Todays, barcodes play a significant role in various industries, and among the two-dimensional barcodes, the most famous one is QR code (Quick Response code) that has grown widely.The main purpose of this paper is to provide a noise-cancellation method based on a autoencoder deep neural network that can be used to restore distorted and illegible QRs to readability.To create noise and distortion, unlike other articles that used added simulated noise to the image, the challenge of extracting QR coded into a color image was used to collect more realistic data by collecting real-world dataset. therefore we Have more reliable estimation of proposed QRs noise-canceling method. As a result, we created a comprehensive data set of distorted QRs from three different watermark extraction approaches after the screen-camera attack. For the noise reduction process, three independent MCNN networks ( which is an upgrade from the U-net network) are used for each of the three extraction approaches,

In this paper, a procedure is reported that discuss how linear algebra can be used in image compression. The basic idea is that each image can be represented as a matrix. We apply linear algebra (QR ‎factorization and wavelet ‎transformation ‎algorithm‏s) on this matrix and get a reduced matrix out such that the image corresponding to this reduced matrix requires much less storage space than the original image.

Trees provide a wide range of benefits to humans and other living organisms. An accurate method tree species identification will improve their management and conservation. Also, tree identification and description are crucial for genetic study, biodiversity conservation, management and regeneration strategies. The conventional methods of tree identification are time-consuming and requires a high level of expertise, necessitating development of a more efficient tree identification means. In this research, a QR code system for tree identification was developed. Tree data were collected from campuses of two tertiary institutions in Akure, Nigeria: Federal University of Technology and Federal College of Agriculture. System design was built around a three-tier architectural model. PostgresSQL was used as the Database System, the lowest tier. The Middle tier is the Web Server, Apache HTTP Server. Php 8. 1 was the scripting language that communicates with the database. For the Client tier, HTML, CSS and Javascript were used. The QR code generator was developed using PHP 8. 1. The PHP script used a QR code library to generate the QR code image. The QR code is linked to the website database containing all tree species information. The generated QR codes were attached to trees, and when scanned, the website is automatically launched and the tree information is retrieved. A survey was conducted to get end-users’ feedback within the study sites. The results obtained revealed that the QR codes are easy to use, and can make tree identification more interesting, thus increasing people’s knowledge about trees and improving Trees management.

Different method are used for channel estimation in MIMO systems, Each of which has different functionality. MIMO systems are like equations with multiple variables, variables are transmitted symbols by transmitter (M) and equations are received symbols in receiver (N). Different mathematical methods are for decomposition of channel matrix, than Q&R Decomposition is one of these methods. Using decomposition for channel matrix with adaptive algorithms such as LMS and RLS in MIMO systems will simplify and reduce complexity. In this paper, the MIMO channel will be modeled by LMS and RLS algorithms and instead directly of estimated the channel matrix H that very complexity, in QR matrix, first estimated Q and then estimated R, that the channel matrix is estimated. According result, in MIMO systems, channel modeling with LMS and RLS adaptive algorithms and applying QR decomposition will result in the error reduction.

Given the increasing number of mobile users, mobile technology is used as a powerful and useful tool for marketing and communication with consumers. One of these communication methods is Quick Response Codes. The aim of this study was to investigate those factors influencing the use of Quick Response Codes in sport products. 280 physical education students of University of Kurdistan were selected by census method with a correlation method using SEM. 139 participants used these codes. With a review of literature, a questionnaire in line with the goals of this study was designed. Face and content validity of this questionnaire was confirmed by experts and construct validity was confirmed by confirmatory factor analysis. The internal reliability was confirmed by Cronbach’ s alpha. Data were analyzed through descriptive and inferential statistics (SEM) by SPSS22 and Amos22 software. Findings showed that the final model had a good fit; therefore, it and its components can be suitable to deliver those factors influencing the use of Quick Response Codes in sport products and can receive the attention of sport marketers.