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94 articles for “robust test”
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Research ArticleOpen accessIn the abstractOptimized Local Ternary Patterns: A New Texture Model with Set of Optimal Patterns for Texture AnalysisG. Madasamy Raja, V. SadasivamTexture analysis is one of the important as well as useful tasks in image processing applications. Many texture models have been developed over the past few years and Local Binary Patterns (LBP) is one of the simple and efficient approach among them. A number of extensions to the LBP method have been also presented but the problem remains challenging in … …Journal of Computer Science, Vol. 9, Issue 1 · 22 Jan 2013 · 6,955 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Robust Recognition System for Pecan Weevil using Artificial Neural NetworksSaleh Mufleh Al-SaqerProblem statement: Pecan Weevil is a widely found pest among pecan trees and these pests are known to cause significant damage to the pecan trees resulting in enormous annual losses to pecan growers. Traditional identification techniques for pecan weevil include traps with pheromones to detect the infestation of these pests. However, these traditional methods require expensive labor hours to set-up … …American Journal of Applied Sciences, Vol. 9, Issue 9 · 14 Jul 2012 · 6,836 accessesView PDFCite
Research ArticleOpen accessIn the abstractRobust Speech Recognition Using Fusion Techniques and Adaptive FilteringS. A.R. Al-Haddad, S. A. Samad, A. Hussain et al.The study proposes an algorithm for noise cancellation by using recursive least square (RLS) and pattern recognition by using fusion method of Dynamic Time Warping (DTW) and Hidden Markov Model (HMM). Speech signals are often corrupted with background noise and the changes in signal characteristics could be fast. These issues are especially important for robust speech recognition. Robustness is a … …American Journal of Applied Sciences, Vol. 6, Issue 2 · 28 Feb 2009 · 7,999 accessesView PDFCite
Research ArticleOpen accessIn the abstractDecentralized Controller Design for Static Synchronous Compensator Using Robust Quantitative Feedback Theory MethodSeyed Abbas Taher, Reza Hematti, Ali Abdolalipour, Majid NematiThe Static Synchronous Compensator (STATCOM) provides shunt compensation in similar way to the Static VAR Compensator (SVC) but utilizes a voltage source converter rather than capacitors and reactor. In practice systems use simple Proportional-Integral (PI) controllers for control of STATCOM. However, since the PI control parameters were usually tuned based on classical or trial-and-error approaches, they were incapable of obtaining … …American Journal of Engineering and Applied Sciences, Vol. 1, Issue 1 · 31 Mar 2008 · 7,461 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Value of Serologic Tests for Diagnosis and Follow up of Patients having BrucellosisNidia E. Lucero, Sandra M. Ayala, Gabriela I. Escobar, N R. JacobThough diagnosis of human brucellosis is accurate when the causal agent is isolated, this procedure is not always successful and the most of patients are diagnosed on the basis of rising titres of antibodies in serum. The classical tests used for detection of antibodies to S-Brucella sp., include Rose Bengal (RBT), buffered plate antigen (BPAT), serum agglutination (SAT), 2-mercapto-ethanol (2MET) … …American Journal of Infectious Diseases, Vol. 3, Issue 1 · 31 Mar 2007 · 7,447 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 · 6,098 accessesView PDFCite
Research ArticleOpen accessIn the abstractNamed Entity Recognition for Kannada using Gazetteers list with Conditional Random FieldsK. P. Pallavi, L. Sobha, M. M. RamyaNamed Entities (NEs) that exist in the sentences are essential to build Natural Language Processing (NLP) applications for Information Extraction (IE) from large corpora. However, generating a large corpus is challenging for resource poor languages, such as Kannada. Further, there is no annotated corpus available online. The challenges faced in annotating NEs with pre-defined classes are: It is morphologically joined … …Journal of Computer Science, Vol. 14, Issue 5 · 24 Feb 2018 · 8,278 accessesView PDFCite
Research ArticleOpen accessIn the abstractAuthorship Attribution of Short Historical Arabic Texts using Stylometric Features and a KNN Classifier with Limited Training DataFatma Howedi, Masnizah Mohd, Zahra Aborawi Aborawi, Salah A. JowanAuthorship Attribution (AA) is a task that aims to recognize the authorship of unknown texts based on writing style. Out of the various approaches to solve the AA problem, Stylometry is a promising one. This paper explores the use of a K-Nearest Neighbor (KNN) classifier combined with stylometry features to perform AA. This study indicates the robustness of KNN in … …Journal of Computer Science, Vol. 16, Issue 10 · 3 Oct 2020 · 8,194 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnomaly Detection Algorithms for Streaming Data: Performance ComparisonZirije HasaniToday’s most of the data are streaming time-series data, where is very important anomaly detection over this data because gives significant information of possible critical situations. Detecting anomalies in big streaming data is yet difficult task because we have to process them in real time, even before they are stored and instantly alarm on potential threats. For real time streaming … …Journal of Computer Science, Vol. 16, Issue 7 · 18 Jul 2020 · 7,296 accessesView PDFCite
Research ArticleOpen accessIn the abstractQSAR Modeling of Thirty Active Compounds for the Inhibition of the Acetylcholinesterase EnzymeNour El Houda Hammoudi, Yacine Benguerba, Widad SobhiThis work aims at developing a reliable and predictive QSAR model which allows, on one hand, an exploration of the main molecular descriptors responsible for the inhibitory activity towards the Acetylcholinesterase enzyme and, on the other hand, predict the inhibitory activity of new compounds before testing them experimentally. This study involves a series of DL0410 and its 29 DL0410 derivatives. … …Current Research in Bioinformatics, Vol. 8, Issue 1 · 2 Mar 2020 · 11,431 accessesView PDFCite