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Reference-frame-independent measurement-device-independent quantum key distribution using fewer states

Physical Review A 2021年第2期103卷 022602-022602页

作者： Jing-Yang Liu Xing-Yu Zhou Qin Wang Institute of Quantum Information and Technology Nanjing University of Posts and Telecommunications Nanjing 210003 China Broadband Wireless Communication and Sensor Network Technology Key Laboratory of Ministry of Education Ministry of Education Nanjing 210003 China Telecommunication and Networks National Engineering Research Center NUPT Nanjing 210003 China

Reference-frame-independent measurement-device-independent quantum key distribution (RFI-MDI-QKD) is immune to both detector side channel attacks and slow drifts of reference frames, and thus possesses a high level of security. In the traditional protocol of RFI-MDI-QKD, each legitimate user, Alice or Bob, has to prepare six encoding states in three orthogonal bases (X, Y, and Z), which are sent to the untrusted third party, Charlie. Then all the successful counting events are utilized for parameter estimations, which suffer from a severe finite-size effect. In this paper, we propose a scheme on RFI-MDI-QKD with fewer states and demonstrate that it can be secured and made useful by utilizing semidefinite programming. Numerical simulation results reveal the equivalence between those groups of different monitoring states from Alice and Bob. In addition, when considering practical experimental conditions and taking finite-size effects into account, our proposal can achieve a better performance than the traditional six-state RFI-MDI scheme, which provides a resource-saving and simpler state-preparation approach for practical implementations without sacrificing key rates.

关键词： Quantum communication Quantum cryptography

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Value of Information-Based Packet Scheduling for AUV-Assisted UASNs

Value of Information-Based Packet Scheduling for AUV-Assiste...

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IEEE International Conference on Communications (ICC)

作者： Xiaoxiao Zhuo Wen Wu Liang Tang Fengzhong Qu Xuemin Shen Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China Key Laboratory of Wireless Sensor Network and Communications SIMIT CAS Shanghai China Peng Cheng Laboratory Frontier Research Center Shenzhen China Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province Zhejiang University Zhoushan China Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada

This paper studies autonomous underwater vehicles (AUV)-assisted underwater acoustic sensor networks (UASNs), where AUVs act as mobile sensor nodes to collect information from areas not accessible to static nodes and then relay data via static nodes. Due to the difficulty of obtaining the accurate global information of all the static nodes, we propose a novel packet scheduling scheme by utilizing local information obtained by AUVs. In the proposed scheme, the localization of static nodes stage and the topology construction stage are carried out beforehand to obtain the local information, based on which the transmission scheduling stage is implemented. Furthermore, in the transmission scheduling stage, we design a value of information (VoI)-based packet transmission scheduling (VBPS) strategy to avoid packet collision. Specifically, we introduce a performance metric, i.e., VoI, to measure the importance of data packets with different levels of urgency. Then, we formulate a combinatorial optimization problem to maximize VoI taking packet collision avoidance into consideration. A low-complexity distributed search algorithm is proposed to solve the problem, which exploits the spatial-temporal reuse to establish data packet collision constraints and then determines the next-hop node and data transmission time for AUVs. Extensive simulations under various scenarios are carried out to evaluate the performance of the proposed algorithm.

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A Review of the Evolutionary Algorithm Based VRP Problem

A Review of the Evolutionary Algorithm Based VRP Problem

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Chinese Control Conference (CCC)

作者： Lili Pan Bing Hu Zhe Sun Lei Xu Guangfu Gong Xiangpeng Xie Zhixin Sun Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing P. R. China Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing P. R. China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P. R. China Anhui Yougu Express Intelligent Technology Co. LTD Nanling Anhui P. R. China

The problem of vehicle routing planning (VRP) has far-reaching influence, and is widely used in vehicle scheduling, industrial production, transportation, logistics and distribution. The study of VRP and its associated derivations has grown significantly in recent years. So, starting with the fundamental VRP, this paper categorizes the VRP based on its traits and real-world applications. It then in-depth analyses the capacity constrained VRP, time window VRP, batched delivery VRP, dynamic VRP, and stochastic demand VRP, and provides an update on each type of VRP's research. Additionally, a summary of the VRP problem-solving methods is provided. The study of evolutionary algorithms is the main topic of this paper, and the fundamental solution method is provided in accordance with the development of the algorithms.

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A spectrum-based shortcut method for topological systems

arXiv

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arXiv 2023年

作者： Xu, Jian Mei, Feng Zhu, Yan-Qing College of Electronics and Information Engineering Guangdong Ocean University Guangdong Engineering Technology Research Center of Intelligent Ocean Sensor Network and Equipment guangdong Zhanjiang524088 China Guangdong Provincial Smart Ocean Sensing Networks and Equipment Engineering Technology Research Center Zhanjiang524088 China State Key Laboratory of Quantum Optics and Quantum Optics Devices Institute of Laser Spectroscopy Shanxi University Shanxi Taiyuan030006 China Quantum Science Center of Guangdong-Hong Kong-Macau Great Bay Area 3 Binlang Road Shenzhen China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Department of Physics HK Institute of Quantum Science & Technology The University of Hong Kong Pokfulam Road Hong Kong

The need for fast and robust quantum state transfer is an essential element in scalable quantum information processing, leading to widespread interest in shortcuts to adiabaticity for speeding up adiabatic quantum protocols. However, shortcuts to adiabaticity for systems with more than a few levels is occasionally challenging to compute in theory and frequently difficult to implement in experiments. In this work, we develop a protocol for constructing shortcuts to adiabaticity through the multi-state Landau-Zener approach and a stricter adiabatic condition. Importantly, our protocol only requires a few pieces of information about the energy spectrum and just adjusts the evolutionary rate of the system. It means that our protocol has broad applicability to theoretical models and does not require increasing the difficulty of the experiment. As examples, we apply our protocol to state transfer in the two-level Landau-Zener model, the non-Hermitian Su-Schrieffer-Heeger (SSH) model and the topological Thouless pump model and find that it can speed up the manipulation speed while remaining robust to Hamiltonian errors. Furthermore, based on the experimental friendliness of our findings, it can potentially be extended to many-body systems, dissipation cases, or Floquet processes. Overall, the proposed shortcut protocol offers a promising avenue for enhancing the efficiency and reliability of quantum state transfer protocols. © 2023, CC0.

关键词： Topology

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A 26-ppm/oC, 13.2-ppm/V, 0.11%-inaccuracy picowatt voltage reference with PVT compensation and fast startup

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Microelectronics Journal 2021年 115卷 105189-105189页

作者： Hu, Jinlong Xu, Huachao Wang, Jin Liang, Ke Lu, Chao Li, Guofeng Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology College of Electronic Information and Optical Engineering Nankai University China Engineering Research Center of Thin Film Optoelectronics Technology Ministry of Education Nankai University China School of Electrical Computer and Biomedical Engineering Southern Illinois University CarbondaleIL62901 United States

This paper proposes a picowatt voltage reference for Internet-of-Things applications, which require fast response speed and high insensitivity to variations of the process, supply voltage, and temperature (PVT). By employing a novel topology with a startup circuit and an effective PVT compensation method, the proposed voltage reference can achieve both high PVT stability and shorten the setup time. Based on a 0.18 μm standard CMOS process, post-layout simulation results show that the proposed design achieves a mean reference voltage of 755.6 mV with a variation coefficient of 0.11 % without trimming. The line regulation is 13.2 ppm/V over a supply voltage from 1 V to 1.8 V at 27 °C. The average temperature coefficient is about 26 ppm/°C in a temperature range from −20 °C to 120 °C. The 1 % settling time of the output reference voltage is about 274 μs. © 2021 Elsevier Ltd

关键词： Internet of things

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In-Situ and Ultrasensitive Detection of Mercury (Ii) Ions (Hg2+) Using the Localized Surface Plasmon Resonance (Lspr) Nanosensor and the Microfluidic Chip

SSRN

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SSRN 2022年

作者： Zhang, Wenjia Liu, Guohua Bi, Jinqiang Bao, Kexin Wang, Peiren Tianjin Research Institute of Water Transport Engineering M.O.T. Tianjin300456 China National Engineering Research Center of Port Hydraulic Construction Technoloy Tianjin300456 China College of Microelectronics Nankai University Tianjin300350 China Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Tianjin300350 China Engineering Research Center of thin film optoelectronics technology Ministry of Education Nankai University Tianjin300350 China School of Marine Science and Technology Tianjin University Tianjin300192 China

Mercury is one of the most dangerous heavy metals due to its extreme toxicity to both humans and the biosphere. In this work, an in-situ and ultrasensitive method for the detection of mercury (II) ions (Hg 2+ ) using the dark-field microspectroscopy-based localized surface plasmon resonance (LSPR) nanosensor is demonstrated. In our homemade high-throughput microfluidic chip, the fixed nanorods and the free small gold nanospheres combine to form the core-satellite structures with the help of T- Hg 2+ -T chemical coordination. Such a process results in a spectral red shift due to plasmonic coupling, which allows us to reach a picomolar detection limit and a linear response range from 10 pM to 10 µM. In addition, our LSPR nanosensor has excellent selectivity and no interference for the detection of Hg 2+ , which was evaluated by monitoring responses to different heavy metal ions (Pb 2+ , Cd 2+ , Cr 2+ , Ni 2+ , and Cu 2+ ) and their mixed samples. Our sensor platform's effectiveness offers a practical method for detecting traces of Hg 2+ in real-life water samples. © 2022, The Authors. All rights reserved.

关键词： Microfluidic chips

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Fire Detection Method Based on Improved Fruit Fly Optimization-Based SVM

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Computers, Materials & Continua 2020年第1期62卷 199-216页

作者： Fangming Bi Xuanyi Fu Wei Chen Weidong Fang Xuzhi Miao Biruk Assefa College of Computer Science and Technology China University of Mining and TechnologyXuzhou221116China College of Computer Science and Technology Mine Digitization Engineering Research Center of the Ministry of EducationChina University of Mining and TechnologyXuzhou221116China College of Computer Science and Technology Xi’an University of Science and TechnologyXi’an710054China Key Laboratory of Wireless Sensor Network&Communication Shanghai Institute of Micro-System and Information TechnologyChinese Academy of SciencesShanghai201899China Infromation Communication Technology Department Wollo UniversityDessie EthiopiaP.o Box 1145Ethiopia

Aiming at the defects of the traditional fire detection methods,which are caused by false positives and false negatives in large space buildings,a fire identification detection method based on video images is *** algorithm first uses the hybrid Gaussian background modeling method and the RGB color model to perform fire prejudgment on the video image,which can eliminate most non-fire ***,the traditional regional growth algorithm is improved and the fire image segmentation effect is effectively ***,based on the segmented image,the dynamic and static features of the fire flame are further analyzed and extracted in the area of the suspected fire ***,the dynamic features of the extracted fire flame images were fused and classified by improved fruit fly optimization support vector machine,and the recognition results were *** video-based fire detection method proposed in this paper greatly improves the accuracy of fire detection and is suitable for fire detection and identification in large space scenarios.

关键词： Fire detection image segmentation feature extraction fruit fly optimization support vector machine

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INTRODUCTION

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Bulletin of the American meteorological Society 2024年第8期105卷 S1-S11页

作者： Boyer, T. Blunden, J. Dunn, R.J.H. NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Met Office Hadley Centre Exeter United Kingdom European Centre for Medium-Range Weather Forecasts Reading United Kingdom University of Maryland College Park Maryland Scripps Institution of Oceanography University of California San Diego La Jolla California NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland Brandenburg University of Technology (BTU) Cottbus-Senftenberg Germany Servicio Meteorológico Nacional Buenos Aires Argentina NOAA/OAR Physical Sciences Laboratory Boulder Colorado European Centre for Medium-Range Weather Forecasts Bonn Germany Center for Geophysical Research and School of Physics University of Costa Rica San José Costa Rica Department of Meteorology and National Centre for Earth Observation University of Reading Reading United Kingdom Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Université Grenoble Alpes Institut des Géosciences de l’Environnement IRD CNRS Grenoble INP Grenoble France Hampton University Hampton Virginia Seychelles Meteorological Authority Mahe Seychelles Section for Glaciers Ice and Snow Norwegian Water Resources and Energy Directorate Oslo Norway National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Agriculture Osaka Metropolitan University Sakai Japan Science Faculty Universidad Nacional de Colombia Bogotá Colombia University of Bremen Bremen Germany NOAA Global Monitoring Laboratory Boulder Colorado Servicio Nacional de Meteorología e Hidrología del Perú Lima Perú Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CSIC-UV-GVA) Valencia Spain Hydro-Climate Extremes Lab (H-CEL) Ghent University Ghent Belgium Department o

In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. A

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DisCANTree: A Distributed Algorithm for Incremental Frequent Itemset Mining based on MapReduce

DisCANTree: A Distributed Algorithm for Incremental Frequent...

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2020 International Conference on Machine Learning and Computer Application, ICMLCA 2020

作者： Xiao, Wen Hu, Juan Key Lab. of Unmanned Aer. Vehicle Devmt. and Data Application of Anhui Higher Education Institutes Wanjiang University of Technology Maanshan243000 China Ma'Anshan Engineering Technology Research Center for Wireless Sensor Network and IntelliSense Wanjiang University of Technology Maanshan243000 China

Frequent itemset mining is one of the most important data mining tasks. Classical frequent itemset mining algorithms need to store data in a centralized way and run in a batch way, which cannot meet the requirements of fast updating big data mining. In this paper, we propose a distributed incremental frequent itemset mining algorithm, DisCANTree, which uses CANTree to store the conditional database, achieves the load balance between nodes by grouping all items, updates the new transaction to the existing CANTree to avoid the load of tree reconstruction, and uses the efficient FPGrowth algorithm to mine CANTree to generate frequent itemsets. The popular distributed programming model MapReduce and its open source system Hadoop are used to implement the DisCANTree algorithm. The experimental results show that the DisCANTree algorithm has more advantages than the most popular PFP algorithm in performance as well as the number of transferred records between nodes, and especially suits for the fast updating sparse big data. © Published under licence by IOP Publishing Ltd.

关键词： MapReduce

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Tme: Temporal and Motion Enhancement for Action Recognition

SSRN

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SSRN 2021年

作者： Wang, Hao Zhao, Bin Liu, Guohua Sensor Technology Intelligent System Lab College of Electronic Information and Optical Engineering Nankai University Tianjin 300350 China School of Artificial Intelligence Guilin University of Electronic Technology Guangxi Guilin541004 China Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Tianjin 300350 China Engineering Research Center of thin film optoelectronics technology Ministry of Education Nankai University Tianjin 300350 China

The key to video understanding is to capture temporal information. 3D CNNs can achieve good performance by directly fusing spatial and temporal features but are computationally intensive. Conventional 2D CNNs perform well in image recognition, but the inability to extract temporal features leads to poor performance in video action recognition. In this work, we aim to catch temporal relationships for video action recognition. To this end, we propose a Temporal and Motion Enhancement (TME) module consisting of two submodules: Multi-path Temporal Enhancement(MTE) module and Long Short-range Motion Enhancement(LSME) module. The MTE module consists of four paths: Residual path, Temporal Aggregation(TA) path, Channel-wise Temporal Excitation(CTE) path and Spatial-attention Temporal Excitation(STE) path. The Residual path makes part of the information in the original activation accessible. The TA path employs convolution on temporal dimension to characterize temporal representation. The CTE path rebuilds channel-wise feature relationships in terms of the temporal aspect. The STE path introduces attention mechanisms and explores the temporal modeling. We aggregate features of different paths by splitting channels, which is efficient for model inference. The LSME module calculates feature-level temporal differences between long and short range frames, which enhances the motion-related features. TME module is plug-and-play and can be inserted into 2D CNNs to form an effective TMENet with limited extra computational cost. The extensive experiments on several action recognition datasets, such as Kinetics400, Something-Something V1\&V2, HMDB51, and UCF101, demonstrate that the TMENet outperforms the state-of-the-art methods with high efficiency. Code will be released soon. © 2021, The Authors. All rights reserved.

关键词： Image recognition

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