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An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test AVSS systems. In its basic form, this review aims to highlight the growing importance of AVSS in improving the quality of audio signals.

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Thu Jun 06 2024
Journal Name
Journal Of Applied Engineering And Technological Science (jaets)
Deep Learning and Its Role in Diagnosing Heart Diseases Based on Electrocardiography (ECG)
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Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad

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Publication Date
Fri May 01 2020
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Smart grid in the context of industry 4.0: an overview of communications technologies and challenges
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The recent advances in technology, the increased dependence on electrical energy and the emergence of the fourth industrial revolution (Industry 4.0) were all factors in the increased need for smart, efficient and reliable energy systems. This introduced the concept of the Smart Grid (SG). A SG is a potential replacement for older power grids, capable of adapting and distributing energy based on demand. SG systems are complex. They combine various components and have high requirements for real time reliable operation. This paper attempts to provide an overview of SG systems, by outlining SG architecture and various components. It also introduces communication technologies, integration and network management tools that are involved in SG sys

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
The Compatibility between leadership of empowerment and organizational learning abilities and their reflection on knowledge capital Applied research at Wasit University
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The current research aims at: - Identifying the role played by the leadership in empowerment and organizational learning abilities and their reflection on the knowledge capital, and the extent to which these concepts can be applied effectively at Wasit University. The problem of research .... In a series of questions: The most important is that the dimensions leadership empowerment and distance learning organizational capacity correlation relationship and impact and significant statistical significance with the capital knowledge.

     To understand the nature of the relationship and the impact between the variables, leadership was adopted by empowerment as the fir

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Publication Date
Wed Dec 01 2021
Journal Name
Computers & Electrical Engineering
Utilizing different types of deep learning models for classification of series arc in photovoltaics systems
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Publication Date
Wed Feb 06 2019
Journal Name
International Journal Of Dynamics And Control
Biomechanics, actuation, and multi-level control strategies of power-augmentation lower extremity exoskeletons: an overview
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Publication Date
Sun Jun 21 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Nanotechnology-Based Topical Drug Delivery Systems for Management of Dandruff and Seborrheic Dermatitis: An overview
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Dandruff and seborrheic dermatitis (SD) are common skin disorders affecting the scalp and extending to other body sites in the case of SD. They are associated with pruritus and scaling, causing an esthetical disturbance in the population affected.   Treatment of such conditions involves using a variety of drugs for long terms, thus optimizing drug formulation is essential to improve therapeutic efficacy and patient compliance. Conventional topical formulations like shampoos and creams have been widely used but their use is associated with disadvantages. To overcome such effects, novel topical nanotechnology-based formulations are currently under investigation. In the following article, we highlight recently published formulatio

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Publication Date
Fri Mar 29 2024
Journal Name
Surgical Neurology International
Enhancing neuro-ophthalmic surgical education: The role of neuroanatomy and 3D digital technologies – An overview
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Background:

Neuro-ophthalmology, bridging neurology and ophthalmology, highlights the nervous system’s crucial role in vision, encompassing afferent and efferent pathways. The evolution of this field has emphasized the importance of neuroanatomy for precise surgical interventions, presenting educational challenges in blending complex anatomical knowledge with surgical skills. This review examines the interplay between neuroanatomy and surgical practices in neuro-ophthalmology, aiming to identify educational gaps and suggest improvements.

Methods:

A literature search across databases such as PubMed, Scopus, and W

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Publication Date
Tue Sep 30 2008
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Separation Benzene and Toluene from BTX using Zeolite 13X
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This work deals with the separation of benzene and toluene from a BTX fraction. The separation was carried out using adsorption by molecular sieve zeolite 13X in a fixed bed. The concentration of benzene and toluene in the influent streams was measured using gas chromatography. The effect of flow rate in the range 0.77 – 2.0 cm3/min on the benzene and toluene extraction from BTX fraction was studied. The flow rate increasing decreases the breakthrough and saturation times. The effect of bed height in the range 31.6 – 63.3 cm on benzene and toluene adsorption from BTX fraction was studied. The increase of bed height increasing increases the break point values. The effect of the concentration of benzene in the range 0.0559 – 0.2625g/

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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of Educational And Psychological Researches
Training Program based on Some Strategies of Self-Regulated Learning for the Teachers of Mathematics and its Effect on their Relational Mathematics
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This research aims at building a proposed training program according to the self-regulated strategies for the mathematics teachers and to identify the effect of this program on relational Mathematics of teachers. The sample of the research was (60) Math teachers; (30) teachers as experimental group and (30) teachers as control group. The results of the current research reacheded that the proposed training program according to some self-managed learning strategies, meets the needs of trainees with remarkable effectiveness to improve the level of their teaching performance to achieve the desired goals. Training teacher according to self-managed learning strategies is effective in bringing about the transition of training to their students

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