• 센서학회지
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• 제24권3호
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• pp.169-174
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• 2015

In this study, we developed a system to detect the various defects in the metallic objects using the phenomenon that the defects cause the changes of the natural resonant frequencies. Our system consists of a FFT Amp, an Auto Impact Hammer, a Hammer controller and a PC. Auto Impact Hammer creates vibrations in the metallic objects when tapped on the surface. These vibrational signals are converted to the voltage signals by an acceleration sensor attached to the metallic part surface. These analog voltage signals were fed into an ADC (analog-digital converter) and an FFT (fast fourier transform) conversion in the FFT Amp to obtain the digital data in the frequency domain. Labview graphical program was used to process the digital data from th FFT amp to display the spectrum. We compared those spectra with the standard spectrum to find the shifts in the resonant frequencies of the metal parts, and thus detecting the defects. We used PCB's acceleration sensor and TI's TMS320F28335 DSP (digital signal processor) to obtain the resolution of 2.93 Hz and to analyze the frequencies up to 44 kHz.

• Imaging Science in Dentistry
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• 제34권3호
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• pp.117-122
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• 2004

Purpose : To determine the proper image compression method and ratio without image quality degradation in intraoral digital radiographic images, comparing the discrete cosine transform (DCT)-based JPEG with the wavelet-based JPEG 2000 algorithm. Materials and Methods : Thirty extracted sound teeth and thirty extracted teeth with occlusal caries were used for this study. Twenty plaster blocks were made with three teeth each. They were radiographically exposed using CDR sensors (Schick Inc., Long Island, USA). Digital images were compressed to JPEG format, using Adobe Photoshop v.7.0 and JPEG 2000 format using Jasper program with compression ratios of 5 : 1,9 : 1, 14 : 1,28 : 1 each. To evaluate the lesion detectability, receiver operating characteristic (ROC) analysis was performed by the three oral and maxillofacial radiologists. To evaluate the image quality, all the compressed images were assessed subjectively using 5 grades, in comparison to the original uncompressed images. Results: Compressed images up to compression ratio of 14 : 1 in JPEG and 28 : 1 in JPEG 2000 showed nearly the same the lesion detectability as the original images. In the subjective assessment of image quality, images up to compression ratio of 9 : 1 in JPEG and 14 : 1 in JPEG 2000 showed minute mean paired differences from the original Images. Conclusion : The results showed that the clinically acceptable compression ratios were up to 9 : 1 for JPEG and 14 : 1 for JPEG 2000. The wavelet-based JPEG 2000 is a better compression method, comparing to DCT-based JPEG for intraoral digital radiographic images.

• Journal of the Optical Society of Korea
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• 제19권6호
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• pp.629-637
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• 2015

Compact system cameras (CSCs) are commonly used nowadays and feature enhanced video functions and thin yet light interchangeable lenses. They differ from digital single-lens reflex (DSLR) cameras in their lack of mirror boxes. CSCs, however, have autofocus (AF) speeds lower than those of conventional DSLRs, requiring weight reduction of their AF groups. To ensure the marketability of large telephoto zoom lenses with fixed f/2.8 regardless of field angle variation, in particular, light weight AF groups are essential. In this paper, we introduce a paraxial optical design method and present a new, large, telephoto zoom lens with f/2.8 regardless of the field angle variation, plus a lightweight AF group consisting of only one lens. Using the basic paraxial optical design and optimization methods, we fabricated a new and lighter zoom lens system, including a single-lens, lightweight AF group with almost the same performance.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 춘계학술대회 및 창립 30주년 심포지엄(논문집)
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• pp.77-85
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• 2006

이 연구의 최종목적은 기존의 선박용 자기 컴퍼스를 대체할 수 있는 디지털 컴퍼스 개발에 있다. 우선, 3축의 고정밀 프럭스-게이트 센서와 소형 스텝 모터를 이용하여 새로운 디지털 컴퍼스 장치를 개발하였다. 그리고 기존 자차측정 방법과 달리 선박의 선회 없이 자동으로 자차를 분석하고 수정하며 갱신할 수 있는 자차수정 이론을 제안하였다. 실습선 '새누리호'를 이용한 성능평가 실험을 통하여 개발한 디지털 컴퍼스와 제안한 자차수정 방법의 유효성을 검증하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2019년도 춘계학술대회
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• pp.283-284
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• 2019

In the last decades patient's suffering with Parkinson's disease is increasing at a rapid rate and as per prediction it will grow more rapidly as old age population is increasing at a rapid rate through out the world. As the performance of wearable sensor based approach reached to a new height as well as powerful machine learning technique provides more accurate result these combination has been widely used for assessment of various neurological diseases. ON state is the state where the effect of medicine is present and OFF state the effect of medicine is reduced or not present at all. Classification of ON/OFF state for the Parkinson's disease is important because the patients could injure them self due to freezing of gait and gait related problems in the OFF state. in this paper wearable sensor based approach has been used to collect the data in ON and OFF state and machine learning techniques are used to automate the classification based on the gait pattern. Supervised machine learning techniques able to provide 97.6% accuracy while classifying the ON/OFF state.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 춘계학술발표대회
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• pp.273-276
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• 2023

This paper presents the integration of Digital twin and Blockchain-based Supply Chain Management (DB-SCM) in a smart warehouse to create a more efficient, secure, and transparent facility. The process involves creating a digital twin of the warehouse using sensors and IoT devices and then integrating it with a blockchain-based supply chain management system to connect all stakeholders. All data are collected and tracked in real-time as goods move through the warehouse, and smart contracts are automatically executed to ensure accountability for all parties involved. The study also highlights the critical role of effective supply chain management in modern business operations and the significance of smart warehouses, which leverage advanced technologies such as robotics, AI, and data analytics to optimize warehouse operations. Later, we discuss the importance of digital twins, which allow for creating a virtual representation of a physical object or system, and their potential to revolutionize a wide range of industries. Therefore, DB-SCM offers numerous benefits, including enhanced efficiency, improved customer satisfaction, and increased sustainability, and provides a valuable case study for organizations seeking to optimize their supply chain operations.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.147-154
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• 2024

The continuous increase in urban population due to migration of mases from rural areas to big cities has set urban water supply under serious stress. Urban water resources face scarcity of available water quantity, which ultimately effects the water supply. It is high time to address this challenging problem by taking appropriate measures for the improvement of water utility services linked with better understanding of demand side management (DSM), which leads to an effective state of water supply governance. We propose a dynamic framework for preventive DSM that results in optimization of water resource management. This paper uses Agent Based Modeling (ABM) with Digital Twin (DT) to model water consumption behavior of a population and consequently forecast water demand. DT creates a digital clone of the system using physical model, sensors, and data analytics to integrate multi-physical quantities. By doing so, the proposed model replicates the physical settings to perform the remote monitoring and controlling jobs on the digital format, whilst offering support in decision making to the relevant authorities.

• 디지털융복합연구
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• 제14권3호
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• pp.373-379
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• 2016

국내에서 주 5일제 근무가 시행되어 많은 사람들이 주말을 즐기기 위해 취미활동이나 레저활동 혹은 캠핑 등에 관심이 집중되고 있다. 또한 최근 출퇴근을 위한 퍼스널 모빌리티 제품도 샤오미를 통한 가격 인하 제품의 출시로 직장인들에게 많이 판매되고 있다. 이러한 시점에서 본 연구는 레저활동이나 혹은 퍼스널 모빌리티 제품 사용에 있어서의 안전을 위한 자이로스코프 센서를 이용한 방향지시등의 개발을 목적으로 하고 있다. 현재 레저활동이나 퍼스널 모빌리티 제품의 안전을 위한 방향지시등의 제작 사례와 문제점등을 알아 보고 그것을 보완할 수 있는 사용자의 안전을 위한 방향지시등 개발을 개발하였다. 그모양은 원형의 링으로 LED를 사용하여 사용자의 움직임 방향을 후측방에 지시할 수 있다. 이러한 연구는 퍼스널모빌리티 제품을 사용하는 사용자를 위한 하나의 해결책이 될 수있다.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• 대한조선학회논문집
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• 제61권3호
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• pp.143-151
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• 2024

In this study, we present a mapping framework for 3D spatial reconstruction of digital twin model using navigation and perception sensors mounted on an Autonomous Surface Vehicle (ASV). For improving the level of realism of digital twin models, 3D spatial information should be reconstructed as a digitalized spatial model and integrated with the components and system models of the ASV. In particular, for the 3D spatial reconstruction, color and 3D point cloud data which acquired from a camera and a LiDAR sensors corresponding to the navigation information at the specific time are required to map without minimizing the noise. To ensure clear and accurate reconstruction of the acquired data in the proposed mapping framework, a image preprocessing was designed to enhance the brightness of low-light images, and a preprocessing for 3D point cloud data was included to filter out unnecessary data. Subsequently, a point matching process between consecutive 3D point cloud data was conducted using the Generalized Iterative Closest Point (G-ICP) approach, and the color information was mapped with the matched 3D point cloud data. The feasibility of the proposed mapping framework was validated through a field data set acquired from field experiments in a inland water environment, and its results were described.