As low resolution shots, rotations of the head with respect to the camera, face deformation due to speech and so on inflict a great deal of uncertainty in FAP measurements, uncertainty is also inherent in the process ...
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ISBN:
(纸本)0780383532
As low resolution shots, rotations of the head with respect to the camera, face deformation due to speech and so on inflict a great deal of uncertainty in FAP measurements, uncertainty is also inherent in the process of expression analysis. In this paper we tackle such uncertainty via the observation that user emotions do not typically alter rapidly very often. Thus, possibilistic evidence may be gathered from each frame about the user expression;evidence from the current and recent frames can be combined using evidence theory.
We describe a cell bank construction which was designed by a content-based image retrieval system using SQL database and XML for breast carcinoma images. However, the conventional pathological images for storage, mana...
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A unified strategy for reforming all engineering curricula at the sch.ol of engineering and Applied science (SEAS) by integrating academic skills and enhancing the learning culture is discussed. The academic skills ar...
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A unified strategy for reforming all engineering curricula at the sch.ol of engineering and Applied science (SEAS) by integrating academic skills and enhancing the learning culture is discussed. The academic skills are integrated throughout the four years and the learning culture is enhanced by utilizing teams comprised of students, faculty and industrial representatives. This strategy is designed to enhance the educational environment within SEAS as enrollment increases and to provide an integrated first-year curriculum for all majors. This strategy is an effort to create an intellectual interdisciplinary community within SEAS to provide an enhanced collaborative learning environment.
In this paper we propose a hybrid model which includes both first principles differential equations and a least squares support vector machine (LS-SVM). It is used to forecast and control an environmental process. Thi...
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In this paper we propose a hybrid model which includes both first principles differential equations and a least squares support vector machine (LS-SVM). It is used to forecast and control an environmental process. This inclusion of the first principles knowledge in this hybrid model is shown to improve substantially the stability of the model predictions in spite of the unmeasurability of some of the key parameters. Proposed hybrid model is compared with both a hybrid neural network(HNN) as well as hybrid neural network with extended kalman filter (HNN-EKF). From experimental results, proposed hybrid model shown to be far superior when used for extrapolation compared to HNN and HNN-EKF.
Now-a-days, spell checker has become an essential part of any application software. Today, undoubtedly it can be acknowledged that Microsoft Office is the most widely used software bundle all over the world. But unfor...
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ISBN:
(纸本)0646423134
Now-a-days, spell checker has become an essential part of any application software. Today, undoubtedly it can be acknowledged that Microsoft Office is the most widely used software bundle all over the world. But unfortunately it provides the spell checking tool only for some limited languages. South Asian languages are deprived more in this case though more than 100 million people live in this region and use their very rich local languages like Bangla, Hindi, Tamil etc. These languages are far different from Western languages in phonetic properties and grammatical rules. This is why the existing algorithms and techniques that are being used to check the spelling and to generate efficient suggestions for miss-spelt words of English and other Western languages are not actually suitable for South Asian languages;rather they need different algorithms and techniques for expected efficiency. This paper is an approach to present a new algorithm based on the existing algorithms to generate suggestions for miss-spelt words along with a complete design and implementation of a spell checker which is much efficient for South Asian languages.
This paper discusses a host-independent network system where a network interface card is utilized in an efficient way. By eliminating protocol stack processing overheads from host system, the proposed system improves ...
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This paper discusses a host-independent network system where a network interface card is utilized in an efficient way. By eliminating protocol stack processing overheads from host system, the proposed system improves the communication speed by 11-36% under heavy network and CPU loads.
We constructed a three-dimensional fractal model of the vascular network in a tumour periphery. We model the highly disorganised structure of the neoplastic vasculature by using a high degree of variation in segment p...
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We constructed a three-dimensional fractal model of the vascular network in a tumour periphery. We model the highly disorganised structure of the neoplastic vasculature by using a high degree of variation in segment properties such as length, diameter and branching angle. The overall appearance of the vascular tree is subjectively similar to that of the disorganised vascular network which encapsulates tumours. The fractal dimension of the model is within the range of clinically measured values.
Hierarchical approaches, which are dominated by the generic agglomerative clustering algorithm, are suitable for cases in which the count of distinct clusters in the data is not known a priori;this is not a rare case ...
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ISBN:
(纸本)9728865007
Hierarchical approaches, which are dominated by the generic agglomerative clustering algorithm, are suitable for cases in which the count of distinct clusters in the data is not known a priori;this is not a rare case in real data. On the other hand, important problems are related to their application, such as susceptibility to errors in the initial steps that propagate all the way to the final output and high complexity. Finally, similarly to all other clustering techniques, their efficiency decreases as the dimensionality of their input increases. In this paper we propose a robust, generalized, quick and efficient extension to the generic agglomerative clustering process. Robust refers to the proposed approach's ability to overcome the classic algorithm's susceptibility to errors in the initial steps, generalized to its ability to simultaneously consider multiple distance metrics, quick to its suitability for application to larger datasets via the application of the computationally expensive components to only a subset of the available data samples and efficient to its ability to produce results that are comparable to those of trained classifiers, largely outperforming the generic agglomerative process.
Standards for the storage, description and visualisation of the large datasets produced by numerical computational models in biomedicine are essential to ensure the success of international efforts such as the Physiom...
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ISBN:
(纸本)0889863792
Standards for the storage, description and visualisation of the large datasets produced by numerical computational models in biomedicine are essential to ensure the success of international efforts such as the Physiome Project [12]. In this paper we present Visiome, a toolkit for the description and visualisation of these datasets. Visiome enables investigators to use intuitive mathematical expressions to define the shading, colour, texture and animation of an interactive 3D rendering. Visiome has been developed in conjunction with our own computational models of activation in the mammalian sinoatrial node and we show a number of visualisations of those models.
Machine Learning has traditionally been a topic of research and instruction in computerscience and computerengineering programs. Yet, due to its wide applicability in a variety of fields, its research use has expand...
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Machine Learning has traditionally been a topic of research and instruction in computerscience and computerengineering programs. Yet, due to its wide applicability in a variety of fields, its research use has expanded in other disciplines, such as electrical engineering, industrial engineering, civil engineering, and mechanical engineering. Currently, many undergraduate and first-year graduate students in the aforementioned fields do not have exposure to recent research trends in Machine Learning. This paper reports on a project in progress, funded by the National science Foundation under the program Combined Research and Curriculum Development (CRCD), whose goal is to remedy this shortcoming. The project involves the development of a model for the integration of Machine Learning into the undergraduate curriculum of those engineering and science disciplines mentioned above. The goal is increased exposure to Machine Learning technology for a wider range of students in science and engineering than is currently available. Our approach of integrating Machine Learning research into the curriculum involves two components. The first component is the incorporation of Machine Learning modules into the first two years of the curriculum with the goal of sparking student interest in the field. The second is the development of new upper level Machine Learning courses for advanced undergraduate students. The paper will focus on the details of the integration of a machine learning module (related to neural networks) applied to a Numerical Analysis class, taught to sophomores and juniors in the engineering Departments at the University of Central Florida. Furthermore, it will report results on the assessment and evaluation of the effectiveness of the module by the students taking the class. Finally, based on the assessment results some conclusions will be drawn regarding the potential of the modules in attracting undergraduate students into research, specifically machine-learning
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