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Aprus: An Airborne Altitude-Adaptive Purpose-Related UAV system for Object Detection

Aprus: An Airborne Altitude-Adaptive Purpose-Related UAV Sys...

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IEEE International conference on High Performance Computing and Communications (HPCC)

作者： Weiqiang Wang Haiyang Chen Xingzhou Zhang Wei Zhou Weisong Shi Engineering Research Center of Cyberspace Yunnan University Kunming China School of Software Yunnan University Kunming China Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Department of Computer and Information Sciences University of Delaware Newark DE USA

Unmanned aerial vehicle (UAV) system plays an important role in new edge scenarios such as disaster relief, situational awareness, and so on. In order to improve efficiency, computing tasks such as object detection are carried out on the drone-mounted computing unit. However, there is a trade-off between flight altitude and mission accuracy. Higher altitudes result in smaller images, which influence the accuracy. In comparison, shorter altitudes reduce the difficulty of detection while decreasing the recognition range, which affects user experience. therefore, this paper proposes an airborne altitude adaptive UAV system, Aprus, which selects the most suitable object detection models based on a self-adaptation strategy at different altitudes. the selection strategy is based on a purpose-related evaluation indicator, PEI. It comprehensively considers the model's accuracy, recall, and inference speed at the current altitude according to the user's purpose. Moreover, Aprus sends the original image to a divider instead of scaling the image before pushing it to the model, thus ensuring that the original picture information will not be lost. To evaluate the system, we build a high-resolution UAV dataset with altitude, UDWA, which contains 46037 images. From the experiments, Aprus obtained 58.52% mAP, 94.17%mAP 50 , 66.17%mAR, 1.61FPS results on DJI Manifold 2G when the purpose is set to Balance mode, and the system can be adjusted by multiple preset purposes or according to the user customs.

关键词： Meters Manifolds Adaptation models Image resolution Atmospheric modeling Object detection Autonomous aerial vehicles

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Autonomous Graph Mining Algorithm Search with Best Speed/Accuracy Trade-off 20

Autonomous Graph Mining Algorithm Search with Best Speed/Acc...

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20th IEEE International conference on Data Mining (ICDM)

作者： Yoon, Minji Gervet, theophile Hooi, Bryan Faloutsos, Christos Carnegie Mellon Univ Pittsburgh PA 15213 USA Natl Univ Singapore Singapore Singapore

ISBN: (纸本)9781728183169

Graph data is ubiquitous in academia and industry, from social networks to bioinformatics. the pervasiveness of graphs today has raised the demand for algorithms that can answer various questions: Which products would a user like to purchase given her order list? Which users are buying fake followers to increase their public reputation? Myriads of new graph mining algorithms are proposed every year to answer such questions - each with a distinct problem formulation, computational time, and memory footprint. this lack of unity makes it difficult for a practitioner to compare different algorithms and pick the most suitable one for a specific application. these challenges - even more severe for non-experts - create a gap in which state-of-the-art techniques developed in academic settings fail to be optimally deployed in real-world applications. To bridge this gap, we propose AUTOGM, an automated system for graph mining algorithm development. We first define a unified framework UNIFIEDGM that integrates various message-passing based graph algorithms, ranging from conventional algorithms like PageRank to graph neural networks. then UNIFIEDGM defines a search space in which five parameters are required to determine a graph algorithm. Under this search space, AUTOGM explicitly optimizes for the optimal parameter set of UNIFIEDGM using Bayesian optimization. AUTOGM defines a novel budget-aware objective function for the optimization to incorporate a practical issue - finding the best speed-accuracy trade-off under a computation budget - into the graph algorithm generation problem. Experiments on real-world benchmark datasets demonstrate that AUTOGM generates novel graph mining algorithms with the best speed/accuracy trade-off compared to existing models with heuristic parameters.

关键词： automation unified framework optimization

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Effective system Level Liveness Verification 20

Effective System Level Liveness Verification

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20th International conference on Formal Methods in Computer-Aided Design, FMCAD 2020

作者： Fedotov, Alexander Keiren, Jeroen J.A. Schmaltz, Julien Eindhoven University of Technology Eindhoven Netherlands Ict Group Eindhoven Netherlands

ISBN: (纸本)9783854480426

the language xMAS has been designed by Intel with the purpose of modelling and verification of hardware. Recently, the language was extended with finite state machines to make it more expressive [19]. Furthermore, it was shown how to prove liveness of such extended xMAS networks [19]. Unfortunately, we demonstrate that the proof technique is unsound. We provide an alternative approach which we have carefully proven to be correct. Moreover, we show that our approach scales very well, which makes it possible to prove liveness properties at the system level. In particular, we show that using our approach, it is possible to verify a power control architecture composed of 1299 state machines representing 50 power domains where each domain contains 5 master and 5 slave devices. Proving liveness of this system takes less than 10 minutes. © 2020 FMCAD Association.

关键词： modeling languages

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Analysis of Passenger Transportation Structure optimization Based on Travel Mode Selection 20

Analysis of Passenger Transportation Structure Optimization ...

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20th COTA International conference of Transportation Professionals (CICTP) - Advanced Transportation, Enhanced Connection

作者： Yu, Fengjun Zhang, Bing Huang, Nana East China Jiaotong Univ Sch Transportat & Logist Nanchang Peoples R China

ISBN: (纸本)9780784483053

this paper focuses on the optimization of the passenger transport structure in the passenger transportation corridor. Firstly, we use the residual gray prediction model to predict the total demand of the passenger transport market. Secondly, the structural equation model (SEM) is applied to analyze the latent variables that affect the traffic mode choosing behaviors in the passenger transportation corridor. Based on the maximum utility theory, the travel mode utility function of the original Logit model is improved and the SEM-Logit integration model considering the latent variables is constructed to determine the share rate of different travel modes. Finally, we analyze the supply and demand of different transportation modes to judge saturation, proposing a method of optimizing the structure of passenger transportation to achieve mutual coordination between the different modes of transport and form benign competition in the passenger transport system.

关键词： Residual gray prediction model SEM-Logit integration model optimization of passenger transport structure Share rate

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Algorithms and Scenarios of Online Decision Support system for Selection of the Distribution Laws of positive Random Variables 20th

Algorithms and Scenarios of Online Decision Support System f...

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20th International conference on Mathematical modeling and Supercomputer Technologies, MMST 2020

作者： Anna, Ivleva Sergey, Smirnov Samara Federal Research Scientific Center RAS Institute for the Control of Complex Systems RAS Samara443020 Russia

ISBN: (纸本)9783030787585

the problem of making online decision support system for selecting the two-parametric distribution law of a continuous positive random variable with a finite second moment is considered. Algorithms and scenarios of the system operation are given. the main priority is a practical application-oriented approach based on minimal data sets and user’s criteria to select the most appropriate type of distribution law out of a finite set of models. the proposed algorithm for selecting the distribution law of random variables is based on a natural factorization of the space of empirical characteristics – the average and MSD. Differential entropy;graphs of densities, distribution functions, and failure rates;scatter plots and a table of metrics are applied to visually compare the distribution laws. To rank the distribution laws, the following simple and intuitive criteria, focused on solving practical problems, are proposed for a user (engineer, economist, biologist, etc.): maximization of the differential entropy, fitting empirical quantiles, fitting empirical moments of higher orders, availability of analytically defined restoration function, behaviour of the intensity function, and the possibility of decomposition into exponential phases. Online decision support system is being developed in Python using the Dash framework. the following Python libraries are used for calculations: math, numpy, random2, scipy, sympy, and plotly module for graphical visualization. the decision support system can be applied in combination with other existing methods for selecting the distribution law of a random variable. © 2021, Springer Nature Switzerland AG.

关键词： Decision support systems

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An Adaptive RPC Mechanism for Performance and Node Fault Tolerance optimization in HDFS

An Adaptive RPC Mechanism for Performance and Node Fault Tol...

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IEEE International conference on High Performance Computing and Communications (HPCC)

作者： Jingyu Zhang Zhengwen Shu Lailong Luo School of Computer & Communication Engineering Changsha University of Science & Technology Changsha China Science and Technology on Information Systems Engineering Laboratory School of Systems Engineering National University of Defense Technology Changsha China

With the rapid development and evolution of information technologies, the big data industry has been experiencing exponential explosive data growth. Since the huge business and research value behind the large-scale data, big data technology has become one of the hotest research fields in academia and industry. To the big data, storing and processing the data is core function of the file systems. Hadoop Distributed File system (HDFS) is the most typical distributed big data architecture, which has the characteristics of high reliability, high fault tolerance, and low hardware cost. HDFS provides the efficient task implementation and fault tolerance among nodes by Remote Procedure Call (RPC) mechanism. However, the traditional RPC mechanism has remarkable defects with the fixed timing method, and cannot quickly establish the relationship between node downtime and network congestion. In this paper, we propose an improved adaptive RPC mechanism for node fault tolerance and performance. the proposed method classifies nodes by the data block access statistic, and dynamically adjusts the RPC interval time. this method can be used to reduce the networking traffic and processing pressure of NameNode nodes, and improve the I/O and task performance. through the node classification, an inrack method is used to achieve better performance on fault tolerance. Eventually, we design the extensive experiments to evaluate the proposed method, and experimental results show it improves the performance compared with state-of-the-art method.

关键词： Industries Fault tolerance Adaptive systems Heart beat File systems system performance Fault tolerant systems

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Grid Voltage Modulated Direct Power Control for Output Smoothing in Battery Energy Storage systems 20

Grid Voltage Modulated Direct Power Control for Output Smoot...

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20th International conference on Control, Automation and systems (ICCAS)

作者： Hong, Yeon Joo Jeong, Yong Woo Chung, Chung Choo Hanyang Univ Dept Elect Engn Seoul 04763 South Korea Hanyang Univ Dept Elect Bioengn Seoul 04763 South Korea

ISBN: (纸本)9788993215199

this paper proposes a sliding mode control (SMC) method for the grid voltage modulated direct power control(GVM-DPC) of Energy Storage systems and Power Conversion system (ESS/PCS), which can control the instantaneous active power and reactive power directly. Wind power (WP) can cause serious stability problems in the power system because of its high variability depending on wind speed. To solve this problem, many power generation companies or grid operators have begun to use ESS. the conventional control method needs to use Phase-Locked-Loop (PLL), which extracts a phase angle of the grid required for the controller because it is modeling in d - q frame. this PLL performance affects the transient performance of ESS/PCS systems. We show the proposed SMC for the GVM-DPC algorithm enhances the tracking performance of the output power. We validate the proposed SMC for the GVM-DPC algorithm with MATLAB/Simulink and OPAL-RT (real-time simulator) environment systems. It turns out that the proposed method shows improved tracking performance over other conventional controllers.

关键词： Direct Power Control Energy Storage system Wind Power Fluctuation Nonlinear Control

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A multi-objective and multi-decision maker approach for the balancing market in distribution grids in presence of aggregators 7

A multi-objective and multi-decision maker approach for the ...

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7th International conference on Control, Decision and Information Technologies (CoDIT)

作者： Ferro, G. Minciardi, R. Parodi, L. Robba, M. Rossi, M. Univ Genoa Dept Informat Bioengn Robot & Syst Engn Genoa Italy Univ Genoa Dept Naval Elect Elect & Telecommun Engn Genoa Italy

ISBN: (纸本)9781728159539

A multi-objective optimization problem is here formalized for a distribution grid in which are present both traditional generators and aggregators of microgrids, buildings, or general local prosumers. At the lower level, generators and aggregators want to maximize their profit, taking into account the limits of the flexibility they can sell. At the higher level, the distribution system operator (DSO) receives power/price bids from market participants and, based on technical and economic considerations, decides which bid to accept. For the lower-level decision problem, the Karush Khun Tucker (KKT) conditions are developed and included as constraints within the higher-level optimization problem. the resulting optimization problem is applied to a modified IEEE 13-bus system.

关键词： Generators optimization Reactive power Economics Information technology Distribution networks modeling

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Engineering Platform as Integrated Software for Model Mediated Research 20

Engineering Platform as Integrated Software for Model Mediat...

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20th International conference on New Trends in Intelligent Software Methodologies, Tools and Techniques (SoMeT)

作者： Horvath, Laszlo Kovacs, Levente Obuda Univ Doctoral Sch Appl Informat & Appl Math Becsi U 96-B H-1037 Budapest Hungary

ISBN: (纸本)9781643681955;9781643681948

Engineering software platform supports engineering activities in continuously widening disciplinary area of complex systems operated industrial and commercial products and other engineering achievements. Engineering activities increasingly include research extending the conventional product lifecycle engineering to the whole innovation cycle. Comprehensive engineering platform comprises wide range of integrated software solutions to manage complex model systems to represent situation controlled autonomous products and offers all software solutions necessary for the integrated innovation and life cycle. By now, engineering platforms are amongst the largest and most complex applications of advanced software. this paper reports recent contributions to concept and methodology of research integration representations for engineering model systems using research capabilities of engineering platform. First, concept on model organized research project (MORP) is introduced. MORP is a new model system based concept of research project which is managed using capabilities of software organized in these platforms. MORP relies on the formerly defined concept of model mediated research (MMR) which is extended to research in situation control of autonomous functions of the represented systems operated engineering achievements recognizing that situation control reorganizes engineering related research to a great extent. Following this, connection of MORP with software which provides situation based control for physical execution in cyber physical system (CPS) is analyzed and discussed. the MMR based MORP is about pilot projecting at the recently established virtual research laboratory (VRL) at the Doctoral School of Applied Informatics and Applied Mathematics (DSAIAM) at the Obuda University.

关键词： modeling software platform research eligible engineering model system model organized research project extended model mediated research

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An RL based Approach for thermal-Aware Energy Optimized Task Scheduling in Multi-core Processors

An RL based Approach for Thermal-Aware Energy Optimized Task...

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International conference on VLSI Design

作者： Sudipa Mandal Krushna Gaurkar Pallab Dasgupta Aritra Hazra IIT Kharagpur West Bengal India

In order to cope up with the growing performance demands, rapid increase in the transistor density in modern on-chip cores has made power dissipation a primary concern for the chip-designers. Chip temperature surpasses thermal limits at multiple hot-spots which significantly affects its performance and reliability. this work explores the possibility of readjusting the task schedules intelligently under real-time constraints, so that the on-chip power and thermal profiles remain within admissible limits. Our target platform is a homogeneous multicore environment with Dynamic Voltage and Frequency Scaling (DVFS) capabilities. We use multi-objective optimization techniques to restrict power dissipation under thermal constraints. We also use Reinforcement Learning (RL) using Proximal Policy optimization (PPO) to readjust task schedules based on a set of proposed reward functions and energy optimization processes. We show the efficacy of our methodology by running the algorithm on a model test case and comparing the results with other state-of-the-art methods.

关键词： Schedules Multicore processing Reinforcement learning Very large scale integration Scheduling system-on-chip Power dissipation

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