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Defect Detection Using Thermography Camera Techniques: A review
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Individuals across different industries, including but not limited to agriculture, drones, pharmaceuticals and manufacturing, are increasingly using thermal cameras to achieve various safety and security goals. This widespread adoption is made possible by advancements in thermal imaging sensor technology. The current literature provides an in-depth exploration of thermography camera applications for detecting faults in sectors such as fire protection, manufacturing, aerospace, automotive, non-destructive testing and structural material industries. The current discussion builds on previous studies, emphasising the effectiveness of thermography cameras in distinguishing undetectable defects by the human eye. Various methods for defect detection, including temperature analysis and image processing algorithms, are thoroughly presented. The factors contributing to the effectiveness of thermography cameras are explored, along with their advantages over traditional inspection methods. The literature review highlights the diverse applications of thermography cameras in fault detection. The review highlights the remarkable transformation brought by thermal camera technology in mechanical system fault detection, leading to improved maintenance practices. These cameras can detect unseen irregularities, enable non-invasive testing and support hands-on system maintenance, making them indispensable tools for ensuring mechanical systems operate efficiently, reliably and safely. With the continuous advancement of technology, the integration of Industry 4.0 and IoT technologies will further enhance the capabilities of thermal cameras, ensuring elevated performance across different domains. In electrical systems, thermal cameras allow for the early identification of faults, enabling proactive maintenance to mitigate risks. Additionally, by assessing structural integrity, thermal cameras can detect thermal and insulation inefficiencies, leading to improved energy efficiency.  

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Publication Date
Sat Sep 27 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluation of en-masse retraction using microimplant versus conventional techniques: An in vitro study
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Background: The study aimed to investigate the effect of different techniques of en masse retraction on the vertical and sagittal position, axial inclination, rate of space closure, and type of movement of maxillary central incisor. Materials and methods: A typodont simulation system was used (CL II division 2 malocclusion). Three groups were used group 1(N=10, T-loop), group 2(N=10, Time-Saving loop), and group 3(N=10, Microimplant). Photographs were taken before and after retraction and measurements were made using Autodesk AutoCAD© software 2010. Kruskal-Wallis one-way analyses of variance and Mann-Whitney U test (p?0.05) were used. Results: The rate of space closure showed no significant difference among the three groups (p?0.05), whi

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Engineering
Copy Move Image Forgery Detection using Multi-Level Local Binary Pattern Algorithm
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Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Change detection of remotely sensed image using NDVI subtractive and classification methods.
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Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac

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Publication Date
Tue Sep 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Analysis of Wave Propagation in Detection of Aorta Dieses Using Lumps Analysis
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In this paper a theoretical attempt is made to determine whether changes in the aorta diameter at different location along the aorta can be detected by brachial artery measurement.  The aorta is divided into six main parts, each part with 4 lumps of 0.018m length. It is assumed that a desired section of the aorta has a radius change of 100,200, 500%. The results show that there is a significant change for part 2 (lumps 5-8) from the other parts. This indicates that the nearest position to the artery gives the significant change in the artery wave pressure while other parts of the aorta have a small effect.

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Publication Date
Sun Jan 01 2017
Journal Name
Spe
SPE-188966-MS: Drilling problems detection in Basrah oil fields using smartphones
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Scopus
Publication Date
Sat Mar 08 2025
Journal Name
Fusion: Practice And Applications
Fast Numeric Sign Detection Using Adaptive Thresholding and Geometry of Optimized Fingers
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A strong sign language recognition system can break down the barriers that separate hearing and speaking members of society from speechless members. A novel fast recognition system with low computational cost for digital American Sign Language (ASL) is introduced in this research. Different image processing techniques are used to optimize and extract the shape of the hand fingers in each sign. The feature extraction stage includes a determination of the optimal threshold based on statistical bases and then recognizing the gap area in the zero sign and calculating the heights of each finger in the other digits. The classification stage depends on the gap area in the zero signs and the number of opened fingers in the other signs as well as

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Scopus
Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Detection and interpretation of clouds types using visible and infrared satellite images
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One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

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Publication Date
Wed Jul 24 2024
Journal Name
Journal Of Plant Protection Research
Developing smart sprayer for weed control using an object detection algorithm (yolov5)
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Spraying pesticides is one of the most common procedures that is conducted to control pests. However, excessive use of these chemicals inversely affects the surrounding environments including the soil, plants, animals, and the operator itself. Therefore, researchers have been encouraged to...

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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Sat Aug 31 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Credit Card Fraud Detection Using an Autoencoder Model with New Loss Function
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