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44 results for “Decomposition model”
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Research ArticleOpen accessIn the abstractReal-Time Monitoring and Injury Risk Warning Algorithm Based on Data Fusion of Motor Muscle ContractionGuomin Wang, Jingying HuangThe existing sports injury warning algorithms are difficult to achieve dynamic injury risk modeling based on individual muscle characteristics while ensuring real-time fusion efficiency of multimodal signals. This article proposes a real-time muscle contraction state perception and injury risk warning algorithm based on adaptive weighted feature fusion and lightweight temporal modeling. The system synchronously collected surface electromyography (sEMG), Inertial Measurement … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 3 · 10 Aug 2026 · 1,089 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Risk of Diabetes using a Model based on Multilayer Perceptron and Features ExtractionFrancesca Fallucchi, Alessandro CabroniDiabetes (diabetes mellitus) is a disease emerging when a person has a high blood sugar level for a prolonged period. In the healthcare context, one of the most important topic is the prevention of the disease. This study relates to diabetes prevention. In particular, it aims to produce random generated datasets according to a rule named Finnish Diabetes Risk Score … …Journal of Computer Science, Vol. 17, Issue 9 · 7 Sep 2021 · 6,580 accessesView PDFCite
Research ArticleOpen accessIn the abstractEarly Detection and Classification Approach for Plant Diseases based on MultiScale Image DecompositionAssia Ennouni, Noura Ouled Sihamman, My Abdelouahed Sabri, Abdellah AarabThis paper presents a new and powerful approach for detecting and classifying leaf diseases for plant diagnosis with high accuracy. The main contribution of this paper is that a hybrid approach is proposed by using the combination of Partial Differential Equations (PDE) based image decomposition, segmentation, feature extraction, features selection and classification aiming to improve the classification accuracy and provide … …Journal of Computer Science, Vol. 17, Issue 3 · 25 Mar 2021 · 7,205 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvSVD++: A Hybrid Deep CF Recommender Model using Convolutional Neural NetworkMohamed Grida, Lamiaa Fayed, Mohamed HassanRecommender systems are powerful systems that give added value to business and corporation. They are relatively recent technology and they will only keep improving in the future. The most widely used algorithms for recommender systems are categorized into the traditional recommender and deep-based recommender system. The traditional recommendation algorithm suffers from sparse data that significantly degrades recommendation accuracy. The hybrid … …Journal of Computer Science, Vol. 16, Issue 12 · 13 Jan 2021 · 6,731 accessesView PDFCite
Research ArticleOpen accessIn the abstractECG Energy Change Study Based on Variational Mode DecompositionKai Dong, Lin Sun, Hongjun Xiong, Wenbo WangVariational Mode Decomposition (VMD) decomposes the signal into a series of Intrinsic Mode Type Functions (IMTFs) according with variational model and fluctuating characteristics of the signal itself, thus very suitable for the analysis of nonlinear and non-stationary Electrocardiogram (ECG) signal. Energy of ECG signal has certain distribution rules, but which could be affected by diseases; therefore, the study of ECG … …American Journal of Biochemistry and Biotechnology, Vol. 16, Issue 1 · 12 Mar 2020 · 7,397 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultiresolution Laplacian Sparse Coding Technique for Image ClassificationIntidhar Jemel, Ridha Ejbali, Mourad ZaiedSparse coding is a set of techniques used for learning a collection of over-complete bases to represent data efficiently. This technique has been used in different domain such as feature quantization and image classification. Despite its capacity of modeling, it could not represent similarity of the image coding which cause a poor performance in locality. The cause of this limitation … …Journal of Computer Science, Vol. 14, Issue 8 · 23 May 2018 · 7,920 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrediction on Land Market Value Based on the Real Estate Market in USALei WangThe Land Market Value, defined as the total value of land price and quantity data are derived from data on housing values, is an important factor in the estimation of structure costs using price indexes for housing and construction costs. In this study, we gather and analyze 34 years' national data on past and present real estate transaction. According to … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 23 May 2017 · 7,555 accessesView PDFCite
Research ArticleOpen accessIn the abstractHydrological Forecasting Using Hybrid Data-Driven ApproachYoungmin Seo, Sungwon KimThis study develops a hybrid model, EEMD-FANN, coupling feed Forward Artificial Neural Network (FANN) and Ensemble Empirical Mode Decomposition (EEMD) for improving the accuracy of daily river stage forecasting. An original river stage data is broken down into a residue and Intrinsic Mode Functions (IMFs) using the EEMD and different FANNs are developed as forecasting models for the decomposed IMFs … …American Journal of Applied Sciences, Vol. 13, Issue 8 · 2 Sep 2016 · 8,136 accessesView PDFCite
Research ArticleOpen accessIn the abstractConformal Mapping of Temperature Variation in Compost HeapJonah Chukwuemeka Agunwamba, Oji Achuka NwokeLaboratory in vessel trapezoidal compost system was designed and constructed. Temperature variation in the compost heap was measured for five days at various depths. Mathematical model for the variation of temperature of the composting process was developed using Conformal Mapping Technique. One of the parameters in the model had two distinct roots, one a positive root and the other negative … …American Journal of Environmental Sciences, Vol. 12, Issue 3 · 17 Jun 2016 · 7,347 accessesView PDFCite