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Shadow Detection and Elimination for Robot and Machine Vision Applications
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Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensities. In the third stage, the boundary of the target object is extracted, and in the fourth and fifth stages, respectively, the region of interest (ROI) is highlighted and reconstructed. Our model was tested and evaluated using realistic scenarios which include outdoor and indoor scenes. The results reflect the ability of our approach to detect and remove shadows and reconstruct a shadow free image with a small error of approximately 6%.

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Publication Date
Thu Dec 01 2022
Journal Name
Neuroscience Informatics
Epileptic EEG activity detection for children using entropy-based biomarkers
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Publication Date
Fri Jul 30 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and Machine learning algorithm
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The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi

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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Publication Date
Fri Jul 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
A study Some Technical Indicators Under Impact Tillage Depth and Disk harrow Angle of the Compound Machine
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Abstract<p>The research included studying the effect of different plowing depths (10,20and30) cm and three angles of the disc harrows (18,20and25) when they were combined in one compound machine consisting of a triple plow and disc harrows tied within one structure. Draft force, fuel consumption, practical productivity, and resistance to soil penetration. The results indicated that the plowing depth and disc angle had a significant effect on all studied parameters. The results showed that when the plowing depth increased and the disc angle increased, leads to increased pull force ratio, fuel consumption, resistance to soil penetration, and reduce the machine practical productivity.</p>
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Thu Feb 03 2022
Journal Name
Biologia
Developing multiplex PCR for the rapid and simultaneous detection of Staphylococcus aureus, Pseudomonas aeruginosa and Klebsiella pneumoniae associated with sheep respiratory tract infections
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Respiratory tract infections in sheep are among the important health problems that affect all sheep ages around the world. Nine bacterial isolates obtained from sheep with respiratory tract infections were selected to be used in the current study. The isolates included 3 Staphylococcus aureus, 4 Klebsiella pneumoniae, and 2 Pseudomonas aeruginosa. Following the primers design by the Primer3Plus software tool and optimization of the conventional polymerase chain reaction (PCR), the primers were validated for their use in the multiplex PCR experiments. The MFEprimer program was used to check the suitability of the primer set combinations for multiplex PCR. The MFEprimer software was successful in designing the multiplex-PCR experiments and de

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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Materials Science
Investigations on TiO2–NiO@In2O3 nanocomposite thin films (NCTFs) for gas sensing: synthesis, physical characterization, and detection of NO2 and H2S gas sensors
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Publication Date
Fri Apr 26 2024
Journal Name
Mathematical Modelling Of Engineering Problems
Solving Tri-criteria: Total Completion Time, Total Earliness, and Maximum Tardiness Using Exact and Heuristic Methods on Single-Machine Scheduling Problems
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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 Jun 07 2015
Journal Name
Baghdad Science Journal
Serum Vascular Endothelial Growth Factor VEGF and Interlukin-8 As a Novel Biomarkers For Early Detection of Ovarian Tumors
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Epithelial ovarian cancer is the leading cause of cancer deaths from gynecological malignancies. Angiogenesis is considered essential for tumor growth and the development of metastases. VEGF and IL?8 are potent angiostimulatory molecules and their expression has been demonstrated in many solid tumors, including ovarian cancer.VEGF and IL-8 concentrations were measured by ELISA test (HumanVEGF,IL-8). Bioassay ELISA/ US Biological / USA).The median VEGF and IL-8 levels were significantly higher in the sera of ovarian cancer patients than in those with benign tumors and in healthy controls.Pretreatment VEGF and IL-8 serum levels might be regarded as an additional tool in the differentiation of ovarian tumors.

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