• Proceedings of the Korea Information Processing Society Conference
• /
• 2020.11a
• /
• pp.5-7
• /
• 2020

본 논문에서는 응급상황 발생 시, 응급 처치가 가능한 주변 사용자에게 알람을 보내 구급대원이 오기 전까지 응급 구조를 원활하게 도와주는 안드로이드 애플리케이션 시스템 구현 결과를 보인다. Google Map API를 이용하여 사용자의 위치를 실시간으로 지도에 표시한다. 그리고 FireBase Cloud Messaging API를 이용하여 애플리케이션 이용자들에게 알람을 보낸다. 또한, WebRTC API를 이용하여 애플리케이션 안에서 음성 및 영상 통화를 할 수 있다. 애플리케이션을 켜지 않아도 위젯을 활용하여 응급상황을 신고할 수 있도록 하여 애플리케이션의 활용성을 높였다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.05a
• /
• pp.312-313
• /
• 2021

가짜뉴스가 사회연결망 상에서 빠르게 전파되면서 사회적 혼란을 야기하고 있어 가짜뉴스를 탐지하는 것이 중요한 문제로 대두되고 있다. 최근 가짜뉴스 탐지 연구에서 사회연결망의 전파 정보를 활용한 방법이 기존 뉴스 컨텐츠 기반 가짜뉴스 탐지 방법보다 효과적임을 보였다. 따라서 본 논문에서는 기존 CoAID 데이터셋을 기반으로 사회연결망상의 전파 데이터를 포함하는 COVID-19 Cascade 데이터셋을 소개한다. COVID-19 Cascade 를 활용하면 전파 기반 가짜뉴스 탐지 방법에도 적용이 가능하다. 이후 간단한 분석을 통해 진짜뉴스와 가짜뉴스의 차이를 확인한다.

• Journal of Information Processing Systems
• /
• v.19 no.3
• /
• pp.323-333
• /
• 2023

Facial expression recognition can aid in the development of fatigue driving detection, teaching quality evaluation, and other fields. In this study, a facial expression recognition method was proposed with a residual masking reconstruction network as its backbone to achieve more efficient expression recognition and classification. The residual layer was used to acquire and capture the information features of the input image, and the masking layer was used for the weight coefficients corresponding to different information features to achieve accurate and effective image analysis for images of different sizes. To further improve the performance of expression analysis, the loss function of the model is optimized from two aspects, feature dimension and data dimension, to enhance the accurate mapping relationship between facial features and emotional labels. The simulation results show that the ROC of the proposed method was maintained above 0.9995, which can accurately distinguish different expressions. The precision was 75.98%, indicating excellent performance of the facial expression recognition model.

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.2
• /
• pp.83-90
• /
• 2015

Almost of current Automatic Incident Detection(AID) algorithms involve the vulnerability that detects the traffic accident in open road or in tunnel as the traffic jam not as the traffic accident. This paper proposes the improved accident detection algorithm to enhance the detection probability based on accident detection algorithms applied in open roads. The improved accident detection algorithm provides the preliminary judgment of potential accident by detecting the stopped object by Gaussian Mixture Model. Afterwards, it measures the detection area is divided into blocks so that the occupancy rate can be determined for each block. All experimental results of applying the new algorithm on a real incident was detected image without error.

• Transactions of Materials Processing
• /
• v.9 no.4
• /
• pp.404-412
• /
• 2000

It is desirable to use the square grid analysis with the aid of the stereo vision and image processing techniques in order to automatically measure the surface-strain distribution over a stamped part. But this method has some inherent problems such as the difficulty in enhancement of bad images, the measurement error due to the digital image resolution and the limit of the area that can be measured at a time. Therefore, it is still hard to measure the strain distribution over the entire surface of a medium-or large-sized stamped part even by using an automated strain measurement system. In this study, several methods which enable to solve these problems considerably without losing accuracy and precision In measurement are suggested. The superposition of images that have different high-lightened or damaged part from each other gives much enhanced image. A new algorithm for constructing of the element connectivity from the line-thinned image helps recognize up to 1,000 elements. And the geometry assembling algorithm including the global error minimization makes it possible to measure a large specimen with reliability and efficiency.

• Bulletin of the Korean Chemical Society
• /
• v.35 no.10
• /
• pp.3005-3008
• /
• 2014

Human ChlR1 protein (hChlR1), a member of the cohesion establishment factor family, plays an important role in the segregation of sister chromatids for maintenance of genome integrity. We previously reported that hChlR1 interacts with hFen1 and stimulates its nuclease activity on the flap-structured DNA substrate covered with RPA. To elucidate the relationship between hChlR1 and Okazaki fragment processing, the effect of hChlR1 on in vitro nuclease activities of hFen1 and hDna2 was examined. Independent of ATPase activity, hChlR1 stimulated endonuclease activity of hFen1 but not that of hDna2. Our findings suggest that the acceleration of Okazaki fragment processing near cohesions may aid in reducing the size of the replication machinery, thereby facilitating its entry through the cohesin ring.

• International journal of advanced smart convergence
• /
• v.11 no.2
• /
• pp.7-12
• /
• 2022

Safety and security are the topmost priority in every environment. With the aid of Artificial Intelligence (AI), many objects are becoming more intelligent, conscious, and curious of their surroundings. The recent scientific breakthroughs in autonomous vehicular designs and development; powered by AI, network of sensors and the rapid increase of Internet of Things (IoTs) could be utilized in maintaining safety and security in our environments. AI based on deep learning architectures and models, such as Deep Neural Networks (DNNs), is being applied worldwide in the automotive design fields like computer vision, natural language processing, sensor fusion, object recognition and autonomous driving projects. These features are well known for their identification, detective and tracking abilities. With the embedment of sensors, cameras, GPS, RADAR, LIDAR, and on-board computers in many of these autonomous vehicles being developed, these vehicles can properly map their positions and proximity to everything around them. In this paper, we explored in detail several ways in which these enormous features embedded in these autonomous vehicles, such as the network of sensors fusion, computer vision and natural image processing, natural language processing, and activity aware capabilities of these automobiles, could be tapped and utilized in safeguarding our lives and environment.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2023.11a
• /
• pp.235-236
• /
• 2023

The process of construction site supervision plays a crucial role in ensuring safety and quality assurance in construction projects. However, traditional methods of supervision largely depend on human vision and individual experience, posing limitations in quickly detecting and preventing all defects. In particular, the thorough supervision of expansive sites is time-consuming and makes it challenging to identify all defects. This study proposes a new construction supervision system that utilizes vision processing technology and Artificial Intelligence(AI) to automatically detect and analyze defects as a solution to these issues. The system we developed is provided in the form of an application that operates on portable devices, designed to a lower technical barrier so that even non-experts can easily aid construction site supervision. The developed system swiftly and accurately identifies various potential defects at the construction site. As such, the introduction of this system is expected to significantly enhance the speed and accuracy of the construction supervision process.

• Progress in Medical Physics
• /
• v.3 no.1
• /
• pp.71-78
• /
• 1992

This study describes the design of the biophysiological signal processing analyzer which can collect and analyze the biosignal raw data. System hardware is consisted of the IBM PC AT. pre-amplifier. AID converter, Counter/Timer. and RS-232C processor. Biophysiological signal data were processed by the software digital filter. FFT and graphic processing routine. The tachogram and FFT of the the peak to peak interval time was accomplished by the Graphic user interface software using the biophysiological signal processed data. Using this system. the powerspectrum of the heart rate variability during the long term could be observed. Experimental results of this system approach our purpose. which is improved the cost performance. easy to use. reducing raw-data noise and optimizing model for digital filter.

• Journal of Korea Foundry Society
• /
• v.26 no.1
• /
• pp.17-26
• /
• 2006

The substitution of cooling method from water quenching to air cooling after solution heat treatment was aimed for the development of a convenient and economical heat treatment process of duplex stainless steels without deterioration of mechanical and corrosion resistant properties for the industry. In order to achieve this goal, the mechanical properties and corrosion properties of a ASTM A890-4A duplex stainless steel were systematically investigated as functions of casting condition and cooling method after solution heat treatment. A 3-stepped sand mold and a permanent Y-block mold were used to check the effects of solidification structure and cooling rate after solution heat treatment. The microstructural characteristics such as the ferrite/austenite phase ratio and the precipitation behavior of ${\sigma}$ phase and carbides were investigated by combined analysis of OM and SEM-EDX with an aid of TTT diagram. Hardness and tension test were performed to evaluate the mechanical properties. Impact property at $-40^{\circ}C$ and corrosion resistance were also examined to check the possibility of the industrial application of this basic study. Throughout this investigation, air-cooling method was proved to effectively substitute for water-quenching process after the solution heat treatment, when the duplex stainless steel was sand mold cast with a thickness below 15 mm or permanent mold cast with a thickness below 20 mm.