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22 results for “Dimensionality Reduction”
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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 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
Research ArticleOpen accessIn the abstractPerformance Analysis of Threshold Based Compressive Sensing Algorithm in Wireless Sensor NetworkParnasree Chakraborty, C. ThariniWireless Sensor Networks (WSN) are comprised of spatially distributed sensor nodes, where each node contains sensors, processors and transceivers for communicating data. Regardless of the application in which the sensor network is serving, the data generated in the network eventually must be delivered to the sink. However the limited network bandwidth, frequent node/link failure along with the unreliable communication medium … …American Journal of Applied Sciences, Vol. 14, Issue 2 · 3 Feb 2017 · 7,507 accessesView PDFCite
Research ArticleOpen accessIn the abstractAsymptotic Properties of Local Sampling on ManifoldYury Aleksandrovich YanovichIn many applications, the real high-dimensional data occupy only a very small part in the high dimensional ‘observation space’ whose intrinsic dimension is small. The most popular model of such data is Manifold model which assumes that the data lie on or near an unknown manifold Data Manifold, (DM) of lower dimensionality embedded in an ambient high-dimensional input space (Manifold … …Journal of Mathematics and Statistics, Vol. 12, Issue 3 · 26 Aug 2016 · 7,698 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 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
Research ArticleOpen accessIn the abstractBRAIN TUMOR CLASSIFICATION BASED ON CLUSTERED DISCRETE COSINE TRANSFORM IN COMPRESSED DOMAINV. Anitha, S. MurugavalliThis study presents a novel method to classify the brain tumors by means of efficient and integrated methods so as to increase the classification accuracy. In conventional systems, the problem being the same to extract the feature sets from the database and classify tumors based on the features sets. The main idea in plethora of earlier researches related to any … …Journal of Computer Science, Vol. 10, Issue 10 · 6 May 2014 · 7,532 accessesView PDFCite
Research ArticleOpen accessIn the abstractIndex Financial Time Series Based on Zigzag-Perceptually Important PointsAli Selamat, Chawalsak Phetchanchai, Tanzila Saba, Amjad RehmanProblem statement: Financial time series were usually large in size, unstructured and of high dimensionality. Since, the illustration of financial time series shape was typically characterized by a few number of important points. These important points moved in zigzag directions which could form technical patterns. However, these important points exhibited in different resolutions and difficult to determine. Approach: In this … …Journal of Computer Science, Vol. 6, Issue 12 · 2 Nov 2010 · 9,464 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Detection Algorithm for a Multiple-Input and Multiple-Output Multiuser Multi-Carrier Code Division Multiple Access in Time-Varying ChannelsFares Sayadi, Mahamod Ismail, Norbahiah Misran et al.Problem statement: Maximum Likelihood (ML) decoding has been applied for the uplink of a Multi-Carrier Code Division Multiple Access (MC-CDMA) system based on Orthogonal Frequency Division Multiplexing (OFDM). Multiple-Input Multiple-Output (MIMO) channel from k users, which moves at vehicular speed, to the Base-Station (BS) is time-varying. For time-varying channels, Sphere Decoding (SD) was introduced to perform ML decoding. Whereas, computational … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 4 · 31 Dec 2009 · 7,576 accessesView PDFCite