• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.216-223
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• 2019

Fault detection during production processes is one of the required operational tasks to run production processes both safely and consistently. Unexpected operational events or undetected process faults can have a serious impact on the production systems and subsequently on the final products' quality. In addition, such situations may lead to malfunctions or breakdowns of production processes. To reliably detect such abnormalities, a new one-class classification-based detection scheme has recently been developed The proposed method consists of four steps:1) noise filtering, 2) feature selection, 3) nonlinear representation and 4) outlier detection. The performance of the proposed scheme was demonstrated using the multivariate data obtained from a simulation process. The results have shown that the proposed method produced reliable monitoring results and outperforms any existing methods with an average improvement of 25.4%. The use of proper feature selection in the proposed framework yielded better detection performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.165-171
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• 2019

The study of the computer architecture has shown that major improvements in price-to-energy performance stems from domain-specific hardware development. This paper analyzes the tensor processing unit (TPU) ASIC which can accelerate the reasoning of the artificial neural network (NN). The core device of the TPU is a MAC matrix multiplier capable of high-speed operation and software-managed on-chip memory. The execution model of the TPU can meet the reaction time requirements of the artificial neural network better than the existing CPU and the GPU execution models, with the small area and the low power consumption even though it has many MAC and large memory. Utilizing the TPU for the tensor flow benchmark framework, it can achieve higher performance and better power efficiency than the CPU or CPU. In this paper, we analyze TPU, simulate the Python modeled OpenTPU, and synthesize the matrix multiplication unit, which is the key hardware.

• Journal of the Society of Disaster Information
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• v.15 no.2
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• pp.186-197
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• 2019

Purpose: This study intends to develop a nonlinear cyclic plasticity damage model in the framework of finite element formulation, which is capable of taking large deformation effects into account, in order to accurately predict the hysteretic behavior of stainless steel structures. Method: The new cyclic constitutive equations that utilize the combined isotropic-kinematic hardening rule for plastic deformation is incorporated into the damage mechanic model in conjunction with the large strain formulation. The damage growth law is based on the experimental observations that the evolution of microvoids yields nonlinear damage accumulation with plastic deformation. The damage model parameters and the procedure for their identification are presented. Results and Conclusion: The proposed nonlinear damage model has been verified by simulating uniaxial strain-controlled monotonic and cyclic loading tests, and successfully applied to a thin-walled stainless steel pipe subjected to constant and alternating strain-controlled cyclic loadings.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.393-399
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• 2017

According to the United Nations Framework Convention on Climate Change (UNFCCC), all parties have to submit the national GHG inventory report. Estimating carbon stocks and changes in Land Use, Land-Use Changes and Forestry (LULUCF) needs an activity data and emission factors. So this study was conducted to develop carbon emission factor for Robinia pseudoacacia L., Betula platyphylla var. japonica, and Liriodendron tulipifera. As a result, the basic wood density ($g/cm_3$) was 0.64 for R. pseudoacacia, 0.55 for B. platyphylla, and 0.46 for L. tulipifera. Biomass expansion factor was 1.47 for R. pseudoacacia, 1.30 for B. platyphylla, and 1.24 for L. tulipifera. Root to shoot ratio was 0.48 for R. pseudoacacia, 0.29 for B. platyphylla, and 0.23 for L. tulipifera. Uncertainty of estimated emission factors on three species ranged from 3.39% to 27.43% within recommended value (30%) by IPCC. We calculated carbon stock and change using these emission factors. Three species stored carbon in forest and net $CO_2$ removal was $1,255,398\;t\;CO_2/yr$ during 5 years. So we concluded that our result could be used as emission factors for national GHG inventory report on forest sector.

• The Journal of the Acoustical Society of Korea
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• v.37 no.6
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• pp.506-511
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• 2018

This paper proposes an GMM(Gaussian Mixture Model)-DNN(Deep Neural Network) hybrid-based feature compensation method for effective speech recognition in noisy environments. In the proposed algorithm, the posterior probability for the conventional GMM-based feature compensation method is calculated using DNN. The experimental results using the Aurora 2.0 framework and database demonstrate that the proposed GMM-DNN hybrid-based feature compensation method shows more effective in Known and Unknown noisy environments compared to the GMM-based method. In particular, the experiments of the Unknown environments show 9.13 % of relative improvement in the average of WER (Word Error Rate) and considerable improvements in lower SNR (Signal to Noise Ratio) conditions such as 0 and 5 dB SNR.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.121-126
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• 2018

IEEE 802.1 TSN TG is developing standards for end-to-end delay bounds and zero packet loss based on Ethernet technology. We focus on packet forwarding techniques. TSN packet forwarding techniques can be classified into Synchronous and Asynchronous framework. Synchronous approach allocates fixed time period for a class, yet is complex for large networks. Asynchronous approach provides delay guarantee by regulator-scheduler pair, yet is unnecessarily complex, too. We propose network components for TSN Asynchronous architecture, which remove the complexity of maintaining flow state for regulation decisions. Despite such a simplicity, the proposed architecture satisfies the TSN's delay requirements provided the limited high priority traffic's maximum packet length.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.131-134
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• 2014

The Internet allows firms to serve customers more effectively than ever before. In the B2C context, we examine the interrelationships among information privacy concerns, e-trust, and e-loyalty. The authors extend prior research by incorporating constructs of information privacy concerns into a more holistic conceptual framework. This study answers three research questions: Will the three components of information privacy concerns have a significant effect on e-loyalty through e-trust?, Does e-trust mediate e-loyalty?, Finally, do switching costs have a moderation effect between e-trust and e-loyalty?, The authors examine data from customers who have booked hotel accommodations online. The results support our hypotheses and confirm both the mediation role of e-trust and the moderation role of switching costs. Conceptually, this study provides an empirical validation of information privacy concerns, e-trust, and loyalty linkage. On the managerial level, this research provides insights into critical drivers of loyalty in the emerging online marketplace.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.811-814
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• 2014

There is increasing interest in the introduction of smart work as a flexible working form to perform a task without restrictions of time and place by using the information and communication technology as a creative innovative capacity has become an important element of enterprise competitiveness. However, because of the lack of understanding about smart work and concrete practices, most local SMEs are staying at the beginning of introducing the smart work. It is required to provide the standard of a smart work common structure and interface to quickly develop smart work services in a standardized way for SMEs and promote the deployment of the smart work in this environment. In this paper, we present standard development directions for the smart work service common structure and component interface to develop specialized services according to the size, the purpose and the needs of local SMEs.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.45 no.4
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• pp.199-206
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• 2019

Objectives: In mandibular edentulism, the treatment option with a two-interforaminal implant-retained bridge and a removable partial denture is rarely evaluated in literature. The aim of this in vitro study was to evaluate the stress distribution of this treatment option by comparing it with traditional treatment options with interforaminal implants in the edentulous mandible. Materials and Methods: Two interforaminal implants were placed in a formalin-fixed cadaver mandible, and overdentures with three different types of attachments were fabricated: (1) two ball attachments and an overdenture, (2) a Dolder bar and an overdenture, and (3) screw-retained two-implant inter-canine porcelain fused to a metal bridge and an implant-assisted removable denture (IARD) with precision attachments. Three biting conditions were generated for each denture type, and the strains were documented under vertical loading of 100 N. Results: The calculated strain values from measured strains in all measurement sites and loading conditions for the screw-retained two-implant intercanine porcelain fused to a metal bridge and a cast framework partial denture with precision attachments situation were lower than in the other scenarios (P<0.05). Conclusion: Within the limitations of the present study, it can be concluded that an IARD may be a reasonable and valuable alternative to ball attachments or a bar in two interforaminal implants, especially when the patients prefer to be able to show their teeth even when they take out their removable dentures.

• Journal of Korea Water Resources Association
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• v.52 no.9
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• pp.589-601
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• 2019

Various applications of radar rainfall data have been actively employed in the field of hydro-meteorology. Since radar rainfall is estimated by using predefined reflectivity-rainfall intensity relationships, they may not have sufficient reproducibility of observations. In this study, a generalized linear model is introduced to better capture the Z-R relationship in the context of bias correction within a Bayesian regression framework. The bias-corrected radar rainfall with the generalized linear model is more accurate than the widely used mean field bias correction method. In addition, we analyzed variability of the bias correction parameters under various geomorphological conditions such as the height of the weather station and the separation distance from the radar. The identified relationship is finally used to derive a regionalized formula which can provide bias correction factors over the entire watershed. It can be concluded that the bias correction parameters and regionalized method obtained from this study could be useful in the field of radar hydrology.