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SSRN 2023年

作者： He, Shuang Tian, Jia Hao, Lina Zhang, Sen Tian, Qingjiu International Institute for Earth System Science Nanjing University Nanjing210046 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Nanjing University Nanjing210023 China Collaborative Innovation Center for the South Sea Studies Nanjing University Nanjing210093 China School of Instrumentation and Optoelectronic Engineering Beihang University Beijing100191 China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China

Hyperspectral image classification (HSIC) is a rapidly developing field that utilizes deep learning methods. However, the reliance on convolutional neural networks (CNNs) for spectral-spatial feature extraction presents certain limitations. Specifically, the use of the fixed-position convolutional kernels in CNNs hinders their ability to fully capture the spectral information around the spatial central pixel, thereby overlooking critical differences between features. To address this issue, we proposed a decoupled image- and frequency-domain spectral-spatial framework for HSIC. Our method incorporated image- and frequency-domain-based multiscale learnable convolutional attention to refine the differentiating features of the different feature distributions. Additionally, we designed a novel frequency-domain information enhancement module to extract the structural shape and texture details under the semantic constraints of the frequency phase, complementing the image domain to improve the extracted feature maps. Furthermore, we introduced a simple and efficient hierarchical feature representation module to effectively extract both local and global information from the fused features. Experimental results on three open datasets and a practical hyperspectral image of the Gaofen-5 satellite demonstrate that our method outperforms other state-of-the-art HSIC methods. © 2023, The Authors. All rights reserved.

关键词： Feature extraction

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LBAA: A novel load balancing mechanism in cloud environments using ant colony optimization and artificial bee colony algorithms

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International Journal of Communication systems 2023年第9期36卷 e5481-e5481页

作者： Mohammadian, Vahid Navimipour, Nima Jafari Hosseinzadeh, Mehdi Darwesh, Aso Department of Computer Engineering Qeshm Branch Islamic Azad University Qeshm Iran Department of Computer Engineering Tabriz Branch Islamic Azad University Tabriz Iran Future Technology Research Center National Yunlin University of Science and Technology Yunlin Douliou64002 Taiwan Pattern Recognition and Machine Learning Lab Gachon University Seongnam Korea Republic of Information Technology Departments University of Human Development Sulaimaniyah Iraq

Recently, cloud computing has been recognized as an effective paradigm for offering an on-demand platform, software services, and an efficient infrastructure to cloud clients. Due to the exponential growth of cloud tasks and the rapidly increasing number of cloud users, scheduling and balancing these tasks among involved heterogeneous virtual machines becomes an Non-deterministic Polynomial hard (NP-hard) optimization problem considering significant constraints, such as high rate of resource usage, low scheduling time, and low implementation cost. Therefore, various meta-heuristic algorithms have been widely used to tackle the issue. The current paper proposes a novel load balancing mechanism using the ant colony optimization and artificial bee colony algorithms, called LBAA, which aims to balance the load division among systems in data centers. The simulation outcomes confirm that our algorithm outperforms previous works regarding response time, imbalance degree, makespan, and resource utilization up to 25%, 15%, 12%, and 10%, respectively. © 2023 John Wiley & Sons Ltd.

关键词： Ant colony optimization

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system Network Analytics: Evolution and Stable Rules of a State Series

arXiv

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arXiv 2022年

作者： Chaturvedi, Animesh Tiwari, Aruna Spyratos, Nicolas Data Science and Intelligent Systems Indian Institute of Information Technology Dharwad Karnataka Dharwad India Computer Science and Engineering Indian Institute of Technology Indore Indore India Computer Science Department LISN Lab University of Paris-Saclay Paris France

system Evolution Analytics on a system that evolves is a challenge because it makes a State Series SS = {S1, S2… SN} (i.e., a set of states ordered by time) with several inter-connected entities changing over time. We present stability characteristics of interesting evolution rules occurring in multiple states. We defined an evolution rule with its stability as the fraction of states in which the rule is interesting. Extensively, we defined stable rule as the evolution rule having stability that exceeds a given threshold minimum stability (minStab). We also defined persistence metric, a quantitative measure of persistent entity-connections. We explain this with an approach and algorithm for system Network Analytics (SysNet-Analytics), which uses minStab to retrieve Network Evolution Rules (NERs) and Stable NERs (SNERs). The retrieved information is used to calculate a proposed system Network Persistence (SNP) metric. This work is automated as a SysNet-Analytics Tool to demonstrate application on real world systems including: software system, natural-language system, retail market system, and IMDb system. We quantified stability and persistence of entity-connections in a system state series. This results in evolution information, which helps in system evolution analytics based on knowledge discovery and data mining. © 2022, CC BY.

关键词： Stability

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Optical-Amplification-Free 206/112 Gbaud OOK/PAM4 O-Band SiP RRM-Based Links 16

Optical-Amplification-Free 206/112 Gbaud OOK/PAM4 O-Band SiP...

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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Ostrovskis, Armands Salgals, Toms Koenigsmann, Michael Rubuls, Kristaps Farid, Azra Krüger, Benjamin Sedulis, Arvids Pittalà, Fabio Scott, Ryan P. Haisch, Hansjoerg Zhang, Lu Yu, Xianbin Puerta, Rafael Spolitis, Sandis Schatz, Richard Gallo, Katia Gruen, Markus Louchet, Hadrien Jahn, Robert Yamaguchi, Kazuo Bobrovs, Vjaceslavs Pang, Xiaodan Ozolins, Oskars Keysight Technologies Deutschland GmbH Böblingen71034 Germany Keysight Technologies Inc. Santa ClaraCA United States College of Information Science and Electronic Engineering Zhejiang University Zhejiang Lab Hangzhou China Ericsson Research Ericsson Ab Stockholm Sweden Kth Royal Institute of Technology Department of Applied Physics Stockholm10691 Sweden Rise Research Institutes of Sweden Kista16440 Sweden Institute of Photonics Electronics and Telecommunications Riga Technical University Riga1048 Latvia

We report on an optical-amplification-free O-band SiP RRM-based IM/DD link with unprecedented data rates achieved below the 6.25%-OH HD-FEC threshold. Transmission of 206 Gbaud OOK and 112 Gbaud PAM4 over 500-m SMF ar... 详细信息

ISBN: (纸本)9798350372076

关键词： Light modulation

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L21-Norm-Based Common Spatial Pattern with Regularized Filters 4

L21-Norm-Based Common Spatial Pattern with Regularized Filte...

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4th IEEE Advanced information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2021

作者： Gu, Jingyu Cai, Qian Gong, Weiqiang Wang, Haixian Southeast University Key Laboratory of Child Development and Learning Science of Ministry of Education School of Biological Science Medical Engineering Nanjing210096 China Nanjing Audit University School of Statistics and Mathematics Nanjing211815 China Nanjing les Information System Technology Company Ltd. Nanjing210007 China

ISBN: (纸本)9781728185347

Common spatial pattern (CSP) is one of the most popular feature extraction techniques that performs well in the field of brain-computer interface (BCI). However, the classical CSP based on the squared Frobenious norm is known to be sensitive to noise and prone to overfitting. In recent years, efforts have been made to solve the problem of robust and sparse modeling. Therefore, we describe the formulation of a CSP criterion by using the L21-norm and add the L21-norm regularization term. The regularized version of the L21-norm-based common spatial pattern is termed RCSP-L21 in this paper. An iterative algorithm is designed to obtain the spatial filters of the regularized objective function. Experimental results on EEG dataset IIa of BCI Competition IV verify the effectiveness of our new method. © 2021 IEEE.

关键词： Brain computer interface

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Sulfonic acid-functionalized core-shell Fe_(3)O_(4)@carbon microspheres as magnetically recyclable solid acid catalysts

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Chinese Chemical Letters 2021年第6期32卷 2079-2085页

作者： Chenyi Yuan Xiqing Wang Xuanyu Yang Abdulaziz AAlghamdi Fahad AAlharthi Xiaowei Cheng Yonghui Deng Department of Chemistry State Key Laboratory of Molecular Engineering of PolymersShanghai Key Laboratory of Molecular Catalysis and Innovative MaterialsFudan UniversityShanghai 200433China State Key Lab of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China Department of Chemistry College of ScienceKing Saud UniversityPO Box 2455Riyadh 11451Saudi Arabia

Green and recyclable solid acid catalysts are in urgent demand as a substitute for conventional liquid mineral *** this work,a series of novel sulfonic acid-functionalized core-shell Fe_(3)O_(4)@carbon microspheres(Fe_(3)O_(4)@C-SO_(3)H)have been designed and synthesized as an efficient and recyclable heterogeneous acid *** the synthesis,core-shell Fe_(3)O_(4)@RF(resorcinol-formaldehyde)microspheres with tunable shell thickness were achieved by interfacial polymerization on magnetic Fe_(3)O_(4)*** high-temperature carbonization,the microspheres were eventually treated by surface sulfonation,re sulting in Fe_(3)O_(4)@C-x-SO_(3)H(x stands for carbonization temperature)microspheres with abundant surface SO_(3)H *** obtained microspheres possess uniform core-shell structure,partially-graphitized carbon skeletons,superparamagnetic property,high magnetization saturation value of 10.6 emu/g,and rich SO_(3)H *** surface acid amounts can be adju sted in the range of 0.59-1.04 mmol/g via sulfonation treatment of carbon shells with different graphitization *** magnetic Fe_(3)O_(4)@C-x-SO_(3)H microspheres were utilized as a solid acid catalyst for the acetalization reaction between benzaldehyde and ethylene glycol,demonstrating high selectivity(97%)to benzaldehyde ethylene glycol *** importantly,by applying an external magnetic field,the catalysts can be easily separated from the heterogeneous reaction solutions,which later show well preserved catalytic activity even after 9 cycles,revealing good recyclability and high stability.

关键词： Core-shell Fe_(3)O_(4)@carbon Interfacial polymerization Magnetic microspheres Recyclability Solid acid catalyst Sulfonic acid-functionalization

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Towards Yo-Yo attack mitigation in cloud auto-scaling mechanism

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Digital Communications and Networks 2020年第3期6卷 369-376页

作者： Xiaoqiong Xu Jin Li Hongfang Yu Long Luo Xuetao Wei Gang Sun Key Lab of Optical Fiber Sensing and Communications(Ministry of Education) University of Electronic Science and Technology of ChinaChengdu611731China National Key Laboratory of Science and Technology on Information System Security Beijing100101China Center for Cyber Security University of Electronic Science and Technology of ChinaChengdu611731China University of Cincinnati CincinnatiOH45220USA

Cloud platforms could automatically scale underlying network resources up and down in response to changes in the traffic *** an auto-scaling mechanism can largely enhance the elasticity and scalability of cloud ***,it may introduce new security *** example,the Yo-Yo attack is a newly disclosed attack against the cloud auto-scaling *** periodically send bursts of traffic to cause the autoscaling mechanism to oscillate between the scale-up process and the scale-down process,which may result in significant performance degradation and economic *** of the prior work addressed the problem of mitigating such an *** this paper,we propose a Trust-based Adversarial Scanner Delaying(TASD)approach to effectively and proactively mitigate the Yo-Yo attack on the cloud auto-scaling *** TASD,we first propose to use the trust-based scheme to establish trust values for users,which is leveraged to identify adversarial *** values are updated by jointly considering the request mode and the auto-scaling ***,we aim to disable the condition under which the Yo-Yo attack takes effect by injecting certain delay,under the QoS constraints,to manipulate the response time of suspicious requests and deceive the *** extensive evaluation demonstrates that our approach achieves promising results,e.g.,it can detect at least 80%Yo-Yo adversarial users and reduce more than 41%malicious scale-ups.

关键词： Cloud computing Auto-scaling mechanism Yo-yo attack Attack detection Attack defense

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Early Stage Design of a mHealth Intervention for Managing Gestational Diabetes Mellitus in Bangladeshi Women 25th

Early Stage Design of a mHealth Intervention for Managing...

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25th International Conference on Human-Computer Interaction, HCII 2023

作者： Islam, Ashraful Ahmed, Eshtiak Islam, Md Rakibul EMPATHY Lab Center for Computational and Data Sciences Independent University Bangladesh Dhaka Bangladesh Department of Computer Science and Engineering Independent University Bangladesh Dhaka Bangladesh Faculty of Information Technology and Communication Sciences Tampere University Tampere Finland Computer Science Department University of Wisconsin - Eau Claire Eau ClaireWI United States

ISBN: (纸本)9783031492112

Gestational Diabetes Mellitus (GDM) is a rising concern worldwide, particularly in low-resource countries such as Bangladesh, where access to healthcare facilities is limited and awareness of GDM management is inadequate. This work proposes an early-stage design of user interfaces (UIs) for a mobile health (mHealth) intervention using the Bengali language that allows users to input daily measures of blood glucose, weight, and other GDM-related health data. The intervention is designed to provide users with personalized feedback based on their input and the necessary coaching for managing GDM. It also reminds users to take medication if prescribed by their doctors. The app has six key features: blood glucose tracking, food logging, medication reminders, activity tracking, educational resources, and personalized recommendations. Overall, this work provides a valuable contribution to the field of mHealth-based maternal and child health in Bangladesh. However, further research is necessary to evaluate the effectiveness and feasibility of the intervention in real-world scenarios. Such evaluations will provide valuable insights into its potential impact and help refine the design to better serve the needs of GDM patients in Bangladesh. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： mHealth

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Unlocking the Secrets Behind Advanced Artificial Intelligence Language Models in Deidentifying Chinese-English Mixed Clinical Text: Development and Validation Study

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Journal of Medical Internet Research 2024年第1期26卷 e48443页

作者： Lee, You-Qian Chen, Ching-Tai Chen, Chien-Chang Lee, Chung-Hong Chen, Peitsz Wu, Chi-Shin Dai, Hong-Jie Dialogue System Technical Department Asustek Computer Inc Taipei Taiwan Intelligent System Laboratory Department of Electrical Engineering College of Electrical Engineering and Computer Science National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung Taiwan Center for Precision Health Research Asia University Taichung Taiwan Electromagnetic Sensing Control and AI Computing System Laboratory Department of Electrical Engineering College of Electrical Engineering and Computer Science National Kaohsiung University of Science and Technology Kaohsiung Taiwan Knowledge Discovery and Data Mining Lab Department of Electrical Engineering College of Electrical Engineering and Computer Science National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Chemical Engineering Feng Chia University Taichung Taiwan National Center for Geriatrics and Welfare Research National Health Research Institutes Zhunan Taiwan National Institute of Cancer Research National Health Research Institutes Tainan Taiwan School of Post-Baccalaureate Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Center for Big Data Research Kaohsiung Medical University Kaohsiung Taiwan

Background: The widespread use of electronic health records in the clinical and biomedical fields makes the removal of protected health information (PHI) essential to maintain privacy. However, a significant portion of information is recorded in unstructured textual forms, posing a challenge for deidentification. In multilingual countries, medical records could be written in a mixture of more than one language, referred to as code mixing. Most current clinical natural language processing techniques are designed for monolingual text, and there is a need to address the deidentification of code-mixed text. Objective: The aim of this study was to investigate the effectiveness and underlying mechanism of fine-tuned pretrained language models (PLMs) in identifying PHI in the code-mixed context. Additionally, we aimed to evaluate the potential of prompting large language models (LLMs) for recognizing PHI in a zero-shot manner. Methods: We compiled the first clinical code-mixed deidentification data set consisting of text written in Chinese and English. We explored the effectiveness of fine-tuned PLMs for recognizing PHI in code-mixed content, with a focus on whether PLMs exploit naming regularity and mention coverage to achieve superior performance, by probing the developed models’ outputs to examine their decision-making process. Furthermore, we investigated the potential of prompt-based in-context learning of LLMs for recognizing PHI in code-mixed text. Results: The developed methods were evaluated on a code-mixed deidentification corpus of 1700 discharge summaries. We observed that different PHI types had preferences in their occurrences within the different types of language-mixed sentences, and PLMs could effectively recognize PHI by exploiting the learned name regularity. However, the models may exhibit suboptimal results when regularity is weak or mentions contain unknown words that the representations cannot generate well. We also found that the availability of cod

关键词： ChatGPT code mixing deidentification electronic health record large language model pretrained language model

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An Economic Scheduling Strategy of Photovoltaic Storage Micro-grid Considering Demand Response

An Economic Scheduling Strategy of Photovoltaic Storage Micr...

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IEEE Asia Power and Energy engineering Conference (APEEC)

作者： Rundong Liu Sen Zhang Yincheng Zhao Haojie Ma Luan Chen Weihao Hu Ming Tang Wei Zhan Qingjia Zhou Sichuan Provincial Key Lab of Power System Wide Area Measurement and Control School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China SPIC Sichuan Electric Power Co. LTD Chengdu China SPIC Southwest Energy Research Institute Chengdu China

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

To realize the economic optimization dispatch of PSMG (Photovoltaic Storage Micro-grid), considering the stochastic influence of multiple uncertainties, this study formulates a day-ahead optimal dispatching strategy of PSMG with the minimum comprehensive operating cost as the objective function. Firstly, the source-load uncertainty is dealt with by scenario generation using the Monte Carlo method and k-means clustering algorithm. Then the peak shaving ability of the system is enhanced by the introduction of flexible loads, and the scheduling flexibility of the photovoltaic storage system is increased by the integrated demand response increases the scheduling flexibility of the photovoltaic storage system. Finally, simulation results show that the scheduling scheme can prompt the source-load to participate in peak shaving and valley filling at the same time, increase the new energy consumption capacity of the photovoltaic storage micro-grid, and effectively improve the economic and social benefits of the micro-grid.

关键词： Photovoltaic systems Uncertainty Fluctuations Costs Monte Carlo methods Simulation Demand response

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