Extracting moving object from video sequence is one of the most important steps
in the video-based analysis. Background subtraction is the most commonly used
moving object detection methods in video, in which the extracted object will be
feed to a higher-level process ( i.e. object localization, object tracking ).
The main requirement of background subtraction method is to construct a
stationary background model and then to compare every new coming frame with it
in order to detect the moving object.
Relied on the supposition that the background occurs with the higher appearance
frequency, a proposed background reconstruction algorithm has been presented
based on pixel intensity classification ( PIC ) approach. First, pixel intensity in a
predetermined time period has been classified according to a proposed clustering
method, second, pixels frequency of those clusters has been calculated, finally, the
center of the cluster with the higher pixel frequency has been chosen as the
background pixel intensity value.
The efficiency and effectiveness of the proposed algorithm has been confirmed
through comparing its results with those of the most common traditional methods,
besides , the results of the proposed algorithm in a number of testing environment
which are traffic monitoring and pedestrian surveillance shows that the proposed
algorithm can save space and economize computation time and give good accuracy.
Light is an important factor that influences the growth and photosynthetic efficiency of microalgae; however, little is known about how light intensity together with the wavelength affect the photosynthetic capacity and growth of marine microalgae. In the present study, the growth of the marine green microalga Dunaliella parva was studied and optimized under different light intensities (25 ~ 70 μmol m-2 s-1) and qualities (blue, green, and red) in comparison with white light at 40 μmol m-2 s-1 as a control. The growth was monitored by counting the cell number, pigment content, Chl a, Chl b, and carotenoids concentrations. The optimal growth and highest photosyntheti
... Show MoreIn this research we assumed that the number of emissions by time (𝑡) of radiation particles is distributed poisson distribution with parameter (𝑡), where < 0 is the intensity of radiation. We conclude that the time of the first emission is distributed exponentially with parameter 𝜃, while the time of the k-th emission (𝑘 = 2,3,4, … . . ) is gamma distributed with parameters (𝑘, 𝜃), we used a real data to show that the Bayes estimator 𝜃 ∗ for 𝜃 is more efficient than 𝜃̂, the maximum likelihood estimator for 𝜃 by using the derived variances of both estimators as a statistical indicator for efficiency
This work was conducted to study the extraction of eucalyptus oil from natural plants (Eucalyptus camadulensis leaves) by organic solvents. the effects of the main operating parameters were studied; type of solvent (n-hexane and ethanol), time to reach equilibrium, the temperature (45°C to 65°C) for n-hexane and (45°C to 75°C) for ethanol, solvent to solid ratio (5:1 to 8:1 (v/w)), agitation speed (0 to 900 rpm) and the particle size (0.5 to 2.5 cm) of fresh leaves to find the best processing conditions for the achieving maximum oil yield. The concentration of eucalyptus oil in solvent was measured by using UV-spectrophotometer. The results (for n-hexane) showed that the agitation speed of 900 rpm, temperature 65°C with solvent to soli
... Show MoreAbstract: The aim of the current research is to identify (the relationship between deep understanding skills and mathematical modeling among fifth grade students) the research sample consisted of (411) male and female students of the fifth grade of biology distributed over the General Directorates of Education in Baghdad / Al-Rusafa / 2 / and Al-Karkh / 1 /, and two research tools were built: 1- A test of deep understanding skills, consisting of (20) test items and a scale for two skills. 2- The second test consists of (24) test items distributed among (18) essay items and (6) objective items. The psychometric properties of validity, stability, discriminatory strength, and effectiveness of alternatives were verified for the two tests fo
... Show MoreA total of 48 experiments were conducted to investigate the impact of slit weir dimensions and locations on the maximum scour depth and scour area created upstream. The slit weir model was a 110 mm slit opening, and it was installed at the end of the working section in a laboratory flume. The flume was 10.0 m long, 30 cm wide, 30 cm deep, and almost middle. It includes a 2 m working section with a mobile bed with 110 mm in thickness. In the mobile bed, two types of nonuniform sand (with a geometric standard deviation of 1.58 and 1.6) were tested separately. The weir dimensions and location were changed with flow rates. Then dimensions of the slit weir were changed from 60 x 110 mm to 60 x 70 mm (width x height), while th
... Show MoreThe incorporation of safety characteristics into the traditional pavement structural design or in the functional evaluation of pavement condition has not been established yet. The design has focused on the structural capacity of the roadway so that the pavement can withstand specific level of repetitive loading over the design life. On the other hand, the surface texture condition was neither included in the AASHTO design procedure nor in the present serviceability index measurements.
The pavement surface course should provide adequate levels of friction and ride quality and maintain low levels of noise and roughness. Many transportation departments perform routine skid resistant testing, the type of equipment us
... Show MoreThe adult worms of the Microphallidae family are mainly found as intestinal parasites of birds and mammals, while metacercariae is most commonly found in decapodal crustaceans. The Microphallidaeare family is spread throughout the world. It includes approximately 47 genera. Mature worms usually enter the digestive system of vertebrates, especially birds and mammals. Microphallidae contain eight subfamilies: Androcotylinae - Basantisiinae - Endocotylinae - Gynaecotylinae - Levinseniellinae - MaritrematinaeMicrophallinae - Sphairiotrematinae. Therefore, due to the lack of studies on the Microphallidae family in Iraq, we began to develop a database on this important family.
Knowledge of the mineralogical composition of a petroleum reservoir's formation is crucial for the petrophysical evaluation of the reservoir. The Mishrif formation, which is prevalent in the Middle East, is renowned for its mineralogical complexity. Multi-mineral inversion, which combines multiple logs and inversions for multiple minerals at once, can make it easier to figure out what minerals are in the Mishrif Formation. This method could help identify minerals better and give more information about the minerals that make up the formation. In this study, an error model is used to find a link between the measurements of the tools and the petrophysical parameters. An error minimization procedure is subsequently applied to determine
... Show MoreThe recent development in communication technologies between individuals allows for the establishment of more informal collaborative map data projects which are called volunteered geographic information (VGI). These projects, such as OpenStreetMap (OSM) project, seek to create free alternative maps which let users add or input new materials to the data of others. The information of different VGI data sources is often not compliant to any standard and each organization is producing a dataset at various level of richness. In this research the assessment of semantic data quality provided by web sources, e.g. OSM will depend on a comparison with the information from standard sources. This will include the validity of semanti
... Show MoreThe transition of customers from one telecom operator to another has a direct impact on the company's growth and revenue. Traditional classification algorithms fail to predict churn effectively. This research introduces a deep learning model for predicting customers planning to leave to another operator. The model works on a high-dimensional large-scale data set. The performance of the model was measured against other classification algorithms, such as Gaussian NB, Random Forrest, and Decision Tree in predicting churn. The evaluation was performed based on accuracy, precision, recall, F-measure, Area Under Curve (AUC), and Receiver Operating Characteristic (ROC) Curve. The proposed deep learning model performs better than othe
... Show More