Joining tissue is a growing problem in surgery with the advancement of the technology and more precise and difficult surgeries are done. Tissue welding using laser is a promising technique that might help in more advancement of the surgical practice. Objectives: To study the ability of laser in joining tissues and the optimum parameters for yielding good welding of tissues. Methods: An in-vitro study, done at the Institute of Laser, Baghdad University during the period from October 2008 to February 2009. Diode and Nd-YAG lasers were applied, using different sessions, on sheep small intestine with or without solder to obtain welding of a 2-mm length full thickness incision. Different powers and energies were used to get maximum effect. Results: Welding of sheep intestine had been achieved by Nd-YAG laser 1064 nm at 400 and 500 mJ and PRR 4Hz, using human albumin 20% as a solder. Welding failed using the diode laser 4W for 10 min with albumin and indocyanine green. Conclusion: Laser may be useful tool in certain condition for joining tissue and wound closure. This is important because in certain circumstances no other technique is feasible for wound closure.
Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file. In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,
... Show MoreA content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a
... Show MoreIn this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce
Paper Type: Review article.
another suggestion based on artificial neural networks.
The current study performs an explicit nonlinear finite element simulation to predict temperature distribution and consequent stresses during the friction stir welding (FSW) of AA 7075-T651 alloy. The ABAQUS® finite element software was used to model and analyze the process steps that involve plunging, dwelling, and traverse stages. Techniques such as Arbitrary Lagrangian–Eulerian (ALE) formulation, adaptive meshing, and computational feature of mass scaling were utilized to simulate sequence events during the friction stir welding process. The contact between the welding tool and workpiece was modelled through applying Coulomb’s friction model with a nonlinear friction coefficient value. Also, the model considered the effect of nonlin
... Show MoreThe current study performs an explicit nonlinear finite element simulation to predict temperature distribution and consequent stresses during the friction stir welding (FSW) of AA 7075-T651 alloy. The ABAQUS® finite element software was used to model and analyze the process steps that involve plunging, dwelling, and traverse stages. Techniques such as Arbitrary Lagrangian–Eulerian (ALE) formulation, adaptive meshing, and computational feature of mass scaling were utilized to simulate sequence events during the friction stir welding process. The contact between the welding tool and workpiece was modelled through applying Coulomb’s friction model with a nonlinear friction coefficient value. Also, the model considered the effect o
... Show More This paper introduces a relation between resultant and the Jacobian determinant
by generalizing Sakkalis theorem from two polynomials in two variables to the case of (n) polynomials in (n) variables. This leads us to study the results of the type: , and use this relation to attack the Jacobian problem. The last section shows our contribution to proving the conjecture.
the banks are one of the public services that must be available in the city to ensure easy financial dealings between citizens and state departments and between the state departments with each other and between the citizens themselves and to ensure easy access to it, so it is very important to choose the best location for the bank, which can serve the largest number of The population achieves easy access. Due to the difficulty of obtaining accurate information dealing with the exact coordinates and according to the country's specific projection, the researcher will resort to the default work using some of the files available in the arcview program
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
... Show MoreIn this work, results of a mathematical analysis of the role of workpiece preheating in laser keyhole welding were presented. This analysis considered the steady-state welding as well as certain range of boundary conditions over which preheating effect would be indicated. This work is an attempt to interpret the role of preheating to increase welding depth and perform keyhole welding with high quality using physical and thermal properties of steel alloys.
Pumping a BBO crystal by a violet diode laser with a wavelength of (405 nm) output power of (24 mW) and a line width of (3nm) was employed to generate entangled photons with a wavelength of 810 nm by achieving type II phase matching conditions.The coincidence count rate obtained in this experiment was in the range of (18000) counts/s. Two BBO crystals with different thicknesses of (4 mm and 2 mm) were tested, where maximum count rates of about (18000) counts/s was obtained with a (5*5*2) mm BBO crystal where the short coherence time for the pumping source was tolerated by using shorter BBO crystals. Also, the effect of compensating crystal on the walk-off effect was studied. The coincidence count rates were increased by using these crystal
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