In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of how the

This paper focuses on the optimization of drilling parameters by utilizing “Taguchi method” to obtain the minimum surface roughness. Nine drilling experiments were performed on Al 5050 alloy using high speed steel twist drills. Three drilling parameters (feed rates, cutting speeds, and cutting tools) were used as control factors, and L9 (3³) “orthogonal array” was specified for the experimental trials. Signal to Noise (S/N) Ratio and “Analysis of Variance” (ANOVA) were utilized to set the optimum control factors which minimized the surface roughness. The results were tested with the aid of statistical software package MINITAB-17. After the experimental trails, the tool diameter was found as the most important facto

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

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

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

Mixed ligand of Co and Ni (II) complexes were prepared from [5-(p-nitrophenyl)-4/-phenyl-1,2,4-triazole-3-dithiocarbamato hydrazide](TRZ.DTC) as primary ligand and 2,2'-bipyridyl (bipy) as a co-ligand with metal salts. These complexes were analytically and spectroscopically characterized in solid state by elemental analyses, flame atomic absorption, magnetic susceptibility and molar conductance measurements, as well as by UV–Vis and FTIR spectroscopy. Infrared, ultra violet spectra reveal a bidentate coordination of the two ligands with metal ions 1:1:1 mole ratio. Room temperature magnetic moments and solid reflectance spectra data indicate paramagnetic complexes with five-coordinate square pyramidal geometry for nickel (II) comple