• 토지주택연구
• /
• 제11권4호
• /
• pp.99-104
• /
• 2020

This paper presents the recent research developments identified through a review of literature on the application of artificial intelligence in developing automated designs of fire protection facilities. The literature review covered research related to image recognition and applicable neural networks. Firstly, it was found that convolutional neural network (CNN) may be applied to the development of automating the design of fire protection facilities. It requires a high level of object detection accuracy necessitating the classification of each object making up the image. Secondly, to ensure accurate object detection and building information, the data need to be pulled from architectural drawings. Thirdly, by applying image recognition and classification, this can be done by extracting wall and surface information using dimension lines and pixels. All combined, the current review of literature strongly indicates that it is possible to develop automated designs for fire protection utilizing artificial intelligence.

• IEIE Transactions on Smart Processing and Computing
• /
• 제3권4호
• /
• pp.195-204
• /
• 2014

This paper presents the depth evaluation for object detection by automated assembling robots. Pattern distortion analysis from a structured light system identifies an object with the greatest depth from its background. An automated assembling robot should prior select and pick an object with the greatest depth to reduce the physical harm during the picking action of the robot arm. Object detection is then combined with a depth evaluation to provide contour, showing the edges of an object with the greatest depth. The contour provides shape information to an automated assembling robot, which equips the laser based proxy sensor, for picking up and placing an object in the intended place. The depth evaluation process using structured light for an automated electronics assembling robot is accelerated for an image frame to be used for computation using the simplest experimental set, which consists of a single camera and projector. The experiments for the depth evaluation process required 31 ms to 32 ms, which were optimized for the robot vision system that equips a 30-frames-per-second camera.

• Journal of Information Processing Systems
• /
• 제15권1호
• /
• pp.100-115
• /
• 2019

Malicious code distribution on the Internet is one of the most critical Internet-based threats and distribution technology has evolved to bypass detection systems. As a new defense against the detection bypass technology of malicious attackers, this study proposes the automated tracing of malicious websites in a malware distribution network (MDN). The proposed technology extracts automated links and classifies websites into malicious and normal websites based on link structure. Even if attackers use a new distribution technology, website classification is possible as long as the connections are established through automated links. The use of a real web-browser and proxy server enables an adequate response to attackers' perception of analysis environments and evasion technology and prevents analysis environments from being infected by malicious code. The validity and accuracy of the proposed method for classification are verified using 20,000 links, 10,000 each from normal and malicious websites.

• 한국측량학회지
• /
• 제23권3호
• /
• pp.331-340
• /
• 2005

수치지도는 지형도 제작뿐만 아니라 지리정보체계 구축 및 활용, 토목설계 및 시공, 국토계획 등 다양한 분야의 기본이 되는 중요한 디지틸 지리정보이다. 따라서 정확도가 높은 수치지도의 제작은 지킥정보체계의 활용성을 높이고 디지틸국토를 완성하기 위한 필요조건이다. 본 연구는 수치지도 Ver2.0 제작 시 정위치 편집과 구조화 편집 이후에 이루어지는 검수 공정을 자동화시컥 전수 검수가 가능하도록 하여 오류가 최소화된 수치지도가 생산될 수 있도록 했으며, 이 때 오류를 자동으로 인식하고 탐색하여 유형별로 분류한 뒤 해결방법까지 제시하는 자동 오류검출 방법을 적용시켜 기존 기술에 비해 정확성, 효율성과 경제성을 높였다.

• 대한임상검사과학회지
• /
• 제38권3호
• /
• pp.152-157
• /
• 2006

The purpose of this study was to evaluate the usefulness of the automated TB-PCR assay for the detection of Mycobacterium tuberculosis. The 807 cases were analyzed with their TB-PCR, AFB smear and culture in bronchial washing fluids, sputum and body fluids samples. The TB-PCR positive of the bronchial washing fluid, sputum and body fluids were 11.3%, 7.3% and 3.6%, respectively, in cases of AFB smear-negative and culture-negative. The sensitivity values of the bronchial washing fluid, sputum and body fluids were 93.3%, 100% and 50%, respectively, according to the culture result. The sensitivity of body fluids was lower than that of the bronchial washing fluid and sputum. The specificity values of the bronchial washing fluid, sputum and body fluids were 83.3%, 89.0% and 95.7%, respectively, according to the culture result. In conclusion, the automated TB-PCR assay proved to be a useful method for the detection of Mycobacterium tuberculosis in the bronchial washing fluid and sputum. But we think that there is still a need for us to study body fluids further.

• 한국건축시공학회:학술대회논문집
• /
• 한국건축시공학회 2022년도 봄 학술논문 발표대회
• /
• pp.133-134
• /
• 2022

This study proposed vision artificial intelligence-based automated supervision technology for external insulation and finishing system, and basic research was conducted for it. The automated supervision technology proposed in this study consists of the object detection model (YOLOv5) and the part that derives necessary information based on the object detection result and then determines whether the external insulation-related adhesion regulations are complied with. As a result of a test, the judgement accuracy of the proposed model showed about 70%. The results of this study are expected to contribute to securing the external insulation quality and further contributing to the realization of energy-saving eco-friendly buildings. As further research, it is necessary to develop a technology that can improve the accuracy of the object detection model by supplementing the number of data for model training and determine additional related regulations such as the adhesive area ratio.

• 정보과학회 논문지
• /
• 제43권10호
• /
• pp.1173-1178
• /
• 2016

2001년 비트토렌트 프로토콜이 설계된 후로 음악, 영화, 소프트웨어 등 모든 것을 다운로드할 수 있게 되었다. 이를 통해 저작권이 있는 파일이 무분별하게 공유가 되었고 저작권자들은 많은 피해를 입었다. 이 문제를 해결하기 위해 국가에서는 관련법을 제정하였고 ISP는 불법 사이트를 차단하였다. 이러한 노력들에도 불구하고 pirate bay와 같은 불법 사이트들은 도메인을 바꾸는 등 쉽게 사이트를 재오픈하고 있다. 이에 우리는 재오픈된 불법 사이트를 쉽게 탐지하는 기술을 제안한다. 이 자동화 기술은 구글 검색엔진을 이용하여 도메인을 수집하고, 최장공통부분수열(LCS) 알고리즘을 이용하여 기존 웹페이지 태그와 검색된 웹페이지 태그를 비교, 유사도를 측정한다. 실험을 위해 총 2,383개의 검색 결과를 구글 검색으로 얻었다. LCS 유사도 알고리즘을 적용하여 검사한 결과 44개의 해적 사이트를 탐지하였다. 또한 해외 불법 사이트에 적용한 결과 805개 검색 도메인에서 23개의 불법 사이트를 탐지하였다. 이를 통해 제안된 탐지 자동화 기술을 사용한다면 불법 사이트가 재 오픈을 하더라도 쉽게 탐지할 것으로 보인다.

• Journal of Biosystems Engineering
• /
• 제31권2호
• /
• pp.128-134
• /
• 2006

Frequent outbreaks of foodborne illness demand the need for rapid and sensitive methods for detection of these pathogens. Recent development of biosensor technology has a great potential to meet the need for rapid and sensitive pathogens detection from foods. An antibody-based fiber-optic biosensor and an automated reagents supply system to detect Listeria monocytogenes were developed. The biosensor for detection of Listeria monocytogenes in PBS and bacteria spiked food samples was evaluated. The automated reagents supply system eliminated cumbersome sample and detection antibody injection procedures that had been done manually. The biosensor could detect $10^4$ cfu/ml of Listeria monocytogenes in PBS. By using the fiber-optic biosensor, $2x10^8$ cfu/ml of Listeria monocytogenes in the food samples were detectable.

• 대한원격탐사학회지
• /
• 제22권5호
• /
• pp.337-350
• /
• 2006

The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.

• International Journal of Computer Science & Network Security
• /
• 제22권4호
• /
• pp.374-386
• /
• 2022

Nowadays, research in deep learning leveraged automated computing and networking paradigm evidenced rapid contributions in terms of Software Defined Networking (SDN) and its diverse security applications while handling cybercrimes. SDN plays a vital role in sniffing information related to network usage in large-scale data centers that simultaneously support an improved algorithm design for automated detection of network intrusions. Despite its security protocols, SDN is considered contradictory towards DDoS attacks (Distributed Denial of Service). Several research studies developed machine learning-based network intrusion detection systems addressing detection and mitigation of DDoS attacks in SDN-based networks due to dynamic changes in various features and behavioral patterns. Addressing this problem, this research study focuses on effectively designing a multistage hybrid and intelligent deep learning classifier based on modified deep forest classification to detect DDoS attacks in SDN networks. Experimental results depict that the performance accuracy of the proposed classifier is improved when evaluated with standard parameters.