Background: As photochemical reaction that can stiffen the cornea, CXL is the only promising method of preventing progression of keratectasia such as KC and secondary ectasia following refractive surgery. The aim of CXL is to stabilize the underlying condition with a small chance of visual improvement. Objective: To show the sequences of changes in visual acuity and topographic outcomes during 1 year post CXL for patients with progressive Keratoconus.Type of the study: Cross sectional studyMethods: CXL procedure was done for 45 eyes with progressive KC. The following parameters had been monitored pre operatively, 1, 3, 6 and 12 months postoperatively: K apex, K2, corneal thickness at thinnest location, anterior and posterior elevation points, BCVA and UCVA. Placido –Scheimpflug topography (Sirius) device had been used to monitor the corneal parameters of the study. One –way ANOVA and Paired sample T test was used for statistical analysis.The study done in Lasik specialty center /Baghdad/IraqResults: At 1 year, an averages flattening of (2.11 D) diopter in K2 and (1.88 D) diopter in K apex were found. Mean BCVA improved by 1 line from (0.18) Log MAR to (0.13) Log MAR and mean UCVA improved by 3.5 lines from (0.89) to (0.64) log MAR. The corneal thickness at thinnest location was 5.71 Mm less than the baseline. All the above mentioned parameters showed a trend of worsening between the baseline and 1 month, and improvement thereafter. We found no statistically significant changes in the anterior elevation points while the posterior elevation point changed (increased) significantly.Conclusions: Corneal collagen cross-linking seems to be effective in decreasing progression of KC , with improvements in optical measures in many patients. Post operative parameters discussed within this review followed a seemingly reproducible trend in there natural course over 12 months .Generally, the trend that observed was immediate worsening between baseline and 1 month resolution at approximately 3 months, and improvement thereafter.
Skin detection is classification the pixels of the image into two types of pixels skin and non-skin. Whereas, skin color affected by many issues like various races of people, various ages of people gender type. Some previous researchers attempted to solve these issues by applying a threshold that depends on certain ranges of skin colors. Despite, it is fast and simple implementation, it does not give a high detection for distinguishing all colors of the skin of people. In this paper suggests improved ID3 (Iterative Dichotomiser) to enhance the performance of skin detection. Three color spaces have been used a dataset of RGB obtained from machine learning repository, the University of California Irvine (UCI), RGB color space, HSV color sp
... Show MoreThe effect of thickness variation on some physical properties of hematite α-Fe2O3 thin films was investigated. An Fe2O3 bulk in the form of pellet was prepared by cold pressing of Fe2O3 powder with subsequent sintering at 800 . Thin films with various thicknesses were obtained on glass substrates by pulsed laser deposition technique. The films properties were characterized by XRD, and FT-IR. The deposited iron oxide thin films showed a single hematite phase with polycrystalline rhombohedral crystal structure .The thickness of films were estimated by using spectrometer to be (185-232) nm. Using Debye Scherrerś formula, the average grain size for the samples was found to be (18-32) nm. Atomic force microscopy indicated that the films had
... Show MoreIn this paper , an efficient new procedure is proposed to modify third –order iterative method obtained by Rostom and Fuad [Saeed. R. K. and Khthr. F.W. New third –order iterative method for solving nonlinear equations. J. Appl. Sci .7(2011): 916-921] , using three steps based on Newton equation , finite difference method and linear interpolation. Analysis of convergence is given to show the efficiency and the performance of the new method for solving nonlinear equations. The efficiency of the new method is demonstrated by numerical examples.
This book includes four main chapters: 1. Indefinite Integral. 2. Methods of Integration. 3. Definite Integral. 4. Multiple Integral. In addition to many examples and exercises for the purpose of acquiring the student's ability to think correctly in solving mathematical questions.
Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS
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The corrosion behavior of 2024 aluminium alloy was investigated in alkaline medium (pH=13) containing 0.6 . in absence and presence of different concentrations of three amino acids separately [Methionine, Glutamice acid and Lysine] as environmentally friendly corrosion inhibitors over the temperature range (293-308)K. Electrochemical polarization method using potentiostatic technique was employed. The inhibition efficiency increased with an increase of the inhibitor concentration but decreased with increase in temperature . The maximum efficiency value was found with lysine =80.4 of 293 k and 10 . concentration of lysine. The adsorption of the amino acids was found to obey Langmuir adsorption isotherm . Some thermodynamic parameter âˆ
... Show MoreBackground: DVT is a very common problem with a very serious complications like pulmonary embolism (PE) which carries a high mortality,and many other chronic and annoying complications ( like chronic DVT, post-phlebitic syndrome, and chronic venous insufficiency) ,and it has many risk factors that affect its course, severity ,and response to treatment. Objectives: Most of those risk factors are modifiable, and a better understanding of the relationships between them can be beneficial for better assessment for liable pfatients , prevention of disease, and the effectiveness of our treatment modalities. Male to female ratio was nearly equal , so we didn’t discuss the gender among other risk factors. Type of the study:A cross- secti
Co-composting process can be acquired by combining organic fraction of municipal solid waste (OFMSW) with sewage sludge (SS) and mature compost (MC) as enhancement and bulking agent to overcome the problems of municipal solid waste and wastewater treatment plants besides the finally produced fertilizer usage for agriculture and horticulture. The effects of different mixture ratios of (OFMSW), (SS) and (MC) on the performance of composting process were investigated in this study. Piles of about 10 kg were prepared by mixing OFMSW, SS and MC in three different ratios (w/w) [OFMSW: SS: MC= 3:1:1, 3:2:1, and 3:3:1]. Results showed that the pile [3:1:1] was most beneficial to composting. The final compost products contained a
... Show MoreThis book includes three main chapters: 1. Functions & Their Derivatives. 2. Minimum, Maximum and Inflection points. 3. Partial Derivative. In addition to many examples and exercises for the purpose of acquiring the student's ability to think correctly in solving mathematical questions.
World statistics declare that aging has direct correlations with more and more health problems with comorbid conditions. As healthcare communities evolve with a massive amount of data at a faster pace, it is essential to predict, assist, and prevent diseases at the right time, especially for elders. Similarly, many researchers have discussed that elders suffer extensively due to chronic health conditions. This work was performed to review literature studies on prediction systems for various chronic illnesses of elderly people. Most of the reviewed papers proposed machine learning prediction models combined with, or without, other related intelligence techniques for chronic disease detection of elderly patie
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