Research ArticleOpen accessIn the abstractA Robust Ensemble Convolutional Neural Networks for Diagnosing Chest DiseasesMansour Ali Alhlalat, Ahmad Abdel-Aziz Sharieh, Mohammed Belal Al-ZoubiRadiologists employ X-ray images to differentiate various chest diseases. Given the intricate and meticulous nature of this diagnostic procedure, the assistance of automated models becomes imperative in detecting and diagnosing diseases from X-ray images. This research paper proposed a novel approach called Ensemble Convolutional Neural Network for Diagnosing Chest Diseases (ECDCNet), aimed at accurately and efficiently diagnosing fifteen different chest … …Journal of Computer Science, Vol. 19, Issue 12 · 27 Oct 2023 · 5,104 accessesView PDFCite
Research ArticleOpen accessIn the abstractGender Classification from Face and Eyes Images Using Deep Learning AlgorithmZahraa Salam Abu Ghrban, Nidhal Khdhair EL AbbadiGender classification provides additional information about the individual’s identity, which is crucial in surveillance, smart interface, and smart advertising, it is a very important aspect of face analysis that has piqued the interest of researchers in areas such as demographic information collection, surveillance, human-computer interaction, marketing intelligence, security, etc. Usually, facial images are used to extract features for classification. This … …Journal of Computer Science, Vol. 19, Issue 3 · 24 Feb 2023 · 6,937 accessesView PDFCite
Research ArticleOpen accessIn the abstractMULTI SCALE TIME SERIES PREDICTION FOR INTRUSION DETECTIONG. Palanivel, K. DuraiswamyWe propose an anomaly-based network intrusion detection system, which analyzes traffic features to detect anomalies. The proposed system can be used both in online as well as off-line mode for detecting deviations from the expected behavior. Although our approach uses network packet or flow data, it is general enough to be adaptable for use with any other network variable, which … …American Journal of Applied Sciences, Vol. 11, Issue 8 · 27 Jun 2014 · 6,776 accessesView PDFCite
Research ArticleOpen accessIn the abstractFAULT DETECTION IN SWITCHED RELUCTANCE MOTOR DRIVES USING DISCRETE WAVELET TRANSFORM AND K-MEANS CLUSTERINGV. S. Chandrika, A. Ebenezer JeyakumarThis study presents a novel method of detection of inter turn shorts based on k means clustering technique. In addition to inter turn short detection, the other faults like open, short, phase to phase faults and DC volt-age faults are detected through wavelet transforms and k means clustering. Open and short faults are classified using artificial neural network. All other … …American Journal of Applied Sciences, Vol. 11, Issue 3 · 30 Dec 2013 · 7,983 accessesView PDFCite
Research ArticleOpen accessIn the abstractSPECTRAL DOMAIN FEATURES FOR OVARIAN CANCER DATA ANALYSISAhmed Farag Seddik, Riham Amin Hassan, Mahmoud A. FakhreldeinThe early detection of cancer is crucial for successful treatment. Medical researchers have investigated a number of early-diagnosis techniques. Recently, they have discovered that some cancers affect the concentration of certain molecules in the blood, which allows early diagnosis by analyzing the blood mass spectrum. Researchers have developed several techniques for the analysis of the mass-spectrum curve analysis and used … …Journal of Computer Science, Vol. 9, Issue 8 · 9 Jul 2013 · 6,915 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Evaluation of Adaptive Filter and Neuro-Fuzzy Filter in Artifacts Removal From Electroencephalogram SignalPaulchamy Balaiah, IlavennilaProblem statement: This study presents an effective method for removing mixed artifacts (EOG-Electro-ocular gram, ECG-Electrocardiogram, EMG-Electromyogram) from the EEG-Electroencephalogram records. The noise sources increases the difficulty in analyzing the EEG and obtaining clinical information. EEG signals are multidimensional, non-stationary (i.e., statistical properties are not invariant in time), time domain biological signals, which are not reproducible. It is supposed to contain … …American Journal of Applied Sciences, Vol. 9, Issue 10 · 15 Aug 2012 · 7,087 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Compression Algorithms Using Intensity Based Adaptive Quantization CodingSaad Al-Azawi, Said Boussakta, Alex YakovlevProblem statement: Low complexity image compression algorithms are necessary for modern portable devices such as mobile phones, wireless sensor networks and high constraint power consumption devices. In such applications low bit rate along with an acceptable image quality are an essential requirements. Approach: This study proposes low and moderate complexity algorithms for colour image compression. Two algorithms will be presented; … …American Journal of Engineering and Applied Sciences, Vol. 4, Issue 4 · 18 Jan 2012 · 8,496 accessesView PDFCite
Research ArticleOpen accessIn the abstractSeasonal Time Series Data Forecasting by Using Neural Networks Multiscale Autoregressive ModelSuhartono, B. S.S. Ulama, A. J. EndhartaProblem statement: The aim of this research was to study further some latest progress of wavelet transform for time series forecasting, particularly about Neural Networks Multiscale Autoregressive (NN-MAR). Approach: There were three main issues that be considered further in this research. The first was some properties of scale and wavelet coefficients from Maximal Overlap Discrete Wavelet Transform (MODWT) decomposition, particularly … …American Journal of Applied Sciences, Vol. 7, Issue 10 · 31 Oct 2010 · 7,751 accessesView PDFCite
Research ArticleOpen accessIn the abstractParallel Approach for Content Based Medical Image Retrieval SystemM. Emmanuel, D.R. Ramesh Babu, Jayashree Jagdale et al.Problem statement: Parallel implementation of a CBIR system for medical applications due to the rapid progress in the technologies for obtaining and storing digital images for diagnostic purposes in medicine. Approach: For feature extraction Wavelet decomposition was used for texture, global color histograms for color and novel wavelet based approach for shape feature extraction. The system had been implemented in … …Journal of Computer Science, Vol. 6, Issue 11 · 23 Oct 2010 · 7,631 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Analysis of Structures Using Neural NetworksN. Ahmadi, R. Kamyab Moghadas, A. LavaeiIn the recent years, neural networks are considered as the best candidate for fast approximation with arbitrary accuracy in the time consuming problems. Dynamic analysis of structures against earthquake has the time consuming process. We employed two kinds of neural networks: Generalized Regression neural network (GR) and Back-Propagation Wavenet neural network (BPW), for approximating of dynamic time history response of … …American Journal of Applied Sciences, Vol. 5, Issue 9 · 30 Sep 2008 · 7,154 accessesView PDFCite