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

Forty eight isolates (41.02%) were obtained from 117 wound and burn samples. The isolates that showed high resistance for both antibiotic was two only that represent 4,1% from all isolates. The result of PCR product electrophoresis was referred that the gene is VIM gene. Lactose and raffinose showed double increasing in diameter of inhibition zone of imipenem with 1% that mean showed highest susceptibility that decreased with the concentration increasing, the same result were with meropenem. But no effect were detected on meropenem inhibition zone diameter. Mannose have no effect on the resistance in 1%, 3% and 7%. Results showed that only three case that increase the expression of gene, they were lactose at 1% concentration that increased

        End Stage Renal Disease is a well-known global public health problem. Maintenance hemodialysis is considered a life-saving treatment for patients with such disease. This treatment method that requires patients to be adherent to hemodialysis attendance, dietary and fluid recommendations as well as adherence to prescribed medications to ensure success. The aim of the current study was to assess adherence, perception, and counseling among hemodialysis patients to different modalities of treatment (fluid restriction, dietary recommendations, medications, and hemodialysis schedules). A cross-sectional study carried out on hemodialysis patients who attended to the dialysis centers at al- Karama teachi

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

  Empirical research in the disciplines of art and design has started to escalate and gather consideration within the academic community over the past few decades. However, still, graphic design tends to be a topic extremely under-researched by scholarly persons. Profound research in the field of graphic design extends far beyond the works produced by the designer himself (Khoury, 2009, p.844). In order to develop a clear insight, one needs to delve deep into the subcategories that the diverse field of graphic design is comprised of, including illustration, typography, interaction design, branding and even the impact of notable, eminent institutes from around the world that have taken the budding artists for quite a long time (Walke

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

The use of appropriate and accurate language is of utmost importance when describing people on the move and their dilemma, particularly refugees and displaced persons who have unique legal protection. So, there are a lot of scholars who have investigated the United Nations High Commissioner for Refugees’ (UNHCR) reports, but no one has examined representational and interactional meanings of UNHCR reports. Accordingly, this research aims to explore the role of UNHCR reports in enhancing the value of the humanitarian, which is attributed to the uniqueness of its use of language. The current study investigates the manner in which the textual content interacts with the images that are associated with the category of the UNHCR reports. Four re

Research in Iraq has expanded in the field of material technology involving the properties of the lightweight concrete using natural aggregate. The use of the porcelinate aggregate in the production of structural light concrete has a wide objective
and requires a lot of research to become suitable for practical application. In this work metakaolin was used to improve compressive strength of lightweight porcelinate concrete which usually have a low compressive strength about 17 MPa . The effect of metakaolin on compressive, splitting tensile, flexure strengths and modulus of elasticity of lightweight porcelinate concrete have been investigated. Many experiments were carried out by replacing cement with different percentages of
met

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima