• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Composites Research
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• v.35 no.6
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• pp.431-438
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• 2022

Efficient heat dissipation in current electronics is crucial to ensure the best performance and lifespan of the devices along with the users' safety. Materials with high thermal conductivity are often used to dissipate the generated heat from the electronics to the surroundings. For this purpose, polymer composites have been attracted much attention as they possess advantages rooted from both polymer matrix and thermally conductive filler. In order to meet the thermal conductivity required by relevant industries, composites with high filler loadings (i.e., >60 vol%) have been fabricated. At such high filler loadings, however, composites lose benefits originated from the polymer matrix. To achieve high thermal conductivity at a relatively low filler loading, therefore, constructing the heat conduction pathway by controlling filler structure within the composites may represent a judicious strategy. To this end, this review introduces several recent approaches to manufacturing heat dissipating materials with high thermal conductivity by manipulating thermally conductive filler structures in polymer composites.

• Journal of Korea Technology Innovation Society
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• v.20 no.2
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• pp.487-517
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• 2017

In the context of an increased demand in universities' expansion of networks between other innovation actors, this research attempts to make a comparison on university-centered SCIE knowledge networks between regions. Using regional comparison, we have looked into these networks in regards to their characteristics, the importance of regional boundaries, and the effect of the regional industrial policy. As a result of this comparative analysis, we discovered that the point universities and research universities hold high centrality in regional knowledge networks, and that the characteristics of regions are reflected into this network. For instance, the Gyeonggi province had a preeminent level of industry-academy relationship, while for Daejeon it was public research institutions and academy, and Gangwon province it was between academy between academy. As a network analysis based on journals above SCIE levels, regional boundaries were not very clear in the network structures. However, within these boundaries, the impact of regional industrial policies were proven to be stronger in the Gang-won province where the academy-academy network was most prominent. The implication of this research outcome is that for regional innovation, government should more actively implement policies that can link academic institutes' knowledge to industry by expanding knowledge networks. In addition, we emphasize on the necessity of a regionally-appropriate policy, rather than a generalized industrial policy. And fundamentally, in regards to innovation, establishing a sound industrial infrastructure for regional development and efforts to link relevant actors are required.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.74-77
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• 2021

최근 딥러닝을 이용하여 객체 인식 학습을 위한 데이터셋을 구축하는데 있어 시간과 인력을 단축하기 위해 인조 데이터를 생성하는 연구가 진행되고 있다. 하지만 실제 환경과 관계없이 임의의 배경에 배치되어 구축된 데이터셋으로 학습된 네트워크를 실제 환경으로 구성된 데이터셋으로 테스트할 경우 인식률이 저조하다. 이에 본 논문에서는 실제 배경 이미지에 객체 이미지를 합성하고, 다양성을 위해 3차원으로 회전하여 증강하는 인조 데이터셋 생성 시스템을 제안한다. 제안된 방법으로 구축된 인조 데이터셋으로 학습한 네트워크와 실제 데이터셋으로 학습된 네트워크의 인식률을 비교한 결과, 인조 데이터셋의 성능이 실제 데이터셋의 성능보다 2% 낮았지만, 인조 데이터셋을 구축하는 시간이 실제 데이터셋을 구축하는 시간보다 약 11배 빨라 시간적으로 효율적인 데이터셋 구축 시스템임을 증명하였다.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.182-189
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• 2023

Depth estimation is a key technology in 3D map generation for autonomous driving of vehicles, robots, and drones. The existing sensor-based method has high accuracy but is expensive and has low resolution, while the camera-based method is more affordable with higher resolution. In this study, we propose self-attention-based unsupervised monocular depth estimation for UAV camera system. Self-Attention operation is applied to the network to improve the global feature extraction performance. In addition, we reduce the weight size of the self-attention operation for a low computational amount. The estimated depth and camera pose are transformed into point cloud. The point cloud is mapped into 3D map using the occupancy grid of Octree structure. The proposed network is evaluated using synthesized images and depth sequences from the Mid-Air dataset. Our network demonstrates a 7.69% reduction in error compared to prior studies.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.875-890
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• 2009

Metabolimics interprets an organism as a network of functional units and an organism is represented by a metabolic pathway i.e., well-displayed graph. So a software tool for drawing pathway is necessary to understand it comprehensively. These tools have a problem that edge-crossings exponentially increase as the number of nodes grows. To apply automatic graph layout techniques to the genome-scale metabolic flow, it is very important to reduce unnecessary edge-crossing on a metabolic pathway layout. In this paper, we design and implement 2.5D metabolic pathway layout modules. Metabolic pathways are represented hierarchically by making use of the '2-layered layout algorithm' in 3D. It enhances the readability and reduces unnecessary edge-crossings by using 3D layout modules instead of 2D layout algorithms.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.3
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• pp.385-396
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• 1999

In the process of structural design for large-scale structures with several thousands of degrees of freedom, a plethora of structural calculations with large amount of data storage are required to obtain the forces and displacements of the members. However, current computational environment with single microprocessor such as a personal computer or a workstation is not capable of generating a high-level of efficiency in structural analysis and design process for large-scale structures. In this paper, a high-performance parallel computing system interconnected by a network of personal computers is proposed for an efficient structural analysis. Two distributed structural analysis algorithms are developed in the form of distributed or parallel preconditioned conjugate gradient (DPCG) method. To enhance the performance of the developed distributed structural analysis algorithms, the number of communications and the size of data to be communicated are minimized. These algorithms are applied to the structural analyses of three large space structures as well as a 144-story tube-in-tube framed structure.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.5
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• pp.389-395
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• 2012

U-City has been promoted nation-wide by development of recent IT technology. This paper studied the concept of 3D-virtual city in order to realize the current Ubiquitous City(U-City) efficiently, and to manage all the RFID/USN monitoring data in the real U-City. 3D-Virtual City is the concept of the reproduction of real world U-City, for embodying Ubiquitous technology while using Digital map, satellite image, VRML(Virtual Reality Modeling Language). U&V-City is the four-dimensional future city that real-time wire/wireless communication network and 3D-web GIS shall be connected that massive database, intelligent service be perceived through employing EAI(External Authoring Interface) that provides HTML&JAVA, and interface for efficient removal/process of massive information/ service and also by employing GPS/LBS/Navigation in support of world-wide orientation concept, and RTLS(Real Time Location System).

• The Transactions of the Korea Information Processing Society
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• v.13 no.7
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• pp.326-334
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• 2024

Extra-oral imaging techniques such as Panoramic X-rays (PXs) and Cone Beam Computed Tomography (CBCT) are the most preferred imaging modalities in dental clinics owing to its patient convenience during imaging as well as their ability to visualize entire teeth information. PXs are preferred for routine clinical treatments and CBCTs for complex surgeries and implant treatments. However, PXs are limited by the lack of third dimensional spatial information whereas CBCTs inflict high radiation exposure to patient. When a PX is already available, it is beneficial to reconstruct the 3D oral structure from the PX to avoid further expenses and radiation dose. In this paper, we propose 3DentAI - an U-Net based deep learning framework for 3D reconstruction of oral structure from a PX image. Our framework consists of three module - a reconstruction module based on attention U-Net for estimating depth from a PX image, a realignment module for aligning the predicted flattened volume to the shape of jaw using a predefined focal trough and ray data, and lastly a refinement module based on 3D U-Net for interpolating the missing information to obtain a smooth representation of oral cavity. Synthetic PXs obtained from CBCT by ray tracing and rendering were used to train the networks without the need of paired PX and CBCT datasets. Our method, trained and tested on a diverse datasets of 600 patients, achieved superior performance to GAN-based models even with low computational complexity.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2003.11a
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• pp.101-114
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• 2003

홈 유비퀴터스 네트워크란 PC, 휴대 전화, 디지털TV, 냉장고, 에어컨, 개인 휴대 정보 단말기(PDA), 게임기 등 가정 내의 정보기기들 사이에 통합된 네트워크를 형성해 데이터를 공유할 수 있는 환경을 구성한 것이다. 홈 네트워크 서비스를 가능케 한 요인은 기술적 측면에서 가전기기의 디지털화 및 초고속망의 보급, 수요측면에서 가전기기를 통한 다양한 서비스를 이용하고자 하는 소비자의 요구, 공급측면으로 포화된 정보통신기기 시장에서 새로운 수요창출이 필요한 환경 등으로 요약될 수 있다. 이와 같이 현재 정보통신산업은 지금까지 구축된 정보통신 인프라를 바탕으로 새롭게 등장한 홈 네트워크 서비스 분야에 주목하고 있다. 홈 네트워크는 정보통신기술을 가전기기에 융합시킴으로써 새로운 서비스를 창출한다는 점에서 정보통신산업은 물론, 기존의 백색가전 산업까지 포괄하여 관련 산업의 전후방 효과가 매우 크다. 본 연구에서는 홈 네트워크 서비스에 관련한 핵심 속성을 분석하고, 핵심 속성에 대한 소비자의 선호를 분석하는 실증연구를 수행하였다. 현재 홈 네트워크 시장이 본격적으로 형성되지 않아 현시선호(revealed preference) 자료의 구득이 불가능하므로, 소비자에게 향후 제공될 수 있는 서비스 특성을 지닌 가상적인 제품 조합을 제시하고, 이에 대해 소비자가 실제 시장에서와 같은 구매행위를 가정하도록 한 후, 각 제품 조합에 대한 선호 순위를 매기게 함으로써 소비자의 진술선호(stated preference)를 측정하는 컨조인트(conjoint) 방법론을 사용하였다. 이러한 분석을 통해서 홈 네트워크 서비스의 각 속성에 대한 소비자의 선호구조를 파악하고 지불의 사액(Willingness To Pay, WTP)을 분석하도록 한다. 본 연구의 결과를 이용하여 향후 전개될 홈 네트워크 서비스 및 관련시장의 발전 방향을 전망해 보고 이에 따른 기업이나 정부차원의 대응전략을 파악하고자 한다.육구에서는 큰 변화를 나타내고 있지 않았다(p<0.05). 운동과 비운동시킨 참돔의 지질 함량의 변화는 운동시킨 참돔은 운동으로 인한 에너지 소비로 인하여 함량이 유의적으로 감소했으며(r=-0.35), 비운동사육구에서는 절식으로 인하여 지질함량이 감소하였다(r=-0.38). 파괴강도와 가장 밀접한 영향을 가지는 콜라겐은 운동과 비운동 모두 사육기간동안 큰 변화는 보이지 않았다. 초기의 파괴강도값은 1.45±0.02kg(운동사육구), 1.36±0.18kg(비운동사육구)이였으며 사육기간동안 운동사육구는 파괴강도값이 증가한 반면, 비운동수조에서는 참돔의 파괴강도는 사육기간동안 큰 유의차가 없었다. 각 성분간의 상관도를 살펴보면, 수분함량과 파괴강도는 상관성을 가졌으며, 지질함량과 파괴강도도 같은 경향은 나타내었다. 운동기간동안의 파괴강도와 콜라겐 사이에는 상관성의 거의 없었다. 이는 운동기간에 따른 파괴강도의 증가가 콜라겐의 함량의 증가보다는 지질함량의 감소와 수분함량의 증가와 같은 성분과의 상관성이 크다고 판단된다. 다음으로는, 운동횟수에 의한 영향으로써 운동시간을 1일 6시간으로 설정하여, 운동횟수를 결정하기 위하여 오전, 오후에 각 3시간씩 운동시키는 방법과 오전부터 6시간동안 운동시키는 두 방법을 이용하여 품질을 비교하였다. 각 조건에 따라 운동시킨 참돔의 수분함량을 나타낸 것으로, 2회(오전 3시간, 오후 3시간)에 나누어서 운동시키기 위한 육의 수분함량은 73.37±2.02%를 나타냈으며, 1회(6시간 운동)운동시키기 위한 육은 71.74±1.66%을 나타내었다. 각각의 운동조건에서 양식된 참돔은 사육초기에는 큰 변화가 없었으나, 사육 5일 이후에는 수분함량이 증가하여 15일에는 76.40±0.14, 75.62±0.98%의 수분함량을 2회와 1회 운동시킨 참돔의 육에서 각각 나타났다. 운동횟수에 따른 지질함량은 2회 운동시킨 참돔은 5.83±2.08, 1회 운동시킨 참돔은 6.72