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24th ACM Conference on Economics and Computation, EC 2023

作者： Feige, Uriel Huang, Xin Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot Israel Computer Science Technion - Israel Institute of Technology Haifa Israel

ISBN: (纸本)9798400701047

We consider the problem of allocating m indivisible chores to n agents with additive disvaluation (cost) functions. It is easy to show that there are picking sequences that give every agent (that uses the greedy picking strategy) a bundle of chores of disvalue at most twice her share value (maximin share, MMS, for agents of equal entitlement, and anyprice share, APS, for agents of arbitrary entitlement). Aziz, Li and Wu (2022) designed picking sequences that improve this ratio to 5/3 for the case of equal entitlement. We design picking sequences that improve the ratio to 1.733 for the case of arbitrary entitlement, and to 8/5 for the case of equal entitlement. (In fact, computer assisted analysis suggests that the ratio is smaller than 1.543 in the equal entitlement case.) We also prove a lower bound of 3/2 on the obtainable ratio when n is sufficiently *** results trivially imply that (for additive valuation over chores) in the arbitrary entitlement case, there always is an allocation that gives every agent at most 1.733APS, and in the equal entitlement case, there always is a distribution over allocations that gives every agent at most 1.6MMS ex-post, and at most the proportional share ex-ante. Neither of these implications were previously known to *** contributions of our work include improved guarantees in the equal entitlement case when n is small;introduction of the chore share as a convenient proxy to other share notions for chores;introduction of ex-ante notions of envy for risk averse agents, and enhancements to our picking sequences that eliminate such envy. © 2023 Owner/Author(s).

关键词： Additives

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AI-driven optimisation of metal alloys for space applications

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Discover Artificial Intelligence 2025年第1期5卷 1-22页

作者： Rickard, Luke Bampoulas, Adamantios Laad, Meena Mangina, Eleni School of Computer Science University College Dublin Belfield DublinD04V1W8 Ireland Department of Applied Sciences Symbiosis Institute of Technology Mulshi Pune412 115 India

This study investigates the application of artificial intelligence (AI) to accelerate the development of metal alloys for space applications, with a focus on aluminum, nickel, and titanium alloys. The research integrates data analysis, feature selection, and machine learning (ML) models to predict critical alloy properties for space environments, including Young’s modulus, yield strength, tensile strength, specific heat, and the coefficient of thermal expansion. The study optimises ML models, such as multi-layer perceptrons and ensemble techniques, demonstrating superior predictive accuracy compared to traditional benchmarks. Additionally, predictive models are employed to recommend novel alloy compositions, potentially enhancing specific properties crucial for aerospace applications. The proposed framework identifies significant predictors through correlation analysis, optimises models to achieve superior predictive accuracy, and recommends novel alloy compositions with the potential for enhanced performance in space applications. This study significantly contributes to materials science by integrating AI with traditional methods, offering a more efficient and targeted approach to alloy development, with the potential to enhance the design and durability of space vehicles and structures. © The Author(s) 2025.

关键词： Thermal expansion

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Survey of Intelligent Program Synthesis Techniques

Survey of Intelligent Program Synthesis Techniques

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2023 International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, AHPCAI 2023

作者： Zhou, Baishun Ding, Gangyi School of Computer Science and Technology Beijing Institute of Technology Beijing China School of Applied Technology China University of Labor Relations Beijing China

ISBN: (纸本)9781510671881

Program synthesis refers to the task of solving a specific problem by automatically generating a computer program. It has received considerable attention from artificial intelligence and programming language communities. Over time, software codes and group wisdom have been accumulated on the internet. Simultaneously, artificial intelligence, such as deep learning, has obtained promising achievements in numerous fields, which has motivated researchers to address the problem of automatic program generation by considering both software engineering and intelligent technology. The key challenges in the field of program synthesis mainly consist of the huge search space of the programs and the ambiguity of user intent. In this study, we analyze program synthesis techniques according to their user intent description, focus on the impact of new technologies on program synthesis, such as data-driven and artificial intelligence, and summarize the pruning methods of program space and search technologies. Further, we discuss the existing challenges in program synthesis technology and present suggestions for further studies in this field. © 2023 SPIE. All rights reserved.

关键词： Deep learning

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SMS Spam Detection using Advance Naive-Bayes Approach

SMS Spam Detection using Advance Naive-Bayes Approach

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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Arora, Yojna Gupta, Neha Rathore, Yogesh Singh Bansal, Nidhi Mehta, Aina Chadha, Shikha Kumar, Ashwani Sharda University Department of Computer Science and Engineering Greater Noida India Symbiosis University of Applied Sciences School of Computer Science & Information Technology Madhya Pradesh Indore India Sharda University School of Engineering and Technology Department of Computer Science and Applications Uttar Pradesh Greater Noida India School of Engineering and Technology Department of Computer Science & Engineering Haryana Faridabad India Bennett University School of Computer Science Engineering and Technology India

ISBN: (纸本)9798331508685

Recently, with increased use of mobile phones, it has transformed into a multibillion-dollar Short Message Service or SMS. However, the drop in the cost of messaging services has led to an increased number of unsolicited commercial messages, or spam, being delivered to mobile phones. Several reasons exist for which traditional algorithms used in email filtering may not efficiently classify the spam in SMS such as the absence of strong SMS spam databases, with the short length and features of the message, the informal language used, etc. This paper uses a real SMS spam database After preprocessing the data and extraction of relevant features, Naïve Bayes machine learning techniques is applied to get the results. Then it is analyzed using confusion matrix, accuracy, precision and recall values. A learning curve with clearly defined relationship between the training and testing data set and overall error at the end. © 2025 IEEE.

关键词： Adversarial machine learning

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Automated Vickers hardness system with closed-loop control for polishing pads for semiconductor production

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Instrumentation Science and technology 2024年第4期52卷 401-414页

作者： Huy, Le Nam Quoc Hoa, Le Ngoc Quynh Haq, Muhamad Amirul Huynh, Tan-Thanh Department of Mechanical Engineering National Taiwan University of Science and Technology Taipei Taiwan Nanyang Technological University Singapore Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taiwan School of Applied Chemistry Tra Vinh University Viet Nam

Chemical mechanical polishing plays a pivotal role in enhancing the topography of wafers during semiconductor fabrication. The hardness of polishing pads holds great significance as it determines the material removal rate during the planarization process. Hence, precise determination of polishing pad hardness at both micro and macro scales is essential for optimizing the semiconductor polishing process, ensuring the prevention of wafer erosion or dishing. In this study, an automated system was developed for determining Vickers hardness of microporous polishing pads employing a closed-loop control method. The system was calibrated based on the relationship between load-unloading force and displacement observed in Vickers indentation experiments. The designed apparatus is not only successfully verified with standard values for Vickers reference blocks with less than 2% error, but it also demonstrated a smaller average relative error percentage than the commercial system using traditional open-loop measurement method. The closed-loop Vickers hardness apparatus proves to be a promising alternative for measuring hardness accurately, particularly in samples with noisy surfaces, rough surfaces, and porous microstructures. © 2023 Taylor & Francis Group, LLC.

关键词： Fabrication

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A Convolutional Neural Network Model for Wheat Crop Disease Prediction

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computers, Materials & Continua 2023年第5期75卷 3867-3882页

作者： Mahmood Ashraf Mohammad Abrar Nauman Qadeer Abdulrahman A.Alshdadi Thabit Sabbah Muhammad Attique Khan Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddah21577Saudi Arabia Department of Computer Science Bacha Khan University CharsaddaKhyber Pakhtunkhwa24461Pakistan Department of Computer Science Federal Urdu University of ArtsScience&TechnologyIslamabad45570Pakistan Department of Information Systems and Technology College of Computer Science and EngineeringUniversity of JeddahJeddah21577Saudi Arabia Faculty of Technology and Applied Sciences Al-Quds Open UniversityAl-Bireh1804Palestine Department of Computer Science HITEC UniversityTaxila47080Pakistan

Wheat is the most important cereal crop,and its low production incurs import pressure on the *** fulfills a significant portion of the daily energy requirements of the human *** wheat disease is one of the major factors that result in low production and negatively affects the national ***,timely detection of wheat diseases is necessary for improving *** CNN-based architectures showed tremendous achievement in the image-based classification and prediction of crop ***,these models are computationally expensive and need a large amount of training *** this research,a light weighted modified CNN architecture is proposed that uses eight layers particularly,three convolutional layers,three SoftMax layers,and two flattened layers,to detect wheat diseases *** high-resolution images were collected from the fields in Azad Kashmir(Pakistan)and manually annotated by three human *** convolutional layers use 16,32,and 64 *** filter uses a 3×3 kernel *** strides for all convolutional layers are set to *** this research,three different variants of datasets are *** variants S1-70%:15%:15%,S2-75%:15%:10%,and S3-80%:10%:10%(train:validation:test)are used to evaluate the performance of the proposed *** extensive experiments revealed that the S3 performed better than S1 and S2 datasets with 93%*** experiment also concludes that a more extensive training set with high-resolution images can detect wheat diseases more accurately.

关键词： Machine learning wheat crop disease prediction convolutional neural network artificial intelligence

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Avoid Suspicious Route of Blackhole Nodes in MANET’s:Using A Cooperative Trapping

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computer Systems Science & Engineering 2023年第5期45卷 1901-1915页

作者： Abdllkader Esaid Mary Agoyi Department of Computer Engineering Faculty of EngineeringCyprus International UniversityNicosiaCyprus Information Technology Department School of Applied SciencesCyprus International UniversityNicosiaCyprus

Mobile Ad hoc Network(MANET)is decentralized wireless network and can communicate without existing infrastructure in many *** is vulnerable to various attacks that affect its performance such as blackhole *** attacker,inject fault routing information to persuade the source node to select the path with malicious node as the shortest *** eliminate malicious nodes from launching any collaborative attack.A cooperative Trapping Approach(CTA)was proposed based on modifying Ad-hoc On-demand Distance Vector(AODV)routing protocol and trapping the malicious nodes by responding to the trap request *** approach aims to eliminate and rule out both single and collaborative malicious blackhole nodes from any *** approach realizes a backward tracking mechanism to perform the elimination *** proposed algorithm(CTA)was executed using NS-2 network *** performance metrics that has been considered to evaluate the performance of the proposed algorithm such as throughput,end to end delay,packet delivery ratio,and consuming *** experimental results have shown the performance metrics of the proposed approach outperformed other state of at algorithms.

关键词： AODV Blackhole MANET Malicious node

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Strategic Renewable Energy Resource Selection Using a Fuzzy Decision-Making Method

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Intelligent Automation & Soft Computing 2023年第2期35卷 2117-2134页

作者： Anas Quteishat M.A.A.Younis Electrical Engineering Department Faculty of Engineering TechnologyAl-Balqa Applied UniversityAl-SaltJordan Department of Electrical and Computer Engineering Sohar UniversitySultanate of Oman

Renewable energy is created by renewable natural resources such as geothermal heat,sunlight,tides,rain,and *** resources are vital for all countries in terms of their economies and *** a result,selecting the optimal option for any country is critical in terms of energy *** country is nowadays planning to increase the share of renewable energy in their universal energy sources as a result of global *** the present work,the authors suggest fuzzy multi-characteristic decision-making approaches for renew-able energy source selection,and fuzzy set theory is a valuable methodology for dealing with uncertainty in the presence of incomplete or ambiguous *** study employed a hybrid method for order of preference by resemblance to an ideal solution based on fuzzy analytical network process-technique,which agrees with professional assessment scores to be linguistic phrases,fuzzy numbers,or crisp *** hybrid methodology is based on fuzzy set ideologies,which calculate alternatives in accordance with professional functional requirements using objective or subjective *** best-suited renewable energy alternative is discovered using the approach presented.

关键词： Multi characteristic decision making framework fuzzy sets fuzzy theory renewable energy energy resource selection

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Monocular Vision-Based Localization and Pose Estimation with a Nudged Particle Filter and Ellipsoidal Confidence Tubes

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无人系统（英文） 2023年第1期11卷 109-120页

作者： Tony X.Lin Samuel Coogan Daniel M.Lofaro Donald A.Sofge Fumin Zhang School of Electrical and Computer Engineering Georgia Institute of TechnologyAtlantaGA 30332USA Navy Center for Applied Research in Artificial Intelligence Naval Research LaboratoryWashingtonDC 20375USA

This paper proposes a nudged particle filter for estimating the pose of a camera mounted on flying robots collecting a video *** nudged particle filter leverages two image-to-pose and pose-to-image neural networks trained in an auto-encoder fashion with a dataset of pose-labeled *** an image,the retrieved camera pose using the image-to-pose network serves as a special particle to nudge the set of particles generated from the particle filter while the pose-to-image network serves to compute the likelihoods of each *** demonstrate that such a nudging scheme effectively mitigates low likelihood samplings during the particle propagation *** confidence tubes are constructed from the set of particles to provide a computationally efficient bound on localization *** an ellipsoidal tube self-intersects,the probability volume of the intersection can be significantly shrunken using a novel Dempster-Shafer probability mass assignment *** from the intersection,a loop closure procedure is developed to move backward in time to shrink the volumes of the entire ellipsoidal *** results using the Georgia Tech Miniature Autonomous Blimp platform are provided to demonstrate the feasibility and effectiveness of the proposed algorithms in providing localization and pose estimation based on monocular vision.

关键词： Monocular vision-based localization Dempster-Shafer particle filters

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BEESO:Multi-strategy Boosted Snake-Inspired Optimizer for Engineering Applications

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Journal of Bionic Engineering 2023年第4期20卷 1791-1827页

作者： Gang Hu Rui Yang Muhammad Abbas Guo Wei Department of Applied Mathematics Xi’an University of TechnologyXi’an710054China School of Computer Science and Engineering Xi’an University of TechnologyXi’an710048China Department of Mathematics University of SargodhaSargodha40100Pakistan University of North Carolina at Pembroke PembrokeNC28372USA

This paper presents an efficient enhanced snake optimizer termed BEESO for global optimization and engineering *** a newly mooted meta-heuristic algorithm,snake optimizer(SO)mathematically models the mating characteristics of snakes to find the optimal *** has a simple structure and offers a delicate balance between exploitation and ***,it also has some shortcomings to be *** proposed BEESO consequently aims to lighten the issues of lack of population diversity,convergence slowness,and the tendency to be stuck in local optima in *** presentation of Bi-Directional Search(BDS)is to approach the global optimal value along the direction guided by the best and the worst individuals,which makes the convergence speed *** increase in population diversity in BEESO benefits from Modified Evolutionary Population Dynamics(MEPD),and the replacement of poorer quality individuals improves population *** Elite Opposition-Based Learning(EOBL)provides improved local exploitation ability of BEESO by utilizing solid solutions with good *** performance of BEESO is illustrated by comparing its experimental results with several algorithms on benchmark functions and engineering ***,the results of the experiment are analyzed again from a statistical point of view using the Friedman and Wilcoxon rank sum *** findings show that these introduced strategies provide some improvements in the performance of SO,and the accuracy and stability of the optimization results provided by the proposed BEESO are competitive among all *** conclude,the proposed BEESO offers a good alternative to solving optimization issues.

关键词： Snake optimizer Bi-Directional Search Evolutionary Population Dynamics Elite Opposition-Based Learning Strategy Mechanical optimization design

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