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A Study on Formal Verification of Smart Contracts in distributed Ledger Technology 3

A Study on Formal Verification of Smart Contracts in Distrib...

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3rd ieee international conference on Recent Advances in systems Science and Engineering, RASSE 2023

作者： Gokulnath, G. Kizhakkethottam, Jubilant J APJ Abdul Kalam Technological University Kerala India Department of Computer Science and Engineering India

ISBN: (纸本)9798350341676

This study paper explores the critical topic of formal verification of smart contracts in distributed ledger technology (DLT) systems. Smart contracts, self-executing code running on blockchain platforms, have gained widespread adoption in various industries due to their automation and transparency benefits. However, the decentralized and immutable nature of DLT raises concerns regarding smart contract security, leading to vulnerabilities and potential exploits. Formal verification methods offer a systematic approach to analyze smart contracts for correctness and safety. This paper provides an overview of smart contracts, DLT, and the importance of formal verification. It reviews various formal verification techniques and presents state-of-The-Art tools and frameworks. The paper concludes with discussions on challenges, future research opportunities, and the role of formal verification in enhancing DLT-based applications' security and usability. © 2023 ieee.

关键词： Smart contract

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sensor Fusion for Traffic Monitoring Using Camera, Radar, and ROS 3

Sensor Fusion for Traffic Monitoring Using Camera, Radar, an...

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3rd international conference on Intelligent computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Garvin, Joe McVicker, Mason Mshar, Alec Williamson, Jonathan Alkhelaifi, Yahia Anderson, Wolfe Jeong, Nathan The University of Alabama Department of Electrical and Computer Engineering TuscaloosaAL United States

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

In this paper, a self-contained system that is capable of precisely recognizing traffic data in real-time is designed and tested. This system detects the range and velocity of objects using a high-frequency automotive radar module. The system also records a video stream and employs a YOLOv3 detection algorithm using the COCO dataset to identify, label, and track different classes of vehicles and pedestrians. The fusion of these two sensor systems combines the benefits of both the radar's accuracy and the camera's object detection. The final design is deployed in a real-world environment and validated against collected ground-truth data. The system is capable of providing traffic information accurately. © 2022 ieee.

关键词： Cameras

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A voltage control method for isolated grid based on long short-term memory neural network optimized by improved particle swarm optimization algorithm 3

A voltage control method for isolated grid based on long sho...

引用

3rd international conference on Intelligent Power and systems, ICIPS 2023

作者： He, Xiangqiang Liu, Mingshun Pu, Qingxin Li, Chengxiang Chang, Dongxu Power dispatching control center of Guizhou Power Grid Co. Ltd Guizhou China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9798350328691

With the access of numerous distributed generations such as wind turbines, photovoltaic generators, and energy storage devices, the composition and operation mode of the power grid are becoming increasingly complex, and more uncertain factors affect the recovery of the isolated grid voltage. Aiming at the problem of optimal control of isolated grid voltage under uncertain factors, a voltage control method for isolated grid is proposed, based on long short-term memory neural network optimized by improved particle swarm optimization algorithm. Firstly, the relationship between the gain of the distributed power controller and the performance of the isolated grid controller is analyzed. Then, the particle swarm optimization algorithm is utilized to optimize the hyper-parameters such as the learning rate and neuron number of the long short-term memory neural network, so as to prevent the hyper-parameters from selecting training effect affecting network improperly. Finally, the optimized long short-term memory neural network is mapped to the relationship between the voltage deviation of the distributed generation and the controller gain, and a voltage optimization control model for the isolated grid is constructed. The simulation results show that the voltage of the distributed generation is stabilized at 1 after 0.92 s, which indicates that the proposed optimal control method improves the voltage level of the isolated grid, verifying the effectiveness of the method. ©2023 ieee.

关键词： distributed power generation

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Underwater Wireless sensor Networks Using distributed Fusion of Optimally Quantized Estimations from Local Trackers 3

Underwater Wireless Sensor Networks Using Distributed Fusion...

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3rd international conference on Pervasive computing and Social Networking, ICPCSN 2023

作者： Pal, Yogesh Mohan, Ravi Rao, Ganga Rama Koteswara Suresh Kumar, A. Rastogi, Ravi Shah, Mohd Asif Bennett University Scset Uttar Pradesh Greater Noida India Shri Ram Institute of Technology Electronics & Communication Engineering Madhya Pradesh Jabalpur India Koneru Lakshmaiah Education Foundation Department of Csit Andhra Pradesh Guntur India Department of CSE Rathinam Technical Campus Tamilnadu Coimbatore India Nielit Uttar Pradesh Gorakhpur India University School of Business Chandigarh University Punjab Mohali India

ISBN: (纸本)9798350322842

Underwater wireless sensor networks (UWSNs) have come to rely heavily on localization technology due to their usefulness in a wide variety of contexts. Multi-sensor underwater surveillance has been an important area of study for both military and civilian uses. UWSNs employ measurement quantization to send data from individual sensors to the fusion Centre in order to accomplish centralized tracking/fusion despite bandwidth constraints. Yet, due to its non-linear nature, azimuth information is difficult to quantify at the measurement level. This work presents a solution by distributing the tracking and quantizing the local estimates in order to increase available bandwidth and decrease the computational burden. Yet, underwater acoustic communications have a very low bandwidth because of the temporal and geographical diversity of sound channels. Data quantization helps decrease the length of information sent from local sensors to the fusion Centre, which can help alleviate network congestion. Although quantization might lessen the burden on a network's budget, the information loss that ensues from the process also leads to subpar tracking performance. This work presents a target tracking system based on optimum quantization to address this issue. Namely, it reduces the extra covariance introduced by quantization in low-bit quantized measurements, hence enhancing their tracking efficiency. The simulation results show that our method outperforms the standard uniform quantization-based target tracking technique and that the increase in data length has a negligible impact on its performance. The proposed technique has been tested in simulation and shown to effectively reduce localization errors and reduce the burden of data transfer in massive 3D submerged sensor nodes. © 2023 ieee.

关键词： Target tracking

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Research of Seismic Streaming Storage Based on Druid 23

Research of Seismic Streaming Storage Based on Druid

引用

23rd ieee international conference on High Performance computing and Communications, 7th ieee international conference on Data Science and systems, 19th ieee international conference on Smart City and 7th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Gao, Bing Chen, Jie Zou, Qijie Qin, Jing School of Information Engineering Dalian University Dalian Key Laboratory of Smart Medical and Health Dalian China School of Software Engineerin Dalian University Dalian Key Laboratory of Smart Medical and Health Dalian China

ISBN: (纸本)9781665494571

Along with the growth of seismic observation networks, the amount of seismic observation data is also increasing rapidly with the form of fast arrival stream, and it is an important and challenging task to store seismic data in time. However, two bottlenecks (slow read/write speed, poor user concurrency) still make the practical applications difficult. We proposes an Apache Druid-based storage solution for seismic observation data streams. The solution is more adaptable to the read/write requirement of large-scale seismic data streams. Specifically, we achieve real-time observation for two aspects: (I) using Kafka as a distributed message exchange system;and (II) implementing accesses and exchange with massive seismic stream data onto the Kafka indexing service provided by Druid. The experimental results show that the Druid-based temporal data storage solution has better stream input and real-time query performance compared with the existed Hbase storage method. © 2021 ieee.

关键词： Concurrent computing Smart cities Time series analysis Memory distributed databases Real-time systems Task analysis

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Fault Section Locating Method in Distribution Network with distributed Generators Based on Adaboost Ensemble Learning Algorithm 3

Fault Section Locating Method in Distribution Network with D...

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3rd international conference on Power systems and Electrical Technology, PSET 2024

作者： Pan, Shi Gao, Jipu Ma, Haoyu Zhang, Yuanyuan Bi, Ran Xin, Mingyong Wu, Shilin Hu, Jun Tsinghua University Department of Electrical Engineering Beijing100084 China Institute of Guizhou Power Grid Co. Ltd. Electric Power Research Guiyang550002 China

ISBN: (纸本)9798350353204

Small current grounding systems are widely used in medium and low voltage distribution networks. Distribution networks are prone to ground faults. It is very important to locate the fault quickly. The access to distributed power sources has changed the topology of the small current grounding system. It causes significant changes in the current characteristics of the system when a ground fault occurs. Many traditional distribution network fault section location algorithms which based on the direction of zero-sequence current and the direction of zero-sequence current power flow during fault are not useful. It is very important and urgent to develop a new and effective fault location algorithm for distribution network. With the development of artificial intelligence technology, machine learning algorithms are increasingly capable of extracting and analyzing complex data features. This paper proposes a distribution network fault section location algorithm based on wavelet packet transform and Adaboost ensemble learning algorithm. An improved ieee33 node distribution network model with distributed generators is established with PSCAD/EMTDC. Different types of fault data and Different section locations fault were simulated. Using wavelet packet transform, the zero-sequence current time-frequency matrix of signals in each section of the distribution network can be obtained. The three-phase current signals are also added to form a feature matrix. The Adaboost ensemble learning algorithm is used to train the feature matrix. The parameters of the model are optimized until the fault can be located effectively. The fault section location accuracy can reach 99.8%. The proposed method was used for training and verification, and the rationality and applicability of the proposed method were demonstrated. © 2024 ieee.

关键词： Power distribution faults

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Renewable DG Integration in the Unbalanced Distribution System with Impact of EV Penetration for Sustainable Operation 3

Renewable DG Integration in the Unbalanced Distribution Syst...

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3rd ieee international conference on Smart Technologies for Power, Energy and Control, STPEC 2023

作者： Kumar, Abhinav Kumar, Sanjay Sinha, Umesh Kumar Bohre, Aashish Kumar Nit Jamshedpur Electrical Department Jamshedpur India Nit Durgapur Electrical Department Durgapur India

ISBN: (纸本)9798350304732

Electric vehicle loads are becoming more and more useful in distribution systems, and their unbalance load behaviour has an impact on the bus voltage profile and phase angle distortion. DG systems can be implemented into already-existing distribution networks to improve the system's power quality. Clean, dependable power is needed today. DG is frequently employed to link electricity producing facilities to the grid or to meet high energy demand. Renewable DG systems can lessen electricity losses and improve grid resilience while also assisting in the provision of clean energy by reducing dependency on centralised power generation. Renewable DG systems can not only help to provide clean energy but also minimise electricity losses and increase grid resilience. The network capacity, per phase voltage stability, and quality of power are all impacted by the integration of renewable DG systems into distribution systems. In both balanced and unbalanced case conditions, DG was integrated with the ieee 69 and modified ieee 69 bus in this study. To optimise the voltage profile and aid in the minimising of loss, the best location for renewable DG can be calculated. © 2023 ieee.

关键词： and multi-objective functions (MOF) Backward-forward distributed generation (DG) Distribution network (DN) ieee 69 bus Renewable energy sources (RES)

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2023 ieee 3rd international conference on Sustainable Energy and Future Electric Transportation, SeFet 2023

2023 IEEE 3rd International Conference on Sustainable Energy...

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3rd ieee international conference on Sustainable Energy and Future Electric Transportation, SeFet 2023

ISBN: (纸本)9798350319972

The proceedings contain 253 papers. The topics discussed include: levitation of a flat steel plate for MagLev vehicles;horizontal axis wind turbine pitch actuation fault and reaching law based sliding mode controller performance analysis;state-of-the-art on light-emitting-diode drivers and related technologies;low device count based power converter for electric vehicle charging application from grid;novel red bellied malimbe swarm optimization algorithm for active power loss diminution in transmission network;analyzing the effect of choke placement on differential-mode supra-harmonics in variable frequency drives: new standardization;design of an air-based thermal management and predictions of thermal characteristics of lithium-ion cell using 1D numerical model;delicate remarks in simultaneous placement of distributed energy generators and reactive power compensators in variable loading power systems;an empirical analysis of electric vehicle in urban transportation market using deep-learning techniques;and reinforcement learning based cost-effective smart home energy management.

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PipePrune: Pipeline Parallel Based on Convolutional Layer Pruning for distributed Deep Learning 23

PipePrune: Pipeline Parallel Based on Convolutional Layer Pr...

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作者： Tan, Daojun Jiang, Wenbin Qin, Shang Jin, Hai School of Computer Science and Technology Huazhong University of Science and Technology Natl. Eng. Res. Ctr. for Big Data Technol. and Syst. Serv. Comp. Technol. and Syst. Lab Cluster and Grid Comp. Lab Wuhan430074 China

ISBN: (纸本)9781665494571

Benefitting from the combination of the idea of pipeline with model parallelism and data parallelism, pipeline parallelism improves the efficiency of distributed deep learning systems significantly. However, suffering from the bubbles and gaps caused by the imbalance of different stages in pipeline, it can not output ideal performance yet. To explore the potential of pipeline parallelism further, we propose a novel approach called PipePrune, which adds a convolutional layer pruning strategy to pipeline creatively to reduce the bubbles and gaps. For the convolutional layers with heavy overheads, some unimportant kernels are pruned by the measurement of the L1-norm. This approach makes the processing overheads of different pipeline stages more balanced. The experimental results show that, compared with state-of-the-art pipeline methods, PipePrune can improve the training speeds obviously (e.g. for ResNet50 on ImageNet, about 30% speed improvement is realized with only 1.1% loss of training accuracies). © 2021 ieee.

关键词： Training Deep learning Smart cities Pipelines Neural networks distributed databases Parallel processing

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distributed Service Placement in Ultra-Dense Edge computing: A Game-Theoretical Approach 23

Distributed Service Placement in Ultra-Dense Edge Computing:...

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作者： He, Junyi Zhang, Di Li, Xishuo Zhou, Yuezhi Zhang, Yaoxue School of Software Engineering Beijing Jiaotong University China School of Science and Engineering The Chinese University of Hong Kong Shenzhen China School of Computer Science and Engineering Beihang University China Tsinghua University Department of Computer Science and Technology China

ISBN: (纸本)9781665494571

Ultra-dense mobile edge computing (MEC) is expected as an effective approach to provide services with ultra-low latency and massive connectivity, which is extremely important for delay-sensitive applications. In this paper, we study service instance (SI) placement for delay-sensitive applications in ultra-dense MEC, which decides where to place applications and the required data (programming codes and datasets). In general, the SI placement problem is a combinatorial optimization and usually does not have low-complexity optimal solutions. Existing centralized policies are difficult to implement due to the high complexity, especially when edge servers are densely deployed in the ultra-dense network (UDN). To design an approach that can make SI placement decisions quickly and efficiently, this paper investigates a distributed strategy for multi-user multi-server edge systems in UDN. We first formulate the SI placement problem as a non-linear combinatorial optimization, which is proven to be NP-hard to compute a centralized optimal solution. Then, we propose an uncooperative game to design a low-complexity distributed algorithm. We further analyze the properties of the game and prove the existence of pure strategy Nash Equilibrium. A polynomial-complexity distributed algorithm is proposed to get the Nash Equilibrium. Theoretical analysis shows the algorithm's convergence and the bound of the price of anarchy (PoA), which serves as a performance guarantee in the worst-case scenarios compared to the global optimum. Numerical results validate the convergence and near-optimal performance of the proposed distributed algorithm. © 2021 ieee.

关键词： Performance evaluation Games Reinforcement learning Nash equilibrium Servers distributed algorithms Ultra-dense networks

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