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Yolo Versions Architecture: Review
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Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing items in images.This article, will be focusing on comparing the main differences among the YOLO version's Architecture, and will discuss its evolution from YOLO to YOLOv8, its network architecture, newfeatures, and applications. Itstarts by looking at the basic ideas and design of the first YOLO model, which laid the groundwork for the following improvements in the YOLO family. In additionally, this article will provide a step-by-step guide on how to use the YOLO version architecture, Understanding the primary drivers, feature development, constraints, and even relationships for the versions is crucial as the YOLO versions advance.Researchers interested in object detection, especially beginning researchers, would find this paper useful and enlightening

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network
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The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (kLa), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Engineering
Experimental Evaluation of the Strut-and-Tie Model Applied to Deep Beam with Near-Load Openings
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It is commonly known that Euler-Bernoulli’s thin beam theorem is not applicable whenever a nonlinear distribution of strain/stress occurs, such as in deep beams, or the stress distribution is discontinuous. In order to design the members experiencing such distorted stress regions, the Strut-and-Tie Model (STM) could be utilized. In this paper, experimental investigation of STM technique for three identical small-scale deep beams was conducted. The beams were simply supported and loaded statically with a concentrated load at the mid span of the beams. These deep beams had two symmetrical openings near the application point of loading. Both the deep beam, where the stress distribution cannot be assumed linear, and the ex

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Publication Date
Wed Sep 29 2021
Journal Name
Biomass Conversion And Biorefinery
Encapsulated deep eutectic solvent for esterification of free fatty acid
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A novel encapsulated deep eutectic solvent (DES) was introduced for biodiesel production via a two-step process. The DES was encapsulated in medical capsules and were used to reduce the free fatty acid (FFA) content of acidic crude palm oil (ACPO) to the minimum acceptable level (< 1%). The DES was synthesized from methyltriphenylphosphonium bromide (MTPB) and p-toluenesulfonic acid (PTSA). The effects pertaining to different operating conditions such as capsule dosage, reaction time, molar ratio, and reaction temperature were optimized. The FFA content of ACPO was reduced from existing 9.61% to less than 1% under optimum operating conditions. This indicated that encapsulated MTPB-DES performed high catalytic activity in FFA esterificatio

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Advance Science And Technology
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

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Publication Date
Mon Apr 30 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
An efficient artificial fish swarm algorithm with harmony search for scheduling in flexible job-shop problem
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Flexible job-shop scheduling problem (FJSP) is one of the instances in flexible manufacturing systems. It is considered as a very complex to control. Hence generating a control system for this problem domain is difficult. FJSP inherits the job-shop scheduling problem characteristics. It has an additional decision level to the sequencing one which allows the operations to be processed on any machine among a set of available machines at a facility. In this article, we present Artificial Fish Swarm Algorithm with Harmony Search for solving the flexible job shop scheduling problem. It is based on the new harmony improvised from results obtained by artificial fish swarm algorithm. This improvised solution is sent to comparison to an overall best

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Publication Date
Sat Aug 13 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The efficiency of the tax examiner and its impact on discovering the artificial adjustment of profits: Applied research in the General Tax Authority
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The aim of the research is to measure the length between the variable the efficiency of the tax examiner with its dimensions represented by (scientific questions, practical process (experience), training and development, impartiality and independence, ethics of the profession) and the approved variable discovering the artificial adaptation of profits, and the degree of arrangement of those dimensions its importance and priority, and the research problem has been identified  In a main question that is there any effect of copying the images of the image examiner in discovering the adaptation, the financial statements and reports of the companies (X, Y) and the banks (A, B) were relied on in the interpretation of the results, t

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Publication Date
Tue Jul 15 2025
Journal Name
Smart Innovation, Systems And Technologies
The Role of Artificial Intelligence in Enhancing Translation and Cultural Diversity with Reference English and Arabic Translation
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With the spread of globalization, the need for translators and scholars has grown, as translation is the only process that helps bridge linguistic gaps. Following the emergence of artificial intelligence (AI), a strong competitor has arisen to the translators, sweeping through all scientific and professional fields, including translation sector, with a set of tools that aid in the translation process. The current study aims to investigate the capability of AI tools in translating texts rich in cultural variety from one language to another, specifically focusing on English-Arabic translations, through qualitative analysis to uncover cultural elements in the target language and determine the ability of AI tools to preserve, lose, or alter the

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Modeling Jar Test Results Using Gene Expression to Determine the Optimal Alum Dose in Drinking Water Treatment Plants
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Coagulation is the most important process in drinking water treatment. Alum coagulant increases the aluminum residuals, which have been linked in many studies to Alzheimer's disease. Therefore, it is very important to use it with the very optimal dose. In this paper, four sets of experiments were done to determine the relationship between raw water characteristics: turbidity, pH, alkalinity, temperature, and optimum doses of alum [   .14 O] to form a mathematical equation that could replace the need for jar test experiments. The experiments were performed under different conditions and under different seasonal circumstances. The optimal dose in every set was determined, and used to build a gene expression model (GEP). The models were co

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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)
Evaluation the Incidence of Genotoxic Effects of Artificial Food Favoring Additives in Bone Marrow Cells and Spleen Cells in Mice
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Genetic material is the most important component of cells because it contains the genetic information; hence any disruption to the structure chromosome of cells could lead to very bad results. Genotoxicity use to evaluate the safety of any chemical compounds on genetic materials. Artificial food flavoring additive are chemical substances to produce specific placebo effects added to foods but impart specific flavor to it.

The present study evaluates the genotoxic effect of artificial food flavoring additive on structure of chromosomes at three different concentrations (50%, 100%and 150%) on both bone marrow cells and spleen cells in mice for fourteen successive days. It was found that artificial food flavoring addit

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Publication Date
Mon Dec 16 2024
Journal Name
International Journal Of Computing And Digital Systems
Digital Intelligence for University Students Using Artificial Intelligence Techniques
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The research problem arose from the researchers’ sense of the importance of Digital Intelligence (DI), as it is a basic requirement to help students engage in the digital world and be disciplined in using technology and digital techniques, as students’ ideas are sufficiently susceptible to influence at this stage in light of modern technology. The research aims to determine the level of DI among university students using Artificial Intelligence (AI) techniques. To verify this, the researchers built a measure of DI. The measure in its final form consisted of (24) items distributed among (8) main skills, and the validity and reliability of the tool were confirmed. It was applied to a sample of 139 male and female students who were chosen

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