Alzheimer’s disease (AD) is the most leading symptom of neurodegenerative dementia; AD is defined now as one of the most costly chronic diseases. For that automatic diagnosis and control of Alzheimer’s disease may h...
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Alzheimer’s disease (AD) is the most leading symptom of neurodegenerative dementia; AD is defined now as one of the most costly chronic diseases. For that automatic diagnosis and control of Alzheimer’s disease may have a significant effect on society along with patient well-being. Language disorder is regarded to be among the most common symptoms of AD, as a direct and natural result of cognitive impairment. Hence, the diagnosis of Alzheimer’s disease using speech-based features is gaining growing attention. The aim of this study is to extract linguistic features following a proposed taxonomy of language impairment of AD patients. Obtained results indicate that the proposed taxonomy of the linguistic features extracted from the speech samples can be used to differentiate between Alzheimer’s disease patients and the healthy control group. Support Vector Machine (SVM) classifier obtained classification accuracy over 90 percent.
Business process outsourcing has regained further attention with the emergence of Cloud computing. In fact, enterprises can benefit from the cloud at the service (i.e., business), the platform and/or the infrastructur...
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ISBN:
(纸本)9781479904051
Business process outsourcing has regained further attention with the emergence of Cloud computing. In fact, enterprises can benefit from the cloud at the service (i.e., business), the platform and/or the infrastructure levels. Face to these various benefits, an enterprise that desires to outsource and/or deploy parts of its business process in the Cloud must resolve two decisional points: which part of its business process to outsource, which Cloud and which level of the Cloud environment are the most beneficial. The resolution of these decisional points must take into account several contextual factors that are specific to each enterprise. This paper presents the elements of enterprise context that influence the decision whether to outsource or not in a Cloud environment. In addition, it shows how AHP can be used to assist manager in taking their decision.
The objective of this work is to design a new method to solve the problem of integrating the Vapnik theory, as regards support vector machines, in the field of clustering data. For this we turned to bio-inspired meta-...
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ISBN:
(纸本)9781467358125
The objective of this work is to design a new method to solve the problem of integrating the Vapnik theory, as regards support vector machines, in the field of clustering data. For this we turned to bio-inspired meta-heuristics. Bio-inspired approaches aim to develop models resolving a class of problems by drawing on patterns of behavior developed in ethology. For instance, the Particle Swarm Optimization (PSO) is one of the latest and widely used methods in this regard. Inspired by this paradigm we propose a new method for clustering. The proposed method PSvmC ensures the best separation of the unlabeled data sets into two groups. It aims specifically to explore the basic principles of SVM and to combine it with the meta-heuristic of particle swarm optimization to resolve the clustering problem. Indeed, it makes a contribution in the field of analysis of multivariate data. Obtained results present groups as homogeneous as possible. Indeed, the intra-class value is more efficient when comparing it to those obtained by Hierarchical clustering, Simple K-means and EM algorithms for different database of benchmark.
The emergence of the TV channels number and the appearance of the Internet led to an exponential growth of the audiovisual documents. Several works were proposed in the literature for automatic video segmentation. How...
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The emergence of the TV channels number and the appearance of the Internet led to an exponential growth of the audiovisual documents. Several works were proposed in the literature for automatic video segmentation. However, the effectiveness of these works depends on video type. So, for a better quality of the segmentation, it is necessary to consider a priori knowledge concerning video types. Besides, TV channels use a set of rules during the production and the streaming of their programs such as the respect of the graphic charter, the recurring of studios... The exploitation of these rules, as a priori knowledge for the temporal and/or semantic structuring of the video documents, would be then advantageous for the quality of the indexing and the performance of the multimediasystems. In this context, we propose a method for the extraction and the formalization of descriptors based on a priori knowledge in order to conceive a video grammar model. This model will be used thereafter for a multitude of interesting applications like automatic structuring of TV streams or TV news segmentation. Video grammar; video grammar modeling; multimedia descriptors; video indexing.
This paper introduces an augmented reality-based framework (called AugmentedBook) for e-learning that allows the creation of collaborative notes, illustrative media (i.e. video, 2D or 3D image, audio) for mobile devic...
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Knowledge management process is a set of procedures and tools applied to facilitate capturing, sharing and effectively using knowledge. However, knowledge collected from organizations is generally expressed in various...
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Time-To-event prediction is an important analytical approach in medical research and personalized medicine that aims to predict the timing of clinically relevant occurrences and find associated risk variables. In the ...
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Boson sampling, thought to be intractable classically, can be solved by a quantum machine composed of merely generation, linear evolution and detection of single photons. Such an analog quantum computer for this speci...
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Boson sampling, thought to be intractable classically, can be solved by a quantum machine composed of merely generation, linear evolution and detection of single photons. Such an analog quantum computer for this specific problem provides a shortcut to boost the absolute computing power of quantum computers to beat classical ones. However, the capacity bound of classical computers for simulating boson sampling has not yet been identified. Here we simulate boson sampling on the Tianhe-2 supercomputer, which occupied the first place in the world ranking six times from 2013 to 2016. We computed the permanent of the largest matrix using up to 312 000 CPU cores of Tianhe-2, and inferred from the current most efficient permanent-computing algorithms that an upper bound on the performance of Tianhe-2 is one 50-photon sample per ~100 min. In addition, we found a precision issue with one of two permanent-computing algorithms.
This presentation considers the impact on logic design and computing of the fundamental unreliability of nanoscale device technologies. In general, these technologies will provide implementations of logic gates and ci...
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Genetic Algorithm (GA) are common probabilistic optimization methods inspired by the process of natural selection. Quantum computers promise substantial speedups over conventional machines, and libraries allow the emu...
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