Search results for: frequency estimation

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

Abstract:

In the current paper, an indoor positioning system is proposed with consideration of measurement delay. Firstly, an estimation filter with a measurement delay is designed for the indoor positioning mechanism under a weighted least square criterion, which utilizes only finite measurements on the most recent window. The proposed estimation filtering based scheme gives the filtered estimates for position, velocity and acceleration of moving target in real-time, while removing undesired noisy effects and preserving desired moving positions. Secondly, the proposed scheme is shown to have good inherent properties such as unbiasedness, efficiency, time-invariance, deadbeat, and robustness due to the finite memory structure. Finally, computer simulations shows that the performance of the proposed estimation filtering based scheme can outperform to the existing infinite memory filtering based mechanism.

Keywords: indoor positioning system, wireless sensor networks, measurement delay

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Authors: Abdullah Eqal Al Mazrooei

Abstract:

In this paper, we introduce a mathematical algorithm which is used for estimating the states in the bilinear systems. This algorithm uses a special linearization of the second-order term by using the best available information about the state of the system. This technique makes our algorithm generalizes the well-known Kalman estimators. The system which is used here is of the bilinear class, the evolution of this model is linear-bilinear in the state of the system. Our algorithm can be used with linear and bilinear systems. We also here introduced a real application for the new algorithm to prove the feasibility and the efficiency for it.

Keywords: estimation algorithm, bilinear systems, Kakman filter, second order linearization

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Authors: Naime Boudemagh, Zoheir Hammoudi

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The parameters estimation of the K-distribution is an essential part in radar detection. In fact, presence of interfering targets in reference cells causes a decrease in detection performances. In such situation, the estimate of the shape and the scale parameters are far from the actual values. In the order to avoid interfering targets, we propose an Automatic Censoring (AC) algorithm of radar interfering targets in K-distribution. The censoring technique used in this work offers a good discrimination between homogeneous and non-homogeneous environments. The homogeneous population is then used to estimate the unknown parameters by the classical Method of Moment (MOM). The AC algorithm does not need any prior information about the clutter parameters nor does it require both the number and the position of interfering targets. The accuracy of the estimation parameters obtained by this algorithm are validated and compared to various actual values of the shape parameter, using Monte Carlo simulations, this latter show that the probability of censing in multiple target situations are in good agreement.

Keywords: parameters estimation, method of moments, automatic censoring, K distribution

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

Abstract:

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: Mekonen G., Sileshi M., Melkamu M.

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Recharge estimation is important for the assessment and management of groundwater resources effectively. This study applied the soil moisture balance and Baseflow separation methods to estimate groundwater recharge in the Fetam Catchment. It is one of the major catchments understudied from the different catchments in the upper Blue Nile River basin. Surface water has been subjected to high seasonal variation; due to this, groundwater is a primary option for drinking water supply to the community. This research has been conducted to estimate groundwater recharge by using fifteen years of River flow data for the Baseflow separation and ten years of daily meteorological data for the daily soil moisture balance recharge estimating method. The recharge rate by the two methods is 170.5 and 244.9mm/year daily soil moisture and baseflow separation method, respectively, and the average recharge is 207.7mm/year. The average value of annual recharge in the catchment is almost equal to the average recharge in the country, which is 200mm/year. So, each method has its own limitations, and taking the average value is preferable rather than taking a single value. Baseflow provides overestimated result compared to the average of the two, and soil moisture balance is the list estimator. The recharge estimation in the area also should be done by other recharge estimation methods.

Keywords: groundwater, recharge, baseflow separation, soil moisture balance, Fetam catchment

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Authors: Wikanda Phaphan

Abstract:

Mixture generalized gamma distribution is a combination of two distributions: generalized gamma distribution and length biased generalized gamma distribution. These two distributions were presented by Suksaengrakcharoen and Bodhisuwan in 2014. The findings showed that probability density function (pdf) had fairly complexities, so it made problems in estimating parameters. The problem occurred in parameter estimation was that we were unable to calculate estimators in the form of critical expression. Thus, we will use numerical estimation to find the estimators. In this study, we presented a new method of the parameter estimation by using the expectation – maximization algorithm (EM), the conjugate gradient method, and the quasi-Newton method. The data was generated by acceptance-rejection method which is used for estimating α, β, λ and p. λ is the scale parameter, p is the weight parameter, α and β are the shape parameters. We will use Monte Carlo technique to find the estimator's performance. Determining the size of sample equals 10, 30, 100; the simulations were repeated 20 times in each case. We evaluated the effectiveness of the estimators which was introduced by considering values of the mean squared errors and the bias. The findings revealed that the EM-algorithm had proximity to the actual values determined. Also, the maximum likelihood estimators via the conjugate gradient and the quasi-Newton method are less precision than the maximum likelihood estimators via the EM-algorithm.

Keywords: conjugate gradient method, quasi-Newton method, EM-algorithm, generalized gamma distribution, length biased generalized gamma distribution, maximum likelihood method

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Authors: Ranjitkumar Patil

Abstract:

Age estimation has its importance in forensic dentistry. Dental age estimation has emerged as an alternative to skeletal age determination. The methods based on stages of tooth formation, as appreciated on radiographs, seems to be more appropriate in the assessment of age than those based on skeletal development. The study was done to evaluate dental age in north Indian population using Cameriere’s method. Aims/Objectives: The study was conducted to assess the dental age of North Indian children using Cameriere’smethodand to compare the chronological age and dental age for validation of the Cameriere’smethod in the north Indian population. A comparative study of 02 year duration on the OPG (using PLANMECA Promax 3D) data of 497 individuals with age ranging from 5 to 15 years was done based on simple random technique ethical approval obtained from the institutional ethical committee. The data was obtained based on inclusion and exclusion criteria was analyzed by a software for dental age estimation. Statistical analysis: Student’s t test was used to compare the morphological variables of males with those of females and to compare observed age with estimated age. Regression formula was also calculated. Results: Present study was a comparative study of 497 subjects with a distribution between male and female, with their dental age assessed by using Panoramic radiograph, following the method described by Cameriere, which is widely accepted. Statistical analysis in our study indicated that gender does not have a significant influence on age estimation. (R2= 0.787). Conclusion: This infers that cameriere’s method can be effectively applied in north Indianpopulation.

Keywords: Forensic, Chronological Age, Dental Age, Skeletal Age

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Authors: Tugba Bayoglu

Abstract:

Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

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Authors: W. Du, X. Wang, Jun Cao, H. F. Wang

Abstract:

Due to the randomness and uncertainty of wind energy, modern power systems integrating large-scale wind generation will be significantly impacted in terms of system performance and technical challenges. System inertia with high wind penetration is decreasing when conventional thermal generators are gradually replaced by wind turbines, which do not naturally contribute to inertia response. The power imbalance caused by wind power or demand fluctuations leads to the instability of system frequency. Accordingly, the need to attach the supplementary virtual inertia control to wind farms (WFs) strongly arises. When multi-wind farms are connected to the grid simultaneously, the selection of which critical WFs to install the virtual inertia control is greatly important to enhance the stability of system frequency. By building the small signal model of wind power systems considering frequency regulation, the installation locations are identified by the geometric measures of the mode observability of WFs. In addition, this paper takes the impacts of grid topology and selection of feedback control signals into consideration. Finally, simulations are conducted on a multi-wind farms power system and the results demonstrate that the designed virtual inertia control method can effectively assist the frequency regulation.

Keywords: frequency regulation, virtual inertia control, installation locations, observability, wind farms

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Authors: Alam Ali, Ashok Kumar Pathak

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Nowadays, copulas have attracted significant attention for modeling multivariate observations, and the foremost feature of copula functions is that they give us the liberty to study the univariate marginal distributions and their joint behavior separately. The copula parameter apprehends the intrinsic dependence among the marginal variables, and it can be estimated using parametric, semiparametric, or nonparametric techniques. This work aims to compare the coverage rates between an Elliptical and an Archimedean family of copulas via a fully parametric estimation technique.

Keywords: elliptical copula, archimedean copula, estimation, coverage rate

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Authors: B. Gepts, E. Meex, E. Nuyts, E. Knaepen, G. Verbeeck

Abstract:

The importance of resource efficiency and environmental impact assessment has raised the interest in knowing the amount of materials used in buildings. If no BIM model or energy performance certificate is available, material quantities can be obtained through an estimation or time-consuming calculation. For the interior wall area, no validated estimation method exists. However, in the case of environmental impact assessment or evaluating the existing building stock as future material banks, knowledge of the material quantities used in interior walls is indispensable. This paper presents a validated method for the estimation of the interior wall area for dwellings based on easy-to-collect building characteristics. A database of 4963 residential buildings spread all over Belgium is used. The data are collected through onsite measurements of the buildings during the construction phase (between mid-2010 and mid-2017). The interior wall area refers to the area of all interior walls in the building, including the inner leaf of exterior (party) walls, minus the area of windows and doors, unless mentioned otherwise. The two predictive modelling techniques used are 1) a (stepwise) linear regression and 2) a decision tree. The best estimation method is selected based on the best R² k-fold (5) fit. The research shows that the building volume is by far the most important variable to estimate the interior wall area. A stepwise regression based on building volume per building, building typology, and type of house provides the best fit, with R² k-fold (5) = 0.88. Although the best R² k-fold value is obtained when the other parameters ‘building typology’ and ‘type of house’ are included, the contribution of these variables can be seen as statistically significant but practically irrelevant. Thus, if these parameters are not available, a simplified estimation method based on only the volume of the building can also be applied (R² k-fold = 0.87). The robustness and precision of the method (output) are validated three times. Firstly, the prediction of the interior wall area is checked by means of alternative calculations of the building volume and of the interior wall area; thus, other definitions are applied to the same data. Secondly, the output is tested on an extension of the database, so it has the same definitions but on other data. Thirdly, the output is checked on an unrelated database with other definitions and other data. The validation of the estimation methods demonstrates that the methods remain accurate when underlying data are changed. The method can support environmental as well as economic dimensions of impact assessment, as it can be used in early design. As it allows the prediction of the amount of interior wall materials to be produced in the future or that might become available after demolition, the presented estimation method can be part of material flow analyses on input and on output.

Keywords: buildings as material banks, building stock, estimation method, interior wall area

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Authors: M. Abderrahmane Mograne, Didier Laux, Jean-Yves Ferrandis

Abstract:

Rheological characterizations of complex liquids like polymer solutions present an important scientific interest for a lot of researchers in many fields as biology, food industry, chemistry. In order to establish master curves (elastic moduli vs frequency) which can give information about microstructure, classical rheometers or viscometers (such as Couette systems) are used. For broadband characterization of the sample, temperature is modified in a very large range leading to equivalent frequency modifications applying the Time Temperature Superposition principle. For many liquids undergoing phase transitions, this approach is not applicable. That is the reason, why the development of broadband spectroscopic methods around room temperature becomes a major concern. In literature many solutions have been proposed but, to our knowledge, there is no experimental bench giving the whole rheological characterization for frequencies about a few Hz (Hertz) to many MHz (Mega Hertz). Consequently, our goal is to investigate in a nondestructive way in very broadband frequency (A few Hz – Hundreds of MHz) rheological properties using longitudinal ultrasonic waves (L waves), a unique experimental bench and a specific container for the liquid: a test tube. More specifically, we aim to estimate the three viscosities (longitudinal, shear and bulk) and the complex elastic moduli (M*, G* and K*) respectively longitudinal, shear and bulk moduli. We have decided to use only L waves conditioned in two ways: bulk L wave in the liquid or guided L waves in the tube test walls. In this paper, we will present first results for very low frequencies using the ultrasonic tracking of a falling ball in the test tube. This will lead to the estimation of shear viscosity from a few mPa.s to a few Pa.s (Pascal second). Corrections due to the small dimensions of the tube will be applied and discussed regarding the size of the falling ball. Then the use of bulk L wave’s propagation in the liquid and the development of a specific signal processing in order to assess longitudinal velocity and attenuation will conduct to the longitudinal viscosity evaluation in the MHz frequency range. At last, the first results concerning the propagation, the generation and the processing of guided compressional waves in the test tube walls will be discussed. All these approaches and results will be compared to standard methods available and already validated in our lab.

Keywords: nondestructive measurement for liquid, piezoelectric transducer, ultrasonic longitudinal waves, viscosities

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Authors: Win Zaw Hein, Khin Sandar Linn, Su Su Yi Mon, Yoshitaka Goto

Abstract:

The Earth ionosphere is located at the altitude of about 70 km to several 100 km from the ground, and it is composed of ions and electrons called plasma. In the ionosphere, these plasma makes delay in GPS (Global Positioning System) signals and reflect in radio waves. The delay along the signal path from the satellite to the receiver is directly proportional to the total electron content (TEC) of plasma, and this delay is the largest error factor in satellite positioning and navigation. Sounding observation from the top and bottom of the ionosphere was popular to investigate such ionospheric plasma for a long time. Recently, continuous monitoring of the TEC using networks of GNSS (Global Navigation Satellite System) observation stations, which are basically built for land survey, has been conducted in several countries. However, in these stations, multi-frequency support receivers are installed to estimate the effect of plasma delay using their frequency dependence and the cost of multi-frequency support receivers are much higher than single frequency support GPS receiver. In this research, single frequency GPS receiver was used instead of expensive multi-frequency GNSS receivers to measure the ionospheric plasma variation such as vertical TEC distribution. In this measurement, single-frequency support ublox GPS receiver was used to probe ionospheric TEC. The location of observation was assigned at Mandalay Technological University in Myanmar. In the method, the ionospheric TEC distribution is represented by polynomial functions for latitude and longitude, and parameters of the functions are determined by least-squares fitting on pseudorange data obtained at a known location under an assumption of thin layer ionosphere. The validity of the method was evaluated by measurements obtained by the Japanese GNSS observation network called GEONET. The performance of measurement results using single-frequency of GPS receiver was compared with the results by dual-frequency measurement.

Keywords: ionosphere, global positioning system, GPS, ionospheric delay, total electron content, TEC

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Authors: Muhammad Faizan Rehman Qureshi, Ahmed Al-Kaisy

Abstract:

Accurate estimation of traffic loads is critical for pavement and bridge design, among other transportation applications. Given the disproportional impact of heavier axle loads on pavement and bridge structures, truck and heavy vehicle traffic is expected to be a major determinant of traffic load estimation. Further, heavy vehicle traffic is also a major input in transportation planning and economic studies. The traditional method for estimating heavy vehicle traffic primarily relies on AADT estimation using Monthly Day of the Week (MDOW) adjustment factors as well as the percent heavy vehicles observed using statewide data collection programs. The MDOW factors are developed using daily and seasonal (or monthly) variation patterns for total traffic, consisting predominantly of passenger cars and other smaller vehicles. Therefore, while using these factors may yield reasonable estimates for total traffic (AADT), such estimates may involve a great deal of approximation when applied to heavy vehicle traffic. This research aims at assessing the approximation involved in estimating heavy vehicle traffic using MDOW adjustment factors for total traffic (conventional approach) along with three other methods of using MDOW adjustment factors for total trucks (class 5-13), combination-unit trucks (class 8-13), as well as adjustment factors for each vehicle class separately. Results clearly indicate that the conventional method was outperformed by the other three methods by a large margin. Further, using the most detailed and data intensive method (class-specific adjustment factors) does not necessarily yield a more accurate estimation of heavy vehicle traffic.

Keywords: traffic loads, heavy vehicles, truck traffic, adjustment factors, traffic data collection

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Authors: Pui I. Chao, Shanju Lin

Abstract:

Purpose: Children with developmental language disorder (DLD) have persistent language difficulties and often face great challenges when demands are high. The aim of this study was to investigate whether verb frequency would trade-off with syntactic complexity when they talk. Method: Forty-five children with DLD, 45 chronological age matches with TD (AGE), and 45 MLU-matches with TD (MLU) who were Mandarin speakers were selected from the previous study. Language samples were collected under three contexts: conversation about children’s family and school, story retelling, and free play. MLU, verb density, utterance length difference, verb density difference, and average verb frequency were calculated and further analyzed by ANOVAs. Results: Children with DLD and their MLU matches produced shorter utterances and used fewer verbs in expressions than the AGE matches. Compared to their AGE matches, the DLD group used more verbs and verbs with lower frequency in shorter utterances but used fewer verbs and verbs with higher frequency in longer utterances. Conclusion: Mandarin-speaking children with DLD showed difficulties in verb usage and were more vulnerable to trade-offs than their age-matched peers in utterances with high demand. As a result, task demand should be taken into account as speech-language pathologists assess whether children with DLD have adequate abilities in verb usage.

Keywords: developmental language disorder, syntactic complexity, trade-offs, verb frequency

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Authors: Celina Pestano-Gabino, Concepcion Gonzalez-Concepcion, M. Candelaria Gil-Fariña

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Some estimation methods for VARMA models, and Multivariate Time Series Models in general, rely on the use of a Hankel matrix. It is known that if the data sample is populous enough and the dimension of the Hankel matrix is unnecessarily large, this may result in an unnecessary number of computations as well as in numerical problems. In this sense, the aim of this paper is two-fold. First, we provide some theoretical results for these matrices which translate into a lower dimension for the matrices normally used in the algorithms. This contribution thus serves to improve those methods from a numerical and, presumably, statistical point of view. Second, we have chosen an estimation algorithm to illustrate in practice our improvements. The results we obtained in a simulation of VARMA models show that an increase in the size of the Hankel matrix beyond the theoretical bound proposed as valid does not necessarily lead to improved practical results. Therefore, for future research, we propose conducting similar studies using any of the linear system estimation methods that depend on Hankel matrices.

Keywords: covariances Hankel matrices, Kronecker indices, system identification, VARMA models

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Authors: Alexander N. Pisarchik, Parth Chholak

Abstract:

Intrinsic brain noise was estimated via magneto-encephalograms (MEG) recorded during perception of flickering visual stimuli with frequencies of 6.67 and 8.57 Hz. First, we measured the mean phase difference between the flicker signal and steady-state event-related field (SSERF) in the occipital area where the brain response at the flicker frequencies and their harmonics appeared in the power spectrum. Then, we calculated the probability distribution of the phase fluctuations in the regions of frequency locking and computed its kurtosis. Since kurtosis is a measure of the distribution’s sharpness, we suppose that inverse kurtosis is related to intrinsic brain noise. In our experiments, the kurtosis value varied among subjects from K = 3 to K = 5 for 6.67 Hz and from 2.6 to 4 for 8.57 Hz. The majority of subjects demonstrated leptokurtic kurtosis (K < 3), i.e., the distribution tails approached zero more slowly than Gaussian. In addition, we found a strong correlation between kurtosis and brain complexity measured as the correlation dimension, so that the MEGs of subjects with higher kurtosis exhibited lower complexity. The obtained results are discussed in the framework of nonlinear dynamics and complex network theories. Specifically, in a network of coupled oscillators, phase synchronization is mainly determined by two antagonistic factors, noise, and the coupling strength. While noise worsens phase synchronization, the coupling improves it. If we assume that each neuron and each synapse contribute to brain noise, the larger neuronal network should have stronger noise, and therefore phase synchronization should be worse, that results in smaller kurtosis. The described method for brain noise estimation can be useful for diagnostics of some brain pathologies associated with abnormal brain noise.

Keywords: brain, flickering, magnetoencephalography, MEG, visual perception, perception time

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Authors: Bülent Kantar, Numan Ünaldı

Abstract:

This paper presents a new method which includes robust and invisible digital watermarking on images that is colored. Colored images are used as watermark. Frequency region is used for digital watermarking. Discrete wavelet transform and discrete stationary wavelet transform are used for frequency region transformation. Low, medium and high frequency coefficients are obtained by applying the two-level discrete wavelet transform to the original image. Low frequency coefficients are obtained by applying one level discrete stationary wavelet transform separately to all frequency coefficient of the two-level discrete wavelet transformation of the original image. For every low frequency coefficient obtained from one level discrete stationary wavelet transformation, watermarks are added. Watermarks are added to all frequency coefficients of two-level discrete wavelet transform. Totally, four watermarks are added to original image. In order to get back the watermark, the original and watermarked images are applied with two-level discrete wavelet transform and one level discrete stationary wavelet transform. The watermark is obtained from difference of the discrete stationary wavelet transform of the low frequency coefficients. A total of four watermarks are obtained from all frequency of two-level discrete wavelet transform. Obtained watermark results are compared with real watermark results, and a similarity result is obtained. A watermark is obtained from the highest similarity values. Proposed methods of watermarking are tested against attacks of the geometric and image processing. The results show that proposed watermarking method is robust and invisible. All features of frequencies of two level discrete wavelet transform watermarking are combined to get back the watermark from the watermarked image. Watermarks have been added to the image by converting the binary image. These operations provide us with better results in getting back the watermark from watermarked image by attacking of the geometric and image processing.

Keywords: watermarking, DWT, DSWT, copy right protection, RGB

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Authors: M. Emami, R. Tarighi, R. Goodarzi

Abstract:

Maximal radar wave absorbing cannot be achieved by shaping alone. We have to focus on the parameters of absorbing materials such as permittivity, permeability, and thickness so that best absorbing according to our necessity can happen. The real and imaginary parts of the relative complex permittivity (ε_r' and ε_r") and permeability (µ_r' and µ_r") were obtained by simulation. The microwave absorbing property of carbon and Ni(C) is simulated in this study by MATLAB software; the simulation was in the frequency range between 2 to 12 GHz for carbon black (C), and carbon coated nickel (Ni(C)) with different thicknesses. In fact, we draw reflection loss (RL) for C and Ni-C via frequency. We have compared their absorption for 3-mm thickness and predicted for other thicknesses by using of electromagnetic wave transmission theory. The results showed that reflection loss position changes in low frequency with increasing of thickness. We found out that, in all cases, using nanocomposites as absorbance cannot get better results relative to pure nanoparticles. The frequency where absorption is maximum can determine the best choice between nanocomposites and pure nanoparticles. Also, we could find an optimal thickness for long wavelength absorbing in order to utilize them in protecting shields and covering.

Keywords: absorbing, carbon, carbon nickel, frequency, thicknesses

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Authors: Shogo Nagano, Yusuke Tanigaki, Hirokazu Fukuda

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Vegetables harvested early in the morning or late in the afternoon are valued in plant production, and so the time of harvest is important. The biological functions known as circadian clocks have a significant effect on this harvest timing. The purpose of this study was to non-destructively estimate the circadian clock and so construct a method for determining a suitable harvest time. We took eight samples of green busil (Perilla frutescens var. crispa) every 4 hours, six times for 1 day and analyzed all samples at the same time. A hyperspectral camera was used to collect spectrum intensities at 141 different wavelengths (350–1050 nm). Calculation of correlations between spectrum intensity of each wavelength and harvest time suggested the suitability of the hyperspectral camera for non-destructive estimation. However, even the highest correlated wavelength had a weak correlation, so we used machine learning to raise the accuracy of estimation and constructed a machine learning model to estimate the internal time of the circadian clock. Artificial neural networks (ANN) were used for machine learning because this is an effective analysis method for large amounts of data. Using the estimation model resulted in an error between estimated and real times of 3 min. The estimations were made in less than 2 hours. Thus, we successfully demonstrated this method of non-destructively estimating internal time.

Keywords: artificial neural network (ANN), circadian clock, green busil, hyperspectral camera, non-destructive evaluation

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Authors: Daniel Fundi Murithi

Abstract:

Data from economic, social, clinical, and industrial studies are in some way incomplete or incorrect due to censoring. Such data may have adverse effects if used in the estimation problem. We propose the use of Maximum Likelihood Estimation (MLE) under a progressive type-II censoring scheme to remedy this problem. In particular, maximum likelihood estimates (MLEs) for the location (µ) and scale (λ) parameters of two Parameter Rayleigh distribution are realized under a progressive type-II censoring scheme using the Expectation-Maximization (EM) and the Newton-Raphson (NR) algorithms. These algorithms are used comparatively because they iteratively produce satisfactory results in the estimation problem. The progressively type-II censoring scheme is used because it allows the removal of test units before the termination of the experiment. Approximate asymptotic variances and confidence intervals for the location and scale parameters are derived/constructed. The efficiency of EM and the NR algorithms is compared given root mean squared error (RMSE), bias, and the coverage rate. The simulation study showed that in most sets of simulation cases, the estimates obtained using the Expectation-maximization algorithm had small biases, small variances, narrower/small confidence intervals width, and small root of mean squared error compared to those generated via the Newton-Raphson (NR) algorithm. Further, the analysis of a real-life data set (data from simple experimental trials) showed that the Expectation-Maximization (EM) algorithm performs better compared to Newton-Raphson (NR) algorithm in all simulation cases under the progressive type-II censoring scheme.

Keywords: expectation-maximization algorithm, maximum likelihood estimation, Newton-Raphson method, two-parameter Rayleigh distribution, progressive type-II censoring

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Authors: Ranjitkumar Patil

Abstract:

Age estimation has importance in forensic dentistry. Dental age estimation has emerged as an alternative to skeletal age determination. The methods based on stages of tooth formation, as appreciated on radiographs, seem to be more appropriate in the assessment of age than those based on skeletal development. The study was done to evaluate dental age in the north Indian population using Cameriere’s method. Aims/Objectives: The study was conducted to assess the dental age of North Indian children using Cameriere’s method and to compare the chronological age and dental age for validation of the Cameriere’s method in the north Indian population. A comparative study of 02-year duration on the OPG (using PLANMECA Promax 3D) data of 497 individuals with ages ranging from 5 to 15 years was done based on simple random technique ethical approval obtained from institutional ethical committee. The data was obtained based on inclusion and exclusion criteria and was analyzed by software for dental age estimation. Statistical analysis: The student’s t-test was used to compare the morphological variables of males with those of females and to compare observed age with estimated age. The regression formula was also calculated. Results: Present study was a comparative study of 497 subjects with a distribution between males and females, with their dental age assessed by using a Panoramic radiograph, following the method described by Cameriere, which is widely accepted. Statistical analysis in our study indicated that gender does not have a significant influence on age estimation. (R2= 0.787). Conclusion: This infers that Cameriere’s method can be effectively applied to the north Indian population.

Keywords: forensic, dental age, skeletal age, chronological age, Cameriere’s method

Procedia PDF Downloads 116

Authors: Fatima Zahra Moussa, Yamina Belhadef, Souheyla Ferouani

Abstract:

In this work, we present a new form of miniature circular patch antenna based on CSRR metamaterials with an extended bandwidth proposed for 5 GHz Wi-Fiapplications. A reflection coefficient of -35 dB and a radiation pattern of 7.47 dB are obtained when simulating the initial proposed antenna with the CST microwave studio simulation software. The notch insertion technique in the radiating element was used for matching the antenna to the desired frequency in the frequency band [5150-5875] MHz.An extension of the bandwidth from 332 MHz to 1423 MHz was done by the DGS (defected ground structure) technique to meet the user's requirement in the 5 GHz Wi-Fi frequency band.

Keywords: patch antenna, miniaturisation, CSRR, notches, wifi, DGS

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Authors: M. Y. Ismail, M. Inam

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This paper presents the design and analysis of Liquid Crystal (LC) based tunable reflect array antenna with different design configurations within X-band frequency range. The effect of LC volume used for unit cell element on frequency tunability and reflection loss performance has been investigated. Moreover different slot embedded patch element configurations have been proposed for LC based tunable reflect array antenna design with enhanced performance. The detailed fabrication and measurement procedure for different LC based unit cells has been presented. The waveguide scattering parameter measured results demonstrated that by using the circular slot embedded patch elements, the frequency tunability and dynamic phase range can be increased from 180 MHz to 200 MHz and 120° to 124° respectively. Furthermore the circular slot embedded patch element can be designed at 10 GHz resonant frequency with a patch volume of 2.71 mm3 as compared to 3.47 mm3 required for rectangular patch without slot.

Keywords: liquid crystal, tunable reflect array, frequency tunability, dynamic phase range

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

Abstract:

The seismic responses-based structural health monitoring system has been performed to reduce seismic damage. The inter-story drift ratio which is the major index of the seismic capacity assessment is employed for estimating the seismic damage of buildings. Meanwhile, seismic response analysis to estimate the structural responses of building demands significantly high computational cost due to increasing number of high-rise and large buildings. To estimate the inter-story drift ratio of buildings from the earthquake efficiently, this paper suggests the estimation method of inter-story drift for buildings using an artificial neural network (ANN). In the method, the radial basis function neural network (RBFNN) is integrated with optimization algorithm to optimize the variable through evolutionary learning that refers to evolutionary radial basis function neural network (ERBFNN). The estimation method estimates the inter-story drift without seismic response analysis when the new earthquakes are subjected to buildings. The effectiveness of the estimation method is verified through a simulation using multi-degree of freedom system.

Keywords: structural health monitoring, inter-story drift ratio, artificial neural network, radial basis function neural network, genetic algorithm

Procedia PDF Downloads 327

Authors: Murad Almadani, Khalil Abu-Hantash, Xinyu Wang, Herbert Jelinek, Kinda Khalaf

Abstract:

Gait analysis is used by healthcare professionals as a tool to gain a better understanding of the movement impairment and track progress. In most circumstances, monitoring patients in their real-life environments with low-cost equipment such as cameras and wearable sensors is more important. Inertial sensors, on the other hand, cannot provide enough information on angular dynamics. This research offers a method for tracking 2D joint coordinates using cutting-edge vision algorithms and a single RGB camera. We provide an end-to-end comprehensive deep learning pipeline for marker-less gait parameter estimation, which, to our knowledge, has never been done before. To make our pipeline function in real-time for real-world applications, we leverage the AlphaPose human posture prediction model and a deep learning transformer. We tested our approach on the well-known GPJATK dataset, which produces promising results.

Keywords: gait analysis, human pose estimation, deep learning, real time gait estimation, AlphaPose, transformer

Procedia PDF Downloads 118

Authors: G. Levacic, A. Zupan

Abstract:

Application of new technological solutions and installation of new elements into the network requires special attention when investigating its interaction with the existing power system. Special attention needs to be devoted to the occurrence of harmonic resonance. Sources of increasing harmonic penetration could be wind power plants, Flexible Alternating Current Transmission System (FACTS) devices, underground and submarine cable installations etc. Calculation in frequency domain with various software, for example, the software for power systems transients EMTP-RV presents one of the most common ways to obtain the harmonic impedance of the system. Along calculations in frequency domain, such software allows performing of different type of calculations as well as steady-state domain. This paper describes a power system modeling with software EMTP-RV based on data from SCADA/EMS system. The power flow results on 220 kV and 400 kV voltage levels retrieved from EMTP-RV are verified by comparing with power flow results from power transmissions system planning software PSS/E. The determination of the harmonic impedance for the case of remote power plant connection with cable up to 2500 Hz is presented as an example of calculations in frequency domain.

Keywords: power system modeling, frequency domain, steady state, EMTP-RV, PSS/E

Procedia PDF Downloads 323

Authors: D. Sankara Reddy, T. Kranthi Kumar, K. Sreevani

Abstract:

This paper investigates the impact of carrier frequency offset (CFO) on the performance of different MIMO-OFDM schemes with high spectral efficiency for next generation of terrestrial digital TV. We show that all studied MIMO-OFDM schemes are sensitive to CFO when it is greater than 1% of intercarrier spacing. We show also that the Alamouti scheme is the most sensitive MIMO scheme to CFO.

Keywords: modulation and multiplexing (MIMO-OFDM), signal processing for transmission carrier frequency offset, future digital TV, imaging and signal processing

Procedia PDF Downloads 487

Authors: B. S. Harish, M. B. Revanasiddappa

Abstract:

Due to rapid growth of text documents in digital form, automated text classification has become an important research in the last two decades. The major challenge of text document representations are high dimension, sparsity, volume and semantics. Since the terms are only features that can be found in documents, selection of good terms (features) plays an very important role. In text classification, feature selection is a strategy that can be used to improve classification effectiveness, computational efficiency and accuracy. In this paper, we present a quantitative analysis of most widely used feature selection (FS) methods, viz. Term Frequency-Inverse Document Frequency (tf
idf ), Mutual Information (MI), Information Gain (IG), CHISquare (x2), Term Frequency-Relevance Frequency (tf
rf ), Term Strength (TS), Ambiguity Measure (AM) and Symbolic Feature Selection (SFS) to classify text documents. We evaluated all the feature selection methods on standard datasets like 20 Newsgroups, 4 University dataset and Reuters-21578.

Keywords: classifiers, feature selection, text classification

Procedia PDF Downloads 461

Authors: Jaehyung Jung, Kiman Kim, Heesang Eum

Abstract:

Solar cell is one of the main technologies to reduce greenhouse gas (GHG). Thereby, accurate estimation of greenhouse gas reduction by solar cell technology is crucial to consider strategic applications of the solar cell. The bottom-up approach using operating data such as operation time and efficiency is one of the methodologies to improve the accuracy of the estimation. In this study, alternative GHG reductions from solar cell technology were estimated by a bottom-up approach to indirect emission source (scope 2) in Korea, 2015. In addition, the scenario-based analysis was conducted to assess the effect of technological change with respect to efficiency improvement and rate of operation. In order to estimate GHG reductions from solar cell activities in operating condition levels, methodologies were derived from 2006 IPCC guidelines for national greenhouse gas inventories and guidelines for local government greenhouse inventories published in Korea, 2016. Indirect emission factors for electricity were obtained from Korea Power Exchange (KPX) in 2011. As a result, the annual alternative GHG reductions were estimated as 21,504 tonCO2eq, and the annual average value was 1,536 tonCO2eq per each solar cell technology. Those results of estimation showed to be 91% levels versus design of capacity. Estimation of individual greenhouse gases (GHGs) showed that the largest gas was carbon dioxide (CO2), of which up to 99% of the total individual greenhouse gases. The annual average GHG reductions from solar cell per year and unit installed capacity (MW) were estimated as 556 tonCO2eq/yr•MW. Scenario analysis of efficiency improvement by 5%, 10%, 15% increased as much as approximately 30, 61, 91%, respectively, and rate of operation as 100% increased 4% of the annual GHG reductions.

Keywords: bottom-up approach, greenhouse gas (GHG), reduction, scenario, solar cell

Procedia PDF Downloads 221