KE Sharquie, SM Al-Tammimy, S Al-Mashhadani, RK Hayani, AA Al-Nuaimy, Dermatology online journal, 2006 - Cited by 34

Breast mass is by far the most important clinical problem that concerns the breast today. This study was carried out to evaluate diode laser as a cutting tool in breast mass excision and as a hemostatic tool for coagulation during surgery. Using 810 nm diode laser with optical fiber 600μm in diameter of conical tip, udder (cow's breast) tissue, and three female patients (mean age of 35.5 y with clinically palpable breast mass) had been used in this study. The patients were followed up regularly postoperatively. In preliminary work on udder tissue, the power needed for cutting and excision was 15W (power density= 5.3 kW/cm2). The time consumed for excision of a piece of udder tissue, 40×10×3 mm in dimensions was 5 min. The depth range

Optical spectrum of SN1987A at days 4 from the explosion and its light curve through the first 1444 days after the explosion have been studied. The hydrogen lines present in the spectrum confirms the general characteristics of Type II SN that occur due to core collapse of massive star. Each of the total mass ejected from the explosion and the amount of the total mass of Nickel radioactive isotopes that produced during the explosion as well as the initial velocity of the ejecta and the explosion energy have been determined and compared with different observed and calculated models obtained by different researchers and it’s found that, about 8.8 Mʘ of the progenitor envelope mass had been ejected during the explosion and it’s mixed with

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Erro

It is very difficult to obtain the value of a rock strength along the wellbore.  The value of Rock strength utilizing to perform different analysis, for example, preventing failure of the wellbore, deciding a completion design and, control the production of sand.  In this study, utilizing sonic log data from (Bu-50) and (BU-47) wells at Buzurgan oil field.  Five formations have been studied (Mishrif, Sadia, Middle lower Kirkuk, Upper Kirkuk, and Jaddala) Firstly, calculated unconfined compressive strength (UCS) for each formation, using a sonic log method.  Then, the derived confined compressive rock strengthens from (UCS) by entering the effect of bore and hydrostatic pressure for each formation.  Evaluations th

Flexible joint robot (FJR) manipulators can offer many attractive features over rigid manipulators, including light weight, safe operation, and high power efficiency. However, the tracking control of the FJR is challenging due to its inherent problems, such as underactuation, coupling, nonlinearities, uncertainties, and unknown external disturbances. In this article, a terminal sliding mode control (TSMC) is proposed for the FJR system to guarantee the finite-time convergence of the systems output, and to achieve the total robustness against the lumped disturbance and estimation error. By using two coordinate transformations, the FJR dynamics is turned into a canonical form. A cascaded finite-time sliding mode observer (CFTSMO) is construct