The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

       In the current work, aromatic amines and alkyl halides have been converted to the corresponding azides 2a‒d and 4a-d by the reaction with sodium nitrite and sodium azide respectively for amines and sodium azide for halides. Then, dipropargyl ether derivative of D-mannose 8 has been synthesized from diacetone mannose that has been obtained by the treatment of D-mannose (5) with dry acetone in the presence of sulfuric acid. Then, aldol condensation has been used to prepare diol 7 from the mannose diacetonide 6. The reaction of compound 7 with propargyl bromide in alkaline media has been afforded dipropargyl

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

Objective(s): The main aim of the study is to determine the level of burden on mothers toward children with anorectal malformation.
Methodology: A descriptive study was carried out at Welfare Pediatric Teaching Hospital and Central Pediatric Teaching Hospital in Baghdad City. From November 15th, 2017 to April 29th, 2018. Convenient sample comprised of (140) children mothers with anorectal malformation were interviewed for the study. The instrument of study is composed of six domains related mothers' burden toward psychosocial burden as a result of child with anorectal malformation. Validity of the study instrument was determined through a panel of experts and the reliability of the questionnaire is determined in a pilot study among (1

This paper is a review of the genus Sitta in Iraq, Five species of this genus are recognized
Sitta kurdistanica, S. neumayr, S. europaea, S.dresseri and S. tephronota. Geographical
distribution and systematic nots were given for separation and identification, also some notes
on nest building and nest sites of S. tephronota supporting by figures are presented.

A chemical study was carried out to evaluate the efficiency of the liver enzyme concertation and uric acid level and its antagonists in the serum of the professors exposed to chemicals in the laboratories of the University of Samarra and their comparison with the healthy people. The research included 25 samples of the exposed professors and 20 samples as a group of officers.

              The results of the current study showed a significant increase in the level of   AST, ALT in the serum of professors exposed to chemicals compared to healthy people. The results showed no significant increase in

The data preprocessing step is an important step in web usage mining because of the nature of log data, which are heterogeneous, unstructured, and noisy. Given the scalability and efficiency of algorithms in pattern discovery, a preprocessing step must be applied. In this study, the sequential methodologies utilized in the preprocessing of data from web server logs, with an emphasis on sub-phases, such as session identification, user identification, and data cleansing, are comprehensively evaluated and meticulously examined.

In present study the effect of soil extracts of different types of soil on ability of two clinical isolates, Pseudomonas aeruginosa and Staphylococcus aureus to form biofilm. The extract of soil was done by using sterile phosphate buffer saline and analyzed by Fourier Transform Infrared Spectroscopic (FTIR). Spectrophotometric method was used to check ability of the studied isolated bacteria to form biofilm on polystyrene microtiter plates. The data of FTIR showed very little difference was observed among extracts of three types of soil (soil contaminated with hydrocarbons; garden soil collected from gardens of al-jadrea, Baghdad and containers soil), but the highest difference was observed in the extract obtained from peat moss clay soil.