Learning Techniques
A SLA-Aware Scheduling Architecture in Grid System Using Learning Techniques
... In the Grid environment, the relationship between a customer and a service provider should be clearly defined. The responsibility of each partner can be stated in the so-called Service Level Agreement (SLA). A SLA is a ...
10
Learning ecosystem for higher education disruption: A new approach proposal based on blended active learning techniques
... Active Learning, promoted by the Center for Excellence in Teaching of the Portucalense University (CET-UPT), in July 2017, the challenge was to develop an innovative pilot ...Active Learning ...
12
Machine learning techniques for accuracy improvement of RANS simulations
... machine learning has entered the universe of computational fluid dynamics simulations of turbulent flows aiming to correct the shortcomings of the turbulence models of describing phenomena such as separation of ...
90
Precipitates Segmentation from Scanning Electron Microscope Images through Machine Learning Techniques
... machine learning techniques, we used here five implementations: Self Organizing Maps (SOM), Optimum-Path Forest (OPF), SVM without ker- nel mapping (SVM-nokernel), SVM with RBF (Radial Basis Function) as ...
13
Using Linguistic Information and Machine Learning Techniques to Identify Entities from Juridical Documents
... We propose a mixed approach, using linguistic information and machine learning techniques. In this approach, top-level legal concepts are identified and used for document classification using a well known ...
18
Comparative Performance Analysis of Machine Learning Techniques for Software Bug Detection
... machine learning techniques for software bug ...mining techniques for software bug prediction but did not provide the comparative performance analysis of ...machine learning techniques ...
9
Water demand modeling using machine learning techniques
... Water demand forecasting is fundamental to decisions related to long-term water resources management. However, spatial variability of water consumption may turn prediction into a difficult task. The main purpose of the ...
61
Twitter Sentiment Analysis of Movie Reviews using Machine Learning Techniques.
... In general, various symbolic techniques and machine learning techniques are used to analyze the sentiment from the twitter data. So in another way we can say that a sentiment analysis is a system or ...
7
Influence of heartwood on wood density and pulp properties explained by machine learning techniques
... Machine learning focuses on the biological learning process and tries to emulate it through algorithms that are able to learn from given data and provide new ...Machine learning techniques ...
10
Distinguishing long non-coding RNAs from protein coding transcripts based on machine learning techniques
... Among the analyses that have to be performed in sequencing projects, an important problem to be addressed is the distinction of protein coding transcripts (PCTs) and long non-coding RNAs (lncRNA). This work investigates ...
93
Machine learning techniques for music information retrieval
... classifications techniques 15 to deal with multiple labels such as k-nearest neighbors [Zhang and Zhou, 2005], neural networks [Zhang and Zhou, 2006], and support vector machines [Elisseeff and Weston, 2001, ...
210
Learning techniques for automatic email message tagging
... Farkas et al [32] present a work in the field of automatic tagging on news articles. They ex- tract potential tags from the documents through linguistic analysis and from external sources. In order to limit the number of ...
82
Cyberthreat discovery in open source intelligence using deep learning techniques
... In our working problem, the data consists of tweets, whose content is basically con- veyed as text, thus calling for Natural Language Processing (NLP) techniques to be re- sorted to. Additionally, in recent ...
81
Improving cyberthreat discovery in open source intelligence using deep learning techniques
... In short, the network receives a tweet in the input layer, then converts indexes to vectors in the embedding layer, followed by the convolutional layer containing several different kerne[r] ...
83
Customer Clustering in the Insurance Sector by Means of Unsupervised Machine Learning Techniques
... 10 The second divisive algorithm that should be presented is bisecting k-means. The bisecting k-means clustering algorithm tries to combine the time efficiency of the k-means algorithm with the high quality results from ...
122
Application of machine learning techniques on the discovery and annotation of transposons in genomes
... Support vector machines are a set of related supervised learning methods used for classification and regression. They use a nonlinear mapping to transform the original training data into a higher dimension. Within ...
122
Embedded real-time speed limit sign recognition using image processing and machine learning techniques
... Many of the ADAS systems use computer vision techniques in their oper- ations. For example, Lane Departure Warning System (LDWS) is a warning system that alerts the driver when he or she is veering out of or ...
21
Tool Wear Prediction System Using Deep-Learning Techniques on High Precision Milling Process
... In order to overcome this problem on the regression networks, an approach used weights in order to raise the priority of the pairs where the flank wear 30 > 𝑉𝐵 > 100. This procedure forced the networks to improve ...
137
Using Multiple Instance Learning techniques to rank maize ears according to their traits
... Predicting crop is a Multiple Instance Regression problem which is a challenge that needs proper attention (Wagstaff and Roper 2008). Accuracy of yield prediction will improve the management of maize ear cultivation with ...
64
Machine-learning techniques and short-term combination forecasting of industrial production
... of techniques are used in the process of forecasting ...2017). Techniques that combine forecasts made using different methods into a single more accurate forecast have also been used (Elliott et ...
10