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Automated Pavement Distress Detection Using Image Processing Techniques
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Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels with a medium validity of 76%. There are two kinds of methods, manual and automated, for distress evaluation that are used to assess pavement condition. A committee of three expert engineers in the maintenance department of the Mayoralty of Baghdad did the manual assessment of a highway in Baghdad city by using a Pavement Condition Index (PCI). The automated method was assessed by processing the videos of the road. By comparing the automated with the manual method, the accuracy percentage for this case study was 88.44%. The suggested method proved to be an encouraging solution for identifying cracks and potholes in asphalt pavements and sorting their severity. This technique can replace manual road damage assessment.

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Publication Date
Wed Oct 06 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Image segmentation by using thresholding technique in two stages
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Publication Date
Fri Apr 30 2010
Journal Name
Journal Of Applied Computer Science & Mathematics
Image Hiding Using Magnitude Modulation on the DCT Coefficients
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In this paper, we introduce a DCT based steganographic method for gray scale images. The embedding approach is designed to reach efficient tradeoff among the three conflicting goals; maximizing the amount of hidden message, minimizing distortion between the cover image and stego-image,and maximizing the robustness of embedding. The main idea of the method is to create a safe embedding area in the middle and high frequency region of the DCT domain using a magnitude modulation technique. The magnitude modulation is applied using uniform quantization with magnitude Adder/Subtractor modules. The conducted test results indicated that the proposed method satisfy high capacity, high preservation of perceptual and statistical properties of the steg

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Publication Date
Thu Aug 01 2024
Journal Name
Iop Conference Series: Earth And Environmental Science
Collapse Pattern in Gypseous Soil using Particle Image Velocimetry
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Abstract<p>Gypseous soil is prevalent in arid and semi-arid areas, is from collapsible soil, which contains the mineral gypsum, and has variable properties, including moisture-induced volume changes and solubility. Construction on these soils necessitates meticulous assessment and unique designs due to the possibility of foundation damage from soil collapse. The stability and durability of structures situated on gypseous soils necessitate close collaboration with specialists and careful, methodical preparation. It had not been done to find the pattern of failure in the micromechanical behavior of gypseous sandy soil through particle image velocity (PIV) analysis. This adopted recently in geotech</p> ... Show More
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Publication Date
Tue Dec 31 2024
Journal Name
Journal Of Soft Computing And Computer Applications
Enhancing Image Classification Using a Convolutional Neural Network Model
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In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

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Crossref
Publication Date
Sun Oct 31 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Image segmentation by using thresholding technique in two stages
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Image segmentation can be defined as a cutting or segmenting process of the digital image into many useful points which are called segmentation, that includes image elements contribute with certain attributes different form Pixel that constitute other parts. Two phases were followed in image processing by the researcher in this paper. At the beginning, pre-processing image on images was made before the segmentation process through statistical confidence intervals that can be used for estimate of unknown remarks suggested by Acho & Buenestado in 2018. Then, the second phase includes image segmentation process by using "Bernsen's Thresholding Technique" in the first phase. The researcher drew a conclusion that in case of utilizing

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Crossref
Publication Date
Mon Sep 01 2025
Journal Name
Journal Of Information Hiding And Multimedia Signal Processing
Steganography Based on Image Compression Using a Hybrid Technique
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Information security is a crucial factor when communicating sensitive information between two parties. Steganography is one of the most techniques used for this purpose. This paper aims to enhance the capacity and robustness of hiding information by compressing image data to a small size while maintaining high quality so that the secret information remains invisible and only the sender and recipient can recognize the transmission. Three techniques are employed to conceal color and gray images, the Wavelet Color Process Technique (WCPT), Wavelet Gray Process Technique (WGPT), and Hybrid Gray Process Technique (HGPT). A comparison between the first and second techniques according to quality metrics, Root-Mean-Square Error (RMSE), Compression-

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Publication Date
Mon Dec 30 2019
Journal Name
College Of Islamic Sciences
The biography of the Prophet Muhammad () and his Sunnah between softness and distress
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The Prophet Muhammed () is distinguished in the history of mankind by the fact that he came with a law that combined these two opposing sides, reality and ideals, a wonderful and amazing collection, and he created a wonderful composition between them, and they used together a wise comprehension to ensure the treatment of its ills, and the reform of their delusions together, and uses both Both of them are in the necessary position of the needs of life, and the contradictions and separation of this collection and the wise harness in this research from his law, may God bless him and grant him peace, which shows us this balance in the system of Islam, the most sincere representation, where it is one of the honors of morality, good appreci

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Publication Date
Thu Mar 31 2022
Journal Name
Pakistan Journal Of Medical And Health Sciences
Effect of Moral Distress on Decision Making among Nurses in Intensive Care Units
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Background: Moral distress, as one of the most important issues in the nursing profession, can negatively affect the healthcare system Objectives: To examine the effect of moral distress on decision making. Methodology: A descriptive cross-sectional study a non-probability sampling method was used and a total sample collected was (126) ICU nurses Result: Moral distress among ICUs nurses were moderate and decision making was good Conclusion: Although nurses in ICUs perceive good decision making but suffered from moderate MD which affected their decision making. MD is still an important issue that nurses may face in ICUs Conclusion: Although nurses in ICUs perceive good decision making but suffered from moderate MD which affected the

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Physics
Detection of Physical and Chemical Parameters Using Water Indices (NDWI, MNDWI, NDMI, WRI, and AWEI) for Al-Abbasia River in Al-Najaf Al-Ashraf Governorate Using Remote Sensing and Geographic Information System (GIS) Techniques
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The purpose of this study was to find out the connection between the water parameters that were examined in the laboratory and the water index acquired from the examination of the satellite image of the study area. This was accomplished by analysing the Landsat-8 satellite picture results as well as the geographic information system (GIS). The primary goal of this study is to develop a model for the chemical and physical characteristics of the Al-Abbasia River in Al-Najaf Al-Ashraf Governorate. The water parameters employed in this investigation are as follows: (PH, EC, TDS, TSS, Na, Mg, K, SO4, Cl, and NO3). To collect the samples, ten sampling locations were identified, and the satellite image was obtained on the

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Crossref (1)
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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Automatic voice activity detection using fuzzy-neuro classifier
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Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

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