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A Phase Estimation Algorithm for Quantum Speed-Up Multi-Party Computing

computers, Materials & Continua 2021年第4期67卷 241-252页

作者： Wenbin Yu Hao Feng Yinsong Xu Na Yin Yadang Chen Zhi-Xin Yang Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Jiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Department of Computer Science and Engineering Michigan State UniversityEast Lansing48824MIUSA State Key Laboratory of Internet of Things for Smart City and Department of Electromechanical Engineering University of Macao999078Macao

Security and privacy issues have attracted the attention of researchers in the field of IoT as the information processing scale grows in sensor *** computing,theoretically known as an absolutely secure way to store and transmit information as well as a speed-up way to accelerate local or distributed classical algorithms that are hard to solve with polynomial complexity in computation or *** this paper,we focus on the phase estimation method that is crucial to the realization of a general multi-party computing model,which is able to be accelerated by quantum algorithms.A novel multi-party phase estimation algorithm and the related quantum circuit are proposed by using a distributed Oracle operator with *** proved theoretical communication complexity of this algorithm shows it can give the phase estimation before applying multi-party computing efficiently without increasing any additional ***,a practical problem of multi-party dating investigated shows it can make a successful estimation of the number of solution in advance with zero communication complexity by utilizing its special statistic *** simulations present the correctness,validity and efficiency of the proposed estimation method.

关键词： Edge computing security multi-party computing quantum algorithm phase estimation communication complexity

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Remote Sensing Target Recognition Model Based on Small Sample Image Generation

Remote Sensing Target Recognition Model Based on Small Sampl...

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computer engineering and Intelligent Communications (ISCEIC), International Symposium on

作者： Lei Chen Liting Sun School of Space Information Space engineering University Beijing China General Department of Network and Information Security Beijing Institute of Computer Technology and Application Beijing China

In recent years, remote sensing object recognition methods based on deep learning have received extensive attention. Deep learning methods need to use a large number of labeled data to carry out network training. However, the cost of labeling remote sensing image data is very high. Therefore, how to use a small number of labeled target images to train the remote sensing target classifier with high performance is an urgent problem to be solved. In view of the above problems, this paper has carried out the following work. Firstly, based on WGAN-GP, this paper optimizes the constraint conditions of neural network and proposes a depth generation model, namely CCWGAN-GP, for remote sensing image generation. Secondly, this paper proposes a remote sensing target classification model SCLNet, which makes full use of the original one-hot label and the generated soft classification label to train the neural network. Experimental results show that the proposed model can generate highly similar images to real images, and can significantly improve the performance of the classifier under training conditions with only a few labels.

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Secure and Energy-Efficient Communication for Internet of Drones networks: A Deep Reinforcement Learning Approach

Secure and Energy-Efficient Communication for Internet of Dr...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Noor Aboueleneen Abdulmalik Alwarafy Mohamed Abdallah Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Doha Qatar Department of Computer and Network Engineering College of Information Technology United Arab Emirates University United Arab Emirates

Internet of Drones (IoD)-aided wireless networks are proving their efficiency in various commercial and military applications, such as object recognition, surveillance, and data acquisition. However, the broadcast communication nature of IoD networks raises significant communication security issues. This paper investigates drone-to-ground communication subject to eavesdroppers in urban environments. We aim to provide secure communication utilizing physical layer security by increasing network secrecy rates. In addition, we aim to reduce the energy consumption within the IoD network by optimizing drones’ transmitting and jamming power and employing energy harvesting techniques to charge drones wirelessly. Our optimization problem is formulated as a Markov decision process (MDP), and a deep reinforcement learning (DRL) algorithm is proposed to solve the problem.

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Ensemble Inequivalence and Phase Transitions in Unlabeled networks

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Physical Review Letters 2025年第20期134卷 207401-207401页

作者： Oleg Evnin Dmitri Krioukov High Energy Physics Research Unit Faculty of Science Chulalongkorn University Bangkok Thailand and Theoretische Natuurkunde Vrije Universiteit Brussel and International Solvay Institutes Brussels Belgium Department of Physics and Network Science Institute and Department of Mathematics and Department of Electrical and Computer Engineering Northeastern University Boston Massachusetts USA

We discover a first-order phase transition in the canonical ensemble of random unlabeled networks with a prescribed average number of links. The transition is caused by the nonconcavity of microcanonical entropy. Above the critical point coinciding with the graph symmetry phase transition, the canonical and microcanonical ensembles are equivalent and have a well-behaved thermodynamic limit. Below the critical point, the ensemble equivalence is broken, and the canonical ensemble is a mixture of phases: empty networks and networks with average degrees diverging logarithmically with the network size. As a consequence, networks with bounded average degrees do not survive in the thermodynamic limit, decaying into the empty phase. The celebrated percolation transition in labeled networks is thus absent in unlabeled networks. In view of these differences between labeled and unlabeled ensembles, the question of which one should be used as a null model of different real-world networks cannot be ignored.

关键词： Maximum entropy methods

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Bi-layered coded metasurface for multi-functional hologram with broadband transmission and efficient reflection

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Chinese Optics Letters 2024年第5期22卷 8-16页

作者：朱磊李绪胜董亮谢文静尚关玉 Shah Nawaz Burokur 丁旭旻 School of Computer and Control Engineering Qiqihar UniversityQiqihar 161006China Communication and Electronics Engineering Institute Qiqihar UniversityQiqihar 161006China Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis Qiqihar UniversityQiqihar 161000China Department of Microwave Engineering Harbin Institute of TechnologyHarbin 150001China LEME UPLUniversitéParis NanterreF92410 Ville d’AvrayFrance Advanced Microscopy and Instrumentation Research Center Harbin Institute of TechnologyHarbin 150080China Key Laboratory of Millimeter Waves Southeast UniversityNanjing 210096China

A multi-functional full-space metasurface based on frequency and polarization multiplexing is *** metasurface unit consists of metallic patterns printed on the two faces of a single-layered dielectric *** unit cell can control electromagnetic wavefronts to achieve a broadband transmission with amplitudes greater than 0.4 from 4.4 to 10.4 ***,at 11.7 GHz and 15.4 GHz,four high-efficiency reflection channels with a reflection amplitude greater than 0.8 are also *** illuminated by linearly polarized waves,five different functions can be realized at five different frequencies,which are demonstrated by theoretical calculations,full-wave simulations,and experimental measurements.

关键词： multi-functional metasurface broadband transmission efficient reflection full space

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Multi-Agent Reinforcement Learning for Covert Semantic Communications over Wireless networks

Multi-Agent Reinforcement Learning for Covert Semantic Commu...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yining Wang Ye Hu Hongyang Du Tao Luo Dusit Niyato Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China Department of Electrical Engineering Columbia University New York NY USA School of Computer Science and Engineering (SCSE) NTU Singapore

In this paper, a covert semantic communication framework is proposed for image transmission over wireless networks. In the proposed framework, devices extract and selectively transmit semantic information of image data to a base station (BS). The semantic information consists of the objects in the image and a set of attributes of each object. A warden selects a device to detect and eavesdrops the semantic information. To ensure the security of semantic communications, a jammer, acts as the defender, requires to find a vulnerable device and transmits jamming signals to the vulnerable device. The metric to measure the performance of the covert semantic communications is defined as the difference in the average accuracy of the BS and the warden answering a set of questions for each image. To maximize the performance of covert semantic communications, each device and the jammer must jointly optimize their transmit power, determine the vulnerable device to be protected, and determine the partial semantic information that each device needs to transmit. To solve this problem, we propose a multi-agent policy gradient (MAPG) algorithm. The proposed algorithm enables each device and the jammer to cooperatively discover the vulnerable devices as well as find the semantic information transmission and power control policies that maximize the performance of the covert semantic communication system. Simulation results show that the proposed algorithm can improve the communication performance by up to 14.5% compared to the independent reinforcement learning.

关键词： Performance evaluation Wireless networks Simulation Semantics Signal processing algorithms Reinforcement learning Signal processing

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The Design and Analysis of a Storytelling Chatbot with Natural Language Processing Techniques for Enhancing EFL Reading

The Design and Analysis of a Storytelling Chatbot with Natur...

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International Conference on Advanced Learning Technologies (ICALT)

作者： Yong Ting Feng Chen-Chung Liu Chia-Hui Chang Graduate Instittute of Network Learning Technology National Central University Taoyuan Taiwan Department of Computer Science and Information Engineering National Central University Taoyuan Taiwan

This study explored the applications of natural language processing techniques on the analysis of storybook to design the storytelling chatbots. Two natural language processing techniques, co-reference and dependency parsing techniques, were applied to process the text of 157 stories books as a means to implement in the invite-narration, positive recognition, follow-up strategies when the chatbot retells the story with the students. The results of the study found that 19 (42%) students demonstrated full narratives which can re-tell the overall story in the storybook, while 22 (49%) students could only retell a simplified story. Affordances and limitations of the use of the two techniques in developing chatbots for reading are discussed.

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A Multi-Scale Feature Extraction and Fusion Deep Learning Method for Classification of Wheat Diseases

arXiv

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arXiv 2025年

作者： Saleem, Sajjad Hussain, Adil Majeed, Nabila Akhtar, Zahid Siddique, Kamran Department of Information and Technology Washington University of Science and Technology United States Department of Physics Kansas State University ManhattanKS United States Department of Network and Computer Security State University of New York Polytechnic Institute Utica United States Department of Computer Science and Engineering University of Alaska Anchorage Anchorage United States

Wheat is an important source of dietary fiber and protein that is negatively impacted by a number of risks to its growth. The difficulty of identifying and classifying wheat diseases is discussed with an emphasis on wheat loose smut, leaf rust, and crown and root rot. Addressing conditions like crown and root rot, this study introduces an innovative approach that integrates multi-scale feature extraction with advanced image segmentation techniques to enhance classification accuracy. The proposed method uses neural network models Xception, Inception V3, and ResNet 50 to train on a large wheat disease classification dataset 2020 in conjunction with an ensemble of machine vision classifiers, including voting and stacking. The study shows that the suggested methodology has a superior accuracy of 99.75% in the classification of wheat diseases when compared to current state-of-the-art approaches. A deep learning ensemble model Xception showed the highest accuracy. © 2025, CC BY.

关键词： Image segmentation

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Adaptive Image Steganography: A Review and Research Directions*

Adaptive Image Steganography: A Review and Research Directio...

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International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Ayyah Abdulhafith Mahmoud Fadhl Hanein Omar Mohamed Shareif Malak Ahmed Elsherif Ali Abdullah Mohammad Abdullah Elmangoush Artificial Intelligence Department Libyan International University Benghazi Libya Software Engineering Department Libyan International University Benghazi Libya Telecommunication Department Libyan International University Benghazi Libya Computer Network Department Libyan International University Benghazi Libya

ISBN: (数字)9798350351484

ISBN: (纸本)9798350351491

Steganography involves concealing secret information in an appropriate multimedia carrier, such as text, image, audio, and video files, in such a way that only the sender and receiver suspect the existence of the secret information. Images are the most popular multimedia carriers. Adaptive image steganography is a promising new trend in the steganographic field. It basically means that the embedding locations are altered adaptively depending on the image content. The primary objective of this paper is to investigate and discuss various approaches to adaptive image steganography. The approaches can be broadly categorized as CNN-based, end_to_end GAN-based, and minimizing additive distortion function-based, both huristically and automatically designed. In addition to discussing the four categorized approaches, this paper provides an overview of image steganography including its characteristics or properties, and evaluation metrics. A summary table of all the details is also provided for convenience. The purpose of this paper is to assist fellow researchers by compiling current trends, their advantages and disadvantages, and identifying improvement gaps

关键词： Training Steganography Additives Reviews Streaming media Market research Generative adversarial networks

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Performance Evaluation of Grounding System of MV/LV Outdoor Compact Substation

Performance Evaluation of Grounding System of MV/LV Outdoor ...

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International Universities Power engineering Conference (UPEC)

作者： Konstantinos D. Merentitis Spyridon Christoforos Emmanouil D. Ellinas Eleftheria C. Pyrgioti Christos A. Christodoulou Ioannis F. Gonos Department of Electrical and Computer Engineering University of Patras Patras Greece Grid Operations Department Hellenic Distribution Network Operator Greece School of Electrical and Computer Engineering National Technical University Athens Greece

ISBN: (数字)9781665455053

ISBN: (纸本)9781665455060

The commitment of many countries worldwide to reduce their carbon footprint in the next few decades, has led to increased penetration of Renewable Energy Sources (RES) into power distribution networks. The connection of those RES to the MV power grid requires the installation of more compact and reliable MV/LV substations that would be easily accessible on the site of the PV Park or Wind Farm. Compact substations consist the preferred option for the connection of RES and LV loads on a power distribution grid since they provide key benefits compared to the conventional overhead substations. However, since they are made of a metal enclosure that is easily accessible, either by qualified personnel either by passers-by, it is necessary to study the adequacy of the grounding system, in order to ensure the reduction of the developed touch and step voltages in case of a short-circuit on the network. In this paper, the efficacy of two grounding grids, under various scenarios, is being evaluated by using the appropriate software tools. Purpose of the present work is to provide comprehensible data on the most common faults of power distribution networks and identify the worst-case scenarios that should be considered during the optimal techno-economic design of grounding grids of MV/LV outdoor compact substations.

关键词： Surface impedance Substations Grounding Soil measurements Surface resistance Soil Conductivity

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