• Title/Summary/Keyword: performance monitor

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Machine Learning-based Detection of HTTP DoS Attacks for Cloud Web Applications (머신러닝 기반 클라우드 웹 애플리케이션 HTTP DoS 공격 탐지)

  • Jae Han Cho;Jae Min Park;Tae Hyeop Kim;Seung Wook Lee;Jiyeon Kim
    • Smart Media Journal
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    • v.12 no.2
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    • pp.66-75
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    • 2023
  • Recently, the number of cloud web applications is increasing owing to the accelerated migration of enterprises and public sector information systems to the cloud. Traditional network attacks on cloud web applications are characterized by Denial of Service (DoS) attacks, which consume network resources with a large number of packets. However, HTTP DoS attacks, which consume application resources, are also increasing recently; as such, developing security technologies to prevent them is necessary. In particular, since low-bandwidth HTTP DoS attacks do not consume network resources, they are difficult to identify using traditional security solutions that monitor network metrics. In this paper, we propose a new detection model for detecting HTTP DoS attacks on cloud web applications by collecting the application metrics of web servers and learning them using machine learning. We collected 18 types of application metrics from an Apache web server and used five machine learning and two deep learning models to train the collected data. Further, we confirmed the superiority of the application metrics-based machine learning model by collecting and training 6 additional network metrics and comparing their performance with the proposed models. Among HTTP DoS attacks, we injected the RUDY and HULK attacks, which are low- and high-bandwidth attacks, respectively. As a result of detecting these two attacks using the proposed model, we found out that the F1 scores of the application metrics-based machine learning model were about 0.3 and 0.1 higher than that of the network metrics-based model, respectively.

Analysis and Evaluation of CPC / COLSS Related Test Result During YGN 3 Initial Startup (영광 3호기 초기 시운전 동안 CPC / COLSS 관련시험 결과 분석 및 평가)

  • Chi, S.G.;Yu, S.S.;In, W.K.;Auh, G.S.;Doo, J.Y.;Kim, D.K.
    • Nuclear Engineering and Technology
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    • v.27 no.6
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    • pp.877-887
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    • 1995
  • YGN 3 is the first nuclear power plant to use the Core Protection Calculator (CPC) as the core protection system and the Core Operating Limit Supervisory System (COLSS) as the core monitor-ing system in Korea. The CPC is designed to provide on-line calculations of Departure from Nucleate Boiling Ratio (DNBR) and Local Power Density (LPD) and to initiate reactor trip if the core conditions exceed the DNBR or LPD design limit. The COLSS is designed to assist the operator in implementing the Limiting Conditions for Operation (LCOs) in Technical Specifications for DNBR/Linear Heat Rate (LHR) margin, azimuthal tilt, and axial shape index and to provide alarm when the LCOs are reached. During YGN 3 initial startup testing, extensive CPC/COLSS related tests ore peformed to ver-ify the CPC/COLSS performance and to obtain optimum CPC/COLSS calibration constants at var, -ious core conditions. Most of test results met their specific acceptance criteria. In the case of missing the acceptance criteria, the test results ore analyzed, evaluated, and justified. Through the analysis and evaluation of each of the CPC/COLSS related test results, it can be concluded that the CPC/COLSS are successfully Implemented as designed at YGN 3.

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A comparative study of cavitation inception of naval ship's propeller using on-board noise and vibration signals (선체 부착 소음/진동 센서를 이용한 함정 추진기 캐비테이션 초생 분석 비교 연구)

  • Hongseok Jeong;Hanshin Seol
    • The Journal of the Acoustical Society of Korea
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    • v.42 no.3
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    • pp.243-249
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    • 2023
  • The occurrence of cavitation on the propeller is directly linked to the naval ship's survivability, and it is necessary to design a propeller shape that delays the cavitation inception. However, the propeller cavitation can occur under various operating conditions, thus it is important to identify whether the propeller cavitation exists during operation as well as in the design phase. To this end, it is necessary to use noise or vibration signals on board to monitor the cavitation inception. In this study, a hydrophone and an accelerometer were installed on the ship hull right above the propeller to compare the performance of analyzing cavitation inception between acoustic and vibration signals. Also, a high speed camera was used to visually observe the occurrence of cavitation through an observation window. The measured results showed that the spectral shapes between acoustic and vibration signals were different, but the level increases at each frequency band and the overall level of the frequency band from 1 kHz to 10 kHz showed a similar tendency. The Detection of Envelope Modulation On Noise (DEMON) analysis also showed similar results for both acoustic and vibration signals, confirming that both hydrophones and accelerometers can be utilized in the analysis of cavitation inception.

A Study on Class Sample Extraction Technique Using Histogram Back-Projection for Object-Based Image Classification (객체 기반 영상 분류를 위한 히스토그램 역투영을 이용한 클래스 샘플 추출 기법에 관한 연구)

  • Chul-Soo Ye
    • Korean Journal of Remote Sensing
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    • v.39 no.2
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    • pp.157-168
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    • 2023
  • Image segmentation and supervised classification techniques are widely used to monitor the ground surface using high-resolution remote sensing images. In order to classify various objects, a process of defining a class corresponding to each object and selecting samples belonging to each class is required. Existing methods for extracting class samples should select a sufficient number of samples having similar intensity characteristics for each class. This process depends on the user's visual identification and takes a lot of time. Representative samples of the class extracted are likely to vary depending on the user, and as a result, the classification performance is greatly affected by the class sample extraction result. In this study, we propose an image classification technique that minimizes user intervention when extracting class samples by applying the histogram back-projection technique and has consistent intensity characteristics of samples belonging to classes. The proposed classification technique using histogram back-projection showed improved classification accuracy in both the experiment using hue subchannels of the hue saturation value transformed image from Compact Advanced Satellite 500-1 imagery and the experiment using the original image compared to the technique that did not use histogram back-projection.

Researches on Tidal Flats in Korea (한국의 간석지 연구)

  • JANG, Dong-Ho
    • Journal of The Geomorphological Association of Korea
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    • v.18 no.4
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    • pp.59-78
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    • 2011
  • In this study, the tidal flat research history of South Korea was organized by type and period. South Korea's tidal flat research history was largely divided into four fields: sediment research of tidal flat, research using satellite imagery, research on the Quaternary environment change and tidal flats, and ecological research on tidal flats. The comprehensive review of the South Korean tidal flat research history showed that tidal flats had been researched on since the period of Japanese colonial period, but most of the past studies were related to fisheries. Then, in the 1960s, the studies started to focus on the reclaimed land created through reclamation projects. The research on tidal flats from a geomorphological perspective fundamentally started in the 1970s, and the importance of tidal flats became more widely known in the 1980s. Most of the studies then were about the sedimentary environment and the form of landform, the ecosystem, and morphological changes. Since the 2000s, research has been carried out on satellite imagery data together with field survey, to continuously monitor the changes in the sedimentary facies of tidal flats, and in the sedimentary environment. There have been many academic studies on the geographic field of tidal flats, but the research performance on tidal flats in terms of geomorphology is still a blue ocean that has been touched by only a few. Therefore, it is hoped that various studies on Korean tidal flats will be conducted by geomorphologists in the future, and that such area will be established as an important field of study in geomorphology.

LAN Based MFD Interface for Integrated Operation of Radio Facilities using Fishery Vessel (어선용 무선설비의 통합운용을 위한 LAN 기반 MFD 인터페이스)

  • In-ung Ju;In-suk Kang;Jeong-yeon Kim;Seong-Real Lee;Jo-cheon Choi
    • Journal of Advanced Navigation Technology
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    • v.26 no.6
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    • pp.496-503
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    • 2022
  • In the reality that the fishing population is decreasing and the single-man fishing vessels is increasing, mandatory equipment for navigation and radio equipments for the safety of fishing boats has continued to be added. Therefore, many equipment such as navigation, communication and fishing are installed in the narrow steering room, so it is very confusing and a number of monitors are placed in the front, which is a factor that degrades the function of maritime observation. To solve this problem, we studied an interface that integrates and operates to major radio facilities such as very high frequency-digital selective calling equipment (VHF-DSC), automatic identification system (AIS) and fishing boat location transmission device (V-pass) into one multi function display (MFD) based on LAN. In addition, IEC61162-450 UDP packets and IEC61162 sentence were applied to exchange data through link between MFD and radio equipments, and additional messages needed for each equipment and function were defined. The integrated MFD monitor is easily operated by the menu method, and the performance of the interface was evaluated by checking the distress and emergency communication functions related to maritime safety and the message transmission status by equipment.

Intelligent Motion Pattern Recognition Algorithm for Abnormal Behavior Detections in Unmanned Stores (무인 점포 사용자 이상행동을 탐지하기 위한 지능형 모션 패턴 인식 알고리즘)

  • Young-june Choi;Ji-young Na;Jun-ho Ahn
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.73-80
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    • 2023
  • The recent steep increase in the minimum hourly wage has increased the burden of labor costs, and the share of unmanned stores is increasing in the aftermath of COVID-19. As a result, theft crimes targeting unmanned stores are also increasing, and the "Just Walk Out" system is introduced to prevent such thefts, and LiDAR sensors, weight sensors, etc. are used or manually checked through continuous CCTV monitoring. However, the more expensive sensors are used, the higher the initial cost of operating the store and the higher the cost in many ways, and CCTV verification is difficult for managers to monitor around the clock and is limited in use. In this paper, we would like to propose an AI image processing fusion algorithm that can solve these sensors or human-dependent parts and detect customers who perform abnormal behaviors such as theft at low costs that can be used in unmanned stores and provide cloud-based notifications. In addition, this paper verifies the accuracy of each algorithm based on behavior pattern data collected from unmanned stores through motion capture using mediapipe, object detection using YOLO, and fusion algorithm and proves the performance of the convergence algorithm through various scenario designs.

Smartphone-Attachable Vascular Compliance Monitoring Module (스마트폰 탈착형 혈관 탄성 모니터링 모듈)

  • Se-Hwan Yang;Ji-Yong Um
    • Journal of IKEEE
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    • v.28 no.2
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    • pp.221-227
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    • 2024
  • This paper presents a smartphone-attachable vascular compliance monitoring module. The proposed sensor module measures photoplethysmogram (PPG) and reconstructs an accelerated PPG waveform. The feature points are extracted from the accelerated PPG waves, and vascular compliance is estimated using these extracted features. The module is powered via the smartphone's USB terminal and transmits the acquired waveforms along with vascular compliance values through Bluetooth. The transmitted waveforms and vascular compliance value are displayed through the smartphone application. This work proposes an assessment method for consistency of PPG instrumentation, and it was implemented in a processor of sensor module. The proposed sensor module can be easily attached to smartphone that does not support PPG instrumentation, providing simple measurment and numerical analysis of vascular compliance. To verify the performance of the implemented sensor module, we acquired vascular compliance and pulse pressure data from 29 subjects. Pulse pressure, which serves as a representative indicator of vascular compliance, was obtained using a commercial blood pressure monitor. The analysis results showed that the Pearson coefficient between vascular compliance and pulse pressure was 0.778, confirming a relatively high correlation between two metrics.

Proposal for Research Model of High-Function Patrol Robot using Integrated Sensor System (통합 센서 시스템을 이용한 고기능 순찰 로봇의 연구모델 제안)

  • Byeong-Cheon Yoo;Seung-Jung Shin
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.24 no.3
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    • pp.77-85
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    • 2024
  • In this dissertation, a we designed and implemented a patrol robot that integrates a thermal imaging camera, speed dome camera, PTZ camera, radar, lidar sensor, and smartphone. This robot has the ability to monitor and respond efficiently even in complex environments, and is especially designed to demonstrate high performance even at night or in low visibility conditions. An orbital movement system was selected for the robot's mobility, and a smartphone-based control system was developed for real-time data processing and decision-making. The combination of various sensors allows the robot to comprehensively perceive the environment and quickly detect hazards. Thermal imaging cameras are used for night surveillance, speed domes and PTZ cameras are used for wide-area monitoring, and radar and LIDAR are used for obstacle detection and avoidance. The smartphone-based control system provides a user-friendly interface. The proposed robot system can be used in various fields such as security, surveillance, and disaster response. Future research should include improving the robot's autonomous patrol algorithm, developing a multi-robot collaboration system, and long-term testing in a real environment. This study is expected to contribute to the development of the field of intelligent surveillance robots.

Korean Food Review Analysis Using Large Language Models: Sentiment Analysis and Multi-Labeling for Food Safety Hazard Detection (대형 언어 모델을 활용한 한국어 식품 리뷰 분석: 감성분석과 다중 라벨링을 통한 식품안전 위해 탐지 연구)

  • Eun-Seon Choi;Kyung-Hee Lee;Wan-Sup Cho
    • The Journal of Bigdata
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    • v.9 no.1
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    • pp.75-88
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    • 2024
  • Recently, there have been cases reported in the news of individuals experiencing symptoms of food poisoning after consuming raw beef purchased from online platforms, or reviews claiming that cherry tomatoes tasted bitter. This suggests the potential for analyzing food reviews on online platforms to detect food hazards, enabling government agencies, food manufacturers, and distributors to manage consumer food safety risks. This study proposes a classification model that uses sentiment analysis and large language models to analyze food reviews and detect negative ones, multi-labeling key food safety hazards (food poisoning, spoilage, chemical odors, foreign objects). The sentiment analysis model effectively minimized the misclassification of negative reviews with a low False Positive rate using a 'funnel' model. The multi-labeling model for food safety hazards showed high performance with both recall and accuracy over 96% when using GPT-4 Turbo compared to GPT-3.5. Government agencies, food manufacturers, and distributors can use the proposed model to monitor consumer reviews in real-time, detect potential food safety issues early, and manage risks. Such a system can protect corporate brand reputation, enhance consumer protection, and ultimately improve consumer health and safety.