Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutilized crossbar regions and supports rapid on-chip training within two clock cycles. This research also leverages plasticity mechanisms such as neurogenesis and homeostatic intrinsic plasticity to strengthen the robustness and performance of the SP. The proposed design is benchmarked for image recognition tasks using Modified National Institute of Standards and Technology (MNIST) and Yale faces datasets, and is evaluated using different metrics including entropy, sparseness, and noise robustness. Detailed power analysis at different stages of the SP operations is performed to demonstrate the suitability for mobile platforms.
Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University
... Show MoreThe convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog
... Show MoreGenome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id
... Show MoreSorghum seeds suffer from a low germination ratio, so a factorial experiment was carried out in the Seed Technology Laboratory, Department of Field Crops, College of Agricultural Engineering Sciences, University of Baghdad during 2022 according to a Completely Randomized Design with four replications to study the effect of stimulating seeds with aqueous extract of banana peels with a concentration of (0, 15, 25 and 35%) and citric acid at concentrations (0, 50, 100 and 200 mg L-1) on viability and vigour of seed properties. Seeds that soaked with banana peel extract at a concentration of 25% outperformed in first count (79.8%), final count (85.0%), radicle length (13.2 cm), plumule length (11.6 cm), and seedling vigour index (2109), noting
... Show MoreGermination and field emergence are delayed and their duration is prolonged due to the declining soil temperature during the spring season, which is reflected in the subsequent stages of crop growth, therefore, this study aimed to improve germination. Under a wide range of environmental conditions, a laboratory factorial experiment was carried out to study the effect of seed stimulation with potassium nitrate (distilled water only (0), 2, 4, and 6 mg L-1) and with an aqueous extract of licorice roots (distilled water only (0), 3, 6, and 9 g L-1) on the seed viability and vigor. The laboratory experiment was carried out according to the Completely Randomized Design (CRD) with four repetitions. The results showed the superiority of the intera
... Show MoreThe current research aimed to conducting two experiments to study the effect of coating hatching eggs with nano-titanium dioxide (nano-TiO2) and nano-silica dioxide (nano-SiO2) particles and their mixture with carboxymethyl cellulose (CMC) on the characteristics of hatching percentage, embryo growth inside the egg. The study was conducted in the Department of Animal Production, College of Agriculture, Tikrit University for the period from 19/3/2023 to 17/9/2024. It aimed to evaluate the coating of hatching eggs with Nano-TiO2 and Nano-SiO2 particles and their mixture with carboxymethyl cellulose CMC on the qualities of hatching percentage, embryo growth inside the egg, as well as trying to obtain the best and longest storage method for fert
... Show MoreThis experiment was carried out at a private field in the eastern Radwaniyah Baghdad for the fall season 2020/2021 and spring 2021 to study the effects of adding mineral fertilizers, spraying salicylic acid and amino acids on some growth traits and yield of industrial potato plants. 200 kg N h-1 , 100 kg P2O5 h-1, 100 kg K2O h-1 and F2 consist of 275 kg N h-1, 180 kg P2O5 h-1, 200 K2O h-1 and F3 consist of 350 kg N h-1, 360 kg P2O5 h-1, 300 K2O h-1 and salicylic acid in three concentrations of 0,50 and 100 mg L-1 ( S1, S2, S3) and amino acids in three concentrations of 0, 1.25 and 2.5 ml L-1 ( A1, A2 , A3) It was carried out as a factorial split plot experiment, where the fertilizer levels (F1, F2 and F3) are in the main plot and th
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