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Research ArticleOpen accessIn the abstractStudy of Cutoff Frequency of High Collector Current Density in SiGe Single-Heterojunction Bipolar TransistorG. M. Khanduri, B. S. PanwarThe cutoff frequency performance of an NPN Si/SiGe/SiGe Single-heterojunction bipolar transistor (SiGe SHBT) at high collector current densities has been analyzed using a 2-dimensional MEDICI device simulator. A conventional NPN Si/SiGe/Si Double-heterojunction bipolar transistor (SiGe DHBT) having uniform 14%Ge in the base region has been investigated for comparison. The analysis shows the formation of a retarding potential barrier for minority … …American Journal of Applied Sciences, Vol. 1, Issue 3 · 30 Sep 2004 · 6,891 accessesView PDFCite
Research ArticleOpen accessIn the abstractLogistic Regression with Multi-Connected WeightsAvazjon Marakhimov Rakhimovich, Kabul Khudaybergenov Kadirbergenovich, Zahriddin Muminov Ishkobilovich, Kudaybergenov Jabbarbergen KadirbergenovichResults of current research in biological and cognitive science reveal that neuronal interactions predominantly depend on neurotransmitters for signaling and sending information between neurons. Furthermore, a specific neuron that is connected to the next neuron transmits or sends multiple neurotransmitters in parallel ways, where each neurotransmitter has specific functional roles. Based on these results, a new type of logistic regression … …Journal of Computer Science, Vol. 20, Issue 9 · 4 Jul 2024 · 5,059 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Deep Learning Framework for Classifying and Evaluating Yoga ExercisesMehar Latif Malik, Arun KhoslaYoga is a type of physical activity that combines physical postures with breathing techniques. Cardiovascular disease is the leading cause of illness and mortality. Yoga's potential involvement in cardiac recovery can be incorporated into cardiovascular rehabilitation. Classifying and evaluating yoga exercises using a deep learning framework plays a significant role in postoperative recovery. Home based rehabilitation often suffers from a … …Journal of Computer Science, Vol. 19, Issue 2 · 30 Jan 2023 · 6,091 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT Intrusion Detection using Auto-Encoder and Machine Learning TechniquesAhmed Ridha Khudhu, Khairulmizam SamsudinIoTnetwork refers to the capability of connecting smart and various devices to asingle network for the sake of performing a particular task. Similar toconventional networks, IoT networks are vulnerable to several attacks.Therefore, IoT Intrusion Detection has caught much research attention. Severalstudies have examined the task of intrusion detection for IoT networks. Withinsuch studies, the focus was set to accommodate a … …Journal of Computer Science, Vol. 18, Issue 10 · 27 Sep 2022 · 6,458 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel SIFT-SVM Approach for Prostate Cancer DetectionSwetha Parvatha Reddy Chandrasekhara, Mohan Govindsa Kabadi, SrivinayProstate cancer is a major cause of concern in male population as it is said to affect 1 in every 7 men in their lifetime. The number of cases being registered for prostate cancer and its mortality rates are increasing yearly at an alarming rate. Due to the high resolution and multi-dimensionality of the Magnetic Resonance Imaging (MRI) images, proper … …Journal of Computer Science, Vol. 16, Issue 12 · 22 Dec 2020 · 7,524 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Implementation of Support Vector Machine on the Multi-Label Classification of English-Translated Quranic VersesSatrio Adi Prabowo, Adiwijaya, Mohamad Syahrul Mubarok et al.One of the attempts to understand the meaning and content of the Quran, the central religious text of Islam, is the topic classification of Quranic verses. Verse topic classification aims to help the reader, so he can easily and quickly find information or knowledge contained in the Quran. In this paper, we build a classification model for the topics of … …Journal of Computer Science, Vol. 15, Issue 12 · 19 Dec 2019 · 7,783 accessesView PDFCite
EditorialOpen accessIn the abstractBig Data and Parkinson’s Disease - from Understanding of Disease to Personalised MedicineYen F. Tai, Nicola PaveseThe advancement of information technology in recent years has generated a huge amount of datasets in all areas of scientific research. This has led to new opportunities to harness the 'Big Data' to improve our understanding of diseases - from investigating disease mechanisms to monitoring treatment responses. The Big Data approach is a data-driven and often hypothesis-free, way of studying … …Neuroscience International, Vol. 7, Issue 1 · 27 Jul 2016 · 7,755 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Breast Tumor in Mammogram Images Using Unsupervised Feature LearningAidarus M. Ibrahim, Baharum Baharudin, Abas Md Said, P. N. HashimahIn this study, we propose a learning-based approach using feature learning to minimize the manual effort required to extract features. Firstly, we extracted features from equally spaced sub-patches covering the input Region of Interest (ROI). The dimensionality of the extracted features is reduced using max-pooling. Furthermore, spherical k-means clustering coupled with max pooling (k-means-max pooling) is compared with well-known feature … …American Journal of Applied Sciences, Vol. 13, Issue 5 · 13 May 2016 · 7,497 accessesView PDFCite
Research ArticleOpen accessIn the abstractExtended Kalman Filter versus Newton-Lowe's Method for Robot Pose EstimationMohammad Ehab RagabIn this work, we study the pose estimation problem of anautonomous mobile robot. Particularly, we compare the Extended Kalman Filter (EKF) to Lowe's method based on the iterative Newton's method for solving a system of nonlinear equations. Although the EKF is recursive which renders it suitable for the real-time problem at hand, Lowe's method has much less dimensionality. This is … …Journal of Computer Science, Vol. 11, Issue 7 · 5 Nov 2015 · 6,937 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Distinguishability Based Weighted Feature Selection Algorithms for Improved Classification of Gene Microarray DatasetJ. Jeyachidra, M. PunithavalliData mining played vital role in comprehending, analyzing, understanding and interpreting microarray technology expression data. That includes search for genes that had similar or correlated patterns of expression. For that, the feature selection was one of the frequently used important techniques for data preprocessing. Many feature selection algorithms had been developed. Yet the persisting problem was in selecting optimal subset … …Journal of Computer Science, Vol. 11, Issue 2 · 2 Feb 2015 · 6,376 accessesView PDFCite