检索结果-内蒙古大学图书馆

IEEE General Meeting Power& Energy Society

作者： Dennis Agnew Sharon Boamah Reynold Mathieu Austin Cooper Janise McNair Arturo Bretas Department of Electrical and Computer Engineering University of Florida Gainesville FL Distributed Systems Group Pacific Northwest National Laboratory Richland WA

An important challenge for smart grid security is designing a secure and robust smart grid communications architecture to protect against cyber-threats, such as Denial-of-Service (DoS) attacks, that can adversely impact the operation of the power grid. Researchers have proposed using Software Defined Network frameworks to enhance cybersecurity of the smart grid, but there is a lack of benchmarking and comparative analyses among the many techniques. In this work, a distributed three-controller software-defined networking (D3-SDN) architecture, benchmarking, and comparative analysis with other techniques is presented. The selected distributed flat SDN architecture divides the network horizontally into multiple areas or clusters, where each cluster is handled by a single Open Network Operating System (ONOS) controller. A case study using the IEEE 118-bus system is provided to compare the performance of the presented ONOS-managed D3-SDN, against the POX controller. In addition, the proposed architecture outperforms a single SDN controller framework by a tenfold increase in throughput; a reduction in latency of > 20%; and an increase in throughput of approximately 11% during the DoS attack scenarios.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Peer to Peer Federated Learning: Towards Decentralized Machine Learning on Edge Devices 7

Peer to Peer Federated Learning: Towards Decentralized Machi...

引用

7th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2022

作者： Karras, Aristeidis Karras, Christos Giotopoulos, Konstantinos C. Tsolis, Dimitrios Oikonomou, Konstantinos Sioutas, Spyros University of Patras Decentralized Systems Computing Group Computer Engineering and Informatics Department Patras Greece University of Patras Department of Management Science and Technology Patras Greece Ionian University Department of Informatics Corfu Greece

ISBN: (数字)9798350398588

ISBN: (纸本)9798350398588

Federated Learning (FL) is an emerging technique that assures user privacy and data integrity in distributed machine learning environments. To perform so, chunks of data are trained across edge devices and a high performance cluster server maintains a local copy without exchanging it with other parties. In this work, we investigate a FL scenario in a real-world case study using 5, 10 and 20 Raspberry Pi devices acting as clients. Under this setup, we employ the widely known FedAvg algorithm which trains each client for several local epochs and then the weight of each model is aggregated. Moreover we perform experiments across imbalanced and noisy data so as to explore scalability and robustness based on real-world datasets were noise is present and we also propose two innovative algorithms where the FL scenario is considered as a peer-to-peer formulation. Ultimately, to ensure that each device is not oversampled a client-balancing Dirichlet sampling algorithm with probabilistic guarantees is proposed. © 2022 IEEE.

关键词： computer aided instruction

来源：评论

学校读者我要写书评

暂无评论

Abstracting Linear Stochastic systems via Knowledge Filtering

Abstracting Linear Stochastic Systems via Knowledge Filterin...

引用

IEEE Conference on Decision and Control

作者： M.H.W. Engelaar L. Romao Y. Gao M. Lazar A. Abate S. Haesaert Department of Electrical Engineering (Control Systems Group) Eindhoven University of Technology The Netherlands Department of Computer Science University of Oxford United Kingdom

In this paper, we propose a new model reduction technique for linear stochastic systems that builds upon knowledge filtering and utilizes optimal Kalman filtering techniques. This new technique will reduce the dimension of the noise disturbance and will allow any controller designed for the reduced model to be refined into a controller for the original stochastic system, while preserving any specification on the output. Although initially the reduced model will be time-varying, a method will be provided with which the reduced model can become time-invariant if it satisfies some minor technical conditions. We present our theoretical findings with an example that supports the proposed framework and illustrates how model reduction and controller refinement of stochastic systems can be achieved. We finish the paper by considering specific examples to analyze both completeness with respect to controller synthesis and model order reduction with respect to the state.

关键词：

来源：评论

学校读者我要写书评

暂无评论

High-Gain, Low-Profile, Integrable Planar Lens Antenna at 275 GHz 11

High-Gain, Low-Profile, Integrable Planar Lens Antenna at 27...

引用

11th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2023 - Proceedings

作者： Li, Mingxiang Stephen Ako, Rajour Tanyi Sriram, Sharath Fumeaux, Christophe Withayachumnankul, Withawat Rmit University Functional Materials and Microsystems Research Group and the Micro Nano Research Facility Arc Centre of Excellence for Transformative Meta-Optical Systems MelbourneVIC3000 Australia The University of Adelaide Terahertz Engineering Laboratory AdelaideSA5005 Australia The University of Queensland School of Electrical Engineering and Computer Science BrisbaneQLD4072 Australia

ISBN: (纸本)9798350326277

Terahertz communications require compact, high-gain antennas that can be integrated with sources, as alternative to traditional lenses, which have bulky sizes and lack design flexibility. This paper introduces a high-gain, low-profile silicon cavity antenna integrated with a WR-3 waveguide feed. The antenna consists of a 2-mm thick silicon wafer with non-uniform hole arrays designed to locally control the effective permittivity. The holes are laser-etched on both sides of the silicon wafer, to overcome phase coverage limitations caused by the tapered side walls of the air hole during fabrication. Experimental results confirm a gain of 19 dBi at 275 GHz, with a 3-dB bandwidth of approximately 29%. We further demonstrate that the high-gain antenna can be integrated with a quarter-wave plate for circularly polarized (CP) radiation. © 2023 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Price Prediction of Digital Currencies using Machine Learning 10

Price Prediction of Digital Currencies using Machine Learnin...

引用

10th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2023

作者： Dwivedi, Ashutosh Dhar Dutta, Subhayu Adhikary, Subhrangshu Pedersen, Jens Myrup Aalborg University Cyber Security Group Department of Electronic Systems Copenhagen Denmark Dr. B.C. Roy Engineering College Department of Computer Science & Engineering West Bengal Durgapur713206 India Spiraldevs Automation Industries Pvt. Ltd. Department of Research & Development West Bengal Raiganj733123 India

ISBN: (纸本)9798350345032

Cryptocurrencies have gained immense significance and popularity in recent times. With thousands of digital currencies available, selecting the right one can be challenging for users. In the financial sector, accurately predicting future prices is crucial for profitable investments in digital currencies. However, price prediction in this realm poses unique challenges, as it lacks physical goods or services as the basis, unlike stock prices. Machine learning emerges as a pivotal tool for addressing this challenge and plays a vital role in price prediction. This research analyzes five prominent currencies - Monero, Bitcoin, Ethereum, IOTA, and Zcash - employing five models: SVR, LRG, Huber, RANSAC, MLP, and AdaBoost. The experimental results demonstrate promising outcomes, showcasing the ability to predict digital currency prices with an impressive R2 score of 1.0 for specific machine learning algorithms. This advancement opens new avenues for informed decision-making and profitable ventures in the dynamic world of digital currencies. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Orthogonal projection for anomaly detection in networking datasets

引用

Journal of Ambient Intelligence and Humanized Computing 2023年第6期14卷 7957-7966页

作者： Cortes-Polo, David Jimenez, Luis I. Paoletti, Mercedes E. Calle-Cancho, Jesus Rico-Gallego, Juan A. Department of Signal Theory and Communication University Rey Juan Carlos Cam. del Molino 5 Madrid Fuenlabrada28942 Spain Intelligent Systems Group Department of Computer Science University of Valladolid P.O de Belén 15 Valladolid47011 Spain Hyperspectral Computing Laboratory Department of Technology of Computers and Communication University of Extremadura Av. de la Universidad s/n Caceres10003 Spain Calle Sola 1 Extremadura Trujillo10200 Spain Computer and Telematics Systems Engineering University of Extremadura Av. de la Universidad s/n Caceres10003 Spain

In recent years, the impressive growth of new wireless technologies, together with the appearance of new requirements in applications and services, is progressively changing the use of networks. Due to the high mobility required, the network must adapt to the infrastructure to meet the demands of the users. As a result, service providers currently have to over-provision network capacity, which is costly. In addition, considering efficient resource planning in advance involves a lot of labor-intensive efforts. Consequently, network usage analysis is a very useful tool that allows network administrators to find patterns and anomalies. Whilst pattern detection provides administrators the ability to define the infrastructure, anomaly detection provides rich and valuable information for certain applications, for example, to avoid network saturation in urban areas during peak hours. This article proposes a new methodology based on orthogonal projections over Call Detail Records (CDR) for anomaly detection to help in the dynamic management of the network in an urban area. The method is evaluated in a real scenario provided by an Italian telecommunications operator, considering different locations in the Milan metropolitan area, differentiated by the geographic resolution of the data, reaching F1 scores above 0.8. In addition, a new ground truth is presented, hoping it will become a reference data set for the community, in the form of a set of locations that have been corroborated for use in evaluating anomaly detection techniques. © 2023, The Author(s).

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Particle Swarm Optimization to Forecast Implied Volatility Risk

引用

computers, Materials & Continua 2022年第11期73卷 4291-4309页

作者： Kais Tissaoui Sahbi Boubaker Waleed Saud Alghassab Taha Zaghdoudi Jamel Azibi University of Ha’il Applied CollegeHail CitySaudi Arabia University of Tunis El Manar Faculty of Economic Sciences and Management of Tunisthe International Finance GroupTunisTunisia Department of Computer and Network Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah21959Saudi Arabia Research Unit on Study of Systems and Renewable Energy National College of Engineering of MonastirUniversity of MonastirMonastirTunisia LAREQUAD&FSEGT University of Tunis El ManarTunisTunisia University of Jendouba Law FacultyManagement and Economic Sciences of JendoubaTunisia

The application of optimization methods to prediction issues is a continually exploring *** line with this,this paper investigates the connectedness between the infected cases of COVID-19 and US fear index from a forecasting *** complex characteristics of implied volatility risk index such as non-linearity structure,time-varying and nonstationarity motivate us to apply a nonlinear polynomial Hammerstein model with known structure and unknown *** use the Hybrid Particle Swarm Optimization(HPSO)tool to identify the model parameters of nonlinear polynomial Hammerstein *** indicate that,following a nonlinear polynomial behaviour cascaded to an autoregressive with exogenous input(ARX)behaviour,the fear index in US financial market is significantly affected by COVID-19-infected cases in the US,COVID-19-infected cases in the world and COVID-19-infected cases in China,*** performance indicators provided by the developed models show that COVID-19-infected cases in the US are particularly powerful in predicting the Cboe volatility index compared to COVID-19-infected cases in the world and China(MAPE(2.1013%);R2(91.78%)and RMSE(0.6363 percentage points)).The proposed approaches have also shown good convergence characteristics and accurate fits of the data.

关键词： Forecasting Cboe’s volatility index COVID-19 pandemic nonlinear polynomial hammerstein model hybrid particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

Dual Dynamic Threshold Adjustment Strategy for Deep Metric Learning

arXiv

引用

arXiv 2024年

作者： Jiang, Xiruo Yao, Yazhou Liu, Sheng Shen, Fumin Nie, Liqiang Hua, Xian-Sheng The School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China The State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China The School of Computer Science and Engineering University of Electronic Science and Technology Chengdu China Shenzhen China The Terminus Group Beijing China

Loss functions and sample mining strategies are essential components in deep metric learning algorithms. However, the existing loss function or mining strategy often necessitate the incorporation of additional hyperparameters, notably the threshold, which defines whether the sample pair is informative. The threshold provides a stable numerical standard for determining whether to retain the pairs. It is a vital parameter to reduce the redundant sample pairs participating in training. Nonetheless, finding the optimal threshold can be a time-consuming endeavor, often requiring extensive grid searches. Because the threshold cannot be dynamically adjusted in the training stage, we should conduct plenty of repeated experiments to determine the threshold. Therefore, we introduce a novel approach for adjusting the thresholds associated with both the loss function and the sample mining strategy. We design a static Asymmetric Sample Mining Strategy (ASMS) and its dynamic version Adaptive Tolerance ASMS (AT-ASMS), tailored for sample mining methods. ASMS utilizes differentiated thresholds to address the problems (too few positive pairs and too many redundant negative pairs) caused by only applying a single threshold to filter samples. AT-ASMS can adaptively regulate the ratio of positive and negative pairs during training according to the ratio of the currently mined positive and negative pairs. This meta-learning-based threshold generation algorithm utilizes a single-step gradient descent to obtain new thresholds. We combine these two threshold adjustment algorithms to form the Dual Dynamic Threshold Adjustment Strategy (DDTAS). Experimental results show that our algorithm achieves competitive performance on CUB200, Cars196, and SOP datasets. Our codes are available at https://***/NUST-Machine-Intelligence-Laboratory/DDTAS. Copyright © 2024, The Authors. All rights reserved.

关键词： Image retrieval

来源：评论

学校读者我要写书评

暂无评论

A Quality Diversity Study in EvoDevo Processes for engineering Design

A Quality Diversity Study in EvoDevo Processes for Engineeri...

引用

Congress on Evolutionary Computation

作者： Edgar Buchanan Simon Hickinbotham Rahul Dubey Imelda Friel Andrew Colligan Mark Price Andy M. Tyrrell Intelligent Systems & Robotics Research Group School of Physics Engineering and Technology University of York UK Computer Science Missouri State University USA School of Mechanical & Aerospace Engineering Queen's University Belfast

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

For a long time engineering design has relied on human engineers manually crafting and refining designs using their expertise and experience. In Bio-inspired Evolutionary Development (EvoDevo), generative algorithms are employed to investigate a broader design space that may go beyond what human engineers have considered. Previous literature has demonstrated the use of quality and diversity (QD) algorithms in evolutionary approaches to drive the process to better quality solutions. This paper provides a study to understand the effects of using QD algorithms in EvoDevo processes for engineering design. This paper also analyses the impact of using different behavioural characterisations (BC) in the performance of the quality of the solutions found. The results demonstrate that quality and diversity algorithms can find better solutions than other EAs for engineering design problems. It was also found that the characterisation of the BC is important to get the best results.

关键词： Measurement Dimensionality reduction Refining Evolutionary computation Calibration

来源：评论

学校读者我要写书评

暂无评论

Data-Driven Model for Photovoltaic Generation: Comparison with Physical Models Using a Microgrid in Puerto Rico

Data-Driven Model for Photovoltaic Generation: Comparison wi...

引用

IEEE General Meeting Power& Energy Society

作者： Marcos R. Pesante Colón Alberto I. Cruz Salamán Dylan Cruz Figueroa Aditya Sundararajan Maximiliano Ferrari Electrical and Computer Engineering Department University of Puerto Rico Mayagüez USA Grid Systems Architecture Group Oak Ridge National Laboratory Oak Ridge TN USA

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

Photovoltaic (PV) generation is a critical component of microgrids, but its accurate modeling is challenging due to the complex and dynamic interactions between solar irradiance, temperature, and PV system installation. This paper develops a multilayer perceptron (MLP) model that inputs solar irradiance and temperature to estimate the PV generation, and it compares the proposed data-driven model’s performance to two well-known physical models: the single-diode model and the inverter model. The results demonstrate that all the models can reach high levels of accuracy. However, the MLP model outperforms the physical models on average by 4.5 to 6.6 percent in R squared scores and 220 to 290 Watts in RMSE scores, and it does not require physical system parameters. Moreover, the data-driven model can overcome the limitations of the lack of real-time PV generation data.

关键词： Temperature measurement Solar irradiance Photovoltaic systems Adaptation models Accuracy Voltage measurement Predictive models Multilayer perceptrons Data models Inverters

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：