检索结果-内蒙古大学图书馆

arXiv 2020年

作者： Csapó, Tamás Gábor Xu, Kele Department of Telecommunications and Media Informatics Budapest University of Technology and Economics Budapest Hungary MTA-ELTE Lendület Lingual Articulation Research Group Budapest Hungary National Key Lab of Parallel and Distributed Processing National University of Defense Technology Changsha China School of Computer National University of Defense Technology Changsha China

In speech production research, different imaging modalities have been employed to obtain accurate information about the movement and shaping of the vocal tract. Ultrasound is an affordable and non-invasive imaging modality with relatively high temporal and spatial resolution to study the dynamic behavior of tongue during speech production. However, a longstanding problem for ultrasound tongue imaging is the transducer misalignment during longer data recording sessions. In this paper, we propose a simple, yet effective, misalignment quantification approach. The analysis employs MSE distance and two similarity measurement metrics to identify the relative displacement between the chin and the transducer. We visualize these measures as a function of the timestamp of the utterances. Extensive experiments are conducted on a Hungarian and Scottish English child dataset. The results suggest that large values of Mean Square Error (MSE) and small values of Structural Similarity Index (SSIM) and Complex Wavelet SSIM indicate corruptions or issues during the data recordings, which can either be caused by transducer misalignment or lack of gel. Copyright © 2020, The Authors. All rights reserved.

关键词： Ultrasonics

来源：评论

学校读者我要写书评

暂无评论

Underwater acoustic classification using masked modeling-based swin transformer

引用

The Journal of the Acoustical Society of America 2022年第4_SUPPLEMENT期152卷 A296-A296页

作者： Kang you Kele Xu Ming Feng Boqing Zhu Tonguing Univ. Shanghai China National Key Lab. of Parallel and Distributed Processing (PDL) Changsha China 107 Yanwachi Changsha 410073 China kelele.xu@*** National Key Lab. of Parallel and Distributed Processing (PDL) Changsha China Changsha China

Underwater acoustic classification is a challenging task due to complex background noise and complicated sound propagation patterns. How to represent the signals is important for the classification task. In this paper, we propose a novel representation learning method for the underwater acoustic signals, leveraging the mask modeling-based self-supervised learning paradigm. Specifically, we first explore modifying the Swin Transformer architecture to learn general representation for the audio signals, accompanied with random masking on the log-mel spectrogram. The main goal of the pretext task is to predict the masked parts of Log-mel spectrogram and the gamma-stone spectrogram, so that the model can not only learn the local and global features but also learn complementary information. For downstream task, we utilize the labelled datasets to fine-tune the pre-trained model. On DeepShip datasets which consist of 47 hand 4 minof ship sounds in four categories, our model achieves state-of-the-art performance compared with competitive approaches. Our method obtains a classification accuracy of 78.03%, which is better than the separable convolution autoencoder (SCAE) and using the constant-Q transform spectrogram. This work demonstrates the potential of the masked modeling based self-supervised learning for understanding and interpretation of underwater acoustic signals.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Convolutional neural network-based age estimation using B-mode ultrasound tongue image

arXiv

引用

arXiv 2021年

作者： Xu, Kele Csapó, Tamás Gábor Feng, Ming National Key Lab of Parallel and Distributed Processing National University of Defense Technology Changsha China School of Computer National University of Defense Technology Changsha China Department of Telecommunications and Media Informatics Budapest University of Technology and Economics Budapest Hungary MTA-ELTE Lendület Lingual Articulation Research Group Budapest Hungary Tongji University Shanghai China

Ultrasound tongue imaging is widely used for speech production research, and it has attracted increasing attention as its potential applications seem to be evident in many different fields, such as the visual biofeedback tool for second language acquisition and silent speech interface. Unlike previous studies, here we explore the feasibility of age estimation using the ultrasound tongue image of the speakers. Motivated by the success of deep learning, this paper leverages deep learning on this task. We train a deep convolutional neural network model on the UltraSuite dataset. The deep model achieves mean absolute error (MAE) of 2.03 for the data from typically developing children, while MAE is 4.87 for the data from the children with speech sound disorders, which suggest that age estimation using ultrasound is more challenging for the children with speech sound disorder. The developed method can be used a tool to evaluate the performance of speech therapy sessions. It is also worthwhile to notice that, although we leverage the ultrasound tongue imaging for our study, the proposed methods may also be extended to other imaging modalities (e.g. MRI) to assist the studies on speech production. © 2021, CC BY-NC-SA.

关键词： Ultrasonics

来源：评论

学校读者我要写书评

暂无评论

Feature and Performance Comparison of FaaS Platforms

Feature and Performance Comparison of FaaS Platforms

引用

IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Penghui Ma Peichang Shi Guodong Yi National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems College of Computer Science National University of Defense Technology Changsha China Xiangjiang Lab Changsha China School of Advanced Interdisciplinary Studies Hunan University Of Technology and Business Changsha China

With serverless computing offering more efficient and cost-effective application deployment, the diversity of serverless platforms presents challenges to users, including platform lock-in and costly migration. Moreover, due to the black box nature of function computing, traditional performance benchmarking methods are not applicable, necessitating new studies. This article presents a detailed comparison of six major public cloud function computing platforms and introduces a benchmarking framework for function computing performance. This framework aims to help users make comprehensive comparisons and select the most suitable platform for their specific needs.

关键词：

来源：评论

学校读者我要写书评

暂无评论

MMDSSE: Multi-client and Multi-keyword Dynamic Searchable Symmetric Encryption for Cloud Storage

MMDSSE: Multi-client and Multi-keyword Dynamic Searchable Sy...

引用

Annual Conference on Privacy, Security and Trust, PST

作者： Panyu Wu Zhenfu Cao Jiachen Shen Xiaolei Dong Yihao Yang Jun Zhou Liming Fang Zhe Liu Chunpeng Ge Chunhua Su Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Research Center for Basic Theories of Intelligent Computing Research Institute of Basic Theories Zhejiang Lab Hangzhou China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Science and Technology on Parallel and Distributed Processing Laboratory (PDL) Changsha China Shandong University Jinan China University of Aizu Fukushima Japan

Since data outsourcing poses privacy concerns with data leakage, searchable symmetric encryption (SSE) has emerged as a powerful solution that enables clients to perform query operations on encrypted data while preserving their privacy. Dynamic SSE schemes have been proposed to handle update operations. However, it is shown that updates might increase the risk of information leakage. Meanwhile, to meet the requirement of real-world applications, it is desirable to have the searchable encryption scheme which supports both multiple clients and multi-keyword queries. To address these issues, this paper proposes MMDSSE, a multi-client forward secure dynamic SSE scheme that supports multi-keyword queries. MMDSSE allows the clients narrow down the results by providing an arbitrary subset of the entire archive, and thus suitable for cloud storage environment. Security analysis and experimental evaluations show that MMDSSE is secure and efficient.

关键词：

来源：评论

学校读者我要写书评

暂无评论

MDPPC: Efficient Scalable Multiparty Delegated PSI and PSI Cardinality

MDPPC: Efficient Scalable Multiparty Delegated PSI and PSI C...

引用

Annual Conference on Privacy, Security and Trust, PST

作者： Yihao Yang Xiaolei Dong Jiachen Shen Zhenfu Cao Yunbo Yang Jun Zhou Liming Fang Zhe Liu Chunpeng Ge Chunhua Su Zongyang Hou Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Research Center for Basic Theories of Intelligent Computing Research Institute of Basic Theories Zhejiang Lab Hangzhou China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Science and Technology on Parallel and Distributed Processing Laboratory (PDL) Changsha China Shandong University Jinan China University of Aizu Fukushima Japan Print-Rite Technology Development Co. Ltd. Of Zhuhai China

Private Set Intersection (PSI) is one of the most important functions in secure multiparty computation (MPC). PSI protocols have been a practical cryptographic primitive and there are many privacy-preserving applications based on PSI protocols such as computing conversion of advertising and distributed computation. Private Set Intersection Cardinality (PSI-CA) is a useful variant of PSI protocol. PSI and PSI-CA allow several parties, each holding a private set, to jointly compute the intersection and cardinality, respectively without leaking any additional information. Nowadays, most PSI protocols mainly focus on two-party settings, while in multiparty settings, parties are able to share more valuable information and thus more desirable. On the other hand, with the advent of cloud computing, delegating computation to an untrusted server becomes an interesting problem. However, most existing delegated PSI protocols are unable to efficiently scale to multiple clients. In order to solve these problems, this paper proposes MDPPC, an efficient PSI protocol which supports scalable multiparty delegated PSI and PSI-CA operations. Security analysis shows that MDPPC is secure against semi-honest adversaries and it allows any number of colluding clients. For 15 parties with set size of 2 20 on server side and 2 16 on clients side, MDPPC costs only 81 seconds in PSI and 80 seconds in PSI-CA, respectively. The experimental results show that MDPPC has high scalability.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Deep learning-based age estimation using B-mode ultrasound tongue imaging

引用

The Journal of the Acoustical Society of America 2021年第4_SUPPLEMENT期150卷 A190-A190页

作者： Kele Xu Tamás G. Csapó Ming Feng National Key Lab. of Parallel and Distributed Processing (PDL) 107 Yanwachi Changsha 410073 China kelele.xu@*** Budapest Univ. of Technol. and Economics Budapest Hungary Tongji Univ. Shanghai China

The feasibility of age estimation is explored using the ultrasound tongue image of the speakers. Motivated by the success of deep learning, a deep convolutional neural network model is trained on the UltraSuite dataset. The deep model achieves mean absolute error (MAE) of 2.03 years for the data from typically developing children, while MAE is 4.87 for the data from the children with speech sound disorders, which suggest that age estimation using ultrasound is more challenging for the children with speech sound disorder. Also, we explore to visualize what does the deep model learn for the age estimation task. We firstly visualize the convolutional layers in the learned convolutional neural networks. We observe that the deep model not only focuses on the contour in the ultrasound tongue image, but also pays more attention to the regions corresponding to the tendon and tongue root regions, which may provide guidance for future ultrasound tongue imaging interpretation tasks. The developed method can be used a tool to evaluate the performance of speech therapy sessions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Strategy of transcription analysis for alternative splicing research

引用

Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology 2006年第4期28卷 37-42页

作者： Wang, Zheng-Zhi Li, Zhi-Feng Hang, Xing-Yi Mao, Yi-Qing Luo, Zhi-Gang Zhao, Dong-Sheng Zhang, Cheng-Gang College of Mechatronics Engineering and Automation National Univ. of Defense Technology Changsha 410073 China Institute of Radiation Medicine Academy of Military Medical Sciences Beijing 100850 China Institute of Health Administration and Medical Information Academy of Military Medical Sciences Beijing 100850 China National Lab of Parallel and Distributed Processing National Univ. of Defense Technology Changsha 410073 China

Experiments on transcription analysis have resulted huge genes expression data related with specific temporal and spatial information. These data can be used in new genes identification, analysis of genes express patterns and the annotation of genomes, which may provide the reference standard for experiment design and result analysis of transcription experiments. Since the alternative splicing of eukaryotic genes have found to be universal and play an important role in physiology and pathology, systematic analysis of alternative splicing is becoming a new hotspot of functional genome research. Facing the immense and exponential increase of experimental express data and more new genomes getting sequenced, there is exigent of the strategy which can handle transcription sequences in large scale and automatic way. We elucidate the algorithms, the computing requirements and programs in different transcription sequences analysis systems and propose a strategy more suitable for large scale analysis of alternative splicing.

关键词： Alternative splicing EST assembly EST clustering High performance computing Transcripton

来源：评论

学校读者我要写书评

暂无评论

NTIRE 2021 multi-modal aerial view object classification challenge

arXiv

引用

arXiv 2021年

作者： Nina, Oliver Liu, Jerrick Menart, Chris Lee, Bob Timofte, Radu Inkawhich, Nathan Duan, Yuru Wei, Wei Zhang, Lei Xu, Songzheng Sun, Yuxuan Tang, Jiaqi Li, Gongzhe Tan, Zhiwen Pan, Lin-Peng Cummings, Sol Yang, Cheng-Yen Hsu, Hung-Min Cai, Jiarui Mei, Jie Yeh, Chia-Ying Hwang, JenqNeng Yifei, Xu Jain, Sahil Geng, Xueli Ma, Mengru Cai, Huanqia Cai, Chengxue Miron, Casian Pasarica, Alexandru Shangguan, Zhongkai Zheng, Zihe Yang, Lehan Xu, Kele Air Force Research Laboratory United States University of Illinois at Urbana-Champaign United States Wright Brothers Institute United States Duke University United States Computer Vision Lab ETH Zürich Switzerland Chang'an Campus Northwestern Polytechnical University Shaanxi Province Xi'an China Beihang University China PASCO Corporation Japan University of Washington United States Xidian University China Dengzhuang South Road Haidian District China Gheorghe Asachi Technical University Romania University of Rochester United States The University of Sydney Key Laboratory for Parallel and Distributed Processing China

In this paper, we introduce the first Challenge on Multi-modal Aerial View Object Classification (MAVOC) in conjunction with the NTIRE 2021 workshop at CVPR. This challenge is composed of two different tracks using EO and SAR imagery. Both EO and SAR sensors possess different advantages and drawbacks. The purpose of this competition is to analyze how to use both sets of sensory information in complementary ways. We discuss the top methods submitted for this competition and evaluate their results on our blind test set. Our challenge results show significant improvement of more than 15% accuracy from our current baselines for each track of the competition. © 2021, CC BY.

关键词： Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

CACAI: Comparative analysis of crypto apps in India

引用

AIP Conference Proceedings 2023年第1期2916卷

作者： Rahul Johari Anuj Talwar Suhas Harbola Jyotsna Yadav Himesh Nayak Deo Prakash Vidyarthi SWINGER: Security Wireless IoT Network Group of Engineering and Research University School of Information Communication and Technology (USICT) Guru Gobind Singh Indraprastha University Sector-16C Dwarka Delhi India Computer vision and Image processing lab University School of Information Communication and Technology (USICT) Guru Gobind Singh Indraprastha University Sector-16C Dwarka Delhi India School of Computer and Systems Sciences Parallel and Distributed Systems Lab JNU Delhi India

Crypto-currency is a decentralized digital currency which can be used as a medium of exchange. As it does not have any central authority, it is unregulated and a volatile asset. Globally the crypto market is worth a few trillion dollars. The Indian crypto market suffered a lot due to a ban imposed by the Reserve Bank of India (RBI), an Indian regulatory agency, which lasted for around two years. Even after the ban and cautions issued by the RBI, the crypto market in India touched a billion dollar mark in no time. Currently, the crypto market has more than 10 million Indian investors which is growing fast as the number of exchange apps in the Indian market increase with the ease of trading in crypto. In the current research work Comparative Analysis of Crypto App in India (CACAI) has been performed and results exceed the expectations.

关键词：

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：