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

Due to restrictions and limitations on agricultural water worldwide, one of the most effective ways to conserve water in this sector is to reduce the water losses and improve irrigation uniformity. Nowadays, the low-pressure sprinkler has been widely used to replace the high-pressure impact sprinklers in lateral move sprinkler irrigation systems due to its low operating cost and high efficiency. However, the hazard of surface runoff represents the biggest obstacle for low-pressure sprinkler systems. Most researchers have used the pulsing technique to apply variable-rate irrigation to match the crop water needs within a normal application rate that does not produce runoff. This research introduces a variable pulsed irrigation algorit

In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

Jumping ability is a fundamental variable in many sports, as its execution requires an integration of muscular strength Q1 and certain biomechanical variables. This is particularly evident in gymnastics jumping events and jump shots in ball games, both of which rely on a high level of vertical resistance. Vertical resistance serves as an indicator of an athlete’s ability to overcome their body weight while counteracting gravitational force to achieve optimal performance. As such, it is considered one of the key factors in movements that demand explosive power and speed. The researchers believe that despite the significant relationship between vertical resistance, speed-strength of the arms and legs, and certain biomechanical varia

Background: Axial spondyloarthritis (axSpA) is an inflammatory, systemic rheumatic condition that mostly affects the axial skeleton. Tenascin-C (TN-C) is a hexameric glycoprotein of considerable size, upregulated in many inflammatory conditions, while Interleukin-17 (IL-17) a cytokine that plays an important role in SpA symptoms. Objective: to investigate the upregulation between the serum levels of TN-C and IL-17 in Iraqi axSpA patients and the disease characteristics. Patients and Methods: Seventy-four axSpA patients and 28 matched controls were studied. Fifty-four patients received a tumor necrosis factor inhibitor (TNFi) and 20 did not. Serum TN-C and IL-17 concentrations were determined using the ELISA technique. The Bath Ankyl

The purpose of this research shed light on the analysis of the relationship between the knowledge gap and the strategic performance  gap and diagnose the level of impact this relationship in building a learning organization, and sought search to achieve a number of goals, cognitive and Applied been tested nature of the relationship and effect between variables in a sample size (62) of the managers of banks civil in Baghdad (Baghdad, Gulf, Assyria, Union, Elaf) and focused research problem in question is bold is whether the analysis of the relationship between the knowledge gap and the performance gap strategic leads to recognize organizations need to shift to organizations educated, either in the side of the field was the pr

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a

The application of the test case prioritization method is a key part of system testing intended to think it through and sort out the issues early in the development stage. Traditional prioritization techniques frequently fail to take into account the complexities of big-scale test suites, growing systems and time constraints, therefore cannot fully fix this problem. The proposed study here will deal with a meta-heuristic hybrid method that focuses on addressing the challenges of the modern time. The strategy utilizes genetic algorithms alongside a black hole as a means to create a smooth tradeoff between exploring numerous possibilities and exploiting the best one. The proposed hybrid algorithm of genetic black hole (HGBH) uses the