• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.667-674
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• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3797-3822
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• 2020

The inspection of cracks on the surface of tunnel linings is a common method of evaluate the condition of the tunnel. In particular, determining the thickness and shape of a crack is important because it indicates the external forces applied to the tunnel and the current condition of the concrete structure. Recently, several automatic crack detection methods have been proposed to identify cracks using captured tunnel lining images. These methods apply an image-segmentation mechanism with well-annotated datasets. However, generating the ground truths requires many resources, and the small proportion of cracks in the images cause a class-imbalance problem. A weakly annotated dataset is generated to reduce resource consumption and avoid the class-imbalance problem. However, the use of the dataset results in a large number of false positives and requires post-processing for accurate crack detection. To overcome these issues, we propose a crack detection method using a ternary classifier. The proposed method significantly reduces the false positive rate, and the performance (as measured by the F1 score) is improved by 0.33 compared to previous methods. These results demonstrate the effectiveness of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2470-2491
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• 2018

Web-scale open information extraction (Open IE) plays an important role in NLP tasks like acquiring common-sense knowledge, learning selectional preferences and automatic text understanding. A large number of Open IE approaches have been proposed in the last decade, and the majority of these approaches are based on supervised learning or dependency parsing. In this paper, we present a novel method for web scale open information extraction, which employs cosine distance based on Google word vector as the confidence score of the extraction. The proposed method is a purely unsupervised learning algorithm without requiring any hand-labeled training data or dependency parse features. We also present the mathematically rigorous proof for the new method with Bayes Inference and Artificial Neural Network theory. It turns out that the proposed algorithm is equivalent to Maximum Likelihood Estimation of the joint probability distribution over the elements of the candidate extraction. The proof itself also theoretically suggests a typical usage of word vector for other NLP tasks. Experiments show that the distance-based method leads to further improvements over the newly presented Open IE systems on three benchmark datasets, in terms of effectiveness and efficiency.

• Journal of the Korean earth science society
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• v.39 no.1
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• pp.23-45
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• 2018

Moderately diverse, but very abundant trace fossils are found from the Late Pleistocene deposits of Jeju Island, Korea. Vertical I-, Y- and U-shaped domichnia of annelids or decapods are, over 2500, extremely abundant, 3D network domichnia of callianassids are, over 200, very abundant, and small sinuous trails of nematode repichnia are, over 50, abundant in number. Horizontal trails attributable to polychaete or worm-like animals are, less than 50, common, but horizontal spreiten burrows, fish traces and crab trackways are, less than 10, rare in occurrence. Of these trace fossils, Taenidium barretti, Undichna britannica and Undichna unisulca represent the first record from the Pleistocene in Asia. Psilonichnus upsilon is the second record in Asia. Crab trackways probably produced by underwater punting gait of sideway walking crabs may represent the first record in the world. In addition, diverse and very abundant footprints of more than 500 hominids, more than 200 birds and more than 1000 mammals are closely associated with these invertebrate trace fossils. Trace fossil assemblage integrated with sedimentary facies is interpreted to have been formed in the marginal marine foreshore to backshore environment corresponding to the Psilonichnus and Skolithos ichnofacies.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.343-346
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• 2002

Toward more accurate determination of the water cycle in association with climate variability and change as well as baseline data on the impacts of this variability on water resources, the Coordinated Enhanced Observing Period (CEOP) was launched on July 1,2001. The preliminary data period, EOP-1, was implemented from July to September in 2001. The first annual enhanced observing period, EOP-3, is going to start on October 1,2002. CEOP is seeking to achieve a database of common measurements from both in situ and satellite remote sensing, model output, and four-dimensional data analyses (4DDA; including global and regional reanalyses) for a specified period. In this context a number of carefully selected reference stations are linked closely with the existing network of observing sites involved in the GEWEX Continental Scale Experiments, which are distributed across the world. The initial step of CEOP is to develop a pilot global hydro-climatological dataset with global consistency under the climate variability that can be used to help validate satellite hydrology products and evaluate, develop and eventually predict water and energy cycle processes in global and regional models. Based on the dataset, we will address the studies on the inter-comparison and inter-connectivity of the monsoon systems and regional water and energy budget, and a path to down-scaling from the global climate to local water resources, as the second step.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.659-665
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• 2000

In this paper a platoon merging control system is considered as a remotely located system with state represented by a stochastic process. in the system it is common to encounter situations where a single decision maker controls a large number of subsystems and observation and control signals are sent over a communication channel with finite capacity and significant transmission delays. Unlike a classical estimation problem where the observation is a continuous process corrupted by additive noise there is a constraint that the observation must be coded and transmitted over a digital communication channel with fintie capacity. A recursive coder-estimator sequence is a state estimation scheme based on observations transmitted with finite communication capacity constraint. in this paper we introduce a stochastic model for the lead vehicle in a platoon of vehicles in a lane considering the angle between the road surface and a horizontal plane as a stochastic process. In order to merge two platoons the lead vehicle of the following platoon is controlled by a remote control station. Using the observation transmitted over communication channel the remote control station designs the feedback controller. The simulation results show that the intervehicle spacings and the deviations from the desired intervehicle spacing are well regulated.

• Journal of Korea Multimedia Society
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• v.4 no.2
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• pp.145-160
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• 2001

With the rapid of computer applications and digital communication networks, group based applications on the open network have been common tendency. The multicast infrastructure has played an important researching part in this application area. However the conventional solutions to achieve the secure and efficient structure don't satisfy all requirements. In this study, we classified and analyzed several existing multicast key management structure on the safety, the efficiency and the strengthen. Based on the analysis, we developed a new secure and efficient multicast key management structure. By comparing various aspects, that the number of communication and computation, of the new and the conventional methods, we were able to demonstrate the effectiveness of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.607-615
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• 2005

Group key agreement protocols are designed to allow a group of parties communicating over a public network to securely establish a common secret key. Over the years, a number of solutions to this problem have been proposed with varying degrees of complexity. However, there seems to have been no previous systematic look at the growing problem of key agreement over combined wired/wireless networks, consisting of both high-performance computing machines and low-power mobile devices. In this paper we present an efficient group key agreement scheme well suited for this networking environment. Our scheme meets efficiency, scalability, and all the desired security requirements.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.95-105
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• 2018

As the IT industry developed, the information held by the company soon became a corporate asset. As this information has value as an asset, the number and scale of various cyber attacks which targeting enterprises and institutions is increasing day by day. Therefore, research are being carried out to protect the assets from cyber attacks by using the attack graph to identify the possibility and risk of various attacks in advance and prepare countermeasures against the attacks. In the attack graph, security metric is used as a measure for determining the importance of each asset or the risk of an attack. This is a key element of the attack graph used as a criterion for determining which assets should be protected first or which attack path should be removed first. In this survey, we research trends of various security metrics used in attack graphs and classify the research according to application viewpoints, use of CVSS(Common Vulnerability Scoring System), and detail metrics. Furthermore, we discussed how to graft the latest security technologies, such as MTD(Moving Target Defense) or SDN(Software Defined Network), onto the attack graphs.

• The Journal of KAIRB
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• v.5 no.1
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• pp.1-13
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• 2023

In the United States (US), due to the Common Rule, completely revised in 2017, single Institutional Review Board (IRB) review has become mandatory for government-sponsored multi-institutional research since 2020 regardless of the number of participating institutions. The goal of these changes is to reduce redundant reviews by the IRB at each institution and better protect research participants. In this paper, single IRB and Human Research Protection Program (HRPP) in the US and Korea were compared and considered, and their implications were discussed. A comparison of the HRPP evaluation and certification systems of the US and Korea includes that of SMART IRB in the US and Korea Central IRB, aiming at single IRB review for efficient review with support from the country and building a more efficient national human subject research network in the future. Its comparison and analysis will be helpful in deriving future tasks and development directions of single IRB and HRPP in Korea.