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234 results for “Model Training”

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Research ArticleOpen accessIn the abstractThe Implementation of Online Learning for Early Detection of Cervical CancerHery Harjono Muljo, Bens Pardamean, Anzaludin Samsinga PerbangsaCervical cancer is the second leading type of cancer causing death among women in Indonesia. The mortality rate caused by cervical cancer could be reduced through an early detection program, which would require the training of healthcare workers in educating women in Indonesia. The aim of this study was to develop an online learning management system prototype that is suitable … …Journal of Computer Science, Vol. 13, Issue 11 · 9 Nov 2017 · 7,566 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeast Absolute Deviation Regression and Least Squares for Modeling Retention Indices of Set Compounds Food and Pollutants of the EnvironmentFatiha Mebarki, Khadija Amirat, Salima Ali Mokhnach, Djellol MessadiConsidering the importance of the statistical analysis of regression in modeling based separately on study for Quantitative structure retention indices on Carbowax 20 M (ICw20M) and OV-101 columns (IOV-101) relationships (QSRR) are determined for 114 pyrazines. The detection of influential observations for the standard least squares regression model is a problem which has been extensively studied. Least Absolute Deviation regression … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 5 Jun 2017 · 7,424 accessesView PDFCite
Research ArticleOpen accessIn the abstractBiomechanically Inspired Shape Memory Effect Machines Driven by Muscle like Acting NiTi AlloysRaffaella Aversa, Francesco Tamburrino, Relly Victoria V. Petrescu et al.The research shows a bioinspired approach to be adopted to design of systems based on Shape Memory Alloys (SMAs), a class of Smart Materials that has in common with muscles the capability to react to an impulse (thermal for SMAs) with a contraction. The biomechanically inspired machine that is discussed in the paper refers to the antagonistic muscles pairs, which … …American Journal of Applied Sciences, Vol. 13, Issue 11 · 24 Nov 2016 · 9,109 accessesView PDFCite
Research ArticleOpen accessIn the abstract3D-QSAR and SVM Prediction of BRAF-V600E and HIV Integrase Inhibitors: A Comparative Study and Characterization of Performance with a New Expected Prediction Performance MetricLeonard Wesley, Saihitha Veerapaneni, Rachana Desai et al.The results of directly comparing the prediction accuracy of optimized 3D Quantitative Structure-Activity Relationship (3D-QSAR) models and linear Support Vector Machine (SVM) classifiers to identify small molecule inhibitors of the BRAF-V600E and HIV Integrase targets are reported. Performance comparisons were carried out using 303 compounds (68 active) against BRAF-V600E and 204 compounds (159 active) against HIV Integrase. A SVM prediction … …American Journal of Biochemistry and Biotechnology, Vol. 12, Issue 4 · 17 Oct 2016 · 7,802 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved Dynamic Threshold Method for Skin Colour Detection Using Multi-Colour SpaceMohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad RohaniThis paper presents a skin colour detection based on an improved dynamic threshold method to reduce false skin detection. Current fixed threshold skin detection fails in certain situations such as misclassification between non skin-like with similar skin-like colour. Any true skin may falsely be detected as non-skin. Research work introduces high-level skin detection strategy based on online sampling where offline … …American Journal of Applied Sciences, Vol. 13, Issue 2 · 19 Dec 2015 · 7,939 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Soft Sensor Modelling of Biomass Concentration during Fermentation using Accurate Incremental Online v-Support Vector Regression Learning AlgorithmBinjie Gu, Feng PanIn order to model real fermentation process, a soft sensor modelling of biomass concentration during fermentation using accurate incremental online ν-Support Vector Regression (ν-SVR) learning algorithm was proposed. Firstly, an accurate incremental online ν-SVR learning algorithm was proposed. This algorithm solved the two complications introduced in the dual problem based on the equivalent formulation of ν-SVR. Moreover, it addressed the … …American Journal of Biochemistry and Biotechnology, Vol. 11, Issue 3 · 8 Aug 2015 · 7,327 accessesView PDFCite
Research ArticleOpen accessIn the abstractANALYSIS OF BAYESIAN CLASSIFIER ACCURACYFelipe Schneider Costa, Maria Marlene De Souza Pires, Silvia Modesto NassarThe naïve Bayes classifier is considered one of the most effective classification algorithms today, competing with more modern and sophisticated classifiers. Despite being based on unrealistic (naïve) assumption that all variables are independent, given the output class, the classifier provides proper results. However, depending on the scenario utilized (network structure, number of samples or training cases, number of variables), the … …Journal of Computer Science, Vol. 9, Issue 11 · 26 Sep 2013 · 8,375 accessesView PDFCite
Research ArticleOpen accessIn the abstractA NOVEL APPROACH BASED ON GENETIC FUZZY CLUSTERING AND ADAPTIVE NEURAL NETWORKS FOR SALES FORECASTINGAttariuas Hichama, Bouhorma Mohameda, El Fallahi AbdellahbThis article proposes a new hybrid sales forecasting system based on genetic fuzzy clustering and Back-Propagation (BP) Neural Networks with adaptive learning rate (GFCBPN).The proposed architecture consists of three stages: (1) utilizing Winter’s Exponential Smoothing method and Fuzzy C-Means clustering, all normalized data records will be categorized into k clusters; (2) using an adapted Genetic Fuzzy System (MCGFS), the fuzzy … …Journal of Computer Science, Vol. 9, Issue 8 · 2 Jul 2013 · 6,669 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 · 7,754 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Face Recognition in Video by Bit Planes SlicingM. Jasmine Pemeena Priyadarsini, K. Murugesan, Srinivasa Rao Inbathini, Visal KumarProblem statement: Video-based face recognition must be able to overcome the imaging interference such as pose and illumination. Approach: A model is designed to study for face recognition based on video sequence and also test image. In training stage, single frontal image is taken as a input to the recognition system. A new virtual image is generated using bit plane … …Journal of Computer Science, Vol. 8, Issue 1 · 26 Oct 2011 · 7,420 accessesView PDFCite