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New feature splitting criteria for co-training using genetic algorithm optimization

Often in real world applications only a small number of labeled data is available while unlabeled data is abundant. Therefore, it is important to make use of unlabeled data. Co-training is a popular semi-supervised learning technique that uses a small set of labeled data and enough unlabeled data to create more accurate classification models. A key feature for successful co-training is to split

Circuit Theory and Applications
Innovation, Entrepreneurship and Competitiveness

Interactive 3D visualization for wireless sensor networks

Wireless sensor networks open up a new realm of ubiquitous computing applications based on distributed large-scale data collection by embedded sensor nodes that are wirelessly connected and seamlessly integrated within the environment. 3D visualization of sensory data is a challenging issue, however, due to the large number of sensors used in typical deployments, continuous data streams, and

Software and Communications
Innovation, Entrepreneurship and Competitiveness

Different regions identification in composite strain-encoded (C-SENC) images using machine learning techniques

Different heart tissue identification is important for therapeutic decision-making in patients with myocardial infarction (MI), this provides physicians with a better clinical decision-making tool. Composite Strain Encoding (C-SENC) is an MRI acquisition technique that is used to acquire cardiac tissue viability and contractility images. It combines the use of blackblood delayed-enhancement (DE)

Artificial Intelligence
Healthcare

Segmentation of ascending and descending aorta from magnetic resonance flow images

In this work, we propose an algorithm for segmenting the ascending and descending aorta from magnetic resonance phase contrast images, also referred to as MR flow imaging. The proposed algorithm is based on the active contour model combined with some refinements. In addition, false segmentation results due to severe image artifacts are automatically detected and corrected. The developed algorithm

Artificial Intelligence
Healthcare

Body and visual sensor fusion for motion analysis in Ubiquitous healthcare systems

Human motion analysis provides a valuable solution for monitoring the wellbeing of the elderly, quantifying post-operative patient recovery and monitoring the progression of neurodegenerative diseases such as Parkinson's. The development of accurate motion analysis models, however, requires the integration of multi-sensing modalities and the utilization of appropriate data analysis techniques

Artificial Intelligence
Healthcare

Change analysis for gait impairment quantification in smart environments

Visual Sensor Networks (VSNs) open up a new realm of smart autonomous applications based on enhanced three- dimensional sensing and collaborative reasoning. An emerging VSN application domain is pervasive healthcare delivery where gait information computed from distributed vision nodes is used for observing the wellbeing of the elderly, quantifying post-operative patient recovery and monitoring

Healthcare
Software and Communications

Parallel suffix sorting based on bucket pointer refinement

Suffix array is one of the most important data structures in bioinformatics. Much effort has been devoted to find efficient sequential algorithms for its construction, but little is done to introduce parallel construction algorithms. The bucket pointer refinement algorithm is one of the efficient suffix sorting algorithms that is tuned for genomic datasets. In this paper, we introduce a parallel

Healthcare

Parallel chaining algorithms

Given a set of weighted hyper-rectangles in a k-dimensional space, the chaining problem is to identify a set of colinear and non-overlapping hyper-rectangles of total maximal weight. This problem is used in a number of applications in bioinformatics, string processing, and VLSI design. In this paper, we present parallel versions of the chaining algorithm for bioinformatics applications, running on

Healthcare

Exploiting neural networks to enhance trend forecasting for hotels reservations

Hotel revenue management is perceived as a managerial tool for room revenue maximization. A typical revenue management system contains two main components: Forecasting and Optimization. A forecasting component that gives accurate forecasts is a cornerstone in any revenue management system. It simply draws a good picture for the future demand. The output of the forecast component is then used for

Artificial Intelligence
Software and Communications

Investigating analysis of speech content through text classification

The field of Text Mining has evolved over the past years to analyze textual resources. However, it can be used in several other applications. In this research, we are particularly interested in performing text mining techniques on audio materials after translating them into texts in order to detect the speakers' emotions. We describe our overall methodology and present our experimental results. In

Artificial Intelligence
Software and Communications