Search results for: motion estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3074

Search results for: motion estimation

3044 Mixed Sub-Fractional Brownian Motion

Authors: Mounir Zili

Abstract:

We will introduce a new extension of the Brownian motion, that could serve to get a good model of many natural phenomena. It is a linear combination of a finite number of sub-fractional Brownian motions; that is why we will call it the mixed sub-fractional Brownian motion. We will present some basic properties of this process. Among others, we will check that our process is non-Markovian and that it has non-stationary increments. We will also give the conditions under which it is a semimartingale. Finally, the main features of its sample paths will be specified.

Keywords: mixed Gaussian processes, Sub-fractional Brownian motion, sample paths

Procedia PDF Downloads 456
3043 Motion Planning of SCARA Robots for Trajectory Tracking

Authors: Giovanni Incerti

Abstract:

The paper presents a method for a simple and immediate motion planning of a SCARA robot, whose end-effector has to move along a given trajectory; the calculation procedure requires the user to define in analytical form or by points the trajectory to be followed and to assign the curvilinear abscissa as function of the time. On the basis of the geometrical characteristics of the robot, a specifically developed program determines the motion laws of the actuators that enable the robot to generate the required movement; this software can be used in all industrial applications for which a SCARA robot has to be frequently reprogrammed, in order to generate various types of trajectories with different motion times.

Keywords: motion planning, SCARA robot, trajectory tracking, analytical form

Procedia PDF Downloads 286
3042 Mixed-Sub Fractional Brownian Motion

Authors: Mounir Zili

Abstract:

We will introduce a new extension of the Brownian motion, that could serve to get a good model of many natural phenomena. It is a linear combination of a finite number of sub-fractional Brownian motions; that is why we will call it the mixed sub-fractional Brownian motion. We will present some basic properties of this process. Among others, we will check that our process is non-markovian and that it has non-stationary increments. We will also give the conditions under which it is a semi-martingale. Finally, the main features of its sample paths will be specified.

Keywords: fractal dimensions, mixed gaussian processes, sample paths, sub-fractional brownian motion

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3041 Effective Virtual Tunnel Shape for Motion Modification in Upper-Limb Perception-Assist with a Power-Assist Robot

Authors: Kazuo Kiguchi, Kouta Ikegami

Abstract:

In the case of physically weak persons, not only motor abilities, but also sensory abilities are sometimes deteriorated. The concept of perception-assist has been proposed to assist the sensory ability of the physically weak persons with a power-assist robot. Since upper-limb motion is very important in daily living, perception-assist for upper-limb motion has been proposed to assist upper-limb motion in daily living. A virtual tunnel was applied to modify the user’s upper-limb motion if it was necessary. In this paper, effective shape of the virtual tunnel which is applied in the perception-assist for upper-limb motion is proposed. Not only the position of the grasped tool but also the angle of the grasped tool are modified if it is necessary. Therefore, the upper-limb motion in daily living can be effectively modified to realize certain proper daily motion. The effectiveness of the proposed virtual tunnel was evaluated by performing the experiments.

Keywords: motion modification, power-assist robots, perception-assist, upper-limb motion

Procedia PDF Downloads 218
3040 Latency-Based Motion Detection in Spiking Neural Networks

Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

Abstract:

Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: neural network, motion detection, signature detection, convolutional neural network

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3039 Cepstrum Analysis of Human Walking Signal

Authors: Koichi Kurita

Abstract:

In this study, we propose a real-time data collection technique for the detection of human walking motion from the charge generated on the human body. This technique is based on the detection of a sub-picoampere electrostatic induction current, generated by the motion, flowing through the electrode of a wireless portable sensor attached to the subject. An FFT analysis of the wave-forms of the electrostatic induction currents generated by the walking motions showed that the currents generated under normal and restricted walking conditions were different. Moreover, we carried out a cepstrum analysis to detect any differences in the walking style. Results suggest that a slight difference in motion, either due to the individual’s gait or a splinted leg, is directly reflected in the electrostatic induction current generated by the walking motion. The proposed wireless portable sensor enables the detection of even subtle differences in walking motion.

Keywords: human walking motion, motion measurement, current measurement, electrostatic induction

Procedia PDF Downloads 315
3038 Simulation of 3-D Direction-of-Arrival Estimation Using MUSIC Algorithm

Authors: Duckyong Kim, Jong Kang Park, Jong Tae Kim

Abstract:

DOA (Direction of Arrival) estimation is an important method in array signal processing and has a wide range of applications such as direction finding, beam forming, and so on. In this paper, we briefly introduce the MUSIC (Multiple Signal Classification) Algorithm, one of DOA estimation methods for analyzing several targets. Then we apply the MUSIC algorithm to the two-dimensional antenna array to analyze DOA estimation in 3D space through MATLAB simulation. We also analyze the design factors that can affect the accuracy of DOA estimation through simulation, and proceed with further consideration on how to apply the system.

Keywords: DOA estimation, MUSIC algorithm, spatial spectrum, array signal processing

Procedia PDF Downloads 339
3037 Lithium-Ion Battery State of Charge Estimation Using One State Hysteresis Model with Nonlinear Estimation Strategies

Authors: Mohammed Farag, Mina Attari, S. Andrew Gadsden, Saeid R. Habibi

Abstract:

Battery state of charge (SOC) estimation is an important parameter as it measures the total amount of electrical energy stored at a current time. The SOC percentage acts as a fuel gauge if it is compared with a conventional vehicle. Estimating the SOC is, therefore, essential for monitoring the amount of useful life remaining in the battery system. This paper looks at the implementation of three nonlinear estimation strategies for Li-Ion battery SOC estimation. One of the most common behavioral battery models is the one state hysteresis (OSH) model. The extended Kalman filter (EKF), the smooth variable structure filter (SVSF), and the time-varying smoothing boundary layer SVSF are applied on this model, and the results are compared.

Keywords: state of charge estimation, battery modeling, one-state hysteresis, filtering and estimation

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3036 The Modelling of Real Time Series Data

Authors: Valeria Bondarenko

Abstract:

We proposed algorithms for: estimation of parameters fBm (volatility and Hurst exponent) and for the approximation of random time series by functional of fBm. We proved the consistency of the estimators, which constitute the above algorithms, and proved the optimal forecast of approximated time series. The adequacy of estimation algorithms, approximation, and forecasting is proved by numerical experiment. During the process of creating software, the system has been created, which is displayed by the hierarchical structure. The comparative analysis of proposed algorithms with the other methods gives evidence of the advantage of approximation method. The results can be used to develop methods for the analysis and modeling of time series describing the economic, physical, biological and other processes.

Keywords: mathematical model, random process, Wiener process, fractional Brownian motion

Procedia PDF Downloads 319
3035 Frequency Offset Estimation Schemes Based on ML for OFDM Systems in Non-Gaussian Noise Environments

Authors: Keunhong Chae, Seokho Yoon

Abstract:

In this paper, frequency offset (FO) estimation schemes robust to the non-Gaussian noise environments are proposed for orthogonal frequency division multiplexing (OFDM) systems. First, a maximum-likelihood (ML) estimation scheme in non-Gaussian noise environments is proposed, and then, the complexity of the ML estimation scheme is reduced by employing a reduced set of candidate values. In numerical results, it is demonstrated that the proposed schemes provide a significant performance improvement over the conventional estimation scheme in non-Gaussian noise environments while maintaining the performance similar to the estimation performance in Gaussian noise environments.

Keywords: frequency offset estimation, maximum-likelihood, non-Gaussian noise environment, OFDM, training symbol

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3034 Parameters Estimation of Multidimensional Possibility Distributions

Authors: Sergey Sorokin, Irina Sorokina, Alexander Yazenin

Abstract:

We present a solution to the Maxmin u/E parameters estimation problem of possibility distributions in m-dimensional case. Our method is based on geometrical approach, where minimal area enclosing ellipsoid is constructed around the sample. Also we demonstrate that one can improve results of well-known algorithms in fuzzy model identification task using Maxmin u/E parameters estimation.

Keywords: possibility distribution, parameters estimation, Maxmin u\E estimator, fuzzy model identification

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3033 A Study on the Establishment of a 4-Joint Based Motion Capture System and Data Acquisition

Authors: Kyeong-Ri Ko, Seong Bong Bae, Jang Sik Choi, Sung Bum Pan

Abstract:

A simple method for testing the posture imbalance of the human body is to check for differences in the bilateral shoulder and pelvic height of the target. In this paper, to check for spinal disorders the authors have studied ways to establish a motion capture system to obtain and express motions of 4-joints, and to acquire data based on this system. The 4 sensors are attached to the both shoulders and pelvis. To verify the established system, the normal and abnormal postures of the targets listening to a lecture were obtained using the established 4-joint based motion capture system. From the results, it was confirmed that the motions taken by the target was identical to the 3-dimensional simulation.

Keywords: inertial sensor, motion capture, motion data acquisition, posture imbalance

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3032 Quantification of Soft Tissue Artefacts Using Motion Capture Data and Ultrasound Depth Measurements

Authors: Azadeh Rouhandeh, Chris Joslin, Zhen Qu, Yuu Ono

Abstract:

The centre of rotation of the hip joint is needed for an accurate simulation of the joint performance in many applications such as pre-operative planning simulation, human gait analysis, and hip joint disorders. In human movement analysis, the hip joint center can be estimated using a functional method based on the relative motion of the femur to pelvis measured using reflective markers attached to the skin surface. The principal source of errors in estimation of hip joint centre location using functional methods is soft tissue artefacts due to the relative motion between the markers and bone. One of the main objectives in human movement analysis is the assessment of soft tissue artefact as the accuracy of functional methods depends upon it. Various studies have described the movement of soft tissue artefact invasively, such as intra-cortical pins, external fixators, percutaneous skeletal trackers, and Roentgen photogrammetry. The goal of this study is to present a non-invasive method to assess the displacements of the markers relative to the underlying bone using optical motion capture data and tissue thickness from ultrasound measurements during flexion, extension, and abduction (all with knee extended) of the hip joint. Results show that the artefact skin marker displacements are non-linear and larger in areas closer to the hip joint. Also marker displacements are dependent on the movement type and relatively larger in abduction movement. The quantification of soft tissue artefacts can be used as a basis for a correction procedure for hip joint kinematics.

Keywords: hip joint center, motion capture, soft tissue artefact, ultrasound depth measurement

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3031 A Packet Loss Probability Estimation Filter Using Most Recent Finite Traffic Measurements

Authors: Pyung Soo Kim, Eung Hyuk Lee, Mun Suck Jang

Abstract:

A packet loss probability (PLP) estimation filter with finite memory structure is proposed to estimate the packet rate mean and variance of the input traffic process in real-time while removing undesired system and measurement noises. The proposed PLP estimation filter is developed under a weighted least square criterion using only the finite traffic measurements on the most recent window. The proposed PLP estimation filter is shown to have several inherent properties such as unbiasedness, deadbeat, robustness. A guideline for choosing appropriate window length is described since it can affect significantly the estimation performance. Using computer simulations, the proposed PLP estimation filter is shown to be superior to the Kalman filter for the temporarily uncertain system. One possible explanation for this is that the proposed PLP estimation filter can have greater convergence time of a filtered estimate as the window length M decreases.

Keywords: packet loss probability estimation, finite memory filter, infinite memory filter, Kalman filter

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3030 Fast Prediction Unit Partition Decision and Accelerating the Algorithm Using Cudafor Intra and Inter Prediction of HEVC

Authors: Qiang Zhang, Chun Yuan

Abstract:

Since the PU (Prediction Unit) decision process is the most time consuming part of the emerging HEVC (High Efficient Video Coding) standardin intra and inter frame coding, this paper proposes the fast PU decision algorithm and speed up the algorithm using CUDA (Compute Unified Device Architecture). In intra frame coding, the fast PU decision algorithm uses the texture features to skip intra-frame prediction or terminal the intra-frame prediction for smaller PU size. In inter frame coding of HEVC, the fast PU decision algorithm takes use of the similarity of its own two Nx2N size PU's motion vectors and the hierarchical structure of CU (Coding Unit) partition to skip some modes of PU partition, so as to reduce the motion estimation times. The accelerate algorithm using CUDA is based on the fast PU decision algorithm which uses the GPU to make the motion search and the gradient computation could be parallel computed. The proposed algorithm achieves up to 57% time saving compared to the HM 10.0 with little rate-distortion losses (0.043dB drop and 1.82% bitrate increase on average).

Keywords: HEVC, PU decision, inter prediction, intra prediction, CUDA, parallel

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3029 Derivation of Fractional Black-Scholes Equations Driven by Fractional G-Brownian Motion and Their Application in European Option Pricing

Authors: Changhong Guo, Shaomei Fang, Yong He

Abstract:

In this paper, fractional Black-Scholes models for the European option pricing were established based on the fractional G-Brownian motion (fGBm), which generalizes the concepts of the classical Brownian motion, fractional Brownian motion and the G-Brownian motion, and that can be used to be a tool for considering the long range dependence and uncertain volatility for the financial markets simultaneously. A generalized fractional Black-Scholes equation (FBSE) was derived by using the Taylor’s series of fractional order and the theory of absence of arbitrage. Finally, some explicit option pricing formulas for the European call option and put option under the FBSE were also solved, which extended the classical option pricing formulas given by F. Black and M. Scholes.

Keywords: European option pricing, fractional Black-Scholes equations, fractional g-Brownian motion, Taylor's series of fractional order, uncertain volatility

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3028 Evaluation of the MCFLIRT Correction Algorithm in Head Motion from Resting State fMRI Data

Authors: V. Sacca, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

Abstract:

In the last few years, resting-state functional MRI (rs-fMRI) was widely used to investigate the architecture of brain networks by investigating the Blood Oxygenation Level Dependent response. This technique represented an interesting, robust and reliable approach to compare pathologic and healthy subjects in order to investigate neurodegenerative diseases evolution. On the other hand, the elaboration of rs-fMRI data resulted to be very prone to noise due to confounding factors especially the head motion. Head motion has long been known to be a source of artefacts in task-based functional MRI studies, but it has become a particularly challenging problem in recent studies using rs-fMRI. The aim of this work was to evaluate in MS patients a well-known motion correction algorithm from the FMRIB's Software Library - MCFLIRT - that could be applied to minimize the head motion distortions, allowing to correctly interpret rs-fMRI results.

Keywords: head motion correction, MCFLIRT algorithm, multiple sclerosis, resting state fMRI

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3027 Nonuniformity of the Piston Motion in a Radial Aircraft Engine

Authors: K. Pietrykowski, M. Bialy, M. Duk

Abstract:

One of the main disadvantages of radial engines is non-uniformity of operating cycles of each cylinder. This paper discusses the results of the kinematic analysis of pistons motion of the ASz-62IR radial engine. The ASz-62IR engine is produced in Poland and mounted in the M-18 Dromader and the An-2. The results are shown as the courses of the motion of the pistons. The discrepancies in the courses for individual pistons can result in different masses of the charge to fill the cylinders. Besides, pistons acceleration of individual cylinders is different, which triggers an additional vibration in the engine.

Keywords: nonuniformity, kinematic analysis, piston motion, radial engine

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3026 Priority of Goal Over Source in Persian Directional Motion Verbs

Authors: Tahereh Samenian

Abstract:

There is ample evidence that source and goal are disproportionately expressed in languages, and goal usually plays a more prominent role than source. The results show that the mismatch between the goal and the source is not entirely rooted in non-linguistic behaviors, i.e. that linguistic descriptions also show the focus of the goal on the source in events; Non-verbal memory for events, on the other hand, indicates that the focus of the goal is only on events that are purposefully moving and the actor is alive. In the present study, an attempt is made to examine the principle of priority of the goal over the source by focusing on Persian directional motion verbs. For this purpose, 117 Persian directional motion verbs have been selected from the dictionary and data for them have been collected from the body of Bijan Khan and the components of goal and source have been identified in sentences and the prominence of the components of goal and source has been shown in the form of diagrams. As it was obtained from the data, Persian motion-directional verbs also showed the bias of the goal over source in motion events.

Keywords: motion-directional verbs, priority of goal over source principle, cognitive factors, linguistic factors

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3025 Development of 4D Dynamic Simulation Tool for the Evaluation of Left Ventricular Myocardial Functions

Authors: Deepa, Yashbir Singh, Shi Yi Wu, Michael Friebe, Joao Manuel R. S. Tavares, Hu Wei-Chih

Abstract:

Cardiovascular disease can be detected by measuring the regional and global wall motion of the left ventricle (LV) of the heart; In this study, we designed a dynamic simulation tool using Computed Tomography (CT) images to assess the difference between actual and simulated left ventricular functions. Thirteen healthy subjects were involved in the study with actual and simulated left ventricular functions. In this research, we found the high correlation between actual left ventricular wall motion and simulated left ventricular wall motion. Our results confirm that our simulation tool is feasible for simulating left ventricular motion.

Keywords: cardiac imaging, left-ventricular remodeling, cardiac wall motion, myocardial functions

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3024 Plantation Forests Height Mapping Using Unmanned Aerial System

Authors: Shiming Li, Qingwang Liu, Honggan Wu, Jianbing Zhang

Abstract:

Plantation forests are useful for timber production, recreation, environmental protection and social development. Stands height is an important parameter for the estimation of forest volume and carbon stocks. Although lidar is suitable technology for the vertical parameters extraction of forests, but high costs make it not suitable for operational inventory. With the development of computer vision and photogrammetry, aerial photos from unmanned aerial system can be used as an alternative solution for height mapping. Structure-from-motion (SfM) photogrammetry technique can be used to extract DSM and DEM information. Canopy height model (CHM) can be achieved by subtraction DEM from DSM. Our result shows that overlapping aerial photos is a potential solution for plantation forests height mapping.

Keywords: forest height mapping, plantation forests, structure-from-motion photogrammetry, UAS

Procedia PDF Downloads 238
3023 Prediction of Seismic Damage Using Scalar Intensity Measures Based on Integration of Spectral Values

Authors: Konstantinos G. Kostinakis, Asimina M. Athanatopoulou

Abstract:

A key issue in seismic risk analysis within the context of Performance-Based Earthquake Engineering is the evaluation of the expected seismic damage of structures under a specific earthquake ground motion. The assessment of the seismic performance strongly depends on the choice of the seismic Intensity Measure (IM), which quantifies the characteristics of a ground motion that are important to the nonlinear structural response. Several conventional IMs of ground motion have been used to estimate their damage potential to structures. Yet, none of them has been proved to be able to predict adequately the seismic damage. Therefore, alternative, scalar intensity measures, which take into account not only ground motion characteristics but also structural information have been proposed. Some of these IMs are based on integration of spectral values over a range of periods, in an attempt to account for the information that the shape of the acceleration, velocity or displacement spectrum provides. The adequacy of a number of these IMs in predicting the structural damage of 3D R/C buildings is investigated in the present paper. The investigated IMs, some of which are structure specific and some are nonstructure-specific, are defined via integration of spectral values. To achieve this purpose three symmetric in plan R/C buildings are studied. The buildings are subjected to 59 bidirectional earthquake ground motions. The two horizontal accelerograms of each ground motion are applied along the structural axes. The response is determined by nonlinear time history analysis. The structural damage is expressed in terms of the maximum interstory drift as well as the overall structural damage index. The values of the aforementioned seismic damage measures are correlated with seven scalar ground motion IMs. The comparative assessment of the results revealed that the structure-specific IMs present higher correlation with the seismic damage of the three buildings. However, the adequacy of the IMs for estimation of the structural damage depends on the response parameter adopted. Furthermore, it was confirmed that the widely used spectral acceleration at the fundamental period of the structure is a good indicator of the expected earthquake damage level.

Keywords: damage measures, bidirectional excitation, spectral based IMs, R/C buildings

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3022 Time Delay Estimation Using Signal Envelopes for Synchronisation of Recordings

Authors: Sergei Aleinik, Mikhail Stolbov

Abstract:

In this work, a method of time delay estimation for dual-channel acoustic signals (speech, music, etc.) recorded under reverberant conditions is investigated. Standard methods based on cross-correlation of the signals show poor results in cases involving strong reverberation, large distances between microphones and asynchronous recordings. Under similar conditions, a method based on cross-correlation of temporal envelopes of the signals delivers a delay estimation of acceptable quality. This method and its properties are described and investigated in detail, including its limits of applicability. The method’s optimal parameter estimation and a comparison with other known methods of time delay estimation are also provided.

Keywords: cross-correlation, delay estimation, signal envelope, signal processing

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3021 Basic Properties of a Fundamental Particle: Behavioral-Physical and Visual Methods for the Study of Fundamental Particle

Authors: Shukran M. Dadayev

Abstract:

To author's best knowledge, in this paper, the Basic Properties and Research methods of a Fundamental Particle is studied for the first time. That's to say, Fundamental Particle has not been discovered in the Nature yet. Because Fundamental Particle consists of specific Physical, Geometrical and Internal bases. Geometrical and Internal characteristics that are considered significant for the elementary and fundamental particles aren’t basic properties, characteristics or criteria of a Fundamental Particle. Of course, completely new Physical and Visual experimental methods of Quantum mechanics and Behavioral-Physical investigations of Particles are needed to study and discover the Fundamental Particle. These are new Physical, Visual and Behavioral-Physical experimental methods for describing and discovering the Fundamental Particle in the Nature and Microworld. Fundamental Particle consists of the same Energy-Mass-Motion system and a symmetry of Energy-Mass-Motion. Fundamental Particle supplies each of the elementary particles with the same Energy-Mass-Motion system at the same time and regulates each of the particles. Fundamental Particle gives Energy, Mass and Motion to each particles at the same time, each of the Particles consists of acquired Energy-Mass-Motion system and symmetry. Energy, Mass, Motion given by the Fundamental Particle to the particles are Symmetrical Equivalent and they remain in their primary shapes in all cases. Fundamental Particle gives Energy-Mass-Motion system and symmetry consisting of different measures and functions to each of the particles. The Motion given by the Fundamental Particle to the particles is Gravitation, Gravitational Interaction not only gives Motion, but also cause Motion by attracting. All Substances, Fields and Cosmic objects consist of Energy-Mass-Motion. The Field also includes specific Mass. They are always Energetic, Massive and Active. Fundamental Particle establishes the bases of the Nature. Supplement and Regulating of all the particles existing in the Nature belongs to Fundamental Particle.

Keywords: basic properties of a fundamental particle, behavioral-physical and visual methods, energy-mass-motion system and symmetrical equivalence, fundamental particle

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3020 VaR Estimation Using the Informational Content of Futures Traded Volume

Authors: Amel Oueslati, Olfa Benouda

Abstract:

New Value at Risk (VaR) estimation is proposed and investigated. The well-known two stages Garch-EVT approach uses conditional volatility to generate one step ahead forecasts of VaR. With daily data for twelve stocks that decompose the Dow Jones Industrial Average (DJIA) index, this paper incorporates the volume in the first stage volatility estimation. Afterwards, the forecasting ability of this conditional volatility concerning the VaR estimation is compared to that of a basic volatility model without considering any trading component. The results are significant and bring out the importance of the trading volume in the VaR measure.

Keywords: Garch-EVT, value at risk, volume, volatility

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3019 Platform Virtual for Joint Amplitude Measurement Based in MEMS

Authors: Mauro Callejas-Cuervo, Andrea C. Alarcon-Aldana, Andres F. Ruiz-Olaya, Juan C. Alvarez

Abstract:

Motion capture (MC) is the construction of a precise and accurate digital representation of a real motion. Systems have been used in the last years in a wide range of applications, from films special effects and animation, interactive entertainment, medicine, to high competitive sport where a maximum performance and low injury risk during training and competition is seeking. This paper presents an inertial and magnetic sensor based technological platform, intended for particular amplitude monitoring and telerehabilitation processes considering an efficient cost/technical considerations compromise. Our platform particularities offer high social impact possibilities by making telerehabilitation accessible to large population sectors in marginal socio-economic sector, especially in underdeveloped countries that in opposition to developed countries specialist are scarce, and high technology is not available or inexistent. This platform integrates high-resolution low-cost inertial and magnetic sensors with adequate user interfaces and communication protocols to perform a web or other communication networks available diagnosis service. The amplitude information is generated by sensors then transferred to a computing device with adequate interfaces to make it accessible to inexperienced personnel, providing a high social value. Amplitude measurements of the platform virtual system presented a good fit to its respective reference system. Analyzing the robotic arm results (estimation error RMSE 1=2.12° and estimation error RMSE 2=2.28°), it can be observed that during arm motion in any sense, the estimation error is negligible; in fact, error appears only during sense inversion what can easily be explained by the nature of inertial sensors and its relation to acceleration. Inertial sensors present a time constant delay which acts as a first order filter attenuating signals at large acceleration values as is the case for a change of sense in motion. It can be seen a damped response of platform virtual in other images where error analysis show that at maximum amplitude an underestimation of amplitude is present whereas at minimum amplitude estimations an overestimation of amplitude is observed. This work presents and describes the platform virtual as a motion capture system suitable for telerehabilitation with the cost - quality and precision - accessibility relations optimized. These particular characteristics achieved by efficiently using the state of the art of accessible generic technology in sensors and hardware, and adequate software for capture, transmission analysis and visualization, provides the capacity to offer good telerehabilitation services, reaching large more or less marginal populations where technologies and specialists are not available but accessible with basic communication networks.

Keywords: inertial sensors, joint amplitude measurement, MEMS, telerehabilitation

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3018 Depth Estimation in DNN Using Stereo Thermal Image Pairs

Authors: Ahmet Faruk Akyuz, Hasan Sakir Bilge

Abstract:

Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea.

Keywords: thermal stereo matching, deep neural networks, CNN, Depth estimation

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3017 Parameter Estimation of Induction Motors by PSO Algorithm

Authors: A. Mohammadi, S. Asghari, M. Aien, M. Rashidinejad

Abstract:

After emergent of alternative current networks and their popularity, asynchronous motors became more widespread than other kinds of industrial motors. In order to control and run these motors efficiently, an accurate estimation of motor parameters is needed. There are different methods to obtain these parameters such as rotor locked test, no load test, DC test, analytical methods, and so on. The most common drawback of these methods is their inaccuracy in estimation of some motor parameters. In order to remove this concern, a novel method for parameter estimation of induction motors using particle swarm optimization (PSO) algorithm is proposed. In the proposed method, transient state of motor is used for parameter estimation. Comparison of the simulation results purtuined to the PSO algorithm with other available methods justifies the effectiveness of the proposed method.

Keywords: induction motor, motor parameter estimation, PSO algorithm, analytical method

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3016 Design and Test a Robust Bearing-Only Target Motion Analysis Algorithm Based on Modified Gain Extended Kalman Filter

Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

Abstract:

Passive sonar is a method for detecting acoustic signals in the ocean. It detects the acoustic signals emanating from external sources. With passive sonar, we can determine the bearing of the target only, no information about the range of the target. Target Motion Analysis (TMA) is a process to estimate the position and speed of a target using passive sonar information. Since bearing is the only available information, the TMA technique called Bearing-only TMA. Many TMA techniques have been developed. However, until now, there is not a very effective method that could be used to always track an unknown target and extract its moving trace. In this work, a design of effective Bearing-only TMA Algorithm is done. The measured bearing angles are very noisy. Moreover, for multi-beam sonar, the measurements is quantized due to the sonar beam width. To deal with this, modified gain extended Kalman filter algorithm is used. The algorithm is fine-tuned, and many modules are added to improve the performance. A special validation gate module is used to insure stability of the algorithm. Many indicators of the performance and confidence level measurement are designed and tested. A new method to detect if the target is maneuvering is proposed. Moreover, a reactive optimal observer maneuver based on bearing measurements is proposed, which insure converging to the right solution all of the times. To test the performance of the proposed TMA algorithm a simulation is done with a MATLAB program. The simulator program tries to model a discrete scenario for an observer and a target. The simulator takes into consideration all the practical aspects of the problem such as a smooth transition in the speed, a circular turn of the ship, noisy measurements, and a quantized bearing measurement come for multi-beam sonar. The tests are done for a lot of given test scenarios. For all the tests, full tracking is achieved within 10 minutes with very little error. The range estimation error was less than 5%, speed error less than 5% and heading error less than 2 degree. For the online performance estimator, it is mostly aligned with the real performance. The range estimation confidence level gives a value equal to 90% when the range error less than 10%. The experiments show that the proposed TMA algorithm is very robust and has low estimation error. However, the converging time of the algorithm is needed to be improved.

Keywords: target motion analysis, Kalman filter, passive sonar, bearing-only tracking

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3015 A Passive Reaction Force Compensation for a Linear Motor Motion Stage Using Pre-Compressed Springs

Authors: Kim Duc Hoang, Hyeong Joon Ahn

Abstract:

Residual vibration of the system base due to a high-acceleration motion of a stage may reduce life and productivity of the manufacturing device. Although a passive RFC can reduce vibration of the system base, spring or dummy mass should be replaced to tune performance of the RFC. In this paper, we develop a novel concept of the passive RFC mechanism for a linear motor motion stage using pre-compressed springs. Dynamic characteristic of the passive RFC can be adjusted by pre-compression of the spring without exchanging the spring or dummy mass. First, we build a linear motor motion stage with pre-compressed springs. Then, the effect of the pre-compressed spring on the passive RFC is investigated by changing both pre-compressions and stiffness of springs. Finally, the effectiveness of the passive RFC using pre-compressed springs was verified with both simulations and experiments.

Keywords: linear motor motion stage, residual vibration, passive RFC, pre-compressed spring

Procedia PDF Downloads 314