Search results for: tracking and control centers ATTTCC).
4037 A Location Routing Model for the Logistic System in the Mining Collection Centers of the Northern Region of Boyacá-Colombia
Authors: Erika Ruíz, Luis Amaya, Diego Carreño
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The main objective of this study is to design a mathematical model for the logistics of mining collection centers in the northern region of the department of Boyacá (Colombia), determining the structure that facilitates the flow of products along the supply chain. In order to achieve this, it is necessary to define a suitable design of the distribution network, taking into account the products, customer’s characteristics and the availability of information. Likewise, some other aspects must be defined, such as number and capacity of collection centers to establish, routes that must be taken to deliver products to the customers, among others. This research will use one of the operation research problems, which is used in the design of distribution networks known as Location Routing Problem (LRP).
Keywords: Location routing problem, logistic, mining collection, model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7724036 A New Method in Detection of Ceramic Tiles Color Defects Using Genetic C-Means Algorithm
Authors: Mahkameh S. Mostafavi
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In this paper an algorithm is used to detect the color defects of ceramic tiles. First the image of a normal tile is clustered using GCMA; Genetic C-means Clustering Algorithm; those results in best cluster centers. C-means is a common clustering algorithm which optimizes an objective function, based on a measure between data points and the cluster centers in the data space. Here the objective function describes the mean square error. After finding the best centers, each pixel of the image is assigned to the cluster with closest cluster center. Then, the maximum errors of clusters are computed. For each cluster, max error is the maximum distance between its center and all the pixels which belong to it. After computing errors all the pixels of defected tile image are clustered based on the centers obtained from normal tile image in previous stage. Pixels which their distance from their cluster center is more than the maximum error of that cluster are considered as defected pixels.
Keywords: C-Means algorithm, color spaces, Genetic Algorithm, image clustering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16364035 Person Re-Identification Using Siamese Convolutional Neural Network
Authors: Sello Mokwena, Monyepao Thabang
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In this study, we propose a comprehensive approach to address the challenges in person re-identification models. By combining a centroid tracking algorithm with a Siamese convolutional neural network model, our method excels in detecting, tracking, and capturing robust person features across non-overlapping camera views. The algorithm efficiently identifies individuals in the camera network, while the neural network extracts fine-grained global features for precise cross-image comparisons. The approach's effectiveness is further accentuated by leveraging the camera network topology for guidance. Our empirical analysis of benchmark datasets highlights its competitive performance, particularly evident when background subtraction techniques are selectively applied, underscoring its potential in advancing person re-identification techniques.
Keywords: Camera network, convolutional neural network topology, person tracking, person re-identification, Siamese.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 544034 Real-time Tracking in Image Sequences based-on Parameters Updating with Temporal and Spatial Neighborhoods Mixture Gaussian Model
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Gaussian mixture background model is widely used in moving target detection of the image sequences. However, traditional Gaussian mixture background model usually considers the time continuity of the pixels, and establishes background through statistical distribution of pixels without taking into account the pixels- spatial similarity, which will cause noise, imperfection and other problems. This paper proposes a new Gaussian mixture modeling approach, which combines the color and gradient of the spatial information, and integrates the spatial information of the pixel sequences to establish Gaussian mixture background. The experimental results show that the movement background can be extracted accurately and efficiently, and the algorithm is more robust, and can work in real time in tracking applications.Keywords: Gaussian mixture model, real-time tracking, sequence image, gradient.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14684033 Detection of Moving Images Using Neural Network
Authors: P. Latha, L. Ganesan, N. Ramaraj, P. V. Hari Venkatesh
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Motion detection is a basic operation in the selection of significant segments of the video signals. For an effective Human Computer Intelligent Interaction, the computer needs to recognize the motion and track the moving object. Here an efficient neural network system is proposed for motion detection from the static background. This method mainly consists of four parts like Frame Separation, Rough Motion Detection, Network Formation and Training, Object Tracking. This paper can be used to verify real time detections in such a way that it can be used in defense applications, bio-medical applications and robotics. This can also be used for obtaining detection information related to the size, location and direction of motion of moving objects for assessment purposes. The time taken for video tracking by this Neural Network is only few seconds.
Keywords: Frame separation, Correlation Network, Neural network training, Radial Basis Function, object tracking, Motion Detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31364032 Adaptive Gaussian Mixture Model for Skin Color Segmentation
Authors: Reza Hassanpour, Asadollah Shahbahrami, Stephan Wong
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Skin color based tracking techniques often assume a static skin color model obtained either from an offline set of library images or the first few frames of a video stream. These models can show a weak performance in presence of changing lighting or imaging conditions. We propose an adaptive skin color model based on the Gaussian mixture model to handle the changing conditions. Initial estimation of the number and weights of skin color clusters are obtained using a modified form of the general Expectation maximization algorithm, The model adapts to changes in imaging conditions and refines the model parameters dynamically using spatial and temporal constraints. Experimental results show that the method can be used in effectively tracking of hand and face regions.Keywords: Face detection, Segmentation, Tracking, Gaussian Mixture Model, Adaptation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24034031 Emerging Methods as a Tool for Obtaining Subconscious Feedback in E-commerce and Marketplace
Authors: J. Berčík, A. Mravcová, A. Rusková, P. Jurčišin, R. Virágh
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The online world is changing every day. With this comes the emergence and development of new business models. One of them is the sale of several types of products in one place. This type of sales in the form of online marketplaces has undergone a positive development in recent years and represents a kind of alternative to brick-and-mortar shopping centers. The main philosophy is to buy several products under one roof. Examples of popular e-commerce marketplaces are Amazon, eBay or Allegro. Their share of total e-commerce turnover is expected to even double in the coming years. The paper highlights possibilities for testing web applications and online marketplace using emerging methods like stationary eye camera (Eye tracking) and facial analysis (FaceReading).
Keywords: Emerging methods, consumer neuroscience, e-commerce, marketplace, user experience, user interface.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 294030 Modeling Sustainable Truck Rental Operations Using Closed-Loop Supply Chain Network
Authors: Khaled S. Abdallah, Abdel-Aziz M. Mohamed
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Moving industries consume numerous resources and dispose masses of used packaging materials. Proper sorting, recycling and disposing the packaging materials is necessary to avoid a sever pollution disaster. This research paper presents a conceptual model to propose sustainable truck rental operations instead of the regular one. An optimization model was developed to select the locations of truck rental centers, collection sites, maintenance and repair sites, and identify the rental fees to be charged for all routes that maximize the total closed supply chain profits. Fixed costs of vehicle purchasing, costs of constructing collection centers and repair centers, as well as the fixed costs paid to use disposal and recycling centers are considered. Operating costs include the truck maintenance, repair costs as well as the cost of recycling and disposing the packing materials, and the costs of relocating the truck are presented in the model. A mixed integer model is developed followed by a simulation model to examine the factors affecting the operation of the model.Keywords: Modeling, truck rental, supply chains management, simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8104029 Enhance Construction Visual As-Built Schedule Management Using BIM Technology
Authors: Shu-Hui Jan, Hui-Ping Tserng, Shih-Ping Ho
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Construction project control attempts to obtain real-time as-built schedule information and to eliminate project delays by effectively enhancing dynamic schedule control and management. Suitable platforms for enhancing an as-built schedule visually during the construction phase are necessary and important for general contractors. As the application of building information modeling (BIM) becomes more common, schedule management integrated with the BIM approach becomes essential to enhance visual construction management implementation for the general contractor during the construction phase. To enhance visualization of the updated as-built schedule for the general contractor, this study presents a novel system called the Construction BIM-assisted Schedule Management (ConBIM-SM) system for general contractors in
Keywords: BIM, Building information modeling, construction schedule management, as-built schedule management, BIM schedule updating mechanism.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33924028 Sensorless Backstepping Control Using an Adaptive Luenberger Observer with Three Levels NPC Inverter
Authors: A. Bennassar, A. Abbou, M. Akherraz, M. Barara
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In this paper, we propose a sensorless backstepping control of induction motor (IM) associated with three levels neutral clamped (NPC) inverter. First, the backstepping approach is designed to steer the flux and speed variables to theirs references and to compensate the uncertainties. A Lyapunov theory is used and it demonstrates that the dynamic trajectories tracking are asymptotically stable. Second, we estimate the rotor flux and speed by using the adaptive Luenberger observer (ALO). Simulation results are provided to illustrate the performance of the proposed approach in high and low speeds and load torque disturbance.
Keywords: Sensorless backstepping, IM, Three levels NPC inverter, Lyapunov theory, ALO.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21894027 The Effects of Logistical Centers Realization on Society and Economy
Authors: Anna Dolinayova, Juraj Camaj, Martin Loch
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Presently, it is necessary to ensure the sustainable development of passenger and freight transport. Increasing performance of road freight has had a negative impact to environment and society. It is therefore necessary to increase the competitiveness of intermodal transport, which is more environmentally friendly. The study describes the effectiveness of logistical centers realization for companies and society and research how the partial internalization of external costs reflected in the efficient use of these centers and increase the competitiveness of intermodal transport to road freight. In our research, we use the method of comparative analysis and market research to describe the advantages of logistic centers for their users as well as for society as a whole. Method normal costing is used for calculation infrastructure and total costs, method of conversion costing for determine the external costs. We modelled total society costs for road freight transport and inter modal transport chain (we assumed that most of the traffic is carried by rail) with different loading schemes for condition in the Slovak Republic. Our research has shown that higher utilization of inter modal transport chain do good not only for society, but for companies providing freight services too. Increase in use of inter modal transport chain can bring many benefits to society that do not bring direct immediate financial return. They often bring the multiplier effects, such as greater use of environmentally friendly transport mode and reduce the total society costs.
Keywords: Delivery time, economy effectiveness, logistical centers, ecological efficiency, optimization, society.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20344026 Multi-Agent Coverage Control with Bounded Gain Forgetting Composite Adaptive Controller
Authors: Mert Turanli, Hakan Temeltas
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In this paper, we present an adaptive controller for decentralized coordination problem of multiple non-holonomic agents. The performance of the presented Multi-Agent Bounded Gain Forgetting (BGF) Composite Adaptive controller is compared against the tracking error criterion with a Feedback Linearization controller. By using the method, the sensor nodes move and reconfigure themselves in a coordinated way in response to a sensed environment. The multi-agent coordination is achieved through Centroidal Voronoi Tessellations and Coverage Control. Also, a consensus protocol is used for synchronization of the parameter vectors. The two controllers are given with their Lyapunov stability analysis and their stability is verified with simulation results. The simulations are carried out in MATLAB and ROS environments. Better performance is obtained with BGF Adaptive Controller.
Keywords: Adaptive control, Centroidal Voronoi Tessellations, composite adaptation, coordination.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10294025 Light Tracking Fault Tolerant Control System
Authors: J. Florescu, T. Vinay, L. Wang
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A fault detection and identification (FDI) technique is presented to create a fault tolerant control system (FTC). The fault detection is achieved by monitoring the position of the light source using an array of light sensors. When a decision is made about the presence of a fault an identification process is initiated to locate the faulty component and reconfigure the controller signals. The signals provided by the sensors are predictable; therefore the existence of a fault is easily identified. Identification of the faulty sensor is based on the dynamics of the frame. The technique is not restricted to a particular type of controllers and the results show consistency.Keywords: algorithm, detection and diagnostic, fault-tolerantcontrol, fault detection and identification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13994024 Day/Night Detector for Vehicle Tracking in Traffic Monitoring Systems
Authors: M. Taha, Hala H. Zayed, T. Nazmy, M. Khalifa
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Recently, traffic monitoring has attracted the attention of computer vision researchers. Many algorithms have been developed to detect and track moving vehicles. In fact, vehicle tracking in daytime and in nighttime cannot be approached with the same techniques, due to the extreme different illumination conditions. Consequently, traffic-monitoring systems are in need of having a component to differentiate between daytime and nighttime scenes. In this paper, a HSV-based day/night detector is proposed for traffic monitoring scenes. The detector employs the hue-histogram and the value-histogram on the top half of the image frame. Experimental results show that the extraction of the brightness features along with the color features within the top region of the image is effective for classifying traffic scenes. In addition, the detector achieves high precision and recall rates along with it is feasible for real time applications.Keywords: Day/night detector, daytime/nighttime classification, image classification, vehicle tracking, traffic monitoring.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 44904023 A Study on Algorithm Fusion for Recognition and Tracking of Moving Robot
Authors: Jungho Choi, Youngwan Cho
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This paper presents an algorithm for the recognition and tracking of moving objects, 1/10 scale model car is used to verify performance of the algorithm. Presented algorithm for the recognition and tracking of moving objects in the paper is as follows. SURF algorithm is merged with Lucas-Kanade algorithm. SURF algorithm has strong performance on contrast, size, rotation changes and it recognizes objects but it is slow due to many computational complexities. Processing speed of Lucas-Kanade algorithm is fast but the recognition of objects is impossible. Its optical flow compares the previous and current frames so that can track the movement of a pixel. The fusion algorithm is created in order to solve problems which occurred using the Kalman Filter to estimate the position and the accumulated error compensation algorithm was implemented. Kalman filter is used to create presented algorithm to complement problems that is occurred when fusion two algorithms. Kalman filter is used to estimate next location, compensate for the accumulated error. The resolution of the camera (Vision Sensor) is fixed to be 640x480. To verify the performance of the fusion algorithm, test is compared to SURF algorithm under three situations, driving straight, curve, and recognizing cars behind the obstacles. Situation similar to the actual is possible using a model vehicle. Proposed fusion algorithm showed superior performance and accuracy than the existing object recognition and tracking algorithms. We will improve the performance of the algorithm, so that you can experiment with the images of the actual road environment.Keywords: SURF, Optical Flow Lucas-Kanade, Kalman Filter, object recognition, object tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22834022 Formant Tracking Linear Prediction Model using HMMs for Noisy Speech Processing
Authors: Zaineb Ben Messaoud, Dorra Gargouri, Saida Zribi, Ahmed Ben Hamida
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This paper presents a formant-tracking linear prediction (FTLP) model for speech processing in noise. The main focus of this work is the detection of formant trajectory based on Hidden Markov Models (HMM), for improved formant estimation in noise. The approach proposed in this paper provides a systematic framework for modelling and utilization of a time- sequence of peaks which satisfies continuity constraints on parameter; the within peaks are modelled by the LP parameters. The formant tracking LP model estimation is composed of three stages: (1) a pre-cleaning multi-band spectral subtraction stage to reduce the effect of residue noise on formants (2) estimation stage where an initial estimate of the LP model of speech for each frame is obtained (3) a formant classification using probability models of formants and Viterbi-decoders. The evaluation results for the estimation of the formant tracking LP model tested in Gaussian white noise background, demonstrate that the proposed combination of the initial noise reduction stage with formant tracking and LPC variable order analysis, results in a significant reduction in errors and distortions. The performance was evaluated with noisy natual vowels extracted from international french and English vocabulary speech signals at SNR value of 10dB. In each case, the estimated formants are compared to reference formants.Keywords: Formants Estimation, HMM, Multi Band Spectral Subtraction, Variable order LPC coding, White Gauusien Noise.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19524021 Real Time Detection, Tracking and Recognition of Medication Intake
Authors: H. H. Huynh, J. Meunier, J.Sequeira, M.Daniel
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In this paper, the detection and tracking of face, mouth, hands and medication bottles in the context of medication intake monitoring with a camera is presented. This is aimed at recognizing medication intake for elderly in their home setting to avoid an inappropriate use. Background subtraction is used to isolate moving objects, and then, skin and bottle segmentations are done in the RGB normalized color space. We use a minimum displacement distance criterion to track skin color regions and the R/G ratio to detect the mouth. The color-labeled medication bottles are simply tracked based on the color space distance to their mean color vector. For the recognition of medication intake, we propose a three-level hierarchal approach, which uses activity-patterns to recognize the normal medication intake activity. The proposed method was tested with three persons, with different medication intake scenarios, and gave an overall precision of over 98%.
Keywords: Activity recognition, background subtraction, tracking, medication intake, video surveillance
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19754020 Improved Torque Control of Electrical Load Simulator with Parameters and State Estimation
Authors: Nasim Ullah, Shaoping Wang
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ELS is an important ground based hardware in the loop simulator used for aerodynamics torque loading experiments of the actuators under test. This work focuses on improvement of the transient response of torque controller with parameters uncertainty of Electrical Load Simulator (ELS).The parameters of load simulator are estimated online and the model is updated, eliminating the model error and improving the steady state torque tracking response of torque controller. To improve the Transient control performance the gain of robust term of SMC is updated online using fuzzy logic system based on the amount of uncertainty in parameters of load simulator. The states of load simulator which cannot be measured directly are estimated using luenberger observer with update of new estimated parameters. The stability of the control scheme is verified using Lyapunov theorem. The validity of proposed control scheme is verified using simulations.Keywords: ELS, Observer, Transient Performance, SMC, Extra Torque, Fuzzy Logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20274019 Heuristic Methods for the Capacitated Location- Allocation Problem with Stochastic Demand
Authors: Salinee Thumronglaohapun
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The proper number and appropriate locations of service centers can save cost, raise revenue and gain more satisfaction from customers. Establishing service centers is high-cost and difficult to relocate. In long-term planning periods, several factors may affect the service. One of the most critical factors is uncertain demand of customers. The opened service centers need to be capable of serving customers and making a profit although the demand in each period is changed. In this work, the capacitated location-allocation problem with stochastic demand is considered. A mathematical model is formulated to determine suitable locations of service centers and their allocation to maximize total profit for multiple planning periods. Two heuristic methods, a local search and genetic algorithm, are used to solve this problem. For the local search, five different chances to choose each type of moves are applied. For the genetic algorithm, three different replacement strategies are considered. The results of applying each method to solve numerical examples are compared. Both methods reach to the same best found solution in most examples but the genetic algorithm provides better solutions in some cases.Keywords: Location-allocation problem, stochastic demand, local search, genetic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7364018 The Control of a Highly Nonlinear Two-wheels Balancing Robot: A Comparative Assessment between LQR and PID-PID Control Schemes
Authors: A. N. K. Nasir, M. A. Ahmad, R. M. T. Raja Ismail
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The research on two-wheels balancing robot has gained momentum due to their functionality and reliability when completing certain tasks. This paper presents investigations into the performance comparison of Linear Quadratic Regulator (LQR) and PID-PID controllers for a highly nonlinear 2–wheels balancing robot. The mathematical model of 2-wheels balancing robot that is highly nonlinear is derived. The final model is then represented in statespace form and the system suffers from mismatched condition. Two system responses namely the robot position and robot angular position are obtained. The performances of the LQR and PID-PID controllers are examined in terms of input tracking and disturbances rejection capability. Simulation results of the responses of the nonlinear 2–wheels balancing robot are presented in time domain. A comparative assessment of both control schemes to the system performance is presented and discussed.Keywords: PID, LQR, Two-wheels balancing robot.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 52594017 Target Tracking in Sensor Networks: A Distributed Constraint Satisfaction Approach
Authors: R.Mostafaei, A.Habiboghli, M.R.Meybodi
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In distributed resource allocation a set of agents must assign their resources to a set of tasks. This problem arises in many real-world domains such as distributed sensor networks, disaster rescue, hospital scheduling and others. Despite the variety of approaches proposed for distributed resource allocation, a systematic formalization of the problem, explaining the different sources of difficulties, and a formal explanation of the strengths and limitations of key approaches is missing. We take a step towards this goal by using a formalization of distributed resource allocation that represents both dynamic and distributed aspects of the problem. In this paper we present a new idea for target tracking in sensor networks and compare it with previous approaches. The central contribution of the paper is a generalized mapping from distributed resource allocation to DDCSP. This mapping is proven to correctly perform resource allocation problems of specific difficulty. This theoretical result is verified in practice by a simulation on a realworld distributed sensor network.
Keywords: Distributed CSP, Target Tracking, Sensor Network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11814016 Optimization of Transmitter Aperture by Genetic Algorithm in Optical Satellite
Authors: Karim Kemih, Yacine Yaiche, Malek Benslama
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To establish optical communication between any two satellites, the transmitter satellite must track the beacon of the receiver satellite and point the information optical beam in its direction. Optical tracking and pointing systems for free space suffer during tracking from high-amplitude vibration because of background radiation from interstellar objects such as the Sun, Moon, Earth, and stars in the tracking field of view or the mechanical impact from satellite internal and external sources. The vibrations of beam pointing increase the bit error rate and jam communication between the two satellites. One way to overcome this problem is the use of very small transmitter beam divergence angles of too narrow divergence angle is that the transmitter beam may sometimes miss the receiver satellite, due to pointing vibrations. In this paper we propose the use of genetic algorithm to optimize the BER as function of transmitter optics aperture.Keywords: Optical Satellite Communication, Genetic Algorithm, Transmitter Optics Aperture
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19804015 An Android Geofencing App for Autonomous Remote Switch Control
Authors: Jamie Wong, Daisy Sang, Chang-Shyh Peng
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Geofence is a virtual fence defined by a preset physical radius around a target location. Geofencing App provides location-based services which define the actionable operations upon the crossing of a geofence. Geofencing requires continual location tracking, which can consume noticeable amount of battery power. Additionally, location updates need to be frequent and accurate or order so that actions can be triggered within an expected time window after the mobile user navigate through the geofence. In this paper, we build an Android mobile geofencing Application to remotely and autonomously control a power switch.Keywords: Location based service, geofence, autonomous, remote switch.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14244014 Single-Camera Basketball Tracker through Pose and Semantic Feature Fusion
Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro
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Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.Keywords: Basketball, deep learning, feature extraction, single-camera, tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6824013 Investigation of Improved Chaotic Signal Tracking by Echo State Neural Networks and Multilayer Perceptron via Training of Extended Kalman Filter Approach
Authors: Farhad Asadi, S. Hossein Sadati
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This paper presents a prediction performance of feedforward Multilayer Perceptron (MLP) and Echo State Networks (ESN) trained with extended Kalman filter. Feedforward neural networks and ESN are powerful neural networks which can track and predict nonlinear signals. However, their tracking performance depends on the specific signals or data sets, having the risk of instability accompanied by large error. In this study we explore this process by applying different network size and leaking rate for prediction of nonlinear or chaotic signals in MLP neural networks. Major problems of ESN training such as the problem of initialization of the network and improvement in the prediction performance are tackled. The influence of coefficient of activation function in the hidden layer and other key parameters are investigated by simulation results. Extended Kalman filter is employed in order to improve the sequential and regulation learning rate of the feedforward neural networks. This training approach has vital features in the training of the network when signals have chaotic or non-stationary sequential pattern. Minimization of the variance in each step of the computation and hence smoothing of tracking were obtained by examining the results, indicating satisfactory tracking characteristics for certain conditions. In addition, simulation results confirmed satisfactory performance of both of the two neural networks with modified parameterization in tracking of the nonlinear signals.Keywords: Feedforward neural networks, nonlinear signal prediction, echo state neural networks approach, leaking rates, capacity of neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7474012 A Novel Method for Non-Invasive Diagnosis of Hepatitis C Virus Using Electromagnetic Signal Detection: A Multicenter International Study
Authors: Gamal Shiha, Waleed Samir, Zahid Azam, Premashis Kar, Saeed Hamid, Shiv Sarin
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A simple, rapid and non-invasive electromagnetic sensor (C-FAST device) was- patented; for diagnosis of HCV RNA. Aim: To test the validity of the device compared to standard HCV PCR. Subjects and Methods: The first phase was done as pilot in Egypt on 79 participants; the second phase was done in five centers: one center from Egypt, two centers from Pakistan and two centers from India (800, 92 and 113 subjects respectively). The third phase was done nationally as multicenter study on (1600) participants for ensuring its representativeness. Results: When compared to PCR technique, C-FAST device revealed sensitivity 95% to 100%, specificity 95.5% to 100%, PPV 89.5% to 100%, NPV 95% to 100% and positive likelihood ratios 21.8% to 38.5%. Conclusion: It is practical evidence that HCV nucleotides emit electromagnetic signals that can be used for its identification. As compared to PCR, C-FAST is an accurate, valid and non-invasive device.
Keywords: C-FAST- a valid and reliable device, Distant cellular interaction, Electromagnetic signal detection, Non-invasive diagnosis of HCV.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 180314011 Tracking Objects in Color Image Sequences: Application to Football Images
Authors: Mourad Moussa, Ali Douik, Hassani Messaoud
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In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.
Keywords: Image segmentation, objects tracking, Parzen window, singular value decomposition, target recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19684010 Comparison of Zero Voltage Soft Switching and Hard Switching Boost Converter with Maximum Power Point Tracking
Authors: N. Ravi Kumar, R. Kamalakannan
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The inherent nature of normal boost converter has more voltage stress across the power electronics switch and ripple. The presented formation of the front end rectifier stage for a photovoltaic (PV) organization is mainly used to give the supply. Further increasing of the solar efficiency is achieved by connecting the zero voltage soft switching boost converter. The zero voltage boost converter is used to convert the low level DC voltage to high level DC voltage. The inherent nature of zero voltage switching boost converter is used to shrink the voltage tension across the power electronics switch and ripple. The input stage allows the determined power point tracking to be used to extract supreme power from the sun when it is available. The hardware setup was implemented by using PIC Micro controller (16F877A).
Keywords: Boost converter, duty cycle, hard switching, MOSFET, maximum power point tracking, photovoltaic, soft switching, zero voltage switching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11944009 Tehran-Tabriz Intelligent Highway
Authors: P. Parvizi, F. Norouzifard, S.Mohammadi
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The need to implement intelligent highways is much more emphasized with the growth of vehicle production line as well as vehicle intelligence. The control of intelligent vehicles in order to reduce human error and boost ease congestion is not accomplished solely by the aid of human resources. The present article is an attempt to introduce an intelligent control system based on a single central computer. In this project, central computer, without utilizing Global Positioning System (GPS), is capable of tracking all vehicles, crisis management and control, traffic guidance and recording traffic crimes along the highway. By the help of RFID technology, vehicles are connected to computerized systems, intelligent light poles and other available hardware along the way. By the aid of Wimax communicative technology, all components of the system are virtually connected together through local and global networks devised in them and the energy of the network is provided by the solar cells installed on the intelligent light poles.Keywords: intelligent highway, intelligent light pole, highway automation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17464008 Intelligent Swarm-Finding in Formation Control of Multi-Robots to Track a Moving Target
Authors: Anh Duc Dang, Joachim Horn
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This paper presents a new approach to control robots, which can quickly find their swarm while tracking a moving target through the obstacles of the environment. In this approach, an artificial potential field is generated between each free-robot and the virtual attractive point of the swarm. This artificial potential field will lead free-robots to their swarm. The swarm-finding of these free-robots dose not influence the general motion of their swarm and nor other robots. When one singular robot approaches the swarm then its swarm-search will finish, and it will further participate with its swarm to reach the position of the target. The connections between member-robots with their neighbors are controlled by the artificial attractive/repulsive force field between them to avoid collisions and keep the constant distances between them in ordered formation. The effectiveness of the proposed approach has been verified in simulations.
Keywords: Formation control, potential field method, obstacle avoidance, swarm intelligence, multi-agent systems.
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