The present paper discusses morphological and syntactic structures of time in Russian language. The morphological and syntactic structures are considered part component of time category in Russian language.

The morphological categories of time are formed through a various types of expressions .Tenses generally express time relative to the moment of speaking. In some contexts, however, their meaning may be relativized to a point in the past ,present or future which is established in the discourse .Some languages have different verb forms or constructions and that are opposed in meaning not in syntactic category. Hence, the present study traces and compares the syntacti

In this work, a deep computational study has been conducted to assign several qualities for the graph ⁠. Furthermore, determine the amount of the dihedral subgroups in the Held simple group He through utilizing the attributes of gamma.

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

Today's smart engineering systems are often faced with situations that are structurally uncertain, informationally incomplete, and non-probabilistically ambiguous, especially for electrical systems. ARDL models are limited in applications in complex computational environments where the uncertainty is due to vagueness, not randomness, and assume the exact parametric representation of the models and the structure of the stochastic uncertainty. This study proposes a new soft-computing paradigm using Fuzzy Autoregressive Distributed Lag (FARDL) models and compares the performance of the Linear Programming (LP) and Quadratic Programming (QP) estimation algorithms using large-scale parallel Monte Carlo simulations to overcome these drawba

In this work, γ-Al2O3NPs were successfully biosynthesized, mediated aluminum nitrate nona hydrate Al(NO3)3.9H2O, sodium hydroxide, and aqueous clove extract in alkali media. The γ-Al2O3NPs were characterized by different techniques like Fourier transform infrared spectroscopy (FT-IR), UV-Vis spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy–dispersive x-ray spectroscopy, transmission electron microscope (TEM), Energy-dispersive X-ray spectroscopy (EDX), and atomic force microscopy (AFM). The final results indicated the γ-Al2O3NPs nanoparticle size, bonds nature, element phase, crystallinity, morphology, surface image, particle analysis – threshold detection, and the topography parameter. The id

The study was aimed to determine the coordinates of  the points were measured by different ways and different instruments, the most precise way using the differential global positioning system (DGPS) that will be the reference measurements in comparison, less precise way using navigator GPS. Google earth (pro.), and the other applications of GPS mobile ( Samsung and I-phone). In this research (8 points) were chosen that are occasional in location. The comparison of the different observations can give us an idea of ​​the extent to which the accuracy of the observations differs from the different devices used in the observing, as well as through the knowledge of the best device and the best way to measure coordinates accurately t

Bismuth oxide nanoparticle Bi2O3NPs has a wide range of applications and less adverse effects than conventional radio sensitizers. In this work, Bi2O3NPs (D1, D2) were successfully synthesized by using the biosynthesis method with varying bismuth salts, bismuth sulfate Bi2(SO4)3 (D1) or bismuth nitrate. Penta hydrate Bi(NO3)3.5H2O (D2) with NaOH with beta-vulgaris extract. The Bi2O3NPs properties were characterized by different spectroscopic methods to determine Bi2O3NPs structure, nature of bonds, size of nanoparticle, element phase, presence, crystallinity and morphology. The existence of the Bi2O3 band was verified by the FT-IR. The Bi2O3 NPs revealed an absorption peak in the UV-visible spectrum, with energy gap Eg = 3.80eV. The X-ray p

Study showed structure of pecten oculi in the Kestrel Falco tinnunculus L.was
Pleated type and consisted of 17 folds which were thick. While in the Collared Dove
Streptopelia decaocto F. was Vaned type and consisted of 13 folds and it described
thin. The illustrated histological study of pecten oculi folds in the Kestrel and the
Collared Dove was composed of large number of capillaries, large blood vessels and
pigment cells which were few in Kestrel compare with the Collared Dove. The bridge
in the Kestrel and the Collared Dove pecten oculi was consisted of connective tissue,
many pigment cells, and contains on little capillaries and it linked the membrane to
the internal limiting membrane of the retina in the Kes