Search results for: curve detection

Authors: Sangbum Park, Namki Lee, Youngjoon Han, Hernsoo Hahn

Abstract:

In this paper, we propose the robust water level detection method based on the accumulated histogram under small changed image which is acquired from water level surveillance camera. In general surveillance system, this is detecting and recognizing invasion from searching area which is in big change on the sequential images. However, in case of a water level detection system, these general surveillance techniques are not suitable due to small change on the water surface. Therefore the algorithm introduces the accumulated histogram which is emphasizing change of water surface in sequential images. Accumulated histogram is based on the current image frame. The histogram is cumulating differences between previous images and current image. But, these differences are also appeared in the land region. The band pass filter is able to remove noises in the accumulated histogram Finally, this algorithm clearly separates water and land regions. After these works, the algorithm converts from the water level value on the image space to the real water level on the real space using calibration table. The detected water level is sent to the host computer with current image. To evaluate the proposed algorithm, we use test images from various situations.

Keywords: accumulated histogram, water level detection, band pass filter.

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Authors: Abu Salim Mustafa

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Polymerase chain reaction (PCR) assays targeting genomic DNA segments have been established for the detection of Helicobacter pylori in clinical specimens. However, the data on comparative evaluations of various targets in detection of H. pylori are limited. Furthermore, the frequencies of vacA (s1 and s2) and cagA genotypes, which are suggested to be involved in the pathogenesis of H. pylori in other parts of the world, are not well studied in Kuwait. The aim of this study was to evaluate PCR assays for the detection and genotyping of H. pylori by targeting the amplification of DNA targets from four genomic segments. The genomic DNA were isolated from 72 clinical isolates of H. pylori and tested in PCR with four pairs of oligonucleotides primers, i.e. ECH-U/ECH-L, ET-5U/ET-5L, CagAF/CagAR and Vac1F/Vac1XR, which were expected to amplify targets of various sizes (471 bp, 230 bp, 183 bp and 176/203 bp, respectively) from the genomic DNA of H. pylori. The PCR-amplified DNA were analyzed by agarose gel electrophoresis. PCR products of expected size were obtained with all primer pairs by using genomic DNA isolated from H. pylori. DNA dilution experiments showed that the most sensitive PCR target was 471 bp DNA amplified by the primers ECH-U/ECH-L, followed by the targets of Vac1F/Vac1XR (176 bp/203 DNA), CagAF/CagAR (183 bp DNA) and ET-5U/ET-5L (230 bp DNA). However, when tested with undiluted genomic DNA isolated from single colonies of all isolates, the Vac1F/Vac1XR target provided the maximum positive results (71/72 (99% positives)), followed by ECH-U/ECH-L (69/72 (93% positives)), ET-5U/ET-5L (51/72 (71% positives)) and CagAF/CagAR (26/72 (46% positives)). The results of genotyping experiments showed that vacA s1 (46% positive) and vacA s2 (54% positive) genotypes were almost equally associated with VaCA+/CagA- isolates (P > 0.05), but with VacA+/CagA+ isolates, S1 genotype (92% positive) was more frequently detected than S2 genotype (8% positive) (P< 0.0001). In conclusion, among the primer pairs tested, Vac1F/Vac1XR provided the best results for detection of H. pylori. The genotyping experiments showed that vacA s1 and vacA s2 genotypes were almost equally associated with vaCA⁺/cagA^- isolates, but vacA s1 genotype had a significantly increased association with vacA⁺/cagA⁺ isolates.

Keywords: H. pylori, detection, genotyping, Kuwait.

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Authors: Abdallah A. Alshennawy, Ayman A. Aly

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The fuzzy technique is an operator introduced in order to simulate at a mathematical level the compensatory behavior in process of decision making or subjective evaluation. The following paper introduces such operators on hand of computer vision application. In this paper a novel method based on fuzzy logic reasoning strategy is proposed for edge detection in digital images without determining the threshold value. The proposed approach begins by segmenting the images into regions using floating 3x3 binary matrix. The edge pixels are mapped to a range of values distinct from each other. The robustness of the proposed method results for different captured images are compared to those obtained with the linear Sobel operator. It is gave a permanent effect in the lines smoothness and straightness for the straight lines and good roundness for the curved lines. In the same time the corners get sharper and can be defined easily.

Keywords: Fuzzy logic, Edge detection, Image processing, computer vision, Mechanical parts, Measurement.

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Authors: N. Arulanand, K. Premalatha

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Bloom filter is a probabilistic and memory efficient data structure designed to answer rapidly whether an element is present in a set. It tells that the element is definitely not in the set but its presence is with certain probability. The trade-off to use Bloom filter is a certain configurable risk of false positives. The odds of a false positive can be made very low if the number of hash function is sufficiently large. For spam detection, weight is attached to each set of elements. The spam weight for a word is a measure used to rate the e-mail. Each word is assigned to a Bloom filter based on its weight. The proposed work introduces an enhanced concept in Bloom filter called Bin Bloom Filter (BBF). The performance of BBF over conventional Bloom filter is evaluated under various optimization techniques. Real time data set and synthetic data sets are used for experimental analysis and the results are demonstrated for bin sizes 4, 5, 6 and 7. Finally analyzing the results, it is found that the BBF which uses heuristic techniques performs better than the traditional Bloom filter in spam detection.

Keywords: Cuckoo search algorithm, levy’s flight, metaheuristic, optimal weight.

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Authors: Lilia M. Fernando, Matthew K. Vasher, Evangelyn C. Alocilja

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This paper describes the development of a DNA-based nanobiosensor to detect the dengue virus in mosquito using electrically active magnetic (EAM) nanoparticles as concentrator and electrochemical transducer. The biosensor detection encompasses two sets of oligonucleotide probes that are specific to the dengue virus: the detector probe labeled with the EAM nanoparticles and the biotinylated capture probe. The DNA targets are double hybridized to the detector and the capture probes and concentrated from nonspecific DNA fragments by applying a magnetic field. Subsequently, the DNA sandwiched targets (EAM-detector probe– DNA target–capture probe-biotin) are captured on streptavidin modified screen printed carbon electrodes through the biotinylated capture probes. Detection is achieved electrochemically by measuring the oxidation–reduction signal of the EAM nanoparticles. Results indicate that the biosensor is able to detect the redox signal of the EAM nanoparticles at dengue DNA concentrations as low as 10 ng/μl.

Keywords: Dengue, magnetic nanoparticles, mosquito, nanobiosensor.

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Authors: Gholamreza Ghodrati Amiri, Mojtaba Jafarian Abyaneh, Ali Zare Hosseinzadeh

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This paper presents an effective model updating strategy for damage localization and quantification in frames by defining damage detection problem as an optimization issue. A generalized version of the Modal Residual Force (MRF) is employed for presenting a new damage-sensitive cost function. Then, Grey Wolf Optimization (GWO) algorithm is utilized for solving suggested inverse problem and the global extremums are reported as damage detection results. The applicability of the presented method is investigated by studying different damage patterns on the benchmark problem of the IASC-ASCE, as well as a planar shear frame structure. The obtained results emphasize good performance of the method not only in free-noise cases, but also when the input data are contaminated with different levels of noises.

Keywords: Frame, grey wolf optimization algorithm, modal residual force, structural damage detection.

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Authors: Jamuna Bhandari

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String matching also known as pattern matching is one of primary concept for network security. In this area the effectiveness and efficiency of string matching algorithms is important for applications in network security such as network intrusion detection, virus detection, signature matching and web content filtering system. This paper presents brief review on some of string matching techniques used for network security.

Keywords: Filtering, honeypot, network telescope, pattern, string, signature.

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Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

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This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: Intelligent transportation systems, object detection, video processing, road traffic, vehicle counting, vehicle classification.

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Authors: K. Soldatova, Y. Galerkin

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A loading factor performance is necessary for the modeling of centrifugal compressor gas dynamic performance curve. Measured loading factors are linear function of a flow coefficient at an impeller exit. The performance does not depend on the compressibility criterion. To simulate loading factor performances, the authors present two parameters: a loading factor at zero flow rate and an angle between an ordinate and performance line. The calculated loading factor performances of non-viscous are linear too and close to experimental performances. Loading factor performances of several dozens of impellers with different blade exit angles, blade thickness and number, ratio of blade exit/inlet height, and two different type of blade mean line configuration. There are some trends of influence, which are evident – comparatively small blade thickness influence, and influence of geometry parameters is more for impellers with bigger blade exit angles, etc. Approximating equations for both parameters are suggested. The next phase of work will be simulating of experimental performances with the suggested approximation equations as a base.

Keywords: Centrifugal compressor stage, centrifugal compressor, loading factor, gas dynamic performance curve.

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Authors: Masoud Abedini, Azrul A. Mutalib, Shahrizan Baharom, Hong Hao

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This study was conducted published to investigate there liability of the equation pressure-impulse (PI) reinforced concrete column inprevious studies. Equation involves three different levels of damage criteria known as D =0. 2, D =0. 5 and D =0. 8.The damage criteria known as a minor when 0-0.2, 0.2-0.5is known as moderate damage, high damage known as 0.5-0.8, and 0.8-1 of the structure is considered a failure. In this study, two types of reliability analyzes conducted. First, using pressure-impulse equation with different parameters. The parameters involved are the concrete strength, depth, width, and height column, the ratio of longitudinal reinforcement and transverse reinforcement ratio. In the first analysis of the reliability of this new equation is derived to improve the previous equations. The second reliability analysis involves three types of columns used to derive the PI curve diagram using the derived equation to compare with the equation derived from other researchers and graph minimum standoff versus weapon yield Federal Emergency Management Agency (FEMA). The results showed that the derived equation is more accurate with FEMA standards than previous researchers.

Keywords: Blast load, RC column, P-I curve, Analytical formulae, Standard FEMA.

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Authors: K.M. Faraoun, A. Boukelif

Abstract:

This paper describes a new approach of classification using genetic programming. The proposed technique consists of genetically coevolving a population of non-linear transformations on the input data to be classified, and map them to a new space with a reduced dimension, in order to get a maximum inter-classes discrimination. The classification of new samples is then performed on the transformed data, and so become much easier. Contrary to the existing GP-classification techniques, the proposed one use a dynamic repartition of the transformed data in separated intervals, the efficacy of a given intervals repartition is handled by the fitness criterion, with a maximum classes discrimination. Experiments were first performed using the Fisher-s Iris dataset, and then, the KDD-99 Cup dataset was used to study the intrusion detection and classification problem. Obtained results demonstrate that the proposed genetic approach outperform the existing GP-classification methods [1],[2] and [3], and give a very accepted results compared to other existing techniques proposed in [4],[5],[6],[7] and [8].

Keywords: Genetic programming, patterns classification, intrusion detection

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Authors: Vidhu Mitha Goutham, Ruma Mukherjee

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The low availability of well-trained, unlimited, dynamic-access models for specific languages makes it hard for corporate users to adopt quick translation techniques and incorporate them into product solutions. As translation tasks increasingly require a dynamic sequence learning curve; stable, cost-free opensource models are scarce. We survey and compare current translation techniques and propose a modified sequence to sequence model repurposed with attention techniques. Sequence learning using an encoder-decoder model is now paving the path for higher precision levels in translation. Using a Convolutional Neural Network (CNN) encoder and a Recurrent Neural Network (RNN) decoder background, we use Fairseq tools to produce an end-to-end bilingually trained Spanish-English machine translation model including source language detection. We acquire competitive results using a duo-lingo-corpus trained model to provide for prospective, ready-made plug-in use for compound sentences and document translations. Our model serves a decent system for large, organizational data translation needs. While acknowledging its shortcomings and future scope, it also identifies itself as a well-optimized deep neural network model and solution.

Keywords: Attention, encoder-decoder, Fairseq, Seq2Seq, Spanish, translation.

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Authors: Chiou-Yng Lee, Wen-Yo Lee, Chieh-Tsai Wu, Cheng-Chen Yang

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Shifted polynomial basis (SPB) is a variation of polynomial basis representation. SPB has potential for efficient bit level and digi -level implementations of multiplication over binary extension fields with subquadratic space complexity. For efficient implementation of pairing computation with large finite fields, this paper presents a new SPB multiplication algorithm based on Karatsuba schemes, and used that to derive a novel scalable multiplier architecture. Analytical results show that the proposed multiplier provides a trade-off between space and time complexities. Our proposed multiplier is modular, regular, and suitable for very large scale integration (VLSI) implementations. It involves less area complexity compared to the multipliers based on traditional decomposition methods. It is therefore, more suitable for efficient hardware implementation of pairing based cryptography and elliptic curve cryptography (ECC) in constraint driven applications.

Keywords: Digit-serial systolic multiplier, elliptic curve cryptography (ECC), Karatsuba algorithm (KA), shifted polynomial basis (SPB), pairing computation.

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Authors: Mustafa S. Fawad, Wang Wencheng, Wu Enhua

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Shadows add great amount of realism to a scene and many algorithms exists to generate shadows. Recently, Shadow volumes (SVs) have made great achievements to place a valuable position in the gaming industries. Looking at this, we concentrate on simple but valuable initial partial steps for further optimization in SV generation, i.e.; model simplification and silhouette edge detection and tracking. Shadow volumes (SVs) usually takes time in generating boundary silhouettes of the object and if the object is complex then the generation of edges become much harder and slower in process. The challenge gets stiffer when real time shadow generation and rendering is demanded. We investigated a way to use the real time silhouette edge detection method, which takes the advantage of spatial and temporal coherence, and exploit the level-of-details (LOD) technique for reducing silhouette edges of the model to use the simplified version of the model for shadow generation speeding up the running time. These steps highly reduce the execution time of shadow volume generations in real-time and are easily flexible to any of the recently proposed SV techniques. Our main focus is to exploit the LOD and silhouette edge detection technique, adopting them to further enhance the shadow volume generations for real time rendering.

Keywords: LOD, perception, Shadow Volumes, SilhouetteEdge, Spatial and Temporal coherence.

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Authors: Panagiotis Lemonakis, Theodoros Αlimonakis, George Kaliabetsos, Nikos Eliou

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It is very well known that certain vertical and longitudinal slopes have to be assured in order to achieve adequate rainwater runoff from the pavement. The selection of longitudinal slopes, between the turning points of the vertical curves that meet the afore-mentioned requirement does not ensure adequate drainage because the same condition must also be applied at the transition curves. In this way none of the pavement edges’ slopes (as well as any other spot that lie on the pavement) will be opposite to the longitudinal slope of the rotation axis. Horizontal and vertical alignment must be properly combined in order to form a road which resultant slope does not take small values and hence, checks must be performed in every cross section and every chainage of the road. The present research investigates the rain water runoff from the road surface in order to identify the conditions under which, areas of inadequate drainage are being created, to analyze the rainwater behavior in such areas, to provide design examples of good and bad drainage zones and to track down certain motorcycle types which might encounter hazardous situations due to the presence of water film between the pavement and both of their tires resulting loss of traction. Moreover, it investigates the combination of longitudinal and cross slope values in critical pavement areas. It should be pointed out that the drainage gradient is analytically calculated for the whole road width and not just for an oblique slope per chainage (combination of longitudinal grade and cross slope). Lastly, various combinations of horizontal and vertical design are presented, indicating the crucial zones of bad pavement drainage. The key conclusion of the study is that any type of motorcycle will travel for some time inside the area of improper runoff for a certain time frame which depends on the speed and the trajectory that the rider chooses along the transition curve. Taking into account that on this section the rider will have to lean his motorcycle and hence reduce the contact area of his tire with the pavement it is apparent that any variations on the friction value due to the presence of a water film may lead to serious problems regarding his safety. The water runoff from the road pavement is improved when between reverse longitudinal slopes, crest instead of sag curve is chosen and particularly when its edges coincide with the edges of the horizontal curve. Lastly, the results of the investigation have shown that the variation of the longitudinal slope involves the vertical shift of the center of the poor water runoff area. The magnitude of this area increases as the length of the transition curve increases.

Keywords: Drainage, motorcycle safety, superelevation, transition curves, vertical grade.

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Authors: Zacharenia I. Garofalaki, John T. Amorginos, John N. Ellinas

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This paper presents the development of a robot car that can track the motion of an object by detecting its color through an Android device. The employed computer vision algorithm uses the OpenCV library, which is embedded into an Android application of a smartphone, for manipulating the captured image of the object. The captured image of the object is subjected to color conversion and is transformed to a binary image for further processing after color filtering. The desired object is clearly determined after removing pixel noise by applying image morphology operations and contour definition. Finally, the area and the center of the object are determined so that object’s motion to be tracked. The smartphone application has been placed on a robot car and transmits by Bluetooth to an Arduino assembly the motion directives so that to follow objects of a specified color. The experimental evaluation of the proposed algorithm shows reliable color detection and smooth tracking characteristics.

Keywords: Android, Arduino Uno, Image processing, Object motion detection, OpenCV library.

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Authors: Heeseung Choi, Raechoong Kang, Kyungtaek Choi, Jaihie Kim

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Fake finger submission attack is a major problem in fingerprint recognition systems. In this paper, we introduce an aliveness detection method based on multiple static features, which derived from a single fingerprint image. The static features are comprised of individual pore spacing, residual noise and several first order statistics. Specifically, correlation filter is adopted to address individual pore spacing. The multiple static features are useful to reflect the physiological and statistical characteristics of live and fake fingerprint. The classification can be made by calculating the liveness scores from each feature and fusing the scores through a classifier. In our dataset, we compare nine classifiers and the best classification rate at 85% is attained by using a Reduced Multivariate Polynomial classifier. Our approach is faster and more convenient for aliveness check for field applications.

Keywords: Aliveness detection, Fingerprint recognition, individual pore spacing, multiple static features, residual noise.

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Authors: Omar GACI, Stefan BALEV, Antoine DUTOT

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In this paper we introduce the notion of protein interaction network. This is a graph whose vertices are the protein-s amino acids and whose edges are the interactions between them. Using a graph theory approach, we observe that according to their structural roles, the nodes interact differently. By leading a community structure detection, we confirm this specific behavior and describe thecommunities composition to finally propose a new approach to fold a protein interaction network.

Keywords: interaction network, protein structure, community structure detection.

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Authors: S. Bouhouche, M. Lahreche, S. Ziani, J. Bast

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Modern manufacturing facilities are large scale, highly complex, and operate with large number of variables under closed loop control. Early and accurate fault detection and diagnosis for these plants can minimise down time, increase the safety of plant operations, and reduce manufacturing costs. Fault detection and isolation is more complex particularly in the case of the faulty analog control systems. Analog control systems are not equipped with monitoring function where the process parameters are continually visualised. In this situation, It is very difficult to find the relationship between the fault importance and its consequences on the product failure. We consider in this paper an approach to fault detection and analysis of its effect on the production quality using an adaptive centring and scaling in the pickling process in cold rolling. The fault appeared on one of the power unit driving a rotary machine, this machine can not track a reference speed given by another machine. The length of metal loop is then in continuous oscillation, this affects the product quality. Using a computerised data acquisition system, the main machine parameters have been monitored. The fault has been detected and isolated on basis of analysis of monitored data. Normal and faulty situation have been obtained by an artificial neural network (ANN) model which is implemented to simulate the normal and faulty status of rotary machine. Correlation between the product quality defined by an index and the residual is used to quality classification.

Keywords: Modeling, fault detection and diagnosis, parameters estimation, neural networks, Fault Detection and Diagnosis (FDD), pickling process.

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Authors: H. Abaali, M. T. Lamchich, M. Raoufi

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In this paper, we propose the Modified Synchronous Detection (MSD) Method for determining the reference compensating currents of the shunt active power filter under non sinusoidal voltages conditions. For controlling the inverter switching we used the PI regulator. The numerical simulation results, using Power System Blockset Toolbox PSB of Matlab, from a complete structure, are presented and discussed.

Keywords: Distorted, harmonic, Modified Synchronous Detection Method, PI regulator, Shunt Active Power Filter, unbalanced.

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Authors: Joval P George, Dr. Zheng Chen, Philip Shaw

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This paper deals with the application of Principal Component Analysis (PCA) and the Hotelling-s T2 Chart, using data collected from a drinking water treatment process. PCA is applied primarily for the dimensional reduction of the collected data. The Hotelling-s T2 control chart was used for the fault detection of the process. The data was taken from a United Utilities Multistage Water Treatment Works downloaded from an Integrated Program Management (IPM) dashboard system. The analysis of the results show that Multivariate Statistical Process Control (MSPC) techniques such as PCA, and control charts such as Hotelling-s T2, can be effectively applied for the early fault detection of continuous multivariable processes such as Drinking Water Treatment. The software package SIMCA-P was used to develop the MSPC models and Hotelling-s T2 Chart from the collected data.

Keywords: Principal component analysis, hotelling's t2 chart, multivariate statistical process control, drinking water treatment.

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Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

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Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: Cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing.

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Authors: Ali Rabiee, Hessam Ghasemnejad

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Extensive experimental investigation on the effect of stitching pattern on tubular composite structures was conducted. The effect of stitching reinforcement through thickness on using glass flux yarn on energy absorption of fiber-reinforced polymer (FRP) was investigated under high speed loading conditions at axial loading. Keeping the mass of the structure at 125 grams and applying different pattern of stitching at various locations in theory enables better energy absorption, and also enables the control over the behaviour of force-crush distance curve. The study consists of simple non-stitch absorber comparison with single and multi-location stitching behaviour and its effect on energy absorption capabilities. The locations of reinforcements are 10 mm, 20 mm, 30 mm, 10-20 mm, 10-30 mm, 20-30 mm, 10-20-30 mm and 10-15-20-25-30-35 mm from the top of the specimen. The effect of through the thickness reinforcements has shown increase in energy absorption capabilities and crushing load. The significance of this is that as the stitching locations are closer, the crushing load increases and consequently energy absorption capabilities are also increased. The implementation of this idea would improve the mean force by applying stitching and controlling the behaviour of force-crush distance curve.

Keywords: Through-thickness, stitching, reinforcement, Tulbular composite structures, energy absorption.

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Authors: Ching-Fen Jiang

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Edge detection is usually the first step in medical image processing. However, the difficulty increases when a conventional kernel-based edge detector is applied to ultrasonic images with a textural pattern and speckle noise. We designed an adaptive diffusion filter to remove speckle noise while preserving the initial edges detected by using a Sobel edge detector. We also propose a genetic algorithm for edge selection to form complete boundaries of the detected entities. We designed two fitness functions to evaluate whether a criterion with a complex edge configuration can render a better result than a simple criterion such as the strength of gradient. The edges obtained by using a complex fitness function are thicker and more fragmented than those obtained by using a simple fitness function, suggesting that a complex edge selecting scheme is not necessary for good edge detection in medical ultrasonic images; instead, a proper noise-smoothing filter is the key.

Keywords: edge detection, ultrasonic images, speckle noise

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Authors: M. M. Abutaleb, A. Hamdy, M. E. Abuelwafa, E. M. Saad

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Optical flow is a research topic of interest for many years. It has, until recently, been largely inapplicable to real-time applications due to its computationally expensive nature. This paper presents a new reliable flow technique which is combined with a motion detection algorithm, from stationary camera image streams, to allow flow-based analyses of moving entities, such as rigidity, in real-time. The combination of the optical flow analysis with motion detection technique greatly reduces the expensive computation of flow vectors as compared with standard approaches, rendering the method to be applicable in real-time implementation. This paper describes also the hardware implementation of a proposed pipelined system to estimate the flow vectors from image sequences in real time. This design can process 768 x 576 images at a very high frame rate that reaches to 156 fps in a single low cost FPGA chip, which is adequate for most real-time vision applications.

Keywords: Optical flow, motion detection, real-time systems, FPGA.

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Authors: T. Davitashvili, G. Gubelidze

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In this paper two mathematical models for definition of gas accidental escape localization in the gas pipelines are suggested. The first model was created for leak localization in the horizontal branched pipeline and second one for leak detection in inclined section of the main gas pipeline. The algorithm of leak localization in the branched pipeline did not demand on knowledge of corresponding initial hydraulic parameters at entrance and ending points of each sections of pipeline. For detection of the damaged section and then leak localization in this section special functions and equations have been constructed. Some results of calculations for compound pipelines having two, four and five sections are presented. Also a method and formula for the leak localization in the simple inclined section of the main gas pipeline are suggested. Some results of numerical calculations defining localization of gas escape for the inclined pipeline are presented.

Keywords: Branched and inclined gas pipelines, leak detection, mathematical modeling.

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Authors: Shobha Sharma, Amita Dev, Akanksha Kant

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Digital signal processor, image signal processor and FIR filters have multipliers as an important part of their design. On the basis of Vedic mathematics, Vedic multipliers have come out to be very fast multipliers. One of the image processing applications is edge detection. This research presents a small area and high speed 8 bit Vedic multiplier system comprising of compressor based adders. This results in faster edge detection. This architecture is tested on Xilinx vertex 4 FPGA board and simulations were carried out using the Xilinx synthesis tool. Comparisons are made and this system is found to be smaller in area with high speed (the lesser propagation delay). This compressor based Vedic multiplier is 1.1 times speedier than a typical Vedic multiplier. Also, this Vedic Multiplier is 2 times speedier than a ‘simple’ multiplier.

Keywords: Detection of edges, Vedic multiplier, image processing, Urdhva Tiryakbhyam sutra.

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Authors: Bandula-Heva, T., Dhanasekar, M.

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True stress-strain curve of railhead steel is required to investigate the behaviour of railhead under wheel loading through elasto-plastic Finite Element (FE) analysis. To reduce the rate of wear, the railhead material is hardened through annealing and quenching. The Australian standard rail sections are not fully hardened and hence suffer from non-uniform distribution of the material property; usage of average properties in the FE modelling can potentially induce error in the predicted plastic strains. Coupons obtained at varying depths of the railhead were, therefore, tested under axial tension and the strains were measured using strain gauges as well as an image analysis technique, known as the Particle Image Velocimetry (PIV). The head hardened steel exhibit existence of three distinct zones of yield strength; the yield strength as the ratio of the average yield strength provided in the standard (σyr=780MPa) and the corresponding depth as the ratio of the head hardened zone along the axis of symmetry are as follows: (1.17 σyr, 20%), (1.06 σyr, 20%-80%) and (0.71 σyr, > 80%). The stress-strain curves exhibit limited plastic zone with fracture occurring at strain less than 0.1.

Keywords: Stress-Strain Curve, Tensile Test, Particle Image Velocimetry, Railhead Metal Properties

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Authors: Simon Lessard, Pascal Bigras, Caroline Lau, Daniel Roy, Gilles Soulez, Jacques A. de Guise

Abstract:

The segmentation of endovascular tools in fluoroscopy images can be accurately performed automatically or by minimum user intervention, using known modern techniques. It has been proven in literature, but no clinical implementation exists so far because the computational time requirements of such technology have not yet been met. A classical segmentation scheme is composed of edge enhancement filtering, line detection, and segmentation. A new method is presented that consists of a vector that propagates in the image to track an edge as it advances. The filtering is performed progressively in the projected path of the vector, whose orientation allows for oriented edge detection, and a minimal image area is globally filtered. Such an algorithm is rapidly computed and can be implemented in real-time applications. It was tested on medical fluoroscopy images from an endovascular cerebral intervention. Ex- periments showed that the 2D tracking was limited to guidewires without intersection crosspoints, while the 3D implementation was able to cope with such planar difficulties.

Keywords: Edge detection, Line Enhancement, Segmentation, Fluoroscopy.

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Authors: Fırat Matur, Yekta Ülgen

Abstract:

Cole-Cole parameters of 40 post-menopausal women are compared with their DEXA bone mineral density measurements. Impedance characteristics of four extremities are compared; left and right extremities are statistically same, but lower extremities are statistically different than upper ones due to their different fat content. The correlation of Cole-Cole impedance parameters to bone mineral density (BMD) is observed to be higher for dominant arm. With the post-menopausal population, ANOVA tests of the dominant arm characteristic frequency, as a predictor for DEXA classified osteopenic and osteoporic population around lumbar spine, is statistically very significant. When used for total lumbar spine osteoporosis diagnosis, the area under the Receiver Operating Curve of the characteristic frequency is 0.830, suggesting that the Cole-Cole plot characteristic frequency could be a useful diagnostic parameter when integrated into standard screening methods for osteoporosis. Moreover, the characteristic frequency can be directly measured by monitoring frequency driven angular behavior of the dominant arm without performing any complex calculation.

Keywords: Bio-impedance spectroscopy, bone mineral density, characteristic frequency, osteoporosis, receiver operating curve.

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