In this study, nano TiO₂ was prepared with titanium isopropoxide (TTIP) as a resource to titanium oxide. The catalyst was synthesized using phosphotungstic acid (PTA) and, stearyl trimethyl ammonium bromide (STAB) was used as the structure-directing material. Characterization of the product was done by the X-ray diffraction (XRD), X-ray fluorescent spectroscopy (XRF), nitrogen adsorption/desorption measurements, Atomic Force Microscope (AFM) and Fourier transform infrared (FTIR) spectra, were used to characterize the calcined TiO₂ nanoparticles by STAB and PWA. The TiO₂ nanomaterials were prepared in three crystalline forms (amorphous, anatase, anatase-rutile). The results showed that the

The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

Natural settings make it challenging to identify facial expressions since head position, illumination level, and ‎‎occlusion vary. Thus, developing a more generic model without front-facing images alone is quite crucial. This ‎research proposes a facial expression ‎recognition model based on pre-trained deep convolutional neural networks ‎with transfer learning. The model was trained ‎on several cases to classify face expressions into seven ‎classifications efficiently. The proposed system used the EfficientNetB0 model ‎that has one dense dropout layer. The model first rescales and norms the input dataset in the input ‎layer that takes images of a larger resolution to get better results. After entering 7 blocks sequential

Optimized Link State Routing Protocol (OLSR) is an efficient routing protocol used for various Ad hoc networks. OLSR employs the Multipoint Relay (MPR) technique to reduce network overhead traffic. A mobility model's main goal is to realistically simulate the movement behaviors of actual users. However, the high mobility and mobility model is the major design issues for an efficient and effective routing protocol for real Mobile Ad hoc Networks (MANETs). Therefore, this paper aims to analyze the performance of the OLSR protocol concerning various random and group mobility models. Two simulation scenarios were conducted over four mobility models, specifically the  Random Waypoint model (RWP), Random Direction model (RD), Nomadic Co

Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

This paper delves into the significant role played by local social and traditional structures in shaping Traditional Community Tenure (TCT) within Iraqi Land Tenure Legislation (ILTR), and examines their impact on gender inequalities, with a specific focus on women's land tenure rights. The methodological approach employed in this study identified the sources of barriers to gender equality within TCT as outlined in ILTR at two different bilateral levels, with input obtained from key stakeholders in a selected city in Iraq. The case study survey encompassed three districts, which served as local layers within the historic sectors of the Iraqi city of Al-Nasiriya. the study employed quantitative methods, including a household surveyو with

The radial wave functions of the Bear–Hodgson potential have been used to study the ground state features such as the proton, neutron and matter densities and the as- sociated rms radii of two neutrons halo 6He, 11Li, 14Be and 17B nuclei. These halo nuclei are treated as a three-body system composed of core and outer two-neutron (Core + n + n). The radial wave functions of the Bear–Hodgson potential are used to describe the core and halo density distributions. The interaction of core-neutron takes the Bear–Hodgson potential form. The outer two neutrons of 6He and 11Li interact by the realistic interaction REWIL whereas those of 14Be and 17B interact by the realistic interaction of HASP. The obtained results show that this model succee

Competitive swimming is a highly researched area and technological developments have aided advances in the understanding of the biomechanical principles that underpin these elements and govern propulsion. Moreover, those working in the sports field especially in swimming are interested in studying, analyzing, evaluating and developing motor skills by diagnosing the strengths and weaknesses of the skill, and accordingly, coaches and specialists correct these errors. The researchers chose this (Butterfly swimming) and the (arm length) is an important variable because the success of the stroke is greatly dependent on the propulsion generated from the arm pull, and swimmers with a longer arm span have a mechanical advantage with the resulting f