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

In this study, gold nanoparticle samples were prepared by the chemical reduction method (seed-growth) with 4 ratios (10, 12, 15 and 18) ml of seed, and the growth was stationary at 40 ml. The optical and structural properties of these samples were studied. The 18 ml seed sample showed the highest absorbance. The X- ray diffraction (XRD) patterns of these samples showed clear peaks at (38.25^o, 44.5^o, 64.4^o, and 77.95^o). The UV-visible showed that the absorbance of all the samples was in the same range as the standard AuNPs. The field emission-scanning electron microscope (FE-SEM) showed the shape of AuNPs as nanorods and the particle size between 30-50 nm. Rhodamine-610 (RhB) was prepared at 10<

This paper aims at the fact that most organizations today suffer from a waste of time, effort, and cost, and they have difficulty in achieving the best performance situations and compete strongly. The researcher distributed 108 questionnaires as a statistical analyzable sample society where the sample intentionally consists of general managers, department head, and division head. The questionnaire was formulated according to the Likert scale. The use of personal interviews and observations are additional tools for data collection and a number of statistical methods is used for data analysis such as simple regression and correlation coefficient (Pearson). One of the most prominent conclusions is that the company has adequate and c

Tin oxide films (SnO2) of thickness (1 ?m) are prepared on glass substrate by post oxidation of metal films technique. Films were irradiated with Nd:YAG double frequency laser of wavelength (532 nm) pulses of three energies (100, 500, 1000) mJ. The optical absorption, transmission, reflectance, refractive index and optical conductivity of these films are investigated in the UV-Vis region (200-900) nm. It was found that the average transmittance of the films is around (80%) at wavelength (550 nm) and showed high transmission (? 90 %) in the visible and near infrared region. The absorption edge shifts towards higher energies, which is due to the Moss-Burstien effect and it lies at (4 eV). The optical band gap increased with increasing of ene

ABSTRACT Porous silicon has been produced in this work by photochemical etching process (PC). The irradiation has been achieved using ordinary light source (150250 W) power and (875 nm) wavelength. The influence of various irradiation times and HF concentration on porosity of PSi material was investigated by depending on gravimetric measurements. The I-V and C-V characteristics for CdS/PSi structure have been investigated in this work too.

The D.C electrical and thermoelectrically properties of randomly mixed isolator – electrolyte system as (Al/ PVC – LiF/Al) junction consisting of polyvinyl chloride (PVC)resin reinforced with Lithium Fluoride (LiF) powder were studied. A comparison is made the properties of (PVC) material with varying percentage of (LiF) powder (0%, 30%, 50%, 80%)to find out the effect of reinforcement of isolator material. The composites dissolving in 10ml form tettraHaedroflourn (THF) and Solution were the castled in Petri dish and Laved it dry in the air, The out coming Sample were disc - Like shape of a diameter of about 3cm and thickness reneged between (0.01- 0.018) cm . The composites dissolving in 10ml form tettraHaedroflourn (THF) a