Search results for: Exponential smoothing

Authors: János Levendovszky, András Oláh

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In this paper, novel statistical sampling based equalization techniques and CNN based detection are proposed to increase the spectral efficiency of multiuser communication systems over fading channels. Multiuser communication combined with selective fading can result in interferences which severely deteriorate the quality of service in wireless data transmission (e.g. CDMA in mobile communication). The paper introduces new equalization methods to combat interferences by minimizing the Bit Error Rate (BER) as a function of the equalizer coefficients. This provides higher performance than the traditional Minimum Mean Square Error equalization. Since the calculation of BER as a function of the equalizer coefficients is of exponential complexity, statistical sampling methods are proposed to approximate the gradient which yields fast equalization and superior performance to the traditional algorithms. Efficient estimation of the gradient is achieved by using stratified sampling and the Li-Silvester bounds. A simple mechanism is derived to identify the dominant samples in real-time, for the sake of efficient estimation. The equalizer weights are adapted recursively by minimizing the estimated BER. The near-optimal performance of the new algorithms is also demonstrated by extensive simulations. The paper has also developed a (Cellular Neural Network) CNN based approach to detection. In this case fast quadratic optimization has been carried out by t, whereas the task of equalizer is to ensure the required template structure (sparseness) for the CNN. The performance of the method has also been analyzed by simulations.

Keywords: Cellular Neural Network, channel equalization, communication over fading channels, multiuser communication, spectral efficiency, statistical sampling.

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Authors: M. Rüstü Karaman, Tekin Susam, Fatih Er, Servet Yaprak, Osman Karkacıer

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Computer based geostatistical methods can offer effective data analysis possibilities for agricultural areas by using vectorial data and their objective informations. These methods will help to detect the spatial changes on different locations of the large agricultural lands, which will lead to effective fertilization for optimal yield with reduced environmental pollution. In this study, topsoil (0-20 cm) and subsoil (20-40 cm) samples were taken from a sugar beet field by 20 x 20 m grids. Plant samples were also collected from the same plots. Some physical and chemical analyses for these samples were made by routine methods. According to derived variation coefficients, topsoil organic matter (OM) distribution was more than subsoil OM distribution. The highest C.V. value of 17.79% was found for topsoil OM. The data were analyzed comparatively according to kriging methods which are also used widely in geostatistic. Several interpolation methods (Ordinary,Simple and Universal) and semivariogram models (Spherical, Exponential and Gaussian) were tested in order to choose the suitable methods. Average standard deviations of values estimated by simple kriging interpolation method were less than average standard deviations (topsoil OM ± 0.48, N ± 0.37, subsoil OM ± 0.18) of measured values. The most suitable interpolation method was simple kriging method and exponantial semivariogram model for topsoil, whereas the best optimal interpolation method was simple kriging method and spherical semivariogram model for subsoil. The results also showed that these computer based geostatistical methods should be tested and calibrated for different experimental conditions and semivariogram models.

Keywords: Geostatistic, kriging, organic matter, sugarbeet.

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Authors: Walenty Oniszczuk

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The use of buffer thresholds, blocking and adequate service strategies are well-known techniques for computer networks traffic congestion control. This motivates the study of series queues with blocking, feedback (service under Head of Line (HoL) priority discipline) and finite capacity buffers with thresholds. In this paper, the external traffic is modelled using the Poisson process and the service times have been modelled using the exponential distribution. We consider a three-station network with two finite buffers, for which a set of thresholds (tm1 and tm2) is defined. This computer network behaves as follows. A task, which finishes its service at station B, gets sent back to station A for re-processing with probability o. When the number of tasks in the second buffer exceeds a threshold tm2 and the number of task in the first buffer is less than tm1, the fed back task is served under HoL priority discipline. In opposite case, for fed backed tasks, “no two priority services in succession" procedure (preventing a possible overflow in the first buffer) is applied. Using an open Markovian queuing schema with blocking, priority feedback service and thresholds, a closed form cost-effective analytical solution is obtained. The model of servers linked in series is very accurate. It is derived directly from a twodimensional state graph and a set of steady-state equations, followed by calculations of main measures of effectiveness. Consequently, efficient expressions of the low computational cost are determined. Based on numerical experiments and collected results we conclude that the proposed model with blocking, feedback and thresholds can provide accurate performance estimates of linked in series networks.

Keywords: Blocking, Congestion control, Feedback, Markov chains, Performance evaluation, Threshold-base networks.

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Authors: V. Churkin, M. Lopatin

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The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second – 95,3%.

Keywords: Bass model, generalized Bass model, replacement purchases, sales forecasting of innovations, statistics of sales of small wind turbines in the United States.

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Authors: Abbas Hani, Seyed Ali Hoseini Abari

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Soil chemical and physical properties have important roles in compartment of the environment and agricultural sustainability and human health. The objectives of this research is determination of spatial distribution patterns of Cd, Zn, K, pH, TNV, organic material and electrical conductivity (EC) in agricultural soils of Natanz region in Esfehan province. In this study geostatistic and non-geostatistic methods were used for prediction of spatial distribution of these parameters. 64 composite soils samples were taken at 0-20 cm depth. The study area is located in south of NATANZ agricultural lands with area of 21660 hectares. Spatial distribution of Cd, Zn, K, pH, TNV, organic material and electrical conductivity (EC) was determined using geostatistic and geographic information system. Results showed that Cd, pH, TNV and K data has normal distribution and Zn, OC and EC data had not normal distribution. Kriging, Inverse Distance Weighting (IDW), Local Polynomial Interpolation (LPI) and Redial Basis functions (RBF) methods were used to interpolation. Trend analysis showed that organic carbon in north-south and east to west did not have trend while K and TNV had second degree trend. We used some error measurements include, mean absolute error(MAE), mean squared error (MSE) and mean biased error(MBE). Ordinary kriging(exponential model), LPI(Local polynomial interpolation), RBF(radial basis functions) and IDW methods have been chosen as the best methods to interpolating of the soil parameters. Prediction maps by disjunctive kriging was shown that in whole study area was intensive shortage of organic matter and more than 63.4 percent of study area had shortage of K amount.

Keywords: Electrical conductivity, Geostatistics, Geographical Information System, TNV

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Authors: Pradeep Kulshrestha, Maulana Ayoub Ali

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The level of penetration of Islamic banking products and services has recorded a reasonable growth at an exponential rate in many parts of the world. There are many factors which have contributed to this growth including, but not limited to the rapid growth of number of Muslims who are uncomfortable with the conventional ways of banking, interest and higher interest rates scheduled by conventional banks and financial institutions as well as the financial inclusion campaign conducted in many countries. The system is facing legal challenges which open the research fdoor for practitioners and academicians for the sake of finding out solutions to those challenges. This paper tries to investigate the development of the Islamic banking system in the United Kingdom (UK), Saudi Arabia, Malaysia, Iran, Kenya, Nigeria and Uganda in order to understand the modalities which have been employed to run an Islamic banking system in the aforementioned countries. The methodology which has been employed in doing this research paper is Doctrinal, of which legislations, policies and other legal tools have been carefully studied and analysed. Again, papers from academic journals, books and financial reports have been deeply analysed for the purpose of enriching the paper and come up with a tangible results. The paper found that in Asia, Malaysia has created the smoothest legal platform for Islamic banking system to work properly in the country. The United Kingdom has tried harder to smooth the banking system without affecting the conventional banking methods and without favouring the operations of Islamic banks. It also tries harder to make UK as an Islamic banking and finance hub in Europe. The entire banking system in Iran is Islamic, while Nigeria has undergone several legal reforms to suit Islamic banking system in the country. Kenya and Uganda are at a different pace in making Islamic Banking system work alongside the conventional banking system.  

Keywords: Shariah, Islamic banking, law, alternative banking.

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Authors: Iacopo Testi, Diego Pajarito, Nicoletta Roberto, Carmen Greco

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Today, a consistent segment of the world’s population lives in urban areas, and this proportion will vastly increase in the next decades. Therefore, understanding the key trends in urbanization, likely to unfold over the coming years, is crucial to the implementation of sustainable urban strategies. In parallel, the daily amount of digital data produced will be expanding at an exponential rate during the following years. The analysis of various types of data sets and its derived applications have incredible potential across different crucial sectors such as healthcare, housing, transportation, energy, and education. Nevertheless, in city development, architects and urban planners appear to rely mostly on traditional and analogical techniques of data collection. This paper investigates the prospective of the data science field, appearing to be a formidable resource to assist city managers in identifying strategies to enhance the social, economic, and environmental sustainability of our urban areas. The collection of different new layers of information would definitely enhance planners' capabilities to comprehend more in-depth urban phenomena such as gentrification, land use definition, mobility, or critical infrastructural issues. Specifically, the research results correlate economic, commercial, demographic, and housing data with the purpose of defining the youth economic discomfort index. The statistical composite index provides insights regarding the economic disadvantage of citizens aged between 18 years and 29 years, and results clearly display that central urban zones and more disadvantaged than peripheral ones. The experimental set up selected the city of Rome as the testing ground of the whole investigation. The methodology aims at applying statistical and spatial analysis to construct a composite index supporting informed data-driven decisions for urban planning.

Keywords: Data science, spatial analysis, composite index, Rome, urban planning, youth economic discomfort index.

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Authors: E. L. Suarez, D. E. Meeroff, Y. Yong

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Current flooding risk modeling focuses on resilience, defined as the probability of recovery from a severe flooding event. However, the long-term damage to property and well-being by nuisance flooding and its long-term effects on communities are not typically included in risk assessments. An approach was developed to address the probability of recovering from a severe flooding event combined with the probability of community performance during a nuisance event. A consolidated model, namely the conflation flooding recovery (&FR) model, evaluates risk-coping mitigation strategies for communities based on the recovery time from catastrophic events, such as hurricanes or extreme surges, and from everyday nuisance flooding events. The &FR model assesses the variation contribution of each independent input and generates a weighted output that favors the distribution with minimum variation. This approach is especially useful if the input distributions have dissimilar variances. The &FR is defined as a single distribution resulting from the product of the individual probability density functions. The resulting conflated distribution resides between the parent distributions, and it infers the recovery time required by a community to return to basic functions, such as power, utilities, transportation, and civil order, after a flooding event. The &FR model is more accurate than averaging individual observations before calculating the mean and variance or averaging the probabilities evaluated at the input values, which assigns the same weighted variation to each input distribution. The main disadvantage of these traditional methods is that the resulting measure of central tendency is exactly equal to the average of the input distribution’s means without the additional information provided by each individual distribution variance. When dealing with exponential distributions, such as resilience from severe flooding events and from nuisance flooding events, conflation results are equivalent to the weighted least squares method or best linear unbiased estimation. The combination of severe flooding risk with nuisance flooding improves flood risk management for highly populated coastal communities, such as in South Florida, USA, and provides a method to estimate community flood recovery time more accurately from two different sources, severe flooding events and nuisance flooding events.

Keywords: Community resilience, conflation, flood risk, nuisance flooding.

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Authors: Appanah Rao Appadu, Muhammad Zaid Dauhoo

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In this paper, we have combined some spatial derivatives with the optimised time derivative proposed by Tam and Webb in order to approximate the linear advection equation which is given by = 0. Ôêé Ôêé + Ôêé Ôêé x f t u These spatial derivatives are as follows: a standard 7-point 6 th -order central difference scheme (ST7), a standard 9-point 8 th -order central difference scheme (ST9) and optimised schemes designed by Tam and Webb, Lockard et al., Zingg et al., Zhuang and Chen, Bogey and Bailly. Thus, these seven different spatial derivatives have been coupled with the optimised time derivative to obtain seven different finite-difference schemes to approximate the linear advection equation. We have analysed the variation of the modified wavenumber and group velocity, both with respect to the exact wavenumber for each spatial derivative. The problems considered are the 1-D propagation of a Boxcar function, propagation of an initial disturbance consisting of a sine and Gaussian function and the propagation of a Gaussian profile. It is known that the choice of the cfl number affects the quality of results in terms of dissipation and dispersion characteristics. Based on the numerical experiments solved and numerical methods used to approximate the linear advection equation, it is observed in this work, that the quality of results is dependent on the choice of the cfl number, even for optimised numerical methods. The errors from the numerical results have been quantified into dispersion and dissipation using a technique devised by Takacs. Also, the quantity, Exponential Error for Low Dispersion and Low Dissipation, eeldld has been computed from the numerical results. Moreover, based on this work, it has been found that when the quantity, eeldld can be used as a measure of the total error. In particular, the total error is a minimum when the eeldld is a minimum.

Keywords: Optimised time derivative, dissipation, dispersion, cfl number, Nomenclature: k : time step, h : spatial step, β :advection velocity, r: cfl/Courant number, hkrβ= , w =θ, h : exact wave number, n :time level, RPE : Relative phase error per unit time step, AFM :modulus of amplification factor

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Authors: A. A. Purohit, M. M. Vaidya, M. D. Kudale

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Among the various developing countries in the world like China, Malaysia, Korea etc., India is also developing its infrastructures in the form of Road/Rail/Airports and Waterborne facilities at an exponential rate. Mumbai, the financial epicenter of India is overcrowded and to relieve the pressure of congestion, Navi Mumbai suburb is being developed on the east bank of Thane creek near Mumbai. The government due to limited space at existing Mumbai Airports (domestic and international) to cater for the future demand of airborne traffic, proposes to build a new international airport near Panvel at Navi Mumbai. Considering the precedence of extreme rainfall on 26^th July 2005 and nearby townships being in a low-lying area, wherein new airport is proposed, it is inevitable to study this complex confluence area from a hydrodynamic consideration under both tidal and extreme events (predicted discharge hydrographs), to avoid inundation of the surrounding due to the proposed airport reclamation (1160 hectares) and to determine the safe grade elevation (SGE). The model studies conducted using the application of unstructured mesh to simulate the Panvel estuarine area (93 km²), calibration, validation of a model for hydraulic field measurements and determine the maxima water levels around the airport for various extreme hydrodynamic events, namely the simultaneous occurrence of highest tide from the Arabian Sea and peak flood discharges (Probable Maximum Precipitation and 26^th July 2005) from five rivers, the Gadhi, Kalundri, Taloja, Kasadi and Ulwe, meeting at the proposed airport area revealed that: (a) The Ulwe River flowing beneath the proposed airport needs to be diverted. The 120m wide proposed Ulwe diversion channel having a wider base width of 200 m at SH-54 Bridge on the Ulwe River along with the removal of the existing bund in Moha Creek is inevitable to keep the SGE of the airport to a minimum. (b) The clear waterway of 80 m at SH-54 Bridge (Ulwe River) and 120 m at Amra Marg Bridge near Moha Creek is also essential for the Ulwe diversion and (c) The river bank protection works on the right bank of Gadhi River between the NH-4B and SH-54 bridges as well as upstream of the Ulwe River diversion channel are essential to avoid inundation of low lying areas. The maxima water levels predicted around the airport keeps SGE to a minimum of 11m with respect to Chart datum of Ulwe Bundar and thus development is not only technologically-economically feasible but also sustainable. The unstructured mesh modeling is a promising tool to simulate complex extreme hydrodynamic events and provides a reliable solution to evolve optimal SGE of airport.

Keywords: Airport, hydrodynamics, hydrographs, safe grade elevation, tides.

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Authors: M. N. Nwodo, Y. P. Cheng, N. H. Minh

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In the process of recovering oil in weak sandstone formations, the strength of sandstones around the wellbore is weakened due to the increase of effective stress/load from the completion activities around the cavity. The weakened and de-bonded sandstone may be eroded away by the produced fluid, which is termed sand production. It is one of the major trending subjects in the petroleum industry because of its significant negative impacts, as well as some observed positive impacts. For efficient sand management therefore, there has been need for a reliable study tool to understand the mechanism of sanding. One method of studying sand production is the use of the widely recognized Discrete Element Method (DEM), Particle Flow Code (PFC^3D) which represents sands as granular individual elements bonded together at contact points. However, there is limited knowledge of the particle-scale behavior of the weak sandstone, and the parameters that affect sanding. This paper aims to investigate the reliability of using PFC^3D and a simple Darcy flow in understanding the sand production behavior of a weak sandstone. An isotropic tri-axial test on a weak oil sandstone sample was first simulated at a confining stress of 1MPa to calibrate and validate the parallel bond models of PFC^3D using a 10m height and 10m diameter solid cylindrical model. The effect of the confining stress on the number of bonds failure was studied using this cylindrical model. With the calibrated data and sample material properties obtained from the tri-axial test, simulations without and with fluid flow were carried out to check on the effect of Darcy flow on bonds failure using the same model geometry. The fluid flow network comprised of every four particles connected with tetrahedral flow pipes with a central pore or flow domain. Parametric studies included the effects of confining stress, and fluid pressure; as well as validating flow rate – permeability relationship to verify Darcy’s fluid flow law. The effect of model size scaling on sanding was also investigated using 4m height, 2m diameter model. The parallel bond model successfully calibrated the sample’s strength of 4.4MPa, showing a sharp peak strength before strain-softening, similar to the behavior of real cemented sandstones. There seems to be an exponential increasing relationship for the bigger model, but a curvilinear shape for the smaller model. The presence of the Darcy flow induced tensile forces and increased the number of broken bonds. For the parametric studies, flow rate has a linear relationship with permeability at constant pressure head. The higher the fluid flow pressure, the higher the number of broken bonds/sanding. The DEM PFC^3D is a promising tool to studying the micromechanical behavior of cemented sandstones.

Keywords: Discrete Element Method, fluid flow, parametric study, sand production/bonds failure.

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