Geographic Information Systems (GIS) are obtaining a significant role in handling strategic applications in which data are organized as records of multiple layers in a database. Furthermore, GIS provide multi-functions like data collection, analysis, and presentation. Geographic information systems have assured their competence in diverse fields of study via handling various problems for numerous applications. However, handling a large volume of data in the GIS remains an important issue. The biggest obstacle is designing a spatial decision-making framework focused on GIS that manages a broad range of specific data to achieve the right performance. It is very useful to support decision-makers by providing GIS-based decision support syste

The basic idea of the Main Outfall Drain, MOD, was to construct a main channel to collect saline drained water of the irrigation projects within central and southern parts of Iraq and discharge it down to the Arabian Gulf. The MOD has a navigation lock structures near Addalmage Lake at station 299.4km. This structure is designed to ensure navigation within the MOD. The water level difference upstream the cross regulator and the downstream conjugation structure is about 9m. This head difference can be used to generate electrical power by constricting a low head power plant. This study aimed to utilize the head difference in navigation lock structures for power generation. Different operation condition an

This paper demonstrates the design of an algorithm to represent the design stages of fixturing system that serve in increasing the flexibility and automation of fixturing system planning for uniform polyhedral part. This system requires building a manufacturing feature recognition algorithm to present or describe inputs such as (configuration of workpiece) and built database system to represents (production plan and fixturing system exiting) to this algorithm. Also knowledge – base system was building or developed to find the best fixturing analysis (workpiece setup, constraints of workpiece and arrangement the contact on this workpiece) to workpiece.

The Ant System Algorithm (ASA) is a member of the ant colony algorithms family in swarm intelligence methods (part of the Artificial Intelligence field), which is based on the behavior of ants seeking a path and a source of food in their colonies. The aim of This algorithm is to search for an optimal solution for Combinational Optimization Problems (COP) for which is extremely difficult to find solution using the classical methods like linear and non-linear programming methods. 

The Ant System Algorithm was used in the management of water resources field in Iraq, specifically for Haditha dam which is one of the most important dams in Iraq. The target is to find out an efficient management system for

Objective: Econazole nitrate (ECZ) is one of the triazole antifungal drugs with poor aqueous solubility and dissolution rate; there is a need for enhancement of solubility. Therefore; inclusion complexation with β cyclodextrin (βCD) was performed. Methods: In this study kneading method and co-evaporation method of preparation of inclusion complex between βCD and ECZ using two molar ratios of βCD. The solubility of these complexes in isotonic saline solution and distilled water was studied. Complexes prepared by kneading method were used for the preparation of different ophthalmic gel formulas using carbomer (CB) and sodium carboxymethylcellulose (sod CMC) as a gelling agent. The release profile and the rheological behaviour of the gel w

In this paper, a novel flow control strategy which is the inlet throttled pump was used to design an angular velocity control system for rotary actuator. Inlet throttled systems have good performance in addition to their high efficiency compared to traditional valve controlled systems. The flow in the proposed system is adjusted by a valve that is positioned at the pump inlet with the purpose of reducing the energy loses across the valve. This regulated flow is used then to control the actuator angular velocity. The system was modeled and the open loop stability and performance were studied. In order to improve the system performance, Robust-Proportional-Integral-Derivative (RPID) and structured singular value (M@#@) controllers have been d

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

Due to the intensity of competition between economic units that run the trade in durable goods had to pay a lot of these companies to follow the new selling methods aimed at attracting customers to be able to increase its sales and thereby increase their profits ,  these methods are installment sales, which had been in great demand by the customers with limited income, who provides them with the possibility of possession and use of such goods and to postpone the full amount of the payment to the seller, This transaction sales have grown even became installment sales system at the present time of the common types of sales transactions and deployed a lot in our environment and in many sectors of the market, and in some cases m

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Automatic license plate recognition (ALPR) used for many applications especially in security applications, including border control. However, more accurate and language-independent techniques are still needed. This work provides a new approach to identifying Arabic license plates in different formats, colors, and even including English characters. Numbers, characters, and layouts with either 1-line or 2-line layouts are presented. For the test, we intend to use Iraqi license plates as there is a wide range of license plate styles written in Arabic, Kurdish, and English/Arabic languages, each different in style and color. This variety makes it difficult for recent traditional license plate recognition systems and algorithms to recogn