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Optical Fibers and Sensors for Medical Diagnostics, Treatment, and Environmental Applications XXV 2025

作者： Alexis, Al Anderson, London Khan, Mohammad A. Division of Physics Engineering Mathematics and Computer Science Optical Science Center for Applied Research Delaware State University 1200 N. Dupont Hwy DoverDE19901 United States

ISBN: (纸本)9781510683686

Mid-infrared laser-based sensing is widely used for the detection and quantification of trace gases for environmental monitoring, industrial process control, defense, and security applications. However, such laser spectroscopy-based field instruments require frequent calibration to correct for long-term drifts and precision. In many situations, such calibrations may be redundant and may not be effective in monitoring instrument errors or discriminating "real"environmental effects with instrument drifts. This paper shows that physics and diffusion-based models can be developed to predict gradual or rapid changes in density at given temperatures and appropriate source characterizations. We used a 3.3μm, laser-based instrument to demonstrate an adaptive and auto-calibration methodology to account for drifts during field deployments and an adaptive method to validate environmental changes, e.g., plume detection, diurnal variations, and flux emissions. We field operation and implementation of adaptive auto-calibration. The instruments are used for the detection of methane and water vapor, but an adaptive auto-calibration technique can be employed for any laser sensing instrument. © 2025 SPIE.

关键词： Laser spectroscopy

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Optimizing Fresh Food Supply Chains: Leveraging 3PL for Carbon Reduction and Profit Maximization - A Game-Theoretic Analysis

Optimizing Fresh Food Supply Chains: Leveraging 3PL for Carb...

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IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)

作者： Anil Dhanda Divya Aggarwal Lovely Jain Priyansh Tyagi Mandeep Mittal Abhay Bansal Department of Mathematics Amity Institute of Applied Sciences Amity University Noida Uttar Pradesh India Department of Mathematics School of Computer Science Engineering and Technology Bennett University Greater Noida India

ISBN: (数字)9798350385922

ISBN: (纸本)9798350385939

Mounting pressure on governments to reduce carbon emissions has forced them to impose regulations on supply chain members. Carbon cap-and-trade regulation has been widely adopted as a means to reduce carbon emissions. A fresh food supply chain involving a Manufacturer, 3PL, and a retailer is introduced. The 3PL is used by the manufacturer for its logistics because of its expertise, resources, and sustainable practices, Also many third-party logistics companies(3PL) offer refrigerated logistics services to the retailer and the 3PL has an overabundance of carbon permits. Trading of permits occurs and the impact on the retail price, the price of refrigerated logistics services in different carbon trading options, without carbon trade, inner carbon trade, and inner and outer carbon trade is studied. The prices are optimized through a game-theoretic approach, we model the trading of carbon permits as a leader-follower game with the 3PL as leader and Retailer as followers. The items are assumed to be of imperfect quality when delivered to the retailer by the 3PL.

关键词： Costs Supply chains Government Carbon dioxide Emissions trading Games Regulation

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Fractional order modeling of dengue transmission dynamics in Bangladesh

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Partial Differential Equations in applied mathematics 2025年 14卷

作者： Sikder, Arun Kumar Islam, Md Hamidul Department of Computer Science and Engineering Varendra University Rajshahi 6204 Bangladesh Department of Applied Mathematics University of Rajshahi Rajshahi 6205 Bangladesh

Over the past three decades, the epidemiological characteristics of dengue fever in Bangladesh have raised significant public health concerns, with the disease progressively spreading across the country's subtropical and tropical regions since 2004. This study introduces a fractional-order mathematical model that incorporates both human and mosquito populations using Caputo derivatives to account for memory and hereditary effects in disease transmission. Analytical solutions are approximated using the Laplace–Adomian decomposition method, while the Adams–Bashforth-Moulton predictor–corrector (PECE) scheme is applied for numerical solutions. Model parameters are estimated via the maximum likelihood method, using dengue case data from Bangladesh (June 1, 2022–September 30, 2022). Our findings indicate that the fractional-order model effectively captures a range of transmission scenarios, with lower derivative orders correlating with reduced outbreak severity. Moreover, numerical solutions exhibit higher accuracy compared to analytical approximations, particularly for complex nonlinear systems. Additionally, the results suggest that controlling mosquito populations, reducing transmission rates, and improving treatment measures are critical strategies for dengue mitigation. © 2025 The Authors

关键词： Dengue fever Fractional order modeling LADM Mathematical modeling MLE fitting Monte Carlo method PECE method

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Exploring 3D Reconstruction with Drone Images: Advances and Challenges in Urban Environments 50

Exploring 3D Reconstruction with Drone Images: Advances and ...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Miranda Baldivieso, Thiago João da Silva Batista, Taise Grazielle Chagas, Fabio Suim Rodrigues Velho, Luiz Carlos Pacheco Ferreira Rosa, Paulo Fernando Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil State Institute of the Environment Inea RJ Rio de Janeiro Brazil Department of Science and Industry systems University of South-Eastern Norway Kongsberg Norway Department of Computer Graphics Institute for Pure and Applied Mathematics Rio de Janeiro Brazil Electrical Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

ISBN: (纸本)9781665464543

This working-in-progress paper aims to present a three-dimensional reconstruction using aerial images in different environments. The experiments were conducted with aircraft in both external and internal settings, starting with image acquisition, followed by the application of specific photogrammetry software-both commercial and open-source-and concluding with a qualitative evaluation of the results. © 2024 IEEE.

关键词： Aerial photography

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Thermal-Aware Channel Capacity

Thermal-Aware Channel Capacity

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2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Meng Chee, Yeow Etzion, Tuvi Schouhamer Immink, Kees A. Thanh Nguyen, Tuan Khu Vu, Van Weber, Jos H. Yaakobi, Eitan National University of Singapore Department of Industrial Systems Engineering and Management Singapore Technion - Israel Institute of Technology Department of Computer Science Haifa3200003 Israel Turing Machines Inc. Rotterdam3016 DK Netherlands Singapore University of Technology and Design Science Mathematics and Technology Cluster Singapore Delft University of Technology Department of Applied Mathematics Delft2628 CD Netherlands

ISBN: (纸本)9781665475549

High temperatures in electronic devices have a negative effect on their performance. Various techniques have been proposed and studied to address and combat this thermal challenge. To guarantee that the peak temperature of the devices will be bounded by some maximum temperature, the transmitted signal has to satisfy some *** this motivation, we study the constrained channel that only accepts sequences that satisfy prescribed thermal constraints. The main goal in this paper is to compute the capacity of this channel. We provide the exact capacity of the channel with some certain parameters and we also present some bounds on the capacity in various ***, we consider the model that multiple wires are available to use and find out the smallest number of wires required to satisfy the thermal constraints. © 2023 IEEE.

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Discovering High Utility Episodes in Sequences

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第3期4卷 473-486页

作者： Gan, Wensheng Lin, Jerry Chun-Wei Chao, Han-Chieh Yu, Philip S. Jinan University College of Cyber Security Guangzhou510632 China Pazhou Lab Guangzhou510330 China Western Norway University of Applied Sciences Department of Computing Mathematics and Physics Bergen5063 Norway National Dong Hwa University Department of Electrical Engineering Hualien974 Taiwan University of Illinois at Chicago Department of Computer Science ChicagoIL60607 United States

Sequence data are more commonly seen than other types of data (e.g., transaction data) in real-world applications. For the mining task from sequence data, several problems have been formulated, such as sequential pattern mining, episode mining, and sequential rule mining. As one of the fundamental problems, episode mining has often been studied. The common wisdom is that discovering frequent episodes is not useful enough. In this article, we propose an efficient utility mining approach, namely, UMEpi: utility mining of high-utility episodes from complex event sequences. We propose the concept of remaining utility of episodes and achieve a tighter upper bound, namely, episode-weighted utilization (EWU), which will provide better pruning. Thus, the optimized EWU-based pruning strategies can achieve better improvements in mining efficiency. The search space of UMEpi w.r.t. a prefix-based lexicographic sequence tree is spanned and determined recursively for mining high-utility episodes, by prefix-spanning in a depth-first way. Finally, extensive experiments on four real-life datasets demonstrate that UMEpi can discover the complete high-utility episodes from complex event sequences. Furthermore, the improved variants of UMEpi significantly outperform the baseline in terms of execution time, memory consumption, and scalability. © 2020 IEEE.

关键词： Artificial intelligence

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Refining Blockchain-Powered Industrial Internet-of-Things Architecture for Improved Performance

Refining Blockchain-Powered Industrial Internet-of-Things Ar...

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Blockchain Computing and Applications (BCCA), International Conference on

作者： Ishaya Gambo Timilehin Ogundare Michael Magreola Temitope Ajayi Department of Computer Science and Engineering Obafemi Awolowo University Ile-Ife Nigeria Computer Science and Applied Mathematics University of the Witwatersrand Johannesburg South Africa Department of Computer Science University of Arkansas AR USA

This paper introduces a high-performance blockchain solution to enhance Industrial Internet of Things (IIoT) operations, effectively addressing the challenge of reconciling blockchain's computational demands with the limited capabilities of IIoT devices. Through quantitative research, we present an IIoT blockchain-powered deep reinforcement learning performance optimization protocol. Our evaluation covers key aspects such as latency, scalability, security, and decentralization, demonstrating enhanced scalability without compromising security or latency. We establish a scalable and robust blockchain architecture tailored for high-processing IIoT systems, fine-tuning its components using deep reinforcement learning. Our simulations illustrate the framework's capacity to significantly boost the performance of blockchain-powered IIoT systems while adapting to their diverse operational dynamics.

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K-Banhatti Invariants Empowered Topological Investigation of Bridge Networks

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computers, Materials & Continua 2022年第12期73卷 5423-5440页

作者： Khalid Hamid Muhammad Waseem Iqbal Erssa Arif Yasir Mahmood Ahmad Salman Khan Nazri Kama Azri Azmi Atif Ikram Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Software Engineering Faculty of Information TechnologyThe University of Lahore54000Pakistan Advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi MalaysiaKuala Lumpur54100Malaysia Faculty of Informatics and Applied Mathematics University Malaysia TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of Lahore54000Pakistan

Any number that can be uniquely determined by a graph is called graph *** the most recent twenty years’innumerable numerical graph invariants have been described and used for correlation *** the fast and advanced environment of manufacturing of networks and other products which used different networks,no dependable assessment has been embraced to choose,how much these invariants are connected with a network graph or molecular *** this paper,it will talk about three distinct variations of bridge networks with great capability of expectation in the field of computer science,chemistry,physics,drug industry,informatics,and mathematics in setting with physical and synthetic constructions and networks,since K-Banhatti invariants are newly introduced and have various forecast characteristics for various variations of bridge graphs or *** review settled the topology of bridge graph/networks of three unique sorts with three types of K-Banhatti *** concluded outcomes can be utilized for the modeling of interconnection networks of Personal computers(PC),networks like Local area network(LAN),Metropolitan area network(MAN)and Wide area network(WAN),the spine of internet and different networks/designs of PCs,power generation interconnection,bio-informatics and chemical structures.

关键词： Bridge networks invariants k-banhatti indices maple network graph molecular graph

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Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms

arXiv

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arXiv 2024年

作者： Wanner, Marc Lewis, Laura Bhattacharyya, Chiranjib Dubhashi, Devdatt Gheorghiu, Alexandru Department of Computer Science and Engineering Chalmers University of Technology University of Gothenburg Gothenburg Sweden Department of Applied Mathematics and Theoretical Physics University of Cambridge Cambridge United Kingdom Department of Computer Science and Automation Indian Institute of Science Bangalore India Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden

A fundamental problem in quantum many-body physics is that of finding ground states of local Hamiltonians. A number of recent works gave provably efficient machine learning (ML) algorithms for learning ground states. Specifically, Huang et al. in [1], introduced an approach for learning properties of the ground state of an n-qubit gapped local Hamiltonian H from only nO(1) data points sampled from Hamiltonians in the same phase of matter. This was subsequently improved by Lewis et al. in [2], to O(log n) samples when the geometry of the n-qubit system is known. In this work, we introduce two approaches that achieve a constant sample complexity, independent of system size n, for learning ground state properties. Our first algorithm consists of a simple modification of the ML model used by Lewis et al. and applies to a property of interest known in advance. Our second algorithm, which applies even if a description of the property is not known, is a deep neural network model. While empirical results showing the performance of neural networks have been demonstrated, to our knowledge, this is the first rigorous sample complexity bound on a neural network model for predicting ground state properties. We also perform numerical experiments on systems of up to 45 qubits that confirm the improved scaling of our approach compared to [1, 2]. © 2024, CC BY.

关键词： Qubits

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To Heart via Liver: a Study on Prognostic Stratification of Heart Disease in MASLD Patients using Machine Learning Models 3

To Heart via Liver: a Study on Prognostic Stratification of ...

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3rd AIxIA Workshop on Artificial Intelligence For Healthcare, HC@AIxIA 2024

作者： Bruno, Pierangela Cirella, Antonio Di Cesare, Ernesto Greco, Gianluigi Guzzo, Antonella Palumbo, Pierpaolo Santini, Silvano Sinatti, Gaia Vittorini, Pierpaolo Calimeri, Francesco Balsano, Clara Department of Mathematics and Computer Science University of Calabria Rende Italy Department of Clinical Medicine Life Health & Environmental Sciences-MESVA University of L'Aquila Italy Department of Applied Clinical Sciences and Biotechnology University of L'Aquila Italy Department of Informatics Modeling Electronics and Systems Engineering University of Calabria Rende Italy

Accurate cardiovascular (CV) risk assessment is relevant for asymptomatic individuals, in particular for those at risk for cardiovascular diseases (CVD). Metabolic-associated fatty liver disease (MASLD), previously known as non-alcoholic fatty liver disease (NAFLD), is recognized as a critical independent risk factor for increased CV morbidity and mortality. With a prevalence of 25% in the general population, MASLD is the leading cause of chronic liver diseases and is strongly associated with the development of coronary artery disease (CAD). Coronary CT is widely used to detect CAD, and it can also assess liver steatosis, providing valuable prognostic information for at-risk patients. In this paper, we present a study on methods for performing prognostic stratification of CAD risk in asymptomatic MASLD patients using machine learning (ML) approaches. In particular, we conducted a retrospective analysis of clinical data from 60 patients who underwent Coronary CT at L'Aquila Hospital (Italy) between 2017 and 2021. Dataset includes significant features, such as radiodensity (Hounsfield Unit), calcium score (Agatston score), and liver fibrosis (Fib-4 score and APRI). We compared several ML algorithms (Logistic Regression, Support Vector Classifier (SVC), Random Forest, Extreme Gradient Boosting, K-Nearest Neighbors (KNN), Naive Bayes), with the main goal of performing binary classification tasks and creating a model able to differentiate between healthy patients and those affected by both MASLD and CVD. SVCs emerged as the best-performing models, achieving an AUC of 94%, an accuracy of 95%, and a recall of 94%. Our approach offers a robust and accurate tool for predicting CAD risk in MASLD patients, providing a valuable contribution to clinical practice for early CV risk stratification and management. © 2024 CEUR-WS. All rights reserved.

关键词： Risk assessment

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