Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

     The research aims to prepare a preliminary feasibility study that shows the importance of preliminary feasibility study in investment decision making, carrying out of the local demand of service provided in accordance with international standards and statement of investment opportunities available to the private sector in several investment methods. In order to reach the objectives of the study was adopted as a method of partial analysis at the level of economic unity through the study demand, supply, costs, economic and social profitability.

      The health sector in Iraq is one of the service sectors facing today a continuous deficiency

Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls sh

المقال منشور على موقع مجلة الفورين بوليسي الأميركية (Foreign Policy) على الانترنت في 27 أيلول/سبتمبر 2019. يُشير مصطلح العزل (Impeachment) في الثقافة السياسية الأميركية إلى مجموعة الإجراءات التي يتم بموجبها عزل الرئيس من منصبه، وهذه الإجراءات هي بمثابة عملية طويلة تجري داخل الكونجرس، وتتم وفقاً لخطوات يؤدي فيها كل من مجلسيّ النواب والشيوخ دوراَ. ولا يعني القيام بهذه الإجراءات أن يتم عزل الرئيس، فقد تتم إ

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

Soil fertility is a crucial factor in measuring soil quality, it indicates the extent to which soil can support plant life. Soil fertility is measured by the amount of macro and micronutrients, pH, etc. Soil nutrients are depleted after each harvest and therefore must be added. To maintain soil nutrient levels, fertilizer is added to the soil. Adding fertilizer in the precise amount is a matter of great importance because excess or insufficient application can harm plant life and reduce productivity. The use of modern technology is a solution to this problem. Although automated techniques for sowing, weeding, crop harvesting, etc. have been proposed and implemented, none of the techniques are aimed to maintaining soil fertility. The study a

This paper proposes feedback linearization control (FBLC) based on function approximation technique (FAT) to regulate the vibrational motion of a smart thin plate considering the effect of axial stretching. The FBLC includes designing a nonlinear control law for the stabilization of the target dynamic system while the closedloop dynamics are linear with ensured stability. The objective of the FAT is to estimate the cubic nonlinear restoring force vector using the linear parameterization of weighting and orthogonal basis function matrices. Orthogonal Chebyshev polynomials are used as strong approximators for adaptive schemes. The proposed control architecture is applied to a thin plate with a large deflection that stimulates the axial loadin