检索结果-内蒙古大学图书馆

International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2014

作者： Zarrouk, Elyes Benayed, Yassine Gargouri, Faïez MIRACL Multimedia InfoRmation system and Advanced Computing Laboratory Higher Institute of Computer Science and Multimedia ISIMS University of Sfax Tunisia

Hidden Markov Models (HMM) are currently widely used in Automatic Speech Recognition (ASR) as being the most effective models. In addition, the HMM are just a special case of graphical models which are dynamic Bayesian Networks (DBN). These are modeling tools more sophisticated because they allow to include several specific variables in the problem of automatic speech recognition other than the one used in HMM. The use of DBNs in speech recognition beyond has generated much interest in recent years. This paper deals a comparative study between DBN and HMM systems for multi-dialect isolated Arabic words. Performance using DBNs is found to exceed that of HMMs trained on an identical task, giving higher recognition accuracy for four different Arabic dialects. In fact, the average of recognition rates for the four dialects with DBN was 83.01% while 74.17% with HMM standards. © (2014) by Society of Digital information and Wireless Communication (SDIWC). All rights reserved.

关键词： Hidden Markov models

来源：评论

学校读者我要写书评

暂无评论

Particle swarm optimization based method for Bayesian Network structure learning

Particle swarm optimization based method for Bayesian Networ...

引用

2013 5th International Conference on Modeling, Simulation and Applied Optimization, ICMSAO 2013

作者： Aouay, Saoussen Jamoussi, Salma Ayed, Yassine Ben MIRACL Multimedia InfoRmation System and Advanced Computing Laboratory Higher Institute of Computer Science and Multimedia Sfax BP 1030 Tunisia

ISBN: (纸本)9781467358149

Bayesian Networks (BNs) are good tools for representing knowledge and reasoning under conditions of uncertainty. In general, learning Bayesian Network structure from a data-set is considered a NP-hard problem, due to the search space complexity. A novel structure-learning method, based on PSO (Particle Swarm Optimization) and the K2 algorithm, is presented in this paper. To learn the structure of a bayesian network, PSO here is used for searching in the space of orderings. Then the fitness of each ordering is calculated by running the K2 algorithm and returning the score of the network consistent with it. The experimental results demonstrate that our approach produces better performance compared to others BN structure learning algorithms. © 2013 IEEE.

关键词： Bayesian networks

来源：评论

学校读者我要写书评

暂无评论

Computational Complexity Analysis of Ant Colony Clustering Algorithms: Application to Student's Grouping Problem

Computational Complexity Analysis of Ant Colony Clustering A...

引用

2022 IEEE International Conference on systems, Man, and Cybernetics, SMC 2022

作者： Chniter, Malak Abid, Abir Kallel, Ilhem Kanoun, Slim Mir@cl Lab: Multimedia InfoRmation Systems and Advanced Computing Laboratory University of Sfax ReGIM-Lab: Research Groups in Intelligent Machines Tunisia

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

The task of assessing, grouping and arranging data into meaningful groups or clusters based on their similarities/dissimilarities measures known as cluster analysis. Thereby, there are numerous clustering algorithms: hierarchical and partitional. In the last decade, clustering using bio-inspired algorithms received more attention, specifically the ant clustering algorithms. Regardless, they have required a lot of processing power due to the massive amount of data that has been generated during the last years. As a consequence, determining the computational cost of these algorithms is one of the most interesting tasks in the quest for optimal clustering solutions in a real-time system. This study presents a research guide for the researchers working in the same field. A series of experiments are elaborated to investigate the computational complexity of the most promising algorithms applied to students grouping problem. The results indicate two challenges that arise when using ant clustering algorithms: the difficulty in adjusting parameters and extended computation time. © 2022 IEEE.

关键词： Computational complexity

来源：评论

学校读者我要写书评

暂无评论

Building an Arabic linguistic resource from a treebank: The case of property grammar

Building an Arabic linguistic resource from a treebank: The ...

引用

17th International Conference on Text, Speech, and Dialogue, TSD 2014

作者： Bahloul, Raja Bensalem Elkarwi, Marwa Haddar, Kais Blache, Philippe Multimedia Information Systems and Advanced Computing Laboratory Higher Institute of Computer Science and Multimedia Sfax Tunisia Laboratoire Parole et Langage CNRS Université de Provence France

ISBN: (纸本)9783319108155

This paper presents a survey of Arabic treebanks to facilitate their reuse for the building of new linguistic resources. In our case, we created from a treebank an automatically induced Property Grammar (GP). So, we discussed characteristics of these treebanks to choose the appropriate one. To build our resource, we adopted an automatic technique, acquiring first a context-free grammar (CFG) from the chosen treebank, and second, inducing a GP by generating relations between grammatical units described in the CFG. © 2014 Springer International Publishing.

关键词： Context free grammars

来源：评论

学校读者我要写书评

暂无评论

Svm for human identification using the ECG signal

引用

Procedia Computer Science 2020年 176卷 430-439页

作者： Sihem Hamza Yassine Ben Ayed Multimedia InfoRmation systems and Advanced Computing Laboratory MIRACL University of Sfax Tunisia

In this paper, a person identification system has been simulated using electrocardiogram (ECG) signals as biometrics. In this work, we propose a two-phase method to conduct human identification using the ECG signal, which are the feature extraction and the classification. In the first phase, it makes a fusion of three new types of characteristics: cepstral coefficients, ZCR, and entropy. In the second phase, the support vector machines (SVM) has been applied for the classification system. The proposed methods are evaluated using two public databases namely MIT-BIH arrhythmia and ECG-ID database obtained from the Physionet database. Experimental results show that our features can achieve high subject identification accuracy of 100% on ECG signals that are from the MIT-BIH database, ECG-ID (Five recording), and ECG-ID (Two recording), indicating that our features makes it possible to improve the efficiency of our identification system.

关键词： Biometric identification ECG signal Cepstral coefficients ZCR Entropy SVM

来源：评论

学校读者我要写书评

暂无评论

Dynamic construction of dictionaries for sentiment classification

Dynamic construction of dictionaries for sentiment classific...

引用

International Conference on Cloud and Green computing (CGC)

作者： Salma Jamoussi Hanen Ameur Multimedia InfoRmation systems and Advanced Computing Laboratory

The sentiment classification is one of the new challenges emerged with the advence of social networks. Our purpose is to determine the sentimental orientation of a Facebook comment (positive or negative) by using the linguistic approach. In most of the sentiment analysis applications using this approach, the sentiment lexicon plays a key role. Thus, it is very important to create a lexicon covering several sentiment words. For this reason, we address in this paper the problem how to group and list words present in the corpus into two dictionaries. We proposed a new automatic technique to create the positive and negative dictionaries that exploits the emotions symbols (emoticons, acronyms and exclamation words) present in comments. More importantly, our idea allows to enlarge these dictionaries with an enrichment step. Finally, by using these prepared dictionaries, we predict the positive and negative polarities of the comment. We evaluate our approach by comparison to human classification. Our results are also effective and consistent.

关键词： Dictionaries Semantics Facebook Pragmatics Accuracy

来源：评论

学校读者我要写书评

暂无评论

I/O processing in a virtualized platform: A simulation-driven approach 07

I/O processing in a virtualized platform: A simulation-drive...

引用

VEE'07: 3rd International Conference on Virtual Execution Environments

作者： Chadha, Vineet Illiikkal, Ramesh Iyer, Ravi Moses, Jaideep Newell, Donald Figueiredo, Renato J. Advanced Computing and Information Systems Laboratory University of Florida Intel Corporation Hillsboro OR

ISBN: (纸本)1595936300

Virtualization provides levels of execution isolation and service partition that are desirable in many usage scenarios, but its associated overheads are a major impediment for wide deployment of virtualized environments. While the virtualization cost depends heavily on workloads, it has been demonstrated that the overhead is much higher with I/O intensive workloads compared to those which are compute-intensive. Unfortunately, the architectural reasons behind the I/O performance overheads are not well understood. Early research in characterizing these penalties has shown that cache misses and TLB related overheads contribute to most of I/O virtualization cost. While most of these evaluations are done using measurements, in this paper we present an execution-driven simulation based analysis methodology with symbol annotation as a means of evaluating the performance of virtualized workloads. This methodology provides detailed information at the architectural level (with a focus on cache and TLB) and allows designers to evaluate potential hardware enhancements to reduce virtualization overhead. We apply this methodology to study the network I/O performance of Xen (as a case study) in a full system simulation environment, using detailed cache and TLB models to profile and characterize software and hardware hotspots. By applying symbol annotation to the instruction flow reported by the execution driven simulator we derive function level call flow information. We follow the anatomy of I/O processing in a virtualized platform for network transmit and receive scenarios and demonstrate the impact of cache scaling and TLB size scaling on performance. Copyright © 2007 ACM.

关键词： Virtual reality

来源：评论

学校读者我要写书评

暂无评论

Federated Graph Learning via Constructing and Sharing Feature Spaces for Cross-Domain IoT

引用

IEEE Internet of Things Journal 2025年

作者： Chen, Jiale Zhuo, Shengda He, Jinchun Qiu, Wangjie Zhang, Qinnan Xiong, Zehui Zheng, Zhiming Tang, Yin Chen, Min Wang, Changdong Huang, Shuqiang Jinan University College of Cyber Security Guangzhou China Beihang University Institute of Artificial Intelligence Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beijing100191 China Zhongguancun Laboratory Beijing China Singapore University of Technology and Design Information Systems Technology and Design 487372 Singapore Jinan University School of Management Guangzhou China South China University of Technology School of Computer Science and Engineering Guangzhou China Sun Yat-sen University School of Computer Guangzhou China Jinan University College of Cyber Security of Jinan University China Guangdong Key Laboratory of Data Security and Privacy Preserving Guangzhou China

The Internet of Things (IoT) collects large volumes of diverse data, with graph data as a critical component, and extensively utilizes Federated Graph Learning (FGL) to process this data while preserving data security. However, the graph data collected by different IoT institutions are relatively independent due to various factors (e.g., data collection methods, geographical locations), and data access is restricted to local environments due to privacy constraints, IoT institutions typically possess heterogeneous feature spaces. Aggregating under these conditions could potentially contaminate local graph representations. Unfortunately, most existing FGL methods tend to overlook this issue. To address this challenge, we propose Federated Graph Learning via Constructing and Sharing Features (FedCSF), a novel FGL framework designed to build a globally consistent feature space and share it among IoT institutions. To construct and extract the feature space, we employ an uniform feature initialization across IoT institutions and design an encoder to extract both global and local feature relationships, thereby facilitating effective collaboration across data from different IoT institutions. Furthermore, we introduce an independent adaptive aggregation strategy to eliminate the integration of harmful knowledge, ensuring that the contributions from each IoT institution are effectively integrated into the global model. We theoretically analyze the convergence of FedCSF. To validate the effectiveness of FedCSF, we conducted extensive experiments under various settings (i.e., cross-datasets, and cross-domains), demonstrating its significant advantages of FedCSF in terms of performance, convergence speed, and practical adaptability © 2014 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Transducers cascades for an automatic recognition of Arabic named entities in order to establish links to free resources 1

Transducers cascades for an automatic recognition of Arabic ...

引用

1st International Conference on Arabic Computational Linguistics, ACLing 2015

作者： Mesmia, Fatma Ben Friburger, Nathalie Haddar, Kais Maurel, Denis University of Sfax Laboratory MIRACL Multimedia InfoRmation Systems and Advanced Computing Laboratory Sfax Tunisia University of François Rabelais of Tours LI Computer Laboratory Tours France

ISBN: (纸本)9781467391559

Arabic named entities (ANE) are often sources of information. That is why they are used by several applications of natural language processing (NLP) mainly in information retrieval. In order to improve the relevance of the information obtained, links to free resources can be established. Indeed, the recognition of these entities requires the use of adequate formalisms. In this paper, we propose an approach based on transducer cascades which allows the recognition of ANE more precisely the dates. This categorycan be an integral part in the events and the names of places. The implementation of the developed transducers cascades elaborated by using the CasSys tool is available under the Unitex platform. The results are motivating. © 2015 IEEE.

关键词： Transducers

来源：评论

学校读者我要写书评

暂无评论

Speech Emotion Recognition with deep learning

引用

Procedia Computer Science 2020年 176卷 251-260页

作者： Hadhami Aouani Yassine Ben Ayed Multimedia InfoRmation systems and Advanced Computing Laboratory MIRACL University of Sfax Tunisia

This paper proposes an emotion recognition system based on speech signals in two-stage approach, namely feature extraction and classification engine. Firstly, two sets of feature are investigated which are: the first one, we extract an 42-dimensional vector of audio features including 39 coefficients of Mel Frequency Cepstral Coefficients (MFCC), Zero Crossing Rate(ZCR), Harmonic to Noise Rate (HNR) and Teager Energy Operator (TEO). And the second one, we propose the use of the method Auto-Encoder for the selection of pertinent parameters from the parameters previously extracted. Secondly, we use the Support Vector Machines (SVM) as a classifier method. Experiments are conducted on the Ryerson multimedia laboratory (RML).

关键词： Emotion recognition MFCC ZCR TEO HNR SVM auto-encoder

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：