NTU Journal of Engineering and Technology

Research and practical applications to update maps depend on successive steps and take into account the development of surveying devices and methods of producing old cadastral maps. which are the only maps available for ownership in Iraq, and that Iraqi government departments and Iraqi state departments use these maps. The research suggests a way to update old agricultural cadastral maps in Iraq by following a re-measurement-based modernization approach as an accuracy limit. Modern D.G.P.S scanning devices and GIS Software is used. to produce new and effective maps with a solid scientific update methodology. The study area is the Mosul district to which the methodology will be applied and the study area covers the Mosul district according to the approved index and old cadastral maps. The results of the study area showed that the methodology used in the research can produce a new correctly-measured map. The projection WGS 1984_ UTM Zone 38 in the Mosul.

This research focuses on the design and analysis of a seven multilevel cascaded H-Bridge CHB inverter system, with particular emphasis on its control mechanism implemented using Field-Programmable Gate Array (FPGA) behavioral modeling, very high speed integrated circuit hardware description language (VHDL) code, which is created and verified with the Xilinx Integrated Synthesis Environment ISE 14.7 software. The proposed system employs seven cascaded H-Bridge inverters to achieve higher voltage levels and better waveform with lower Total Harmonic Distortion (THD) compared to traditional inverters. To demonstrate this concept, the entire system has been examined and simulated using the MATLAB/Simulink software package. Different values of THDs, Vrms and voltage waveforms have been achieved. The experimental values were compared with that achieved in simulation, and the comparison proved that the results meet the expectations.

The objective of this study is to determine whether or not the median and weighted median filters are efficient in removing salt and pepper noise from digital photographs. The picture quality may be severely diminished when there is a high degree of this noise. Because of its ease of use, efficiency, and capacity to maintain edge details, the median filter is often used for the purpose of noise reduction. On the other hand, it is less effective in environments that are notoriously loud. As an additional, more sophisticated option, the study recommends using a weighted median filter in order to circumvent this issue. By assigning greater weight to pixels with comparable intensity levels, this filter is extremely good at decreasing background noise. As a result, it is highly ideal for use in contexts that possess a high degree of background noise. According to the findings of the experiments, the suggested approach works much better than the conventional median filtering strategies when used to high-noise circumstances.

Several water systems are mechanized to minimize human labor, optimize water utilization, and mitigate water wastage. The researchers suggested implementing remote administration and control for an automated water system. On a remote agricultural property, a pump will utilize a well to replenish a water tank with water. Because of the expensive nature of wired control, it is necessary to activate and deactivate this pump using wireless means in accordance with the water tank's filling level. The system's operator needs have constant access to a cell phone in order to monitor the water level in the tank. In order to accomplish the aforementioned objectives, this article utilizes a LOGO!® Programmable Logic Controller (PLC) and a LOGO!® Communication
Module Radio (CMR) manufactured by SIEMENS. SIEMENS utilizes SoftComfort V8.3 as the software for programming and controlling the system.

Counterfeiting is a serious threat to economies because sophisticated counterfeit banknotes are becoming increasingly difficult to identify through conventional verification techniques, thanks to advancements in printing technology. In this work, we offer a thorough investigation of sophisticated methods for detecting counterfeit money that make use of deep learning and machine learning approaches. Using machine learning algorithms like Random Forest, Decision Tree Classifier, XGBoost, CatBoost, and Support Vector Machine (SVM) in addition to deep learning techniques like Convolutional Neural Networks (CNNs), VGG16, MobileNetV2, and InceptionV3, we examine the security characteristics of Iraqi dinar banknotes and build robust models. All of the models in our results had high accuracy rates, with CNN, CatBoost, and SVM showing particularly strong performance. These results demonstrate how effective cutting-edge technical solutions are in thwarting the dangers posed by counterfeit money, protecting national economies and reducing losses. Sustaining the security of international financial systems and keeping ahead of evolving counterfeiting strategies need ongoing study and development in this area.

The process of diagnosing diseases early is one of the most important goals of the tremendous development in artificial intelligence, and Parkinson’s disease is one of the diseases whose symptoms are similar to many other diseases. It is a neurological disease whose symptoms develop slowly, so the process of its diagnosis is very important in order to preserve the patient's life. One of the most important symptoms is muscle stiffness as well as slow movement. In this research, a method was developed to detect Parkinson's disease using machine learning, learning transfer techniques were relied upon to extract features from handwriting images that we obtained from the NewHandPD database, and then these images were classified into two categories (Parkinson's disease and non-Parkinson's disease) by KNN classification algorithm, for being accurate and fast in calculations, the results of the training of the INCEPTION-V4 model showed a detection accuracy of up to 93%, as well as an area under the curve of 0.89 with a loss of only 0.2 , where this model can be relied on to diagnose and detect Parkinson's disease with high accuracy.

Global electricity demand is rising, prompting increased attention to renewable energy sources like solar power. This research focuses on identifying suitable areas for power lines connecting solar farms to distribution stations in Kirkuk City. Data types, including urban areas, industrial zones, farms, water bodies, and archaeological sites, were analyzed using GIS-based spatial tools. The study highlights accessible and inaccessible regions of Kirkuk's electricity transmission infrastructure, providing insights for decision-makers. The analysis categorizes areas as either benefitted or unbenefited in the context of solar farm suitability. An important consideration is the need for additional electrical distribution stations to accommodate energy transfer from these solar farms.