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检索条件"主题词=software algorithms"

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Hybrid Adhoc Routing Protocol Implementation in Mobile Adhoc Network Using Firefly Algorithm

Hybrid Adhoc Routing Protocol Implementation in Mobile Adhoc...

引用

International Conference on Circuit, Power and Computing Technologies (ICCPCT)

作者： T. Kadhiravan S. Harshavardhan G. Jeevith K. R. Mahesh Kumar S. Nivas Department of Electronics and Communication Engineering Vel Tech High Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai India

ISBN: (数字)9798350372816

ISBN: (纸本)9798350372823

The corporate 5G demos are important in today's rapidly advancing technological environment. In most areas of information and communications, energy conservation is increasingly a need. New wireless network designs are greatly influenced by this demand. Mobile Ad Hoc Networks (MANETs) are the most emerging area of study as a result of this. High-performance, energy-efficient, and fundamentally flexible routing protocols are possible. Routing protocols are therefore the most crucial component of the MANET. Node mobility disruption is one of the main problems with routing in MANETs; end nodes and intermediate nodes in the network move around a lot, causing frequent path breaks. Thus, this study presents using the Firefly algorithm to construct a hybrid ad hoc routing protocol in mobile ad hoc networks. Link-state and distance-vector routing methods are employed in hybrid routing protocols. In data networks, a Distance-Vector Routing Protocol (DVRP) chooses the optimal path for data packets depending on distance. A routing protocol called Link-State Routing Protocol (LSRP) enables routers in a computer network to share routing data. The Firefly algorithm (shows best accuracy 92.7% and specificity 91.4%), which is integrated into hybrid AODV, is utilized in this study to solve the routing path problem and choose the best path based on the most recent data. This initiative offers data transfer pathways that are more effective. In addition, it provides scalability, load balancing, faster convergence, and effective bandwidth utilization and NS2 software is used for executing this work.

关键词： Measurement Accuracy software algorithms Routing Throughput Routing protocols software

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Machine Learning for Cross-Vulnerability Prediction in Smart Contracts

Machine Learning for Cross-Vulnerability Prediction in Smart...

引用

IEEE International Conference on software Testing Verification and Validation Workshop, ICSTW

作者： Hajra Naeem Manar H. Alalfi Department of Computer Science Toronto Metropolitan University Toronto ON Canada

ISBN: (数字)9798350344790

ISBN: (纸本)9798350344806

Smart contracts are programs that are deployed on blockchain to automate the agreements among users. It is hard to fix a security vulnerability once a smart contract is deployed. Vulnerabilities in smart contracts have raised a lot of concerns. Many automated solutions are proposed to identify these vulnerabilities. Supervised machine learning algorithms require historical data to detect vulnerabilities. These solutions will not work if the historical data for a vulnerability in question is not available. To address this problem, we have proposed to use the historical data of another vulnerability. We identify similar features among the vulnerabilities and use them to build the models. The built models are used to test smart contracts with the type of vulnerability that does not have the historical data. We have conducted experiments on 4 datasets and found that worst case $F_{1}$-score is 73% and the best case is 93% and mostly F 1 -score was more than 80%.

关键词： Training software testing Machine learning algorithms Smart contracts software algorithms Machine learning Prediction algorithms

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Optimization and Dynamic Analysis of a Natural Gas Assisted LCPV/T Triple-generation System

Optimization and Dynamic Analysis of a Natural Gas Assisted ...

引用

Power Energy Systems and Applications (ICoPESA), International Conference on

作者： Zhen Yao Huixia Sheng Yang Liu National Institute of Metrology Beijing China SPIC Zhengzhou Gas Power Generation CO.LTD China

ISBN: (数字)9798350351668

ISBN: (纸本)9798350351675

This paper presents an optimization analysis method of the natural gas assisted low-concentrating photovoltaic/thermal (LCPV/T) triple-generation system. The main energy sources of this triple-generation system are solar energy and nature gas, to achieve the purpose of year-round supply of cooling, heating and electricity to the building. The system comprises of a low-concentrating photovoltaic/thermal system, heat pump, absorption chiller, water tanks, and capillary network. The core of the whole system is the low-concentrating photovoltaic/thermal system, used for space heating, electrical production, space cooling and domestic hot water preheating. In particular, an operation strategy and integrated optimization model are established in order to reduce the life cycle costs. Furthermore, a penalty function is implemented in order to balance lab room comfort with operating costs of the triple-generation system. The construction of the whole system, the realization of the operation strategy and the optimization calculation are all realized by TRNSYS software.

关键词： Photovoltaic systems Costs Heuristic algorithms software algorithms Water heating Space cooling Optimization Natural gas Space heating Resistance heating

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MOLAR-NX: building a PET reconstruction framework for exploring the novel features provided by the NeuroEXPLORER

MOLAR-NX: building a PET reconstruction framework for explor...

引用

IEEE Symposium on Nuclear Science (NSS/MIC)

作者： K. Fontaine J.-D. Gallezot J. Zhang L. He P. Gravel T. Zeng T. Li Y. Li E. Leung X. Sun L. Guo T. Mulnix T. Toyonaga Y. Lu H. Li R. Badawi J. Qi R. Carson Yale University New Haven Connecticut United States of America United Imaging Healthcare Houston Texas United States of America UC Davis Davis California United States of America

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

In this work, the PET reconstruction software, MOLAR (Motion-compensation OSEM Listmode Algorithm for Resolution-Recovery Reconstruction), is updated to support the NeuroEXPLORER (NX) - providing an advanced framework for investigating how the new features of the NX can be incorporated into the reconstruction process (MOLAR-NX). MOLAR’s detector masking feature seamlessly accounts for the detector blocks absent from the shoulder-cutout region of the system. Evaluation through phantom studies demonstrates the framework’s effectiveness as a tool for exploring the impact of depth of interaction (DOI), inter-crystal scatter recovery (ICS), energy and motion correction. Furthermore, MOLAR-NX introduces a new capability for merging listmode data, facilitating the integration of multiple listmode files with independent downsampling control during the reconstruction process. Future work focuses on refining scatter correction methods and assessing contrast recovery.

关键词： Microwave integrated circuits Semiconductor detectors software algorithms Refining Merging Process control Phantoms

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Control Allocation for Optimal and Resilient Operation of the MMC

Control Allocation for Optimal and Resilient Operation of th...

引用

IEEE International Conference on Industrial Technology (ICIT)

作者： Grégoire Le Goff Marc Bodson Maurice Fadel LAPLACE University of Toulouse CNRS INPT Toulouse France Dept. of Electrical and Computer Engineering University of Utah Salt Lake City Utah USA

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

The article proposes a new approach to modular multilevel converter (MMC) control. A key feature is the use of real-time optimization for arm voltage regulation and for balancing of the capacitor voltages in the submodules (SMs). The control allocation (CA) method automatically and optimally distributes the control requirements among a large number of switches. As a benefit, the algorithm can be adapted with almost no modification to accommodate failures. First, a control-oriented approach is used to derive the necessary models. Then, the MMC control architecture is designed. Simulations demonstrate the effectiveness of the approach on an MMC with 50 SMs per arm. Test cases include steady state and transient conditions, as well as operation without and with multiple SM faults.

关键词： Adaptation models Atmospheric modeling Capacitors software algorithms Power system dynamics Control systems Steady-state

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Development of a Lunar Rover Simulator with an Interface for Reinforcement Learning

Development of a Lunar Rover Simulator with an Interface for...

引用

Automation, Control and Robotics Engineering (CACRE), International Conference on

作者： Assawayut Khunmaturod Dong Eui Chang School of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon Republic of Korea

ISBN: (数字)9798350350302

ISBN: (纸本)9798350350319

In this paper, we propose an open-source lunar rover simulator integrated with a reinforcement learning framework. We incorporate lunar environmental effects in our simulator to enhance the rover locomotion realism while employing PyBullet to simulate the dynamics of a multi-degree-of-freedom planetary rover. We also extend our lunar rover simulator to interface with a reinforcement learning framework using OpenAI Gym environment and a compatible training workflow. We demonstrate the success of this integration through an autonomous rover navigation task on the lunar environment in our simulator using two reinforcement learning algorithms, DDPG and TD3. The lunar rover simulator is available at https://***/assawayut/LunarRoverSim and an accompanying video can be accessed at https://***/watch?v=8HMqAkDbpqI.

关键词： Space vehicles Training Navigation Moon software algorithms Reinforcement learning software

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Simplifying Sim-to-Real Transfer in Autonomous Driving: Coupling Autoware with the CommonRoad Motion Planning Framework

Simplifying Sim-to-Real Transfer in Autonomous Driving: Coup...

引用

IEEE Symposium on Intelligent Vehicle

作者： Gerald Würsching Tobias Mascetta Yuanfei Lin Matthias Althoff School of Computation Information and Technology Technical University of Munich Garching Germany

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

Validating motion planning algorithms for autonomous vehicles on a real system is essential to improve their safety in the real world. Open-source initiatives, such as Autoware, provide a deployable software stack for real vehicles. However, such driving stacks have a high entry barrier, so that integrating new algorithms is tedious. Especially new research results are thus mostly evaluated only in simulation, e.g., within the CommonRoad benchmark suite. To address this problem, we present CR2AW, a publicly available interface between the CommonRoad framework and Autoware. CR2AW significantly simplifies the sim-to-real transfer of motion planning research, by allowing users to easily integrate their CommonRoad planning modules into Autoware. Our experiments both in simulation and on our research vehicle showcase the usefulness of CR2AW.

关键词： Couplings software algorithms Full stack Benchmark testing Planning Safety Autonomous vehicles

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Flakyrank: Predicting Flaky Tests Using Augmented Learning to Rank

Flakyrank: Predicting Flaky Tests Using Augmented Learning t...

引用

IEEE International Conference on software Analysis, Evolution and Reengineering (SANER)

作者： Jiaguo Wang Yan Lei Maojin Li Guanyu Ren Huan Xie Shifeng Jin Junchao Li Jian Hu School of Big Data & Software Engineering Chongqing University Chongqing China Peng Cheng Laboratory Shenzhen China University College London London United Kingdom

ISBN: (数字)9798350330663

ISBN: (纸本)9798350330670

The ideal principle of software testing is that test results ought to be deterministic: a test failure indicates the presence of a software bug, while a test success suggests the absence of a bug. Nevertheless, flaky tests break the principle. Flaky tests yield inconsistent results when executed repeatedly under the same conditions. The most straightforward approach runs the tests multiple times to predict flaky tests whereas it is highly time-consuming. Many researchers have proposed efficient approaches to reduce the cost, e.g., recent approaches leverage machine learning techniques for the prediction of flaky tests. However, traditional machine learning primarily focuses on predicting specific instances, which is not conducive to identify flaky tests across an entire project. Therefore, we propose Flakyrank, a ranking framework based on augmented learning to rank to predict flaky tests. The insight is that learning to rank, as compared with traditional machine learning, not only concentrates on individual samples but also optimizes the overall ranking. Since flaky tests constitute a small proportion of the dataset (i.e., approximately 3.6% of the total tests), we utilize generative adversarial networks to generate some synthetic flaky tests to augment the dataset. Based on the augmented dataset, FLAKYRANK treats predicting flaky tests as an information retrieval task, where newly detected flaky tests and test cases serve as queries and documents, respectively. For each newly detected flaky test (i.e., query), FLAKYRANK combines multiple relevant features into a learning to rank model to predict flaky tests candidate tests. We conduct large-scale experiments on different learning to rank models, and the results show that FLAKYRANK with the LambdaMART algorithm yields the best performance. In addition, the experimental results on 23 benchmark projects show that FLAKYRANK outperforms the state-of-the-art predictors.

关键词： software testing Computer bugs software algorithms Machine learning Predictive models Prediction algorithms Information retrieval

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Dynamic Test Case Prioritization in Industrial Test Result Datasets

Dynamic Test Case Prioritization in Industrial Test Result D...

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International Workshop on Automation of software Test (AST)

作者： Alina Torbunova Per Erik Strandberg Ivan Porres Åbo Akademi University Turku Finland Westermo Network Technologies AB Västerås Sweden

ISBN: (数字)9798400705885

ISBN: (纸本)9798350352184

Regression testing in software development checks if new software features affect existing ones. Regression testing is a key task in continuous development and integration, where software is built in small increments and new features are integrated as soon as possible. It is therefore important that developers are notified about possible faults quickly. In this article, we propose a test case prioritization schema that combines the use of a static and a dynamic prioritization algorithm. The dynamic prioritization algorithm rearranges the order of execution of tests on the fly, while the tests are being executed. We propose to use a conditional probability dynamic algorithm for this. We evaluate our solution on three industrial datasets and utilize Average Percentage of Fault Detection for that. The main findings are that our dynamic prioritization algorithm can: a) be applied with any static algorithm that assigns a priority score to each test case b) can improve the performance of the static algorithm if there are failure correlations between test cases c) can also reduce the performance of the static algorithm, but only when the static scheduling is performed at a near optimal level.

关键词： Job shop scheduling Correlation Heuristic algorithms Fault detection software algorithms Dynamic scheduling software

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An Internal Environment Anomaly Detection System for Secondary Water Supply Pump Houses Based on the Improved PatchCore Algorithm

An Internal Environment Anomaly Detection System for Seconda...

引用

Chinese Automation Congress (CAC)

作者： Yongtao Yu Xiaoqiang Lu Junchen Gong School of Automation Shenyang Aerospace University Shenyang China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

With the growing public awareness regarding tap water safety, the secondary water supply pump room, acting as the final checkpoint before water enters homes, plays a crucial role in ensuring a safe internal environment. However, pump rooms face challenges such as disordered spatial distribution and a shortage of maintenance staff, leading to significant difficulties and costs in maintenance and supervision. This paper introduces an anomaly detection system for the internal environment of secondary water supply pump rooms, based on an enhanced PatchCore algorithm. The system is designed to alleviate the burden and costs associated with manual monitoring by providing continuous 24-hour anomaly detection through automated equipment. It incorporates 5G communication and edge computing technologies within edge-end devices, showcasing superior capabilities in data transmission speed, detection efficiency, information security, and intelligent processing. On the software front, the system employs an improved PatchCore algorithm that has been trained and tested on a dataset constructed from real-world scenarios of secondary water supply pump rooms, achieving an AUROC metric of up to 0.996 and an inference speed of 23.6ms per image. Anomaly information from the pump rooms is transmitted to an IOT platform, email, and server for remote access by personnel. This research offers an effective solution for the intelligent monitoring of pump rooms and provides valuable practical insights for safeguarding the security and reliability of secondary water supply systems.

关键词： Costs software algorithms Stability analysis Maintenance software reliability Anomaly detection Water resources Monitoring Edge computing Synthetic data

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