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 unutil

This study was conducted in a laboratory experiment at the University of Baghdad, College of Science, computing Department, 5 km from the center of Baghdad city, in 2021 to evaluate the sorting method for the tomato crop. The experiments were conducted in a factorial experiment under a complete randomized design with three replications and using SAS analysis, artificial neural network, image processing, the study of external characteristics, and physical features; fruit surface area and fruit circumference were 1334.46 cm2,57.53 cm2 and free diseases. The error value was less than zero, while training with outputs recorded the highest value and which was 5. The neural network's performance between the input and the mean square of th

Bromelain is a proteolytic enzyme rich in cysteine proteases, extracted from the stem and fruit of pineapple (Ananas comosus). There are several therapeutic applications of the bromelain enzyme, where it has anti-inflammatory, anti-cancer, and antimicrobial activity, reduces joint pain, and accelerates wound healing. In the current study, bromelain enzyme was loaded on silver nanoparticles (Br-AgNPs) prepared using the citrate-reduction Turkevich method. Different characterization analyses were performed, including UV-Vis spectrophotometers, FTIR, SEM, and XRD analyses. Moreover, the antioxidant activity of prepared Br-AgNPs was evaluated by DPPH assay. The results of UV-Vis showed a peak at 434 nm, which referred to the AgNPs f

The results of studying the effects of M. anisopiliae spores on mosquito, C. quinquefasciatus showed a biological effects represented by immature mortality. The mortality increased proportionally with the concentrations of fungal spores, which reached (at high concentration 2×1011 spores / ml), to 86.6, 56.6% in first and late instar larvae, respectively. An important to mention that cumulative death rate was significantly associated with the time, which reached to 56% at 7 day after treatment. In addition, M. anisopiliae had a long period permanence in aquatic habitats; in which the residual effects stay 30 days in aquatic habitats after treatment at laboratory conditions. Interestingly, the long period exposure of fungal spores (30 minut

The study includs,effect of concentration of Lead 0.2 ,0.3 , 0.5, 5 , 10 mg/L and Zinc 0.1,0.5 , 2 , 4 , 8 mg/L lonely or to gether on growth green algae( Scenedesmus quadricauda var . longispina) according to the total qauntity for the cells and the adsorption of the algae to the zn,pb concentration .growth curve and dubbling time growth were calculated with or without there heavy metals . Results shows that there are significant differences (P<0.01) for growth curve and the control. (7.5201 cell /h)and with dubbling times (9.87 cell/h). The heavy metals(Pb, Zn). shows antagonistic effect when both used in media.

The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o