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A Blockchain Query optimization Method Based on Hybrid Indexes 20th

A Blockchain Query Optimization Method Based on Hybrid Index...

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Proceedings of the 20th Web Information systems and Applications conference, WISA 2023

作者： Wang, Junyan Shen, Derong Nie, Tiezheng Kou, Yue Northeastern University Shenyang110004 China

ISBN: (纸本)9789819962211

Blockchain technology possesses the characteristics of decentralization and immutability, making it widely applicable in various fields. However, existing blockchain systems display weak performance in terms of data management, typically only supporting hash-based transaction querying. Current research on query methods usually involves synchronizing data with external databases, using external query engines, or building indexes to improve query performance. In index-based research methods, most blockchain systems build indexes within blocks to enhance query efficiency, but this does not reduce the time overhead of traversing all blocks. Additionally, most indexes only support a specific query type. In this paper, we propose a highly efficient indexing structure that divides data querying into two steps: first, obtaining potential blocks from the index structure that may contain the desired data, and then searching for the specific data records within those blocks. the indexes are further divided into numerical indexes and character indexes based on the attributes being indexed. We describe the construction and use of these two index structures for efficient data querying. As invalid blocks are filtered out, system query efficiency is greatly improved. the numerical index structure further supports range queries and top-k queries on this attribute, enhancing query capabilities. We also conduct experiments to verify the performance of our indexing structure. Results demonstrate that compared with baselines, our proposed index structure improves query performance, and offers a diverse range of query types. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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Tuning Multi Object Tracking systems using Bayesian optimization 24

Tuning Multi Object Tracking Systems using Bayesian Optimiza...

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24th IEEE International conference on Information Fusion (FUSION)

作者： Fleck, Tobias Zoellner, J. Marius FZI Res Ctr Informat Technol Dept Tech Cognit Syst TKS Karlsruhe Germany

ISBN: (纸本)9781737749714

Tracking-by-Detection has become the major paradigm in Multi Object Tracking (MOT) for a large variety of sensors. Regardless of the type of tracking system, hyper parameters are often chosen manually instead of doing a structured search to reveal the full potential of the system. In this work we tackle this problem by utilizing Bayesian optimization (BO) to tune tracking systems, enabling to find the best combination of hyper parameters for Gaussian Mixture Probability Hypothesis Density Trackers (GM-PHD) in two different tracking applications. We use the Tree-structured Parzen Estimator (TPE) algorithm [1] [2] with an Expected Improvement (EI) acquisition function as a blackbox optimizer. TPE supports to conveniently incorporate domain expert knowledge by modeling prior probability distributions of the search space. In our experiments we use the popular MOTA metric as optimization objective. Evaluation is performed in a simulation scenario with an in depth discussion of the found parameters and a real world example that uses the MOT-20 challenge dataset [3] demonstrates the unconditional applicability of the approach. We finish with a conclusion on Bayesian optimization for MOT systems and future research.

关键词： Multi Object Tracking (MOT) Random Finite Set Bayesian optimization Gaussian Mixture PHD Filter Machine Learning

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Implementation and Comparative Assessment of MPPT Techniques in MPC Based Grid-connected PV system

Implementation and Comparative Assessment of MPPT Techniques...

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Eurocon

作者： Jubaer Ahmed Prabhat R Bana Mohammad Amin School of Computing Engineering & Built Environment Edinburgh Napier University Edinburgh United Kingdom Department of Electric Power Engineering Norwegian University of Science and Technology Trondheim Norway

Due to low conversion losses single-stage conversion process for grid-connected PV systems is getting popular. In recent literature, model predictive control (MPC) is introduced in single-stage PV conversion process since it provides better dynamic response compared to the conventional PI controller. However, the performance of different MPPT techniques is still unknown when MPC control is deployed. this work investigated the performance of adaptive P&O, particle swarm optimization (PSO) and Artificial Bee colony-P&O (ABCPO) algorithm in a MPC- based PV inverter control. the algorithms are tested under both uniform irradiance and partial shading in Matlab Simulink and Opal-RT based hardware setups. It is found that, in a 12S30P PV array, adaptive P&O tracks the global MPP faster compared to the other two. Besides thD induced by Adaptive P&O is significantly lower than PSO and ABCPO. It is concluded that adaptive P&O MPPT algorithms is the most suitable and efficient MPPT algorithm method to be deployed while MPC-based inverter control is implemented in single-stage grid-connected PV system.

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End-to-end Integration of OpenTitan Security Features in a Pure RISC-V SoC

End-to-end Integration of OpenTitan Security Features in a P...

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International conference on Synthesis, modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD)

作者： Alberto Musa Emanuele Parisi Luca Barbierato Andrea Acquaviva Francesco Barchi Università di Bologna Bologna Italy Politecnico di Torino Torino Italy

ISBN: (数字)9798350351927

ISBN: (纸本)9798350351934

the RISC-V open-source instruction set architecture (ISA) is gaining popularity in the realm of new processor development. Its maturity allows implementation even in scenarios where security plays a key role. OpenTitan (OT), an open-source silicon Root of Trust (RoT) designed specifically for secure embedded environments is a significant example of this adoption. this study focuses on integrating OT into a system-on-Chip (SoC) exclusively featuring RISC-V architectures. In this configuration, OT serves as a secure co-processor, leveraging its cryptographic accelerators to enhance the performance of cryptographic workloads. A noteworthy aspect of this implementation is the intentional preservation of strong isolation in computation and memory, an essential feature to protect sensitive data, including cryptographic keys and intermediate results of cryptographic tasks. the integration of OT into a complete RISC-V SoC was executed and characterized on an FPGA. the FPGA runs the entire SoC which leverages a specialized communication system between two domains: a Host domain and a Safe domain. the Host domain features a CVA6 processor running Linux, while the Safe domain houses the OT system. During system characterization, the delays introduced by the communication and synchronization system between the Host and Safe domains were measured, along with the performance of cryptographic operations conducted in the Safe domain. Results demonstrate the effectiveness of OT HW/SW integration, compensating for the overhead introduced by the communication and synchronization system between the two domains. this makes the proposed implementation sustainable for various application cases and facilitates its integration into embedded and cyber-physical systems based on secure open-hardware architectures.

关键词： Linux Instruction sets Computer architecture Silicon system-on-chip Cryptography Synchronization Integrated circuit modeling Field programmable gate arrays Hardware acceleration

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Study on optimization of Traffic Emergency Stations Layout in Highway Reconstruction and Extension Sections 21

Study on Optimization of Traffic Emergency Stations Layout i...

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20th and 21st Joint COTA International conference of Transportation Professionals - Advanced Transportation, Enhanced Connection

作者： Sun, Chuanjiao Wei, Panyi RIOH Rd Safety Res Ctr Beijing Peoples R China

ISBN: (数字)9780784483565

ISBN: (纸本)9780784483565

In China, there are many freeways with rapid traffic volume growth, congestion and accidents always happen on these freeways. To solve these problems, the original freeways need reconstruction and extension. During the reconstruction and extension process, the freeway must maintain normal access. Freeway reconstruction and extension will bring pressure to the safety situation of the access part. Traffic accidents will increase and the emergency management is very important. the study focuses on the difference of the traffic accidents characters before and after the reconstruction and extension. To decrease the impact of accidents, the emergency management is studied. the key of the emergency management is layout optimization of traffic emergency stations. the layout optimization of traffic emergency stations is also given according to the theory of system optimization, considering the special freeway reconstruction and extension features. the real He'an freeway with reconstruction and extension in Anhui Province in China are applied to test the study.

关键词： Risk management

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Multi-stage Robust Implicit Decision Rule for Optimal Control Problem of Energy Storage system

Multi-stage Robust Implicit Decision Rule for Optimal Contro...

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IEEE International conference on Automation Science and Engineering (CASE)

作者： Jiexing Zhao Qiaozhu Zhai Yuzhou Zhou Xiaoyu Cao Jianchen Hu Fei Xue Xutao Li School of Automation Science and Engineering and the MOEKLINNS Lab Xi’an Jiaotong University Xi’an China Ningxia Electric Power Research Institute Ningxia China

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

the optimal control problem including random variables is difficult to solve. Existing methods typically rely on defining explicit decision functions to make the problem tractable. However, in practical numerical testing, we observed that some strongly coupled constraints, such as energy storage level limits, will impose strict restrictions on these simplified decision functions, potentially leading to significantly suboptimal solutions. Motivated by these challenges, this paper proposes a multi-stage robust implicit decision rule for the scheduling problem of energy storage systems. the main idea is to find an explicitly feasible decision function space to guarantee the multi-stage operating feasibility. When random variables are observed, decisions are adaptively optimized within the feasible decision space by solving a straightforward mathematical programming. Explicit decision functions are not required, ultimately enhancing the feasibility and optimality of the stochastic optimization for energy storage systems. Numerical tests are implemented on a real-world microgrid, verifying the effectiveness of the proposed method.

关键词： Uncertainty Costs Optimal control Microgrids Aerospace electronics Random variables optimization Energy storage Testing Mathematical programming

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Practical Solutions to Limit Computational Burden of UC in Island Power systems

Practical Solutions to Limit Computational Burden of UC in I...

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International conference on European Electricity Market, EEM

作者： Enrique Lobato Pedro Sánchez-Martín Mohammad Rajabdorri Lukas Sigrist Institute of Research in Technology (IIT) of the School of Engineering (ICAI) Comillas University Alberto Aguilera 23 Madrid Spain

ISBN: (数字)9798350381740

ISBN: (纸本)9798350381757

Unit commitment (UC) models used in real-life island power systems (IPSs) require complex modelling details and low execution times since they have to be launched repeated times for different assumptions and changing conditions. For this reason, system operators and power generation companies discard for daily analysis sophisticated models such as stochastic, robust or frequency-constrained UC. Instead, they prioritize the use of deterministic standard UC (STUC), where units are scheduled imposing a static reserve criterion such that the amount of available spinning reserve is sufficient to cover expected disturbances. this paper outlines why in IPSs the spinning reserve requirement increments dramatically the computational burden of a STUC, proposing practical solutions to contain runtimes. Proposed solutions include incrementing convergence tolerance, dividing a weekly optimization in seven sequential daily problems and formulating alternative equations for the reserve constraints. Results of real-life small and big size Spanish IPS will demonstrate how execution times are drastically diminished with acceptable loss of accuracy.

关键词： Runtime Accuracy Stochastic processes Companies Power system stability Mathematical models Spinning

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modeling of Electrical Insulation system of Turbogenerators with a Higher Value of Coefficient of thermal Conductivity and Associated Ecological Perspectives and Economic Benefit

Modeling of Electrical Insulation System of Turbogenerators ...

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conference on Diagnostics in Electrical Engineering (Diagnostika)

作者： Tetjana Tomaskova Pavel Trnka Department of Materials and Technology Faculty of Electrical Engineering University of West Bohemia Pilsen Czech Republic

ISBN: (数字)9798350361490

ISBN: (纸本)9798350361506

New technologies, production of electricity, and energy savings play a significant role in the rise of the economic potential of each country and have a significant impact on the environment. the growing demand for electrical energy and the use of turbogenerators in electricity production have led to their irreplaceable role. History shows that at the end of the 20th century and at the beginning of the 21st century usable energy from fossil fuels is running out, and renewable energies are still not developed enough to offer a full replacement. therefore, any attempt to improve the quality of turbogenerators is of considerable value. Electrical insulation systems (EIS) of turbogenerators have been developed and optimized during the last 60 years. this article discusses how to improve the removal of heat from electrical insulation systems and at the same time increase the performance of high-voltage electrical equipment thereby reducing weight and reducing their dimensions by increasing the value of the coefficient of thermal conductivity of electrical insulation systems. An increase in thermal conductivity can be achieved by adding a filler with a higher thermal conductivity coefficient to electrical insulation systems. By modeling the distribution of the temperature field with a change in the coefficient of thermal conductivity, the assumption that fillers can affect the thermal properties of the electrical insulation system was verified. the economic benefit of an electrical insulation system with a higher value of the thermal conductivity coefficient is stated at the end of this article.

关键词： Economics Insulation Electricity Turbogenerators Stator windings Production Conductivity thermal conductivity thermal loading Resistance heating

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Research on LDPC channel coding technology in satellite communication system 21

Research on LDPC channel coding technology in satellite comm...

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IEEE/ACIS 21st International Fall Virtual conference on Computer and Information Science (ICIS Fall)

作者： Nie, Shikang Li, Guangting Liu, Xin Zhang, Xin Lin, Chenchen He, Yifeng Xian Inst Space Radio Technol Xian Peoples R China

this paper discusses in detail the development of several research hotspots of Low-Density Parity Check (LDPC) codes and their joint optimization design with other communication technologies, and points out that LDPC ... 详细信息

ISBN: (纸本)9781728176796

关键词： low-density parity check codes construction of check matrix minimum sum algorithm OFDM HARQ

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Enhanced Variational Quantum Regression for Non-Linear Curve Fitting in Higher Dimensions

Enhanced Variational Quantum Regression for Non-Linear Curve...

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International Bhurban conference on Applied Sciences & Technology, IBCAST

作者： Abdul Basit Ali Hassan Jamal Kashif Hameed Saif Ullah Rab Nawaz CE&ME NUST Islamabad Pakistan CESAT Islamabad Pakistan

ISBN: (数字)9798350308259

ISBN: (纸本)9798350308266

the advent of quantum computing, characterized by limited resources and qubits, the large circuit depth presents a substantial challenge for quantum algorithms designed to solve linear systems of equations. this paper proposes an innovative approach, named Enhanced Variational Quantum Regression (EVQR), specifically designed for solving non-linear curve fitting problems in higher dimensions and orders. It is a hybrid quantum-classical algorithm which not only surpasses the limitations of traditional one-dimensional solvers but also leverages variational principles to address complex problems. Our methodology centers around an initial solution known as an “ansatz” parameterized by a function. By employing quantum circuits, qubits are prepared to efficiently compute inner products in the quantum domain, facilitating accelerated and powerful calculations. the estimated inner product is then transmitted back to the classical computer, where classical optimization techniques such as Levenberg-Marquardt are employed to estimate the function parameters. this iterative process is repeated until the estimation reaches a desired level of accuracy within a predefined tolerance. Notably, we empirically observe that the time complexity of EVQR scales efficiently with the system size N. By leveraging the capabilities of SciPy's curve-fit and the robust optimization techniques of the Levenberg-Marquardt algorithm, our approach overcomes the challenge of higher-dimensional curve fitting. Our primary contribution lies in the fusion of quantum and classical methodologies, a novel integration that, unlike previous quantum approaches, outperforms in terms of performance and accuracy. By combining the strengths of classical optimization and quantum computations, EVQR offers a versatile framework for solving challenging problems, opening new possibilities for data analysis & modeling.

关键词： Quantum computing Accuracy Data analysis Scalability Qubit Estimation Curve fitting Quantum circuit Time complexity optimization

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