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29th International Conference on Neural information processing

作者： Zhang, Zepeng Liu, Fenghui Qi, Lin Tie, Yun Zhengzhou Univ Sch Elect & Informat Engn Zhengzhou Peoples R China Zhengzhou Univ Dept Resp & Sleep Med Affiliated Hosp 1 Zhengzhou Peoples R China

ISBN: (纸本)9783031301100;9783031301117

Improving the accuracy of early diagnosis is the key to prolong the survival of lung cancer. Lung Nodule Detection algorithms based on Deep Learning have made significant contributions to improving the accuracy. However, it remains a challenge to reduce the False Positive rate while maintaining high sensitivity. In this paper, we propose a novel MLP-based False Positive Reduction network, Wave-Involution MLP. We design a progressive multi-scale fusion block based on the novel operator Involution to fuse global features preferably. Moreover, inspired by quantum theory, we design a CT-WaveMLP feature extraction backbone, which transforms CT images into wave functions and enhances feature extraction capability. We performed experiments on LUNAV2 dataset, and the results show that our network achieves the average CPM of 0.861, which has a better performance compared with mainstream methods.

关键词： Involution MLP 3D CT Wave function False Positive Reduction Lung Nodule Detection

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Color optical computing: visualization, numbers, alphabet 12

Color optical computing: visualization, numbers, alphabet

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12th International Scientific and Practical Conference "information Control Systems and Technologies", ICST 2024

作者： Timchenko, Victor Kreinovich, Vladik Kondratenko, Yuriy Admiral Makarov National University of Shipbuilding av. Geroev of Ukraine 9 Mykolaiv054025 Ukraine University of Texas at El Paso 550 W University El PasoTX79968 United States Petro Mohyla Black Sea National University 10 68th Desantnykiv Str. Mykolaiv054003 Ukraine Institute of Artificial Intelligence Problems of MES and NAS of Ukraine Kyiv01001 Ukraine

The article is devoted to the development of methods and architecture of optical color computing, techniques of transforming color information for textual representation and numerical calculation, including transmission by optical channels, and thus expanding the functionality of a promising approach to creating artificial intelligence components in decision support systems. This approach is based on the representation of fuzzy information as an information quantum of visible light of a certain color and the construction of an architecture of logical operations based on the additive and subtractive transformation of light radiation using color filters. The paper presents the principles of forming fuzzy input and output color information, algorithms for hybrid calculations with the transformation of optical data into numerical calculus, methods for converting text messages into color information and, further, into numerical encoding. Components of the optical architecture are presented that allow the implementation of transformation algorithms with high computation speed and wide possibilities for constructing parallel structures. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Optical data processing

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Edge Computing Devices Authentication using quantum Computing 15

Edge Computing Devices Authentication using Quantum Computin...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Telsang, Vinayak A. Kakkasageri, Mahabaleshwar S. Devangavi, Anil D. Dept. of Computer Science and Engineering Biluru Gurubasava Mahaswamiji Institute of Technology Mudhol India Dept. Electronics and Communication Engineering Basaveshwar Engineering College Bagalkote India Dept. of Artificial Intelligence and Machine Learning Basaveshwar Engineering College Bagalkote India

ISBN: (纸本)9798350370249

Edge computing allows different technologies such as Internet of Things (IoT), vehicle-to-vehicle communications(VV), Industrial IOT (IIOT) to connect to the cloud computing to facilitate end users. The edge networks uses low bandwidth, and enhances the processing speed. With more number of IoT devices connected in the network the privacy of data stored at the edge server also under threat. Authentication is a major challenge which is be addressed to provide security and privacy to IoT devices connected in the network. The existing works uses cryptographic algorithms to solve the authentication problems, but with increase in growth of quantum computers and quantum computing, breaking the complex cryptographic algorithm is not an issue. Hence one should adopt the quantum approach to provide authentication in edge network. The proposed work uses quantum key and context information of IoT devices to store in the edge server using blockchain, which proves to be more secure. The performance analysis shows that it is better with respect to registration, encryption, decryption and authentication of IoT devices. ©2024 IEEE.

关键词： Authentication Blockchain Cryptography Edge computing quantum key

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A quantum blockchain-enabled framework for secure private electronic medical records in Internet of Medical Things

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information SCIENCES 2022年 612卷 942-958页

作者： Qu, Zhiguo Zhang, Zhexi Zheng, Min Nanjing Univ Informat Sci & Technol Engn Res Ctr Digital Forens Minist Educ Nanjing Peoples R China Hubei Univ Sci & Technol Xianning Peoples R China Beijing Univ Posts & Telecommun State key Lab Networking & Switching Technol Beijing 100876 Peoples R China Nanjing Univ Informat Sci & Technol Sch Comp Sci Nanjing Peoples R China Nanjing Univ Informat Sci & Technol Jiangsu Collaborat Innovat Ctr Atmospher Environm Nanjing Peoples R China

There is a rising need for healthcare as a result of rising public awareness of health issues. Electronic medical records include extremely confidential and sensitive information, and blockchain technology can enable the safe exchange of these records across various med-ical organizations. The current blockchain system is susceptible to quantum computer attacks, nevertheless, as a result of the advent of quantum computers. This research designs a novel distributed quantum electronic medical record system and suggests a new private quantum blockchain network based on security considerations. The blocks in this quantum blockchain's data structure are linked via entangled states. The time stamp is automatically formed by connecting quantum blocks with controlled activities, which lowers the amount of storage space needed. Each block's hash value is recorded using just one qubit. The quantum information processing is detailed in depth in the quantum elec-tronic medical record protocol. Every medical record can be tracked, and the security and privacy of electronic medical records in Internet of Medical Things systems can be guaran-teed. The protocol also ditches the traditional encryption and digital signature algorithms in favor of a quantum authentication system. According to the mathematical analysis, the quantum blockchain network has strong security against attacks from quantum computers since it can withstand External attack, Intercept-Measure-Repeat attack and Entanglement-Measure attack. The quantum circuit diagram for deriving the hash value is provided, along with the correctness and traceability analysis of the quantum block. The comparison between the proposed quantum blockchain model and a few other quan-tum blockchain models is also included.(c) 2022 Elsevier Inc. All rights reserved.

关键词： Blockchain Electronic medical records quantum cryptography Internet of Medical Things Distributed database

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Blind Nonlinearity Equalization by Machine-Learning-Based Clustering for QAM-Based quantum Noise Stream Cipher Transmission

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China Communications 2022年第8期19卷 127-137页

作者： Yajie Li Shoudong Liu Yongli Zhao Chao Lei Jie Zhang State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijing 100876China

In quantum noise stream cipher(QNSC)systems,it is difficult to compensate fiber nonlinearity by digital signal processing(DSP)due to interactions between chromatic dispersion(CD),amplified spontaneous emission(ASE)noise from erbiumdoped fiber amplifier(EDFA)and Kerr *** equalizer(NLE)based on machine learning(ML)algorithms have been extensively ***,most NLE based on supervised ML algorithms have high training overhead and computation *** addition,the performance of these algorithms have a lot of *** paper proposes two clustering algorithms based on Fuzzylogic C-Means Clustering(FLC)to compensate the fiber nonlinearity in quadrature amplitude modulation(QAM)-based QNSC system,including FLC based on subtractive clustering(SC)and annealing evolution(AE)*** performance of FLC-SC and FLC-AE are evaluated through simulation and *** proposed algorithms can promptly obtain suitable initial centroids and choose optimal initial centroids of the clusters to achieve the global optimal initial centroids especially for high order modulation *** the simulation,different parameter configurations are considered,including fiber length,optical signal-to-noise ratio(OSNR),clipping ratio and resolution of digital to analog converter(DAC).Further-more,we measure the Q-factor of transmission signal with different launched powers,DAC resolution and laser linewidth in the optical back-to-back(BTB)experiment with 80-km single mode *** simulation and experimental results show that the proposed techniques can greatly mitigate the signal impairments.

关键词： fiber nonlinear optics machine learning optical fiber communication unsupervised learning

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Improved BV-based quantum attack on block ciphers

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quantum information processing 2022年第1期22卷 1-22页

作者： Sun, Hong-Wei Wei, Chun-Yan Cai, Bin-Bin Qin, Su-Juan Wen, Qiao-Yan Gao, Fei Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Henan Key Lab Network Cryptog Technol Zhengzhou 450001 Henan Peoples R China Luoyang Normal Univ Sch Math Sci Luoyang 471934 Peoples R China

Due to the powerful computing capability of quantum computers, cryptographic researchers have applied quantum algorithms to cryptanalysis and obtained many interesting results. Finding the linear structure of a vector function is an important task in cryptography. In this work, we study how to reduce the complexity of finding linear structure using the Bernstein-Vazirani (BV) algorithm and give a new quantum linear structure finding algorithm with complexity O(n). Our result realizes a quadratic speedup compared with the previous algorithm (with complexity O(n(2))). This leads to a more efficient analysis of symmetric cryptography, that is, the complexity of some previous BV-based attacks reduces from O(n(2)) to O(n). Besides, we find two new applications for this kind of BV-based attack, i.e., related-key attacks on iterated Even-Mansour ciphers and i-round Feistel ciphers with independent round keys.

关键词： quantum cryptanalysis quantum superposition attacks Related-key attack Block ciphers

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Implementing multi-controlled X gates using the quantum Fourier transform

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quantum information processing 2024年第9期23卷 305-305页

作者： Arsoski, Vladimir V. Univ Belgrade Sch Elect Engn Dept Microelect & Tech Phys POB 35-54Bulevar kralja Aleksandra 73 Belgrade Serbia

quantum computing has the potential to solve many complex algorithms in the domains of optimization, arithmetics, structural search, financial risk analysis, machine learning, image processing, and others. quantum circuits built to implement these algorithms usually require multi-controlled gates as fundamental building blocks, where the multi-controlled Toffoli stands out as the primary example. For implementation in quantum hardware, these gates should be decomposed into many elementary gates, which results in a large depth of the final quantum circuit. However, even moderately deep quantum circuits have low fidelity due to decoherence effects and, thus, may return an almost perfectly uniform distribution of the output results. This paper proposes a different approach for efficient cost multi-controlled gates implementation using the quantum Fourier transform. We show how the depth of the circuit can be significantly reduced using only a few ancilla qubits, making our approach viable for application to noisy intermediate-scale quantum computers. This quantum arithmetic-based approach can be efficiently used to implement many complex quantum gates.

关键词： quantum computing quantum algorithms Multi-controlled gates quantum Fourier transform Ancilla qubits

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QGFORMER: quantum-Classical Hybrid Transformer Architecture for Gravitational Wave Detection 20

QGFORMER: Quantum-Classical Hybrid Transformer Architecture ...

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20th International Computer Conference on Wavelet Active Media Technology and information processing, ICCWAMTIP 2023

作者： Jiaxiang, Hu Jiale, Liu Glasgow College University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9798350318982

Gravitational Wave (GW) detection is a pivotal field in astrophysics, gaining prominence for its role in deciphering cosmic phenomena. Traditional machine learning algorithms in GW detection, while effective, grapple with challenges in parallelism, scalability, efficiency in handling high-dimensional data and noise interference. To mitigate these limitations, this paper proposes the quantum-Gravitational Transformer (QGFormer), a novel quantum-classical hybrid transformer for gravitational wave detection. The QGFormer consists of a vision transformer encoder and a quantum classifier following the autoencoder architecture, which first segments the original input signal into small patches and maps them to higher dimensions, and then inputs the higher-dimensional feature map into the quantum classifier for prediction. The excellent parallelism inherent in the multi-head self-attention mechanism and quantum computing makes QGFormer expected to achieve high computational efficiency and scalability on quantum computing devices. Additionally, the super-density coding and quantum state compression techniques that could be used in these devices help mitigate the effects of noise. In experiments on the Gravitational Spy dataset, which utilizes data collected by the LIGO telescope, our results show that QGFormer outperforms the comparison models in accuracy and F1-score, demonstrating the promising future of quantum machine learning approaches in this field. © 2023 IEEE.

关键词： Scalability

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Realization of algorithmic identification of cause and effect in quantum correlations

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Physical Review A 2024年第1期109卷 012406-012406页

作者： Zhao-An Wang Yu Meng Zheng-Hao Liu Yi-Tao Wang Shang Yu Wei Liu Zhi-Peng Li Yuan-Ze Yang Nai-Jie Guo Xiao-Dong Zeng Jian-Shun Tang Chuan-Feng Li Guang-Can Guo CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei 230026 China CAS Center For Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Hefei 230026 China Quantum Optics and Laser Science Blackett Laboratory Imperial College London Prince Consort Rd London SW7 2AZ United Kingdom Research Center for Quantum Sensing Zhejiang Lab Hangzhou 310000 People's Republic China Hefei National Laboratory University of Science and Technology of China Hefei 230088 China

Causal inference revealing causal dependencies between variables from empirical data has found applications in multiple subfields of scientific research. A quantum perspective of correlations holds the promise of overcoming the limitation of Reichenbach's principle and enabling causal inference with only observational data. However, it is still not clear how quantum causal inference can provide operational advantages in general cases. Here, we have devised a photonic setup and experimentally realized an algorithm capable of identifying any two-qubit statistical correlations generated by the two basic causal structures under an observational scenario, thus revealing a universal quantum advantage in causal inference over its classical counterpart. We further demonstrate the explainability and stability of our causal discovery method, which is widely sought in data processing algorithms. Employing a fully observational approach, our result paves the way for studying quantum causality in general settings.

关键词： Optical quantum information processing Optical tests of quantum theory Photon pairs & parametric down-conversion quantum algorithms quantum correlations in quantum information quantum gates quantum information processing

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Variational quantum algorithms: fundamental concepts, applications and challenges

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quantum information processing 2024年第6期23卷 224-224页

作者： Qi, Han Xiao, Sihui Liu, Zhuo Gong, Changqing Gani, Abdullah Shenyang Aerosp Univ Sch Comp Sci Shenyang 110000 Peoples R China Jalan Univ Fac Comp Sci & Informat Technol Univ Malaya Kuala Lumpur 50603 Malaysia

quantum computing is a new discipline combining quantum mechanics and computer science, which is expected to solve technical problems that are difficult for classical computers to solve efficiently. At present, quantum algorithms and hardware continue to develop at a high speed, but due to the serious constraints of quantum devices, such as the limited numbers of qubits and circuit depth, the fault-tolerant quantum computing will not be available in the near future. Variational quantum algorithms(VQAs) using classical optimizers to train parameterized quantum circuits have emerged as the main strategy to address these constraints. However, VQAs still have many challenges, such as trainability, hardware noise, expressibility and entangling capability. The fundamental concepts and applications of VQAs are reviewed. Then, strategies are introduced to overcome the challenges of VQAs and the importance of further researching VQAs is highlighted.

关键词： quantum computing Noisy-intermediate scale quantum Variational quantum algorithms quantum machine learning

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