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Oscillatory velocity in boundary layer over mobile sediment bed under asymmetric wave and current conditions

Journal of Hydrodynamics 2021年第6期33卷 1242-1254页

作者： Xin Chen Beijing Engineering Research Center of Safety and Energy Saving Technology for Water Supply Network System China Agricultural UniversityBeijing 100083China Key Laboratory of Water-Sediment Sciences and Water Disaster Prevention of Hunan Province Changsha University of Science and TechnologyChangsha 410114China

The oscillatory flow provides the major dynamic force for the mass and energy transport in estuary and coastal *** analytical approximate velocity formula is proposed to evaluate the oscillation in the boundary layer over the mobile sediment bed of the sheet flow induced by the asymmetric wave and *** velocity formula consists of an oscillatory force part and a constant force part corresponding to the Navier-Stokes equation of the asymmetric oscillatory sheet flow over the mobile sediment *** mobile sediment bed is defined by an erosion depth formula with consideration of the phase lag,the acceleration and the flow *** wave part includes the phase lead parameters from all components of the free stream *** development of the wave part is affected by the current part through the erosion depth and the boundary layer *** erosion depth,the roughness height and the boundary layer thickness of the mobile sediment bed are introduced into the current part without a transition area for the wave-current eddy *** current part is induced by the wave eddy viscosity within the boundary layer and influenced by the wave-current apparent roughness outside the boundary *** velocity profile and duration are evaluated by an approximate velocity formula through experiments for both asymmetric wave and wave-current *** oscillation feature in the boundary layer is illustrated by the approximate velocity formula through the asymmetric wave cases over the mobile sediment bed.

关键词： Analytical approximation asymmetric wave and current eddy viscosity mobile sediment bed oscillatory sheet flow

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Activity-specific caloric expenditure estimation from kinetic energy harvesting in wearable devices

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Pervasive and Mobile computing 2020年 67卷 101185-101185页

作者： Xiao, Ling Wu, Kai Tian, Xiaobing Luo, Juan College of Computer Science and Electronic Engineering Hunan University Changsha0731 China Key Laboratory for Embedded and Network Computing of Hunan Province China

Accurate and efficient estimation of caloric expenditure during daily activities is desirable in tracking personal activity and health. Kinetic energy harvesting (KEH) has created an opportunity for wearable devices with limited battery power to realize long-term human health monitoring. We postulate to utilize KEH device for calorie estimation instead of accelerometer considering that the kinetic energy is produced when the user expends some calories by doing the bodily movement. In this paper, we propose to use the output voltage of KEH for activity intensity classification and develop activity-specific regression models combined with anthropometric characteristics for caloric expenditure estimation by random forest. To validate our approach, we build a KEH hardware platform and collect the dataset of seven different activities in free-living conditions from ten participants. Experiment results show that our approach achieves an accuracy of 95. 7% to classify intensity of activity and yields a R2 coefficient of 0.93 for regression model and a root mean square error (RMSE) of 1.09 kcal/min to estimate calorie expenditure by only using the output voltage of KEH. The comparison experiments validate the effectiveness of KEH device for caloric expenditure estimation act as a substitute for accelerometer in terms of estimation accuracy and energy saving. © 2020 Elsevier B.V.

关键词： Energy harvesting

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Coordinated dynamic mission planning scheme for intelligent multi-agent systems

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Journal of Central South university 2012年第11期19卷 3170-3179页

作者：彭军文孟飞谢国祺张晓勇 Kuo-chi LIN School of Information Science and Engineering Central South UniversityChangsha 410075China Hunan Engineering Laboratory for Advanced Control and Intelligent Automation(Central South University) Changsha 410075China Embedded Systems and Networking Laboratory Hunan Provincial Key Laboratory of Network and Information Security(Hunan University)Changsha 410075China Department of Mechanical and Aerospace Engineering University of Central FloridaOrlandoFL 32816USA

Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor ***,it still faces challenges due to the system complexity,the execution order constraints,and the dynamic environment *** address it,a coordinated dynamic mission planning scheme is proposed utilizing the method of the weighted AND/OR tree and the *** the scheme,the mission is decomposed into a time-constraint weighted AND/OR tree,which is converted into an AOE-network for mission ***,a dynamic planning algorithm is designed which uses task subcontracting and dynamic re-decomposition to coordinate *** scheme can reduce the task complexity and its execution time by implementing real-time dynamic *** simulation proves the effectiveness of this approach.

关键词： weighted AND/OR tree multiple intelligent agent coordinated dynamic mission planning AOE-network

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A New Method for Evaluating Core Developers In Open Source Software 13

A New Method for Evaluating Core Developers In Open Source S...

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13th IEEE International Conference on Software Engineering and Service Science, ICSESS 2022

作者： Song, Yulin Wang, Tao Shen, Yang Chang, Junsheng National University of Defense Technology National Laboratory for Parallel and Distributed Processing Hunan Province Changsha China National University of Defense Technology Institute for Quantum Information State Key Laboratory of High Performance Computing Hunan Province Changsha China

ISBN: (数字)9781665410328

ISBN: (纸本)9781665410311

The high-quality development of Open Source Software(OSS) benefits from the contributions of developers. An important research question is how to truly assess the extent of contribution of all developers in open source software and effectively identify the core developers to avoid their loss. In this paper, we use the undirected weighted network model to build a Developer Collaboration network(DCN) based on developers and their contributions to the GitHub community's open source software Rails, analyse the characteristics of developer partnerships through the Developer Collaboration network, and propose a Developer Personal Impact Factor(DPIF) to evaluate the importance of developer, select the top 10 core developers in Rails, focus on their participation in the open source software process, and predicting the changes of their contributions. The experimental results show that core developers with extensive partnerships are more likely to associate with developers with fewer partnerships. The average degree of developer contribution does not increase with more developers. Developer partnerships are characterized by close localization and loose overall relationships. The Developer Personal Impact Factor identifies the core developers in open source software well. The Developer Personal Impact Factor gives a ranking in which the core team members rank in the top 1.17% on average. © 2022 IEEE.

关键词： Open source software

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Fine-Grained Multivariate Time Series Anomaly Detection in IoT

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Computers, Materials & Continua 2023年第6期75卷 5027-5047页

作者： Shiming He Meng Guo Bo Yang Osama Alfarraj Amr Tolba Pradip Kumar Sharma Xi’ai Yan School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha410114China Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Computing Science University of AberdeenAberdeenAB243FXUK Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Police AcademyChangsha410138China

Sensors produce a large amount of multivariate time series data to record the states of Internet of Things(IoT)*** time series timestamp anomaly detection(TSAD)can identify timestamps of attacks and ***,it is necessary to determine which sensor or indicator is abnormal to facilitate a more detailed diagnosis,a process referred to as fine-grained anomaly detection(FGAD).Although further FGAD can be extended based on TSAD methods,existing works do not provide a quantitative evaluation,and the performance is ***,to tackle the FGAD problem,this paper first verifies that the TSAD methods achieve low performance when applied to the FGAD task directly because of the excessive fusion of features and the ignoring of the relationship’s dynamic changes between ***,this paper proposes a mul-tivariate time series fine-grained anomaly detection(MFGAD)*** avoid excessive fusion of features,MFGAD constructs two sub-models to independently identify the abnormal timestamp and abnormal indicator instead of a single model and then combines the two kinds of abnormal results to detect the fine-grained *** on this framework,an algorithm based on Graph Attention Neural network(GAT)and Attention Convolutional Long-Short Term Memory(A-ConvLSTM)is proposed,in which GAT learns temporal features of multiple indicators to detect abnormal timestamps and A-ConvLSTM captures the dynamic relationship between indicators to identify abnormal *** simulations on a real-world dataset demonstrate that the proposed algorithm can achieve a higher F1 score and hit rate than the extension of existing TSAD methods with the benefit of two independent sub-models for timestamp and indicator detection.

关键词： Multivariate time series graph attention neural network fine-grained anomaly detection

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Infra-YOLO: Efficient Neural network Structure with Model Compression for Real-Time Infrared Small Object Detection

arXiv

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arXiv 2024年

作者： Chen, Zhonglin Geng, Anyu Jiang, Jianan Lu, Jiwu Wu, Di The College of Electrical and Information Engineering Hunan University Hunan Changsha410082 China The Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University Hunan Changsha410082 China

Although convolutional neural networks have made outstanding achievements in visible light target detection, there are still many challenges in infrared small object detection because of the low signal-to-noise ratio, incomplete object structure, and a lack of reliable infrared small object dataset. To resolve limitations of the infrared small object dataset, a new dataset named InfraTiny was constructed, and more than 85% bounding box is less than 32x32 pixels (3218 images and a total of 20,893 bounding boxes). A multi-scale attention mechanism module (MSAM) and a Feature Fusion Augmentation Pyramid Module (FFAFPM) were proposed and deployed onto embedded devices. The MSAM enables the network to obtain scale perception information by acquiring different receptive fields, while the background noise information is suppressed to enhance feature extraction ability. The proposed FFAFPM can enrich semantic information, and enhance the fusion of shallow feature and deep feature, thus false positive results have been significantly reduced. By integrating the proposed methods into the YOLO model, which is named Infra-YOLO, infrared small object detection performance has been improved. Compared to yolov3, mAP@0.5 has been improved by 2.7%;and compared to yolov4, that by 2.5% on the InfraTiny dataset. The proposed Infra-YOLO was also transferred onto the embedded device in the unmanned aerial vehicle (UAV) for real application scenarios, where the channel pruning method is adopted to reduce FLOPs and to achieve a tradeoff between speed and accuracy. Even if the parameters of Infra-YOLO are reduced by 88% with the pruning method, a gain of 0.7% is still achieved on mAP@0.5 compared to yolov3, and a gain of 0.5% compared to yolov4. Experimental results show that the proposed MSAM and FFAFPM method can improve infrared small object detection performance compared with the previous benchmark method. © 2024, CC BY-NC-ND.

关键词： Convolutional neural networks

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Efficient differential fault analysis attacks to AES decryption for low cost sensors in IoTs

Efficient differential fault analysis attacks to AES decrypt...

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International Symposium on Circuits and Systems

作者： Limin Zhu Yi Wang Renfa Li Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University Changsha China Institute for Infocomm Research A?STAR Singapore

ISBN: (纸本)9781479953424

Robust sensor system plays an important role in Internet of Things (IoTs). These intelligent sensors are required to be low cost and reliable, which provides confidentiality for private sensitive data. However, this protected system is still under the risk of Differential Fault Analysis (DFA) attacks. In this paper, we focus on DFA attacks to AES decryption as decryption receives the equalling importance as encryption. First, we induce a fault at the input of the third round in the procedure of AES decryption, in which w e successfully break it using one pair of fault-free and faulty plaintexts within 232 searching space. Then, we improve this attack by use of S-Box distribution table, which reduces the computational time from 853 ms to 70 ms on a dual Intel(R) Pentium(R) E6700 core (3.20 GHz). Compared to the existing work, our proposed attack reduces 79.5% computational time when both methods employ two pairs of fault-free and faulty ciphertexts/plaintexts.

关键词： Ciphers Mathematical model Encryption Internet of things Intelligent sensors Sensor systems

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IoT data analytics using deep learning

arXiv

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arXiv 2017年

作者： Xie, Xiaofeng Wu, Di Liu, Siping Li, Renfa Key Laboratory for Embedded Networking Computing of Hunan Province Hunan University

Deep learning is a popular machine learning approach which has achieved a lot of progress in all traditional machine learning areas. Internet of thing (IoT) and Smart City deployments are generating large amounts of time-series sensor data in need of analysis. Applying deep learning to these domains has been an important topic of research. The Long-Short Term Memory (LSTM) network has been proven to be well suited for dealing with and predicting important events with long intervals and delays in the time series. LTSM networks have the ability to maintain long-term memory. In an LTSM network, a stacked LSTM hidden layer also makes it possible to learn a high level temporal feature without the need of any fine tuning and preprocessing which would be required by other techniques. In this paper, we construct a long-short term memory (LSTM) recurrent neural network structure, use the normal time series training set to build the prediction model. And then we use the predicted error from the prediction model to construct a Gaussian naive Bayes model to detect whether the original sample is abnormal. This method is called LSTM-Gauss-NBayes for short. We use three real-world data sets, each of which involve long-term time-dependence or short-term time-dependence, even very weak time dependence. The experimental results show that LSTM-Gauss-NBayes is an effective and robust model. Copyright © 2017, The Authors. All rights reserved.

关键词： Long short-term memory

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JDAS: a software development framework for multidatabases

JDAS: a software development framework for multidatabases

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作者： Xie, Guoqi Chen, Yuekun Liu, Yan Fan, Chunnian Li, Renfa Li, Keqin College of Computer Science and Electronic Engineering Hunan University China Key Laboratory for Embedded and Network Computing of Hunan Province China Nanjing University of Information Science and Technology China Department of Computer Science State University of New York New PaltzNY United States

Modern software development for services computing and cloud computing software systems is no longer based on a single database but on existing multidatabases and this convergence needs new software architecture and framework design. Most current popular frameworks are not designed for multidatabases, and many practical problems in development arise. This study designs and implements a software development framework called Java data access service (JDAS) for multidatabases using the object-oriented programming language Java. The JDAS framework solves related problems that arise when other frameworks are employed in practical software development with multidatabases by presenting and introducing design methods. JDAS consists of the modules of the database abstract, object relational mapping, connection pools management, configuration management, data access service, and inversion of control. Results and case study reveal that the JDAS framework effectively reduces development complexity and improves development efficiency of the software systems with multidatabases. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

关键词： Object oriented programming

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A Unified Architecture for Supporting Operations of AES and ECC

A Unified Architecture for Supporting Operations of AES and ...

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International Symposium on Parallel Architectures, Algorithms and Programming (PAAP)

作者： Yi Wang Renfa Li Embedded Systems and Networking Laboratory Hunan Province Key Laboratory of Network and Information Security Hunan University Changsha China

In the recent years, embedded systems began to be used in sensitive applications such as personal digital assistants and smart cards. Due to very strict cost and power constrains, the support for cryptography provided by these devices is often limited to either public or private key primitives. This limitation is much more evident in devices where the cryptographic algorithms are implemented using hardware resources. In this paper, we propose an extension of a public-key cryptosystem to support also private-key, and we evaluate our architecture on FPGA platforms. In particular, we propose a new arithmetic unit in which the polynomial modular multiplication of ECC is extended to compute also the polynomial arithmetic operations over binary extended field of AES. We compare our design with an architecture obtained by instantiating state of the art implementation of AES and ECC and we evaluate the trade-offs. The experimental results show that our proposed architecture takes up less hardware resources. Nevertheless, the achieved performances are better compared to the ECC reference core, while the ones compared to AES only implementation are comparable with the state of the art.

关键词： Elliptic curve cryptography Polynomials Algorithm design and analysis Computer architecture Computer science Hardware

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