is a geostatistical technique. It was shown that two types of data with different degree of uncertainty, for example, drilling logging data and geophysical exploration data, could be simultaneously utilized in evaluating rock mass classes for a real tunnel design.

• Forest Science and Technology
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• v.14 no.4
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• pp.169-180
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• 2018

The Republic of Korea (ROK) has had a successful experience in greening its land because of strong state policy and public participation. This paper aims to analyze the interest positions, participation, and accountability of multiple actors in the process of greening movements in the ROK. These movements were divided into two phases: forest rehabilitation (1973-1997) and urban greening (1998-2017). During the first phase, farmers caused deforestation by slash-and-burn farming and illegal logging, and governmental agencies acted as helpers controlled the farmers' deforestation activities. During the second phase, government agencies and enterprises caused deforestation with urban development projects, including construction of housings and roads. Multiple actors including citizens, NGOs, and enterprises helped urban greening through campaigns, donations, and monitoring. As a result, managing interest positions is significant to motivate multiple actors to participate in the greening movement. Participation with clear accountability is meaningful for successful greening. Therefore interest-based participation requiring accountability contributes to greening. This phenomenon indicates interconnection for interest positions, participation and accountability should be considered in designing greening policies.

• Journal of Soil and Groundwater Environment
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• v.21 no.3
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• pp.21-34
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• 2016

In the present study, we applied various machine learning techniques comparatively for prediction of subsurface structures based on multiple secondary information (i.e., well-logging data). The machine learning techniques employed in this study are Naive Bayes classification (NB), artificial neural network (ANN), support vector machine (SVM) and logistic regression classification (LR). As an alternative model, conventional hidden Markov model (HMM) and modified hidden Markov model (mHMM) are used where additional information of transition probability between primary properties is incorporated in the predictions. In the comparisons, 16 boreholes consisted with four different materials are synthesized, which show directional non-stationarity in upward and downward directions. Futhermore, two types of the secondary information that is statistically related to each material are generated. From the comparative analysis with various case studies, the accuracies of the techniques become degenerated with inclusion of additive errors and small amount of the training data. For HMM predictions, the conventional HMM shows the similar accuracies with the models that does not relies on transition probability. However, the mHMM consistently shows the highest prediction accuracy among the test cases, which can be attributed to the consideration of geological nature in the training of the model.