检索结果-内蒙古大学图书馆

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

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

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

A new video images text localization approach based on a fast hough transform

引用

3rd International Conference on Image Analysis and Recognition, ICIAR 2006

作者： Bouaziz, Bassem Mahdi, Walid Hamadou, Abdelmajid Ben MIRACL Multimedia InfoRmation System and Advanced Computing Laboratory Higher Institute of Computer Science and Multimedia BP 1030 Sfax 69042 Tunisia

ISBN: (纸本)3540448918

The amount of digital video data is increasing over the world. It highlights the need for efficient algorithms that can retrieve this data by content. The full use of this media is currently limited by the opaque nature of the video which prevents content-based access. To facilitate video indexing and browsing, it is essential to allow non-linear access, especially for long programs. This can be achieved by identifying semantic description captured automatically from video story structure. Among these descriptions, text within video frames is considered as rich features that enable a good way for browsing video. In this paper we propose a fast Hough transformation based approach for automatic video frames text localization. Experimental results, that we drove on a large sample of video images issued from portions of news broadcasts, sports program, advertisements and movies, shows that our method is very efficient, capable to locate text regions with different character sizes, directions and styles even in case of complex image background. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Image analysis

来源：评论

学校读者我要写书评

暂无评论

A property grammar-based method to enrich the arabic treebank ATB 7

引用

7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015

作者： Bahloul, Raja Bensalem 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 Marseille France

ISBN: (纸本)9783319527574

We present a method based on the formalism of Property Grammars to enrich the Arabic treebank ATB with syntactic constraints (so-called properties). The Property Grammar formalism is an effectively constraint-based approach that directly specifies the constraints on information categories. This can facilitate the enrichment process. The latter is based on three phases: the problem formalization, the Property Grammar induction from the ATB and the treebank regeneration with a new syntactic property-based representation. The enrichment of the ATB can make it more useful for many NLP applications such as the ambiguity resolution. This allows also the acquisition of new linguistic resources and the ease of the probabilistic parsing process. This enrichment process is purely automatic and independent from any language and source corpus formalism. This motivates its reuse. We obtained good and encouraging experiment results and various properties of different types. © Springer International Publishing AG 2016.

关键词： Syntactics

来源：评论

学校读者我要写书评

暂无评论

Deep support vector machines for speech emotion recognition 19th

Deep support vector machines for speech emotion recognition

引用

19th International Conference on Intelligent systems Design and Applications, ISDA 2019

作者： Aouani, Hadhami Ben Ayed, Yassine National School of Engineers ENIS University of Sfax Sfax Tunisia Multimedia InfoRmation Systems and Advanced Computing Laboratory MIRACL University of Sfax Sfax Tunisia

ISBN: (纸本)9783030493417

Speech Emotions recognition has become the active research theme in speech processing and in applications based on human-machine interaction. In this work, our system is a two-stage approach, namely feature extraction and classification engine. Firstly, two sets of feature are investigated which are: the first one is extracting only 13 Mel-frequency Cepstral Coefficient (MFCC) from emotional speech samples and the second one is applying features fusions between the three features: zero crossing rate (ZCR), Teager Energy Operator (TEO), and Harmonic to Noise Rate (HNR) and MFCC features. Secondly, we use two types of classification techniques which are: the Support Vector Machines (SVM) and the k-Nearest Neighbor (k-NN) to show the performance between them. Besides that, we investigate the importance of the recent advances in machine learning including the deep kernel learning. A large set of experiments are conducted on Surrey Audio-Visual Expressed Emotion (SAVEE) dataset for seven emotions. The results of our experiments showed given good accuracy compared with the previous studies. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Rocchio's model based on vector space basis change for pseudo relevance feedback

Rocchio's model based on vector space basis change for pseud...

引用

3rd Symposium on Languages, Applications and Technologies, SLATE 2014

作者： Mbarek, Rabeb Tmar, Mohamed Hattab, Hawete Sfax University Multimedia Information Systems and Advanced Computing Laboratory Sfax Tunisia Umm Al-qura University Department of Mathematics Makkah Saudi Arabia

ISBN: (纸本)9783939897682

Rocchio's relevance feedback model is a classic query expansion method and it has been shown to be effective in boosting information retrieval performance. The main problem with this method is that the relevant and the irrelevant documents overlap in the vector space because they often share same terms (at least the terms of the query). With respect to the initial vector space basis (index terms), it is difficult to select terms that separate relevant and irrelevant documents. The Vector Space Basis Change is used to separate relevant and irrelevant documents without any modification on the query term weights. In this paper, first, we study how to incorporate Vector Space Basis Change into the Rocchio's model. Second, we propose Rocchio's models based on Vector Space Basis Change, called VSBCRoc models. Experimental results on a TREC collection show that our proposed models are effective. © Rabeb Mbarek, Mohamed Tmar, and Hawete Hattab.

关键词： Vector spaces

来源：评论

学校读者我要写书评

暂无评论

A recursive methodology for radical communities' detection on social networks 24

A recursive methodology for radical communities' detection o...

引用

24th KES International Conference on Knowledge-Based and Intelligent information and Engineering systems, KES 2020

作者： Rekik, Amal Jamoussi, Salma Hamadou, Abdelmajid Ben Multimedia InfoRmation systems and Advanced Computing Laboratory MIRACL University of Sfax 3021 Tunisia Digital Research Center of Sfax DRCS Sfax3021 Tunisia

In the recent years, radical communities have become very aware of the enormous impact of social networks around the world. Thus, these latter are being frequently explored by these groups. Therefore, penetrating into these communities by analyzing both their interactions and their shared content is a considerably challenging task that serves to counter the online radicalization. For this purpose, in this paper, we propose a new recursive methodology for radical communities' detection on social networks based on the analysis and extraction of their violent used vocabulary. Our methodology consists mainly on extracting recursively a set of dangerous profiles from Twitter based on their suspicious interactions. Then, we analyze their textual shared data in order to construct a rich glossary containing their violent used vocabulary. This glossary is exploited and enriched to detect recursively radical communities. Finally, in order to evaluate the performance of our methodology, we resort to an expert who verifies both the list of the dangerous extracted profiles and the violent constructed glossary. The given results show the effectiveness and efficiency of our method. © 2020 The Authors. Published by Elsevier B.V.

关键词： Glossaries

来源：评论

学校读者我要写书评

暂无评论

Semantic multimedia search: the case of SMIL documents

Semantic multimedia search: the case of SMIL documents

引用

4th International Conference on Web and information Technologies, ICWIT 2012

作者： Chkiwa, Mounira Jedidi, Anis Université de Sfax MIRACL Multimedia Information Systems and Advanced Computing Laboratory B.P. 242 Sakiet Ezziet 3021 Sfax Tunisia

Since the first implementations of its principles, the Semantic Web presented a field of free work to ensure its integration and adaptation to the various domains of research. The application of Semantic Web technologies into the process of search in a collection of SMIL documents appears a promising initiative seen the evolution of this language through its various versions. In this paper we propose a semantic search tool in a collection of SMIL documents;this tool adopts a procedure composed of three modules: description, interrogation and representation of the results. We employ for the first module metadata commonly used to annotate information semantically, and for the second we solicit languages of Semantic Web such as RDF, OWL and SPARQL and seen the importance of collaboration of ontologies in the semantic description of multimedia resources, we also present the technique of concepts connection allowing to extend an initial ontology.

关键词： Metadata

来源：评论

学校读者我要写书评

暂无评论

Parameter-efficient fine-tuning of Whisper for low-resource speech recognition 5

Parameter-efficient fine-tuning of Whisper for low-resource ...

引用

5th International Seminar on Artificial Intelligence, Networking and information Technology, AINIT 2024

作者： Liu, Yunpeng Qu, Dan School of Information Systems Engineering University of Information Engineering Laboratory For Advanced Computing and Intelligence Engineering Department of Artificial Intelligence Henan China Systems Engineering University of Information Engineering Laboratory For Advanced Computing and Intelligence Engineering Henan China

ISBN: (纸本)9798350385557

Limited data availability remains a significant challenge for Whisper's low-resource speech recognition performance, falling short of practical application requirements. While previous studies have successfully reduced the recognition error rates of target language speech through fine-tuning, a comprehensive exploration and analysis of Whisper's parameter-efficient fine-tuning capabilities, the advantages and disadvantages are still lacking. This paper aims to fill this gap by conducting comprehensive experimental exploration for Whisper's low-resource speech recognition performance using two parameter-efficient fine-tuning strategies with limited supervised data from multiple low-resource languages. The results and analysis demonstrate that all fine-tuning strategies explored in this paper significantly enhance Whisper's performance. However, different strategies vary in their suitability and practical effectiveness, highlighting the need for careful selection based on specific use cases and resources available. © 2024 IEEE.

关键词： Speech recognition

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：