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Wearable patterned single electrode-based triboelectric nanogenerator for peak-encoded interface

NANO ENERGY 2024年 124卷

作者： Li, Shuhan Xia, Yifan Zhang, Siyu Liu, Kangting Yang, Biao Li, Mingyuan Zhi, Xinrong Wang, Xin Henan Univ Sch Future Technol Henan Key Lab Quantum Mat & Quantum Energy Kaifeng 475004 Peoples R China Anhui Agr Univ Sch Informat & Artificial Intelligence Hefei 230036 Peoples R China

Advancement in human-machine interface (HMI) is indispensable for development of virtual/augmented reality, robotics control, and artificial intelligence (AI). However, there lack a simple facile electronics to achieve accurate finger motion recognition and remote robot control through simple signal processing. Herein, a wearable patterned single electrode-based triboelectric nanogenerator (PS-TENG) based on regenerated silk film (rSF) is developed for peak-encoded interface, which can accurately identify the handwritten numbers or letters. The patterned single electrode, composed of nine units with five different patterns, is successfully constructed by inkjet printing Ag inks on the rSF. When handwriting on the PS-TENG, the generated output voltage with different peak amplitude can be transformed into a peak spectrum with spatial information. Handwriting numbers or letters can be accurately identified through simple digitization data processing of the peak-encoded spectrum without complex algorithms. Furthermore, the PS-TENG as peak-encoded interface enables precise game play, accurate pattern lock, and wireless robot control. Importantly, based on relative amplitude of output signals, the peak-encoded code is regardless of factors including absolute amplitude of output signals, sliding speed and environmental humidity. Consequently, the PS-TENG, characterized by self-powered feature, simple structure and straightforward signal processing, demonstrates remarkable identification accuracy of handwritten numbers and letters through decoding unique and stable peak spectrum, which would have great potential in the field of virtual control panels, HMI and AI.

关键词： Triboelectric nanogenerator Flexible peak-encoded interface Patterned single electrode Peak-encoded code Regenerated silk film

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T-depth-optimized quantum search with quantum data-access machine

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quantum SCIENCE AND TECHNOLOGY 2024年第1期9卷 015011-015011页

作者： Jun Park, Jung Baek, Kyunghyun Kim, M. S. Nha, Hyunchul Kim, Jaewan Bang, Jeongho LG Elect CTO Div AI Lab Seoul 06772 South Korea Elect & Telecommun Res Inst Daejeon 34129 South Korea Imperial Coll London Blackett Lab QOLS London SW7 2AZ England Korea Inst Adv Study Sch Computat Sci Seoul 02455 South Korea Texas A&M Univ Qatar Dept Phys POB 23874 Doha Qatar

quantum search algorithms offer a remarkable advantage of quadratic reduction in query complexity using quantum superposition principle. However, how an actual architecture may access and handle the database in a quantum superposed state has been largely unexplored so far;the quantum state of data was simply assumed to be prepared and accessed by a black-box operation-so-called oracle, even though this process, if not appropriately designed, may adversely diminish the quantum query advantage. Here, we introduce an efficient quantum data-access process, dubbed as quantum data-access machine (QDAM), and present a general architecture for quantum search algorithm. We analyze the runtime of our algorithm in view of the fault-tolerant quantum computation (FTQC) consisting of logical qubits within an effective quantum error correction code. Specifically, we introduce a measure involving two computational complexities, i.e. quantum query and T-depth complexities, which can be critical to assess performance since the logical non-Clifford gates, such as the T (i.e. pi/8 rotation) gate, are known to be costliest to implement in FTQC. Our analysis shows that for N searching data, a QDAM model exhibiting a logarithmic, i.e. O(logN) , growth of the T-depth complexity can be constructed. Further analysis reveals that our QDAM-embedded quantum search requires O(NxlogN) runtime cost. Our study thus demonstrates that the quantum data search algorithm can truly speed up over classical approaches with the logarithmic T-depth QDAM as a key component.

关键词： quantum algorithm quantum data-processing quantum data search

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On applying the lackadaisical quantum walk algorithm to search for multiple solutions on grids

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information SCIENCES 2023年 622卷 873-888页

作者： de Carvalho, Jonathan H. A. de Souza, Luciano S. de Paula Neto, Fernando M. Ferreira, Tiago A. E. Univ Fed Pernambuco Ctr Informat Ave Prof Moraes Rego1235 Cidade Univ BR-50670901 Recife PE Brazil Univ Fed Rural Pernambuco Dept Estat & Informat Rua Dom Manuel Medeiross-nDois Irmaos BR-52171900 Recife PE Brazil

quantum computing promises to improve the information processing power to levels unreachable by classical computation. quantum walks are heading the development of quantum algorithms for searching information on graphs more efficiently than their clas-sical counterparts. A quantum-walk-based algorithm standing out in the literature is the lackadaisical quantum walk. The lackadaisical quantum walk is an algorithm developed to search graph structures whose vertices have a self-loop of weight l. This paper addresses several issues related to applying the lackadaisical quantum walk to search for multiple solutions on grids successfully. Firstly, we show that only one of the two stopping condi-tions found in the literature is suitable for simulations. In the most discrepant case shown here, a stopping condition is prematurely satisfied at the step T = 288 with a success prob-ability Pr = 0.593276, while the suitable condition captures the actual amplification that occurred until T = 409 with Pr = 0.878178. We also demonstrate that the final success probability depends on both the space density of solutions and the relative distance between solutions. For instance, we show here that decreases in the density of solutions can even take a success probability of 0.849178 to 0.961896. In contrast, increases in the relative distances can even take a success probability of 0.871665 to 0.940301. Furthermore, this work generalizes the lackadaisical quantum walk to search for multiple solutions on grids of arbitrary dimensions. In addition, we propose an optimal adjustment of the self-loop weight l for such d-dimensional grids. It turns out other fits of l found in the literature are particular cases. Our experiments demonstrate that successful searches for multiple solutions with higher than two dimensions are possible by achieving success probabilities such as 0.999979, with the value of l proposed here, where it would be 0.637346, with the value of l proposed in previous works.

关键词： quantum computing quantum walk Lackadaisical quantum walk Search algorithm Spatial search

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Entanglement Management through Swapping over quantum Internets

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Performance Evaluation Review 2023年第2期51卷 69-71页

作者： Zeng, Yiming Zhang, Jiarui Liu, Zhenhua Yang, Yuanyuan Stony Brook University United States

quantum Internet has the potential to support a wide range of applications in quantum communication and quantum computing by generating, distributing, and processing quantum information. Generating a long-distance quantum entanglement is one of the most essential functions of a quantum Internet to facilitate these applications. However, entanglement is a probabilistic process, and its success rate drops significantly as distance increases. Entanglement swapping is an efficient technique used to address this challenge. How to efficiently manage the entanglement through swapping is a fundamental yet challenging problem. In this paper, we will consider two swapping methods: (1) BSM: a classic entanglement-swapping method based on Bell State measurements that fuse two successful quantum links, (2) nfusion: a more general and efficient swapping method based on Greenberger-Horne-Zeilinger measurements, capable of fusing n successful quantum links. Our goal is to maximize the entanglement rate for multiple quantum-user pairs over the quantum Internet with an arbitrary topology. We propose efficient entanglement management algorithms that utilized the unique properties of BSM and n-fusion. Evaluation results highlight that our approach outperforms existing routing protocols. © 2023 Copyright is held by the owner/author(s).

关键词： quantum entanglement

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A Conceptual Model of quantum Cryptography Techniques used to Provide Online Banking Transactions Security 2

A Conceptual Model of Quantum Cryptography Techniques used t...

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2nd IEEE International Conference on Trends in quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Madje, Uma Pratap Pande, Mandaar B. Faculty of Computer Studies Pune India Symbiosis Centre for Information Technology Pune India

ISBN: (纸本)9798350384277

In today's online environment, a lot of data is created through online transactions and processing, and protecting this data can be difficult. When talking about security and privacy, it takes into account how resistant information and other transaction data is to threats and flaws. Online banking raises three key concerns: user identity, data confidentiality, and the medium or channel over which the information is conveyed. For this reason, the main focus of this study is on the security methods used in online banking that fall within the categories of classical and quantum cryptography in order to combat multiple attacks and problems that may arise when using the service. The study offers a conceptual model for client authentication using the one-time pad (OTP) idea in conjunction with quantum-safe channel technology to boost security and prevent reply attacks. To assess the performance and determine whether the proposed framework operationally feasible, quantum cryptography is being introduced. The performance and speed of financial transaction processing can be increased by combining quantum computing with traditional algorithms for fraud detection. In order to create a safe key exchange with the help of quantum cryptography, the proposed approach takes this into consideration and implements QKD and QRNG. © 2024 IEEE.

关键词： quantum cryptography

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Image segmentation using convolutional neural networks in multi-sensor information fusion

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SOFT COMPUTING 2023年第23期27卷 18353-18372页

作者： Zhang, Wenying Dong, Min Jiang, Li Zhengzhou Univ Sch Elect & Informat Engn Zhengzhou 450001 Henan Peoples R China

In recent years, the rapid advancement of artificial intelligence (AI) has revolutionized various industries, with image processing playing an important role in the revolution. AI-powered image analysis has opened up new possibilities in healthcare diagnostics, autonomous navigation, and security surveillance, fuelling demand for sophisticated image-processing solutions. This paper describes an innovative approach to AI image processing that combines multi-sensor data fusion with convolutional neural networks (CNNs) within a fuzzy neural network framework. This integration uses data from various sensors, including cameras, lidar, and radar, to improve the robustness and precision of image analysis and interpretation. The T-S model serves as the foundation for the information fusion strategy. A comprehensive investigation of deep learning algorithms reveals inherent strengths such as robustness and parallelism. However, it also identifies limitations, particularly in image segmentation tasks, characterized by challenges like premature convergence and prolonged computation times. The paper proposes a quantization technique for deep learning algorithms to address these issues and introduces chaotic optimization to expedite convergence rates. It also presents a novel three-dimensional Otsu threshold segmentation method based on CNNs, which overcomes noise susceptibility in traditional two-dimensional approaches. Integrating Gray morphology and this three-dimensional Otsu threshold segmentation method results in the development of a three-dimensional Gray Otsu model. This model is the basis for designing a fitness function for the CNN algorithm, optimizing its efficacy. Experimental validation demonstrates the proposed algorithm's effectiveness, achieving an impressive 91% accuracy rate while displaying robust noise resistance and versatility. Comparative assessments against other leading AI architectures, including multilayer perceptron, radial basis function network, r

关键词： Image segmentation Convolution neural network Fuzzy neural network Chaotic quantum deep learning algorithm Multi-sensor information fusion

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Evaluation of Equivalency Certificates for International Students using quantum AI of Fairness and Efficiency QAA 3

Evaluation of Equivalency Certificates for International Stu...

引用

3rd International Conference on Electrical, Electronics, information and Communication Technologies, ICEEICT 2024

作者： Krishnan, Sumathy Surendran, R. Sathiamurthy, Maha Sweta Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India Puducherry Technological University Department of Electronics and Communication Engineering Puducherry India

ISBN: (纸本)9798350369083

International student mobility is essential for developing worldwide cooperation and educational exchange. However, the existing method of evaluating international academic qualifications, which frequently relies on Equivalency Certificates, encounters notable obstacles such as subjectivity, lengthy processing periods, and possible biases. In order to tackle these problems, this research suggests an innovative method that use quantum amplitude amplification (QAA) to transform the process of evaluating equivalency certificates for overseas students. QAA utilises the computing capabilities of quantum algorithms to effectively and precisely assess the comparability of educational qualifications across various academic systems. Our project seeks to optimise the equivalency certificate evaluation process by combining quantum computing and artificial intelligence approaches. This will provide a more dependable and unbiased framework for assessing the qualifications of international students. This article provides a detailed analysis of current approaches and proposes new algorithms based on QAA. The main objective is to outline a plan for using QAA in the assessment of equivalency certificates. The prospective ramifications of this strategy encompass enhanced clarity, decreased processing durations, and heightened precision in assessing the qualifications of international students, so promoting seamless transitions into higher education or employment in foreign nations. This paper reviews current equivalence assessment methodologies, proposes QAA-based algorithms tailored for this purpose, and outlines a roadmap for applying QAI to equivalency certificate evaluation. Beyond enhancing accuracy and efficiency, this research has the potential to promote global creativity and collaboration by improving the evaluation process for international students. © 2024 IEEE.

关键词： quantum computers

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quantum zero correlation linear cryptanalysis

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quantum information processing 2022年第8期21卷 1-30页

作者： Shi, Rui Xie, Huiqin Feng, Huamin Yuan, Feng Liu, Biao Beijing Univ Posts & Telecommun Sch Cyberspace Secur Beijing 100876 Peoples R China Hangzhou Normal Univ Key Lab Cryptog Zhejiang Prov Hangzhou 311121 Peoples R China Beijing Elect Sci & Technol Inst Beijing 100070 Peoples R China China Aerosp Sci & Ind Corp Ltd Inst 706 Acad 2 Beijing 100854 Peoples R China

The advent of large-scale quantum computers would greatly threaten the security of current cryptosystems. It is urgent to investigate how quantum computing will affect the security of symmetric cryptosystems. Since the security of symmetric schemes heavily depends on the development of cryptanalytic tools, studying the applications of quantum algorithms to classical cryptanalytic tools is critical. To this end, we study quantum zero correlation linear cryptanalysis and propose two quantum algorithms for finding zero correlation linear hulls of Feistel ciphers and SPN ciphers, respectively. We prove that, as long as the attacked block ciphers satisfy certain algebraic conditions, the linear approximations output by the proposed algorithms have zero correlation with a probability close to one. The proposed algorithms have polynomial-time quantum complexity and do not require any quantum or classical query to the attacked block ciphers. Compared to the classical zero correlation linear cryptanalysis, the quantum version has the advantage for extending the number of rounds of zero correlation linear approximations.

关键词： quantum cryptanalysis quantum computing Symmetric cryptography Zero correlation linear cryptanalysis Block cipher

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Steganography in the quantum Era 6

Steganography in the Quantum Era

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6th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2024

作者： Bharatwaj, Aksaj Kumar Hasabnis, Amey R Dept of Physics Greater Noida201314 India Dept of Basic Studies Madhya Pradesh Mhow453441 India

ISBN: (纸本)9798350306613

The advancement of quantum information and quantum computing has led to an increase in algorithms and new methods to exploit quantum computers in various domains, such as breaking cryptography, quantum Machine learning, quantum Eigensolvers for materials modeling etc. One such way of control-ling quantum computers has led to the inception and emergence of quantum Image processing and quantum Steganography. Steganography has been widely used for secure communication in the past. With the evolution of quantum computing, the exploitation of qubits for image-based steganography has gained attention from academics, government, and military stakeholders alike to improve their respective secure communication channels. This paper aims to discuss a preliminary application of quantum Steganography using IBM's open source software development kit Qiskit [9] in the quantum Era. © 2024 IEEE.

关键词： post-quantum cryptography quantum image processing quantum security quantum steganography quanytum computing

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quantum Enhanced Prediction for Breast Cancer Electronic Health Records

Quantum Enhanced Prediction for Breast Cancer Electronic Hea...

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2024 IEEE International Conference on Signal processing, Informatics, Communication and Energy Systems, SPICES 2024

作者： Rajesh, G. Madhumitha, R. Arunagiri, S.S. Vishal, M. Anna University Department of Information Technology Chennai India

ISBN: (数字)9798350376135

ISBN: (纸本)9798350376135

quantum computing technology allows for more efficient problem-solving and provides essentially distinct answers to computational challenges when compared to classical computations. Machine learning algorithms have come to the fore in medical research and offer promising avenues for increasing the accuracy of cancer diagnosis. Breast cancer represents the majority of cancer cases in women worldwide, making it a serious and widespread public health issue. Improving patient outcomes requires early identification of cancer. The proposed quantum Enhanced Prediction (QEP) project delves into the predictive power of two distinct learning paradigms: Support Vector Machine and quantum Support Vector Machine, using Wisconsin breast cancer dataset. The research underscores the complexity of algorithms in cancer prediction. A departure from the ZZ feature map in QSVM marked the beginning of an intentional shift from traditional design. However, the study looked at the integration of the Z element map and Pauli matrices, providing the foundation for improved accuracy and a better grasp of quantum mechanics in cancer prediction. This conceptual shift intends to investigate the possible influence of quantum computing on breast cancer prediction with more granularity. © 2024 IEEE.

关键词： Electronic health record

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