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177 results for “Problem-Based Learning”
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Research ArticleOpen accessIn the abstractFeature Selection for High Dimensional Data: An Evolutionary Filter ApproachAnwar Ali Yahya, Addin Osman, Abd Rahman Ramli, Adlan BalolaProblem statement: Feature selection is a task of crucial importance for the application of machine learning in various domains. In addition, the recent increase of data dimensionality poses a severe challenge to many existing feature selection approaches with respect to efficiency and effectiveness. As an example, genetic algorithm is an effective search algorithm that lends itself directly to feature selection; … …Journal of Computer Science, Vol. 7, Issue 5 · 9 May 2011 · 7,949 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Virtual Repository Approach to Departmental Information SharingZulikha Jamaludin, Wan Hussain Wan IshakProblem Statement: Realizing the difficulties in information sharing among the academicians, this study introduces an alternative information sharing model supporting information management features. Objective: The model is designed in an attempt to facilitate information distribution and information sharing at minimum effort and cost. Approach: A centralized database approach is used in the model enabling any educator in the higher learning … …American Journal of Economics and Business Administration, Vol. 3, Issue 1 · 7 Jan 2011 · 8,649 accessesView PDFCite
Research ArticleOpen accessIn the abstractNeural Network Change Detection Model for Satellite Images Using Textural and Spectral CharacteristicsA. K. Helmy, Gh. S. El-TaweelProblem statement: Change detection is the process of identifying difference of the state of an object or phenomena by observing it at different time. Essentially, it involves the ability to quantify temporal effects using multi-temporal data sets. Information about change is necessary for evaluating land cover and the management of natural resources. Approach: A neural network model based on both … …American Journal of Engineering and Applied Sciences, Vol. 3, Issue 4 · 4 Nov 2010 · 8,162 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmail Spam Classification Using Gated Recurrent Unit and Long Short-Term MemoryIqbal Basyar, Adiwijaya, Danang Triantoro MurdiansyahHigh numbers of spam emails have led to an increase in email triage, causing losses amounting to USD 355 million per year. One way to reduce this loss is to classify spam email into categories including fraud or promotions made by unwanted parties. The initial development of spam email classification was based on simple methods such as word filters. Now, … …Journal of Computer Science, Vol. 16, Issue 4 · 3 Apr 2020 · 8,333 accessesView PDFCite
Research ArticleOpen accessIn the abstractBoosting Kernel Discriminative Common Vectors for Face RecognitionC. Lakshmi, M. PonnavaikkoProblem statement: Kernel discriminative common vector (KDCV) was one of the most effective non-linear techniques for feature extraction from high dimensional data including images and text data. Approach: This study presented a new algorithm called Boosting Kernel Discriminative Common Vector (BKDCV) to further improve the overall performance of KDCV by integrating the boosting and KDCV techniques. Results: In BKDCV, the … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,579 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimal Thyristor Control Series Capacitor Neuro-Controller for Damping OscillationsM. Magaji, M. W. MustafaThis study applies a neural-network-based optimal TCSC controller for damping oscillations. Optimal neural network controller is related to model-reference adaptive control, the network controller is developed based on the recursive "pseudo-linear regression". Problem statement: The optimal NN controller is designed to damp out the low frequency local and inter-area oscillations of the large power system. Approach: Two multilayer-perceptron neural networks … …Journal of Computer Science, Vol. 5, Issue 12 · 31 Dec 2009 · 7,283 accessesView PDFCite
Research ArticleOpen accessIn the abstractGenetic Algorithm Based Probabilistic Motif Discovery in Unaligned Biological SequencesM. Hemalatha, K. VivekanandanFinding motif in biosequences is the most important primitive operation in computational biology. There are many computational requirements for a motif discovery algorithm such as computer memory space requirement and computational complexity. To overcome the complexity of motif discovery, we propose an alternative solution integrating genetic algorithm and Fuzzy Art machine learning approaches for eliminating multiple sequence alignment process. Problem … …Journal of Computer Science, Vol. 4, Issue 8 · 31 Aug 2008 · 6,730 accessesView PDFCite
Research ArticleOpen accessIn the abstractFramework of Regression-Based Graph Matrix Analysis Approach in Multi-Relational Social Network ProblemFord Lumban Gaol, Belawati WidjajaCommunity mining is one of the major directions in social network analysis. Social network analysis has attracted much attention in recent years. Most of the existing methods on community mining assume that there is only one kind of relation in the network and moreover, the mining results are independent of the users’ needs or preferences. However, in reality, there exist … …Journal of Mathematics and Statistics, Vol. 4, Issue 1 · 31 Mar 2008 · 6,927 accessesView PDFCite
Research ArticleOpen accessIn the abstractArabic Named Entity Recognition Using Artificial Neural NetworkNaji F. Mohammed, Nazlia OmarProblem statement: Named Entity Recognition (NER) is a task to identify proper names as well as temporal and numeric expressions, in an open-domain text. The NER task can help to improve the performance of various Natural Language Processing (NLP) applications such as Information Extraction (IE), Information Retrieval (IR) and Question Answering (QA) tasks. This study discusses on the Named Entity … …Journal of Computer Science, Vol. 8, Issue 8 · 16 Jul 2012 · 8,681 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Algorithm for Fractal Coding Using Self Organizing MapS. Bhavani, k. ThanushkodiProblem statement: In medical imaging, lossy compression schemes are generally not used due to possible loss of useful clinical information and also degradations may result in lossy compression owing to operations like enhancement. As the medical images are huge in size a good lossy compression technology is required to store them in medical archives in an economical manner. There is … …Journal of Computer Science, Vol. 8, Issue 6 · 15 Mar 2012 · 7,588 accessesView PDFCite