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Treatment of Skin Hyperpigmentation using Q-Switched (1064nm and 532nm) Nd:YAG Laser
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Hyperpigmentation is the increase in the natural color of the skin. The purpose of this study is to evaluate the efficacy and safety of Q-Switched Nd:YAG (1064 & 532 nm) Laser in treatment of skin hyper pigmentation. This study was done in the research clinic of Institute of laser for postgraduate Studies/University of Baghdad from October 2008 to the end of January 2009. After clinical assessment of skin hyperpigmentation color, twenty six patients were divided according to their lesions. Eight Patients with freckles, seven patients with melasma, four patients with tattoo. Cases with tattoo, were subdivided into amateur tattoos two, professional tattoos one, and one traumatic tattoo. Four Patients with post inflammatory hyperpigmentation, one patient with gazzal eye, one patient with spilus nevus, one patient with becker's nevus. The time of treatment session was from 5-20 minutes according to the size of lesion at 3-4 week interval. The distributions of lesions were on different part of body, face, hand, forearm, and back. Twenty two patients completed the study; four patients defaulted from the study for unknown reasons. Conclusion: The use of Q-Switched lasers offers a low risk, effective therapy with minimal side effects because they offer bloodless, low risk, effective treatment, Q-Switched Nd:YAG lasers have replaced other methods and are now considered standard treatment. The Q-Switched Nd:YAG laser have great advantages in removing hyperpigmentation, its longer wavelength (1064nm) would increase dermal penetration and decrease melanin absorption so that it’s used in skin type (III,IV,V,VI) without the risk of depigmentation or hypopigmentation.

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Publication Date
Sun Jan 01 2023
Journal Name
Technologies And Materials For Renewable Energy, Environment, And Sustainability: Tmrees23fr
Hyperspectral pansharpening improvement using MNF transformation
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Publication Date
Sat Jan 23 2016
Journal Name
Computer Science & Information Technology ( Cs & It )
Modelling Dynamic Patterns Using Mobile Data
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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Engineering
Image Reconstruction Using Modified Hybrid Transform
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In this paper, an algorithm for reconstruction of a completely lost blocks using Modified
Hybrid Transform. The algorithms examined in this paper do not require a DC estimation
method or interpolation. The reconstruction achieved using matrix manipulation based on
Modified Hybrid transform. Also adopted in this paper smart matrix (Detection Matrix) to detect
the missing blocks for the purpose of rebuilding it. We further asses the performance of the
Modified Hybrid Transform in lost block reconstruction application. Also this paper discusses
the effect of using multiwavelet and 3D Radon in lost block reconstruction.

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Publication Date
Fri Jan 01 2021
Journal Name
Advances In Intelligent Systems And Computing
Optimal Prediction Using Artificial Intelligence Application
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Publication Date
Sat May 16 2009
Journal Name
Journal Of Planner And Development
Support environmental programs using knowledge management
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The research deals with Environmental Management and how to develop its programs with the use of Knowledge Management, the environmental programs that integrate with processes can add strategic value to business through improving rates of resource utilization , efficiencies , reduce waste, use risk management, cut costs, avoid fines and reduce insurance. All these activities and processes can improve it through knowledge management, the optimal usage for all organizations information , employ it in high value and share it among all organizations members who involves in modify its strategy . Choosing suitable environmental management information system, develop it and modify it with organization processes, can greatly serve the en

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Direction Finding Using GHA Neural Networks
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 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

 

 

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Publication Date
Wed Feb 04 2015
Journal Name
The Second Biological Science Conference
Bioethanol Production Using Date Syrup Wastes
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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
An Embedded Data Using Slantlet Transform
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Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image

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Publication Date
Thu Jan 22 2026
Journal Name
Journal Of Engineering
Drag Reduction by using Anionic Surfactants
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Publication Date
Tue Nov 21 2017
Journal Name
Lecture Notes In Computer Science
Emotion Recognition in Text Using PPM
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In this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.

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