Search results for: tracking error

Authors: Abimbola Adedeji, Ahmad Shauqi Zubir

Abstract:

This paper examines the profitability and risk between investing in gold exchange traded funds (ETFs) and gold mutual funds compares to gold prices. The main focus in determining whether there are similarities or differences between those financial products is the tracking error. The importance of understanding the similarities or differences between the gold ETFs, gold mutual funds and gold prices is derived from the fact that gold ETFs and gold mutual funds are used as substitutions for investors who are looking to profit from gold prices although they are short in capital. 10 hypotheses were tested. There are 3 types of tracking error used. Tracking error 1 and 3 gives results that differentiate between types of ETFs and mutual funds, hence yielding the answers in answering the hypotheses that were developed. However, tracking error 2 failed to give the answer that could shed light on the questions raised in this study. All of the results in tracking error 2 technique only telling us that the difference between the ups and downs of the financial instruments are similar, statistically to the physical gold prices movement.

Keywords: gold etf, gold mutual funds, tracking error

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Authors: Yawen Wang, Hongchang Chen, Shaomei Li, Chao Gao, Jiangpeng Zhang

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As the main challenge for target tracking is accounting for target scale change and real-time, we combine Mean-Shift and PCA-SIFT algorithm together to solve the problem. We introduce similarity comparison method to determine how the target scale changes, and taking different strategies according to different situation. For target scale getting larger will cause location error, we employ backward tracking to reduce the error. Mean-Shift algorithm has poor performance when tracking scale-changing target due to the fixed bandwidth of its kernel function. In order to overcome this problem, we introduce PCA-SIFT matching. Through key point matching between target and template, that adjusting the scale of tracking window adaptively can be achieved. Because this algorithm is sensitive to wrong match, we introduce RANSAC to reduce mismatch as far as possible. Furthermore target relocating will trigger when number of match is too small. In addition we take comprehensive consideration about target deformation and error accumulation to put forward a new template update method. Experiments on five image sequences and comparison with 6 kinds of other algorithm demonstrate favorable performance of the proposed tracking algorithm.

Keywords: target tracking, PCA-SIFT, mean-shift, scale-adaptive

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Authors: Raouf Fareh, Maarouf Saad, Sofiane Khadraoui, Tamer Rabie

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This paper presents a tracking control strategy based on Lyapunov approach for nonholonomic wheeled mobile robot. This control strategy consists of two levels. First, a kinematic controller is developed to adjust the right and left wheel velocities. Using this velocity control law, the stability of the tracking error is guaranteed using Lyapunov approach. This kinematic controller cannot be generated directly by the motors. To overcome this problem, the second level of the controllers, dynamic control, is designed. This dynamic control law is developed based on Lyapunov theory in order to track the desired trajectories of the mobile robot. The stability of the tracking error is proved using Lupunov and Barbalat approaches. Simulation results on a nonholonomic wheeled mobile robot are given to demonstrate the feasibility and effectiveness of the presented approach.

Keywords: mobile robot, trajectory tracking, Lyapunov, stability

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Authors: Zainab Almukhtar, Adel Merabet

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In this paper, a method for maximum power point tracking of a photovoltaic energy conversion system is presented. This method is based on using the difference between the power from the solar panel and an estimated power value to control the DC-DC converter of the photovoltaic system. The difference is continuously compared with a preset error permitted value. If the power difference is more than the error, the estimated power is multiplied by a factor and the operation is repeated until the difference is less or equal to the threshold error. The difference in power will be used to trigger a DC-DC boost converter in order to raise the voltage to where the maximum power point is achieved. The proposed method was experimentally verified through a PV energy conversion system driven by the OPAL-RT real time controller. The method was tested on varying radiation conditions and load requirements, and the Photovoltaic Panel was operated at its maximum power in different conditions of irradiation.

Keywords: control system, error, solar panel, MPPT tracking

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Authors: Muhammad Ilyas, Awais Khan, Syed Ali Raza Shah

Abstract:

DC motors are widely used in industries to provide mechanical power in speed and torque. The position and speed control of DC motors is getting the interest of the scientific community in robotics, especially in the robotic arm, a flexible joint manipulator. The current research work is based on position control of DC motors using experimental investigations in LabVIEW. The linear control strategy is applied to track the position and speed of the DC motor with comparative analysis in the LabVIEW platform and simulation analysis in MATLAB. The tracking error in hardware setup based on LabVIEW programming is slightly greater than simulation analysis in MATLAB due to the inertial load of the motor during steady-state conditions. The controller output shows the input voltage applied to the dc motor varies between 0-8V to ensure minimal steady error while tracking the position and speed of the DC motor.

Keywords: DC motor, labview, proportional integral derivative control, position tracking, speed tracking

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Authors: Milca F. Coelho, K. Bousson, Kawser Ahmed

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To accurately track an aerospace vehicle in a time-critical situation and in a highly nonlinear environment, is one of the strongest interests within the aerospace community. The tracking is achieved by estimating accurately the state of a moving target, which is composed of a set of variables that can provide a complete status of the system at a given time. One of the main ingredients for a good estimation performance is the use of efficient estimation algorithms. A well-known framework is the Kalman filtering methods, designed for prediction and estimation problems. The success of the Kalman Filter (KF) in engineering applications is mostly due to the Extended Kalman Filter (EKF), which is based on local linearization. Besides its popularity, the EKF presents several limitations. To address these limitations and as a possible solution to tracking problems, this paper proposes the use of the Ensemble Kalman Filter (EnKF). Although the EnKF is being extensively used in the context of weather forecasting and it is being recognized for producing accurate and computationally effective estimation on systems with a very high dimension, it is almost unknown by the tracking community. The EnKF was initially proposed as an attempt to improve the error covariance calculation, which on the classic Kalman Filter is difficult to implement. Also, in the EnKF method the prediction and analysis error covariances have ensemble representations. These ensembles have sizes which limit the number of degrees of freedom, in a way that the filter error covariance calculations are a lot more practical for modest ensemble sizes. In this paper, a realistic simulation of a radar tracking was performed, where the EnKF was applied and compared with the Extended Kalman Filter. The results suggested that the EnKF is a promising tool for tracking applications, offering more advantages in terms of performance.

Keywords: Kalman filter, nonlinear state estimation, optimal tracking, stochastic environment

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Authors: Qiang Zhang, Xiaojian Hu

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In multi-vehicle tracking, based on feature selection, the tracking system efficiently tracks vehicles in a video with minimal error in combination with color attribution, which focuses on presenting a simple and fast, yet accurate and robust solution to the problem such as inaccurately and untimely responses of statistics-based adaptive traffic control system in the intersection scenario. In this study, a real-time tracking system is proposed for multi-vehicle tracking in the intersection scene. Considering the complexity and application feasibility of the algorithm, in the object detection step, the detection result provided by virtual loops were post-processed and then used as the input for the tracker. For the tracker, lightweight methods were designed to extract and select features and incorporate them into the adaptive color tracking (ACT) framework. And the approbatory online feature selection algorithms are integrated on the mature ACT system with good compatibility. The proposed feature selection methods and multi-vehicle tracking method are evaluated on KITTI datasets and show efficient vehicle tracking performance when compared to the other state-of-the-art approaches in the same category. And the system performs excellently on the video sequences recorded at the intersection. Furthermore, the presented vehicle tracking system is suitable for surveillance applications.

Keywords: real-time, multi-vehicle tracking, feature selection, color attribution

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Authors: Hasan Basaran, Emre Unal

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Formation flying of satellites is a mission that involves a relative position keeping of different satellites in the constellation. In this study, different control algorithms are compared with one another in terms of ΔV, velocity increment, and tracking error. Various control methods, covering continuous and impulsive approaches are implemented and tested for satellites flying in low Earth orbit. Feedback linearization, sliding mode control, and model predictive control are designed and compared with an impulsive feedback law, which is based on mean orbital elements. Feedback linearization and sliding mode control approaches have identical mathematical models that include second order Earth oblateness effects. The model predictive control, on the other hand, does not include any perturbations and assumes circular chief orbit. The comparison is done with 4 different initial errors and achieved with velocity increment, root mean square error, maximum steady state error, and settling time. It was observed that impulsive law consumed the least ΔV, while produced the highest maximum error in the steady state. The continuous control laws, however, consumed higher velocity increments and produced lower amounts of tracking errors. Finally, the inversely proportional relationship between tracking error and velocity increment was established.

Keywords: chief-deputy satellites, feedback linearization, follower-leader satellites, formation flight, fuel consumption, model predictive control, rendezvous, sliding mode

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Authors: G. Obregon-Pulido , G. C. Solis-Perales, J. A. Meda-Campaña

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In this paper, we present a sliding mode controller in discrete time. The design of the controller is based on the theory of regulation for nonlinear systems. In the problem of disturbance rejection and/or output tracking, it is known that in discrete time, a controller that uses the zero-order holder only guarantees tracking at the sampling instances but not between instances. It is shown that using the so-called exponential holder, it is possible to guarantee asymptotic zero output tracking error, also between the sampling instant. For stabilizing the problem of close loop system we introduce the sliding mode approach relaxing the requirements of the existence of a linear stabilizing control law.

Keywords: regulation theory, sliding modes, discrete controller, ripple-free tracking

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Authors: Shaomei Li, Yawen Wang, Chao Gao

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To improve tracking drift which often occurs in adaptive tracking, an algorithm based on the fusion of tracking and detection is proposed in this paper. Firstly, object tracking is posed as a binary classification problem and is modeled by partial least squares (PLS) analysis. Secondly, tracking object frame by frame via particle filtering. Thirdly, validating the tracking reliability based on both positive and negative models matching. Finally, relocating the object based on SIFT features matching and voting when drift occurs. Object appearance model is updated at the same time. The algorithm cannot only sense tracking drift but also relocate the object whenever needed. Experimental results demonstrate that this algorithm outperforms state-of-the-art algorithms on many challenging sequences.

Keywords: object tracking, tracking drift, partial least squares analysis, positive and negative models matching

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Authors: Martins Olatunbosun Babatunde, Muhammed Bashir Muazu, Emmanuel Adewale Adedokun

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This paper presents the development of a double-loop trajectory-tracking controller for the ball and plate system (BPS) using the Normalized Right Coprime Factorization (NRCF) scheme.The Linear Algebraic (LA) method is used to design the inner loop required to stabilize the ball, while H-infinity NRCF method, that involved the lead-lag compensator design approach, is used to develop the outer loop that controls the plate. Simulation results show that the plate was stabilized at 0.2989 seconds and the ball was able to settle after 0.9646 seconds, with a trajectory tracking error of 0.0036. This shows that the controller has good adaptability and robustness.

Keywords: ball and plate system, normalized right coprime factorization, linear algebraic method, compensator, controller, tracking.

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Authors: Iman Iraei, Mina Sharifi

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A method for object tracking in motion blurred images is proposed in this article. This paper shows that object tracking could be improved with this approach. We use mean shift algorithm to track different objects as a main tracker. But, the problem is that mean shift could not track the selected object accurately in blurred scenes. So, for better tracking result, and increasing the accuracy of tracking, wavelet transform is used. We use a feature named as blur extent, which could help us to get better results in tracking. For calculating of this feature, we should use Harr wavelet. We can look at this matter from two different angles which lead to determine whether an image is blurred or not and to what extent an image is blur. In fact, this feature left an impact on the covariance matrix of mean shift algorithm and cause to better performance of tracking. This method has been concentrated mostly on motion blur parameter. transform. The results reveal the ability of our method in order to reach more accurately tracking.

Keywords: mean shift, object tracking, blur extent, wavelet transform, motion blur

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Authors: Tappei Yotsumoto, Atsushi Nomura, Kozo Tanigawa, Kenichi Takahashi, Takao Kawamura, Kazunori Sugahara

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In a human tracking system, expanding a monitoring range of one system is complicating the management of devices and increasing its cost. Therefore, we propose a method to realize a wide-range human tracking by connecting small systems. In this paper, we examined an agent deploy method and information contents across the heterogeneous human tracking systems. By implementing the proposed method, we can construct a human tracking system across heterogeneous systems, and the system can track a target continuously between systems.

Keywords: human tracking system, mobile agent, monitoring, heterogeneous systems

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Authors: Shuting Ji, Yueming Zhang, Jing Zhao

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The output error of the globoidal cam mechanism can be considered as a relevant indicator of mechanism performance, because it determines kinematic and dynamical behavior of mechanical transmission. Based on the differential geometry and the rigid body transformations, the mathematical model of surface geometry of the globoidal cam is established. Then we present the analytical expression of the output error (including the transmission error and the displacement error along the output axis) by considering different manufacture and assembly errors. The effects of the center distance error, the perpendicular error between input and output axes and the rotational angle error of the globoidal cam on the output error are systematically analyzed. A globoidal cam mechanism which is widely used in automatic tool changer of CNC machines is applied for illustration. Our results show that the perpendicular error and the rotational angle error have little effects on the transmission error but have great effects on the displacement error along the output axis. This study plays an important role in the design, manufacture and assembly of the globoidal cam mechanism.

Keywords: globoidal cam mechanism, manufacture error, transmission error, automatic tool changer

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Authors: Sumaya Ismail, Aijaz Ahmad Rehi

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Abstract The location tracking and positioning systems have technologically grown exponentially in recent decade. In particular, Global Position system (GPS) has become a universal norm to be a part of almost every software application directly or indirectly for the location based modules. However major drawback of GPS based system is their inability of working in indoor environments. Researchers are thus focused on the alternative technologies which can be used in indoor environments for a vast range of application domains which require indoor location tracking. One of the most popular technology used for indoor tracking is radio frequency identification (RFID). Due to its numerous advantages, including its cost effectiveness, it is considered as a technology of choice in indoor location tracking systems. To contribute to the emerging trend of the research, this paper proposes an application architecture of passive RFID tag based indoor location tracking system. For the proof of concept, a test bed will be developed to in this study. In addition, various indoor location tracking algorithms will be used to assess their appropriateness in the proposed application architecture.

Keywords: RFID, GPS, indoor location tracking, application architecture, passive RFID tag

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Authors: Muhammad A. Alsubaie, Mubarak K. H. Alhajri, Tarek S. Altowaim

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A repetitive controller designed to accommodate periodic disturbances via state feedback is discussed. Periodic disturbances can be represented by a time delay model in a positive feedback loop acting on system output. A direct use of the small gain theorem solves the periodic disturbances problem via 1) isolating the delay model, 2) finding the overall system representation around the delay model and 3) designing a feedback controller that assures overall system stability and tracking error convergence. This paper addresses uncertainty conditions for the repetitive controller designed in state feedback in either past error feedforward or current error feedback using singular values. The uncertainty investigation is based on the overall system found and the stability condition associated with it; depending on the scheme used, to set an upper/lower limit weighting parameter. This creates a region that should not be exceeded in selecting the weighting parameter which in turns assures performance improvement against system uncertainty. Repetitive control problem can be described in lifted form. This allows the usage of singular values principle in setting the range for the weighting parameter selection. The Simulation results obtained show a tracking error convergence against dynamic system perturbation if the weighting parameter chosen is within the range obtained. Simulation results also show the advantage of weighting parameter usage compared to the case where it is omitted.

Keywords: model mismatch, repetitive control, singular values, state feedback

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Authors: Ravindra B. Patil, P. Krishnamoorthy, Shriram Sethuraman

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This work proposes a novel Gaussian Mixture Model (GMM) based approach for accurate tracking of the arterial wall and subsequent computation of the distension waveform using Radio Frequency (RF) ultrasound signal. The approach was evaluated on ultrasound RF data acquired using a prototype ultrasound system from an artery mimicking flow phantom. The effectiveness of the proposed algorithm is demonstrated by comparing with existing wall tracking algorithms. The experimental results show that the proposed method provides 20% reduction in the error margin compared to the existing approaches in tracking the arterial wall movement. This approach coupled with ultrasound system can be used to estimate the arterial compliance parameters required for screening of cardiovascular related disorders.

Keywords: distension waveform, Gaussian Mixture Model, RF ultrasound, arterial wall movement

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Authors: Sophia Hayes, Kenny L. Liang, Sahil Sharma, Austin Shema, Mahmoud Bader, Mohamed Elbarkouky

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Despite being one of the most significant economic contributors of the country, Canada’s construction industry is lagging behind other sectors when it comes to labor productivity improvements. The construction industry is very collaborative as a general contractor, will hire trade contractors to perform most of a project’s work; meaning low productivity from one contractor can have a domino effect on the shared success of a project. To address this issue and encourage trade contractors to improve their productivity tracking methods, an investigative study was done on the productivity views and tracking methods of various trade contractors. Additionally, an in-depth review was done on four standard tracking methods used in the construction industry: cost codes, benchmarking, the job productivity measurement (JPM) standard, and WorkFace Planning (WFP). The four tracking methods were used as a baseline in comparing the trade contractors’ responses, determining gaps within their current tracking methods, and for making improvement recommendations. 15 interviews were conducted with different trades to analyze how contractors value productivity. The results of these analyses indicated that there seem to be gaps within the construction industry when it comes to an understanding of the purpose and value in productivity tracking. The trade contractors also shared their current productivity tracking systems; which were then compared to the four standard tracking methods used in the construction industry. Gaps were identified in their various tracking methods and using a framework; recommendations were made based on the type of trade on how to improve how they track productivity.

Keywords: labor productivity, productivity tracking methods, trade contractors, construction

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Authors: Cheng Fang, Lingwei Quan, Cunyue Lu

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Human pose estimation and tracking are to accurately identify and locate the positions of human joints in the video. It is a computer vision task which is of great significance for human motion recognition, behavior understanding and scene analysis. There has been remarkable progress on human pose estimation in recent years. However, more researches are needed for human pose tracking especially for online tracking. In this paper, a framework, called PoseSRPN, is proposed for online single-person pose estimation and tracking. We use Siamese network attaching a pose estimation branch to incorporate Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) into one framework. The pose estimation branch has a simple network structure that replaces the complex upsampling and convolution network structure with deconvolution. By augmenting the loss of fully convolutional Siamese network with the pose estimation task, pose estimation and tracking can be trained in one stage. Once trained, PoseSRPN only relies on a single bounding box initialization and producing human joints location. The experimental results show that while maintaining the good accuracy of pose estimation on COCO and PoseTrack datasets, the proposed method achieves a speed of 59 frame/s, which is superior to other pose tracking frameworks.

Keywords: computer vision, pose estimation, pose tracking, Siamese network

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Authors: Ailing Yang, Penghan Song, Aihua Cai

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The nonlinear maneuvering target tracking problem is mainly a state estimation problem when the target motion model is uncertain. Traditional solutions include Kalman filtering based on Bayesian filtering framework and extended Kalman filtering. However, these methods need prior knowledge such as kinematics model and state system distribution, and their performance is poor in state estimation of nonprior complex dynamic systems. Therefore, in view of the problems existing in traditional algorithms, a convolution LSTM target state estimation (SAConvLSTM-SE) algorithm based on Self-Attention memory (SAM) is proposed to learn the historical motion state of the target and the error distribution information measured at the current time. The measured track point data of airborne radar are processed into data sets. After supervised training, the data-driven deep neural network based on SAConvLSTM can directly obtain the target state at the next moment. Through experiments on two different maneuvering targets, we find that the network has stronger robustness and better tracking accuracy than the existing tracking methods.

Keywords: maneuvering target, state estimation, Kalman filter, LSTM, self-attention

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Authors: Zhengkun Guo, Yanbin Li, Wenqing Wang, Bo Zou

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The statically fused converted position and doppler measurements Kalman filter (SF-CMKF) with additive debiased measurement conversion has been previously presented to combine the resulting states of converted position measurements Kalman filter (CPMKF) and converted doppler measurement Kalman filter (CDMKF) to yield the final state estimates under minimum mean squared error (MMSE) criterion. However, the exact compensation for the bias in the polar-to-cartesian and spherical-to-cartesian conversion are multiplicative and depend on the statistics of the cosine of the angle measurement errors. As a result, the consistency and performance of the SF-CMKF may be suboptimal in large-angle error situations. In this paper, the multiplicative unbiased position and Doppler measurement conversion for 2D (polar-to-cartesian) tracking are derived, and the SF-CMKF is improved to use those conversions. Monte Carlo simulations are presented to demonstrate the statistical consistency of the multiplicative unbiased conversion and the superior performance of the modified SF-CMKF (SF-UCMKF).

Keywords: measurement conversion, Doppler, Kalman filter, estimation, tracking

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Authors: Vaibhav Dalmia, Manoj Phirke, Renith G

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With the wide adoption of UAVs (unmanned aerial vehicles) in various industries by the government as well as private corporations for solving computer vision tasks it’s necessary that their potential is analyzed completely. Recent advances in Deep Learning have also left us with a plethora of algorithms to solve different computer vision tasks. This study provides a comprehensive survey on solving the Visual Object Tracking problem and explains the tradeoffs involved in building a real-time yet reasonably accurate object tracking system for UAVs by looking at existing methods and evaluating them on the aerial datasets. Finally, the best trackers suitable for UAV-based applications are provided.

Keywords: deep learning, drones, single object tracking, visual object tracking, UAVs

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Authors: Umarov Jamshid, Ju-Su Kim, Hak-Jun Lee, Man-Kyo Han, Ryum-Duck Oh

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Recently, it becomes convenient to identify the location information of cargos by using GPS and wireless communication technologies. The development of IoT technologies and tracking system allows us to confirm site situation on an ad hoc basis in all the industries and social environments. Moreover, it allows us to apply IT technologies to a manageable extent. However, there have been many limitations for using the system due to the difficulty of identifying location information in real time and also due to the simple features. To globalize the logistics related tracking system, it is required to conduct a study to resolve the aforementioned problem. On that account, this paper designed and developed the IoT and RTLS based intelligent multi tracking agent system for more secure, accurate and reliable transportation in relation to logistics.

Keywords: GPS, tracking agent system, IoT, RTLS, Logistics

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Authors: Cao Xi

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This paper reports a study which used eye-tracking to examine the cognitive validity of TEM 8(Test for English Majors, Band 8). The study investigated test takers' reading patterns on four -item types using eye-tracking, and interviews. Thirty participants completed 22 items on a computer, with the Tobii X2 Eye Tracker recording their eye movements on screen. Eleven students further participated in a recall interview while viewing video footage of their gaze patterns on the test. The findings will indicate that first, different reading item types will employ different cognitive processes; then different reading patterns for stronger and weaker test takers’on each item types. The implication of this study is to provide recommendations for the use of eye tracking technology in language research.

Keywords: eye tracking, reading patterns, test for english majors, cognitive validity

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Authors: Fadwa Alaskar, Fang-Chieh Chou, Carlos Flores, Xiao-Yun Lu, Alexandre M. Bayen

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This article proposes a perception model for enhancing the accuracy and stability of car-following control of a longitudinally automated truck. We applied a fusion-based tracking algorithm on measurements of a single preceding vehicle needed for car-following control. This algorithm fuses two types of data, radar and LiDAR data, to obtain more accurate and robust longitudinal perception of the subject vehicle in various weather conditions. The filter’s resulting signals are fed to the gap control algorithm at every tracking loop composed by a high-level gap control and lower acceleration tracking system. Several highway tests have been performed with two trucks. The tests show accurate and fast tracking of the target, which impacts on the gap control loop positively. The experiments also show the fulfilment of control design requirements, such as fast speed variations tracking and robust time gap following.

Keywords: object tracking, perception, sensor fusion, adaptive cruise control, cooperative adaptive cruise control

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Authors: Nahid Tavakoli, Mohammad H. Yarmohammadian, Ali Samimi

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In earthquake situation, medical response communities such as field and referral hospitals are challenged with injured victims’ identification and tracking. In our project, it was developed a patient tracking platform (PTP) where first responders triage the patients with an electronic tag which report the location and some information of each patient during his/her movement. This platform includes: 1) near field communication (NFC) tags (ISO 14443), 2) smart mobile phones (Android-base version 4.2.2), 3) Base station laptops (Windows), 4) server software, 5) Android software to use by first responders, 5) disaster command software, and 6) system architecture. Our model has been completed through literature review, Delphi technique, focus group, design the platform, and implement in an earthquake exercise. This paper presents consideration for content, function, and technologies that must apply for patient tracking in medical emergencies situations. It is demonstrated the robustness of the patient tracking platform (PTP) in tracking 6 patients in a simulated earthquake situation in the yard of the relief and rescue department of Isfahan’s Red Crescent.

Keywords: test and evaluation, patient tracking platform, earthquake, simulation

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Authors: Boukerch Haroun, Luo Qing Sheng, Li Hua Shi, Boukraa Sebti

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In this paper we present the design and the implementation of a target tracking system where the target is set to be a moving person in a video sequence. The system can be applied easily as a vision system for mobile robot. The system is composed of two major parts the first is the detection of the person in the video frame using the SVM learning machine based on the “HOG” descriptors. The second part is the tracking of a moving person it’s done by using a combination of the Kalman filter and a modified version of the Camshift tracking algorithm by adding the target motion feature to the color feature, the experimental results had shown that the new algorithm had overcame the traditional Camshift algorithm in robustness and in case of occlusion.

Keywords: camshift algorithm, computer vision, Kalman filter, object tracking

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Authors: Thang V. Kieu, Long P. Nguyen

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Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: correlation filter, long-term tracking, random fern, real-time tracking

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Authors: J. B. G. Ibarra, J. M. A. Gagui, E. J. T. Jonson, J. A. V. Lim

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This paper focused on studying the performance of the solar panels that were equipped with water-spray cooling system, solar tracking system, and combination of both systems. The efficiencies were compared with the solar panels without any efficiency improvement technique. The efficiency of each setup was computed on an hourly basis every day for a month. The study compared the efficiencies and combined systems that significantly improved at a specific time of the day. The data showed that the solar tracking system had the highest efficiency during 6:00 AM to 7:45 AM. Then after 7:45 AM, the combination of both solar tracking and water-spray cooling system was the most efficient to use up to 12:00 NN. Meanwhile, from 12:00 NN to 12:45 PM, the water-spray cooling system had the significant contribution on efficiency. From 12:45 PM up to 4:30 PM, the combination of both systems was the most efficient, and lastly, from 4:30 PM to 6:00 PM, the solar tracking system was the best to use. The study intended to use solar tracking or water-spray cooling system or combined systems alternately to improve the solar panel efficiency on a specific time of the day.

Keywords: solar panel efficiency, solar panel efficiency technique, solar tracking system, water-spray cooling system

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Authors: Wesam Jasim, Dongbing Gu

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This paper presents an iterative linear quadratic regulator optimal control technique to solve the problem of quadrotors path tracking. The dynamic motion equations are represented based on unit quaternion representation and include some modelled aerodynamical effects as a nonlinear part. Simulation results prove the ability and effectiveness of iLQR to stabilize the quadrotor and successfully track different paths. It also shows that iLQR controller outperforms LQR controller in terms of fast convergence and tracking errors.

Keywords: iLQR controller, optimal control, path tracking, quadrotor UAVs

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