• 한국가스학회:학술대회논문집
• /
• 1997.09a
• /
• pp.284-291
• /
• 1997

배관망의 해석은 유체역학을 필요로 하며 관내의 유체의 거동과 운전 상태에 따른 유동해석을 위해 여러 식들이 사용되어왔다. 본 연구에서는 정상상태의 유량방정식을 사용해 경인지역가스 배관망에 대한 수학적 모델을 만들고 모사 및 분석을 수행하였다. 개발된 수학적 모델에서 얻어진 데이터에 통계학적인 방법을 도입해 통계학적 모델을 만듦으로써 통계학적 모델을 이용한 배관망 해석의 가능성에 대해 검토하였다.

• Journal of Korea Multimedia Society
• /
• v.23 no.2
• /
• pp.216-226
• /
• 2020

In this paper, a stacked convolutional autoencoder model is proposed in order to classify Alzheimer's disease with high accuracy in PET/CT images. The proposed model makes use of the latent space representation - which is also called the bottleneck, of the encoder-decoder architecture: The input image is sent through the pipeline and the encoder part, using stacked convolutional filters, extracts the most useful information. This information is in the bottleneck, which then uses Softmax classification operation to classify between Alzheimer's disease, Mild Cognitive Impairment, and Normal Control. Using the data from Dong-A University, the model performs classification in detecting Alzheimer's disease up to 98.54% accuracy.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.11 no.4
• /
• pp.318-328
• /
• 2011

Stage-level reconfigurable chip multiprocessor (CMP) aims to achieve highly reliable and fault tolerant computing by using interwoven pipeline stages and on-chip interconnect for communicating with each other. The existing crossbar-switch based stage-level reconfigurable CMPs offer high reliability at the cost of significant area/power overheads. These overheads make realizing large CMPs prohibitive due to the area and power consumed by heavy interconnection networks. On other hand, area/power-efficient architectures offer less reliability and inefficient stage-level resource utilization. In this paper, I propose a hierarchical multiplexing interconnection structure in lieu of crossbar interconnect to design area/power-efficient stage-level reconfigurable CMP. The proposed approach is able to keep the reliability offered by the crossbar-switch while reducing the area and power overheads. Experimental results show that the proposed approach reduces area by up to 21% and power by up to 32% when compared with the crossbar-switch based interconnection network.

• Environmental Engineering Research
• /
• v.19 no.2
• /
• pp.117-122
• /
• 2014

Indexes of safety, restoration, damage impact, and management reliability were developed to assess reliability of drinking water distribution networks (DWDNs) management. The developed indexes were applied to evaluate the reliability of the pipeline management stage during unexpected mechanical and hydraulic accidents of components. The results were used to support the decision-making process in effective management and maintenance by enhancing the administrator's system understanding and by helping to create appropriate maintenance and management policies. The results of this study indicated that application of a management reliability index to assess DWDNs reliability may help create a more effective plan for establishing DWDNs management and maintenance.

• Nuclear Engineering and Technology
• /
• v.53 no.12
• /
• pp.4060-4066
• /
• 2021

Flow-accelerated corrosion (FAC) of carbon steel piping is a significant problem in nuclear power plants. The basic process of FAC is currently understood relatively well; however, the accuracy of prediction models of the wall-thinning rate under an FAC environment is not reliable. Herein, we propose a methodology to construct pipe wall-thinning rate prediction models using artificial neural networks and a convolutional neural network, which is confined to a straight pipe without geometric changes. Furthermore, a methodology to generate training data is proposed to efficiently train the neural network for the development of a machine learning-based FAC prediction model. Consequently, it is concluded that machine learning can be used to construct pipe wall thinning rate prediction models and optimize the number of training datasets for training the machine learning algorithm. The proposed methodology can be applied to efficiently generate a large dataset from an FAC test to develop a wall thinning rate prediction model for a real situation.

• Annual Conference on Human and Language Technology
• /
• 2022.10a
• /
• pp.354-359
• /
• 2022

에세이 자동 평가는 주어진 에세이를 읽고 자동으로 평가하는 작업이다. 본 논문에서는 효과적인 에세이 자동 평가 모델을 위해 Argument Mining 작업을 사용하여 에세이의 논증 구조가 반영된 에세이 표현을 만들고, 에세이의 평가 항목별 표현을 학습하는 방법을 제안한다. 실험을 통해 제안하는 에세이 표현이 사전 학습 언어 모델로 얻은 표현보다 우수함을 입증했으며, 에세이 평가를 위해 평가 항목별로 다른 표현을 학습하는 것이 보다 효과적임을 보였다. 최종 제안 모델의 성능은 QWK 기준으로 0.543에서 0.627까지 향상되어 사람의 평가와 상당히 일치한다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.5
• /
• pp.1390-1411
• /
• 2024

Underwater Wireless Sensors Networks (UWSNs) are deployed in remotely monitored environment such as water level monitoring, ocean current identification, oil detection, habitat monitoring and numerous military applications. Providing scalable and efficient routing is very challenging in UWSNs due to the harsh underwater environment. The biggest difficulties are the nodes inherent movement due to water current, long delay in data transmission, low bandwidth of the acoustic signal, high error rate and energy scarcity in battery powered nodes. Many routing protocols have been proposed to solve the aforementioned problems. There are three broad categories of routing protocols namely depth based, energy based and vector-based routing. Vector Based Forwarding protocols perform routing through virtual pipeline by defining their radius which give proper direction to packets communication. We proposed a routing protocol termed as Path-Oriented Energy Scaled Expanded Vector Based Forwarding (PESEVBF). PESEVBF takes into account all parameters; holding time, the source nodes packets routing path and void holes creation on the second hop; PESEVBF not only considers the packet upward advancement but also focus on density of the forwarded nodes in terms of number of potential forwarding and suppressed nodes for path selection. Node selection in resultant holding time is based on minimum Path Factor (PF) value. Moreover, the suppressed node will be selected for packet forwarding to avoid the void holes occurrences on the second hop. Performance of PESEVBF is compared with other routing protocols using matrices such as energy consumption, packet delivery ratio, packets dropping ratio and duplicate packets creation indicating considerable performance improvement.

• Journal of Energy Engineering
• /
• v.20 no.4
• /
• pp.292-297
• /
• 2011

Gas pipeline safety management and risk prediction are recognized as a very important issue. And the effort to prevent accidents is essential. So, in this study, it was studied through correlation of pressure changes for leak point detection in real-time. It experimented by installing the five leakage valves in the pipe of 378 m and compared the actual leak points with simulation results. The results showed that experimental leak points and the actual leak points have differences within the 6 m. And this technology has to be commercialized by the demonstration in dangerous zone.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.6
• /
• pp.1026-1031
• /
• 2008

Nowdays, homes and small businesses rely more and more PON(Passive Optical Networks) for financial transactions, private communications and even telemedicine. Thus, encryption for these data transactions is very essential due to the multicast nature of the PON In this parer, we presented our implementation of a counter mode AES based on Virtex4 FPGA. Our design exploits three advanced features; 1) Composite field arithmetic SubByte, 2) efficient MixColumn transformation 3) and on-the-fly key-scheduling for fully pipelined architecture. By pipeling the composite field implementation of the S-box, the area cost is reduced to average 17 percent. By designing the on-the-fly key-scheduling, we implemented an efficient key-expander module which is specialized for a pipelined architecture.

• Journal of Korean Society of Water and Wastewater
• /
• v.37 no.6
• /
• pp.347-361
• /
• 2023

Water utilities are making various efforts to reduce water losses from water networks, and an essential part of them is to recognize the moment when a pipe burst occurs during operation quickly. Several physics-based methods and data-driven analysis are applied using real-time flow and pressure data measured through a SCADA system or smart meters, and methodologies based on machining learning are currently widely studied. Water utilities should apply various approaches together to increase pipe burst detection. The most intuitive and explainable water balance method and its procedure were presented in this study, and the applicability and detection performance were evaluated by applying this approach to water supply pipelines. Based on these results, water utilities can establish a mass balance-based pipe burst detection system, give a guideline for installing new flow meters, and set the detection parameters with expected performance. The performance of the water balance analysis method is affected by the water network operation conditions, the characteristics of the installed flow meter, and event data, so there is a limit to the general use of the results in all sites. Therefore, water utilities should accumulate experience by applying the water balance method in more fields.