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Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Thu Dec 01 2022
Journal Name
Al-khwarizmi Engineering Journal
Comparative Transfer Learning Models for End-to-End Self-Driving Car
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Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

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Publication Date
Wed Oct 11 2023
Journal Name
Journal Of Educational And Psychological Researches
The Relationship between Formal Thinking & Learning Styles for Kindergarten Department Students
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The current research aims to reveal the strength of education and the direction of the relationship between the formal thinking and learning methods of Kindergarten department students. To achieve this objective, the researcher developed a scale of formal thinking according to the theory of (Inhelder & Piaget 1958) consisting of (25) items in the form of declarative phrases derived from the analysis of formal thinking skills based on a professional situation that students are expected to interact with in a professional way. The research sample consisted of (100) female students selected randomly who were divided into four groups based on the academic stages, the results revealed that The level of formal thinking of the main sample is

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Synthesis of ZnS Quantum Dots for QDs-LED hybrid device with different cathode materials
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Publication Date
Wed Jun 01 2022
Journal Name
Iraqi Journal Of Physics
Enhanced Mechanical Property of Acrylic Polymer/Graphene/Carbon Fibers Hybrid for Water Proof Coating
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In this work, some mechanical properties of the polymer coating were improved by preparing a hybrid system containing Graphene (GR) of different weight percentages (0.25, 0.5, 1, and 2wt%) with 5wt% carbon fibres (CF) and added to a polymer coating by using casting method. The properties were improved as GR was added with further improvement on adding 5wt% of CF. The impact strength of acrylic polymer with GR increases with increasing weight ratio‏‏ of GR; maximum value was obtained when the polymer coating was incorporated with 1wt% GR and 5wt% CF. The impact strength of acrylic polymer with GR and GR/CF composites incorporated with GR at 1wt% and CF at 5wt%. Hardness increase with increasing weight ratio of Gr and a significant imp

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Publication Date
Wed Mar 10 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A hybrid Grey Wolf optimizer with multi-population differential evolution for global optimization problems
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Study of Fatigue and Bending Properties For Epoxy / Kevlar - Glass Fibers and Hybrid Composite
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In this research a study of the effect of quality, sequential and directional layers for three types of fibers are:(Kevlar fibers-49 woven roving and E- glass fiber woven roving and random) on the fatigue property using epoxy as matrix. The test specimens were prepared by hand lay-up method the epoxy resin used as a matrix type (Quick mast 105) in prepared material composit . Sinusoidal wave which is formed of variable stress amplitudes at 15 Hz cycles was employed in the fatigue test ( 10 mm )and (15mm) value 0f deflection arrival to numbers of cycle failure limit, by rotary bending method by ( S-N) curves this curves has been determined ( life , limit and fa

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Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Engineering
A Hybrid Coefficient Decimation- Interpolation Based Reconfigurable Low Complexity Filter Bank for Cognitive Radio
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Non uniform channelization is a crucial task in cognitive radio receivers for obtaining separate channels from the digitized wideband input signal at different intervals of time. The two main requirements in the channelizer are reconfigurability and low complexity. In this paper, a reconfigurable architecture based on a combination of Improved Coefficient Decimation Method (ICDM) and Coefficient Interpolation Method (CIM) is proposed. The proposed Hybrid Coefficient Decimation-Interpolation Method (HCDIM) based filter bank (FB) is able to realize the same number of channels realized using (ICDM) but with a maximum decimation factor divided by the interpolation factor (L), which leads to less deterioration in stop band at

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Publication Date
Fri Jan 01 2016
Journal Name
Modern Applied Science
Hybrid Methodology for Image Segmentation Based on Active Contour Module and Alpha-Shape Theory
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The concept of the active contour model has been extensively utilized in the segmentation and analysis of images. This technology has been effectively employed in identifying the contours in object recognition, computer graphics and vision, biomedical processing of images that is normal images or medical images such as Magnetic Resonance Images (MRI), X-rays, plus Ultrasound imaging. Three colleagues, Kass, Witkin and Terzopoulos developed this energy, lessening “Active Contour Models” (equally identified as Snake) back in 1987. Being curved in nature, snakes are characterized in an image field and are capable of being set in motion by external and internal forces within image data and the curve itself in that order. The present s

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