Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

This paper analysed the effect of electronic internal auditing (EIA) based on the Control Objectives for Information and Related Technologies (COBIT) framework. Organisations must implement an up-to-date accounting information system (AIS) capable of meeting their auditing requirements. Electronic audit risk (compliance assessment, control assurance, and risk assessment) is a development by Weidenmier and Ramamoorti (2006) to improve AIS. In order to fulfil the study’s objectives, a questionnaire was prepared and distributed to a sample comprising 120 employees. The employees were financial managers, internal auditors, and workers involved in the company’s information security departments in the General Company for Electricity D

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

Several previous investigations and studies utilized silica fume (SF) or (micro silica) particles as supplementary cementitious material added as a substitute to cement-based mortars and their effect on the overall properties, especially on physical properties, strength properties, and mechanical properties. This study investigated the impact of the inclusion of silica fume (SF) particles on the residual compressive strengths and microstructure properties of cement-based mortars exposed to severe conditions of elevated temperatures. The prepared specimens were tested and subjected to 25, 250, 450, 600, and 900 °C. Their residual compressive strengths and microstructure were evaluated and compared with control samples (C

Twitter data analysis is an emerging field of research that utilizes data collected from Twitter to address many issues such as disaster response, sentiment analysis, and demographic studies. The success of data analysis relies on collecting accurate and representative data of the studied group or phenomena to get the best results. Various twitter analysis applications rely on collecting the locations of the users sending the tweets, but this information is not always available. There are several attempts at estimating location based aspects of a tweet. However, there is a lack of attempts on investigating the data collection methods that are focused on location. In this paper, we investigate the two methods for obtaining location-based dat

Protecting information sent through insecure internet channels is a significant challenge facing researchers. In this paper, we present a novel method for image data encryption that combines chaotic maps with linear feedback shift registers in two stages. In the first stage, the image is divided into two parts. Then, the locations of the pixels of each part are redistributed through the random numbers key, which is generated using linear feedback shift registers. The second stage includes segmenting the image into the three primary colors red, green, and blue (RGB); then, the data for each color is encrypted through one of three keys that are generated using three-dimensional chaotic maps. Many statistical tests (entropy, peak signa

Low-Density-Parity-Check (LDPC) codes are a cornerstone for achieving robust error correction capabilities in 5G New Radio applications, significantly improving the reliability of data transmission across noisy and unpredictable wireless channels. Since an evaluation and discussion of the performance with channel coding is significantly absent in two-dimensional Index Modulation (IM)-Differential Chaos Shift Keying (DCSK) schemes. Therefore, in this study, the 5G new radio LDPC codes based generalized joint subcarrier-time index modulation DCSK system (5G NR-LDPC-GJSTIM-DCSK) is proposed, where 5G NR-LDPC codes are used as channel coding. The aim is to improve the system’s performance specifically across AWGN (additive white gauss

Standards play a vital role in documenting the values ​​of new test results in the form of tables. They are one of the basic requirements that the standardization process aims for as a complement to standardizing test procedures, and contribute to knowing the current reality of the student. The degree of readiness and level as a result of practicing different exercises for sports activities, in addition to the possibility of adopting it for comparison with his group or similar groups, classification, prediction and selection. Developing the skill of handling the football in the educational field is an important matter for achieving distinguished performance among students. This skill requires a level of accuracy, speed and control, and

Autorías: Mariam Liwa Abdel Fattah, Liqaa Abdullah Ali. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 4, 2023. Artículo de Revista en Dialnet.