Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

A significant challenge arises in the characterization of urban systems, especially regarding the intricate structures of Central Business Districts (CBDs). Conventional models seem insufficient, failing to comprehend the non-linear, network-oriented structure of the city's economic and social dynamics. This creates a disparity between the city's physical, geographical structure and the unseen processes occurring within it. The fundamental inquiry is thus configurational: how can we systematically examine the inherent spatial logic of the CBD to develop a more efficient and predictive planning model? This paper presents a theoretical and methodological model to explore this inquiry, which focuses on Lower Manhattan as the primary su

A numerical computation for determination transmission coefficient and resonant tunneling energies of multibarriers heterostructure has been investigated. Also, we have considered GaN/Al0.3Ga0.7N superlattice system to estimate the probability of resonance at specific energy values, which are less than the potential barrier height. The transmission coefficient is determined by using the transfer matrix method and accordingly the resonant energies are obtained from the T(E) relation. The effects of both well width and number of barriers (N) are observed and discussed. The numbers of resonant tunneling peaks are generally increasing and they become sharper with the increasing of N. The resonant tunneling levels are shifted inside the well by

A numerical computation for determination transmission coefficient and resonant tunneling energies of multibarriers heterostructure has been investigated. Also, we have considered GaN/Al_0.3Ga_0.7N superlattice system to estimate the probability of resonance at specific energy values, which are less than the potential barrier height. The transmission coefficient is determined by using the transfer matrix method and accordingly the resonant energies are obtained from the T(E) relation. The effects of both well width and number of barriers (N) are observed and discussed. The numbers of resonant tunneling peaks are generally increasing and they become sharper with the increasing of N. The resonant tunneling levels are sh

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

Ruthenium-Ruthenium and Ruthenium–ligand interactions in the triruthenium "[Ru₃(μ-H)(μ₃-κ²-Hamphox-N,N)(CO)₉]" cluster are studied at DFT level of theory. The topological indices are evaluated in term of QTAIM (quantum theory of atoms in molecule). The computed topological parameters are in agreement with related transition metal complexes documented in the research papers. The QTAIM analysis of the bridged core part, i.e., Ru₃H, analysis shows that there is no bond path and bond critical point (chemical bonding) between Ru(2) and Ru(3). Nevertheless, a non-negligible delocalization index for this non-bonding interaction is calculated

The main objective of this study was to evaluate the adsorption efficiency of two adsorbent materials, Iraqi chicken eggshells (ESh) and activated carbon (AC) derived from ESh powder for the removal of a cationic dye (Janus green B; JGD) from aqueous solution. Activated carbon was synthesised from ESh using a simple chemical activation method using phosphoric acid as the activating agent. The physicochemical properties of the adsorbents were characterised by the Brunauer–Emmett–Teller (BET) method, FT-IR spectroscopy, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), inductively coupled plasma optical emission spectroscopy (ICP-OES), and point of zero charge (pHpzc). The results of BET analysis confirmed th

The main objective of this study was to evaluate the adsorptionefficiency of two adsorbent materials, Iraqi chicken eggshells (ESh)and activated carbon (AC) derived from ESh powder for theremoval of a cationic dye (Janus green B; JGD) from aqueoussolution. Activated carbon was synthesised from ESh usinga simple chemical activation method using phosphoric acid asthe activating agent. The physicochemical properties of the adsor-bents were characterised by the Brunauer–Emmett–Teller (BET)method, FT-IR spectroscopy, scanning electron microscopy(SEM), energy-dispersive X-ray spectroscopy (EDS), inductivelycoupled plasma optical emission spectroscopy (ICP-OES), andpoint of zero charge (pHpzc). The results of BET analysis confirmedthat AC has