Search results for: vector median filtering
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1897

Search results for: vector median filtering

1807 An Erudite Technique for Face Detection and Recognition Using Curvature Analysis

Authors: S. Jagadeesh Kumar

Abstract:

Face detection and recognition is an authoritative technology for image database management, video surveillance, and human computer interface (HCI). Face recognition is a rapidly nascent method, which has been extensively discarded in forensics such as felonious identification, tenable entree, and custodial security. This paper recommends an erudite technique using curvature analysis (CA) that has less false positives incidence, operative in different light environments and confiscates the artifacts that are introduced during image acquisition by ring correction in polar coordinate (RCP) method. This technique affronts mean and median filtering technique to remove the artifacts but it works in polar coordinate during image acquisition. Investigational fallouts for face detection and recognition confirms decent recitation even in diagonal orientation and stance variation.

Keywords: curvature analysis, ring correction in polar coordinate method, face detection, face recognition, human computer interaction

Procedia PDF Downloads 254
1806 Improvements in OpenCV's Viola Jones Algorithm in Face Detection–Skin Detection

Authors: Jyoti Bharti, M. K. Gupta, Astha Jain

Abstract:

This paper proposes a new improved approach for false positives filtering of detected face images on OpenCV’s Viola Jones Algorithm In this approach, for Filtering of False Positives, Skin Detection in two colour spaces i.e. HSV (Hue, Saturation and Value) and YCrCb (Y is luma component and Cr- red difference, Cb- Blue difference) is used. As a result, it is found that false detection has been reduced. Our proposed method reaches the accuracy of about 98.7%. Thus, a better recognition rate is achieved.

Keywords: face detection, Viola Jones, false positives, OpenCV

Procedia PDF Downloads 374
1805 Space Vector PWM and Model Predictive Control for Voltage Source Inverter Control

Authors: Irtaza M. Syed, Kaamran Raahemifar

Abstract:

In this paper, we present a comparative assessment of Space Vector Pulse Width Modulation (SVPWM) and Model Predictive Control (MPC) for two-level three phase (2L-3P) Voltage Source Inverter (VSI). VSI with associated system is subjected to both control techniques and the results are compared. Matlab/Simulink was used to model, simulate and validate the control schemes. Findings of this study show that MPC is superior to SVPWM in terms of total harmonic distortion (THD) and implementation.

Keywords: voltage source inverter, space vector pulse width modulation, model predictive control, comparison

Procedia PDF Downloads 479
1804 Computational Modeling of Load Limits of Carbon Fibre Composite Laminates Subjected to Low-Velocity Impact Utilizing Convolution-Based Fast Fourier Data Filtering Algorithms

Authors: Farhat Imtiaz, Umar Farooq

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In this work, we developed a computational model to predict ply level failure in impacted composite laminates. Data obtained from physical testing from flat and round nose impacts of 8-, 16-, 24-ply laminates were considered. Routine inspections of the tested laminates were carried out to approximate ply by ply inflicted damage incurred. Plots consisting of load–time, load–deflection, and energy–time history were drawn to approximate the inflicted damages. Impact test generated unwanted data logged due to restrictions on testing and logging systems were also filtered. Conventional filters (built-in, statistical, and numerical) reliably predicted load thresholds for relatively thin laminates such as eight and sixteen ply panels. However, for relatively thick laminates such as twenty-four ply laminates impacted by flat nose impact generated clipped data which can just be de-noised using oscillatory algorithms. The literature search reveals that modern oscillatory data filtering and extrapolation algorithms have scarcely been utilized. This investigation reports applications of filtering and extrapolation of the clipped data utilising fast Fourier Convolution algorithm to predict load thresholds. Some of the results were related to the impact-induced damage areas identified with Ultrasonic C-scans and found to be in acceptable agreement. Based on consistent findings, utilizing of modern data filtering and extrapolation algorithms to data logged by the existing machines has efficiently enhanced data interpretations without resorting to extra resources. The algorithms could be useful for impact-induced damage approximations of similar cases.

Keywords: fibre reinforced laminates, fast Fourier algorithms, mechanical testing, data filtering and extrapolation

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1803 Exploring Students' Alternative Conception in Vector Components

Authors: Umporn Wutchana

Abstract:

An open ended problem and unstructured interview had been used to explore students’ conceptual and procedural understanding of vector components. The open ended problem had been designed based on research instrument used in previous physics education research. Without physical context, we asked students to find out magnitude and draw graphical form of vector components. The open ended problem was given to 211 first year students of faculty of science during the third (summer) semester in 2014 academic year. The students spent approximately 15 minutes of their second time of the General Physics I course to complete the open ended problem after they had failed. Consequently, their responses were classified based on the similarity of errors performed in the responses. Then, an unstructured interview was conducted. 7 students were randomly selected and asked to reason and explain their answers. The study results showed that 53% of 211 students provided correct numerical magnitude of vector components while 10.9% of them confused and punctuated the magnitude of vectors in x- with y-components. Others 20.4% provided just symbols and the last 15.6% gave no answer. When asking to draw graphical form of vector components, only 10% of 211 students made corrections. A majority of them produced errors and revealed alternative conceptions. 46.5% drew longer and/or shorter magnitude of vector components. 43.1% drew vectors in different forms or wrote down other symbols. Results from the unstructured interview indicated that some students just memorized the method to get numerical magnitude of x- and y-components. About graphical form of component vectors, some students though that the length of component vectors should be shorter than those of the given one. So then, it could be combined to be equal length of the given vectors while others though that component vectors should has the same length as the given vectors. It was likely to be that many students did not develop a strong foundation of understanding in vector components but just learn by memorizing its solution or the way to compute its magnitude and attribute little meaning to such concept.

Keywords: graphical vectors, vectors, vector components, misconceptions, alternative conceptions

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1802 Extracting Terrain Points from Airborne Laser Scanning Data in Densely Forested Areas

Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

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Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: airborne laser scanning, digital terrain models, filtering, forested areas

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1801 An Epsilon Hierarchical Fuzzy Twin Support Vector Regression

Authors: Arindam Chaudhuri

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The research presents epsilon- hierarchical fuzzy twin support vector regression (epsilon-HFTSVR) based on epsilon-fuzzy twin support vector regression (epsilon-FTSVR) and epsilon-twin support vector regression (epsilon-TSVR). Epsilon-FTSVR is achieved by incorporating trapezoidal fuzzy numbers to epsilon-TSVR which takes care of uncertainty existing in forecasting problems. Epsilon-FTSVR determines a pair of epsilon-insensitive proximal functions by solving two related quadratic programming problems. The structural risk minimization principle is implemented by introducing regularization term in primal problems of epsilon-FTSVR. This yields dual stable positive definite problems which improves regression performance. Epsilon-FTSVR is then reformulated as epsilon-HFTSVR consisting of a set of hierarchical layers each containing epsilon-FTSVR. Experimental results on both synthetic and real datasets reveal that epsilon-HFTSVR has remarkable generalization performance with minimum training time.

Keywords: regression, epsilon-TSVR, epsilon-FTSVR, epsilon-HFTSVR

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1800 Calculation of the Normalized Difference Vegetation Index and the Spectral Signature of Coffee Crops: Benefits of Image Filtering on Mixed Crops

Authors: Catalina Albornoz, Giacomo Barbieri

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Crop monitoring has shown to reduce vulnerability to spreading plagues and pathologies in crops. Remote sensing with Unmanned Aerial Vehicles (UAVs) has made crop monitoring more precise, cost-efficient and accessible. Nowadays, remote monitoring involves calculating maps of vegetation indices by using different software that takes either Truecolor (RGB) or multispectral images as an input. These maps are then used to segment the crop into management zones. Finally, knowing the spectral signature of a crop (the reflected radiation as a function of wavelength) can be used as an input for decision-making and crop characterization. The calculation of vegetation indices using software such as Pix4D has high precision for monoculture plantations. However, this paper shows that using this software on mixed crops may lead to errors resulting in an incorrect segmentation of the field. Within this work, authors propose to filter all the elements different from the main crop before the calculation of vegetation indices and the spectral signature. A filter based on the Sobel method for border detection is used for filtering a coffee crop. Results show that segmentation into management zones changes with respect to the traditional situation in which a filter is not applied. In particular, it is shown how the values of the spectral signature change in up to 17% per spectral band. Future work will quantify the benefits of filtering through the comparison between in situ measurements and the calculated vegetation indices obtained through remote sensing.

Keywords: coffee, filtering, mixed crop, precision agriculture, remote sensing, spectral signature

Procedia PDF Downloads 362
1799 Semigroups of Linear Transformations with Fixed Subspaces: Green’s Relations and Ideals

Authors: Yanisa Chaiya, Jintana Sanwong

Abstract:

Let V be a vector space over a field and W a subspace of V. Let Fix(V,W) denote the set of all linear transformations on V with fix all elements in W. In this paper, we show that Fix(V,W) is a semigroup under the composition of maps and describe Green’s relations on this semigroup in terms of images, kernels and the dimensions of subspaces of the quotient space V/W where V/W = {v+W : v is an element in V} with v+W = {v+w : w is an element in W}. Let dim(U) denote the dimension of a vector space U and Vα = {vα : v is an element in V} where vα is an image of v under a linear transformation α. For any cardinal number a let a'= min{b : b > a}. We also show that the ideals of Fix(V,W) are precisely the sets. Fix(r) ={α ∊ Fix(V,W) : dim(Vα/W) < r} where 1 ≤ r ≤ a' and a = dim(V/W). Moreover, we prove that if V is a finite-dimensional vector space, then every ideal of Fix(V,W) is principle.

Keywords: Green’s relations, ideals, linear transformation semi-groups, principle ideals

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1798 Road Accidents Bigdata Mining and Visualization Using Support Vector Machines

Authors: Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

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Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classifiers from the obtained traffic data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.

Keywords: support vector mechanism (SVM), machine learning (ML), support vector machines (SVM), department of transportation (DFT)

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1797 Retrospective Evaluation of Vector-borne Infections in Cats Living in Germany (2012-2019)

Authors: I. Schäfer, B. Kohn, M. Volkmann, E. Müller

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Introduction: Blood-feeding arthropods transmit parasitic, bacterial, or viral pathogens to domestic animals and wildlife. Vector-borne infections are gaining significance due to the increase of travel, import of domestic animals from abroad, and the changing climate in Europe. Aims of the study: The main objective of this retrospective study was to assess the prevalence of vector-borne infections in cats in which a ‘Feline Travel Profile’ had been conducted. Material and Methods: This retrospective study included test results from cats for which a ‘Feline Travel Profile’ established by LABOKLIN had been requested by veterinarians between April 2012 and December 2019. This profile contains direct detection methods via polymerase chain reaction (PCR) for Hepatozoon spp. and Dirofilaria spp. as well as indirect detection methods via immunofluorescence antibody test (IFAT) for Ehrlichia spp. and Leishmania spp. This profile was expanded to include an IFAT for Rickettsia spp. from July 2015 onwards. The prevalence of the different vector-borne infectious agents was calculated. Results: A total of 602 cats were tested using the ‘Feline Travel Profile’. Positive test results were as follows: Rickettsia spp. IFAT 54/442 (12.2%), Ehrlichia spp. IFAT 68/602 (11.3%), Leishmania spp. IFAT 21/602 (3.5%), Hepatozoon spp. PCR 51/595 (8.6%), and Dirofilaria spp. PCR 1/595 cats (0.2%). Co-infections with more than one pathogen could be detected in 22/602 cats. Conclusions: 170/602 cats (28.2%) were tested positive for at least one vector-borne pathogen. Infections with multiple pathogens could be detected in 3.7% of the cats. The data emphasizes the importance of considering vector-borne infections as potential differential diagnoses in cats.

Keywords: arthopod-transmitted infections, feline vector-borne infections, Germany, laboratory diagnostics

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1796 Savi Scout versus Wire-Guided Localization in Non-palpable Breast Lesions – Comparison of Breast Tissue Volume and Weight and Excision Safety Margin

Authors: Walid Ibrahim, Abdul Kasem, Sudeendra Doddi, Ilaria Giono, Tareq Sabagh, Muhammad Ammar, Nermin Osman

Abstract:

Background: wire-guided localization (WL) is the most widely used method for the localization of non-palpable breast lesions. SAVI SCOUT occult lesion localization (SSL) is a new technique in breast-conservative surgery. SSL has the potential benefit of improving radiology workflow as well as accurate localization. Purpose: The purpose of this study is to compare the breast tissue specimen volume and weight and margin excision between WL and SSL. Materials and methods: A single institution retrospective analysis of 377 female patients who underwent wide local breast excision with SAVI SCOUT and or wire-guided technique between 2018 and 2021 in a UK University teaching hospital. Breast department. Breast tissue specimen volume and weight, and margin excision have been evaluated in the three groups of different localization. Results: Three hundred and seventy-seven patients were studied. Of these, 261 had wire localization, 88 had SCOUT and 28 had dual localization techniques. Tumor size ranged from 1 to 75mm (Median 20mm). The pathology specimen weight ranged from 1 to 466gm (Median 46.8) and the volume ranged from 1.305 to 1560cm³ (Median 106.32 cm³). SCOUT localization was associated with a significantly low specimen weight than wire or the dual technique localization (Median 41gm vs 47.3gm and 47gm, p = 0.029). SCOUT was not associated with better specimen volume with a borderline significance in comparison to wire and combined techniques (Median 108cm³ vs 105cm³ and 105cm³, p = 0.047). There was a significant correlation between tumor size and pathology specimen weight in the three groups. SCOUT showed a better >2mm safety margin in comparison to the other 2 techniques (p = 0.031). Conclusion: Preoperative SCOUT localization is associated with better specimen weight and better specimen margin. SCOUT did not show any benefits in terms of specimen volume which may be due to difficulty in getting the accurate specimen volume due to the irregularity of the soft tissue specimen.

Keywords: scout, wire, localization, breast

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1795 Recent Advances in Pulse Width Modulation Techniques and Multilevel Inverters

Authors: Satish Kumar Peddapelli

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This paper presents advances in pulse width modulation techniques which refers to a method of carrying information on train of pulses and the information be encoded in the width of pulses. Pulse Width Modulation is used to control the inverter output voltage. This is done by exercising the control within the inverter itself by adjusting the ON and OFF periods of inverter. By fixing the DC input voltage we get AC output voltage. In variable speed AC motors the AC output voltage from a constant DC voltage is obtained by using inverter. Recent developments in power electronics and semiconductor technology have lead improvements in power electronic systems. Hence, different circuit configurations namely multilevel inverters have become popular and considerable interest by researcher are given on them. A fast Space-Vector Pulse Width Modulation (SVPWM) method for five-level inverter is also discussed. In this method, the space vector diagram of the five-level inverter is decomposed into six space vector diagrams of three-level inverters. In turn, each of these six space vector diagrams of three-level inverter is decomposed into six space vector diagrams of two-level inverters. After decomposition, all the remaining necessary procedures for the three-level SVPWM are done like conventional two-level inverter. The proposed method reduces the algorithm complexity and the execution time. It can be applied to the multilevel inverters above the five-level also. The experimental setup for three-level diode-clamped inverter is developed using TMS320LF2407 DSP controller and the experimental results are analysed.

Keywords: five-level inverter, space vector pulse wide modulation, diode clamped inverter, electrical engineering

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1794 Nontuberculous Mycobacterium Infection – Still An Important Disease Among People With Late HIV Diagnosis

Authors: Jakub Młoźniak, Adam Szymański, Gabriela Stondzik, Dagny Krankowska, Tomasz Mikuła

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Nontuberculous mycobacteria (NTM) are bacterial species that cause diversely manifesting diseases mainly in immunocompromised patients. In people with HIV, NTM infection is an AIDS-defining disease and usually appears when the lymphocyte T CD4 count is below 50 cells/μl. The usage of antiretroviral therapy has decreased the prevalence of NTM among people with HIV, but the disease can still be observed especially among patients with late HIV diagnosis. Common presence in environment, human colonization, clinical similarity with tuberculosis and slow growth on culture makes NTM especially hard to diagnose. The study aimed to analyze the epidemiology and clinical course of NTM among patients with HIV. This study included patients with NTM and HIV admitted to our department between 2017 and 2023. Medical records of patients were analyzed and data on age, sex, median time from HIV diagnosis to identification of NTM infection, median CD4 count at NTM diagnosis, methods of determining NTM infection, type of species of mycobacteria identified, clinical symptoms and treatment course were gathered. Twenty-four patients (20 men, 4 women) with identified NTM were included in this study. Among them, 20 were HIV late presenters. The patients' median age was 40. The main symptoms which patients presented were fever, weight loss and cough. Pulmonary disease confirmed with positive cultures from sputum/bronchoalveolar lavage was present in 18 patients. M. avium was the most common species identified. M. marinum caused disseminated skin lesions in 1 patient. Out of all, 5 people were not treated for NTM caused by lack of symptoms and suspicion of colonization with mycobacterium. Concomitant tuberculosis was present in 6 patients. The median diagnostic time from HIV to NTM infections was 3.5 months. The median CD4 count at NTM identification was 69.5 cells/μl. Median NTM treatment time was 16 months but 7 patients haven’t finished their treatment yet. The most commonly used medications were ethambutol and clarithromycin. Among analyzed patients, 4 of them have died. NTM infections are still an important disease among patients who are HIV late presenters. This disease should be taken into consideration during the differential diagnosis of fever, weight loss and cough in people with HIV with lymphocyte T CD4 count <100 cells/μl. Presence of tuberculosis does not exclude nontuberculous mycobacterium coinfection.

Keywords: mycobacteriosis, HIV, late presenter, epidemiology

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1793 Depth Camera Aided Dead-Reckoning Localization of Autonomous Mobile Robots in Unstructured GNSS-Denied Environments

Authors: David L. Olson, Stephen B. H. Bruder, Adam S. Watkins, Cleon E. Davis

Abstract:

In global navigation satellite systems (GNSS), denied settings such as indoor environments, autonomous mobile robots are often limited to dead-reckoning navigation techniques to determine their position, velocity, and attitude (PVA). Localization is typically accomplished by employing an inertial measurement unit (IMU), which, while precise in nature, accumulates errors rapidly and severely degrades the localization solution. Standard sensor fusion methods, such as Kalman filtering, aim to fuse precise IMU measurements with accurate aiding sensors to establish a precise and accurate solution. In indoor environments, where GNSS and no other a priori information is known about the environment, effective sensor fusion is difficult to achieve, as accurate aiding sensor choices are sparse. However, an opportunity arises by employing a depth camera in the indoor environment. A depth camera can capture point clouds of the surrounding floors and walls. Extracting attitude from these surfaces can serve as an accurate aiding source, which directly combats errors that arise due to gyroscope imperfections. This configuration for sensor fusion leads to a dramatic reduction of PVA error compared to traditional aiding sensor configurations. This paper provides the theoretical basis for the depth camera aiding sensor method, initial expectations of performance benefit via simulation, and hardware implementation, thus verifying its veracity. Hardware implementation is performed on the Quanser Qbot 2™ mobile robot, with a Vector-Nav VN-200™ IMU and Kinect™ camera from Microsoft.

Keywords: autonomous mobile robotics, dead reckoning, depth camera, inertial navigation, Kalman filtering, localization, sensor fusion

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1792 Markov-Chain-Based Optimal Filtering and Smoothing

Authors: Garry A. Einicke, Langford B. White

Abstract:

This paper describes an optimum filter and smoother for recovering a Markov process message from noisy measurements. The developments follow from an equivalence between a state space model and a hidden Markov chain. The ensuing filter and smoother employ transition probability matrices and approximate probability distribution vectors. The properties of the optimum solutions are retained, namely, the estimates are unbiased and minimize the variance of the output estimation error, provided that the assumed parameter set are correct. Methods for estimating unknown parameters from noisy measurements are discussed. Signal recovery examples are described in which performance benefits are demonstrated at an increased calculation cost.

Keywords: optimal filtering, smoothing, Markov chains

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1791 Possibility of Creating Polygon Layers from Raster Layers Obtained by using Classic Image Processing Software: Case of Geological Map of Rwanda

Authors: Louis Nahimana

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Most maps are in a raster or pdf format and it is not easy to get vector layers of published maps. Faced to the production of geological simplified map of the northern Lake Tanganyika countries without geological information in vector format, I tried a method of obtaining vector layers from raster layers created from geological maps of Rwanda and DR Congo in pdf and jpg format. The procedure was as follows: The original raster maps were georeferenced using ArcGIS10.2. Under Adobe Photoshop, map areas with the same color corresponding to a lithostratigraphic unit were selected all over the map and saved in a specific raster layer. Using the same image processing software Adobe Photoshop, each RGB raster layer was converted in grayscale type and improved before importation in ArcGIS10. After georeferencing, each lithostratigraphic raster layer was transformed into a multitude of polygons with the tool "Raster to Polygon (Conversion)". Thereafter, tool "Aggregate Polygons (Cartography)" allowed obtaining a single polygon layer. Repeating the same steps for each color corresponding to a homogeneous rock unit, it was possible to reconstruct the simplified geological constitution of Rwanda and the Democratic Republic of Congo in vector format. By using the tool «Append (Management)», vector layers obtained were combined with those from Burundi to achieve vector layers of the geology of the « Northern Lake Tanganyika countries ».

Keywords: creating raster layer under image processing software, raster to polygon, aggregate polygons, adobe photoshop

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1790 Investigation of the Effects of Sampling Frequency on the THD of 3-Phase Inverters Using Space Vector Modulation

Authors: Khattab Al Qaisi, Nicholas Bowring

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This paper presents the simulation results of the effects of sampling frequency on the total harmonic distortion (THD) of three-phase inverters using the space vector pulse width modulation (SVPWM) and space vector control (SVC) algorithms. The relationship between the variables was studied using curve fitting techniques, and it has been shown that, for 50 Hz inverters, there is an exponential relation between the sampling frequency and THD up to around 8500 Hz, beyond which the performance of the model becomes irregular, and there is an negative exponential relation between the sampling frequency and the marginal improvement to the THD. It has also been found that the performance of SVPWM is better than that of SVC with the same sampling frequency in most frequency range, including the range where the performance of the former is irregular.

Keywords: DSI, SVPWM, THD, DC-AC converter, sampling frequency, performance

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1789 Ultra-Tightly Coupled GNSS/INS Based on High Degree Cubature Kalman Filtering

Authors: Hamza Benzerrouk, Alexander Nebylov

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In classical GNSS/INS integration designs, the loosely coupled approach uses the GNSS derived position and the velocity as the measurements vector. This design is suboptimal from the standpoint of preventing GNSSoutliers/outages. The tightly coupled GPS/INS navigation filter mixes the GNSS pseudo range and inertial measurements and obtains the vehicle navigation state as the final navigation solution. The ultra‐tightly coupled GNSS/INS design combines the I (inphase) and Q(quadrature) accumulator outputs in the GNSS receiver signal tracking loops and the INS navigation filter function intoa single Kalman filter variant (EKF, UKF, SPKF, CKF and HCKF). As mentioned, EKF and UKF are the most used nonlinear filters in the literature and are well adapted to inertial navigation state estimation when integrated with GNSS signal outputs. In this paper, it is proposed to move a step forward with more accurate filters and modern approaches called Cubature and High Degree cubature Kalman Filtering methods, on the basis of previous results solving the state estimation based on INS/GNSS integration, Cubature Kalman Filter (CKF) and High Degree Cubature Kalman Filter with (HCKF) are the references for the recent developed generalized Cubature rule based Kalman Filter (GCKF). High degree cubature rules are the kernel of the new solution for more accurate estimation with less computational complexity compared with the Gauss-Hermite Quadrature (GHQKF). Gauss-Hermite Kalman Filter GHKF which is not selected in this work because of its limited real-time implementation in high-dimensional state-spaces. In ultra tightly or a deeply coupled GNSS/INS system is dynamics EKF is used with transition matrix factorization together with GNSS block processing which is well described in the paper and assumes available the intermediary frequency IF by using a correlator samples with a rate of 500 Hz in the presented approach. GNSS (GPS+GLONASS) measurements are assumed available and modern SPKF with Cubature Kalman Filter (CKF) are compared with new versions of CKF called high order CKF based on Spherical-radial cubature rules developed at the fifth order in this work. Estimation accuracy of the high degree CKF is supposed to be comparative to GHKF, results of state estimation are then observed and discussed for different initialization parameters. Results show more accurate navigation state estimation and more robust GNSS receiver when Ultra Tightly Coupled approach applied based on High Degree Cubature Kalman Filter.

Keywords: GNSS, INS, Kalman filtering, ultra tight integration

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1788 Heart Murmurs and Heart Sounds Extraction Using an Algorithm Process Separation

Authors: Fatima Mokeddem

Abstract:

The phonocardiogram signal (PCG) is a physiological signal that reflects heart mechanical activity, is a promising tool for curious researchers in this field because it is full of indications and useful information for medical diagnosis. PCG segmentation is a basic step to benefit from this signal. Therefore, this paper presents an algorithm that serves the separation of heart sounds and heart murmurs in case they exist in order to use them in several applications and heart sounds analysis. The separation process presents here is founded on three essential steps filtering, envelope detection, and heart sounds segmentation. The algorithm separates the PCG signal into S1 and S2 and extract cardiac murmurs.

Keywords: phonocardiogram signal, filtering, Envelope, Detection, murmurs, heart sounds

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1787 Design and Implementation of a Software Platform Based on Artificial Intelligence for Product Recommendation

Authors: Giuseppina Settanni, Antonio Panarese, Raffaele Vaira, Maurizio Galiano

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Nowdays, artificial intelligence is used successfully in academia and industry for its ability to learn from a large amount of data. In particular, in recent years the use of machine learning algorithms in the field of e-commerce has spread worldwide. In this research study, a prototype software platform was designed and implemented in order to suggest to users the most suitable products for their needs. The platform includes a chatbot and a recommender system based on artificial intelligence algorithms that provide suggestions and decision support to the customer. The recommendation systems perform the important function of automatically filtering and personalizing information, thus allowing to manage with the IT overload to which the user is exposed on a daily basis. Recently, international research has experimented with the use of machine learning technologies with the aim to increase the potential of traditional recommendation systems. Specifically, support vector machine algorithms have been implemented combined with natural language processing techniques that allow the user to interact with the system, express their requests and receive suggestions. The interested user can access the web platform on the internet using a computer, tablet or mobile phone, register, provide the necessary information and view the products that the system deems them most appropriate. The platform also integrates a dashboard that allows the use of the various functions, which the platform is equipped with, in an intuitive and simple way. Artificial intelligence algorithms have been implemented and trained on historical data collected from user browsing. Finally, the testing phase allowed to validate the implemented model, which will be further tested by letting customers use it.

Keywords: machine learning, recommender system, software platform, support vector machine

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1786 A Robust and Adaptive Unscented Kalman Filter for the Air Fine Alignment of the Strapdown Inertial Navigation System/GPS

Authors: Jian Shi, Baoguo Yu, Haonan Jia, Meng Liu, Ping Huang

Abstract:

Adapting to the flexibility of war, a large number of guided weapons launch from aircraft. Therefore, the inertial navigation system loaded in the weapon needs to undergo an alignment process in the air. This article proposes the following methods to the problem of inaccurate modeling of the system under large misalignment angles, the accuracy reduction of filtering caused by outliers, and the noise changes in GPS signals: first, considering the large misalignment errors of Strapdown Inertial Navigation System (SINS)/GPS, a more accurate model is made rather than to make a small-angle approximation, and the Unscented Kalman Filter (UKF) algorithms are used to estimate the state; then, taking into account the impact of GPS noise changes on the fine alignment algorithm, the innovation adaptive filtering algorithm is introduced to estimate the GPS’s noise in real-time; at the same time, in order to improve the anti-interference ability of the air fine alignment algorithm, a robust filtering algorithm based on outlier detection is combined with the air fine alignment algorithm to improve the robustness of the algorithm. The algorithm can improve the alignment accuracy and robustness under interference conditions, which is verified by simulation.

Keywords: air alignment, fine alignment, inertial navigation system, integrated navigation system, UKF

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1785 Tracking Patient Pathway for Assessing Public Health and Financial Burden to Community for Pulmonary Tuberculosis: Pointer from Central India

Authors: Ashish Sinha, Pushpend Agrawal

Abstract:

Background: Patients with undiagnosed pulmonary TB predominantly act as reservoirs for its transmission through 10-15 secondary infections in the next 1-5 Yrs. Delays in the diagnosis and treatment may worsen the disease with increase the risk of death. Factors responsible for such delays by tracking patient pathways to treatment may help in planning better interventions. The provision of ‘free diagnosis and treatment’ forms the cornerstone of the National Tuberculosis Elimination Programme (NTEP). OOPE is defined as the money spent by the patient during TB care other than public health facilities. Free TB care at all health facilities could reduce out-of-pocket expenses to the minimum possible levels. Material and Methods: This cross-sectional study was conducted among randomly selected 252 TB patients from Nov – Oct 2022 by taking in-depth interviews following informed verbal consent. We documented their journey from initial symptoms until they reached the public health facility, along with their ‘out-of-pocket expenditure’ (OOPE) pertaining to TB care. Results: Total treatment delay was 91±72 days on average (median: 77days, IQR: 45-104 days), while the isolated patient delay was 31±45 days (median: 15 days, IQR: 0 days to 43 days); diagnostic delay; 57±60 days (median: 42days, IQR 14-78 days), treatment delay 19 ± 18 days (median: 15days, IQR: 11-19 days). A patient delay (> 30 days) was significantly associated with ignorance about classic symptoms of pulmonary TB, adoption of self-medication, illiteracy, and middle and lower social class. Diagnostic delay was significantly higher among those who contacted private health facilities, were unaware of signs and symptoms, had >2 consultations, and not getting an appropriate referral for TB care. Most (97%) of the study participants interviewed claimed to have incurred some expenditure.Median total expenses were 6155(IQR: 2625-15175) rupees. More than half 141 (56%) of the study participants had expenses >5000 rupees. Median transport expenses were 525(IQR: 200-1012) rupees; Median consultation expenses were 700(IQR: 200-1600) rupees; Median investigation expenses were 1000(IQR: 0-3025) rupees and the Median medicine expenses were 3350(IQR: 1300-7525).OOPE for consultation, investigation, and medicine was observed to be significantly higher among patients who ignored classical signs& symptoms of TB, repeated visits to private health facilities, and due to self-medication practices. Transport expenses and delays in seeking care at facilities were observed to have an upward trend with OOP Expenses (r =1). Conclusion: Delay in TB care due to low awareness about signs and symptoms of TB and poor seeking care, lack of proper consultation, and appropriate referrals reported by the study subjects indicate the areas which need proper attention by the program managers. Despite a centrally sponsored programme, the financial burden on TB patients is still in the unacceptable range. OOPE could be reduced as low as possible by addressing the responsible factors linked to it.

Keywords: patient pathway, delay, pulmonary tuberculosis, out of pocket expenses

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1784 A Horn Antenna Loaded with SIW FSS of Crossed Dipoles

Authors: Ibrahim Mostafa El-Mongy, Abdelmegid Allam

Abstract:

In this article analysis and investigation of the effect of loading a horn antenna with substrate integrated waveguide frequency selective surface (SIW FSS) of crossed dipoles of finite size is presented. It is fabricated on Rogers RO4350 (lossy) of relative permittivity 3.33, thickness 1.524mm and loss tangent 0.004. This structure is called a filtering antenna (filtenna). Basically it is applied for filtering and minimizing the interference and noise in the desired band. The filtration is carried out using a finite SIW FSS of crossed dipoles of overall dimensions 98x58 mm2. The filtration is shown by limiting the transmission bandwidth from 4 GHz (8–12 GHz) to 0.3 GHz (0.955–0.985 GHz). It is simulated using CST MWS and measured using network analyzer. There is a good agreement between the simulated and measured results.

Keywords: antenna, filtenna, frequency-selective surface (FSS), horn antennas

Procedia PDF Downloads 260
1783 Hybrid Anomaly Detection Using Decision Tree and Support Vector Machine

Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

Abstract:

Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: decision tree, feature selection, intrusion detection system, support vector machine

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1782 Radiation Dose and Associated Exposure Parameters in Selected MDCT Scanners in Multiphase Scan of Abdomen-Pelvic Region: A Clinical Study

Authors: P. Sathyathas, H. M. I. S. W. Herath, T. Amalraj, U. J. M. A. L. Jayasinghe

Abstract:

Over two thirds of medical radiation can now be attributed to Computed Tomography (CT). There is little information on amount of radiation received from multiphase CT scan of abdomen- pelvic region in clinical practice. We sought to estimate the radiation dose and associated exposure parameters in the multiphase abdomen - pelvic scan of Multideteror Computed Tomography (MDCT) studies in clinical practice. This was a retrospective cross sectional studies describing radiation dose associated with main exposure parameters in diagnostic multiphase abdomen - pelvic scans performed on 152 consecutive patients by two different sixteen slice CT scanners. Patient information, exposure parameters of CTDI (volume), DLP, kVp, mAs and pitch were recorded for every phases of abdomen- a pelvic study from dose report of MDCT scanners (MDCTs). Age of patients range from 14 years to 87 years in both MDCT scanners. Overall CTDI (volume) median was 63.8 (±10.4) mGy for a multiphase abdominal-pelvic scan with scanner A while it was 35.4 (±15.6) mGy for scanner B. Patients' effective dose for multiphase abdomen - pelvic CT scan range from 8.2 mSv to 58 mSv. Median effective dose for patients, who underwent multiphase abdomen- pelvis scan with scanner A and B were 38.5 (± 8.2) mSv and 21.3 (± 8.6) mSv respectively. Median value of exposure parameters of mAs, kVp and pitch, were 150 (±29.7), 130 (±15.3) and 1.3 (±0.1) respectively in scanner A. In scanner B; they were 60 (±14.5), 120 and 1. The median effective dose for patients between multiphase abdomen-pelvic scan of both MDCT, a significant different (P<0.05) was observed. Multiphase abdomen – pelvic scan of clinical study shows significant different of effective dose with reference level of phantom studies (8-14mSv) and it depends on the type of vendors.

Keywords: abdomen-pelvic region, computed tomography, exposure parameters, radiation dose

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1781 Numerical Investigation of Poling Vector Angle on Adaptive Sandwich Plate Deflection

Authors: Alireza Pouladkhan, Mohammad Yavari Foroushani, Ali Mortazavi

Abstract:

This paper presents a finite element model for a sandwich plate containing a piezoelectric core. A sandwich plate with a piezoelectric core is constructed using the shear mode of piezoelectric materials. The orientation of poling vector has a significant effect on deflection and stress induced in the piezo-actuated adaptive sandwich plate. In the present study, the influence of this factor for a clamped-clamped-free-free and simple-simple-free-free square sandwich plate is investigated using Finite Element Method. The study uses ABAQUS (v.6.7) software to derive the finite element model of the sandwich plate. By using this model, the study gives the influences of the poling vector angle on the response of the smart structure and determines the maximum transverse displacement and maximum stress induced.

Keywords: finite element method, sandwich plate, poling vector, piezoelectric materials, smart structure, electric enthalpy

Procedia PDF Downloads 210
1780 Application of Support Vector Machines in Fault Detection and Diagnosis of Power Transmission Lines

Authors: I. A. Farhat, M. Bin Hasan

Abstract:

A developed approach for the protection of power transmission lines using Support Vector Machines (SVM) technique is presented. In this paper, the SVM technique is utilized for the classification and isolation of faults in power transmission lines. Accurate fault classification and location results are obtained for all possible types of short circuit faults. As in distance protection, the approach utilizes the voltage and current post-fault samples as inputs. The main advantage of the method introduced here is that the method could easily be extended to any power transmission line.

Keywords: fault detection, classification, diagnosis, power transmission line protection, support vector machines (SVM)

Procedia PDF Downloads 533
1779 Determination of Medians of Biochemical Maternal Serum Markers in Healthy Women Giving Birth to Normal Babies

Authors: Noreen Noreen, Aamir Ijaz, Hamza Akhtar

Abstract:

Background: Screening plays a major role to detect chromosomal abnormalities, Down syndrome, neural tube defects and other inborn diseases of the newborn. Serum biomarkers in the second trimester are useful in determining risk of most common chromosomal anomalies; these test include Alpha-fetoprotein (AFP), Human chorionic gonadotropin (hCG), Unconjugated Oestriol (UEȝ)and inhibin-A. Quadruple biomarkers are worth test in diagnosing the congenital pathology during pregnancy, these procedures does not form a part of routine health care of pregnant women in Pakistan, so the median value is lacking for population in Pakistan. Objective: To determine median values of biochemical maternal serum markers in local population during second trimester maternal screening. Study settings: Department of Chemical Pathology and Endocrinology, Armed Forces Institute of Pathology (AFIP) Rawalpindi. Methods: Cross-Sectional study for estimation of reference values. Non-probability consecutive sampling, 155 healthy pregnant women, of 30-40 years of age, will be included. As non-parametric statistics will be used, the minimum sample size is 120. Result: Total 155 women were enrolled into this study. The age of all women enrolled ranged from 30 to39 yrs. Among them, 39 per cent of women were less than 34 years. Mean maternal age 33.46±2.35 SD and maternal body weight were 54.98±2.88. Median value of quadruple markers calculated from 15-18th week of gestation that will be used for calculation of MOM for screening of trisomy21 in this gestational age. Median value at 15 week of gestation were observed hCG 36650 mIU/ml, AFP 23.3 IU/ml, UEȝ 3.5 nmol/L, InhibinA 198 ng/L, at 16 week of gestation hCG 29050 mIU/ml, AFP 35.4 IU/ml, UEȝ 4.1 nmol/L, InhibinA 179 ng/L, at 17 week of gestation hCG 28450 mIU/ml, AFP 36.0 IU/ml, UEȝ 6.7 nmol/L, InhibinA 176 ng/L and at 18 week of gestation hCG 25200 mIU/ml, AFP 38.2 IU/ml, UEȝ 8.2 nmol/L, InhibinA 190 ng/L respectively.All the comparisons were significant (p-Value <0.005) with 95% confidence Interval (CI) and level of significance of study set by going through literature and set at 5%. Conclusion: The median values for these four biomarkers in Pakistani pregnant women can be used to calculate MoM.

Keywords: screening, down syndrome, quadruple test, second trimester, serum biomarkers

Procedia PDF Downloads 152
1778 Bird-Adapted Filter for Avian Species and Individual Identification Systems Improvement

Authors: Ladislav Ptacek, Jan Vanek, Jan Eisner, Alexandra Pruchova, Pavel Linhart, Ludek Muller, Dana Jirotkova

Abstract:

One of the essential steps of avian song processing is signal filtering. Currently, the standard methods of filtering are the Mel Bank Filter or linear filter distribution. In this article, a new type of bank filter called the Bird-Adapted Filter is introduced; whereby the signal filtering is modifiable, based upon a new mathematical description of audiograms for particular bird species or order, which was named the Avian Audiogram Unified Equation. According to the method, filters may be deliberately distributed by frequency. The filters are more concentrated in bands of higher sensitivity where there is expected to be more information transmitted and vice versa. Further, it is demonstrated a comparison of various filters for automatic individual recognition of chiffchaff (Phylloscopus collybita). The average Equal Error Rate (EER) value for Linear bank filter was 16.23%, for Mel Bank Filter 18.71%, the Bird-Adapted Filter gave 14.29%, and Bird-Adapted Filter with 1/3 modification was 12.95%. This approach would be useful for practical use in automatic systems for avian species and individual identification. Since the Bird-Adapted Filter filtration is based on the measured audiograms of particular species or orders, selecting the distribution according to the avian vocalization provides the most precise filter distribution to date.

Keywords: avian audiogram, bird individual identification, bird song processing, bird species recognition, filter bank

Procedia PDF Downloads 356