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Reachability deficit of variational Grover search

Physical Review A 2024年第1期109卷 012414-012414页

作者： Xiao-Wei Li Xiao-Ming Zhang Bin Cheng Man-Hong Yung Shenzhen Institute for Quantum Science and Engineering Southern University of Science and Technology Shenzhen 518055 China Department of Physics Southern University of Science and Technology Shenzhen 518055 China Center on Frontiers of Computing Studies Peking University Beijing 100871 China Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology Sydney New South Wales 2007 Australia Guangdong Provincial Key Laboratory of Quantum Science and Engineering Southern University of Science and Technology Shenzhen 518055 China Shenzhen Key Laboratory of Quantum Science and Engineering Southern University of Science and Technology Shenzhen 518055 China

The quantum approximate optimization algorithm (QAOA) is promising for achieving quantum computational advantage with near-term quantum devices. It was numerically shown that the QAOA cost functions exhibit a phenomenon called reachability deficit (RD), where the success probability cannot reach unity until the circuit depth exceeds a certain critical value. However, an in-depth theoretical understanding of RD remains lacking. Here we focus on a variational variant of Grover search on multiple marked solutions as a prototype for analyzing the RD problem, where we further relax the criterion of reachability by tolerating a certain probability of failure. Specifically, we obtain a general analytical expression relating the critical depth of the quantum circuit to the solution density. In the dilute limit, the critical depth is consistent with the Grover bound, exhibiting a robust quadratic scaling that is insensitive to the failure probability. Moreover, we also find that the projective mixing Hamiltonian performs significantly better than the traditional mixing Hamiltonian in the QAOA, although it is less favorable in terms of physical implementation. However, by taking into account two-body interactions in the mixing Hamiltonian, the performance becomes on par with the projective mixing Hamiltonian at the cost of O(n2) additional terms. These results represent a simplified but insightful model of the QAOA, fully addressing the dependence of required circuit depth over the ground-state degeneracy.

关键词： Quantum algorithms Search strategy

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SHM-NDN: A Seamless Hybrid Mobility Management Scheme For Named Data Mobile Ad Hoc Networks

SSRN

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SSRN 2023年

作者： Fayyaz, Sana Rehman, Muhammad Atif Ur Khalid, Waqas Kim, Byung Seo Department of Electronics & Computer Engineering Hongik University Sejong City30016 Korea Republic of Department of Computing Mathematics Manchester Metropolitan University ManchesterM15 6BH United Kingdom Institute of Industrial Technology Korea University Sejong30019 Korea Republic of Department of Software and Communications Engineering Hongik University Sejong City30016 Korea Republic of

Named Data Networking (NDN), a counterpart of address-centric networking resolves consumer mobility issues to some extent, however, it confronts excessive bandwidth consumption and network congestion problems in Mobile Adhoc Networks (MANET) due to an inefficient default request re-transmission mechanism. The producer mobility in NDN-based MANET, on the other hand, poses even worse challenges owing to the continuous flooding of location advertisement messages in the network. This paper aims to address the aforementioned producer and consumer mobility issues in MANET and proposes SHM-NDN, a seamless hybrid mobility management scheme for NDN-based MANETs. The proposed scheme features newpacket types and extends the functionality of wireless mobile FIB data structure to support efficient mobility management. Moreover, the SHM-NDN proposes a path recovery mechanism to deal with the network partitioning problem caused by a low signal-to-noise ratio and high congestion rate. An illustrative comparative evaluation validates the effectiveness of the proposed scheme. © 2023, The Authors. All rights reserved.

关键词： Mobile ad hoc networks

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A Glove CNN-Bilstm Sentiment Classification 18

A Glove CNN-Bilstm Sentiment Classification

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18th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2021

作者： Atandoh, Peter Feng, Zhang Adu-Gyamfi, Daniel Leka, Habte Lejebo Atandoh, Paul Hakeem University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu610054 China University of Technology and Applied Sciences School of Computing Information Sciences Department of Cyber Security and Computer Engineering CK Tedam Navrongo Ghana Western Michigan University Department of Statistics KalamazooMI49008-5278 United States

ISBN: (纸本)9781665413640

Reviewing products online has become an increasingly popular way for consumers to voice their opinions and feelings about a product or service. Analyzing this Big data of online reviews would help to discern and extract useful facts and information that could provide a competitive and economic advantage to merchants and other organizations that are interested. Text classification organizes documents according to a variety of predefined categories. In other to solve the aforementioned problems, we employed Glove embeddings for our review sentiment analysis. We further integrate this embedding layer into a deep convolutional neural network (CNN)-bidirectional LSTM model. We further train our model on the IMDB and movie review dataset to extract the polarity as positive or negative and subsequently compare our model with other state-of- the-art models. The aforementioned experiments validate the efficacy and superiority of our proposed approach. © 2021 IEEE.

关键词： Sentiment analysis

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A Secure Authentication Framework for Consumer Mobile Crowdsourcing Networks

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IEEE Transactions on Consumer Electronics 2024年

作者： Aldosary, Abdallah Tanveer, Muhammad Ahmad, Musheer Maghrabi, Louai A. Ahmed, Emad A. Hussain, Amir El-Latif, Ahmed A. Abd Department of Computer Engineering Prince Sattam bin Abdulaziz University Riyadh Wadi Addwasir11991 Saudi Arabia University of Management and Technology Department of Computer Science Lahore54770 Pakistan Jamia Millia Islamia Department of Computer Engineering New Delhi110025 India University of Business and Technology College of Engineering Department of Software Engineering Jeddah Saudi Arabia South Valley University Faculty of Computers and Information Department of Computer Science Qena Egypt Edinburgh Napier University United Kingdom Prince Sultan University EIAS Data Science Lab College of Computer and Information Sciences Center of Excellence in Quantum and Intelligent Computing Riyadh11586 Saudi Arabia Menoufia University Faculty of Science Department of Mathematics and Computer Science Shebin El-Koom32511 Egypt

The Mobile crowdsourcing network (MCN) leverages collaborative intelligence to solve complex tasks through group cooperation. It comprises three main components: the end-user, the service provider, and the mobile user. The end-user requests crowd-sensing and computing services from the service provider, who handles task decomposition, distribution, re-composition, and recommendation. Mobile users perform the crowd sensing and computing tasks. Despite its benefits, MCN faces significant security and privacy challenges. Communications between the service provider and the end-user involve sensitive data, and mobile users and service providers communicate over open channels, making them vulnerable to security threats. To address these concerns, we propose a secure authentication framework for MCN, called SAF-MCN. This framework combines the lightweight cryptographic primitive ' ASCON' with elliptic curve cryptography. SAF-MCN allows the service provider to authenticate mobile users before they join the MCN. Once authenticated, a secure channel is established for encrypted communication over the public Internet. The security of SAFMCN is validated using both formal and informal methods, demonstrating its resilience against potential attacks. The use of Scyther further ensures the security of SAF-MCN. Comparative analysis shows that SAF-MCN is superior in terms of security features, computational efficiency, and communication cost. © 1975-2011 IEEE.

关键词： ASCON Authenticated Encryption Authentication Mobile Crowdsourcing Network Scyther Security

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Fundus Image Translation with Scale-Aware Registration and Gradient-Guided GAN

SSRN

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SSRN 2024年

作者： Kim, JuChan Le, Duc-Tai Bum, Junghyun Son, Chang-Hwan Lee, Eun Jung Han, Jong Chul Choo, Hyunseung Department of Artificial Intelligence Systems Engineering Sungkyunkwan University Korea Republic of College of Computing and Informatics Sungkyunkwan University Korea Republic of Sungkyun AI Research Institute Sungkyunkwan University Korea Republic of Software Science and Engineering Major Kunsan National University Korea Republic of Department of Ophthalmology Samsung Medical Center Korea Republic of School of Medicine Sungkyunkwan University Korea Republic of Department of Medical Device Management and Research SAIHST Sungkyunkwan University Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

Two major fundus imaging types, conventional fundus (CF) imaging and ultrawidefield fundus (UF) imaging, are widely used in ophthalmology. In a typical clinical setting, both imaging methods are used simultaneously to diagnose diseases depending on the case. This study introduced an enhanced method of modality transformation to boost the diagnostic support capabilities of deep-learning models in ophthalmology. The method proposed in this study to translate UF images (UFIs) to CF images (CFIs) can replace the common clinical approach of both imaging methods, thereby reducing financial and temporal burdens on patients. This study learns and transforms the relationship between these modalities using UFI–CFI image pairs obtained from the same patient on the same day to minimize distorted information and accurately convert between different modalities. Our proposed model uses scale-aware registration and gradient-guided translation methods to align the UFI–CFI pairs, The generated CFIs not only enhance the quality of images and better represent the retinal area compared to existing methods but also effectively preserve the disease-related details in UFIs, aiding in the diagnosis. In addition, we optimize the image transformation performance, resulting in an 22% improvement in image quality assessment scales compared with previous methods. Furthermore, we acquired the observation that our results are nearly impossible to discern any differences between the real CFIs and the generated CFIs in the view of ophthalmologists. © 2024, The Authors. All rights reserved.

关键词： Ophthalmology

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Countering Eavesdroppers with Meta-learning-based Cooperative Ambient Backscatter Communications

arXiv

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arXiv 2023年

作者： Chu, Nam H. Van Huynh, Nguyen Nguyen, Diep N. Hoang, Dinh Thai Gong, Shimin Shu, Tao Dutkiewicz, Eryk Phan, Khoa T. School of Electrical and Data Engineering University of Technology Sydney Australia School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh United Kingdom School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou China Department of Computer Science and Software Engineering Auburn University AuburnAL36849 United States School of Engineering and Mathematical Sciences Department of Computer Science and Information Technology La Trobe University Melbourne Australia

This article introduces a novel lightweight framework using ambient backscattering communications to counter eavesdroppers. In particular, our framework divides an original message into two parts. The first part, i.e., the active-transmit message, is transmitted by the transmitter using conventional RF signals. Simultaneously, the second part, i.e., the backscatter message, is transmitted by an ambient backscatter tag that backscatters upon the active signals emitted by the transmitter. Notably, the backscatter tag does not generate its own signal, making it difficult for an eavesdropper to detect the backscattered signals unless they have prior knowledge of the system. Here, we assume that without decoding/knowing the backscatter message, the eavesdropper is unable to decode the original message. Even in scenarios where the eavesdropper can capture both messages, reconstructing the original message is a complex task without understanding the intricacies of the message-splitting mechanism. A challenge in our proposed framework is to effectively decode the backscattered signals at the receiver, often accomplished using the maximum likelihood (MLK) approach. However, such a method may require a complex mathematical model together with perfect channel state information (CSI). To address this issue, we develop a novel deep meta-learning-based signal detector that can not only effectively decode the weak backscattered signals without requiring perfect CSI but also quickly adapt to a new wireless environment with very little knowledge. Simulation results show that our proposed learning approach, without requiring perfect CSI and complex mathematical model, can achieve a bit error ratio close to that of the MLK-based approach. They also clearly show the efficiency of the proposed approach in dealing with eavesdropping attacks and the lack of training data for deep learning models in practical scenarios. Copyright © 2023, The Authors. All rights reserved.

关键词： Backscattering

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Managing Service Dependency for Cloud Reliability: The Industrial Practice

Managing Service Dependency for Cloud Reliability: The Indus...

引用

IEEE International Conference on software Reliability engineering Workshops (ISSRE Wksp)

作者： Tianyi Yang Baitong Li Jiacheng Shen Yuxin Su Yongqiang Yang Michael R. Lyu Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong SAR School of Software Engineering Sun Yat-Sen Univeristy Zhuhai China Computing and Networking Innovation Lab Huawei Cloud Shenzhen China

ISBN: (数字)9781665476799

ISBN: (纸本)9781665476805

Interactions between cloud services result in service dependencies. Evaluating and managing the cascading impacts caused by service dependencies is critical to the reliability of cloud systems. This paper summarizes the dependency types in cloud systems and demonstrates the design of the Dependency Management System (DMS), a platform for managing the service dependencies in the production cloud system. DMS features full-lifecycle support for service reliability (i.e., initial service deployment, service upgrade, proactive architectural optimization, and reactive failure mitigation) and refined characterization of the intensity of dependencies.

关键词： Conferences Production Reliability engineering software reliability Optimization

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An Efficient DeFi-based Data Warehousing Approach in Supply Chain Finance 2021

An Efficient DeFi-based Data Warehousing Approach in Supply ...

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The 5th International Conference on Future Networks & Distributed Systems

作者： Elnaz Rabieinejad Abbas Yazdinejad Tahereh Hasani Reza M. Parizi Mohammad Hammoudeh Cyber Science Lab School of Computer Science University of Guelph Canada Lang School of Business and Economics University of Guelph Canada College of Computing and Software Engineering Kennesaw State University USA Department of Computing and Mathematics Manchester Metropolitan University United Kingdom

ISBN: (纸本)9781450387347

In today’s world, industries are looking to improve their productivity through effective logistics and supply chain management. The efficiency of the supply chain in dealing with the huge volumes of data plays a key role in the overall performance of businesses. Supply Chain Finance (SCF) aims to improve the robustness and efficiency of companies’ supply lines. However, SCF suffers from problems like fraudulent transactions, information inconsistencies, and delays in financial transfers. Decentralized finance (Defi) is a new blockchain paradigm that tackles traditional finance problems. This paper proposes a Defi-based model on a hybrid private-public blockchain for SCF. Our model improves the efficiency of SCF by eliminating costs of using centralized financial institutions, reducing overload costs due to better estimation of the required amount of products, and also decreasing supply delays for the requested products. We also evaluated our model using the SWOT technique for adopting it in the supply chain.

关键词： Supply chain finance Blockchain DeFi Smart contract Supply chain efficiency

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Dual-View Interaction-Aware Lane Change Prediction for Autonomous Driving 39

Dual-View Interaction-Aware Lane Change Prediction for Auton...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Lu, Yuhuan Zhang, Zhen Bai, Rufan Liu, Han Wang, Wei Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen MSU-BIT University China Department of Computer and Information Science University of Macau China Department of Computer Science and Engineering Southeast University China School of Software Dalian University of Technology China School of Medical Technology Beijing Institute of Technology China

ISBN: (纸本)157735897X

As artificial intelligence techniques evolve, we are approaching a critical moment for the widespread deployment of autonomous vehicles. Subsequently, the emergence of mixed-autonomy traffic environments presents formidable challenges to autonomous vehicles, especially for the accurate prediction of lane change intentions of their surrounding human-driven vehicles, which is crucial for ensuring the safety of autonomous vehicles. Existing lane change prediction models mainly focus on capturing the temporal variations in the movement dynamics of individual vehicles. However, the neglect to consider inter-vehicle interactions hinders their capability in complex lane change scenarios, resulting in suboptimal prediction performance. Moreover, current interaction-aware approaches for autonomous driving fail to explicitly model future interactions between vehicles, leading to unreasonable prediction results that can cause collisions between vehicles. To address the above issues, we propose to incorporate the concept of perceived safety into future interaction modeling and design a dual-view interaction-aware lane change prediction model. We evaluate the proposed model on two real-world datasets and experimental results show that the proposed model achieves average improvements of 11.7-12.4% in classification ability and 75.6-95.7% in forecast ability over the best-performing baselines across the two datasets. The ablation study and investigation into future interaction modeling demonstrate that our model has advantages in interpreting lane change scenarios from a driving safety perspective. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Characterizing and Mitigating Anti-patterns of Alerts in Industrial Cloud Systems

arXiv

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arXiv 2022年

作者： Yang, Tianyi Shen, Jiacheng Su, Yuxin Ren, Xiaoxue Yang, Yongqiang Lyu, Michael R. Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong School of Software Engineering Sun Yat-Sen Univeristy Zhuhai China Computing and Networking Innovation Lab Cloud BU Shenzhen Huawei China

Alerts are crucial for requesting prompt human intervention upon cloud anomalies. The quality of alerts significantly affects the cloud reliability and the cloud provider's business revenue. In practice, we observe on-call engineers being hindered from quickly locating and fixing faulty cloud services because of the vast existence of misleading, non-informative, non-actionable alerts. We call the ineffectiveness of alerts "anti-patterns of alerts". To better understand the anti-patterns of alerts and provide actionable measures to mitigate anti-patterns, in this paper, we conduct the first empirical study on the practices of mitigating anti-patterns of alerts in an industrial cloud system. We study the alert strategies and the alert processing procedure at Huawei Cloud, a leading cloud provider. Our study combines the quantitative analysis of millions of alerts in two years and a survey with eighteen experienced engineers. As a result, we summarized four individual anti-patterns and two collective anti-patterns of alerts. We also summarize four current reactions to mitigate the anti-patterns of alerts, and the general preventative guidelines for the configuration of alert strategy. Lastly, we propose to explore the automatic evaluation of the Quality of Alerts (QoA), including the indicativeness, precision, and handleability of alerts, as a future research direction that assists in the automatic detection of alerts' anti-patterns. The findings of our study are valuable for optimizing cloud monitoring systems and improving the reliability of cloud services. © 2022, CC BY.

关键词： Web services

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