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SPE-188966-MS: Drilling problems detection in Basrah oil fields using smartphones
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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Animal Health And Production
The Control and Preventative Measures for the Health Problems of Pets
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Publication Date
Tue Oct 16 2018
Journal Name
Springer Science And Business Media Llc
MOGSABAT: a metaheuristic hybrid algorithm for solving multi-objective optimisation problems
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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Computer Sciences And Informatics
Edge Detection Methods: A Review
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This article studies a comprehensive methods of edge detection and algorithms in digital images which is reflected a basic process in the field of image processing and analysis. The purpose of edge detection technique is discovering the borders that distinct diverse areas of an image, which donates to refining the understanding of the image contents and extracting structural information. The article starts by clarifying the idea of an edge and its importance in image analysis and studying the most noticeable edge detection methods utilized in this field, (e.g. Sobel, Prewitt, and Canny filters), besides other schemes based on distinguishing unexpected modifications in light intensity and color gradation. The research as well discuss

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Southwest Jiaotong University
Image Segmentation for Skin Detection
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Human skin detection, which usually performed before image processing, is the method of discovering skin-colored pixels and regions that may be of human faces or limbs in videos or photos. Many computer vision approaches have been developed for skin detection. A skin detector usually transforms a given pixel into a suitable color space and then uses a skin classifier to mark the pixel as a skin or a non-skin pixel. A skin classifier explains the decision boundary of the class of a skin color in the color space based on skin-colored pixels. The purpose of this research is to build a skin detection system that will distinguish between skin and non-skin pixels in colored still pictures. This performed by introducing a metric that measu

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

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Publication Date
Mon Jan 01 2024
Journal Name
Jordanian Journal Of Computers And Information Technology
BEYOND WORDS: HARNESSING SPEECH SOUND FOR SPEAKER AGE AND GENDER DETECTION USING 1D CNN ARCHITECTURE WITH SELF-ATTENTION MECHANISM
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Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Detection of Methamphetamine using Nanobentonite as a Novel Solid Phase Extraction Column Matrix Assisted with Gas Chromatography- Mass Spectroscopy
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          This study was done to evaluate a new technique to determine the presence of methamphetamine in the hair using nano bentonite-based adsorbent as the filler of extraction column. The state of the art of this study was based on the presence of silica in the nano bentonite that was assumed can interact with methamphetamine. The hair used was treated using methanol to extract the presence of methamphetamine, then it was continued by sonicating the hair sample. Qualitative analysis using Marquish reagent was performed to confirm the presence of methamphetamine in the isolate.The hair sample that has been taken in a different period confirmed that this current developing method can be used to analyzed methamphetamine. This m

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Publication Date
Thu Nov 02 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Biology of the Copepod Ergasilus ogawai Kabata , 1992 Parasitic on Gills of Silurus triostegus at Garmat Ali River, North of Basrah City
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During  the period from  September  1999 till  August  2000, a

tota l  of 194 catfish Silurus triostegus were collected from Garmat Ali river,    orth of Basrah city. Heavy infestation with Ergasilus ogawai was  recorded  on  the  gills  of  S.  triostegus  with  an  incidence  of infection approaching  98.9% while the average intensity of infection was 417. The highest intensity recorded was 1985.

The size of parasites and the shape of its cephalothorax and ovaries  changed according to the age. The monthly observations  on egg  production   indicated  multibree

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Publication Date
Sun Sep 27 2020
Journal Name
Journal Of The College Of Education For Women
Problems Facing Working Women in the Labor Market (The Mall) as a Model:a Field Study in Al-RusafaArea/ Baghdad
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Most studies and research have tried to shed light on unemployment and employment in general, with less focus on the problems facing working women and the resulting social and economic consequences that threaten their human and professional lives. For women, working is one of the basic necessities for the sustainability of human life, and it constitutes an essential axis for both sexes and through it. It also gives a person the status and social status where the individual finds a ready opportunity to practice his intentions and desires, test his abilities and talents, and achieve his ambitions. The availability of full employment in general and the joining of women to the labor market is an important and fundamental factor in the sustai

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