Automatic speaker recognition

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır

KALMAN FILTER BASED TECHNIQUES FOR ASSIMILATION OF RADAR DATA

The assimilation of radar data in storm-scale numerical weather prediction models is essential for improved forecasts of thunderstorm events. The huge computational cost of assimilating the high temporal and spatial resolution radar observations poses a challenge to the data assimilation techniques. The objective of this study is to examine the Kalman filter based technique for assimilating the high density radar observations. The first set of experiments evaluates the impact of assimilating high temporal frequency radar observations over a shorter assimilation period using the Ensemble Square Root Filter (EnSRF) data assimilation technique. The impact of model error and the value of using a range of intercept and density parameters for hydrometeor categories across the ensemble members within the same microphysics scheme are examined in the second set of experiments using the EnSRF technique. While the EnSRF technique shows promise in radar data assimilation, one limitation of EnSRF is the high computational expense when the number of observations is very large. Thus in an effort to explore efficient data assimilation method, the feasibility of the information filter as data assimilation technique for large number of observations assimilation is examined. The extended information filter (EIF) is implemented using the Lorenz 96 model and the performance of EIF in assimilating high density observations are compared with the benchmark extended Kalman filter (EKF) data assimilation technique

Evaluation of Tomato Hybrids for Resistance against Tomato Mosaic Virus (ToMV)

Tomato mosaic virus (ToMV) drastically affects the tomato production worldwide. To deal with this problem, breeding of ToMV-resistant hybrids/varieties is the ultimate need and most successful approach. In wild tomato species, three dominant ToMV-resistant genes (Tm-1, Tm-2 and Tm-22 ) were identified and the World Vegetable Center developed few fresh market tomato lines resistant to ToMV by the introgression of these genes. Recently at Nuclear Institute for Agriculture and Biology, Faisalabad, Pakistan a breeding programme was initiated to develop high yielding and ToMV tolerant hybrids using these lines. Current study was performed to screen elite F1 hybrids carrying Tm gene along with their parents against ToMV using mechanical inoculation, confirmation of the virus using DAS-ELISA and marker assisted selection of hybrids. Out of 28 hybrids and 17 parent accessions/genotypes, eight hybrids and five accessions were found to be highly resistant and the virus was not detected in DAS-ELISA. Five hybrids were resistant, nine hybrids and four genotypes were tolerant, while the remaining six hybrids and eight genotypes were susceptible. For the confirmation of Tm-22 gene, the tomato hybrids and their parents were subjected to molecular analysis using cleaved amplified polymorphic sequence (CAPS) primers. The result of CAPS markers for the confirmation of Tm-22 gene was found consistent with phenotypic data of the inoculated tomato genotypes/ hybrids. Higher phenolic content, total soluble proteins, better CAT and SOD activities were positively correlated with resistance. Screening results based on phenotype, biochemical and molecular marker data indicate that hybrids carrying Tm-22 gene are good sources of resistance against ToMV

Horizontal Vortex Tubes near a Simulated Tornado: Three-Dimensional Structure and Kinematics

Supercell thunderstorms can produce a wide spectrum of vortical structures, ranging from midlevel mesocyclones to small-scale suction vortices within tornadoes. A less documented class of vortices are horizontally-oriented vortex tubes near and/or wrapping about tornadoes, that are observed either visually or in high-resolution Doppler radar data. In this study, an idealized numerical simulation of a tornadic supercell at 100 m grid spacing is used to analyze the three-dimensional (3D) structure and kinematics of horizontal vortices (HVs) that interact with a simulated tornado. Visualizations based on direct volume rendering aided by visual observations of HVs in a real tornado reveal the existence of a complex distribution of 3D vortex tubes surrounding the tornadic flow throughout the simulation. A distinct class of HVs originates in two key regions at the surface: around the base of the tornado and in the rear-flank downdraft (RFD) outflow and are believed to have been generated via surface friction in regions of strong horizontal near-surface wind. HVs around the tornado are produced in the tornado outer circulation and rise abruptly in its periphery, assuming a variety of complex shapes, while HVs to the south-southeast of the tornado, within the RFD outflow, ascend gradually in the updraft.The first author is supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Grant number 88881.129505/2016-01 of the “Programa de Doutorado Pleno no Exterior” (DPE – 3830) under the Brazilian Ministry of Education. The second author is supported NSF Grant AGS-1261776 and NOAA VORTEX-SE Grant NA17OAR4590188. Open Access fees paid for in whole or in part by the University of Oklahoma Libraries.Ye

MODELLING A WIND MAP OF NIGERIA TO ASSESS THE UTILIZATION OF WIND AS AN ALTERNETIVE SOURCE OF ENERGY

This paper deals with the feasibility study and efficient utilization of wind energy in Nigeria. Twenty (20) years hourly wind data at 10 m height were collected for 2 stations in each of the 6 geographical zones of Nigeria. The selected stations were: Abeokuta, Osogbo, Calabar, Port Harcourt, Owerri, Enugu, Sokoto, Kano, Jos, Abuja, Maiduguri and Yola. A wind map of Nigeria was modelled using ArcView© Geographical Iinformation System. The study revealed that Jos, Kano and Sokoto have wind energy potential sufficient to generate electrical power that could be connected to the national grid, while Enugu and Maiduguri have enough wind energy potential that could be used to power irrigation devices and other agricultural activities. The establishment of wind power plants for excellent stations such as Jos, Kano and Sokoto for the generation of electricity which could be integrated with the present national grid is recommended

The Effects of Heat Generation on Cutting Tool and Machined Workpiece

Metal cutting processes usually cause heat generation at the cutting zone (around the workpiece-tool intersection). The heat generated during these processes may cause different effects on both the workpiece and tool, this in turn may affect the finished product and the general performance of the machined piece. In this study, a review was done on various types of machining conditions available, effects of heat generated on the workpiece and tool, and the approaches adopted to reduce this heat at cutting zones. This study also focuses on the simulation of percentage ratio of heat removal. To handle the simulation, various approaches of heat removal methods were used to get the percentage ratio using the ansys version 19.1 software. It was discovered that heat generation causes two major types of wear on the tool, crater and flank wear, resulting in the reduction of cutting tool life as well as dimensional inaccuracy, surface damage and severe corrosion cases on the workpiece. Various heat reduction methods and coolant application types were as well studied and their merits and demerits were discussed

Stochastic partial differential equation based modelling of large space-time data sets

Increasingly larger data sets of processes in space and time ask for statistical models and methods that can cope with such data. We show that the solution of a stochastic advection-diffusion partial differential equation provides a flexible model class for spatio-temporal processes which is computationally feasible also for large data sets. The Gaussian process defined through the stochastic partial differential equation has in general a nonseparable covariance structure. Furthermore, its parameters can be physically interpreted as explicitly modeling phenomena such as transport and diffusion that occur in many natural processes in diverse fields ranging from environmental sciences to ecology. In order to obtain computationally efficient statistical algorithms we use spectral methods to solve the stochastic partial differential equation. This has the advantage that approximation errors do not accumulate over time, and that in the spectral space the computational cost grows linearly with the dimension, the total computational costs of Bayesian or frequentist inference being dominated by the fast Fourier transform. The proposed model is applied to postprocessing of precipitation forecasts from a numerical weather prediction model for northern Switzerland. In contrast to the raw forecasts from the numerical model, the postprocessed forecasts are calibrated and quantify prediction uncertainty. Moreover, they outperform the raw forecasts, in the sense that they have a lower mean absolute error

Ensemble forecasts of a flood-producing storm: comparison of the influence of model-state perturbations and parameter modifications

High-resolution ensemble simulations (Δx = 1 km) are performed with the Met Office Unified Model for the Boscastle (Cornwall, UK) flash-flooding event of 16 August 2004. Forecast uncertainties arising from imperfections in the forecast model are analysed by comparing the simulation results produced by two types of perturbation strategy. Motivated by the meteorology of the event, one type of perturbation alters relevant physics choices or parameter settings in the model's parametrization schemes. The other type of perturbation is designed to account for representativity error in the boundary-layer parametrization. It makes direct changes to the model state and provides a lower bound against which to judge the spread produced by other uncertainties. The Boscastle has genuine skill at scales of approximately 60 km and an ensemble spread which can be estimated to within ∼ 10% with only eight members. Differences between the model-state perturbation and physics modification strategies are discussed, the former being more important for triggering and the latter for subsequent cell development, including the average internal structure of convective cells. Despite such differences, the spread in rainfall evaluated at skilful scales is shown to be only weakly sensitive to the perturbation strategy. This suggests that relatively simple strategies for treating model uncertainty may be sufficient for practical, convective-scale ensemble forecasting