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54 articles for “data pre-processing”
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Research ArticleOpen accessIn the abstractSoft Sensors for Monitoring Combustion Quality and Flue Gas Emissions in Power Station BoilersNallamilli P G Bhavani, Kesavan Sujatha, Ponmagal RajendranThis research work includes a combination of Fisher’s Linear Discriminant (FLD) analysis by merging Radial Basis Function (RBF) Network and Back Propagation Algorithm (BPA) for monitoring the combustion conditions of a coal fired boiler. The CCD Camera is used to capture the two dimensional flame images. The features such as images, average intensity, area, brightness and orientation etc., of the … …American Journal of Applied Sciences, Vol. 15, Issue 1 · 7 Feb 2018 · 7,556 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultipatch-GLCM for Texture Feature Extraction on Classification of the Colon Histopathology Images using Deep Neural Network with GPU AccelerationToto Haryanto, Adib Pratama, Heru Suhartanto et al.Cancer is one of the leading causes of death in the world. It is the main reason why research in this field becomes challenging. Not only for the pathologist but also from the view of a computer scientist. Hematoxylin and Eosin (H&E) images are the most common modalities used by the pathologist for cancer detection. The status of cancer with … …Journal of Computer Science, Vol. 16, Issue 3 · 5 Mar 2020 · 9,223 accessesView PDFCite
Research ArticleOpen accessIn the abstractEstimation of Milk Fatty Acids Health Index as Milk Value Added Determinant using FT-NIRSDespal Despal, Dwitamy Anzhany, Idat Galih Permana et al.The current milk price system based on Total Plate Count (TPC) and Total Solids (TS) are less sensitive in determining milk quality. Milk fatty acids profiles reflected milk quality for human health. However, their determination using Gas Chromatography (GC) is impracticable to be included as a daily price decision determinant. The study aimed to find a model for milk value … …American Journal of Animal and Veterinary Sciences, Vol. 16, Issue 4 · 23 Dec 2021 · 6,946 accessesView PDFCite
Research ArticleOpen accessIn the abstractTwo-Stage Estimation in Inverse Problems using Combined Wavelet Thresholding and Penalized Maximum LikelihoodRobert G Aykroyd, Hassan AljohaniInverse problems occur in a wide range of practical scientific investigations where the variables of interest are only observed indirectly, such as magnetic and seismic imaging in geophysics, electrical tomography in industrial process monitoring, or PET scanning in medicine. Linear inverse problems can be thought of as highly multivariate regression problems with strong multicollinearity where the aim is to interpret … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 29 Sep 2017 · 7,928 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest Classification and Support Vector Machine for Detecting Epilepsyusing Electroencephalograph RecordsHeri Kuswanto, Mutiah Salamah, Muhammad Idrus FachruddinComplexity in data structure has led to the rapid development of computational statistics methods. Machine learning approaches have been introduced and applied to solve complex problems in many fields. This paper applies two common machine learning approaches, Random Forest (RF) and Support Vector Machine (SVM), in the detection of epilepsy. The diagnosis of epilepsy can usually only be made when … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 4 May 2017 · 8,141 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
Research ArticleOpen accessIn the abstractParameters Optimization of Adaptive Cashew Shelling Cutter Based on BP Neural Network and Genetic AlgorithmYun-Fei Fu, Jie Gong, Hui Huang et al.The aim of this study is to determine the optimal parameters of the adaptive cashew shelling cutter. To meet the requirements of cashew nut processing enterprises, this study takes the whole-kernel rate as the optimization objective. Let the three main parameters of the adaptive cashew shelling cutter: The distance between upper and lower cutters, the pre-pressure of the spring and … …American Journal of Engineering and Applied Sciences, Vol. 8, Issue 4 · 1 Nov 2015 · 7,907 accessesView PDFCite
Research ArticleOpen accessIn the abstractRadial Basis Function Network Dependent Exclusive Mutual Interpolation for Missing Value ImputationR. S. Somasundaram, R. NedunchezhianThe success of data mining relies on the purity of the data set. Before performing the data mining, the data has to be cleaned. An unprocessed data set may contain noisy or missing values which is a critical research issue in the pre-processing stage. Imputation methods are being used to solve the missing value problems. In this proposed work, a … …Journal of Computer Science, Vol. 9, Issue 3 · 24 Apr 2013 · 7,008 accessesView PDFCite
Research ArticleOpen accessIn the abstractPartial Least Squares Regression Based Variables Selection for Water Level PredictionsNoraini Ibrahim, Antoni WibowoFloods are common phenomenon in the state of Kuala Krai, specifically in Kelantan-Malaysia. Every year, floods affecting biodiversity on this region and also causing property loss of this residential area. The residents in Kelantan always suffered from floods since the water overflows to the areas adjoining to the rivers, lakes or dams. Months, average monthly rainfall, temperature, relative humidity and … …American Journal of Applied Sciences, Vol. 10, Issue 4 · 7 Apr 2013 · 6,624 accessesView PDFCite
Research ArticleOpen accessIn the abstractNeural Networks Based Nonlinear Time Series Regression for Water Level Forecasting of Dungun RiverSiti Hajar Arbain, Antoni WibowoThe Department of Irrigation and Drainage (DID) Malaysia and Meteorological Malaysia Department (MMD) has been measured the flood characteristics benchmark which included water level, area inundation, peak inundation, peak discharge, volume of flow and duration of flooding. In terms of water levels, DID have introduced three categories of critical level stages namely normal, alert and danger levels. One of the … …Journal of Computer Science, Vol. 8, Issue 9 · 13 Aug 2012 · 7,800 accessesView PDFCite