• Title/Summary/Keyword: Approach Detection System

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Development of a System for Music Plagiarism Detection Using Melody Databases (음악 데이터베이스를 이용한 음악 표절 감지 시스템 개발)

  • Park Jeong il;Kim Sang Wook
    • Journal of Korea Multimedia Society
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    • v.8 no.1
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    • pp.1-8
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    • 2005
  • Similar melody searching is an operation that finds such melodies similar to a given query melody from a music database. In this paper, we address the development of a system that detects plagiarism based on the similar melody searching. We first Propose a novel similarity model that supports alignment as well as shifting. Also, we suggest a method for indexing the features extracted from each melody, and a method for processing plagiarism detection by using the index. By our plagiarism detection system composers can easily searches for such melodies that are similar to their ones from music databases. Through performance evaluation via a series of experiments, we show the effectiveness of our approach. The results reveal that our approach outperforms the sequential-scan-based one in speed up to around 31 times.

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Visibility detection approach to road scene foggy images

  • Guo, Fan;Peng, Hui;Tang, Jin;Zou, Beiji;Tang, Chenggong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.9
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    • pp.4419-4441
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    • 2016
  • A cause of vehicle accidents is the reduced visibility due to bad weather conditions such as fog. Therefore, an onboard vision system should take visibility detection into account. In this paper, we propose a simple and effective approach for measuring the visibility distance using a single camera placed onboard a moving vehicle. The proposed algorithm is controlled by a few parameters and mainly includes camera parameter estimation, region of interest (ROI) estimation and visibility computation. Thanks to the ROI extraction, the position of the inflection point may be measured in practice. Thus, combined with the estimated camera parameters, the visibility distance of the input foggy image can be computed with a single camera and just the presence of road and sky in the scene. To assess the accuracy of the proposed approach, a reference target based visibility detection method is also introduced. The comparative study and quantitative evaluation show that the proposed method can obtain good visibility detection results with relatively fast speed.

SEC Approach for Detecting Node Replication Attacks in Static Wireless Sensor Networks

  • Sujihelen, L.;Jayakumar, C.;Senthilsingh, C.
    • Journal of Electrical Engineering and Technology
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    • v.13 no.6
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    • pp.2447-2455
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    • 2018
  • Security is more important in many sensor applications. The node replication attack is a major issue on sensor networks. The replicated node can capture all node details. Node Replication attacks use its secret cryptographic key to successfully produce the networks with clone nodes and also it creates duplicate nodes to build up various attacks. The replication attacks will affect in routing, more energy consumption, packet loss, misbehavior detection, etc. In this paper, a Secure-Efficient Centralized approach is proposed for detecting a Node Replication Attacks in Wireless Sensor Networks for Static Networks. The proposed system easily detects the replication attacks in an effective manner. In this approach Secure Cluster Election is used to prevent from node replication attack and Secure Efficient Centralized Approach is used to detect if any replicated node present in the network. When comparing with the existing approach the detection ratio, energy consumption performs better.

Invader Detection System Using the Morphological Filtering and Difference Images Based on the Max-Valued Edge Detection Algorithm

  • Lee, Jae-Hyun;Kim, Sung-Shin;Kim, Jung-Min
    • Journal of Advanced Marine Engineering and Technology
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    • v.36 no.5
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    • pp.645-661
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    • 2012
  • Recently, pirates are infesting on the sea and they have been hijacking the several vessels for example Samho Dream and Samho Jewelry of Korea. One of the items to reduce the risk is to adopt the invader detection system. If the pirates break in to the ship, the detection system can monitor the pirates and then call the security alarm. The crew can gain time to hide to the safe room and the report can be automatically sent to the control room to cope with the situation. For the invader detection, an unmanned observation system was proposed using the image detection algorithm that extracts the invader image from the recording image. To detect the motion area, the difference value was calculated between the current image and the prior image of the invader, and the 'AND' operator was used in calculated image and edge line. The image noise was reduced based on the morphology operation and then the image was transformed into morphological information. Finally, a neural network model was applied to recognize the invader. In the experimental results, it was confirmed that the proposed approach can improve the performance of the recognition in the invader monitoring system.

Anomaly Detection via Pattern Dictionary Method and Atypicality in Application (패턴사전과 비정형성을 통한 이상치 탐지방법 적용)

  • Sehong Oh;Jongsung Park;Youngsam Yoon
    • Journal of Sensor Science and Technology
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    • v.32 no.6
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    • pp.481-486
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    • 2023
  • Anomaly detection holds paramount significance across diverse fields, encompassing fraud detection, risk mitigation, and sensor evaluation tests. Its pertinence extends notably to the military, particularly within the Warrior Platform, a comprehensive combat equipment system with wearable sensors. Hence, we propose a data-compression-based anomaly detection approach tailored to unlabeled time series and sequence data. This method entailed the construction of two distinctive features, typicality and atypicality, to discern anomalies effectively. The typicality of a test sequence was determined by evaluating the compression efficacy achieved through the pattern dictionary. This dictionary was established based on the frequency of all patterns identified in a training sequence generated for each sensor within Warrior Platform. The resulting typicality served as an anomaly score, facilitating the identification of anomalous data using a predetermined threshold. To improve the performance of the pattern dictionary method, we leveraged atypicality to discern sequences that could undergo compression independently without relying on the pattern dictionary. Consequently, our refined approach integrated both typicality and atypicality, augmenting the effectiveness of the pattern dictionary method. Our proposed method exhibited heightened capability in detecting a spectrum of unpredictable anomalies, fortifying the stability of wearable sensors prevalent in military equipment, including the Army TIGER 4.0 system.

Rotated Face Detection Using Symmetry Detection (대칭성 검출에 의한 회전된 얼굴검출)

  • Won, Bo-Whan;Koo, Ja-Young
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.1
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    • pp.53-59
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    • 2011
  • In many face recognition applications such as security systems, it is assumed that upright faces are given to the system. In order for the system to be used in more general environments, the system should be able to deal with the rotated faces properly. It is a generally used approach to rotate the face detection window and apply face detector repeatedly to detect a rotated face in the given image. But such an approach requires a lot of computation time. In this paper, a method of extracting the axis of symmetry for a given set of points is proposed. The axis of symmetry for the edge points in the face detection window is extracted in a way that is fast and accurate, and the face detector is applied only for that direction. It is shown that the mean and standard deviation of the symmetry detection error is $0^{\circ}$ and $3^{\circ}$ respectively, for the database used.

Smoke Detection System Research using Fully Connected Method based on Adaboost

  • Lee, Yeunghak;Kim, Taesun;Shim, Jaechang
    • Journal of Multimedia Information System
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    • v.4 no.2
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    • pp.79-82
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    • 2017
  • Smoke and fire have different shapes and colours. This article suggests a fully connected system which is used two features using Adaboost algorithm for constructing a strong classifier as linear combination. We calculate the local histogram feature by gradient and bin, local binary pattern value, and projection vectors for each cell. According to the histogram magnitude, this paper applied adapted weighting value to improve the recognition rate. To preserve the local region and shape feature which has edge intensity, this paper processed the normalization sequence. For the extracted features, this paper Adaboost algorithm which makes strong classification to classify the objects. Our smoke detection system based on the proposed approach leads to higher detection accuracy than other system.

Hybrid Fault Detection and Isolation Techniques for Aircraft Inertial Measurement Sensors

  • Kim, Seung-Keun;Jung, In-Sung;Kim, You-Dan
    • International Journal of Aeronautical and Space Sciences
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    • v.7 no.1
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    • pp.73-83
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    • 2006
  • In this paper, a redundancy management system for aircraft is studied, and fault detection and isolation algorithms of inertial sensor system are proposed. Contrary to the conventional aircraft systems, UAV system cannot allow triple or quadruple hardware redundancy due to the limitations on space and weight. In the UAV system with dual sensors, it is very difficult to identify the faulty sensor. Also, conventional fault detection and isolation (FDI) method cannot isolate multiple faults in a triple redundancy system. In this paper, two FDI techniques are proposed. First, hardware based FDI technique is proposed, which combines a parity equation approach with a wavelet based technique. Second, analytic FDI technique based on the Kalman filter is proposed, which is a model-based FDI method utilizing the threshold value and the confirmation time. To provide the reference value for detecting the fault, residuals are calculated using the extended Kalman filter. To verify the effectiveness of the proposed FDI methods, numerical simulations are performed.

A PARITY SPACE APPROACH TO FAULT DETECTION FOR A POSITION SERVO SYSTEM (패리티 공간기법을 이용한 위치 서보계의 고장검출)

  • Choi, Kyung-Yung;Park, Tae-Geon;Lee, Kee-Sang
    • Proceedings of the KIEE Conference
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    • 1997.07b
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    • pp.746-748
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    • 1997
  • The parity relation approach for the fault detection and isolation (FDI) of a large diesel engine actuator position servo system is presented. Main purpose of the FDI system is to detect and isolate two important faults, actuator fault and sensor fault, that, if not detected and compensated, degrade the overall system performance. Simulation results are given to show the practical applicability of the FDI scheme.

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Detection of Oscillatory Pattern Signals and its Application to the Fault Diagnosis of a Boiler Drum-Level Control System (Oscillatory 파형감지에 의한 보일러 플랜트 드럼수위 제어계통의 고장진단)

  • Kim, Jae-Hwa;Seo, Yeol-Kyu;Jang, Tae-Gyu
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.1
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    • pp.44-51
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    • 1999
  • This paper proposes a new approach of plant fault diagnosis which is based on detecting the characteristic pattern signals and associating them with the corresponding faults. The new approach does not require analytic modeling of the target system but best reflects the expertise embedded in the experienced human operation by mimicking them in a systematic way. This paper intends to illustrate the feasibility of the proposed by developing the algorithms to detect and estimate the typical characteristic pattern signals, I. e., oscillatory patterns, and applying them to the diagnosis of various faults of a 500MW boiler control system including tube rupture, feed-water leak, and controller failure.

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