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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"

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Improved Heuristics with Data Rounding for Combinatorial Food Packing Problems

Improved Heuristics with Data Rounding for Combinatorial Foo...

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IEEE international conference on Service-Oriented Computing and Applications (SOCA)

作者： Yoshiyuki Karuno Kenju Tateishi Department of Mechanical and System Engineering Kyoto Institute of Technology Kyoto Japan Graduate School of Science and Technology Kyoto Institute of Technology Kyoto Japan

Given a set I = {i | i = 1, 2, . . . , n} of current n items (for example, n green peppers) with their weights w i and priorities r i , a lexicographic bi-criteria combinatorial food packing problem asks to find a subset I' (⊆ I) so that the total weight Σ i∈I' w i is no less than a specified target bound b for each package, and it is minimized as the primary objective, and further the total priority Σ i∈I' r i is maximized as the second objective. the problem has been known to be NP-hard, while it can be solved exactly in O(nb) time if all the input data are assumed to be integral. For a given real ε > 0, an O(n 2 /ε) time heuristic algorithm with a data rounding technique has been designed and the heuristic total weight has been shown to be at most (2+ε) times the optimal total weight. In this paper, a modification of the data rounding heuristic is proposed, and it is shown that the proposed modification delivers a heuristic solution such that the total weight is at most (1 + ε) times the optimum.

关键词： Heuristic algorithms Vectors Dynamic programming Time complexity Algorithm design and analysis Electronic mail Optimization

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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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Design and Fabrication of Sensorized Soft Effectors for Modular Soft Robots

Design and Fabrication of Sensorized Soft Effectors for Modu...

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Automation, Control and Robots (ICACR), international conference on

作者： Maliha Kabir Prosenjit Kumar Ghosh Md. Sharif Ahmed thinagaran Perumal Prabha Sundaravadivel Dept. of Electrical and Computer Engineering The University of Texas at Tyler Dept. of Computer Science Universiti Putra Malaysia Selangor Malaysia

Biomimicry is a field of study that involves imitating the designs and processes of nature to solve problems using manmade systems. Biomimicry offers an empathetic, interconnected understanding of how life works and where we fit in. In bio-inspired designs, the main challenge is to develop a sustainable and effective framework that can be used in the real world. Most of the soft robotic designs are state-of-the-art models that cannot be used in real sensing applications. In this research, we propose a sustainable sensor-integrated modular soft robot model that can be used for locomotion and gripping applications. this work presents the steps involved in modeling, designing, and fabricating soft and flexible end effectors that can be used for soft robots with integrated soft stretchable sensors. It also demonstrates the design methodology involved in modeling and simulating the proposed model for robots that would require effectors with increased functionalities.

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Smartphone based Human Activity Recognition using CNNs and Autoencoder Features

Smartphone based Human Activity Recognition using CNNs and A...

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international conference on Trends in Electronics and Informatics (ICEI)

作者： Sowmen Mitra Proma Kanungoe Department Of Computer Science And Technology School Of Artificial Intelligence Hebei University Of Technology Beijing China Department Of Information Technology School Of Information Technology And Engineering Vellore Institute Of Technology Vellore India

Recognition of human activities is essential for many applications, and the widespread availability of low-cost sensors on smartphones and wearables has enabled the development of mobile apps capable of tracking user activities “in the wild.” However, dealing with heterogeneous data from different devices and real-time scenarios presents significant challenges. In this study, a novel learning framework is proposed for Human Activity Recognition (HAR) that combines a Convolutional Neural Network (CNN) with an autoencoder for feature extraction. the study also investigates the importance of preprocessing techniques, including orientation-independent transformation, to mitigate heterogeneity when dealing with multiple types of smartphones. the results show that the proposed approach outperforms state-of-the-art methods in HAR, with an accuracy of 95.74% on the heterogeneous dataset used in this study. Furthermore, the study demonstrates that proposed framework can be effectively deployed on smartphones with limited computational resources, making it suitable for real-world applications.

关键词： Wearable computers Market research Feature extraction Real-time systems Mobile applications Convolutional neural networks Informatics

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Blockchain-IoT Layered Architecture, Current Trends, Challenges, and Applications

Blockchain-IoT Layered Architecture, Current Trends, Challen...

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international conference on Trends in Electronics and Informatics (ICEI)

作者： Mukesh Kumar Nidhi Shweta Tiwari Surinder Kaur School of computer Application Lovely Professional University Phagwara India Maharaja Agrasen University Kallujhanda Solan Himachal Pradesh India Computer Science and Engineering Chandigarh University Mohali Punjab India

the term “Internet of things” (IoT) refers to the potential global connectivity of billions of individually networked devices that can collect and share data. this connectivity might occur everywhere on the globe. By combining IoT with Blockchain (BC), a robust and secure system might be created to store information gathered by intelligent gadgets. Internet-connected IoT devices can upload transaction data to private BC networks. As a result, all transactions in such networks are recorded in immutable ledgers. In order to comprehend how devices may connect with one another, this study examines the interplay between BC technology and IoTs. In this article, a BC layered architecture as a practical framework for integrating BC technology with IoT by making use of state-of-the-art tools and methods is proposed. Current trends and difficulties, as well as potential application domains, are discussed which is in relation to the layered architecture of Blockchain technology.

关键词： Privacy Electric potential Distributed ledger Information sharing Oral communication Market research Blockchains

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Learning Multiple Robot Manipulation Tasks with Imperfect Demonstrations

Learning Multiple Robot Manipulation Tasks with Imperfect De...

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international conference on Robotics and Automation sciences (ICRAS)

作者： Jiahua Dai Xiangbo Lin Jianwen Li Faculty of Electronic Information and Electric Engineering Department Dalian University of Technology Dalian China

Deep reinforcement learning (DRL) has been considered to be an effective method when dealing with robot control such as dexterous manipulation. With the increasing complexity of humanoid hand, control task is getting harder. Furthermore, to solve the drawbacks of DRL methods that may cause sample inefficient and slow exploration process, incorporating expert demonstrations have often been considered. Collecting demonstrations using deep learning methods will inevitably introduce errors, which forces the demonstrations to be imperfect. To solve that issue, we propose a weighting strategy ensuring that each demonstration will be used effectively and correctly, encouraging agent to be more efficient during learning. In the simulation experiments, with our weighting strategy and proposed unified reward function, our trained policies have achieved an average success rate over 85%, superior to the state of the art method in multiple manipulation tasks. We also validate that our method emerges more robust performance when using imperfect demonstrations with errors. the experimental results indicate that our method can be leveraged under different types of robotic environments.

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the research of tool integration technology for complex products’ collaborative simulation platform

The research of tool integration technology for complex prod...

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international conference on System Simulation and Scientific Computing, ICSC

作者： Ting Yu Lin Bo Hu Li Xu Dong Chai Bao Cun Hou School of Automatic Science and Electrical Engineering BeiHang University Beijing China Beijing Simulation Center Second Academy of Aerospace Science and Industry Company Beijing China

the collaborative simulation for complex products needs seamless integration of multi-discipline tool software on collaborative simulation platform. However, many kinds of tool software do not provide application programming interface (API), which is vital for collaborative simulation. Under the technical framework of complex productspsila collaborative simulation platform, the paper proposes three methods to realize tool software packaging when the tool software does not provide API. they are the method of calling solver directly, the method of tool interface module and that of secondary integration. the method of calling solver directly realizes interaction between tool software and platform by seeking a way to call solver from background directly; the method of tool interface module adds user defined module to the model of tool software as a way for the interaction between tool software and the outside. the two methods are all dedicated to constructing a user defined uniform tool engine interface for the platform to call. the method of secondary integration realizes integration indirectly by using tool software which has been integrated to the platform. the paper also presents the process of realization of the three methods by giving an example of integrating MSC EASY5 tool software. By doing so, we prove their correctness and analyze their pros and cons.

关键词： Collaborative tools Collaborative software Software tools Computer aided engineering Aerospace industry Collaboration Mathematical model Computational modeling Aerospace simulation Aerospace engineering

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Intelligent PC-based user control interface for on-line correction of robot programs

Intelligent PC-based user control interface for on-line corr...

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international conference on Control, Automation, Robotics and Vision (ICARCV)

作者： U. Berger R. Lepratti Brandenburg University of Technology Cottbus Germany

Today the automotive sector is dominated by high variety of types and increasing product diversification. thus, OEM manufacturers reintegrate key technologies back in the enterprise, due to competitive reason and to stabilize leadership in innovation. As an example, state-of-the-art fuel and diesel engine cylinder heads achieve higher complexity and filigrane structure, therefore careful treatment of specimen as well as net-shape machining processes with high quality output are a major requirement in this sector. A key issue is the surface fretting and finishing of engine parts subsequent following foundry procedures. An advanced factory automation system, based on an industrial robot (6-axis joint coordinate), has been developed in order to obtain the described results. On the system apply various measuring procedures, in order to recognize and remove burr formation (particularly with optical technique). A graphical interactive programming system enables simple and user friendly correction at deburring results for individual workpiece types. A possibility was given to the system user, who can easily remove deburring errors through short operator interaction, mainly input of correction values at controller system. thereby, each authorized robot cell operator can contribute to guaranty process quality without special technical training.

关键词： Intelligent robots Intelligent control Robot kinematics Diesel engines Deburring Automotive engineering Manufacturing Technological innovation Fuels Engine cylinders

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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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Research of Efficiency of Multi-core Computers with Shared Memory

Research of Efficiency of Multi-core Computers with Shared M...

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IEEE international conference on Future Internet of things and Cloud Workshops (FiCloudW)

作者： Dmytro Nedzelskyi Maryna Derkach Yehor Tatarchenko Svitlana Safonova Larisa Shumova Volodymyr Kardashuk Computer Science and Engineering Department V. Dahl East Ukrainian National University Severodonetsk Ukraine

ISBN: (数字)9781728144115

ISBN: (纸本)9781728144122

Efficient utilization of multi-core computers with shared memory depends on many factors. In this article efficiency of multi-core computers with shared memory is investigated. All computer cores execute either parallel streams of a single program, developed in accordance with the OpenMP API, or independent programs. there are no interactions between streams and independent programs. Both parallel and non-parallel (single stream) applications share memory where conflicts may occur. Models for determining the acceleration coefficients of a multi-core computer, analytical expressions which reflect the dependence of the acceleration coefficients on the number of cores, the properties performed the programs, cores and shared memory parameters and formulas for determine recommended numbers of cores for parallel applications in accordance with the OpenMP API are suggested. the main reason for the decrease in performance of multi-core computers with shared memory when parallelizing applications in accordance with the OpenMP API is the overload of shared memory.

关键词： application program interfaces message passing multiprocessing systems parallel programming public domain software shared memory systems shared memory Application programming interfaces open source software shared memory systems Multiprocessing systems speedup factor Parallel programming message passing Computers core

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