The penalized least square method is a popular method to deal with high dimensional data ,where  the number of explanatory variables is large than the sample size . The properties of  penalized least square method are given high prediction accuracy and making estimation and variables selection

 At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and

Esterification reaction is most important reaction in biodiesel production. In this study, oleic acid was used as a suggested feedstock to study and simulate production of biodiesel. Batch esterification of oleic acid was carried out at operating conditions; temperature from 40 to 70 °C, ethanol to oleic acid molar ratio from 1/1 to 6/1, H2SO4 as the catalyst 1 and 5% wt of oleic acid, reaction time up to 180 min. The optimum conditions for the esterification reaction were molar ratio of ethanol/oleic acid 6/1, 5%wt H2SO4 relative to oleic acid, 70 °C, 90 min and conversion of oleic 0.92. The activation energy for the suggested model was 26625 J/mole for forward reaction and 42189 J/mole for equilibrium constant. The obtained results s

Design sampling plan was and still one of most importance subjects because it give lowest cost  comparing with others, time live statistical distribution should be known to give best estimators for  parameters of sampling plan and get best sampling plan.

Research dell with design sampling plan when live time distribution follow Logistic distribution with () as location and shape parameters, using these information can help us getting (number of groups, sample size) associated with reject or accept the Lot

Experimental results for simulated data shows the least number of groups and sample size needs to reject or accept the Lot with certain probability of

Photoacoustic is a unique imaging method that combines the absorption contrast of light or radio frequency waves with ultrasound resolution. When the deposition of this energy is sufficiently short, a thermo-elastic expansion takes place whereby acoustic waves are generated. These waves can be recorded and stored to construct an image. This work presents experimental procedure of laser photoacoustic two dimensional imaging to detect tumor embedded within normal tissue. The experimental work is accomplished using phantoms that are sandwiched from fish heart or blood sac (simulating a tumor) 1-14mm mean diameter embedded within chicken breast to simulate a real tissue. Nd: YAG laser of 1.064μm and 532nm wavelengths, 10ns pulse duration, 4

   Reservoir characterization plays a crucial role in comprehending the distribution of formation properties and fluids within heterogeneous reservoirs. This knowledge is instrumental in constructing an accurate three-dimensional model of the reservoir, facilitating predictions regarding porosity, permeability, and fluid flow distribution. Among the various methods employed for reservoir characterization, the hydraulic flow unit stands out as a widely adopted approach. By effectively subdividing the reservoir into distinct zones, each characterized by unique petrophysical and geological properties, hydraulic flow units enable comprehensive reservoir analysis. The concept of the flow unit is closely tied to the flow zone indicator, a cr

A simulated ion/electron optical transport and focusing system has been put forward to
be mounted on high voltage transmission electron microscope for in situ investigations.
The suggested system consists of three axially symmetric electrostatic lenses namely an
einzel lens, an accelerating immersion lens, and a decelerating immersion lens, in addition
to an electrostatic quadrupole doublet lens placed on the image side. The electrodes
profile of these lenses is determined from the proposed axial field distributions. The
optical properties of the whole system have been computed together with the trajectory of
the accelerated charged-particles beam along the optical axis of the system. The computed
dimensions of th

One and two-dimensional hydraulic models simulations are important to specify the hydraulic characteristics of unsteady flow in Al-Gharraf River in order to define the locations that facing problems and suggesting the necessary treatments. The reach in the present study is 58200m long and lies between Kut and Hai Cities. Both numerical models were simulated using HEC-RAS software, 5.0.4, with flow rates ranging from 100 to 350 m³/s. Multi-scenarios of gates openings of Hai Regulator were applied. While the openings of Al-Gharraf Head Regulator were ranged between 60cm to fully opened. The suitable manning roughness for the unsteady state was

The uniform flow distrbiution in the multi-outlets pipe highly depends on the several parameters act togather. Therefor, there is no general method to achieve this goal. The  goal of this study is to investigate the proposed approach that can provide significant relief of the maldistribution. The method is based on re-circulating portion of flow from the end of the header to reduce pressure at this region . The physical model consists of main manifold with uniform longitudinal section having diameter of 152.4 mm (6 in), five laterals with diameter of 76.2 mm (3 in), and spacing of 300 mm. At first, The experiment is carried out with conventional manifold, which is a closed-end. Then, small amount of water is allowed

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se