Search results for: Parameter estimation.

Authors: Chisato Murakami, Makoto Takahashi

Abstract:

Force sensor has been used as requisite for knowing information on the amount and the directions of forces on the skin surface. We have developed a four-degrees-of-freedom capacitive force sensor (approximately 20×20×5 mm³) that has a flexible structure and sixteen parallel plate capacitors. An iterative algorithm was developed for estimating four displacements from the sixteen capacitances using fourth-order polynomial approximation of characteristics between capacitance and displacement. The estimation results from measured capacitances had large error caused by deterioration of the characteristics. In this study, effective capacitors had major information were selected on the basis of the capacitance change range and the characteristic shape. Maximum errors in calibration and non-calibration points were 25%and 6.8%.However the maximum error was larger than desired value, the smallness of averaged value indicated the occurrence of a few large error points. On the other hand, error in non-calibration point was within desired value.

 

Keywords: Force sensors, capacitive sensors, estimation, iterative algorithms.

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Authors: T. P. Athira, Gibin Chacko George

Abstract:

This paper proposes a dual tree complex wavelet transform (DT-CWT) based directional interpolation scheme for noisy images. The problems of denoising and interpolation are modelled as to estimate the noiseless and missing samples under the same framework of optimal estimation. Initially, DT-CWT is used to decompose an input low-resolution noisy image into low and high frequency subbands. The high-frequency subband images are interpolated by linear minimum mean square estimation (LMMSE) based interpolation, which preserves the edges of the interpolated images. For each noisy LR image sample, we compute multiple estimates of it along different directions and then fuse those directional estimates for a more accurate denoised LR image. The estimation parameters calculated in the denoising processing can be readily used to interpolate the missing samples. The inverse DT-CWT is applied on the denoised input and interpolated high frequency subband images to obtain the high resolution image. Compared with the conventional schemes that perform denoising and interpolation in tandem, the proposed DT-CWT based noisy image interpolation method can reduce many noise-caused interpolation artifacts and preserve well the image edge structures. The visual and quantitative results show that the proposed technique outperforms many of the existing denoising and interpolation methods.

Keywords: Dual-tree complex wavelet transform (DT-CWT), denoising, interpolation, optimal estimation, super resolution.

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Authors: Jin-Hyeok Kim, Won-Chul Choi, Seung-Ri Jin, Dong-Jo Park

Abstract:

In this paper, an analysis of a target location estimation system using the best linear unbiased estimator (BLUE) for high performance radar systems is presented. In synthetic environments, we are here concerned with three key elements of radar system modeling, which makes radar systems operates accurately in strategic situation in virtual ground. Radar Cross Section (RCS) modeling is used to determine the actual amount of electromagnetic waves that are reflected from a tactical object. Pattern Propagation Factor (PPF) is an attenuation coefficient of the radar equation that contains the reflection from the surface of the earth, the diffraction, the refraction and scattering by the atmospheric environment. Clutter is the unwanted echoes of electronic systems. For the data fusion of output results from radar detection in synthetic environment, BLUE is used and compared with the mean values of each simulation results. Simulation results demonstrate the performance of the radar system.

Keywords: Best linear unbiased estimator (BLUE) , data fusion, radar system modeling, target location estimation

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Authors: Mingren Shi, Michael Renton

Abstract:

There is a world-wide need for the development of sustainable management strategies to control pest infestation and the development of phosphine (PH3) resistance in lesser grain borer (Rhyzopertha dominica). Computer simulation models can provide a relatively fast, safe and inexpensive way to weigh the merits of various management options. However, the usefulness of simulation models relies on the accurate estimation of important model parameters, such as mortality. Concentration and time of exposure are both important in determining mortality in response to a toxic agent. Recent research indicated the existence of two resistance phenotypes in R. dominica in Australia, weak and strong, and revealed that the presence of resistance alleles at two loci confers strong resistance, thus motivating the construction of a two-locus model of resistance. Experimental data sets on purified pest strains, each corresponding to a single genotype of our two-locus model, were also available. Hence it became possible to explicitly include mortalities of the different genotypes in the model. In this paper we described how we used two generalized linear models (GLM), probit and logistic models, to fit the available experimental data sets. We used a direct algebraic approach generalized inverse matrix technique, rather than the traditional maximum likelihood estimation, to estimate the model parameters. The results show that both probit and logistic models fit the data sets well but the former is much better in terms of small least squares (numerical) errors. Meanwhile, the generalized inverse matrix technique achieved similar accuracy results to those from the maximum likelihood estimation, but is less time consuming and computationally demanding.

Keywords: mortality estimation, probit models, logistic model, generalized inverse matrix approach, pest control simulation

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Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

Abstract:

 A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: Forecasting model, Steel demand uncertainty, Hierarchical Bayesian framework, Exponential smoothing method.

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Authors: Masoud Nasri, Sadat Feiznia, Mohammad Jafari, Hasan Ahmadi

Abstract:

Today, incorrect use of lands and land use changes, excessive grazing, no suitable using of agricultural farms, plowing on steep slopes, road construct, building construct, mine excavation etc have been caused increasing of soil erosion and sediment yield. For erosion and sediment estimation one can use statistical and empirical methods. This needs to identify land unit map and the map of effective factors. However, these empirical methods are usually time consuming and do not give accurate estimation of erosion. In this study, we applied GIS techniques to estimate erosion and sediment of Menderjan watershed at upstream Zayandehrud river in center of Iran. Erosion faces at each land unit were defined on the basis of land use, geology and land unit map using GIS. The UTM coordinates of each erosion type that showed more erosion amounts such as rills and gullies were inserted in GIS using GPS data. The frequency of erosion indicators at each land unit, land use and their sediment yield of these indices were calculated. Also using tendency analysis of sediment yield changes in watershed outlet (Menderjan hydrometric gauge station), was calculated related parameters and estimation errors. The results of this study according to implemented watershed management projects can be used for more rapid and more accurate estimation of erosion than traditional methods. These results can also be used for regional erosion assessment and can be used for remote sensing image processing.

Keywords: Erosion and sedimentation, Gully, Rill, GIS, GPS, Menderjan Watershed

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Authors: Jaibir S. Yadav, Dimple, Vinod K. Sharma

Abstract:

Molar excess Volumes, VE ijk and speeds of sound , uijk of 2-pyrrolidinone (i) + benzene or toluene (j) + ethanol (k) ternary mixture have been measured as a function of composition at 308.15 K. The observed speeds of sound data have been utilized to determine excess isentropic compressiblities, ( E S κ )ijk of ternary (i + j + k) mixtures. Molar excess volumes, VE ijk and excess isentropic compressibilities, ( E S κ )ijk data have fitted to the Redlich-Kister equation to calculate ternary adjustable parameters and standard deviations. The Moelywn-Huggins concept (Huggins in Polymer 12: 389-399, 1971) of connectivity between the surfaces of the constituents of binary mixtures has been extended to ternary mixtures (using the concept of a connectivity parameter of third degree of molecules, 3ξ , which inturn depends on its topology) to obtain an expression that describes well the measured VE ijk and ( E S κ )ijk data.

Keywords: Connectivity parameter of third degree, 3ξ, Excess isentropic compressibilities, ( ES κ )ijk, Interaction energy parameter, χ, Molar excess volumes, VEijk, Speeds of sound, uijk.

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Authors: Ezad Hafidz Hafidzuddin, Roslinda Nazar, Norihan M. Arifin, Ioan Pop

Abstract:

In this paper, the problem of steady laminar boundary layer flow and heat transfer over a permeable exponentially stretching/shrinking sheet with generalized slip velocity is considered. The similarity transformations are used to transform the governing nonlinear partial differential equations to a system of nonlinear ordinary differential equations. The transformed equations are then solved numerically using the bvp4c function in MATLAB. Dual solutions are found for a certain range of the suction and stretching/shrinking parameters. The effects of the suction parameter, stretching/shrinking parameter, velocity slip parameter, critical shear rate and Prandtl number on the skin friction and heat transfer coefficients as well as the velocity and temperature profiles are presented and discussed.

Keywords: Boundary Layer, Exponentially Stretching/Shrinking Sheet, Generalized Slip, Heat Transfer, Numerical Solutions.

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Authors: Balaji Sankar, Sadanand Kulkarni

Abstract:

Compliant foil gas lubricated bearings are used for the support of light loads in the order of few kilograms at high speeds, in the order of 50,000 RPM. The stiffness of the foil bearings depends both on the stiffness of the compliant foil and on the lubricating gas film. The stiffness of the bearings plays a crucial role in the stable operation of the supported rotor over a range of speeds. This paper describes a numerical approach to estimate the stiffness of the bearings using pseudo spectral scheme. Methodology to obtain the stiffness of the foil bearing as a function of weight of the shaft is given and the results are presented.

Keywords: Foil bearing, simulation, numerical, stiffness estimation.

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Authors: Nga-Viet Nguyen, Georgy Shevlyakov, Vladimir Shin

Abstract:

To solve the problem of multisensor data fusion under non-Gaussian channel noise. The advanced M-estimates are known to be robust solution while trading off some accuracy. In order to improve the estimation accuracy while still maintaining the equivalent robustness, a two-stage robust fusion algorithm is proposed using preliminary rejection of outliers then an optimal linear fusion. The numerical experiments show that the proposed algorithm is equivalent to the M-estimates in the case of uncorrelated local estimates and significantly outperforms the M-estimates when local estimates are correlated.

Keywords: Data fusion, estimation, robustness, M-estimates.

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Authors: M. H. Pol, A. Bidi, A. V. Hoseini

Abstract:

Estimation of natural frequency of structures is very important and isn-t usually calculated simply and sometimes complicated. Lack of knowledge about that caused hard damage and hazardous effects. In this paper, with using from two different models in FEM method and based on hydrodynamic mass of fluids, natural frequency of an especial bearing (Fig. 1) in an electric field (or, a periodic force) is calculated in different stiffness and different geometric. In final, the results of two models and analytical solution are compared.

Keywords: Natural frequency of the bearing, Hydrodynamic mass of fluid method.

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Authors: Amira Mabrouk, Chokri Abdennadher

Abstract:

The reduction of road congestion which is inherent to the use of vehicles is an obvious priority to public authority. Therefore, assessing the willingness to pay of an individual in order to save trip-time is akin to estimating the change in price which was the result of setting up a new transport policy to increase the networks fluidity and improving the level of social welfare. This study holds an innovative perspective. In fact, it initiates an economic calculation that has the objective of giving an estimation of the monetized time value during the trips made in Sfax. This research is founded on a double-objective approach. The aim of this study is to i) give an estimation of the monetized value of time; an hour dedicated to trips, ii) determine whether or not the consumer considers the environmental variables to be significant, iii) analyze the impact of applying a public management of the congestion via imposing taxation of city tolls on urban dwellers. This article is built upon a rich field survey led in the city of Sfax. With the use of the contingent valuation method, we analyze the “declared time preferences” of 450 drivers during rush hours. Based on the fond consideration of attributed bias of the applied method, we bring to light the delicacy of this approach with regards to the revelation mode and the interrogative techniques by following the NOAA panel recommendations bearing the exception of the valorization point and other similar studies about the estimation of transportation externality.

Keywords: Willingness to pay, value of time, contingent valuation, time value, city toll, transport.

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Authors: Evangelos G. Karvelas, Christos Liosis, Andreas Theodorakakos, Theodoros E. Karakasidis

Abstract:

In the present work, a numerical method for the estimation of the appropriate gradient magnetic fields for optimum driving of the particles into the desired area inside the human body is presented. The proposed method combines Computational Fluid Dynamics (CFD), Discrete Element Method (DEM) and Covariance Matrix Adaptation (CMA) evolution strategy for the magnetic navigation of nanoparticles. It is based on an iteration procedure that intents to eliminate the deviation of the nanoparticles from a desired path. Hence, the gradient magnetic field is constantly adjusted in a suitable way so that the particles’ follow as close as possible to a desired trajectory. Using the proposed method, it is obvious that the diameter of particles is crucial parameter for an efficient navigation. In addition, increase of particles' diameter decreases their deviation from the desired path. Moreover, the navigation method can navigate nanoparticles into the desired areas with efficiency approximately 99%.

Keywords: CFD, CMA evolution strategy, DEM, magnetic navigation, spherical particles.

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Authors: Hidir S. Nogay

Abstract:

In this study, two systems were created to predict interior temperature in induction motor. One of them consisted of a simple ANN model which has two layers, ten input parameters and one output parameter. The other one consisted of eight ANN models connected each other as cascaded. Cascaded ANN system has 17 inputs. Main reason of cascaded system being used in this study is to accomplish more accurate estimation by increasing inputs in the ANN system. Cascaded ANN system is compared with simple conventional ANN model to prove mentioned advantages. Dataset was obtained from experimental applications. Small part of the dataset was used to obtain more understandable graphs. Number of data is 329. 30% of the data was used for testing and validation. Test data and validation data were determined for each ANN model separately and reliability of each model was tested. As a result of this study, it has been understood that the cascaded ANN system produced more accurate estimates than conventional ANN model.

Keywords: Cascaded neural network, internal temperature, three-phase induction motor, inverter.

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Authors: Yung-Yuan Hsu

Abstract:

The primary objective of this paper was to construct a “kinematic parameter-independent modeling of three-axis machine tools for geometric error measurement" technique. Improving the accuracy of the geometric error for three-axis machine tools is one of the machine tools- core techniques. This paper first applied the traditional method of HTM to deduce the geometric error model for three-axis machine tools. This geometric error model was related to the three-axis kinematic parameters where the overall errors was relative to the machine reference coordinate system. Given that the measurement of the linear axis in this model should be on the ideal motion axis, there were practical difficulties. Through a measurement method consolidating translational errors and rotational errors in the geometric error model, we simplified the three-axis geometric error model to a kinematic parameter-independent model. Finally, based on the new measurement method corresponding to this error model, we established a truly practical and more accurate error measuring technique for three-axis machine tools.

Keywords: Three-axis machine tool, Geometric error, HTM, Error measuring

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Authors: Panudet Saengseedam, Nanthachai Kantanantha

Abstract:

This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, Linear mixed model, Multivariate conditional autoregressive model, Spatial time series.

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Authors: Naci Büyükkaracığan

Abstract:

Today, the need for water sources is swiftly increasing due to population growth. At the same time, it is known that some regions will face with shortage of water and drought because of the global warming and climate change. In this context, evaluation and analysis of hydrological data such as the observed trends, drought and flood prediction of short term flow has great deal of importance. The most accurate selection probability distribution is important to describe the low flow statistics for the studies related to drought analysis. As in many basins In Turkey, Gediz River basin will be affected enough by the drought and will decrease the amount of used water. The aim of this study is to derive appropriate probability distributions for frequency analysis of annual minimum flows at 6 gauging stations of the Gediz Basin. After applying 10 different probability distributions, six different parameter estimation methods and 3 fitness test, the Pearson 3 distribution and general extreme values distributions were found to give optimal results.

Keywords: Gediz Basin, goodness-of-fit tests, Minimum flows, probability distribution.

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Authors: Weifeng Wang, Guoqing Huang, Xianwei Zeng

Abstract:

The nearly 21-year-old Jiujiang Bridge, which is suffering from uneven line shape, constant great downwarping of the main beam and cracking of the box girder, needs reinforcement and cable adjustment. It has undergone cable adjustment for twice with incomplete data. Therefore, the initial internal force state of the Jiujiang Bridge is identified as the key for the cable adjustment project. Based on parameter identification by means of static force test data, this paper suggests determining the initial internal force state of the cable-stayed bridge according to the cable force-displacement relationship parameter identification method. That is, upon measuring the displacement and the change in cable forces for twice, one can identify the parameters concerned by means of optimization. This method is applied to the cable adjustment, replacement and reinforcement project for the Jiujiang Bridge as a guidance for the cable adjustment and reinforcement project of the bridge.

Keywords: Cable-stayed bridge, cable force-displacement, parameter identification, internal force state

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Authors: Manasjyoti Bhuyan, Kandarpa Kumar Sarma

Abstract:

All the available algorithms for blind estimation namely constant modulus algorithm (CMA), Decision-Directed Algorithm (DDA/DFE) suffer from the problem of convergence to local minima. Also, if the channel drifts considerably, any DDA looses track of the channel. So, their usage is limited in varying channel conditions. The primary limitation in such cases is the requirement of certain overhead bits in the transmit framework which leads to wasteful use of the bandwidth. Also such arrangements fail to use channel state information (CSI) which is an important aid in improving the quality of reception. In this work, the main objective is to reduce the overhead imposed by the pilot symbols, which in effect reduces the system throughput. Also we formulate an arrangement based on certain dynamic Artificial Neural Network (ANN) topologies which not only contributes towards the lowering of the overhead but also facilitates the use of the CSI. A 2×2 Multiple Input Multiple Output (MIMO) system is simulated and the performance variation with different channel estimation schemes are evaluated. A new semi blind approach based on dynamic ANN is proposed for channel tracking in varying channel conditions and the performance is compared with perfectly known CSI and least square (LS) based estimation.

Keywords: MIMO, Artificial Neural Network (ANN), CMA, LS, CSI.

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Authors: Xiaobai Li, Li Li, Yujin Hu, Weiming Deng, Zhe Ding

Abstract:

A size-dependent Euler–Bernoulli beam model, which accounts for nonlocal stress field, strain gradient field and higher order inertia force field, is derived based on the nonlocal strain gradient theory considering velocity gradient effect. The governing equations and boundary conditions are derived both in dimensional and dimensionless form by employed the Hamilton principle. The analytical solutions based on different continuum theories are compared. The effect of higher order inertia terms is extremely significant in high frequency range. It is found that there exists an asymptotic frequency for the proposed beam model, while for the nonlocal strain gradient theory the solutions diverge. The effect of strain gradient field in thickness direction is significant in low frequencies domain and it cannot be neglected when the material strain length scale parameter is considerable with beam thickness. The influence of each of three size effect parameters on the natural frequencies are investigated. The natural frequencies increase with the increasing material strain gradient length scale parameter or decreasing velocity gradient length scale parameter and nonlocal parameter.

Keywords: Euler-Bernoulli Beams, free vibration, higher order inertia, nonlocal strain gradient theory, velocity gradient.

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Authors: Wen-Tzu Chen, Wen-Bin Kao

Abstract:

This paper provides a scheme to improve the read efficiency of anti-collision algorithm in EPCglobal UHF Class-1 Generation-2 RFID standard. In this standard, dynamic frame slotted ALOHA is specified to solve the anti-collision problem. Also, the Q-algorithm with a key parameter C is adopted to dynamically adjust the frame sizes. In the paper, we split the C parameter into two parameters to increase the read speed and derive the optimal values of the two parameters through simulations. The results indicate our method outperforms the original Q-algorithm.

Keywords: RFID, anti-collision, Q algorithm, ALOHA

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Authors: Yoshikazu Onuki, Itsuo Kumazawa

Abstract:

Fundamental motivation of this paper is how gaze estimation can be utilized effectively regarding an application to games. In games, precise estimation is not always important in aiming targets but an ability to move a cursor to an aiming target accurately is also significant. Incidentally, from a game producing point of view, a separate expression of a head movement and gaze movement sometimes becomes advantageous to expressing sense of presence. A case that panning a background image associated with a head movement and moving a cursor according to gaze movement can be a representative example. On the other hand, widely used technique of POG estimation is based on a relative position between a center of corneal reflection of infrared light sources and a center of pupil. However, a calculation of a center of pupil requires relatively complicated image processing, and therefore, a calculation delay is a concern, since to minimize a delay of inputting data is one of the most significant requirements in games. In this paper, a method to estimate a head movement by only using corneal reflections of two infrared light sources in different locations is proposed. Furthermore, a method to control a cursor using gaze movement as well as a head movement is proposed. By using game-like-applications, proposed methods are evaluated and, as a result, a similar performance to conventional methods is confirmed and an aiming control with lower computation power and stressless intuitive operation is obtained.

Keywords: Point-of-gaze, gaze estimation, head movement, corneal reflections, two infrared light sources, game.

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Authors: Roshan Dharshana Yapa, Koichi Harada

Abstract:

Breast skin-line estimation and breast segmentation is an important pre-process in mammogram image processing and computer-aided diagnosis of breast cancer. Limiting the area to be processed into a specific target region in an image would increase the accuracy and efficiency of processing algorithms. In this paper we are presenting a new algorithm for estimating skin-line and breast segmentation using fast marching algorithm. Fast marching is a partial-differential equation based numerical technique to track evolution of interfaces. We have introduced some modifications to the traditional fast marching method, specifically to improve the accuracy of skin-line estimation and breast tissue segmentation. Proposed modifications ensure that the evolving front stops near the desired boundary. We have evaluated the performance of the algorithm by using 100 mammogram images taken from mini-MIAS database. The results obtained from the experimental evaluation indicate that this algorithm explains 98.6% of the ground truth breast region and accuracy of the segmentation is 99.1%. Also this algorithm is capable of partially-extracting nipple when it is available in the profile.

Keywords: Mammogram, fast marching method, mathematical morphology.

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

Current real-estate value estimation, difficult for laymen, usually is performed by specialists. This paper presents an automated estimation process based on big data and machine-learning technology that calculates influences of building conditions on real-estate price measurement. The present study analyzed actual building sales sample data for Nonhyeon-dong, Gangnam-gu, Seoul, Korea, measuring the major influencing factors among the various building conditions. Further to that analysis, a prediction model was established and applied using RapidMiner Studio, a graphical user interface (GUI)-based tool for derivation of machine-learning prototypes. The prediction model is formulated by reference to previous examples. When new examples are applied, it analyses and predicts accordingly. The analysis process discerns the crucial factors effecting price increases by calculation of weighted values. The model was verified, and its accuracy determined, by comparing its predicted values with actual price increases.

Keywords: Big data, building-value analysis, machine learning, price prediction.

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Authors: Dr. L.K. Singh, Dr. R. M. L, Riktesh Srivastava

Abstract:

How to efficiently assign system resource to route the Client demand by Gateway servers is a tricky predicament. In this paper, we tender an enhanced proposal for autonomous recital of Gateway servers under highly vibrant traffic loads. We devise a methodology to calculate Queue Length and Waiting Time utilizing Gateway Server information to reduce response time variance in presence of bursty traffic. The most widespread contemplation is performance, because Gateway Servers must offer cost-effective and high-availability services in the elongated period, thus they have to be scaled to meet the expected load. Performance measurements can be the base for performance modeling and prediction. With the help of performance models, the performance metrics (like buffer estimation, waiting time) can be determined at the development process. This paper describes the possible queue models those can be applied in the estimation of queue length to estimate the final value of the memory size. Both simulation and experimental studies using synthesized workloads and analysis of real-world Gateway Servers demonstrate the effectiveness of the proposed system.

Keywords: Gateway Server, G/M/1 Queuing Model.

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Authors: V. Amosov, Yu. Kashchuk, A. Krasilnikov, A. Kostin, A. Khovanskiy, A. Leonov, N. Rodionov, R. Rodionov

Abstract:

In present work the problem of the ITER fusion plasma neutron source parameter reconstruction using only the Vertical Neutron Camera data was solved. The possibility of neutron source parameter reconstruction was estimated by the numerical simulations and the analysis of adequateness of mathematic model was performed. The neutron source was specified in a parametric form. The numerical analysis of solution stability with respect to data distortion was done. The influence of the data errors on the reconstructed parameters is shown: • is reconstructed with errors less than 4% at all examined values of δ (until 60%); • is determined with errors less than 10% when δ do not overcome 5%; • is reconstructed with relative error more than 10 %; • integral intensity of the neutron source is determined with error 10% while δ error is less than 15%; where -error of signal measurements, (R0,Z0), the plasma center position,- /parameter of neutron source profile.

Keywords: ITER, neutronsource, neutron source profile reconstruction, Vertical Neutron Camera.

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Authors: Yong-jun Zhao, Heng-li Zhang, Zong-yun Hu

Abstract:

Based on the sources- smoothed rank profile (SRP) and modified minimum description length (MMDL) principle, a method for estimation of the source coherency structure (SCS) and the number of wideband sources is proposed in this paper. Instead of focusing, we first use a spatial smoothing technique to pre-process the array covariance matrix of each frequency for de-correlating the sources and then use smoothed rank profile to determine the SCS and the number of wideband sources. We demonstrate the availability of the method by numerical simulations.

Keywords: Wideband sources, source coherency structure (SCS), smoothed rank profile (SRP).

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Authors: Rhoda Afriyie Mensah, Lin Jiang, Solomon Asante-Okyere, Xu Qiang, Cong Jin

Abstract:

Flammability analysis of extruded polystyrene (XPS) has become crucial due to its utilization as insulation material for energy efficient buildings. Using the Kissinger-Akahira-Sunose and Flynn-Wall-Ozawa methods, the degradation kinetics of two pure XPS from the local market, red and grey ones, were obtained from the results of thermogravity analysis (TG) and microscale combustion calorimetry (MCC) experiments performed under the same heating rates. From the experiments, it was discovered that red XPS released more heat than grey XPS and both materials showed two mass loss stages. Consequently, the kinetic parameters for red XPS were higher than grey XPS. A comparative evaluation of activation energies from MCC and TG showed an insignificant degree of deviation signifying an equivalent apparent activation energy from both methods. However, different activation energy profiles as a result of the different chemical pathways were presented when the dependencies of the activation energies on extent of conversion for TG and MCC were compared.

Keywords: Flammability, microscale combustion calorimetry, thermogravity analysis, thermal degradation, kinetic analysis.

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Authors: Krisada Lekdee, Sunee Sammatat, Nittaya Boonsit

Abstract:

This paper proposes a GLMM with spatial and temporal effects for malaria data in Thailand. A Bayesian method is used for parameter estimation via Gibbs sampling MCMC. A conditional autoregressive (CAR) model is assumed to present the spatial effects. The temporal correlation is presented through the covariance matrix of the random effects. The malaria quarterly data have been extracted from the Bureau of Epidemiology, Ministry of Public Health of Thailand. The factors considered are rainfall and temperature. The result shows that rainfall and temperature are positively related to the malaria morbidity rate. The posterior means of the estimated morbidity rates are used to construct the malaria maps. The top 5 highest morbidity rates (per 100,000 population) are in Trat (Q3, 111.70), Chiang Mai (Q3, 104.70), Narathiwat (Q4, 97.69), Chiang Mai (Q2, 88.51), and Chanthaburi (Q3, 86.82). According to the DIC criterion, the proposed model has a better performance than the GLMM with spatial effects but without temporal terms.

Keywords: Bayesian method, generalized linear mixed model (GLMM), malaria, spatial effects, temporal correlation.

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Authors: Yilun Shang

Abstract:

We study a long-range percolation model in the hierarchical lattice ΩN of order N where probability of connection between two nodes separated by distance k is of the form min{αβ−k, 1}, α ≥ 0 and β > 0. The parameter α is the percolation parameter, while β describes the long-range nature of the model. The ΩN is an example of so called ultrametric space, which has remarkable qualitative difference between Euclidean-type lattices. In this paper, we characterize the sizes of large clusters for this model along the line of some prior work. The proof involves a stationary embedding of ΩN into Z. The phase diagram of this long-range percolation is well understood.

Keywords: percolation, component, hierarchical lattice, phase transition.

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