Search results for "methodologies"
showing 10 items of 2106 documents
Environmental Problem-solving and Hands-on Geometry Learning through Storytelling inside a Geodesic Dome : Ice, Honey and Stardust
2019
In this workshop, we introduce a STEAM learning activity based on the construction of geodesic domes. This workshop will engage participants in various preliminary and exploratory constructions, while also applying the geometry of geodesic domes to approximate hemispheres. Various storytelling, role-playing, and environmental connections that can provide needed context for learners of all ages are explored. peerReviewed
Enterprise Architecture Benefits: Perceptions from Literature and Practice
2008
First published in the Proceedings of the 7th IBIMA Conference Internet & Information Systems in the Digital Age, 14-16 December, 2006, Brescia, Italy Enterprise Architecture (EA) is considered a means for acquiring a multitude of benefits in organizations by most academic literature and practitioners alike. However, academic research has almost omitted the domain of EA benefits and value realization, and thus more research on the subject is needed. This paper describes a study which aims to chart the benefits of EA by a comprehensive literature review and a focus group interview of practitioners. As a result, a categorization of the EA benefits is composed and analyzed.
A Goal-Oriented Way to Define Metrics for an Enterprise Architecture Program
2008
First published in the Journal of Enterprise Architecture, Vol. 4, No. 1, 2008, pp. 20-26. Republished with the kind permission of the Journal of Enterprise Architecture Metrics are becoming more and more important in the development of enterprise architecture (EA) programs. Therefore, guidelines and support to define metrics for EA programs are needed. A goal-oriented approach for defining metrics for EA program and the measurement aspects for EA program are presented in this article. This approach was developed and tested during the development of proposals of EA program metrics for two companies. peerReviewed
Text Classification Using “Anti”-Bayesian Quantile Statistics-Based Classifiers
2016
The problem of Text Classification (TC) has been studied for decades, and this problem is particularly interesting because the features are derived from syntactic or semantic indicators, while the classification, in and of itself, is based on statistical Pattern Recognition (PR) strategies. Thus, all the recorded TC schemes work using the fundamental paradigm that once the statistical features are inferred from the syntactic/semantic indicators, the classifiers themselves are the well-established ones such as the Bayesian, the Na¨ıve Bayesian, the SVM etc. and those that are neural or fuzzy. In this paper, we shall demonstrate that by virtue of the skewed distributions of the features, one …
Spam classification for online discussions
2010
Masteroppgave i informasjons- og kommunikasjonsteknologi 2010 – Universitetet i Agder, Grimstad Traditionally, spam messages filtering systems are built by integrating content-based analysis technologies which are developed from the experiences of dealing with E-mail spam. Recently, the new style of information appears in the Internet, Social Media platform, which also expands the space for Internet abusers. In this thesis, we not only evaluated the traditional content-based approaches to classify spam messages, we also investigated the possibility of integrating context-based technology with con-tent-based approaches to classify spam messages. We built spam classifiers using Novelty de-tec…
Metadata record for: Comprehensive dataset of shotgun metagenomes from oxygen stratified freshwater lakes and ponds
2021
This dataset contains key characteristics about the data described in the Data Descriptor Comprehensive dataset of shotgun metagenomes from oxygen stratified freshwater lakes and ponds. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
Study on Support Vector Machine-Based Fault Detection in Tennessee Eastman Process
2014
Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/836895 Open Access This paper investigates the proficiency of support vector machine (SVM) using datasets generated by Tennessee Eastman process simulation for fault detection. Due to its excellent performance in generalization, the classification performance of SVM is satisfactory. SVM algorithm combined with kernel function has the nonlinear attribute and can better handle the case where samples and attributes are massive. In addition, with forehand optimizing the parameters using the cross-validation technique, SVM can produce high accuracy i…
A mahalanobis hyperellipsoidal learning machine class incremental learning algorithm
2014
Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/894246 Open Access A Mahalanobis hyperellipsoidal learning machine class incremental learning algorithm is proposed. To each class sample, the hyperellipsoidal that encloses as many as possible and pushes the outlier samples away is trained in the feature space. In the process of incremental learning, only one subclassifier is trained with the new class samples. The old models of the classifier are not influenced and can be reused. In the process of classification, considering the information of sample's distribution in the feature space, the Ma…
Research on Vocabulary Sizes and Codebook Universality
2014
Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/697245 Open Access Codebook is an effective image representation method. By clustering in local image descriptors, a codebook is shown to be a distinctive image feature and widely applied in object classification. In almost all existing works on codebooks, the building of the visual vocabulary follows a basic routine, that is, extracting local image descriptors and clustering with a user-designated number of clusters. The problem with this routine lies in that building a codebook for each single dataset is not efficient. In order to deal with th…
Khmer character recognition using artificial neural network
2014
Character Recognition has become an interesting and a challenge topic research in the field of pattern recognition in recent decade. It has numerous applications including bank cheques, address sorting and conversion of handwritten or printed character into machine-readable form. Artificial neural network including self-organization map and multilayer perceptron network with the learning ability could offer the solution to character recognition problem. In this paper presents Khmer Character Recognition (KCR) system implemented in Matlab environment using artificial neural networks. The KCR system described the utilization of integrated self-organization map (SOM) network and multilayer per…