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检索条件"任意字段=7th International Conference on the Art, Science, and Engineering of Programming, Programming 2023"

共 1136 条记录，以下是511-520 订阅

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Navigating Complex Multiclass Classification in High-Dimensional Spaces: A Hybrid Approach

Navigating Complex Multiclass Classification in High-Dimensi...

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international conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

作者： Praneeth Nemani Venkata Surya Sundar Vadali Prathistith Raj Medi Ashish Marisetty Satyanarayana Vollala Department of Computer Science and Engineering IIIT Naya Raipur India Department of Data Science and Artificial Intelligence IIIT Naya Raipur India

Large-scale tabular data classification is a critical task and the complexity arises from the vast amount of structured data generated in these fields, coupled with the challenges of high dimensionality and limited sample sizes. To address these challenges, advanced machine learning algorithms are required to analyze and categorize instances within these datasets effectively. In this work, we propose the usage of a state-of-the-art classifier called XBNet, which combines the strengths of tree-based classifiers and neural networks to tackle large tabular datasets. Our methodology is validated on a dataset with 64 dimensions and 11 classes, showcasing the model's capability to detect patterns and extract relevant features automatically. Furthermore, we employ K-Fold cross-validation to assess the model's performance, achieving an impressive training accuracy of 61.9% and a validation accuracy of 31.7%. these results surpass those of competing algorithms, confirming the superiority of our proposed methodology in handling large-scale tabular data classification tasks.

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Using Knowledge Representation and Task Planning for Robot-agnostic Skills on the Example of Contact-Rich Wiping Tasks

Using Knowledge Representation and Task Planning for Robot-a...

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IEEE international conference on Automation science and engineering (CASE)

作者： Matthias Mayr Faseeh Ahmad Alexander Duerr Volker Krueger Department of Computer Science Faculty of Engineering (LTH) Lund University Lund Sweden

the transition to agile manufacturing, Industry 4.0, and high-mix-low-volume tasks require robot programming solutions that are flexible. However, most deployed robot solutions are still statically programmed and use stiff position control, which limit their usefulness. In this paper, we show how a single robot skill that utilizes knowledge representation, task planning, and automatic selection of skill implementations based on the input parameters can be executed in different contexts. We demonstrate how the skill-based control platform enables this with contact-rich wiping tasks on different robot systems. To achieve that in this case study, our approach needs to address different kinematics, gripper types, vendors, and fundamentally different control interfaces. We conducted the experiments with a mobile platform that has a Universal Robots UR5e 6 degree-of-freedom robot arm with position control and a 7 degree-of-freedom KUKA iiwa with torque control.

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How efficient can hydrogen be? Hydrogen technologies and their limits of optimizibility

How efficient can hydrogen be? Hydrogen technologies and the...

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7th international Hybrid Power Plants & Systems Workshop (HYB 2023)

作者： N. Eggers T. Birth M. Scheffler S. Jentsch A. Hurtado Energy Systems and Infrastructures Fraunhofer Institute for Factory Operation and Automation IFF Sandtorstraße 22 Magdeburg Germany Mechanical Science and Engineering Technische Universität Dresden Dresden Germany

Hydrogen offers excellent potential for cross-sector decarbonization through power-to-gas technologies necessary for climate policy. However, studies show that the planned expansion of electrolysis technologies according to current future scenarios will not produce sufficient quantities of hydrogen. One way to address this challenge is to optimize electrolysis technologies, which would increase efficiency and, at the same time, increase hydrogen yield. this approach raises the question of the limit of optimizability. this paper presents and discusses a model to represent an idealized reference process for water electrolysis. the reference model has the potential of identifying the optimum based on applicable laws of nature and the current state of the art, which can be used as a basis for the process design of an electrolysis cell. Furthermore, it allows the real-time evaluation of the operation of an electrolysis cell and, thus, the investigation of degradation effects.

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Minimizing User Connectivity Costs and Latency Between Controllers and Switch-Controllers for Software Defined Networking 19th

Minimizing User Connectivity Costs and Latency Between Cont...

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Mobile Web and Intelligent Information Systems - 19th international conference, MobiWIS 2023, Proceedings

作者： Viveros, Andres Adasme, Pablo Firoozabadi, Ali Dehghan Department of Electrical Engineering Universidad de Santiago de Chile Avenida Víctor Jara No 3519 Santiago9170124 Chile Department of Electricity Universidad Tecnológica Metropolitana Av. Jose Pedro Alessandri 1242 Santiago7800002 Chile

ISBN: (纸本)9783031397639

In this paper, we consider the problem of assigning users to switches and controllers at minimum connectivity costs. We simultaneously minimize the existing latency between controllers and switch controllers for software-defined networks (SDN). In particular, we propose two mixed-integer quadratic programming formulations and their standard linearization counterparts. All the proposed models are solved with the CPLEX solver. More precisely, the quadratic models are solved with the branch and cut (B &C) algorithm of the solver. Whilst the linear ones are solved with both, the B &C and with the automatic Bender’s decomposition algorithmic option of the CPLEX solver. To the best of our knowledge, this work constitutes a first attempt to propose mathematical formulations while including user connectivity to a backbone software-defined network. Notice that we consider which is the best strategy for connecting users to the backbone, either connecting them to switches or to the controller nodes of the network. Our preliminary numerical results indicate that for most of the benchmark instances considered the second strategy which connects users to switches has a better performance in terms of objective function values. On the other hand, we observe that the linear models offer better performance in terms of CPU times to get the optimal or best objective values. Finally, we see that the linear models can be solved faster with the branch and cut algorithm than using Bender’s decomposition approach. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

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Soft Open Point Planning Method for Active Distribution Network Based on Generative Adversarial Network

Soft Open Point Planning Method for Active Distribution Netw...

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IEEE conference on Energy Internet and Energy System Integration (EI2)

作者： Hao Wang Qiyou Lin Hongxing Wang Yuan Ge Nuo Yu Shinong Wang School of Electrical Engineering Anhui Polytechnic University Wuhu China Wuhu Fanchang District Power Supply Company State Grid Anhui Electric Power Co. Ltd Wuhu China Wuwei City Power Supply Company State Grid Anhui Electric Power Co. Ltd Wuhu China School of Electrical Engineering Anhui Polytechnic University Anhui Institute of Future Technology Wuhu China

With the continuous increase of the penetration rate of distributed generation (DG) in the distribution network, higher requirements have been put forward for the dependable and cost-effective operation of the distribution network. In order to address the impact caused by the intermittent output of a large number of DGs on the distribution network, this article proposes a planning method for soft open point (SOP) using generative adversarial network (GAN). First, to accurately simulate the operating characteristics of DG, a GAN is employed for sce-nario generation. then, operational constraints for distribution networks with SOP are proposed, with the objective function being the minimization of annual total cost. By relaxing and linearizing the original non-convex and non-linear constraints, a second-order cone programming model is derived, and the objective function is solved under the constraints. Finally, the proposed scenario generation algorithm and planning model are analyzed and veriffed on the IEEE 33- node test system.

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A Flooding Attack Detection and Mitigation Technique in Wireless Sensor Networks

A Flooding Attack Detection and Mitigation Technique in Wire...

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international conference on ent Computing and Control Systems (ICICCS)

作者： Makul Mahajan Salil Batra Simarjit Singh Malhi Gursharan Singh School of Computer Science and Engineering Lovely Professional University Phagwara India

Wireless Sensor Networks (WSNs) are made up of sensor nodes with a finite supply of energy that cooperate to accomplish a common goal. WSNs are widely used to carry out a variety of monitoring duties in challenging environments that are difficult to reach and even dangerous. the distributed nature of WSNs makes them vulnerable to a wide range of physical attacks, including eavesdropping, Sybil attacks, node replication attacks, signal or radio jamming, denial of service (DoS) attacks, flooding attacks, node outages, and DoS attacks. In order to stop communicating between source and destination, the flooding outbreak attacks the network with unwarranted bogus route requests. the goal of a data flooding attack is to obstruct the communication between source and destination by flooding the network with an overwhelming amount of useless data packets. Using the networks simulator NS 2.33, this research study has assessed and compared the suggested technique FDMM with native AODV and current state-of-the-art protocols. On an average, the proposed algorithm shows 1.34% and 0.18% increase in PDF, 6.03% and 5.47% increase in throughput, 1.93% and 0.54% increase in average residual energy, 3.30% and 4.09% decrease in end to end delay when compared with state-of-the-art algorithms.

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A Review on AI Algorithms for Energy Management in E-Mobility Services

A Review on AI Algorithms for Energy Management in E-Mobilit...

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conference on Vehicle Control and Intelligence (CVCI)

作者： Sen Yan Maqsood Hussain Shah Ji Li Noel O’Connor Mingming Liu School of Electronic Engineering and SFI Insight Centre for Data Analytics Dublin City University Ireland Nanjing University of Aeronautics and Astronautics China Department of Mechanical Engineering University of Birmingham UK

E-mobility, or electric mobility, has emerged as a pivotal solution to address pressing environmental and sustainability concerns in the transportation sector. the depletion of fossil fuels, escalating greenhouse gas emissions, and the imperative to combat climate change underscore the significance of transitioning to electric vehicles (EVs). this paper seeks to explore the potential of artificial intelligence (AI) in addressing various challenges related to effective energy management in e-mobility systems (EMS). these challenges encompass critical factors such as range anxiety, charge rate optimization, and the longevity of energy storage in EVs. By analyzing existing literature, we delve into the role that AI can play in tackling these challenges and enabling efficient energy management in EMS. Our objectives are twofold: to provide an overview of the current state-of-the-art in this research domain and propose effective avenues for future investigations. through this analysis, we aim to contribute to the advancement of sustainable and efficient e-mobility solutions, shaping a greener and more sustainable future for transportation.

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SCOOP: A Scalable Object-Oriented Serverless Platform

SCOOP: A Scalable Object-Oriented Serverless Platform

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IEEE international conference on Cloud Computing, CLOUD

作者： Narges Shahidi Jashwant Raj Gunasekaran Mahmut Taylan Kandemir Bhuvan Urgaonkar Computer Science and Engineering Pennsylvania State University University Park PA Adobe Research

Function-as-a-Service (FaaS) has been the primary component to drive the movement toward serverless computing. these lightweight and scalable components, though attractive, are non-trivial to accommodate the needs of long-running stateful applications. In this paper, we highlight the drawbacks of existing stateful FaaS proposals, in turn motivating the need to rethink the stateful serverless model for building general-purpose applications, while maintaining its benefits such as auto-scaling and pay-per-use cost model. We present a novel serverless model based on the object-oriented (OO) programming paradigm, with Object-as-a-Service (OaaS), acting as the only component of the serverless design. through our experimental evaluations, we demonstrate that the proposed architecture, named SCOOP, can improve the end-to-end latency of applications by 52% and 58%, compared to the state-of-the-art stateless and stateful FaaS implementations, respectively, while reducing the SLO violations by up to 14% by scaling resources based on the traffic fluctuations in the WITS and Berkeley traces.

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7th international Workshopon programming Experience (PX/21)

ACM International Conference Proceeding Series

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ACM international conference Proceeding Series 2021年 viii-ix页

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Augmented Analytics: Modern Business Intelligence and Data Analytics

Augmented Analytics: Modern Business Intelligence and Data A...

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international conference on Computing Communication Control and Automation (ICCUBEA)

作者： Prakash Ukhalkar Manasi Bhate Suraj Hingane Swati Hingane MCA Department Pimpri Chinchwad College of Engineering Pune India MCA Department MES's Institute of Management and Career Courses Pune India MCA Department Abhinav Education Society's Institute of Management and Research Pune India MBA Department RMD Sinhgad School of Management Studies Pune India

Analytics that define the most valuable and possible automation are referred to as augmented analytics. Analytics is the name given to the scientific method of identifying and communicating critical patterns in data. To improve decision-making, gain understanding, prepare data, and exchange data, augmented analytics focused on turning raw data into information. Measurement and insights of data are obtained through augmented analytics. It employs operations research, computer programming, and statistics. It is functional in places with an enormous amount of information. When it comes to analytics and decision-making, augmented analytics can be supplemented and eventually fully automated. Augmented analytics is the most recent method for considering data and analytics. artificial intelligence (AI) and analytics are combined. It involves combining artificial intelligence (AI) with conventional analytics, the most popular machine learning (ML), and natural language processing (NLP). It differs from typical analytics or business intelligence (BI) tools in that ML technology is constantly learning and improving outcomes behind the scenes. Augmented analytics, in particular, allows for faster access to insights gained from vast volumes of structured and unstructured data to provide ML-based recommendations. this intelligence contributes to discovering hidden patterns and deviations in data, as well as the removal of human bias and the development of forecasting capabilities that can help an organization decide the future course of action.

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