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107 articles for “training methods”
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Research ArticleOpen accessIn the abstractCanonical Correlation-based Tests for the Agreement of Sensory PanelistsMarcela C Rocha, Eric B Ferreira, Daniel F FerreiraThe reliability of the results of sensory analysis is directly linked to the performance of panel of assessors what, in general, means the ability of judges to identify small differences between products, the replicability of their ratings for the same product and the panel consonance. The panel consonance - usually called unidimensionality - can be understood as the agreement between … …Journal of Mathematics and Statistics, Vol. 16, Issue 1 · 11 Jan 2020 · 7,054 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 · 7,761 accessesView PDFCite
InvestigationOpen accessIn the abstractBackpropagation Vs. Radial Basis Function Neural Model: Rainfall Intensity Classification For Flood Prediction Using Meteorology DataSoo See Chai, Wei Keat Wong, Kok Luong GohRainfall is one of the important weather variables that vary in space and time. High mean daily rainfall (>30 mm) has a high possibility of resulting in flood. Accurate prediction of this variable would save human lives and properties. Soft computing methods have been widely applied in this field. Among the various soft computing methods, Artificial Neural Network (ANN) is … …Journal of Computer Science, Vol. 12, Issue 4 · 15 Apr 2016 · 8,710 accessesView PDFCite
Research ArticleOpen accessIn the abstractHYBRID FEATURE SELECTION ALGORITHM FOR INTRUSION DETECTION SYSTEMSeyed Reza Hasani, Zulaiha Ali Othman, Seyed Mostafa Mousavi KahakiNetwork security is a serious global concern. Usefulness Intrusion Detection Systems (IDS) are increasing incredibly in Information Security research using Soft computing techniques. In the previous researches having irrelevant and redundant features are recognized causes of increasing the processing speed of evaluating the known intrusive patterns. In addition, an efficient feature selection method eliminates dimension of data and reduce redundancy … …Journal of Computer Science, Vol. 10, Issue 6 · 31 Jan 2014 · 7,357 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Method for Automatic Speech Recognition Performance Improvement in Real World Noisy EnvironmentUrmila Shrawankar, Vilas ThakareIt is a well known fact that, speech recognition systems perform well when the system is used in conditions similar to the one used to train the acoustic models. However, mismatches degrade the performance. In adverse environment, it is very difficult to predict the category of noise in advance in case of real world environmental noise and difficult to achieve … …Journal of Computer Science, Vol. 9, Issue 1 · 27 Feb 2013 · 7,758 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementation and Methods of Project Learning in Quantity Surveying Firms: Barriers, Enablers and Success FactorsHamzah Abdul-Rahman, Ali Mohammed Alashwal, Zatil Hidayah JamaludinProblem statement: Learning from project is vital for organizations to achieve competition and to survive in a dynamic environment. However, learning is not an easy task because there is no specific way for learning from projects. Besides, the practice of project learning and transfer knowledge to the firm’s level is still vague, specifically in the construction milieu. Approach: A questionnaire … …American Journal of Economics and Business Administration, Vol. 3, Issue 3 · 15 Sep 2011 · 7,576 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Study in Classification Techniques for Unsupervised Record Linkage ModelMohammadreza Ektefa, Fatimah Sidi, Hamidah Ibrahim et al.Problem statement: Record linkage is a technique which is used to detect and match duplicate records which are generated in data integration process. A variety of record linkage algorithms with different steps have been developed in order to detect such duplicate records. To find out whether two records are duplicate or not, supervised and unsupervised classification techniques are utilized in … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 8,201 accessesView PDFCite
Research ArticleOpen accessIn the abstractFace Biometrics Based on Principal Component Analysis and Linear Discriminant AnalysisLih-Heng Chan, Sh-Hussain Salleh, Chee-Ming TingProblem statement: In facial biometrics, face features are used as the required human traits for automatic recognition. Feature extracted from face images are significant for face biometrics system performance. Approach: In this thesis, a framework of facial biometric was designed based on two subspace methods i.e., Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). First, PCA is used for … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 7,668 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetermining the Time Required to Detect Induced Sow Lameness Using an Embedded Microcomputer-Based Force Plate SystemBrady McNeil, Julia Calderón Díaz, Caitlyn Bruns et al.Lameness in swine breeding herds is a common cause of compromised animal well-being and economic loss to pig producers. Current lameness assessment methods are subjective and require intensive training. It has been shown that embedded microcomputer-based force plate systems can detect lameness by measuring weight distributions in livestock. The objective of this study was to determine the minimum time required … …American Journal of Animal and Veterinary Sciences, Vol. 13, Issue 2 · 25 May 2018 · 7,616 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Students’ Academic Performance in the University Using Meta Decision Tree ClassifiersShanthini A., G. Vinodhini, R.M. ChandrasekaranStudent performance prediction is an area of concern for educational institutions. At the University level learning system, the method or rule adopted to identify the candidates who pass or fail differs depending on various factors such as the course, the department of study and so on. Predicting the result of a student in a course is an issue that has … …Journal of Computer Science, Vol. 14, Issue 5 · 28 Feb 2018 · 9,200 accessesView PDFCite