• Journal of the Korean Society for Precision Engineering
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• v.12 no.9
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• pp.52-58
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• 1995

Conventional measurement methods for non-destructive testing(NDT) in nuclear power plants and other industrial plants have been performed as the methods of contact with objects to be inspect, but those methods have been taken relatively much time to be inspected. Holographic interferometry which is a non-contact optical measurement method using a coherent light can overcome these demerit, and also has an advantage that the quantitative measurement of small deformation for large areas can be accomplished at a time with high precision. In this paper the comparisons of the experimental results form holographic interferometry with those from the finite element method(FEM) and the analytical solutions of the elastic equation are discussed.

• ETRI Journal
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• v.44 no.1
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• pp.155-167
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• 2022

The Internet of Things (IoT) is a new paradigm that connects physical and virtual objects from various domains such as home automation, industrial processes, human health, and monitoring. IoT sensors receive information from their environment and forward it to their neighboring nodes. However, the large amounts of exchanged data are vulnerable to attacks that reduce the network performance. Most of the previous security methods for IoT have neglected the energy consumption of IoT, thereby affecting the performance and reducing the network lifetime. This paper presents a new multistep routing protocol based on cellular learning automata. The network lifetime is improved by a performance-based adaptive reward and fine parameters. Nodes can vote on the reliability of their neighbors, achieving network reliability and a reasonable level of security. Overall, the proposed method balances the security and reliability with the energy consumption of the network.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.709-712
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• 2020

영상 처리 응용을 위해 개발된 대부분의 CNN 기반 객체 탐지 기법은 mAP 를 올리기 위해 작은 객체 탐지에 더 주력하는 경향이 있다. 본 연구에서는 이미지 피라미드를 통한 서로 다른 해상도의 탐지 결과를 앙상블을 하여 작은 객체의 탐지 성능은 유지하면서 큰 객체의 탐지 성능을 향상시키고자 한다. 또한, 기존 NMS 방식의 문제점을 파악하고 새로운 NMS 방식인 G-NMS 를 제안한다. COCO 데이터로 실험 결과 서로 다른 해상도의 탐지 결과 앙상블을 통하여 30fps 이상의 실시간 탐지를 만족하면서 큰 객체에 대한 AP 가 0.5~1.5% 상승되었음을 확인하였다. 제안한 G-NMS 방식 적용시 큰 객체에 대한 AR 이 2.6~3.8% 상승되었으며, 작은 객체를 포함한 전체 mAP 가 0.7~0.9% 상승되었음을 확인하였다.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.1
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• pp.77-88
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• 1993

In this paper, we propose a stereo vision system to solve correspondence problem with large disparity and sudden change in environment which result from small distance between camera and working objects. First of all, a specific feature is divided by predfined elementary feature. And then these are combined to obtain coded data for solving correspondence problem. We use Neural Network to extract elementary features from specific feature and to have adaptability to noise and some change of the shape. Fourier transformation and Log-polar mapping are used for obtaining appropriate Neural Network input data which has a shift, scale, and rotation invariability. Finally, we use associative memory to obtain coded data of the specific feature from the combination of elementary features. In spite of specific feature with some variation in shapes, we could obtain satisfactory 3-dimensional data from corresponded codes.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.6
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• pp.128-134
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• 1997

Holographic interferometry is a useful whole-field nondestructive tesing method for measuring deformations and vibrations of engineering structure. In practical way most holographic interferometer uses a diverging beam, a point light source. When an oject is relatively small, the optical arrangement using a collimated light source has no difficulty technically but for a large object the collimated beam connot be applied anymore practically. In this paper we calculate the error of measured displacement from the sensi- tivity vector dominated by the geometry of optical arrangement for holographic interferometer and show the result with 2-D plots. A plane surface and a cylindrical surface were chosen as objects to be measured and the results from the cases of a diverging and a collimated beams were compared and analyzed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.69-71
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• 2022

Today, the AI market is very large due to the development of AI. Among them, the most advanced AI is image detection. Thus, there are many object detection models using YOLOv5.However, most object detection in AI is focused on detecting objects that are stereotyped.In order to recognize such unstructured data, the object may be recognized by learning and filtering the object. Therefore, in this paper, a fire monitoring system using YOLOv5 was designed to detect and analyze unstructured data fires and suggest ways to improve the fire object detection model.

• Journal of applied mathematics & informatics
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• v.41 no.6
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• pp.1327-1339
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• 2023

World Wide Web (WWW) use has been increasing recently due to users needing more information. Lately, there has been a growing trend in the document information available to end users through the internet. The web's document search process is essential to find relevant documents for user queries.As the number of general web pages increases, it becomes increasingly challenging for users to find records that are appropriate to their interests. However, using existing Document Information Retrieval (DIR) approaches is time-consuming for large document collections. To alleviate the problem, this novel presents Spatial Clustering Ranking Pattern (SCRP) based Density Ant Colony Information Retrieval (DACIR) for user queries based DIR. The proposed first stage is the Term Frequency Weight (TFW) technique to identify the query weightage-based frequency. Based on the weight score, they are grouped and ranked using the proposed Spatial Clustering Ranking Pattern (SCRP) technique. Finally, based on ranking, select the most relevant information retrieves the document using DACIR algorithm.The proposed method outperforms traditional information retrieval methods regarding the quality of returned objects while performing significantly better in run time.

• Elastomers and Composites
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• v.59 no.1
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• pp.22-33
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• 2024

Passive radiative cooling is a promising technology for cooling objects without energy input. Passive radiative cooling works by radiating heat from the surface, which then passes through the atmosphere and into space. Achieving efficient passive radiative cooling is mainly accomplished by using materials with high emissivity in the atmospheric window (8-13 ㎛). Research has shown that polymers tend to exhibit high emissivity in this spectral range. In addition to elastomers, other materials with potential for passive radiative cooling include metal oxides, carbon-based materials, and polymers. The structure of a passive radiative cooling device can affect its cooling performance. For example, a device with a large surface area will have a greater amount of surface area exposed to the sky, which increases the amount of thermal radiation emitted. Passive radiative cooling has a wide range of potential applications, including building cooling, electronics cooling, healthcare, and transportation. Current research has focused on improving the efficiency of passive radiative cooling materials and devices. With further development, passive radiative cooling can significantly affect a wide range of sectors.

• Acta Via Serica
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• v.8 no.2
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• pp.95-124
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• 2023

Over the past 30 years, intense archaeological research has revealed a great increase in regional and transregional object mobility across the South China Sea during its Iron Age (500 BCE to 500 CE). Some objects had moved from a long distance: intaglios, seals, fine ceramic, glass containers, and gold coins of Mediterranean origin; and large bronzes, mirrors, and lacquerware connected to central East Asia. This evidence has given rise to larger-scale explanations, among which the most prominent has been the growth of (maritime) Silk Road trade. Scholars are divided as to whether the Silk Road is a suitable concept, with some emphasizing its orientalist overtones and colonial baggage and others finding it useful for the investigation of interregional networks trading in silk and other commodities. This paper explores how productive the Silk Road concept or metaphor really is for understanding transregional connectivity and social change in Iron Age Southeast Asia.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.183-193
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• 2024

Recurrent Neural Network technology that learns past patterns and predicts future patterns using technology for recognizing and classifying objects is being applied to various industries, economies, and languages. And research for practical use is making a lot of progress. However, research on the application of Recurrent Neural Networks for evaluating and predicting the safety of mechanical structures is insufficient. Accurate detection of external load applied to the outside is required to evaluate the safety of mechanical structures. Learning of Recurrent Neural Networks for this requires a large amount of load data. This study applied the Gated Recurrent Unit technique to examine the possibility of load learning and investigated the possibility of applying a stacked Auto Encoder as a way to secure load data. In addition, the usefulness of learning mechanical loads was analyzed with the Gated Recurrent Unit technique, and the basic setting of related functions and parameters was proposed to secure accuracy in the recognition and prediction of loads.