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Intelligent Computing and Networking - Proceedings of IC-ICN 2023

作者： Surbakti, Herison Kumar, Athmakuri Naveen Tara, Saikumar Keshta, Ismail khare, Amit Prasad, G.N.R. Faculty of Computing and Digital Technology HELP University Kuala Lumpur Malaysia Senior Software Engineer Glosoft Technologies Pvt Ltd Chennai India Department of ECE BVRIT Hyderabad College of Engineering for Women Hyderabad India Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Department of Technology JIET Institute of Design and Technology Rajasthan Jodhpur India Telangana Hyderabad500091 India

ISBN: (纸本)9789819931767

In recent years, support vector machine has become one of the most important classification techniques in pattern recognition, machine learning, and data mining due to its superior classification effect and solid theoretical base. However, its training time will increase dramatically as the number of samples increases, and training will become more sophisticated when dealing with problems involving multiple classifications. A quick training data reduction approach MOIS appropriate for multi-classification tasks is presented as a solution for the aforementioned issues. While eliminating redundant training samples, the boundary samples that play a vital role are chosen in order to considerably reduce training data and the problem of unequal distribution between categories. The experimental results demonstrate that MOIS may maintain or even improve the classification performance of support vector machines while substantially enhancing training efficiency. On the Opt digit dataset, the suggested method improves classification accuracy from 98.94% to 99.05%, while training time is reduced to 15% of the original;in HCL2000, the proposed method improves classification accuracy from 98.94% to 99.05%. When the accuracy rate is marginally increased (from 99.29% to 99.30%) on the first 100 categories dataset, the training time is dramatically reduced to less than 6% of the original. Additionally, MOIS has a high operational efficiency. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

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Large-scale group decision-making method based on knowledge differentiation and the grouping of alternatives into modifiable scenarios 9th

Large-scale group decision-making method based on knowledge ...

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9th International Conference on Information Technology and Quantitative Management, ITQM 2022

作者： Trillo, José Ramón Herrera-Viedma, Enrique Higueras-Ruiz, María José Alonso, Sergio Morente-Molinera, Juan Antonio Cabrerizo, Francisco Javier Department of Computer Science and Artificial Intelligence Andalusian Research Institute of Data Science and Computational Intelligence DaSCI University of Granada Granada18071 Spain Department of Information and Communication University of Granada Granada18071 Spain Department of Software Engineering Andalusian Research Institute in Data Science and Computational Intelligence DaSCI University of Granada Granada18071 Spain

Nowadays, group decision-making is an everyday event, since we usually live in a community. Nevertheless, when the number of participants is large, it starts to generate a lot of information that is complex to manage, and unlike group decision-making, where the participants are usually experts, when the number of participants increases, not all of them are, which generates a conflict of interest because the value of the vote of an expert and a (non-expert) user is worth the same. Moreover, it may happen that not all participants who start a process will finish it and not all of them will be able to make all the assessments, since they do not know all the options. Therefore, to solve all the drawbacks, this paper presents a large-scale group decision-making system in a modifiable scenario environment that groups participants according to their preferred alternative and also performs knowledge differentiation, clustering them into experts and users. This allows for optimising the consensus process, as the consensus is made by comparing the clusters and the participants with each other. © 2022 The Authors. Published by Elsevier B.V.

关键词： Decision making

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Learning Generalizable Models via Disentangling Spurious and Enhancing Potential Correlations

arXiv

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arXiv 2024年

作者： Wang, Na Qi, Lei Guo, Jintao Shi, Yinghuan Gao, Yang The National Key Laboratory for Novel Software Technology The National Institute of Healthcare Data Science Nanjing University Nanjing210023 China The School of Computer Science and Engineering Southeast United States Ministry of Education Nanjing211189 China

Domain generalization (DG) intends to train a model on multiple source domains to ensure that it can generalize well to an arbitrary unseen target domain. The acquisition of domain-invariant representations is pivotal for DG as they possess the ability to capture the inherent semantic information of the data, mitigate the influence of domain shift, and enhance the generalization capability of the model. Adopting multiple perspectives, such as the sample and the feature, proves to be effective. The sample perspective facilitates data augmentation through data manipulation techniques, whereas the feature perspective enables the extraction of meaningful generalization features. In this paper, we focus on improving the generalization ability of the model by compelling it to acquire domain-invariant representations from both the sample and feature perspectives by disentangling spurious correlations and enhancing potential correlations. 1) From the sample perspective, we develop a frequency restriction module, guiding the model to focus on the relevant correlations between object features and labels, thereby disentangling spurious correlations. 2) From the feature perspective, the simple Tail Interaction module implicitly enhances potential correlations among all samples from all source domains, facilitating the acquisition of domain-invariant representations across multiple domains for the model. The experimental results show that Convolutional Neural Networks (CNNs) or MultiLayer Perceptrons (MLPs) with a strong baseline embedded with these two modules can achieve superior results, e.g., an average accuracy of 92.30% on Digits-DG. Source code is available at https://***/RubyHoho/DGeneralization. Copyright © 2024, The Authors. All rights reserved.

关键词： Multilayer neural networks

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Existence of strongly nonlocal sets of three states in any N-partite system

arXiv

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arXiv 2024年

作者： Xiong, Zong-Xing Li, Mao-Sheng Institute of Quantum Computing and Software School of Computer Science and Engineering Sun Yat-Sen University Guangzhou510006 China School of Mathematics South China University of Technology Guangzhou510641 China

The notion of strong nonlocality, which refers to local irreducibility of a set of orthogonal multipartite quantum states across each bipartition of the subsystems, was put forward by Halder et al. in [Phys. Rev. Lett. 122, 040403 (2019)]. Here, we show the existence of three orthogonal quantum states in (C2)⊗N that cannot be perfectly distinguished locally across any bipartition of the subsystems. Specifically, all these three states are genuinely entangled, among which two are the N-qubit GHZ pairs. Since any three locally indistinguishable states are always locally irreducible, the three N-partite orthogonal states we present are strongly nonlocal. Thus, the caridnality of strongly nonlocal sets here is dramatically smaller than all known ones. © 2024, CC BY.

关键词： Quantum entanglement

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Challenges in Fuzzy Decision Making for Future Research 21

Challenges in Fuzzy Decision Making for Future Research

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21st International Conference on New Trends in Intelligent software Methodologies, Tools and Techniques, SoMeT 2022

作者： Trillo, José Ramón Herrera-Viedma, Enrique Higueras-Ruiz, María José Alonso, Sergio Morente-Molinera, Juan Antonio Cabrerizo, Francisco Javier Department of Computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence DaSCI University of Granada Granada18071 Spain Department of Information and Communication University of Granada Granada18071 Spain Department of Software Engineering Andalusian Research Institute in Data Science and Computational Intelligence DaSCI University of Granada Granada18071 Spain

ISBN: (纸本)9781643683164

Fuzzy Decision Making is a line of research that has had an important presence in the literature since 1965 until nowadays. From that year to the present, the line of research has been consolidated. The research field goals have evolved along with all the research that makes use of these systems and the new technologies requirements. Therefore, new challenges, different from the ones that were faced at the beginning, need to be solved. The aim of this paper is to describe the recent challenges faced by those working in this line of research. This paper will help researchers to know how their work should be oriented in the future. © 2022 The authors and IOS Press. All rights reserved.

关键词： Decision making

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Design of Scatterer Configuration for Spectral Optimization of Random Lasers

Design of Scatterer Configuration for Spectral Optimization ...

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Takashi Okamoto Kouki Kajisa Ryo Ohshige Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Fukuoka Japan

The two-dimensional structure of a random gain medium was designed to obtain the specified emission spectrum from a random laser. Structural optimization was performed using a direct binary search method. The simulation results showed that the emitted light can be concentrated within one or more specific wavelength ranges. The effect of the fabrication errors on the optimized laser emission spectrum was also examined.

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Socioeconomic Analysis of the Proposed Opening of the Brazilian Energy Market Through the Combination of Forecast Method with the Optimized Tariff Model

SSRN

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SSRN 2024年

作者： Silva, Patrícia Ferreira Costa, Vinicius B.F. Bonatto, Benedito Donizeti Dias, Bruno Henrique Soares, Tiago A. Balestrassi, Pedro P. Institute of Electrical Systems and Energy Federal University of Itajubá MG Itajubá37500-903 Brazil Institute of Production Engineering and Management Federal University of Itajubá MG Itajubá37500-903 Brazil National Institute of Science and Technology in Electric Energy Federal University of Juiz de Fora MG Juiz de Fora36036-900 Brazil Energy Systems Center Institute of Systems and Computer Engineering Technology and Science Faculty of Engineering of Porto Porto Portugal

This article combines forecasting methods and the optimized tariff model to examine the effectiveness of the NT n°10/2022-SEM/ANEEL proposal on opening the electricity market to low voltage energy consumers. The results show that the new proposal kept the economic surplus of the concessionaires and the social welfare in balance. On the other hand, there are negative implications for tariffs, where, at the beginning, there was a 2% increase and at the end the tariff increased by 11%. Therefore, it is concluded that regulatory changes are necessary to avoid increasing the energy tariff, reconciling the proposed schedule with the reduction of legacy contracts. © 2024, The Authors. All rights reserved.

关键词： Power markets

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A Simulation-Based Approach to Reduce Waiting Times in Emergency Departments 2nd

A Simulation-Based Approach to Reduce Waiting Times in Eme...

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2nd International Scientific Conference on Innovation in engineering, ICIE 2022

作者： Teymourifar, Aydin CEGE - Centro de Estudos em Gestão e Economia Católica Porto Business School Porto Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal

ISBN: (纸本)9783031093845

The goal of this work is to utilize a simulation model to reduce waiting times before examinations in emergency departments. Different types of arrivals to an emergency department, basic processes, and possible queues are explained. The implementation is conducted in the Rockwell Arena software and some related details are provided. The validity of the simulation model is demonstrated. Then scenarios are developed based on limited boosting of resources to reduce waiting times. It is analyzed how waiting times can be reduced. Also, it is discussed that which resources should be increased for this aim. The Process Analyzer software is used for the analysis of the scenarios, whose details are given. It is also analyzed how the utilization rate of resources changes in scenarios. Data from the literature are used for experimental results. Since the analyzes are based on generalizable approaches, they can be applied in similar emergency departments. The results show that with a reasonable increase in resources, it is possible to significantly reduce waiting times. The implications that may be useful in the management of emergency departments are presented. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Discrete event simulation

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Scalable and low-cost remote lab platforms: Teaching industrial robotics using open-source tools and understanding its social implications

arXiv

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arXiv 2024年

作者： Kumar, Amit Jose, Jaison Jain, Archit Kulkarni, Siddharth Arya, Kavi Centre for Systems and Control Indian Institute of Technology Bombay Mumbai India Embedded Real-Time Systems / e-Yantra Lab. Indian Institute of Technology Bombay Mumbai India Computer Science and Engineering Department Indian Institute of Technology Bombay Mumbai India

With recent advancements in industrial robots, educating students in new technologies and preparing them for the future is imperative. However, access to industrial robots for teaching poses challenges, such as the high cost of acquiring these robots, the safety of the operator and the robot, and complicated training material. This paper proposes two low-cost platforms built using open-source tools like Robot Operating System (ROS) and its latest version ROS 2 to help students learn and test algorithms on remotely connected industrial robots. Universal Robotics (UR5) arm and a custom mobile rover were deployed in different life-size testbeds, a greenhouse, and a warehouse to create an Autonomous Agricultural Harvester System (AAHS) and an Autonomous Warehouse Management System (AWMS). These platforms were deployed for a period of 7 months and were tested for their efficacy with 1,433 and 1,312 students, respectively. The hardware used in AAHS and AWMS was controlled remotely for 160 and 355 hours, respectively, by students over a period of 3 months. © 2024, CC BY.

关键词： Costs

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Towards Efficient Auction Design with ROI Constraints 24

Towards Efficient Auction Design with ROI Constraints

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Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent systems

作者： Xinyu Tang Hongtao Lv Yingjie Gao Fan Wu Lei Liu Lizhen Cui School of Software & C-FAIR Shandong University Jinan China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China School of Software & C-FAIR Shandong University & Shandong Research Institute of Industrial Technology Jinan China

ISBN: (纸本)9798400704864

Online advertising stands as a significant revenue source of the Internet. Recently, the trend among advertisers tilting towards the use of auto-bidding tools has heralded the emergence of a new model of bidders operating with constraints related to return on investment (ROI). However, most of the current research on ROI-constrained bidders in auction design only focuses on either the ROI constraints or values of bidders being private, while it is more practical to keep them both private in reality. Designing a truthful mechanism for bidders with both private values and ROI constraints introduces complexities because of the characteristics of designing mechanisms with multiple parameters. To remedy this, we divide bidders into binary classes: the traditional utility maximizers (UMs) who can be viewed as having an ROI constraint of 1, and the ROI-constrained bidders (RBs) who share a fixed ROI constraint denoted as γ. This framework retains the essence of multi-parameter mechanism design but transitions this into a more tractable form. Then we introduce a novel auction mechanism, cleverly combining the conventional VCG mechanism and an existing mechanism for public ROI-constrained bidders which is called Cavallo's mechanism. Our mechanism can achieve an approximation ratio of 3 over 2 on social welfare. Additionally, we unearth new insights into the limitations posed by ROI constraints. When the ROI constraint γ exceeds 2, the lower bound of social welfare is 5 over 4; when it falls below 2, the lower bound becomes 3+γ over 2+3γ-γ2.

关键词： incentive compatibility mechanism design return on investment

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