Self-compacted concrete (SCC) considered as a revolution progress in concrete technology due to its ability for flowing through forms, fusion with reinforcement, compact itself by its weight without using vibrators and economic advantages. This research aims to assess the fresh properties of SCC and study their effect on its compressive strength using different grading zones and different fineness modulus (F.M) of fine aggregate. The fineness modulus used in this study was (2.73, 2.82,2.9& 3.12) for different zones of grading (zone I, zone II& marginal zone(between zone I&II)) according to Iraqi standards (I.Q.S No.45/1984).Twelve mixes were prepared, each mix were tested in fresh state with slump, V-Funnel and L-Box tests, then 72

Self-compacted concrete (SCC) considered as a revolution progress in concrete technology due to its ability for flowing through forms, fusion with reinforcement, compact itself by its weight without using vibrators and economic advantages. This research aims to assess the fresh properties of SCC and study their effect on its compressive strength using different grading zones and different fineness modulus (F.M) of fine aggregate. The fineness modulus used in this study was (2.73, 2.82,2.9& 3.12) for different zones of grading (zone I, zone II& marginal zone(between zone I&II)) according to Iraqi standards (I.Q.S No.45/1984).Twelve mixes were prepared, each mix were tested in fresh state with slump, V-Funnel and L-Box tests, t

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

A new, Simple, sensitive and accurate spectrophotometric methods have been developed for the determination of sulfamethoxazole (SMZ) drug in pure and dosage forms. This method based on the reaction of sulfamethoxazole (SMZ) with 1,2-napthoquinone-4-sulphonic acid (NQS) to form Nalkylamono naphthoquinone by replacement of the sulphonate group of the naphthoquinone sulphonic acid by an amino group. The colored chromogen shows absorption maximum at 460 nm. The optimum conditions of condensation reaction forms were investigated by (1) univariable method, by optimizing the effect of experimental variables (different bases, reagent concentration, borax concentration and reaction time), (2) central composite design (CCD) including the effect of

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota