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Procedia Computer Science 2020年 176卷 763-770页

作者： Randa Ben Ammar Yassine Ben Ayed Multimedia Information System and Advanced Computing Laboratory Sfax University Tunisia

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.

关键词： Alzheimer’s disease Speech analysis Machine learning

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A decision method for business process outsourcing based on enterprise context

A decision method for business process outsourcing based on ...

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IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises

作者： Mouna Rekik Khouloud Boukadi Hanane Ben Abdallah Multimedia InfoRmation systems & Advanced Computing Laboratory (Mir@cl) University of Sfax

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.

关键词： BPO Cloud models Enterprise context Decision method AHP

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Particle swarm optimization for support vector clustering Separating hyper-plane of unlabeled data

Particle swarm optimization for support vector clustering Se...

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International Conference on Modeling, Simulation and Applied Optimization

作者： Souad CHAABOUNI Salma JAMMOUSSI Yassine BENAYED Multimedia InfoRmation systems and Advanced Computing Laboratory MIRACL. SFAX University

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.

关键词： Support Vector Machines Clustering Particle Swarm Optimization

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Towards a modeling of video grammar based on a priori knowledge for the optimization of the audiovisual documents structuring

Towards a modeling of video grammar based on a priori knowle...

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International Conference on Computer Technology and Development (ICCTD)

作者： Tarek Zlitni Walid Mahdi Hanene Ben-Abdallah Multimedia Information Systems and Advanced Computing Laboratory Sfax MIR CI Tunisia

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 multimedia systems. 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.

关键词： Biological system modeling Nonvolatile memory Random access memory multimedia communication Ferroelectric films TV

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AugmentedBook: A collaborative e-learning augmented reality platform 1st

AugmentedBook: A collaborative e-learning augmented reality ...

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1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019

作者： Alzahrani, Nouf M. Lajmi, Sonia Information Technology Department Faculty of Computer Science and Information Technology Albaha University Albaha Saudi Arabia MIRACL: Multimedia InfoRmation Systems and Advanced Computing Laboratory University of Sfax Technological Pole of Sfax Sakiet Ezzit Sfax3021 Tunisia

ISBN: (纸本)9783030256289

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 devices or Google glass. The augmented content can be added to real-world educational support to make it more comprehensive, interactive and collaborative. In this platform, students and teachers can add collaborative notes to any part of the educational support system. They can also find illustrative media and indicate the pertinence of the result. Using our AugmentedBook platform, students can also download the enriched support using a mobile device. Our framework solves the problem of standard integration of augmented reality applications in education, offering a distributed framework which is e-learning compliant. © 2020, Springer Nature Switzerland AG.

关键词： Augmented reality

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Association Rules Transformation for Knowledge Integration and Warehousing 17th

Association Rules Transformation for Knowledge Integration a...

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17th International Conference on Intelligent systems Design and Applications, ISDA 2017

作者： Ayadi, Rim Hachaichi, Yasser Feki, Jamel Multimedia Information Systems and Advanced Computing Laboratory University of Sfax Sfax Tunisia Department of Computer Science and Quantitative Methods Higher Institute of Business Administration of Sfax Sfax Tunisia Faculty of Computing and IT University of Jeddah Jeddah Saudi Arabia

ISBN: (纸本)9783319763477

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 formalisms, therefore it is heterogeneous. Thus, a Knowledge Warehouse (KW), which is a solution for implementing all phases of the knowledge management process, should solve this structural heterogeneity before loading and storing knowledge. In this paper, we are interested in knowledge normalization. More accurately, we firstly introduce our proposed architecture for a KW, and then we present the MOT (Modeling with Object Types) language for knowledge representation. Since our objective is to transform heterogeneous knowledge into MOT, as a pivot model, we suggest a meta-model for the MOT and another for the explicit knowledge extracted through the association rules technique. Thereafter, we define eight transformation rules and an algorithm to transform an association rules model into the MOT model. © 2018, Springer International Publishing AG, part of Springer Nature.

关键词： Data mining

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New Dynamic Bayesian Network for Time-To-Event Prediction 21

New Dynamic Bayesian Network for Time-To-Event Prediction

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2024 IEEE/ACS 21st International Conference on Computer systems and Applications, AICCSA 2024

作者： Ben Abdallah, Walid Njah, Hasna Jamoussi, Salma National Engineering School of Gabes Gabes University Tunisia Sfax University Multimedia InfoRmation Systems and Advanced Computing Laboratory Tunisia Higher Institute of Computer Sciences and Multimedia of Gabes Gabes University Tunisia Higher Institute of Computer Sciences and Multimedia of Sfax Sfax University Tunisia

ISBN: (纸本)9798331518240

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 context of chronic diseases such as multiple sclerosis (MS), precisely modelling time to disease progression, adverse events, or therapeutic responses can have a significant impact on patient management strategies and clinical results. This study investigate the use of Bayesian networks(BN), augmented with a temporal factor, for time-To-event prediction in predicting disease progression in MS patients. We suggest using dynamic Bayesian networks (DBNs) as a versatile temporal modeling framework to capture the complex dynamics and inter-dependencies found in time-To-event processes. © 2024 IEEE.

关键词： Prediction models

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A benchmark test of boson sampling on Tianhe-2 supercomputer

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National Science Review 2018年第5期5卷 715-720页

作者： Junjie Wu Yong Liu Baida Zhang Xianmin Jin Yang Wang Huiquan Wang Xuejun Yang Institute for Quantum Information & State Key Laboratory of High Performance Computing College of ComputerNational University of Defense Technology State Key Laboratory of Advanced Optical Communication Systems and Networks School of Physics and AstronomyShanghai Jiao Tong University Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China

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.

关键词： boson sampling permanent quantum supremacy quantum computing supercomputer

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Nanocomputing with probabilistic logic

Nanocomputing with probabilistic logic

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2006 6th IEEE Conference on Nanotechnology, IEEE-NANO 2006

作者： Fortes, José A. B. Advanced Computing and Information Systems Laboratory Department of Electrical and Computer Engineering University of Florida Gainesville FL United States

ISBN: (纸本)1424400783

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 circuits where logic levels are "0" or "1" with some probability related to the error rates of gates and interconnect. In this context, reliable circuit design becomes a problem of maximizing the probability of the correct logic levels of the output of the function implemented by the circuit for the relevant inputs. This presentation reviews some recent results and proposes new ideas for the characterization and design of probabilistic logic. Since the early days of computing it has been well known that the design of reliable arbitrary logic circuits is only possible if individual gates have error rates below some threshold which varies with gate functionality. Using bifurcation analysis of probabilistic gate models, thresholds for different types of gates are derived and their implications for logic design are revisited. Similar techniques are used to analyze multi-gate circuits and the functions they implement. The resulting thresholds provide reliability bounds for the circuits. Also considered are several proposed models for either analyzing reliability or maximizing it. Reference is also made to circuits designed to implement probabilistic computations. © 2006 IEEE.

关键词： Nanoelectronics

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Circuit level implementation of the Reduced Quantum Genetic Algorithm using Qiskit 16

Circuit level implementation of the Reduced Quantum Genetic ...

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16th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2022

作者： Ardelean, Sebastian Mihai Udrescu, Mihai Politehnica University of Timisoara Advanced Computing Systems and Architectures Laboratory Department of Computer and Information Technology Timisoara300223 Romania

ISBN: (数字)9781665481250

ISBN: (纸本)9781665481250

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 emulation of circuits on a quantum computer in different highly configurable noise models and even run on quantum computers. Therefore, we need to analyze this class of heuristic methods in the quantum context. We propose a circuit level implementation of the Reduced Quantum Genetic Algorithm (RQGA) using Python and Qiskit. Our main goal is to analyze the circuit complexity from the perspectives of the number of qubits required and the number of quantum gates used. To achieve our goal, we instantiate the framework for solving the knapsack problem, examine the results in a simulated environment, and analyze the circuit's complexity. © 2022 IEEE.

关键词： Heuristic methods

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