• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.73-82
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• 2011

Recent advancement in traffic surveillance systems has allowed the researchers to obtain more detailed vehicular movement such as individual vehicle trajectory data. Understanding the characteristics of interactions between leading and following vehicles in the traffic flow stream is a backbone for designing and evaluating more sophisticated traffic and vehicle control strategies. This study proposes a methodology for estimating rear-end crash potential, as a probabilistic measure, in real-time based on the analysis of vehicular movements. The methodology presented in this study consists of three components. The first predicts vehicle position and speed every second using a Kalman filtering technique. The second estimates the probability for the vehicle's trajectory to belong to either 'changing lane' or 'going straight'. A binary logistic regression (BLR) is used to model the lane-changing decision of the subject vehicle. The other component calculates crash probability by employing an exponential decay function that uses time-to-collision (TTC) between the subject vehicle and the front vehicle. The result of this study is expected to be adapted in developing traffic control and information systems, in particular, for crash prevention.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.8
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• pp.23-32
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• 2007

We propose a group-based security scheme for hierarchical wireless sensor networks. We model the network for secure routing with 3-tier sensor network comprised of three types of nodes: Base Station, Group Dominator and ordinary Sensor Nodes. Group-based deployment is performed using Gaussian (normal) distribution and show that more than 85% network connectivity can be achieved with the proposed model. The small groups with pre-shared secrets form the secure groups where group dominators form the backbone of the entire network. The scheme is devised for dealing with sensory data aggregated by groups of collocated sensors; i.e., local sensed data are collected by the dominating nodes and sent an aggregated packet to the base station via other group dominators. The scheme is shown to be light-weight, and it offers a stronger defense against node capture attacks. Analysis and simulation results are presented to defend our proposal. Analysis shows that robustness can significantly be improved by increasing the deployment density using both the dominating and/or ordinary sensor nodes.

• Bulletin of the Korean Chemical Society
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• v.35 no.6
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• pp.1713-1719
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• 2014

1FSD is a 28-residue designed protein with a ${\beta}{\beta}{\alpha}$ motif. Since this protein displays most essential features of protein structures in such a small size, this model protein can be an outstanding system for evaluating the balance in the propensity of the secondary structures and the quality of all-atom protein force fields. Particularly, this protein would be difficult to fold to its correct native structure without establishing proper balances between the secondary structure elements in all-atom energy functions. In this work, a series of the recently optimized five amber protein force fields [$ff03^*$, $f99sb^*$-ildn, ff99sb-${\phi}^{\prime}$-ildn, ff99sb-nmr1-ildn, ff99sb-${\Phi}{\Psi}$(G24, CS)-ildn] were investigated for the simulations of 1FSD using a conventional molecular dynamics (MD) and a biased-exchange meta-dynamics (BEMD) methods. Among those tested force fields, we found that ff99sb-nmr1-ildn and ff99sb-${\Phi}{\Psi}$(G24, CS)-ildn are promising in that both force fields can locate the native state of 1FSD with a high accuracy (backbone rmsd ${\leq}1.7{\AA}$) in the global free energy minimum basin with a reasonable energetics conforming to a previous circular dichroism (CD) experiment. Furthermore, both force fields led to a common set of two distinct folding pathways with a heterogeneous nature of the transition state to the folding. We anticipate that these force fields are reasonably well balanced, thereby transferable to many other protein folds.

• Bulletin of the Korean Chemical Society
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• v.28 no.12
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• pp.2203-2208
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• 2007

Three possible binding modes of cationic meso-tetrakis(N-methylpyridinium-4-yl)porphyrin (TMPyP) to d[(GCATATATGC)2] duplex were investigated by the molecular dynamics (MD) simulation. Among the three binding modes namely, “along the groove”, “across the groove” and “face on the groove”, the “across the groove” model exhibited the largest negative binding free energy and the DNA backbone remained as the B form. In this model, the molecular plain of the TMPyP tilts 45o with respect to the DNA helix axis and is largely exposed to the solvent. TMPyP was stabilized mainly by the interaction between the positively charged neighboring pyridinium moieties of TMPyP and negatively charged phosphate groups of DNA. The result obtained in this work by MD and the report (Jin, B. et al., J. Am. Chem. Soc. 2005, 127, 2417.) that the spectral properties of poly[d(A-T)2] bound TMPyP in the presence and absence of the minor groove binding drug 4',6- diamidino-2-phenylindole are similar, we propose that TMPyP bind across the minor groove of the AT rich- DNA.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.2
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• pp.281-286
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• 2013

As the product lifecycle is getting shorter and various models should be released to respond to the needs of customers and markets, automation-based flexible production line has been recognized as the core competitiveness. According to these trends, system vendors supply cell-level systems such as FMC(Flexible Manufacturing Cell) that is integration of core functions of FMS(Flexible Manufacturing System) and RMC(Reconfigurable Manufacturing Cell) that can easily extend components of FMC. In the cell-based environment, flexible management for shop floor composed of existing job shop, FMCs and RMCs from various system vendors has emerged as an important issue. However, there could be some problems on integrated operation between heterogeneous cells to use vendor-specific cell controllers and on seamless information flow with high level systems such as ERP(Enterprise Resource Planning). In this context, this paper proposes process management systems supporting integrated shop operation of heterogeneous multi-cell based flexible manufacturing environment: First of all, (1) Integrated Shop Operation System to apply the process management system is introduced, and (2) Multi-Layer BOP(Bill-Of-Process) model, a backbone of the process management system, is derived with its data structure. Finally, application of the proposed model is illustrated through system implementation results.

• Steel and Composite Structures
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• v.34 no.1
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• pp.107-122
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• 2020

Moment resisting stub columns (MRSCs) have increasingly adopted in special moment-resisting frame (SMF) systems in steel building structures, especially in Asian countries. The MRSCs typically provide a lower deformation capacity compared to shear-panel stub columns, a limited post-yield stiffness, and severe strength degradation as adopting slender webs. A new MRSC design with cored configuration, consisting of a core-segment and two side-segments using different steel grades, has been proposed in the study to improve the demerits mentioned above. Several full-scale components of the cored MRSC were experimentally investigated focusing on the hysteretic performance of plastic hinges at the ends. The effects of the depths of the core-segment and the adopted reduced column section details on the hysteretic behavior of the components were examined. The measured hysteretic responses verified that the cored MRSC enabled to provide early yielding, great ductility and energy dissipation, enhanced post-yield stiffness and limited strength degradation due to local buckling of flanges. A parametric study upon the dimensions of the cored MRSC was then conducted using numerical discrete model validated by the measured responses. Finally, a set of model equations were established based on the results of the parametric analysis to accurately estimate strength backbone curves of the cored MRSCs under increasing-amplitude cyclic loadings.

• Journal of radiological science and technology
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• v.45 no.2
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• pp.151-158
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• 2022

The Cardiac Gated Blood Pool (GBP) scintigram, a nuclear medicine imaging, calculates the left ventricular Ejection Fraction (EF) by segmenting the left ventricle from the heart. However, in order to accurately segment the substructure of the heart, specialized knowledge of cardiac anatomy is required, and depending on the expert's processing, there may be a problem in which the left ventricular EF is calculated differently. In this study, using the DeepLabV3 architecture, GBP images were trained on 93 training data with a ResNet-50 backbone. Afterwards, the trained model was applied to 23 separate test sets of GBP to evaluate the reproducibility of the region of interest and left ventricular EF. Pixel accuracy, dice coefficient, and IoU for the region of interest were 99.32±0.20, 94.65±1.45, 89.89±2.62(%) at the diastolic phase, and 99.26±0.34, 90.16±4.19, and 82.33±6.69(%) at the systolic phase, respectively. Left ventricular EF was calculated to be an average of 60.37±7.32% in the ROI set by humans and 58.68±7.22% in the ROI set by the deep learning segmentation model. (p<0.05) The automated segmentation method using deep learning presented in this study similarly predicts the average human-set ROI and left ventricular EF when a random GBP image is an input. If the automatic segmentation method is developed and applied to the functional examination method that needs to set ROI in the field of cardiac scintigram in nuclear medicine in the future, it is expected to greatly contribute to improving the efficiency and accuracy of processing and analysis by nuclear medicine specialists.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4420-4438
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• 2021

Image dehazing is an ill-posed problem which is far from being solved. Traditional image dehazing methods often yield mediocre effects and possess substandard processing speed, while modern deep learning methods perform best only in certain datasets. The haze removal effect when processed by said methods is unsatisfactory, meaning the generalization performance fails to meet the requirements. Concurrently, due to the limited processing speed, most dehazing algorithms cannot be employed in the industry. To alleviate said problems, a lightweight fast dehazing network based on a multiple scale-patch framework (MSP) is proposed in the present paper. Firstly, the multi-scale structure is employed as the backbone network and the multi-patch structure as the supplementary network. Dehazing through a single network causes problems, such as loss of object details and color in some image areas, the multi-patch structure was employed for MSP as an information supplement. In the algorithm image processing module, the image is segmented up and down for processed separately. Secondly, MSP generates a clear dehazing effect and significant robustness when targeting real-world homogeneous and nonhomogeneous hazy maps and different datasets. Compared with existing dehazing methods, MSP demonstrated a fast inference speed and the feasibility of real-time processing. The overall size and model parameters of the entire dehazing model are 20.75M and 6.8M, and the processing time for the single image is 0.026s. Experiments on NTIRE 2018 and NTIRE 2020 demonstrate that MSP can achieve superior performance among the state-of-the-art methods, such as PSNR, SSIM, LPIPS, and individual subjective evaluation.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.293-301
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• 2023

Unstandardized medical data collection and management are still being conducted manually, and studies are being conducted to classify CT data using deep learning to solve this problem. However, most studies are developing models based only on the axial plane, which is a basic CT slice. Because CT images depict only human structures unlike general images, reconstructing CT scans alone can provide richer physical features. This study seeks to find ways to achieve higher performance through various methods of converting CT scan to 2D as well as axial planes. The training used 1042 CT scans from five body parts and collected 179 test sets and 448 with external datasets for model evaluation. To develop a deep learning model, we used InceptionResNetV2 pre-trained with ImageNet as a backbone and re-trained the entire layer of the model. As a result of the experiment, the reconstruction data model achieved 99.33% in body part classification, 1.12% higher than the axial model, and the axial model was higher only in brain and neck in contrast classification. In conclusion, it was possible to achieve more accurate performance when learning with data that shows better anatomical features than when trained with axial slice alone.

• Journal of KIISE:Information Networking
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• v.32 no.2
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• pp.220-235
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• 2005

Internet Service Quality has been constantly the center of attention to Internet Service Providers. The KII project plan (Korea Information Infrastructure) aims to build broadband backbone networks mainly through optical fiber cables and ATM switches and to Provide the government ministries, local authorities and non-profit organizations with high-speed, highly capable broadband access to these networks at reasonable rates. The KB service model, however, is different from other Internet Service models much in the same way SP (Service Provider) and NP (Network Provider) differ from each other. In this paper, we evaluate KII service according to various customer satisfaction indicators under the methodologies and categories as put forth in both the ACSI (American Customer Satisfaction Index) and SEM (Structural Equation Model). We use a structural equation model (SEM) to demarcate the Korea Information Infrastructure Customer Satisfaction Index (KIICSI) in relation to network service quality. The results of our study suggest some strategies for the KII Project need to be modified and effectively implemented in order to increase the satisfaction level of the KII customers.