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Error Investigation for Free Form Surfaces in Bezier Techniques
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Surface modeling utilizing Bezier technique is one of the more important tool in computer aided geometric design (CAD). The aim of this work is to design and implement multi-patches Bezier free-form surface. The technique has an effective contribution in technology domains and in ships, aircrafts, and cars industry, moreover for its wide utilization in making the molds. This work is includes the synthesis of these patches in a method that is allow the participation of these control point for the merge of the patches, and the confluence of patches at similar degree sides due to degree variation per patch.  The model has been implemented to represent the surface. The interior data of the desired surfaces designed by MATLAB software have been transformed to UG-NX8 software to get the machining process simulation and G-code programs for the model, as well as a virtual machining process has been simulated to show the machining pitfalls, using CIMCO edit software. The sample has been machined using 3-axis vertical CNC machine. Finally, the sample has been measured using (CMM inspection) and it’s found that the average of error (0.144 mm).

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Publication Date
Fri Feb 21 2025
Journal Name
Al–bahith Al–a'alami
Organizational reputation: A descriptive study of concept development and measurement techniques
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The study aimed to monitor the concept of reputation in the previous literature, its relationship to mental image and identity, and to reveal recent trends in its measurement Techniques.

    The study relied on a descriptive approach using library survey and comparative analysis, and the study reached following conclusions:

     Despite the beginning of the first signs of reputation In the fifties of the last century, however, Defining and standardizing the concept with clear and specific dimensions began in the 1990s and the beginning of the third millennium. The concept of reputation refers to the stakeholders’ overall evaluation of organizations, which reflects their perceptions of

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Monitoring of south Iraq marshes using classification and change detection techniques
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Digital change detection is the process that helps in determining the changes associated with land use and land cover properties with reference to geo-registered multi temporal remote sensing data. In this research change detection techniques have been employed to detect the changes in marshes in south of Iraq for two period the first one from 1973 to 1984 and the other from 1973 to 2014 three satellite images had been captured by land sat in different period. Preprocessing such as geo-registered, rectification and mosaic process have been done to prepare the satellite images for monitoring process. supervised classification techniques such maximum likelihood classification has been used to classify the studied area, change detection aft

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Energy Consumption Prediction of Smart Buildings by Using Machine Learning Techniques
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     This paper presents an IoT smart building platform with fog and cloud computing capable of performing near real-time predictive analytics in fog nodes. The researchers explained thoroughly the internet of things in smart buildings, the big data analytics, and the fog and cloud computing technologies. They then presented the smart platform, its requirements, and its components. The datasets on which the analytics will be run will be displayed. The linear regression and the support vector regression data mining techniques are presented. Those two machine learning models are implemented with the appropriate techniques, starting by cleaning and preparing the data visualization and uncovering hidden information about the behavior of

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Publication Date
Mon Jul 31 2017
Journal Name
Journal Of Engineering
Assessment of Water Clarity within Dokan Lake Using Remote Sensing Techniques
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Publication Date
Sat Mar 01 2008
Journal Name
Iraqi Journal Of Physics
Comparison between Different Data Image Compression Techniques Applied on SAR Images
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In this paper, image compression technique is presented based on the Zonal transform method. The DCT, Walsh, and Hadamard transform techniques are also implements. These different transforms are applied on SAR images using Different block size. The effects of implementing these different transforms are investigated. The main shortcoming associated with this radar imagery system is the presence of the speckle noise, which affected the compression results.

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Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

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Publication Date
Thu Mar 09 2023
Journal Name
Coatings
Nondestructive Evaluation of Fiber-Reinforced Polymer Using Microwave Techniques: A Review
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Carbon-fiber-reinforced polymer (CFRP) is widely acknowledged as a leading advanced material structure, offering superior properties compared to traditional materials, and has found diverse applications in several industrial sectors, such as that of automobiles, aircrafts, and power plants. However, the production of CFRP composites is prone to fabrication problems, leading to structural defects arising from cycling and aging processes. Identifying these defects at an early stage is crucial to prevent service issues that could result in catastrophic failures. Hence, routine inspection and maintenance are crucial to prevent system collapse. To achieve this objective, conventional nondestructive testing (NDT) methods are utilized to i

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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
A Review on Face Detection Based on Convolution Neural Network Techniques
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     Face detection is one of the important applications of biometric technology and image processing. Convolutional neural networks (CNN) have been successfully used with great results in the areas of image processing as well as pattern recognition. In the recent years, deep learning techniques specifically CNN techniques have achieved marvellous accuracy rates on face detection field. Therefore, this study provides a comprehensive analysis of face detection research and applications that use various CNN methods and algorithms. This paper presents ten of the most recent studies and illustrate the achieved performance of each method. 

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Publication Date
Thu Dec 02 2021
Journal Name
Iraqi Journal Of Science
Quantitative Analysis based on Supervised Classification of Medical Image Fusion Techniques
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Fusion can be described as the process of integrating information resulting from the collection of two or more images from different sources to form a single integrated image. This image will be more productive, informative, descriptive and qualitative as compared to original input images or individual images. Fusion technology in medical images is useful for the purpose of diagnosing disease and robot surgery for physicians. This paper describes different techniques for the fusion of medical images and their quality studies based on quantitative statistical analysis by studying the statistical characteristics of the image targets in the region of the edges and studying the differences between the classes in the image and the calculation

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