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Comparative Study of Classification Algorithms Using Big Data Analytics for Flight Delays Prediction 5th

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Comparative Study of Classification Algorithms Using Big Dat...

5th Doctoral Symposium on Computational Intelligence, DoSCI 2024

作者： Asiri, Mona Hassan AL-Malaise AL-Ghamdi, Abdullah S. Fayoumi, Ayman G. Ragab, Mahmoud Department of Information Systems Collage of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Information Systems Department School of Engineering Computing and Design Dar Al-Hekma University Jeddah34801 Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia Information Technology Department Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia

ISBN: (纸本)9789819771776

Flight delays are the most pressing cause of concern in the airline sector because they can weaken and harm airlines, passengers, and airports. Flight delay prediction has become an essential step in decision-making processes within commercial aviation. Due to the developments of recent technologies, there are many prediction models for flight delays;however, more development of accurate prediction models is still needed. Machine learning, statistical models, and other techniques can be used to create quick and accurate flight delay prediction models. Furthermore, methods for feature selection can be developed to get rid of dimensionality issues. This study aimed to compare four classification algorithms using "big data analytics" to predict flight delays, a function that can improve the whole airline sector. The selected classification algorithms were the "Gaussian Naïve Bayes," "Gradient Boosted Tree" classifier, "Logistic Regression," and "Random Forest" classifier. Many assessment techniques were applied to each one of the suggested models to show the better performance of these models. The comparison used the resulting confusion matrix to summarize prediction results for the following classification problems: "F1 Score", "Accuracy," "Recall," "Precision," "Area Under ROC," and "Area Under PR." The assessment results showed the enhanced outcomes of the "Gradient Boosted Tree" Classifier with existing techniques, and all results of "Logistic Regression" and "Naïve Bayes" are equal. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Prediction models

Hybrid Blockchain and IoT Driven Framework for Supply Chain Optimization by Enhancing Transparency, Efficiency and Cost Reduction 3

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Hybrid Blockchain and IoT Driven Framework for Supply Chain ...

3rd International Conference on Electronics and Renewable systems, ICEARS 2025

作者： Pradeep Kumar, S. Basha, C.H. Hussaian Prasath, C. Arun Amirthayogam, G. Lathif, Syed Ismail Abdul Leelavathi, R. Rajalakshmi Engineering College Computer Science Design Department Thandalam Chennai602105 India Sr University Department of Electrical and Electronics Engineering Warangal506371 India Mahendra Engineering College Department of Ece Namakkal637503 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai600062 India Srm Institute of Science and Technology Department of Data Science and Business Systems Chennai603203 India Velalar College of Engineering and Technology Department of Biomedical Engineering Erode638012 India

ISBN: (纸本)9798331509675

Blockchain technology represents a modern supply chain management revolution which fixes operational challenges while providing enhanced transparency at reduced costs. The research develops HB-SCOF (Hybrid Blockchain-Enabled Supply Chain Optimization Framework) which combines blockchain self-verification databases with automatic smart contracts to maintain continuous supply chain observation and evaluate data credibility. The framework integrates tamper-proof transaction tracking mechanisms with unified supply chain network connectivity for securing data transmission as a trust delivery method through unbreakable shared databases. The retail-industry case study demonstrated a 25% decrease in expenses stemming from agency elimination alongside enhanced flow management and better stock distribution. The system demonstrates its effectiveness through assessments of key performance indicators including transaction speed and data accuracy together with business cost efficiency. This part looks at implementation methods through training stakeholders in addition to transforming organizational policies which produce successful outcomes. Blockchain technology labs verify its capability to enhance supply chain management efficiency while showing realistic deployment methods. © 2025 IEEE.

关键词： Smart contract

Effect of shape of single-roll rapid solidification nozzles on properties of ribbons for magnesium rechargeable batteries

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Keikinzoku/Journal of Japan Institute of Light Metals 2025年第2期75卷 114-119页

作者： Kirimoto, Yuichi Tsukeda, Tadayoshi Aida, Tetsuo Tabata, Hironobu Haga, Toshio Kurihara, Hideki Suzuki, Mayumi Department of Nano and Functional Material Science Graduate School of Science and Engineering for Education University of Toyama 3190 Gofuku Toyama Toyama-shi930-8555 Japan Faculty of Sustainable Design Academic Assembly University of Toyama Toyama Toyama-shi Japan CHUETSU METAL WORKS CO. LTD. Nakaniikawa-gun Toyama Japan Department of Mechanical Engineering Osaka Institute of Technology Osaka Osaka-shi Japan Saitama Industrial Technology Center Saitama Saitama-shi Japan Department of Mechanical Systems Engineering Faculty of Engineering Toyama Prefectural University Toyama Imizu-shi Japan

In developing ribbons for use as anode materials in innovative rechargeable batteries, magnesium ribbons were manufactured using a single-roll rapid solidification method. The quality of ribbons, such as their surface characteristics and defects, was considered to be largely determined by the manufacturing conditions of single-roll rapid solidification method, and it was also reported that shape of nozzle used to spray molten magnesium also had a significant effect on the quality of ribbons. In this study, ribbons were produced using nozzles with various internal gradient angles, and the surface properties, cross-sectional structure, and internal and external defects of the ribbons were evaluated. In actual ribbon production, it was confirmed that a nozzle with a smaller gradient angle could produce ribbons with a stable yield of over 70%. This is because adding a gradient shape allows smooth molten metal to be sprayed out. In the microstructure observation of the ribbons, a network-like second phase was observed near the free-solidification surface. A difference in cell size was also confirmed with the change in nozzle shape. In addition, the relationship between cell size and hardness was investigated, and it was confirmed that the hardness value decreases as the cell size increases. © 2025 The Japan Institute of Light Metals.

关键词： Hardness

Open-Gap Algorithm for Fast Reactive Collision Avoidance by Autonomous UAV using Sensor Array

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Journal of Aeronautics, Astronautics and Aviation 2025年第3期57卷 505-511页

作者： Butt, Muhammad Zohaib Nasir, Nazri Rashid, Rozeha A. Tang, Collin H.H. Department of Aeronautics Automotive and Ocean Engineering Faculty of Mechanical Engineering Universiti Teknologi Malaysia Malaysia UTM Aero Lab Institute for Vehicle Systems & Engineering Universiti Teknologi Malaysia Malaysia Department of Communication Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Malaysia Department of Applied Mechanics and Design Faculty of Mechanical Engineering Universiti Teknologi Malaysia Malaysia

This paper presents a new local reactive collision avoidance strategy for autonomous unmanned aerial vehicles (UAVs) that operate in dynamic environments. Compared to ground robots, UAVs face greater challenges in terms of faster reaction time and encounter rapid environmental changes during low-flight operations due to their higher speed. Additionally, small UAVs have limited payload capacity, restricting their flight time, computational power, and sensing capabilities. For low-altitude autonomous flights, a fast and efficient computation approach is developed to avoid moving as well as stationary obstacles. Using a circular array of sensors onboard, the algorithm detects suitable open gaps within the circular proximity of the UAV. Then, to reach the designated target location, the algorithm chooses the most suitable gap. The proposed algorithm enhances the UAV’s ability at low-altitudes to perform collision-less navigation in unstructured environments without prior knowledge of the obstacle map. A simulated environment was used to test the proposed algorithm. © 2025 The Aeronautical and Astronautical Society of the Republic of China. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

Policy pathways utilizing extended producer responsibility and eco-modulation frameworks for sustainable food packaging waste management in India: A review

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Results in engineering 2025年 26卷

作者： Dey, Amrita Ashok S, Denis Department of Design and Automation Cyber-Physical Systems Lab School of Mechanical Engineering Vellore Institute of Technology Tamilnadu Vellore632014 India

Despite the growing concerns surrounding food packaging waste, India still lacks a well-defined and effectively enforced policy framework to tackle this issue. Multilayered packaging, constituting 35 % of total packaging in India, is currently deemed unrecyclable due to its complex structure and is currently landfilled. While countries like the UK, Belgium, France, Italy, and Canada have successfully implemented measures such as landfill taxes and "pay-as-you-throw" policies, India has yet to establish strict regulations and economic incentives to promote sustainable waste management. The absence of strong Extended Producer Responsibility (EPR) enforcement, inadequate eco-modulation strategies, and limited consumer incentives such as reduced GST on recycled products or rewards for eco-conscious practices highlight the urgent need for India to bridge this policy gap and adopt a more structured approach towards a circular economy. Strengthening of regulatory frameworks and a collaborative approach involving the government, producers, informal sector, and consumers is essential for developing an efficient waste management system. Through this review, we aim to highlight successful global strategies and motivate the adoption of similar policies in India to mitigate the growing environmental threat posed by food packaging waste. © 2025

关键词： Labels

Towards net-zero manufacturing: carbon-aware scheduling for GHG emissions reduction

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arXiv 2025年

作者： Mencaroni, Andrea Leyman, Pieter Raa, Birger De Vuyst, Stijn Claeys, Dieter Department of Industrial Systems Engineering and Product Design Ghent University Ghent Belgium Flanders Make Kortrijk Belgium

Detailed scheduling has traditionally been optimized for the reduction of makespan and manufacturing costs. However, growing awareness of environmental concerns and increasingly stringent regulations are pushing manufacturing towards reducing the carbon footprint of its operations. Scope 2 emissions, which are the indirect emissions related to the production and consumption of grid electricity, are in fact estimated to be responsible for more than one-third of the global GHG emissions. In this context, carbon-aware scheduling can serve as a powerful way to reduce manufacturing’s carbon footprint by considering the time-dependent carbon intensity of the grid and the availability of on-site renewable electricity. This study introduces a carbon-aware permutation flow-shop scheduling model designed to reduce scope 2 emissions. The model is formulated as a mixed-integer linear problem, taking into account the forecasted grid generation mix and available on-site renewable electricity, along with the set of jobs to be scheduled and their corresponding power requirements. The objective is to find an optimal day-ahead schedule that minimizes scope 2 emissions. The problem is addressed using a dedicated memetic algorithm, combining evolutionary strategy and local search. Results from computational experiments confirm that by considering the dynamic carbon intensity of the grid and on-site renewable electricity availability, substantial reductions in carbon emissions can be achieved. © 2025, CC BY-NC-SA.

关键词： Low emission

Self-Supervised Learning Using Nonlinear Dependence

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arXiv 2025年

作者： Sepanj, M. Hadi Ghojogh, Benyamin Fieguth, Paul Vision and Image Processing Group Systems Design Engineering University of Waterloo ON Canada Department of Electrical and Computer Engineering University of Waterloo ON Canada

Self-supervised learning has gained significant attention in contemporary applications, particularly due to the scarcity of labeled data. While existing SSL methodologies primarily address feature variance and linear correlations, they often neglect the intricate relations between samples and the nonlinear dependencies inherent in complex data. In this paper, we introduce Correlation-Dependence Self-Supervised Learning (CDSSL), a novel framework that unifies and extends existing SSL paradigms by integrating both linear correlations and nonlinear dependencies, encapsulating sample-wise and feature-wise interactions. Our approach incorporates the Hilbert-Schmidt Independence Criterion (HSIC) to robustly capture nonlinear dependencies within a Reproducing Kernel Hilbert Space, enriching representation learning. Experimental evaluations on diverse benchmarks demonstrate the efficacy of CDSSL in improving representation quality. Copyright © 2025, The Authors. All rights reserved.

关键词： Self-supervised learning

Competitive Multi-armed Bandit Games for Resource Sharing

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arXiv 2025年

作者： Li, Hongbo Duan, Lingjie Department of Electrical and Computer Engineering The Ohio State University ColumbusOH43210 United States Pillar of Engineering Systems and Design Singapore University of Technology and Design Singapore487372 Singapore

In modern resource-sharing systems, multiple agents access limited resources with unknown stochastic conditions to perform tasks. When multiple agents access the same resource (arm) simultaneously, they compete for successful usage, leading to contention and reduced rewards. This motivates our theoretical study of competitive multi-armed bandit (CMAB) games. In this paper, we study a new N-player K-arm competitive MAB game, where non-myopic players (agents) compete with each other to form diverse private estimations of unknown arms over time. Their possible collisions on the same arms and the time-varying nature of arm rewards make the policy analysis here more involved than the existing studies for myopic players. We explicitly analyze the threshold-based structures of the social optimum and the existing selfish policy, showing that the latter causes prolonged convergence times (Formula presented), while the socially optimal policy with coordinated communication reduces it to (Formula presented). Based on the policy comparison, we prove that the competition among selfish players for the best arm can result in an infinite price of anarchy (PoA), indicating an arbitrarily large efficiency loss compared to the social optimum. We further prove that no informational (non-monetary) mechanism (including Bayesian persuasion) can reduce the infinite PoA, as strategic misreporting by non-myopic players undermines such approaches. To address this, we propose a Combined Informational and Side-Payment (CISP) mechanism, which provides socially optimal arm recommendations with proper informational and monetary incentives to players according to their diverse and time-varying private beliefs. Our CISP mechanism keeps ex-post budget balanced for the social planner and ensures truthful reporting from players, thereby achieving the minimum PoA = 1 and the same convergence time as the social optimum. Copyright © 2025, The Authors. All rights reserved.

关键词： Budget control

ImprovNet: Generating Controllable Musical Improvisations with Iterative Corruption Refinement

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arXiv 2025年

作者： Bhandari, Keshav Chang, Sungkyun Lu, Tongyu Enus, Fareza R. Bradshaw, Louis B. Herremans, Dorien Colton, Simon Electronic Engineering and Computer Science Department Queen Mary University of London United Kingdom Information Systems Technology and Design Singapore University of Technology and Design Singapore

Deep learning has enabled remarkable advances in style transfer across various domains, offering new possibilities for creative content generation. However, in the realm of symbolic music, generating controllable and expressive performance-level style transfers for complete musical works remains challenging due to limited datasets, especially for genres such as jazz, and the lack of unified models that can handle multiple music generation tasks. This paper presents ImprovNet, a transformer-based architecture that generates expressive and controllable musical improvisations through a self-supervised corruption-refinement training strategy. ImprovNet unifies multiple capabilities within a single model: it can perform cross-genre and intra-genre improvisations, harmonize melodies with genre-specific styles, and execute short prompt continuation and infilling tasks. The model’s iterative generation framework allows users to control the degree of style transfer and structural similarity to the original composition. Objective and subjective evaluations demonstrate ImprovNet’s effectiveness in generating musically coherent improvisations while maintaining structural relationships with the original pieces. The model outperforms Anticipatory Music Transformer in short continuation and infilling tasks and successfully achieves recognizable genre conversion, with 79% of participants correctly identifying jazz-style improvisations. Our code and demo page can be found at https://***/keshavbhandari/improvnet. © 2025, CC BY.

关键词： Deep learning