Preferred Language
Articles
/
NBdKPo8BVTCNdQwCcWVJ
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
...Show More Authors

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures and values of learning parameters are determined through cross-validation, and test datasets unseen in the cross-validation are used to evaluate the performance of the DMLP trained using the three-stage learning algorithm. Experimental results show that the proposed method is effective in combating overfitting in training deep neural networks.

Crossref
View Publication
Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
Art Image Compression Based on Lossless LZW Hashing Ciphering Algorithm
...Show More Authors
Abstract<p>Color image compression is a good way to encode digital images by decreasing the number of bits wanted to supply the image. The main objective is to reduce storage space, reduce transportation costs and maintain good quality. In current research work, a simple effective methodology is proposed for the purpose of compressing color art digital images and obtaining a low bit rate by compressing the matrix resulting from the scalar quantization process (reducing the number of bits from 24 to 8 bits) using displacement coding and then compressing the remainder using the Mabel ZF algorithm Welch LZW. The proposed methodology maintains the quality of the reconstructed image. Macroscopic and </p> ... Show More
View Publication
Scopus (9)
Crossref (4)
Scopus Crossref
Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Cybersecurity And Information Management
Machine Learning-based Information Security Model for Botnet Detection
...Show More Authors

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

... Show More
View Publication
Scopus (12)
Crossref (7)
Scopus Crossref
Publication Date
Sat Jan 12 2013
Journal Name
Pierb
RADAR SENSING FEATURING BICONICAL ANTENNA AND ENHANCED DELAY AND SUM ALGORITHM FOR EARLY-STAGE BREAST CANCER DETECTION
...Show More Authors

A biconical antenna has been developed for ultra-wideband sensing. A wide impedance bandwidth of around 115% at bandwidth 3.73-14 GHz is achieved which shows that the proposed antenna exhibits a fairly sensitive sensor for microwave medical imaging applications. The sensor and instrumentation is used together with an improved version of delay and sum image reconstruction algorithm on both fatty and glandular breast phantoms. The relatively new imaging set-up provides robust reconstruction of complex permittivity profiles especially in glandular phantoms, producing results that are well matched to the geometries and composition of the tissues. Respectively, the signal-to-clutter and the signal-to-mean ratios of the improved method are consis

... Show More
Publication Date
Sun Mar 02 2014
Journal Name
Baghdad Science Journal
The Effect of Vitamin A on Testis Weight and Sexual Glands on Albino Male Mice Treated with Hexavalent Chromium
...Show More Authors

This study was conducted to determine the effect of vitamin A ( 10 mg/kg ) on avearage testis weight and sexual glands ( Prostate and Seminal Vesicle ) for albino male mice treated with Hexavalent chromium ( 1000 ppm ) .The current study 40 mice were divided into fife groups : 1st group treated with distilled water and considered an control group (C) / the 2nd group treated with sesame oil ( T1) / 3rd group was givin hexavalent chromium ( 1000 ppm ) (T2) / 4th group treated with vitamin A ( 10 mg / kg ) and exposed to hexavalent chromium ( 1000 ppm ) (T3) / 5th group treated with vitamin A ( 10 mg kg ) (T4) . The expermint lasted 35 day . the results showed a significant ( P ? 0.05 ) decrease in avearage testis weight and sexual glan

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Image And Graphics
Normalized-UNet Segmentation for COVID-19 Utilizing an Encoder-Decoder Connection Layer Block
...Show More Authors

The COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is fre

... Show More
View Publication
Scopus (5)
Scopus Crossref
Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
...Show More Authors

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

... Show More
View Publication Preview PDF
Scopus (2)
Crossref (1)
Scopus Crossref
Publication Date
Sat Mar 29 2014
Journal Name
International Journal Of Academic Research In Progressive Education And Development
The Effects of Problem-Based Learning on Self-Directed Learning Skills among Physics Undergraduates
...Show More Authors

The aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq. In this study, the pre- and post-test were done and the instruments were administered to the students for data collection. The data was analyzed and statistical results rejected null hypothesis of this study. This study revealed that there are no signifigant differences between PBL and PBL with lecture method, thus the PBL without or with lecture method enhances the self-directed learning skills bette

... Show More
Publication Date
Sun Oct 15 2023
Journal Name
Sumer 3
Treatment of shallow and deep white spot lesions with three different mouthwashes evaluated by laser fluorescence (an in vitro study)
...Show More Authors

This research aims to find how three different types of mouthwashes affect the depth of artificial white spot lesions. Teeth with various depths of white spot lesions were immersed in either splat mouthwash, Biorepair mouthwash, Sensodyne mouthwash, or artificial saliva (control)twice daily for one minute for 4 weeks and 8 weeks at 37°C. After this immersion procedure, lesion depth was measured using a diagnosed pen score. A one-way analysis of variance, Dunnett T3 and Tukey's post hoc α = .05 were used to analyze the testing data. Splat mouthwash enhanced the WSL remineralization and made the lowest ΔF compared with other mouthwashes in shallow and deep enamel after 4 and 8 weeks of treatment. In the repair groups, after 4 weeks

... Show More
View Publication Preview PDF
Crossref (1)
Scopus Crossref
Publication Date
Fri Nov 01 2024
Journal Name
Process Safety And Environmental Protection
Optimized ensemble deep random vector functional link with nature inspired algorithm and boruta feature selection: Multi-site intelligent model for air quality index forecasting
...Show More Authors

View Publication
Scopus (8)
Crossref (9)
Scopus Clarivate Crossref
Publication Date
Mon Aug 05 2019
Journal Name
Gen. Lett. Math
Building a three-dimensional maritime transport model to find the best solution by using the heuristic algorithm
...Show More Authors

The aim of this research is to construct a three-dimensional maritime transport model to transport nonhomogeneous goods (k) and different transport modes (v) from their sources (i) to their destinations (j), while limiting the optimum quantities v ijk x to be transported at the lowest possible cost v ijk c and time v ijk t using the heuristic algorithm, Transport problems have been widely studied in computer science and process research and are one of the main problems of transport problems that are usually used to reduce the cost or times of transport of goods with a number of sources and a number of destinations and by means of transport to meet the conditions of supply and demand. Transport models are a key tool in logistics an

... Show More