In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

Biosignal analysis is one of the most important topics that researchers have tried to develop during the last century to understand numerous human diseases. Electroencephalograms (EEGs) are one of the techniques which provides an electrical representation of biosignals that reflect changes in the activity of the human brain. Monitoring the levels of anesthesia is a very important subject, which has been proposed to avoid both patient awareness caused by inadequate dosage of anesthetic drugs and excessive use of anesthesia during surgery. This article reviews the bases of these techniques and their development within the last decades and provides a synopsis of the relevant methodologies and algorithms that are used to analyze EEG sig

Asphaltene is one of the fractions of the crude oil which is soluble in aromatics such as benzene or toluene and insoluble in alkane such as n-heptane, n-pentane or petroleum ether (mixture of alkane compounds).  Asphaltene precipitation is one of the most common problems that sometimes occurs in both oil recovery and refinery processes as a result of changing in pressure, oil composition, or temperature. Therefore the stability of asphaltene in the crude oil must be studied to show the tendency of it for precipitating asphaltene to prevent it (Asphaltene precipitation and deposition problem) and eliminate the burden of high treatment costs.

In the present study, saturate, aromatic, resin and asphaltene (SAR

This article investigates the development of the following material properties of concrete with time: compressive strength, tensile strength, modulus of elasticity, and fracture energy. These properties were determined at seven different hydration ages (18 h, 30 h, 48 h, 72 h, 7 days, 14 days, 28 days) for four pure cement concrete mixes totaling 336 specimens tested throughout the study. Experimental data obtained were used to assess the relationship of the above properties with the concrete compressive strength and how these relationships are affected with age. Further, this study investigates prediction models available in literature and recommendations are made for models that are found suitable for application to early age conc

Objectives To quantify the reproducibility of the drill calibration process in dynamic navigation guided placement of dental implants and to identify the human factors that could affect the precision of this process in order to improve the overall implant placement accuracy. Methods A set of six drills and four implants were calibrated by three operators following the standard calibration process of NaviDent® (ClaroNav Inc.). The reproducibility of the position of each tip of a drill or implant was calculated in relation to the pre-planned implants’ entry and apex positions. Intra- and inter-operator reliabilities were reported. The effects of the drill length and shape on the reproducibility of the calibration process were also investig

Warm mix asphalt (WMA) is relatively a new technology which enables the production and compaction of asphalt concrete mixtures at temperatures 15-40 °C lower than that of traditional hot mix asphalt HMA. In the present work, six asphalt concrete mixtures were produced in the mix plant (1 ton each) in six different batches. Half of these mixes were WMA and the other half were HMA.  Three types of fillers (limestone dust, Portland cement and hydrated lime) were used for each type of mix. Samples were then taken from these patches and transferred to lab for performance testing which includes: Marshall characteristics, moisture susceptibility (indirect tension test), resilient modulus, permanent deformation (axial repeated load test)

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe