In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

Benign prostate hyperplasia (BPH), non-cancerous enlargement of prostate, is the most prevalent disease entity in elderly men. BPH affects 40% of men after the age of 60year worldwide. BPH causes problems for patients with significant lower urinary tract obstructive symptoms, if not responding to medical therapy, surgical intervention is instituted. One method of the treatment of symptomatic BPH is laser prostatectomy. The understanding of tissue effects by laser radiation is very important for the safe clinical application of laser. Objective: study the 2100 nm Ho: YAG laser gross tissue effects in the prostate at different laser dose settings in an vitro model prostate tissue samples harvested from same specimen of open surgery prostat

Leiomyosarcoma (smooth muscle tumor) is a rare type of a malignant neoplasm of smooth
muscle. It is a resistant cancer, generally not very responsive to chemotherapy, radiationand surgery.The
aim of this study was to evaluate photodynamic therapy (PDT) as a possible basis for treatment using
(650 nm)diode laser with methyleneblue (MB) as a photosensitizer on leiomyosarcoma (LMS)cell line
(L20B) in vitro. The cytotoxic effects of 650nm diode laser 0.052 W/cm2 (power density) at different
exposure time (10, 20, and 30 min) with methylene blue at different concentrations (0.01% ,0.1 % ,1%)
was investigated on LMS cell line (L20 B). The cytotoxic effect of laser was increased with increasing
irradiation time for a certai

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

Background : Ebastine (EBS) is an antihistamine medication commonly used to alleviate symptoms associated with allergic rhinitis and pruritic skin conditions, such as urticaria and other pruritic dermatoses. The main advantage of oral lyophilisates is their high porosity, which facilitates rapid salivary penetration, short disintegration times, and improved bioavailability.

Method : EBS-loaded Solusome nanovesicles were formulated via the thin-film hydration technique using Soluplus® as a stabilizing agent within the nanovesicle system. The Solusome nan