Spider veins are a common aesthetic problem mainly in females , the conventional method of treatment is by microsclerotherapy (injections) but laser therapy has become increasingly efficacious and a convenient method for treatment. The present study was performed to investigate the effectiveness and safety of pulsed diode laser (810nm) by doing thermal photocoagulation. Ten patients with lower limbs spider veins were included in this prospective study. They were treated with a repetitive pulsed diode laser in non contact technique using the following laser parameters (wave length 810nm,power 1 W ,pulse duration 0.1 s., pulse interval 0.5 s, spot diameter 4mm ,power density 7.9 W/cm2). Laser therapy was performed on day zero and day fourteen. Clinical assessments were carried out before laser therapy and immediately after the first laser therapy, after 2 weeks, 4 weeks, and 6 weeks. The procedure was performed without using any type of anesthesia. Results showed that there was a remarkable improvement for all patients after the first treatment and after the second treatment. Only six patients showed a complete disappearance of the spider veins with absent peroperative and postoperative pain and complications, within short operative time in comparison with the microsclerotherapy. So the repetitive pulsed diode laser therapy (810nm) is an effective and safe treatment option for lower limbs spider veins. It's recommended that larger numbers of cases to be done to allow for a proper statistical analysis and a longer follow up period to assess the recurrence rate.
Delays occur commonly in construction projects. Assessing the impact of delay is sometimes a contentious
issue. Several delay analysis methods are available but no one method can be universally used over another in
all situations. The selection of the proper analysis method depends upon a variety of factors including
information available, time of analysis, capabilities of the methodology, and time, funds and effort allocated to the analysis. This paper presents computerized schedule analysis programmed that use daily windows analysis method as it recognized one of the most credible methods, and it is one of the few techniques much more likely to be accepted by courts than any other method. A simple case study has been implement
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The complexity of multimedia contents is significantly increasing in the current world. This leads to an exigent demand for developing highly effective systems to satisfy human needs. Until today, handwritten signature considered an important means that is used in banks and businesses to evidence identity, so there are many works tried to develop a method for recognition purpose. This paper introduced an efficient technique for offline signature recognition depending on extracting the local feature by utilizing the haar wavelet subbands and energy. Three different sets of features are utilized by partitioning the signature image into non overlapping blocks where different block sizes are used. CEDAR signature database is used as a dataset f
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Image Fusion Using A Convolutional Neural Network
In this paper we deal with the problem of ciphering and useful from group isomorphism for construct public key cipher system, Where construction 1-EL- Gamal Algorithm. 2- key- exchange Algorithm
This paper is concerned with introducing and studying the first new approximation operators using mixed degree system and second new approximation operators using mixed degree system which are the core concept in this paper. In addition, the approximations of graphs using the operators first lower and first upper are accurate then the approximations obtained by using the operators second lower and second upper sincefirst accuracy less then second accuracy. For this reason, we study in detail the properties of second lower and second upper in this paper. Furthermore, we summarize the results for the properties of approximation operators second lower and second upper when the graph G is arbitrary, serial 1, serial 2, reflexive, symmetric, tra
... Show MoreOver the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time. In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho
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