Image retrieval is used in searching for images from images database. In this paper, content – based image retrieval (CBIR) using four feature extraction techniques has been achieved. The four techniques are colored histogram features technique, properties features technique, gray level co- occurrence matrix (GLCM) statistical features technique and hybrid technique. The features are extracted from the data base images and query (test) images in order to find the similarity measure. The similarity-based matching is very important in CBIR, so, three types of similarity measure are used, normalized Mahalanobis distance, Euclidean distance and Manhattan distance. A comparison between them has been implemented. From the results, it is conclud

Abstract

In this study, mucilage was extracted from Malabar spinach and tested for drag-reducing properties in aqueous liquids flowing through pipelines.  Friction produced by liquids flowing in turbulent mode through pipelines increase power consumption. Drag-reducing agents (DRA) such as polymers, suspended solids and surfactants are used to reduce power losses. There is a demand for natural, biodegradable DRA and mucilage is emerging as an attractive alternative to conventional DRAs. Literature review revealed that very little research has been done on the drag-reducing properties of this mucilage and there is an opportunity to explore the potential applications of mucilage from Malabar spinach. An experi

In this work, copper substituted cobalt ferrite nanoparticles with
chemical formula Co1-xCuxFe2O4 (x=0, 0.3, and 0.7), has been
synthesized via hydrothermal preparation method. The structure of
the prepared materials was characterized by X-ray diffraction (XRD).
The (XRD) patterns showed single phase spinel ferrite structure.
Average crystallite size (D), lattice constant (a), and crystal density
(dx) have been calculated from the most intense peak (311).
Comparative standardization also performed using smaller average
particle size (D) on the XRD patterns of as-prepared ferrite samples
in order to select most convenient hydrothermal synthesis conditions
to get ferrite materials with smallest average particl

              In this work, pure and doped Vanadium Pentoxide (V₂O₅) thin films with different concentration of TiO₂ (0, 0.1, 0.3, 0.5) wt  were obtained using Pulse laser deposition technique on amorphous glass substrate with thickness of (250)nm. The morphological, UV-Visible and Fourier Transform Infrared Spectroscopy (FT-IR) were studied. TiO₂ doping into V₂O₅ matrix revealed an interesting morphological change from an array of high density pure V₂O₅ nanorods (~140 nm) to granular structure in TiO₂-doped V₂O₅ thin film .Transform Infrared Spectro

Micro metal forming has an application potential in different industrial fields. Flexible tool-assisted sheet metal forming at micro scale is among the forming techniques that have increasingly attracted wide attention of researchers. This forming process is a suitable technique for producing micro components because of its inexpensive process, high quality products and relatively high production rate. This study presents a novel micro deep drawing technique through using floating ring as an assistant die with flexible pad as a main die. The floating ring designed with specified geometry is located between the process workpiece and the rubber pad. The function of the floating ring in this work is to produce SS304 micro cups with profile

Excess molar volumes of five ternary mixtures of 2- methoxy ethanol(1) +butyl acetate(2)+benzene(3), +toluene(3), +chlorobenzene(3), +bromobenzene(3), and +nitrobenzene(3) have been measured at 303.15K. The excess molar volume exhibited positive deviation over the entire range of composition in the systems 2-methoxy ethanol(1)+ butyl acetate(2)+ benzene(3),+toluene(3) and sigmoid behavior in the case of the remaining systems. Flory's statistical theory have been extended to predict the excess molar volumes of the five ternary mixtures at 303.15 k over a wide range of composition . An excellent agreement has been found between the experimental and theoretical excess molar volumes , both in magnitude and sign .

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class