Search results for: intensity estimation

Authors: A. Bekbaev, M. Dzhamanbaev, R. Abitaeva, A. Karbozova, G. Nabyeva

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In this paper, the regression dependence of dancing intensity from wind speed and length of span was established due to the statistic data obtained from multi-year observations on line wires dancing accumulated by power systems of Kazakhstan and the Russian Federation. The lower and upper limitations of the equations parameters were estimated, as well as the adequacy of the regression model. The constructed model will be used in research of dancing phenomena for the development of methods and means of protection against dancing and for zoning plan of the territories of line wire dancing.

Keywords: power lines, line wire dancing, dancing intensity, regression equation, dancing area intensity

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Authors: Vladimir S. Timofeev

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In this article the problem of distributional moments estimation is considered. The new approach of moments estimation based on usage of the characteristic function is proposed. By statistical simulation technique, author shows that new approach has some robust properties. For calculation of the derivatives of characteristic function there is used numerical differentiation. Obtained results confirmed that author’s idea has a certain working efficiency and it can be recommended for any statistical applications.

Keywords: characteristic function, distributional moments, robustness, outlier, statistical estimation problem, statistical simulation

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Authors: Naod Mekonnen Anega

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The very objective of this paper was to empirically identify technology tailored determinants to the adoption and adoption intensity (extent of use) of agricultural water management technologies in Meda Welabu Woreda, Oromia regional state, Ethiopia. Meda Welabu Woreda which is one of the administrative Woredas of the Oromia regional state was selected purposively as this Woreda is one of the Woredas in the region where small scale irrigation practices and the use of agricultural water management technologies can be found among smallholders. Using the existence water management practices (use of water management technologies) and land use pattern as a criterion Genale Mekchira Kebele is selected to undergo the study. A total of 200 smallholders were selected from the Kebele using the technique developed by Krejeie and Morgan. The study employed the Logit and Tobit models to estimate and identify the economic, social, geographical, household, institutional, psychological, technological factors that determine adoption and adoption intensity of water management technologies. The study revealed that while 55 of the sampled households are adopters of agricultural water management technology the rest 140 were non adopters of the technologies. Among the adopters included in the sample 97% are using river diversion technology (traditional) with traditional canal while the rest 7% percent are using pond with treadle pump technology. The Logit estimation reveled that while adoption of river diversion is positively and significantly affected by membership to local institutions, active labor force, income, access to credit and land ownership, adoption of treadle pump technology is positively and significantly affected by family size, education level, access to credit, extension contact, income, access to market, and slope. The Logit estimation also revealed that whereas, group action requirement, distance to farm, and size of active labor force negative and significantly influenced adoption of river diversion, age and perception has negatively and significantly influenced adoption decision of treadle pump technology. On the other hand, the Tobit estimation reveled that while adoption intensity (extent of use) of agricultural water management is positively and significantly affected by education, credit, and extension contact, access to credit, access to market and income. This study revealed that technology tailored study on adoption of Agricultural water management technologies (AWMTs) should be considered to indentify and scale up best agricultural water management practices. In fact, in countries like Ethiopia, where there is difference in social, economic, cultural, environmental and agro ecological conditions even within the same Kebele technology tailored study that fit the condition of each Kebele would help to identify and scale up best practices in agricultural water management.

Keywords: water management technology, adoption, adoption intensity, smallholders, technology tailored approach

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Authors: Wael M. Bazzi, Amir Rastegarnia, Azam Khalili

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In this paper we consider the issue of reliability of measurements in distributed adaptive estimation problem. To this aim, we assume a sensor network with different observation noise variance among the sensors and propose new estimation method based on incremental distributed least mean-square (IDLMS) algorithm. The proposed method contains two phases: I) Estimation of each sensors observation noise variance, and II) Estimation of the desired parameter using the estimated observation variances. To deal with the reliability of measurements, in the second phase of the proposed algorithm, the step-size parameter is adjusted for each sensor according to its observation noise variance. As our simulation results show, the proposed algorithm considerably improves the performance of the IDLMS algorithm in the same condition.

Keywords: adaptive filter, distributed estimation, sensor network, IDLMS algorithm

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Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte, V. Grincas

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This paper deals with advanced state estimation algorithms for estimation of biomass concentration and specific growth rate in a typical fed-batch biotechnological process. This biotechnological process was represented by a nonlinear mass-balance based process model. Extended Kalman Filter (EKF) and Particle Filter (PF) was used to estimate the unmeasured state variables from oxygen uptake rate (OUR) and base consumption (BC) measurements. To obtain more general results, a simplified process model was involved in EKF and PF estimation algorithms. This model doesn’t require any special growth kinetic equations and could be applied for state estimation in various bioprocesses. The focus of this investigation was concentrated on the comparison of the estimation quality of the EKF and PF estimators by applying different measurement noises. The simulation results show that Particle Filter algorithm requires significantly more computation time for state estimation but gives lower estimation errors both for biomass concentration and specific growth rate. Also the tuning procedure for Particle Filter is simpler than for EKF. Consequently, Particle Filter should be preferred in real applications, especially for monitoring of industrial bioprocesses where the simplified implementation procedures are always desirable.

Keywords: biomass concentration, extended Kalman filter, particle filter, state estimation, specific growth rate

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Authors: M. R. Al-Rashidi, K. M. El-Naggar, M. F. Al-Hajri

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The fuel cost function describes the electric power generation-cost relationship in thermal plants, hence, it sheds light on economical aspects of power industry. Different models have been proposed to describe this relationship with the quadratic function model being the most popular one. Parameters of second order fuel cost function are estimated in this paper using cuckoo search algorithm. It is a new population based meta-heuristic optimization technique that has been used in this study primarily as an accurate estimation tool. Its main features are flexibility, simplicity, and effectiveness when compared to other estimation techniques. The parameter estimation problem is formulated as an optimization one with the goal being minimizing the error associated with the estimated parameters. A case study is considered in this paper to illustrate cuckoo search promising potential as a valuable estimation and optimization technique.

Keywords: cuckoo search, parameters estimation, fuel cost function, economic dispatch

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Authors: Keunhong Chae, Seokho Yoon

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This paper proposes frequency offset (FO) estimation schemes robust to the non-Gaussian noise for orthogonal frequency division multiplexing (OFDM) systems. A maximum-likelihood (ML) scheme and a low-complexity estimation scheme are proposed by applying the probability density function of the cyclic prefix of OFDM symbols to the ML criterion. From simulation results, it is confirmed that the proposed schemes offer a significant FO estimation performance improvement over the conventional estimation scheme in non-Gaussian noise environments.

Keywords: frequency offset, cyclic prefix, maximum-likelihood, non-Gaussian noise, OFDM

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Authors: S. Ilakkiya, A. Merline

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A multiple-input multiple-output (MIMO) radar systems use modulated waveforms and directive antennas to transmit electromagnetic energy into a specific volume in space to search for targets. This paper deals with the design of transmit beamspace matrix and DOA estimation for multiple-input multiple-output (MIMO) radar with collocated antennas.The design of transmit beamspace matrix is based on minimizing the difference between a desired transmit beampattern and the actual one while enforcing the constraint of uniform power distribution across the transmit array elements. Rotational invariance property is established at the transmit array by imposing a specific structure on the beamspace matrix. Semidefinite programming and spatial-division based design (SDD) are also designed separately. In MIMO radar systems, DOA estimation is an essential process to determine the direction of incoming signals and thus to direct the beam of the antenna array towards the estimated direction. This estimation deals with non-adaptive spectral estimation and adaptive spectral estimation techniques. The design of the transmit beamspace matrix and spectral estimation techniques are studied through simulation.

Keywords: adaptive and non-adaptive spectral estimation, direction of arrival estimation, MIMO radar, rotational invariance property, transmit, receive beamforming

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Authors: Olesya Bolkhovskaya, Alexey Davydov, Alexander Maltsev

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In this paper two approaches to joint signal detection, time of arrival (ToA) and angle of arrival (AoA) estimation in multi-element antenna array are investigated. Two scenarios were considered: first one, when the waveform of the useful signal is known a priori and, second one, when the waveform of the desired signal is unknown. For first scenario, the antenna array signal processing based on multi-element matched filtering (MF) with the following non-coherent detection scheme and maximum likelihood (ML) parameter estimation blocks is exploited. For second scenario, the signal processing based on the antenna array elements covariance matrix estimation with the following eigenvector analysis and ML parameter estimation blocks is applied. The performance characteristics of both signal processing schemes are thoroughly investigated and compared for different useful signals and noise parameters.

Keywords: antenna array, signal detection, ToA, AoA estimation

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Authors: Keunhong Chae, Seokho Yoon

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We address a new integer frequency offset (IFO) estimation scheme with an aid of a pilot for orthogonal frequency division multiplexing systems. After correlating each continual pilot with a predetermined scattered pilot, the correlation value is again correlated to alleviate the influence of the timing offset. From numerical results, it is demonstrated that the influence of the timing offset on the IFO estimation is significantly decreased.

Keywords: estimation, integer frequency offset, OFDM, timing offset

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Authors: Yoshimoto Kurihara, Tad Gonsalves

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Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: 6D posture estimation, image recognition, deep learning, AlexNet

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Authors: Miljan B. Petrović, Dušan B. Petrović, Goran S. Nikolić

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This paper describes a method for AWGN (Additive White Gaussian Noise) variance estimation in noisy stochastic signals, referred to as Multiplicative-Noising Variance Estimation (MNVE). The aim was to develop an estimation algorithm with minimal number of assumptions on the original signal structure. The provided MATLAB simulation and results analysis of the method applied on speech signals showed more accuracy than standardized AR (autoregressive) modeling noise estimation technique. In addition, great performance was observed on very low signal-to-noise ratios, which in general represents the worst case scenario for signal denoising methods. High execution time appears to be the only disadvantage of MNVE. After close examination of all the observed features of the proposed algorithm, it was concluded it is worth of exploring and that with some further adjustments and improvements can be enviably powerful.

Keywords: noise, signal-to-noise ratio, stochastic signals, variance estimation

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Authors: Takhchi Jamal, Ouisse Morvan, Sadoulet-Reboul Emeline, Bouhaddi Noureddine, Gagliardini Laurent, Bornet Frederic, Lakrad Faouzi

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Structural intensity is a technique that can be used to indicate both the magnitude and direction of power flow through a structure from the excitation source to the dissipation sink. However, current analysis is limited to the low frequency range. At medium and high frequencies, a rotational component appear in the field, masking the energy flow and make its understanding difficult or impossible. The objective of this work is to implement a methodology to filter out the rotational components of the structural intensity field in order to fully understand the energy flow in complex structures. The approach is based on the Helmholtz decomposition. It allows to decompose the structural intensity field into rotational, irrotational, and harmonic components. Only the irrotational component is needed to describe the net power flow from a source to a dissipative zone in the structure. The methodology has been applied on academic structures, and it allows a good analysis of the energy transfer paths.

Keywords: structural intensity, power flow, helmholt decomposition, irrotational intensity

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Authors: Kaushal Kishore

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Immense amount of imported fuels are used in Fiji for electricity generation, transportation and for carrying out miscellaneous household work. To alleviate its dependency on fossil fuel, paramount importance has been given to instigate the utilization of renewable energy sources for power generation and to reduce the environmental dilapidation. Amongst the many renewable energy sources, wind has been considered as one of the best identified renewable sources that are comprehensively available in Fiji. In this study the wind resource assessment for three locations in Rakiraki, Fiji has been carried out. The wind resource estimation at Rokavukavu, Navolau and at Tuvavatu has been analyzed. The average wind speed at 55 m above ground level (a.g.l) at Rokavukavu, Navolau, and Tuvavatu sites are 5.91 m/s, 8.94 m/s and 8.13 m/s with the turbulence intensity of 14.9%, 17.1%, and 11.7% respectively. The moment fitting method has been used to estimate the Weibull parameter and the power density at each sites. A high resolution wind resource map for the three locations has been developed by using Wind Atlas Analysis and Application Program (WAsP). The results obtained from WAsP exhibited good wind potential at Navolau and Tuvavatu sites. A wind farm has been proposed at Navolau and Tuvavatu site that comprises six Vergnet 275 kW wind turbines at each site. The annual energy production (AEP) for each wind farm is estimated and an economic analysis is performed. The economic analysis for the proposed wind farms at Navolau and Tuvavatu sites showed a payback period of 5 and 6 years respectively.

Keywords: annual energy production, Rakiraki Fiji, turbulence intensity, Weibull parameter, wind speed, Wind Atlas Analysis and Application Program

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Authors: F. Benhamida, A. Graa, L. Benameur, I. Ziane

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The state estimation of the electrical power system operation state is very important for supervising task. With the nonlinearity of the AC power flow model, the state estimation problem (SEP) is a nonlinear mathematical problem with many local optima. This paper treat the mathematical model for the SEP and the monitoring of the nonlinear systems of great dimensions with an application on power electrical system, the modelling, the analysis and state estimation synthesis in order to supervise the power system behavior. in fact, it is very difficult, to see impossible, (for reasons of accessibility, techniques and/or of cost) to measure the excessive number of the variables of state in a large-sized system. It is thus important to develop software sensors being able to produce a reliable estimate of the variables necessary for the diagnosis and also for the control.

Keywords: power system, state estimation, robustness, observability

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Authors: R. M. Chandler, A. J. Stringer

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In adults, short bursts of high-intensity exercise (intensities between 80-95% of maximum heart rates) increase cardiovascular and metabolic function without the time investment of traditional aerobic training. Similar improvements in various health indices are also becoming increasingly evident in children in countries other than the United States. In the United States, physical education programs have become shorter in length and fewer in frequency. With this in the background, it is imperative that health and physical educators delivered well-organized and focused fitness programs that can be tolerated across many different somatotypes. Perhaps the least effective lag-time in a US physical education (PE) class is the first 10 minutes, a time during which children warm up. Replacing a traditional PE warmup with a 10 min high-intensity excise protocol is a time-efficient method to impact health, leaving as much time for other PE material such as skill development, motor behavior development as possible. This supplemented 10 min high-intensity exercise increases cardiovascular function as well as induces favorable body composition changes in as little as six weeks with further enhancement throughout a semester of activity. The supplemental high-intensity exercise did not detract from the PE lesson outcomes.

Keywords: cardiovascular fitness, high intensity interval training, high intensity exercise, pediatric

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Authors: F. H. Abanda, B. Kamsu-Foguem, J. H. M. Tah

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Construction cost estimation is one of the most important aspects of construction project design. For generations, the process of cost estimating has been manual, time-consuming and error-prone. This has partly led to most cost estimates to be unclear and riddled with inaccuracies that at times lead to over- or under-estimation of construction cost. The development of standard set of measurement rules that are understandable by all those involved in a construction project, have not totally solved the challenges. Emerging Building Information Modelling (BIM) technologies can exploit standard measurement methods to automate cost estimation process and improves accuracies. This requires standard measurement methods to be structured in ontologically and machine readable format; so that BIM software packages can easily read them. Most standard measurement methods are still text-based in textbooks and require manual editing into tables or Spreadsheet during cost estimation. The aim of this study is to explore the development of an ontology based on New Rules of Measurement (NRM) commonly used in the UK for cost estimation. The methodology adopted is Methontology, one of the most widely used ontology engineering methodologies. The challenges in this exploratory study are also reported and recommendations for future studies proposed.

Keywords: BIM, construction projects, cost estimation, NRM, ontology

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Authors: Mojtaba Saeedinezhad, Sarah Yousefi

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In this paper, we present a hybrid subspace approach for Time Delay Estimation (TDE) in multivariable systems. While several methods have been proposed for time delay estimation in SISO systems, delay estimation in MIMO systems were always a big challenge. In these systems the existing TDE methods have significant limitations because most of procedures are just based on system response estimation or correlation analysis. We introduce a new hybrid method for TDE in MIMO systems based on subspace identification and explicit output error method; and compare its performance with previously introduced procedures in presence of different noise levels and in a statistical manner. Then the best method is selected with multi objective decision making technique. It is shown that the performance of new approach is much better than the existing methods, even in low signal-to-noise conditions.

Keywords: system identification, time delay estimation, ARX, OE, merit ratio, multi variable decision making

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Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

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Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square

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Authors: Bader Alkandari, Jamal Y. Madouh, Ahmad M. Alkandari, Anwar A. Alnaqi

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A new formulation of fuzzy linear estimation problem is presented. It is formulated as a linear programming problem. The objective is to minimize the spread of the data points, taking into consideration the type of the membership function of the fuzzy parameters to satisfy the constraints on each measurement point and to insure that the original membership is included in the estimated membership. Different models are developed for a fuzzy triangular membership. The proposed models are applied to different examples from the area of fuzzy linear regression and finally to different examples for estimating the electrical load on a busbar. It had been found that the proposed technique is more suited for electrical load estimation, since the nature of the load is characterized by the uncertainty and vagueness.

Keywords: fuzzy regression, load estimation, fuzzy linear parameters, electrical load estimation

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Authors: Andrey V. Timofeev, Dmitry V. Egorov

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The practical efficient approach is suggested for estimation of the seismoacoustic sources energy in C-OTDR monitoring systems. This approach represents the sequential plan for confidence estimation both the seismoacoustic sources energy, as well the absorption coefficient of the soil. The sequential plan delivers the non-asymptotic guaranteed accuracy of obtained estimates in the form of non-asymptotic confidence regions with prescribed sizes. These confidence regions are valid for a finite sample size when the distributions of the observations are unknown. Thus, suggested estimates are non-asymptotic and nonparametric, and also these estimates guarantee the prescribed estimation accuracy in the form of the prior prescribed size of confidence regions, and prescribed confidence coefficient value.

Keywords: nonparametric estimation, sequential confidence estimation, multichannel monitoring systems, C-OTDR-system, non-lineary regression

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Authors: James Purnama, Riri Fitri Sari

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We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

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Authors: Pilar Cornejo Ulloa, Guy Willems, Steffen Fieuws, Kim Quintelier, Wim Van Neer, Patrick Thevissen

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Dental age estimation can be performed both in living and deceased individuals. In anthropology, few studies have tested the reliability of dental age estimation methods complementary to the usually applied osteological methods. Objectives: In this study, destructive and non-destructive dental age estimation methods were applied on an archeological sample in order to compare them with the previously obtained anthropological age estimates. Materials and Methods: One hundred and thirty-four teeth from 24 individuals were analyzed using Kvaal, Kvaal and Solheim, Bang and Ramm, Lamendin, Gustafson, Maples, Dalitz and Johanson’s methods. Results: A high variability and wider age ranges than the ones previously obtained by the anthropologist could be observed. Destructive methods had a slightly higher agreement than the non-destructive. Discussion: Due to the heterogeneity of the sample and the lack of the real age at death, the obtained results were not representative, and it was not possible to suggest one dental age estimation method over another.

Keywords: archeology, dental age estimation, forensic anthropology, forensic dentistry

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Authors: Wataru Nakamura, Tomoaki Hashimoto, Liang-Kuang Chen

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This paper provides a state estimation method for automatic control systems of nonlinear vehicle dynamics. A nonlinear tire model is employed to represent the realistic behavior of a vehicle. In general, all the state variables of control systems are not precisedly known, because those variables are observed through output sensors and limited parts of them might be only measurable. Hence, automatic control systems must incorporate some type of state estimation. It is needed to establish a state estimation method for nonlinear vehicle dynamics with restricted measurable state variables. For this purpose, unscented Kalman filter method is applied in this study for estimating the state variables of nonlinear vehicle dynamics. The objective of this paper is to propose a state estimation method using unscented Kalman filter for nonlinear vehicle dynamics. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: state estimation, control systems, observer systems, nonlinear systems

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Authors: Rashi Jain

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The LTE systems employ Orthogonal Frequency Division Multiplexing (OFDM) as the multiple access technology for the Downlink channels. For enhanced performance, accurate channel estimation is required. Various algorithms such as Least Squares (LS), Minimum Mean Square Error (MMSE) and Recursive Least Squares (RLS) can be employed for the purpose. The paper proposes channel estimation algorithm based on Kalman Filter for LTE-Downlink system. Using the frequency domain pilots, the initial channel response is obtained using the LS criterion. Then Kalman Filter is employed to track the channel variations in time-domain. To suppress the noise within a symbol, threshold processing is employed. The paper draws comparison between the LS, MMSE, RLS and Kalman filter for channel estimation. The parameters for evaluation are Bit Error Rate (BER), Mean Square Error (MSE) and run-time.

Keywords: LTE, channel estimation, OFDM, RLS, Kalman filter, threshold

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Authors: So-Young Ju, Sung-Mi Jo, Eui-Rim Jeong

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In this paper, based on the conventional single carrier frequency domain equalization (SC-FDE) structure, we propose a new SC-FDE structure to cope with narrowband jammer. In the conventional SC-FDE structure, channel estimation is performed in the time domain. When a narrowband jammer exists, time-domain channel estimation is very difficult due to high power jamming interference, which degrades receiver performance. To relieve from this problem, a new SC-FDE frame is proposed to enable channel estimation under narrow band jamming environments. In this paper, we proposed a modified SC-FDE structure that can perform channel estimation in the frequency domain and verified the performance via computer simulation.

Keywords: channel estimation, jammer, pilot, SC-FDE

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Authors: P. Praveen Kumar, P. Vimal Prabhu, Renu John

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In biology most microscopy specimens, in particular living cells are transparent. In cell imaging, it is hard to create an image of a cell which is transparent with a very small refractive index change with respect to the surrounding media. Various techniques like addition of staining and contrast agents, markers have been applied in the past for creating contrast. Many of the staining agents or markers are not applicable to live cell imaging as they are toxic. In this paper, we report theoretical and experimental results from quantitative phase imaging of yeast cells with a commercial bright field microscope. We reconstruct the phase of cells non-interferometrically based on the transport of intensity equations (TIE). This technique estimates the axial derivative from positive through-focus intensity measurements. This technique allows phase imaging using a regular microscope with white light illumination. We demonstrate nano-metric depth sensitivity in imaging live yeast cells using this technique. Experimental results will be shown in the paper demonstrating the capability of the technique in 3-D volume estimation of living cells. This real-time imaging technique would be highly promising in real-time digital pathology applications, screening of pathogens and staging of diseases like malaria as it does not need any pre-processing of samples.

Keywords: axial derivative, non-interferometric imaging, quantitative phase imaging, transport of intensity equation

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Authors: Hongkui Li, Tongli Lu , Jianwu Zhang

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This paper focuses on developing an estimation method of clutch drag torque in wet DCT. The modelling of clutch drag torque is investigated. As the main factor affecting the clutch drag torque, dynamic viscosity of oil is discussed. The paper proposes an estimation method of clutch drag torque based on recursive least squares by utilizing the dynamic equations of gear shifting synchronization process. The results demonstrate that the estimation method has good accuracy and efficiency.

Keywords: clutch drag torque, wet DCT, dynamic viscosity, recursive least squares

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Authors: Bouthiba Amina

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The estimation of the statistics bound to the precipitation represents a vast domain, which puts numerous challenges to meteorologists and hydrologists. Sometimes, it is necessary, to approach in value the extreme events for sites where there is little, or no datum, as well as their periods of return. The search for a model of the frequency of the heights of daily rains dresses a big importance in operational hydrology: It establishes a basis for predicting the frequency and intensity of floods by estimating the amount of precipitation in past years. The most known and the most common approach is the statistical approach, It consists in looking for a law of probability that fits best the values observed by the random variable " daily maximal rain " after a comparison of various laws of probability and methods of estimation by means of tests of adequacy. Therefore, a frequent analysis of the annual series of daily maximal rains was realized on the data of 54 pluviometric stations of the pond of high and average. This choice was concerned with five laws usually applied to the study and the analysis of frequent maximal daily rains. The chosen period is from 1970 to 2013. It was of use to the forecast of quantiles. The used laws are the law generalized by extremes to three components, those of the extreme values to two components (Gumbel and log-normal) in two parameters, the law Pearson typifies III and Log-Pearson III in three parameters. In Algeria, Gumbel's law has been used for a long time to estimate the quantiles of maximum flows. However, and we will check and choose the most reliable law.

Keywords: return period, extreme flow, statistics laws, Gumbel, estimation

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Authors: Caner Yilmaz, Zuhal Didem Takinaci

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Introduction: Today, our knowledge about the effects of physical activity performed at the different intensity of the cardiovascular system are still not clear. Therefore, to contribute to the literature, in our study, sedentary individuals and amateur athletes were assessed in a single session with the aim of evaluating the cardiovascular effects of the moderate and severe exercise. Methods: 80 participants (40 amateur athletes and 40 sedentary, young adults) participated in our study. Participants were divided into two groups: amateur athletes (mean age: 25.0 ± 3.6 yrs) and sedentary in group II (mean age: 23.8 ± 3.7 yrs). Participants in both groups were assessed twice, namely, firstly, at moderate intensity (5km/h 30 min. walking) and secondly at the vigorous intensity (8km/h 20 min. jogging). Participants’ SBP (Systolic Blood Pressure), DBP (Diastolic Blood Pressure), HR (Heart Rate), SpO₂ (Oxygen Saturation), BT (Body Temperature) and RR (Respiratory Rate) were measured. Results: In our study, the findings showed that after moderate-intensity aerobic exercise, change in SBP, DBP, and SpO₂ were significantly higher in Group II (p < 0.05). After the severe intensity aerobic exercises, change in SBP, SpO₂, HR, and RR was significantly higher in Group II (p < 0.05). The BORG score of Group II was significantly higher after both moderate and severe intensity aerobic exercise (p < 0.05). Conclusion: The cardiovascular responses of amateur athletes were closer to initial values, and the differences between the two groups were increased in direct proportion to the intensity of the exercise. Both exercise intensities could be adequate.

Keywords: aerobic, exercise, sedantary, cardi̇ovascular

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