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A Blockchain-enabled Anonymous-yet-Traceable distributed Key Generation 4

A Blockchain-enabled Anonymous-yet-Traceable Distributed Key...

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4th ieee international conference on Blockchain (Blockchain)

作者： Dehez-Clementi, Marina Lacan, Jerome Deneuville, Jean-Christophe Asghar, Hassan Kaafar, Dali ISAE SUPAERO DISC Toulouse France ENAC ReSCo Toulouse France Macquarie Univ Dept Comp Sydney NSW Australia

ISBN: (纸本)9781665417600

Many threshold systems require some kind of secret sharing during their set-up phase. there has been several recent work in doing secret sharing in a distributed manner through the use of Blockchain so that one does not have to rely on trusted third parties nor strong assumptions about the communication medium. this paper continues this line of work and presents a new protocol for distributed key generation (DKG). We develop a new technique that leverages the mainchain of a popular blockchain platform like Bitcoin, together with a mixing service and a group signature scheme, to provide anonymity and traceability;we connect this to a sidechain, pegged to the mainchain, that brings a better scalability. We implemented the technique on the joint platform Bitcoin/RootStock and use CoinJoin/CoinShuffle as the mixing service. the evaluation section shows a decrease by 99% in the execution cost of our protocol compared to the same implementation on a smart-contract-friendly blockchain such as Ethereum.

关键词： sidechain anonymity-accountability tradeoff secret sharing

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A 4-Channel Ultrafast Wavelength-Swept REC-DFB Laser Array for Fiber Bragg Grating Interrogation

A 4-Channel Ultrafast Wavelength-Swept REC-DFB Laser Array f...

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2023 Asia Communications and Photonics conference/2023 international Photonics and Optoelectronics Meetings, ACP/POEM 2023

作者： Meng, Lingxin Dai, Pan Ban, Qilu Xu, Kaichuan Wang, Jiacheng Li, Zhen Wang, Feng Zeng, Jie Li, Shaobo Ma, Xiang Chen, Xiangfei Res. Center of Precision Photonics Integration and System Application of the Ministry of Education College of Engineering and Applied Sciences Nanjing University Key Lab. of Intelligent Optical Sensing and Manipulation of the Ministry of Education Engineering National Laboratory of Solid State Microstructures Nanjing210023 China Nanjing University of Aeronautics and Astronautics State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing210016 China The 54th Research Institute of China Electronics Technology Group Corporation Optical Communication Research and Development Center Shijiazhuang050081 China

ISBN: (纸本)9798350312614

We present a four-channel ultrafast wavelength-swept distributed feedback (DFB) semiconductor laser array based on the reconstruction-equivalent-chirp (REC) technique using instantaneous injection current modulation. With the aid of our designed laser driving circuit system consists of the microcontroller unit (MCU), field-programmable gate array (FPGA) and negative metal-oxide-semiconductor field effect transistors (n-MOSFETs), the precise pulse driving current for the 4-channel wavelength-swept REC-DFB laser array can be generated and a fast tuning of 16.424 nm within 10 μs is achieved. To further investigate the tuning performance of the proposed wavelength-swept laser source, we then applied it to the fiber Bragg grating (FBG) interrogation system and four FBG temperature sensor arrays were successfully demodulated. the development of high-efficient optical sensing systems heavily relies on the significance of the ultrafast wavelength-swept laser source, which has the potential to greatly enhance FBG interrogator performance in the future. © 2023 ieee.

关键词： DFB laser array fast wavelength-swept fiber Bragg grating interrogation REC technique

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Allocation of FCLs in Transmission Networks with High Penetration of DGs: A Two-Stage Approach 4

Allocation of FCLs in Transmission Networks with High Penetr...

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4th international conference on Smart Energy systems and Technologies (SEST)

作者： Jarrahi, Mohammad Amin Roozitalab, Farzad Arefi, Mohammad Mehdi Mohammadi, Mohammad Javadi, Mohammad Sadegh Catalao, Joao P. S. Shiraz Univ Sch Elect & Comp Engn Shiraz Iran Politecn Milano Univ Sch Ind & Informat Engn Milan Italy Inst Syst & Comp Engn Technol & Sci INESC TEC P-4200465 Porto Portugal Univ Porto FEUP Fac Engn P-4200465 Porto Portugal

ISBN: (纸本)9781728176604

Fault current limiters (FCLs) are getting high-degree of attention since they can properly overcome the transient conditions of modern power systems. FCLs have the ability to limit the short-circuit currents before reaching to its maximum value so that they can be cut off by the available switches. In fact, FCLs show negligible resistance in the normal operation, but their resistance suddenly increases with a short-circuit and prevents it from rising. the technical and economic benefits of FCLs in power systems depend on their number, locations and optimal structural parameters. In this paper, a two-stage approach is proposed for determining the number, location and impedance of FCLs in the transmission network with high penetration of distributed generations (DGs). the suggested algorithm determines the number and locations of FCLs in the first step using a sensitivity based technique and the value of FCL impedance is chosen in the second step utilizing an optimization objective function. the improved grey wolf optimizer (IGWO) is developed to solve the optimization problem which its main objective is reducing the short-circuit level of the network. the proposed approach is assessed on the ieee-30 bus transmission network considering the effects of different kind of DGs. the results shown that FCLs can significantly reduce the short-circuit level of the network along with other advantages.

关键词： Fault Current Limiters Transmission Network distributed Generation Short-Circuit Level Two-Stage

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MASTER: Long-Term Stable Routing and Scheduling in Low-Power Wireless Networks 16

MASTER: Long-Term Stable Routing and Scheduling in Low-Power...

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16th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Harms, Oliver Landsiedel, Olaf Univ Kiel Kiel Germany Chalmers Univ Technol Gothenburg Sweden

ISBN: (纸本)9781728143514

Wireless sensor-Actuator Networks (WSANs) are an important driver for the Industrial Internet of things (IIoT) as they easily retrofit existing industrial infrastructure. Industrial applications require these networks to provide stable communication with high reliability and guaranteed low latency. A common way is using a central scheduler to plan transmissions and routes so that all packets are delivered before a deadline. However, existing centralized schedulers are only able to achieve high reliability in the absence of interference. this limitation lowers the feasibility of using centralized schedulers in most environments susceptible to interference. this paper addresses the challenge of stable, centrally scheduled communication in low-power wireless networks susceptible to interference. We introduce MASTER, a centralized scheduler and router, for ieee 802.15.4 TSCH (Time-Slotted Channel Hopping). MASTER uses Sliding Windows, a novel transmission strategy, which builds on flow-based retransmissions instead of link-based ones. We show in our experimental evaluation that MASTER with Sliding Windows achieves routing and scheduling stability for over 24 hours with end-to-end reliability of over 99.6%. Moreover, we show that MASTER outperforms Orchestra, a state-of-the-art autonomous scheduler, in terms of latency by a factor of 8 while achieving similar reliability under a slight duty-cycle increase.

关键词： TSCH Central Scheduling Routing Wireless sensor-Actuator Networks (Industrial) Internet of things

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Stress Detection via sensor Translation 16

Stress Detection via Sensor Translation

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16th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Samyoun, Sirat Mondol, Abu Sayeed Stankovic, John A. Univ Virginia Dept Comp Sci Charlottesville VA 22903 USA

ISBN: (数字)9781728143514

ISBN: (纸本)9781728143514

Stress increases the risk of several mental and physical health problems like anxiety, hypertension, and cardiovascular diseases. Better guidance and interventions towards mitigating the impact of stress can be provided if stress can be monitored continuously. the recent proliferation of wearable devices and their capability in measuring several physiological signals related to stress have created the opportunity to measure stress continuously in the wild. Wearable devices used to measure physiological signals are mostly placed on the wrist and the chest. though currently chest sensors, with/without wrist sensors, provide better results in detecting stress than using wrist sensors only, chest devices are not as convenient and prevalent as wrist devices, particularly in the free-living context. In this paper, we present a solution to detect stress using wrist sensors that emulate the gold standard chest sensors. Data from wrist sensors are translated into the data from chest sensors, and the translated data is used for stress detection without requiring the users to wear any device on the chest. We evaluated our solution using a public dataset, and results show that our solution detects stress with accuracy comparable to the gold standard chest devices which are impractical for daily use.

关键词： Stress Wrist Chest sensors Physiology

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Using Sub-Giga Hertz Technology In High Sampling Rate Wireless Monitoring systems Used In High-Rise Buildings 7

Using Sub-Giga Hertz Technology In High Sampling Rate Wirele...

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Moratuwa Engineering Research conference (MERCon) / 7th international Multidisciplinary Engineering Research conference

作者： Vishnu, P. Kirishikesan, K. Lewangamage, C. S. Jayasinghe, M. T. R. Univ Moratuwa Dept Civil Engn Moratuwa Sri Lanka Univ Moratuwa Dept Comp Sci & Engn Moratuwa Sri Lanka

ISBN: (纸本)9781665437530

Structural Health Monitoring (SHM) systems have been increasingly used in Civil Infrastructures to extract reliable information about the integrity and other important parameters of the structure in real-time. Using wireless sensor networks (WSN) in SHM applications has seen exponential growth in the last decade with the introduction of new communication protocols. WSN makes monitoring of structures easy and fast with low-cost involved. However, some structures such as high-rise buildings, are considered difficult for establishing WSN due to the presence of vertical obstructions. Radio waves with low-frequency are widely used in long-range SHM applications and monitoring high-rise buildings. Carrier waves with lower frequencies used in WSN travel over long-range and through obstructions easily compared to waves that are with higher frequency. Even though the range is increased in low-frequency waves, data rate is also reduced with decreasing frequency. In the SHM applications of high-rise buildings, it is not possible to compensate one - data transfer rate and penetrating ability for the other. this paper discusses the applications of Sub-Giga hertz technology and the corresponding performance of the developed WSN. Also, the application of simple and efficient data handling method used to ensure near real-time SHM is discussed in this paper.

关键词： Sub-Gigahertz Wireless sensor networks Low-cost Structural health monitoring distributed computing Long-range Data handling

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Hyperspectral Image Classification under PDE-based Cross-sensor Transfer Learning

Hyperspectral Image Classification under PDE-based Cross-sen...

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Artificial Intelligence, Robotics, and Communication (ICAIRC), ieee international conference on

作者： Qiuyi Lu Yunxiang Zhang Yujing Wang Lifen Wang Yanxia Yang Yue Zhao Ruida Ye Space Engineering University Beijing China

ISBN: (数字)9798331531225

ISBN: (纸本)9798331531232

the application of deep neural networks in image classification often demands a substantial amount of supervised data for training to yield relatively satisfactory outcomes. However, in the task of hyperspectral image classification, given the highly specialized nature of data annotation, the existing datasets are predominantly small-sized. the dearth of a large quantity of labeled image datasets for training poses a challenge in enhancing performance. Transfer learning mitigates the requirement for effective training with large-scale labeled samples by reusing the parameters of trained models and adapting them to related new tasks. Nevertheless, from the perspective of application scenarios, the characteristic that a single type of sensor only serves a specific region at a specific time results in the extraction of only one type of feature, which performs suboptimally on diverse datasets. Hence, the research on cross-sensor transfer learning is extremely pressing. Currently, the research on cross-sensor transfer learning mainly centers on extracting consistent features through more efficient models, yet this gives rise to the issue of an excessive number of parameters. PDE enhances the model generalization ability in cross-sensor hyperspectral image classification transfer learning through its stronger capacity for extracting consistent features, significantly reducing the number of parameters.

关键词： Training Transfer learning Redundancy Artificial neural networks Pressing Feature extraction Robot sensing systems Mathematical models Hyperspectral imaging Image classification

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Design and Implementation of an AI-Based Cleaner for Ceilings and Floors

Design and Implementation of an AI-Based Cleaner for Ceiling...

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international conference on Applied Electromagnetics, Signal Processing and Communication (AESPC)

作者： Chinmayee Dutta Ananya Dastidar School of Electronic Sciences Odisha University of Technology and Research Bhubaneswar Odisha India

ISBN: (数字)9798331528171

ISBN: (纸本)9798331528188

Traditional cleaning methods, particularly for ceilings, are laborious and time-consuming, often requiring separate tools for different surfaces. this paper presents a novel robotic cleaning system designed to autonomously clean both floors and ceilings, thereby addressing the limitations of existing single-surface cleaning robots. the system integrates AI-based object detection with dual sensors to facilitate autonomous navigation and effective obstacle avoidance in complex environments. A key innovation is a single robotic mechanism to perform multi-surface cleaning, eliminating the need for multiple cleaning tools and minimizing manual intervention. the system is controlled through a user-friendly mobile app that allows real-time monitoring, scheduling, and customization of cleaning sessions. the proposed solution improves cleaning efficiency by reducing the time and effort required for multi-surface cleaning but also enhances user convenience by providing a comprehensive and intuitive approach to maintaining cleanliness in various settings. these features position the system as a significant advancement in robotic cleaning technologies.

关键词： Surface cleaning Technological innovation Object detection Robot sensing systems Cleaning sensor systems Real-time systems sensors Mobile applications Floors

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Deep Learning based Intelligent Spectrum Sensing Framework Optimizing Dynamic Radio Resource Allocation

Deep Learning based Intelligent Spectrum Sensing Framework O...

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distributed computing and Electrical Circuits and Electronics (ICDCECE), ieee international conference on

作者： Ravi Kumar M Mahesh Kumar A. S Abbas thajeel Rhaif Alsahlanee Bhargav H K Amit Barve Abhijit Mitra Department of Electronics and Communication Engineering Cambridge Institute of Technology Bengaluru India Department of Electronics and Communication Engineering Maharaja Institute of Technology Mysore India Faculty of Education for Human Sciences University of Thi-Qar Nasiriyah Iraq Deptartment of Computer Science and Engineering Shridevi Institute of Engineering and Technology Industry Institute Interaction Cell (IIIC) Tumakuru India Department of Computer Science and Engineering Parul Institute of Technology Faculty of Engineering and Technology Parul University India Symbiosis Centre for Advanced Legal Studies and Research (SCALSAR) Symbiosis Law School Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798331533663

ISBN: (纸本)9798331533670

Efficient spectrum utilization in today's wireless communications requires intelligent spectrum sensing because dynamic spectrum access depends on it for resource allocation. this study presents a new deep learning framework for spectrum sensing which uses convolutional neural networks together with long short-term memory networks. Decision-making processes in real-time employ hybrid architecture which analyses both spectrum data spatial patterns as well as its temporal evolution through reinforcement learning mechanisms. the spectrum sensing framework using deep learning achieved 97.8% accuracy in detecting spectrum holes while reaching 95.3% precision in identifying primary users through its implementation which resulted in a 42% better spectrum utilization than conventional energy detection methods. Under -20dB to 20dB SNR conditions the system maintained steady performance that generated false alarms less than 0.03 times per observation. the proposed system design provides improved spectrum detection capabilities and resource distribution capabilities which makes it applicable for on-going wireless networks in congested urban spaces.

关键词： Deep learning Accuracy Wireless networks Computer architecture Dynamic scheduling Spatial databases sensors Resource management Convolutional neural networks System analysis and design

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Improving Energy Efficiency of Permissioned Blockchains Using FPGAs

Improving Energy Efficiency of Permissioned Blockchains Usin...

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international conference on Parallel and distributed systems (ICPADS)

作者： Nathania Santoso Haris Javaid AMD Singapore

Permissioned blockchains like Hyperledger Fabric have become quite popular for implementation of enterprise applications. Recent research has mainly focused on improving performance of permissioned blockchains without any consideration of their power/energy consumption. In this paper, we conduct a comprehensive empirical study to understand energy efficiency (throughput/energy) of validator peer in Hyperledger Fabric (a major bottleneck node). We pick a number of optimizations for validator peer from literature (allocated CPUs, software block cache and FPGA based accelerator). First, we propose a methodology to measure power/energy consumption of the two resulting compute platforms (CPU-only and CPU+FPGA). then, we use our methodology to evaluate energy efficiency of a diverse set of validator peer configurations, and present many useful insights. With careful selection of software optimizations and FPGA accelerator configuration, we improved energy efficiency of validator peer by 10$\times$ compared to vanilla validator peer (i.e., energy-aware provisioning of validator peer can deliver 10$\times$ more throughput while consuming the same amount of energy). In absolute terms, this means 23,000 tx/s with power consumption of 118W from a validator peer using software block cache running on a 4-core server with AMD/Xilinx Alveo U250 FPGA card. Index Terms--Energy-efficient blockchains, Hyperledger Fabric, FPGA accelerators

关键词： distributed ledger throughput Energy efficiency Software Fabrics Peer-to-peer computing Blockchains

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