With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

A range of batch experiments were carried out for the estimation of the key process parameters in adsorption of Furfural from aqueous solution onto activated carbon in fixed-bed adsorber. A batch absorber model has been used to determine the external mass transfer coefficient (kf) which equal to 6.24*10-5 m/s and diffusion coefficient (Dp) which equal to 9.875*10-10 m2/s for the Furfural system. The Langmuir model gave the best fit for the data at constant temperature (30oC). The pore diffusion mathematical model using nonlinear isotherm provides a good description of the adsorption of Furfural onto activated carbon.

Goal  of  research  is  to  investigate  the  impact  of the  use  of  effective  learning  model in the  collection  of  the  fourth  grade  students/Department of  physics in the material  educational methods  and the  development  of  critical thinking  .to teach  this goal  has  been  formulated  hypothesis cefereeten zero  subsidiary  of the second hypothesis  .To  investigate  the  research  hypothesis  were  selected  sample  of  fourth-grade  students of the  department  of physics at the univers

Land Use / Land Cover (LULC) classification is considered one of the basic tasks that decision makers and map makers rely on to evaluate the infrastructure, using different types of satellite data, despite the large spectral difference or overlap in the spectra in the same land cover in addition to the problem of aberration and the degree of inclination of the images that may be negatively affect rating performance. The main objective of this study is to develop a working method for classifying the land cover using high-resolution satellite images using object based method. Maximum likelihood pixel based supervised as well as object approaches were examined on QuickBird satellite image in Karbala, Iraq. This study illustrated that

Background: Antibacterial action of root canal filling is an important factor for successful root canal treatment, so the aim of the study was to identify and to compare the antimicrobial effect of new sealer (GuttaFlow) to commonly used endodontic sealers (AH Plus, Apexit and EndoFill) against four endodontic microbes. Materials and methods: Twenty patients aged (30-40) years with infected root canals were selected. Four types of microorganisms were isolated from root canals (E faecalis, Staphylococcus aureus, E coli and Candida albicans) and cultured on Mueller Hinton agar Petri-dishes. After identification and isolation of bacterial species, agar diffusion method was used to assess the antibacterial action of four contemporary endodontic

This paper deals with the Magnetohydrodynyamic (Mill)) flow for a viscoclastic fluid of the generalized Oldroyd-B model. The fractional calculus approach is used to establish the constitutive relationship of the non-Newtonian fluid model. Exact analytic solutions for the velocity and shear stress fields in terms of the Fox H-function are obtained by using discrete Laplace transform. The effect of different parameter that controlled the motion and shear stress equations are studied through plotting using the MATHEMATICA-8 software.

A modification to cascaded single-stage distributed amplifier (CSSDA) design by using active inductor is proposed. This modification is shown to render the amplifier suitable for high gain operation in small on-chip area. Microwave office program simulation of the Novel design approach shows that it has performance compatible with the conventional distributed amplifiers but with smaller area. The CSSDA is suitable for optical and satellite communication systems.

The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat