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Optical Microsphere Nano-Imaging:Progress and Challenges

engineering 2024年第5期36卷 102-123页

作者： Guangxing Wu Minghui Hong Department of Electrical and Computer Engineering National University of SingaporeSingapore 117576Singapore Pen-Tung Sah Institute of Micro-Nano Science and Technology Xiamen UniversityXiamen 361005China Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province(IKKEM) Xiamen 361005China

The optical diffraction effect imposes a radical obstacle preventing conventional optical microscopes from achieving an imaging resolution beyond the Abbe diffraction limit and thereby restricting their usage in a multitude of nanoscale *** the past decade,the optical microsphere nanoimaging technique has been demonstrated to be a cost-effective solution for overcoming the diffraction limit and has achieved an imaging resolution of up to about k6k8 in a real-time and label-free manner,making it highly competitive among numerous super-resolution imaging *** this review,we summarize the underlying nano-imaging mechanisms of the microsphere nanoscope and key advancements aimed at imaging performance enhancement:first,to change the working environment or modify the peripheral hardware of a single microsphere nanoscope at the system level;second,to compose the microsphere compound lens;and third,to engineer the geometry or ingredients of *** also analyze challenges yet to be overcome in optical microsphere nano-imaging,followed by an outlook of this technique.

关键词： Microsphere Nano-imaging Virtual imaging Microsphere compound lens Engineered microsphere

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Competition on robust deep learning

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National Science Review 2023年第6期10卷 13-15页

作者： Yinpeng Dong Chang Liu Wenzhao Xiang Hang Su Jun Zhu Department of Computer Science and Technology Institute for AI Tsinghua-Bosch Joint ML Center THBI Lab BNRist Center Tsinghua University Institute of Image Communication and Networks Engineering in the Department of Electronic Engineering (EE) Shanghai Jiao Tong University Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Peng Cheng Laboratory Pazhou Laboratory (Huangpu)

PROBLEM In recent years,the rapid development of artificial intelligence (AI) technology,especially machine learning and deep learning, is profoundly changing human production and *** various fields,such as robotics,face recognition,autonomous driving and healthcare,AI is playing an important ***,although AI is promoting the technological revolution and industrial progress,its security risks are often *** studies have found that the wellperforming deep learning models are extremely vulnerable to adversarial examples [1-3].The adversarial examples are crafted by applying small,humanimperceptible perturbations to natural examples,but can mislead deep learning models to make wrong *** vulnerability of deep learning models to adversarial examples can raise security and safety threats to various realworld applications.

关键词： robustness adversarial example adversarial training deep learning

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Survey on Cryptoprocessors Advances and Technological Trends 3rd

Survey on Cryptoprocessors Advances and Technological Tren...

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3rd International Conference on Innovations in Computing Research, ICR 2024

作者： Kakoulli, Elena Zacharioudakis, Eleftherios Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos Paphos Cyprus Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine

ISBN: (纸本)9783031655210

Cryptoprocessors play a pivotal role in enhancing the security of modern computing systems by accelerating cryptographic operations and fortifying data protection. This survey delves into the world of cryptoprocessors, encompassing their historical development, architectural features, and various types based on their applications. The paper explores the crucial security considerations surrounding cryptoprocessors, covering both physical and logical aspects, as well as potential threats and countermeasures. Furthermore, the survey navigates through the latest technological trends and advancements in cryptoprocessor design. This includes discussions on post-quantum cryptography, secure enclaves, and mitigating side-channel attacks, all of which are shaping the future of cryptoprocessors. Real-world use cases and applications in domains such as secure communications, the Internet of Things (IoT), and data centers are presented, showcasing the practical significance of cryptoprocessors. However, the paper also highlights the persistent challenges faced by cryptoprocessor designers and provides insights into future research directions aimed at addressing emerging security and performance issues. As the digital landscape continues to evolve, the role of cryptoprocessors becomes increasingly vital in safeguarding sensitive information and fortifying the foundations of cybersecurity. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Internet of things

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An Efficient Attack Detection Framework in Software-Defined Networking using Intelligent Techniques 3

An Efficient Attack Detection Framework in Software-Defined ...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： Hassan, Heba A. El-Din Hemdan, Ezz Shokair, Mona El-Samie, Fathi E. Abd El-Shafai, Walid Menoufia University Faculty of Electronic Engineering Department of Computer Science and Engineering Menouf32952 Egypt Menoufia University Faculty of Electronic Engineering Department of Electronics and Communication Engineering Menouf32952 Egypt Prince Sultan University Security Engineering Laboratory Department of Computer Science Riyadh11586 Saudi Arabia

ISBN: (纸本)9798350323511

Recently, Software-Defined Networking (SDN) architecture has offered great benefits due to the separation between the control and network elements such as routers and switches. Unfortunately, the enormous growth of attacks hinders the wide adoption of SDN. Intrusion Detection Systems (IDSs) are used as significant tools to detect and mitigate network attacks of anomalous nature. Several Deep Learning (DL) models, such as Convolutional Neural Networks (CNNs), have been utilized for building IDSs in cyber security in recent years, because they achieve the desired detection results. Nonetheless, little work has been introduced on IDSs in SDN systems. Hence, this paper presents an efficient framework based on intelligent techniques for predicting attacks in SDN systems. This work focuses on the early detection of abnormal attacks existing in an SDN environment. When malicious traffic is identified in an SDN topology, the Artificial Intelligence (AI) module employs Machine Learning (ML) or DL models to identify and stop the attack source. The architecture presented in this research allows for comparing several ML and DL classification techniques that can be used to identify different sorts of network attacks. The proposed framework is tested on the InSDN dataset using several learning models like Random Forest (RF), AdaBoost (AB), K-Nearest Neighbor (KNN), Naïve Bayes (NB), Decision Tree (DT), and Logistic Regression (LR) classifiers. In addition, DL models such as Deep CNN and Long Short Term Memory (LSTM) are considered. The results demonstrate that the proposed Deep CNN model for multi-class attack data classification achieves the highest accuracy of 99.85% compared to RF, AB, KNN, NB, DT, LR, and LSTM classifiers with accuracy levels of 95%, 88 %, 97%, 93 %, 90 %, 98%, and 88.31 %, respectively. © 2023 IEEE.

关键词： Software defined networking

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Adapting the Simulated Annealing Algorithm to Enhance the Performance of the LEACH Protocol

Adapting the Simulated Annealing Algorithm to Enhance the Pe...

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2024 International Conference on computer and Applications, ICCA 2024

作者： Benhadji, Mohammed Mohammed, Kaddi Mohammed, Omari Material Sciences Department Algeria University of Adrar Lddi Laboratory Mathematics and Computer Science Department Algeria American University of Ras Al Khaimah Computer Science and Engineering Department P.O.Box 10021 Ras Al Khaimah United Arab Emirates

ISBN: (纸本)9798350367560

In parallel with the proliferation and extension of wireless sensor networks (WSNs), as well as the diversity of their applications, such networks continue to fail to operate for lengthy periods of time due to node failure and the inability to replace sensor batteries in most circumstances. This hinders the networks' ability to remain operational over extended periods. That necessitates making the best and most efficient use of the nodes' energy. Hierarchical clustering methods augmented with metaphysical algorithms have produced amazing benefits in terms of network longevity. One of the most significant of these algorithms that draws inspiration from nature and yields excellent results is the simulated annealing technique. In this research, we report on our analysis of this method and how it performs best when used to optimize routing in WSN. © 2024 IEEE.

关键词： Simulated annealing

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Stable Stochastic MPC for Uncertain Wind Energy Conversion System Over Whole Operating Regions

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IEEE Transactions on Energy Conversion 2025年第1期40卷 515-528页

作者： Liu, Xiangjie Guo, Shifan Ma, Lele Kong, Xiaobing Lee, Kwang Y. North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China Baylor University Department of Electrical and Computer Engineering WacoTX76798-7356 United States

The stochastic uncertainty of wind speed presents a great challenge for achieving reliable power control in wind energy conversion system (WECS). Due to the excellence in handling the uncertainties based on probabilistic descriptions, stochastic model predictive control (SMPC) has been regarded as a promising strategy for WECS. However, owing to fluctuation characteristic of wind speed, operating points commonly change in WECS. Thus, an important limitation of applying SMPC to WECS stems from the fact that feasibility and stability of the traditional SMPC can only be ensured at one single predesigned operating point. Regarding this issue, a stable SMPC strategy for uncertain WECS is proposed in this paper to ensure the feasibility and stability of WECS under changing operating points over the whole operating regions. A Luenberger observer is employed to estimate model-plant mismatch introduced by linearization process, while a tube-based control framework is deployed to cope with stochastic wind speed disturbance. The feasibility of SMPC is ensured by incorporating artificial steady targets as optimization variables, while the stability of WECS is guaranteed by modifying the cost function and extending the terminal constraint. The effectiveness of the proposed strategy is validated through simulations and experiments under different scenarios. © 1986-2012 IEEE.

关键词： Stochastic systems

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Design of Generalized Frequency Domain Exponential Filters 6

Design of Generalized Frequency Domain Exponential Filters

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6th IEEE Novel Intelligent and Leading Emerging Sciences Conference, NILES 2024

作者： Nako, Julia Tsirimokou, Georgia Psychalinos, Costas Elwakil, Ahmed S. University of Patras Electronics Laboratory Physics Department Rio Patras Greece University of Ioannina Department of Computer Science and Engineering Ioannina Greece University of Sharjah Department of Electrical Engineering Sharjah United Arab Emirates

ISBN: (纸本)9798350378511

A general topology capable of implementing integer and non-integer versions of filters with exponential form of their gain responses in the frequency domain, is introduced in this work. The derivation of the topology is performed by employing a curve-fitting method for approximating the gain response, in each case. The versatility of the presented scheme is confirmed through experimental results obtained using a Field Programmable Analog Array device. A practical design example is also provided, where a combination of the introduced stages is utilized for denoising an electrocardiogram signal. © 2024 IEEE.

关键词： Topology

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Deep CNN Model for Multimodal Medical Image Denoising

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computers, Materials & Continua 2022年第11期73卷 3795-3814页

作者： Walid El-Shafai Amira A.Mahmoud Anas M.Ali El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

In the literature,numerous techniques have been employed to decrease noise in medical image modalities,including X-Ray(XR),Ultrasonic(Us),Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and Positron Emission Tomography(PET).These techniques are organized into two main classes:the Multiple Image(MI)and the Single Image(SI)*** the MI techniques,images usually obtained for the same area scanned from different points of view are used.A single image is used in the entire procedure in the SI *** denoising techniques can be carried out both in a transform or spatial *** paper is concerned with single-image noise reduction techniques because we deal with single medical *** most well-known spatial domain noise reduction techniques,including Gaussian filter,Kuan filter,Frost filter,Lee filter,Gabor filter,Median filter,Homomorphic filter,Speckle reducing anisotropic diffusion(SRAD),Nonlocal-Means(NL-Means),and Total Variation(TV),are ***,the transform domain noise reduction techniques,including wavelet-based and Curvelet-based techniques,and some hybridization techniques are ***,a deep(Convolutional Neural Network)CNN-based denoising model is proposed to eliminate Gaussian and Speckle noises in different medical image *** model utilizes the Batch Normalization(BN)and the ReLU as a basic *** a result,it attained a considerable improvement over the traditional *** previously mentioned techniques are evaluated and compared by calculating qualitative visual inspection and quantitative parameters like Peak Signal-to-Noise Ratio(PSNR),Correlation Coefficient(Cr),and system complexity to determine the optimum denoising algorithm to be applied *** on the quality metrics,it is demonstrated that the proposed deep CNN-based denoising model is efficient and has superior denoising performance over the traditionaldenoising techniques.

关键词： Image enhancement medical imaging speckle noise Gaussian noise denoising filters CNN denoising

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Opinions Are Not Always Positive: Debiasing Opinion Summarization With Model-Specific and Model-Agnostic Methods 30

Opinions Are Not Always Positive: Debiasing Opinion Summariz...

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Zhang, Yanyue Lai, Yilong Wang, Zhenglin Li, Pengfei Zhou, Deyu He, Yulan School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China Department of Informatics King's College London United Kingdom The Alan Turing Institute United Kingdom

ISBN: (纸本)9782493814104

As in the existing opinion summary data set, more than 70% are positive texts, the current opinion summarization approaches are reluctant to generate the negative opinion summary given the input of negative opinions. To address such sentiment bias, two approaches are proposed through two perspectives: model-specific and model-agnostic. For the model-specific approach, a variational autoencoder is proposed to disentangle the input representation into sentiment-relevant and sentiment-irrelevant components through adversarial loss. Therefore, the sentiment information in the input is kept and employed for the following decoding which avoids interference of content information with emotional signals. To further avoid relying on some specific opinion summarization frameworks, a model-agnostic approach based on counterfactual data augmentation is proposed. A dataset with a more balanced emotional polarity distribution is constructed using a large pre-trained language model based on some pairwise and mini-edited principles. Experimental results show that the sentiment consistency of the generated summaries is significantly improved using the proposed approaches, while their semantics quality is unaffected. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Semantics

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Grid Services Demonstration Using Service-Oriented DERMS

Grid Services Demonstration Using Service-Oriented DERMS

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2025 IEEE PES Grid Edge Technologies Conference and Exposition, Grid Edge 2025

作者： Adham, Midrar Keene, Sean J. Slay, Tylor Kolln, Jaime T. Bass, Robert B. Portland State University Department of Electrical & Computer Engineering PortlandOR97201 United States Pacific Northwest National Laboratory RichlandWA99354 United States

ISBN: (纸本)9798350352528

This work demonstrates four grid service use cases using a service-oriented DER Management System within an Energy Grid of Things network. Imposed by a set of rules referred to as the Energy Service Interface, the DER Management System uses IEEE 2030.5 as its primary communication protocol. To simulate the efforts of Grid Operators, Grid Service Providers, and consumers to provide grid services, a co-simulation environment that leverages the GridAPPS-D simulation platform was developed. The results show that a service-oriented DER Management System provides a means of achieving reliable and impactful grid services while protecting customers' privacy and ensuring their agency over their Distributed Energy Resources. © 2025 IEEE.

关键词： DER DERMS Energy Service Interface Grid Services GridAPPS-D

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