Optimization is essentially the art, science and mathematics of choosing the best among a given set of finite or infinite alternatives. Though currently optimization is an interdisciplinary subject cutting through the boundaries of mathematics, economics, engineering, natural sciences, and many other fields of human Endeavour it had its root in antiquity. In modern day language the problem mathematically is as follows - Among all closed curves of a given length find the one that closes maximum area. This is called the Isoperimetric problem. This problem is now mentioned in a regular fashion in any course in the Calculus of Variations. However, most problems of antiquity came from geometry and since there were no general methods to solve suc

The coefficient of performance of a window type Air-Conditioner system can be improved if a reduction in the work of compressor can be achieved by a suitable technique. The present study investigates the effect of dispersing a low concentration of TiO2 nanoparticles in the mineral oil based lubricant, as well as on the overall performance of a window type Air-Conditioner system using R22 as the working fluid. An enhancement in the COP of the refrigeration system has been observed and the existence of an optimum volume fraction noticed, with low concentrations of nanoparticles suspended in the mineral oil. Results showed that the average compressor work reduced by 13.3%, which ultimately resulted in an increase of 11.99% in the COP due to

ِabstract:In this research we prepared nanofibers by electrospinning from poly (Vinyl Alcohol) /TiO2. The spectrum of the solution (Emission) was studied and found to be at 772 nm, several process parameters were such as concentration of TiO2 , and the effect of distance from nozzle tip to the grounded collector (gap distance). The result of the lower concentration of, the smaller the diameter of nanofiber is. Increasing the gap distance will affect nanofibers diameter.

  This paper deals with proposing new lifting scheme (HYBRID Algorithm) that is capable of preventing images and documents which are fraud through decomposing there in to the real colors value arrays (red, blue and green) to create retrieval keys for its properties and store it in the database and then check the document originality by retrieve the query image or document through the decomposition described above and compare the predicted color values (retrieval keys)  of the query document with those stored in the database. The proposed algorithm has been developed from the two known lifting schemes (Haar and D4) by merging them to find out HYBRID lifting scheme. The validity and accuracy of the proposed algorithm have been ev

Background: targeted cancer nanotherapy represents a golden goal for nanobiotechnology to overcome the severe side effects of conventional chemotherapy. Hybrid nanoliposomes (HLs) composed of L-α-dimyristoylphosphatidylcholine (DMPC) and Polyoxyethylene (23) dodecyl ether (C12 (EO)23 ) can integrate selectively into the cancer cell membrane inducing cancer cell death.
Objectives: to assess the capacity of locally (in hose) synthesized hybrid nanoliposome to inhibit the growth of cervix cancer cells (HeLa) and induce apoptosis.
Patients and Methods: hybrid nanoliposomes(nHLs) synthesized by sonication method from a mixture of 90% mol DMPC and 10% mol C12(EO)23 in tissue culture media RPMI-1640 for 6 hours at 300W and 40ºC then fil

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

The rheological behavior among factors that are present in Stokes law can be used to control the stability of the colloidal dispersion system. The felodipine lipid polymer hybrid nanocarriers  (LPHNs) is an interesting colloidal dispersion system that is used for rheological characteristic analysis. The LPHNs compose of polymeric components and lipids. This research aims to prepare oral felodipine LPHNs to investigate the effect of independent variables on the rheological behavior of the nanosystem. The microwave-based technique was used to prepare felodipine LPHNs (H1-H9) successfully. All the formulations enter the characterization process for particle size and PDI to ascertain the colloidal properties of the prepared nanosystem t

 In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F

Carbon Nanopowder was fabricated by arc discharge technique at deposition pressure of 10-5 mbar Argon gas on glass substrates. The prepared carbon nano- powder was collected from chamber and purified with nitric acid at 323K .The morphology and crystalline structure of the prepared powder was examined by X-Ray Diffraction (XRD), Atomic Force Microscope (AFM), and Scanning Electron Microscope (SEM). XRD spectrums showed that the powder exhibits amorphous structure and after purification, the powder showed hexagonal structure with a preferential orientation along(002) direction ,where AFM and SEM gave very compatible estimation on the grain size and shape of the nanopowder.