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Conference proceedings front matter may contain various advertisements, welcome messages, committee or program information, and other miscellaneous conference information. This may in some cases also include the cover art, table of contents, copyright statements, title-page or half title-pages, blank pages, venue maps or other general information relating to the conference that was part of the original...
This study explores the applicability of the state of the art of deep learning convolutional neural network (CNN) to the classification of CT brain images, aiming at bring images into clinical applications. Towards this end, three categories are clustered, which contains subjects' data with either Alzheimer's disease (AD) or lesion (e.g. tumour) or normal ageing. Specifically, due to the characteristics...
Expert system can effectively reduce human error and improve the diagnostic quality. However, due to the medical domain knowledge is large and complex, effective knowledge representation or vocabularies standardization is important issues to ensure both shared understanding and interoperability between people and clinical decision support system (CDS). This paper uses a semantic model to convert natural...
Intelligence can be understood as an agent's ability to predict its environment's dynamic by a level of precision which allows it to effectively foresee opportunities and threats. Under the assumption that such intelligence relies on a knowledge space any effective reasoning would benefit from a maximum portion of useful and a minimum portion of misleading knowledge fragments. It begs the question...
Large high-performance computing systems are built with increasing number of components with more CPU cores, more memory, and more storage space. At the same time, scientific applications have been growing in complexity. Together, they are leading to more frequent unsuccessful job statuses on HPC systems. From measured job statuses, 23.4% of CPU time was spent to the unsuccessful jobs. We set out...
We present a compressed sensing based approach to multilabel classification that exploits the label structure present in many multilabel applications. The compressed sensing method exploits the sparsity in the label vector. The label vector is projected to a lower dimensional space by a random projection matrix. From the training data we learn how to predict the projected vector directly from the...
Obtaining extractive summaries by using functions induced from a training set continue to be a great challenge in the domain of the automatic text summary. This paper presents the VENCE method based on this approach and improves the quality of the abduced functions, using semantic relations of the words (attributes) of the training set that are fetched from a ontology to be inserted in this set. The...
Renewable energy like solar power is crucial for the transition to more sustainable energy supply and use in the modern society. Buildings with rooftop solar panels form microgrids acting as prosumers and are usually not under the control of the regulated companies operating the public grids. Currently much work has focused on the self-consumption of individual microgrids. On the contrary, the CoSSMic...
An Artificial Neural Network has been proposed as predicting the performance of the Software Defined Network according to effective traffic parameters. Those used in this study are round-trip time, throughput and the flow table rules for each switch, POX controller and OpenFlow switches, which characterize the behaviour of the Software Defined Network, have been modelled and simulated via Mininet...
In this paper, we consider the use of the forward time, centered space (FTCS) method to numerically solve the fuzzy heat equation. In particular, we study the effects on the numerical output of the use of two different types of fuzzifications.
Optic disc segmentation is a key element in automatic screening systems, which facilitates the detection of lesions that affect the interior surface of the eye (i.e. fundus). Therefore, this paper aims to provide a fully automated technique for detecting and segmenting the optic disc. First, the fundus image is preprocessed in order to estimate the approximate location of the optic disc, excluding...
This study provides an overview of International Financial Reporting Standards (IFRS) and highlights implications on Canadian Generally Accepted Accounting Principles (CGAAP) besides the influence IFRS will have on their future representation of Financial Statements — Annual Reports. However, the IFRS has developed a conceptual framework for the preparation and presentation of Financial Statement,...
The recording of brain activity at the scalp level, also known as electroencephalography (EEG), is a brain imaging technique commonly used in the clinical environment. Adequate modeling of the recorded signals could help to improve the diagnosis of several illnesses such as sleep disorders and epilepsy. This paper presents a computational cost analysis for dynamic modeling methods and considers their...
Infrared imaging captures the temperature distribution of the human body surface and is presently employed in various medical applications. Most of the conventional and commercial suites for thermal image processing provide only very basic tools to process thermal images which pose challenge to the medical professionals and analysts to interpret the combination of both functional and morphostructural...
Due to the huge increase in the size of the data it becomes troublesome to perform efficient analysis using the current traditional techniques. Big data put forward a lot of challenges due to its several characteristics like volume, velocity, variety, variability, value and complexity. Today there is not only a necessity for efficient data mining techniques to process large volume of data but in addition...
Teeth Periapical lesion is used to be diagnosed by dentists according to patient's x-ray. But most of the time there were a problematic issue to reach a definitive diagnosis. It takes too much time, case and chief complaint history needed, many tests and tools are needed and sometimes taking too many radiographs is required. Even though, before starting the treatment sometimes reaching definitive...
DNA Fragment Assembly Problem (FAP) is an attractive research topic in the field of bioinformatics. The aim of DNA FAP is to generate DNA sequences as close to the original sequence among the given fragments. Various metaheuristic algorithms are applied to DNA Fragment Assembly Problem to find the best matching scores as well as the optimum fragment orders to obtain the original DNA sequence. In this...
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