Polynomial IIR digital filters play a crucial role in the process of image data compression. The main purpose of designing polynomial IIR digital filters of the integer parameters space and introduce efficient filters to compress image data using a singular value decomposition algorithm. The proposed work is designed to break down the complex topic into bite-sized pieces of image data compression through the lens of compression image data using Infinite Impulse Response Filters. The frequency response of the filters is measured using a real signal with an automated panoramic measuring system developed in the virtual instrument environment. The analysis of the output signal showed that there are no limit cycles with a maximum radius

The objective  of this work was to analyze the involvement of AhR in bone metabolism using a rat model of experimental osteoporosis and to analyze the mechanisms behind its activity. Rats were assigned randomly to the subsequent groups; Control, received no treatment; ovariectomized (OVX) rats; Sham; Sham+RES received resveratrol; OVX+RES and OVX+CH received AhR’s antagonist, CH223191 (CH); and finally OVX+CHR group received both AhR antagonist along with resveratrol. Resveratrol and AhR antagonist treatment started 7 days after surgery and continued to 45 days. The serum of osteocalcin (OC) and Ca+2  was measured by ELISA and spectrophotometer, respectively. X-ray was used to estimate bone density of rats. In molecular levels,

Background: Chronic suppurative otitis media (CSOM) is the result of aninitial episode of acute otitis media and is characterized by a persistent discharge from the middle ear through a tympanic perforation for at least 2 weeks duration. It is an important cause of preventable hearing loss, particularly in the developing world.Methods. 1. To get an overview on the bacterial ear infection profile in general 2. To assess the antibiotic resistance of Pseudomonal infection (PS) particularly since it is usually the commonest infection to cause otitis media and the most difficult to treat due to the problem of multi drug resistance... A cross sectional study was done which included 405 patient of CSOM patients196 (48%) case were males ,209 (52

Braces in straight bridge systems improve the lateral-torsional buckling resistance of the girders by reducing the unbraced length, while in horizontally curved and skew bridges, the braces are primary structural elements for controlling deformations by engaging adjacent girders to act as a system to resist the potentially large forces and torques caused by the curved or skewed geometry of the bridge. The cross-frames are usually designed as torsional braces, which increase the overall strength and stiffness of the individual girders by creating a girder system that translates and rotates as a unit along the bracing lines. However, when they transmit the truck’s live load forces, they can produce fatigue cracks at their connection

Symmetric cryptography forms the backbone of secure data communication and storage by relying on the strength and randomness of cryptographic keys. This increases complexity, enhances cryptographic systems' overall robustness, and is immune to various attacks. The present work proposes a hybrid model based on the Latin square matrix (LSM) and subtractive random number generator (SRNG) algorithms for producing random keys. The hybrid model enhances the security of the cipher key against different attacks and increases the degree of diffusion. Different key lengths can also be generated based on the algorithm without compromising security. It comprises two phases. The first phase generates a seed value that depends on producing a rand

Developing smart city planning requires integrating various techniques, including geospatial techniques, building information models (BIM), information and communication technology (ICT), and artificial intelligence, for instance, three-dimensional (3D) building models, in enabling smart city applications. This study aims to comprehensively analyze the role and significance of geospatial techniques in smart city planning and implementation. The literature review encompasses (74) studies from diverse databases, examining relevant solutions and prototypes related to smart city planning. The focus highlights the requirements and preparation of geospatial techniques to support the transition to a smart city. The paper explores various aspects,

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod