Search results for: shot cut detection.
1430 A Novel Impulse Detector for Filtering of Highly Corrupted Images
Authors: Umesh Ghanekar
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As the performance of the filtering system depends upon the accuracy of the noise detection scheme, in this paper, we present a new scheme for impulse noise detection based on two levels of decision. In this scheme in the first stage we coarsely identify the corrupted pixels and in the second stage we finally decide whether the pixel under consideration is really corrupt or not. The efficacy of the proposed filter has been confirmed by extensive simulations.Keywords: Impulse detection, noise removal, image filtering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14001429 Influence of Selected Finishing Technologies on the Roughness Parameters of Stainless Steel Manufactured by Selective Laser Melting Method
Authors: J. Hajnys, M. Pagac, J. Petru, P. Stefek, J. Mesicek, J. Kratochvil
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The new progressive method of 3D metal printing SLM (Selective Laser Melting) is increasingly expanded into the normal operation. As a result, greater demands are placed on the surface quality of the parts produced in this way. The article deals with research of selected finishing methods (tumbling, face milling, sandblasting, shot peening and brushing) and their impact on the final surface roughness. The 20 x 20 x 7 mm produced specimens using SLM additive technology on the Renishaw AM400 were subjected to testing of these finishing methods by adjusting various parameters. Surface parameters of roughness Sa, Sz were chosen as the evaluation criteria and profile parameters Ra, Rz were used as additional measurements. Optical measurement of surface roughness was performed on Alicona Infinite Focus 5. An experiment conducted to optimize the surface roughness revealed, as expected, that the best roughness parameters were achieved through a face milling operation. Tumbling is particularly suitable for 3D printing components, as tumbling media are able to reach even complex shapes and, after changing to polishing bodies, achieve a high surface gloss. Surface quality after tumbling depends on the process time. Other methods with satisfactory results are shot peening and tumbling, which should be the focus of further research.
Keywords: Additive manufacturing, selective laser melting, surface roughness, stainless steel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9511428 Detection of New Attacks on Ubiquitous Services in Cloud Computing and Countermeasures
Authors: L. Sellami, D. Idoughi, P. F. Tiako
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Cloud computing provides infrastructure to the enterprise through the Internet allowing access to cloud services at anytime and anywhere. This pervasive aspect of the services, the distributed nature of data and the wide use of information make cloud computing vulnerable to intrusions that violate the security of the cloud. This requires the use of security mechanisms to detect malicious behavior in network communications and hosts such as intrusion detection systems (IDS). In this article, we focus on the detection of intrusion into the cloud sing IDSs. We base ourselves on client authentication in the computing cloud. This technique allows to detect the abnormal use of ubiquitous service and prevents the intrusion of cloud computing. This is an approach based on client authentication data. Our IDS provides intrusion detection inside and outside cloud computing network. It is a double protection approach: The security user node and the global security cloud computing.
Keywords: Cloud computing, intrusion detection system, privacy, trust.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10931427 Detection Characteristics of the Random and Deterministic Signals in Antenna Arrays
Authors: Olesya Bolkhovskaya, Alexey Davydov, Alexander Maltsev
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In this paper, approach to incoherent signal detection in multi-element antenna array are researched and modeled. Two types of useful signals with unknown wavefront were considered: first one, deterministic (Barker code), and second one, random (Gaussian distribution). The derivation of the sufficient statistics took into account the linearity of the antenna array. The performance characteristics and detecting curves are modeled and compared for different useful signals parameters and for different number of elements of the antenna array. Results of researches in case of some additional conditions can be applied to a digital communications systems.Keywords: Antenna array, detection curves, performance characteristics, quadrature processing, signal detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17641426 Optimization of Two Quality Characteristics in Injection Molding Processes via Taguchi Methodology
Authors: Joseph C. Chen, Venkata Karthik Jakka
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The main objective of this research is to optimize tensile strength and dimensional accuracy in injection molding processes using Taguchi Parameter Design. An L16 orthogonal array (OA) is used in Taguchi experimental design with five control factors at four levels each and with non-controllable factor vibration. A total of 32 experiments were designed to obtain the optimal parameter setting for the process. The optimal parameters identified for the shrinkage are shot volume, 1.7 cubic inch (A4); mold term temperature, 130 ºF (B1); hold pressure, 3200 Psi (C4); injection speed, 0.61 inch3/sec (D2); and hold time of 14 seconds (E2). The optimal parameters identified for the tensile strength are shot volume, 1.7 cubic inch (A4); mold temperature, 160 ºF (B4); hold pressure, 3100 Psi (C3); injection speed, 0.69 inch3/sec (D4); and hold time of 14 seconds (E2). The Taguchi-based optimization framework was systematically and successfully implemented to obtain an adjusted optimal setting in this research. The mean shrinkage of the confirmation runs is 0.0031%, and the tensile strength value was found to be 3148.1 psi. Both outcomes are far better results from the baseline, and defects have been further reduced in injection molding processes.
Keywords: Injection molding processes, Taguchi Parameter Design, tensile strength, shrinkage test, high-density polyethylene, HDPE.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8301425 Segmentation of Noisy Digital Images with Stochastic Gradient Kernel
Authors: Abhishek Neogi, Jayesh Verma, Pinaki Pratim Acharjya
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Image segmentation and edge detection is a fundamental section in image processing. In case of noisy images Edge Detection is very less effective if we use conventional Spatial Filters like Sobel, Prewitt, LOG, Laplacian etc. To overcome this problem we have proposed the use of Stochastic Gradient Mask instead of Spatial Filters for generating gradient images. The present study has shown that the resultant images obtained by applying Stochastic Gradient Masks appear to be much clearer and sharper as per Edge detection is considered.Keywords: Image segmentation, edge Detection, noisy images, spatialfilters, stochastic gradient kernel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15091424 A New Method for Identifying Broken Rotor Bars in Squirrel Cage Induction Motor Based on Particle Swarm Optimization Method
Authors: V. Rashtchi, R. Aghmasheh
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Detection of squirrel cage induction motor (SCIM) broken bars has long been an important but difficult job in the detection area of motor faults. Early detection of this abnormality in the motor would help to avoid costly breakdowns. A new detection method based on particle swarm optimization (PSO) is presented in this paper. Stator current in an induction motor will be measured and characteristic frequency components of faylted rotor will be detected by minimizing a fitness function using pso. Supply frequency and side band frequencies and their amplitudes can be estimated by the proposed method. The proposed method is applied to a faulty motor with one and two broken bars in different loading condition. Experimental results prove that the proposed method is effective and applicable.
Keywords: broken bar, PSO, fault detection, SCIM
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17081423 Detection of Clipped Fragments in Speech Signals
Authors: Sergei Aleinik, Yuri Matveev
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In this paper a novel method for the detection of clipping in speech signals is described. It is shown that the new method has better performance than known clipping detection methods, is easy to implement, and is robust to changes in signal amplitude, size of data, etc. Statistical simulation results are presented.
Keywords: Clipping, clipped signal, speech signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26611422 Target Signal Detection Using MUSIC Spectrum in Noise Environment
Authors: Sangjun Park, Sangbae Jeong, Moonsung Han, Minsoo hahn
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In this paper, a target signal detection method using multiple signal classification (MUSIC) algorithm is proposed. The MUSIC algorithm is a subspace-based direction of arrival (DOA) estimation method. The algorithm detects the DOAs of multiple sources using the inverse of the eigenvalue-weighted eigen spectra. To apply the algorithm to target signal detection for GSC-based beamforming, we utilize its spectral response for the target DOA in noisy conditions. For evaluation of the algorithm, the performance of the proposed target signal detection method is compared with that of the normalized cross-correlation (NCC), the fixed beamforming, and the power ratio method. Experimental results show that the proposed algorithm significantly outperforms the conventional ones in receiver operating characteristics(ROC) curves.Keywords: Beamforming, direction of arrival, multiple signal classification, target signal detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25311421 Burnout Recognition for Call Center Agents by Using Skin Color Detection with Hand Poses
Authors: El Sayed A. Sharara, A. Tsuji, K. Terada
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Call centers have been expanding and they have influence on activation in various markets increasingly. A call center’s work is known as one of the most demanding and stressful jobs. In this paper, we propose the fatigue detection system in order to detect burnout of call center agents in the case of a neck pain and upper back pain. Our proposed system is based on the computer vision technique combined skin color detection with the Viola-Jones object detector. To recognize the gesture of hand poses caused by stress sign, the YCbCr color space is used to detect the skin color region including face and hand poses around the area related to neck ache and upper back pain. A cascade of clarifiers by Viola-Jones is used for face recognition to extract from the skin color region. The detection of hand poses is given by the evaluation of neck pain and upper back pain by using skin color detection and face recognition method. The system performance is evaluated using two groups of dataset created in the laboratory to simulate call center environment. Our call center agent burnout detection system has been implemented by using a web camera and has been processed by MATLAB. From the experimental results, our system achieved 96.3% for upper back pain detection and 94.2% for neck pain detection.
Keywords: Call center agents, fatigue, skin color detection, face recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10361420 An Expert System for Car Failure Diagnosis
Authors: Ahmad T. Al-Taani
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Car failure detection is a complicated process and requires high level of expertise. Any attempt of developing an expert system dealing with car failure detection has to overcome various difficulties. This paper describes a proposed knowledge-based system for car failure detection. The paper explains the need for an expert system and the some issues on developing knowledge-based systems, the car failure detection process and the difficulties involved in developing the system. The system structure and its components and their functions are described. The system has about 150 rules for different types of failures and causes. It can detect over 100 types of failures. The system has been tested and gave promising results.Keywords: Expert system, car failure diagnosis, knowledgebasedsystem, CLIPS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 119021419 CdS Quantum Dots as Fluorescent Probes for Detection of Naphthalene
Authors: Zhengyu Yan, Yan Yu, Jianqiu Chen
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A novel sensing system has been designed for naphthalene detection based on the quenched fluorescence signal of CdS quantum dots. The fluorescence intensity of the system reduced significantly after adding CdS quantum dots to the water pollution model because of the fluorescent static quenching f mechanism. Herein, we have demonstrated the facile methodology can offer a convenient and low analysis cost with the recovery rate as 97.43%-103.2%, which has potential application prospect.Keywords: CdS quantum dots, modification, detection, naphthalene.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12631418 Evaluation of Haar Cascade Classifiers Designed for Face Detection
Authors: R. Padilla, C. F. F. Costa Filho, M. G. F. Costa
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In the past years a lot of effort has been made in the field of face detection. The human face contains important features that can be used by vision-based automated systems in order to identify and recognize individuals. Face location, the primary step of the vision-based automated systems, finds the face area in the input image. An accurate location of the face is still a challenging task. Viola-Jones framework has been widely used by researchers in order to detect the location of faces and objects in a given image. Face detection classifiers are shared by public communities, such as OpenCV. An evaluation of these classifiers will help researchers to choose the best classifier for their particular need. This work focuses of the evaluation of face detection classifiers minding facial landmarks.Keywords: Face datasets, face detection, facial landmarking, haar wavelets, Viola-Jones detectors.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 53921417 Practical Aspects of Face Recognition
Authors: S. Vural, H. Yamauchi
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Current systems for face recognition techniques often use either SVM or Adaboost techniques for face detection part and use PCA for face recognition part. In this paper, we offer a novel method for not only a powerful face detection system based on Six-segment-filters (SSR) and Adaboost learning algorithms but also for a face recognition system. A new exclusive face detection algorithm has been developed and connected with the recognition algorithm. As a result of it, we obtained an overall high-system performance compared with current systems. The proposed algorithm was tested on CMU, FERET, UNIBE, MIT face databases and significant performance has obtained.Keywords: Adaboost, Face Detection, Face recognition, SVM, Gabor filters, PCA-ICA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15901416 A Review on Soft Computing Technique in Intrusion Detection System
Authors: Noor Suhana Sulaiman, Rohani Abu Bakar, Norrozila Sulaiman
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Intrusion Detection System is significant in network security. It detects and identifies intrusion behavior or intrusion attempts in a computer system by monitoring and analyzing the network packets in real time. In the recent year, intelligent algorithms applied in the intrusion detection system (IDS) have been an increasing concern with the rapid growth of the network security. IDS data deals with a huge amount of data which contains irrelevant and redundant features causing slow training and testing process, higher resource consumption as well as poor detection rate. Since the amount of audit data that an IDS needs to examine is very large even for a small network, classification by hand is impossible. Hence, the primary objective of this review is to review the techniques prior to classification process suit to IDS data.Keywords: Intrusion Detection System, security, soft computing, classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18571415 A Deep Learning Framework for Polarimetric SAR Change Detection Using Capsule Network
Authors: Sanae Attioui, Said Najah
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The Earth's surface is constantly changing through forces of nature and human activities. Reliable, accurate, and timely change detection is critical to environmental monitoring, resource management, and planning activities. Recently, interest in deep learning algorithms, especially convolutional neural networks, has increased in the field of image change detection due to their powerful ability to extract multi-level image features automatically. However, these networks are prone to drawbacks that limit their applications, which reside in their inability to capture spatial relationships between image instances, as this necessitates a large amount of training data. As an alternative, Capsule Network has been proposed to overcome these shortcomings. Although its effectiveness in remote sensing image analysis has been experimentally verified, its application in change detection tasks remains very sparse. Motivated by its greater robustness towards improved hierarchical object representation, this study aims to apply a capsule network for PolSAR image Change Detection. The experimental results demonstrate that the proposed change detection method can yield a significantly higher detection rate compared to methods based on convolutional neural networks.
Keywords: Change detection, capsule network, deep network, Convolutional Neural Networks, polarimetric synthetic aperture radar images, PolSAR images.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4741414 Program Memories Error Detection and Correction On-Board Earth Observation Satellites
Authors: Y. Bentoutou
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Memory Errors Detection and Correction aim to secure the transaction of data between the central processing unit of a satellite onboard computer and its local memory. In this paper, the application of a double-bit error detection and correction method is described and implemented in Field Programmable Gate Array (FPGA) technology. The performance of the proposed EDAC method is measured and compared with two different EDAC devices, using the same FPGA technology. Statistical analysis of single-event upset (SEU) and multiple-bit upset (MBU) activity in commercial memories onboard the first Algerian microsatellite Alsat-1 is given.
Keywords: Error Detection and Correction, On-board computer, small satellite missions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22091413 Attention-Based Spatio-Temporal Approach for Fire and Smoke Detection
Authors: A. Mirrashid, M. Khoshbin, A. Atghaei, H. Shahbazi
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In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is the use of infrared thermal and smoke sensors, which cannot be used in outdoor applications. Therefore, the use of vision-based methods seems necessary. The problem of smoke and fire detection is spatiotemporal and requires spatiotemporal solutions. This paper presents a method that uses spatial features along with temporal-based features to detect smoke and fire in the scene. It consists of three main parts; the task of each part is to reduce the error of the previous part so that the final model has a robust performance. This method also uses transformer modules to increase the accuracy of the model. The results of our model show the proper performance of the proposed approach in solving the problem of smoke and fire detection and can be used to increase workplace safety.
Keywords: Attention, fire detection, smoke detection, spatiotemporal.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3261412 Neural Network in Fixed Time for Collision Detection between Two Convex Polyhedra
Authors: M. Khouil, N. Saber, M. Mestari
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In this paper, a different architecture of a collision detection neural network (DCNN) is developed. This network, which has been particularly reviewed, has enabled us to solve with a new approach the problem of collision detection between two convex polyhedra in a fixed time (O (1) time). We used two types of neurons, linear and threshold logic, which simplified the actual implementation of all the networks proposed. The study of the collision detection is divided into two sections, the collision between a point and a polyhedron and then the collision between two convex polyhedra. The aim of this research is to determine through the AMAXNET network a mini maximum point in a fixed time, which allows us to detect the presence of a potential collision.
Keywords: Collision identification, fixed time, convex polyhedra, neural network, AMAXNET.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18061411 An Automated Method to Segment and Classify Masses in Mammograms
Authors: Viet Dzung Nguyen, Duc Thuan Nguyen, Tien Dzung Nguyen, Van Thanh Pham
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Mammography is the most effective procedure for an early diagnosis of the breast cancer. Nowadays, people are trying to find a way or method to support as much as possible to the radiologists in diagnosis process. The most popular way is now being developed is using Computer-Aided Detection (CAD) system to process the digital mammograms and prompt the suspicious region to radiologist. In this paper, an automated CAD system for detection and classification of massive lesions in mammographic images is presented. The system consists of three processing steps: Regions-Of- Interest detection, feature extraction and classification. Our CAD system was evaluated on Mini-MIAS database consisting 322 digitalized mammograms. The CAD system-s performance is evaluated using Receiver Operating Characteristics (ROC) and Freeresponse ROC (FROC) curves. The archived results are 3.47 false positives per image (FPpI) and sensitivity of 85%.Keywords: classification, computer-aided detection, featureextraction, mass detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16461410 Ship Detection Requirements Analysis for Different Sea States: Validation on Real SAR Data
Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores
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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.Keywords: SAR, generalized gamma distribution, detection curves, radar detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11641409 Intrusion Detection Using a New Particle Swarm Method and Support Vector Machines
Authors: Essam Al Daoud
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Intrusion detection is a mechanism used to protect a system and analyse and predict the behaviours of system users. An ideal intrusion detection system is hard to achieve due to nonlinearity, and irrelevant or redundant features. This study introduces a new anomaly-based intrusion detection model. The suggested model is based on particle swarm optimisation and nonlinear, multi-class and multi-kernel support vector machines. Particle swarm optimisation is used for feature selection by applying a new formula to update the position and the velocity of a particle; the support vector machine is used as a classifier. The proposed model is tested and compared with the other methods using the KDD CUP 1999 dataset. The results indicate that this new method achieves better accuracy rates than previous methods.Keywords: Feature selection, Intrusion detection, Support vector machine, Particle swarm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19751408 A Comprehensive Method of Fault Detection and Isolation Based On Testability Modeling Data
Authors: Junyou Shi, Weiwei Cui
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Testability modeling is a commonly used method in testability design and analysis of system. A dependency matrix will be obtained from testability modeling, and we will give a quantitative evaluation about fault detection and isolation. Based on the dependency matrix, we can obtain the diagnosis tree. The tree provides the procedures of the fault detection and isolation. But the dependency matrix usually includes built-in test (BIT) and manual test in fact. BIT runs the test automatically and is not limited by the procedures. The method above cannot give a more efficient diagnosis and use the advantages of the BIT. A Comprehensive method of fault detection and isolation is proposed. This method combines the advantages of the BIT and Manual test by splitting the matrix. The result of the case study shows that the method is effective.
Keywords: BIT, fault detection, fault isolation, testability modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16611407 An Evaluation of Sag Detection Techniques for Fast Solid-State Electronic Transferring to Alternate Electrical Energy Sources
Authors: M. N. Moschakis, I. G. Andritsos, V. V. Dafopoulos, J. M. Prousalidis, E. S. Karapidakis
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This paper deals with the evaluation of different detection strategies used in power electronic devices as a critical element for an effective mitigation of voltage disturbances. The effectiveness of those detection schemes in the mitigation of disturbances such as voltage sags by a Solid-State Transfer Switch is evaluated through simulations. All critical parameters affecting their performance is analytically described and presented. Moreover, the effect of fast detection of sags on the overall performance of STS is analyzed and investigated.
Keywords: Faults (short-circuits), industrial engineering, power electronics, power quality, static transfer switch, voltage sags (or dips).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18771406 Short-Path Near-Infrared Laser Detection of Environmental Gases by Wavelength-Modulation Spectroscopy
Authors: Isao Tomita
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The detection of environmental gases, 12CO2, 13CO2, and CH4, using near-infrared semiconductor lasers with a short laser path length is studied by means of wavelength-modulation spectroscopy. The developed system is compact and has high sensitivity enough to detect the absorption peaks of isotopic 13CO2 of a 3-% CO2 gas at 2 μm with a path length of 2.4 m, where its peak size is two orders of magnitude smaller than that of the ordinary 12CO2 peaks. In addition, the detection of 12CO2 peaks of a 385-ppm (0.0385-%) CO2 gas in the air is made at 2 μm with a path length of 1.4 m. Furthermore, in pursuing the detection of an ancient environmental CH4 gas confined to a bubble in ice at the polar regions, measurements of the absorption spectrum for a trace gas of CH4 in a small area are attempted. For a 100-% CH4 gas trapped in a ∼ 1 mm3 glass container, the absorption peaks of CH4 are obtained at 1.65 μm with a path length of 3 mm, and also the gas pressure is extrapolated from the measured data.
Keywords: Environmental Gases, Near-Infrared Laser Detection, Wavelength-Modulation Spectroscopy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17381405 Edge Detection Algorithm Based on Wavelet De-nosing Applied tothe X-ray Image Enhancement of the Electric Equipment
Authors: Fei Xue, Hong Yu, Da-da Wang, Wei Zhang, Rong-min Zou, Xiao-lanCai
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The X-ray technology has been used in non-destructive evaluation in the Power System, in which a visual non-destructive inspection method for the electrical equipment is provided. However, lots of noise is existed in the images that are got from the X-ray digital images equipment. Therefore, the auto defect detection which based on these images will be very difficult to proceed. A theory on X-ray image de-noising algorithm based on wavelet transform is proposed in this paper. Then the edge detection algorithm is used so that the defect can be pushed out. The result of experiment shows that the method which utilized by this paper is very useful for de-noising on the X-ray images.
Keywords: de-noising, edge detection, wavelet transform, X-ray
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15361404 An Efficient Fundamental Matrix Estimation for Moving Object Detection
Authors: Yeongyu Choi, Ju H. Park, S. M. Lee, Ho-Youl Jung
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In this paper, an improved method for estimating fundamental matrix is proposed. The method is applied effectively to monocular camera based moving object detection. The method consists of corner points detection, moving object’s motion estimation and fundamental matrix calculation. The corner points are obtained by using Harris corner detector, motions of moving objects is calculated from pyramidal Lucas-Kanade optical flow algorithm. Through epipolar geometry analysis using RANSAC, the fundamental matrix is calculated. In this method, we have improved the performances of moving object detection by using two threshold values that determine inlier or outlier. Through the simulations, we compare the performances with varying the two threshold values.
Keywords: Corner detection, optical flow, epipolar geometry, RANSAC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11111403 Challenges in Video Based Object Detection in Maritime Scenario Using Computer Vision
Authors: Dilip K. Prasad, C. Krishna Prasath, Deepu Rajan, Lily Rachmawati, Eshan Rajabally, Chai Quek
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This paper discusses the technical challenges in maritime image processing and machine vision problems for video streams generated by cameras. Even well documented problems of horizon detection and registration of frames in a video are very challenging in maritime scenarios. More advanced problems of background subtraction and object detection in video streams are very challenging. Challenges arising from the dynamic nature of the background, unavailability of static cues, presence of small objects at distant backgrounds, illumination effects, all contribute to the challenges as discussed here.Keywords: Autonomous maritime vehicle, object detection, situation awareness, tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13071402 On the Verification of Power Nap Associated with Stage 2 Sleep and Its Application
Authors: Jetsada Arnin, Yodchanan Wongsawat
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One of the most important causes of accidents is driver fatigue. To reduce the accidental rate, the driver needs a quick nap when feeling sleepy. Hence, searching for the minimum time period of nap is a very challenging problem. The purpose of this paper is twofold, i.e. to investigate the possible fastest time period for nap and its relationship with stage 2 sleep, and to develop an automatic stage 2 sleep detection and alarm device. The experiment for this investigation is designed with 21 subjects. It yields the result that waking up the subjects after getting into stage 2 sleep for 3-5 minutes can efficiently reduce the sleepiness. Furthermore, the automatic stage 2 sleep detection and alarm device yields the real-time detection accuracy of approximately 85% which is comparable with the commercial sleep lab system.Keywords: Stage 2 sleep, nap, sleep detection, real-time, EEG
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14491401 A Novel Framework for Abnormal Behaviour Identification and Detection for Wireless Sensor Networks
Authors: Muhammad R. Ahmed, Xu Huang, Dharmendra Sharma
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Despite extensive study on wireless sensor network security, defending internal attacks and finding abnormal behaviour of the sensor are still difficult and unsolved task. The conventional cryptographic technique does not give the robust security or detection process to save the network from internal attacker that cause by abnormal behavior. The insider attacker or abnormally behaved sensor identificationand location detection framework using false massage detection and Time difference of Arrival (TDoA) is presented in this paper. It has been shown that the new framework can efficiently identify and detect the insider attacker location so that the attacker can be reprogrammed or subside from the network to save from internal attack.Keywords: Insider Attaker identification, Abnormal Behaviour, Location detection, Time difference of Arrival (TDoA), Wireless sensor network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1765