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Exploring Applications of Convolutional Neural Networks in Analyzing Multispectral Satellite Imagery:A Systematic Review

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Big Data Mining and Analytics 2025年第2期8卷 407-429页

作者： Antonia Ivanda LjiljanaŠerić Maja Braović Department of Electronics and Computer Science Faculty of Electrical EngineeringMechanical Engineering and Naval ArchitectureUniversity of SplitSplit 21000Croatia

Remote sensing is of great importance for analyzing and studying various phenomena occurrence and development on *** is possible to extract features specific to various fields of application with the application of modern machine learning techniques,such as Convolutional Neural Networks(CNN)on MultiSpectral Images(MSI).This systematic review examines the application of 1D-,2D-,3D-,and 4D-CNNs to MSI,following Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)*** review addresses three Research Questions(RQ):RQ1:“In which application domains different CNN models have been successfully applied for processing MSI data?”,RQ2:“What are the commonly utilized MSI datasets for training CNN models in the context of processing multispectral satellite imagery?”,and RQ3:“How does the degree of CNN complexity impact the performance of classification,regression or segmentation tasks for multispectral satellite imagery?”.Publications are selected from three databases,Web of Science,IEEE Xplore,and *** on the obtained results,the main conclusions are:(1)The majority of studies are applied in the field of agriculture and are using Sentinel-2 satellite data;(2)Publications implementing 1D-,2D-,and 3D-CNNs mostly utilize *** 4D-CNN,there are limited number of studies,and all of them use segmentation;(3)This study shows that 2D-CNNs prevail in all application domains,but 3D-CNNs prove to be better for spatio-temporal pattern recognition,more specifically in agricultural and environmental monitoring applications.1D-CNNs are less common compared to 2D-CNNs and 3D-CNNs,but they show good performance in spectral analysis tasks.4D-CNNs are more complex and still underutilized,but they have potential for complex data *** details about metrics according to each CNN are provided in the text and supplementary files,offering a comprehensive overview of the evaluation metrics for each type of machine learning technique

关键词： remote sensing MultiSpectral Images(MSI) satellite images Convolutional Neural Networks(CNN) machine learning classification regression segmentation

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THEMIS: Time, Heterogeneity, and Energy Minded Scheduling for Fair Multi-Tenant Use in FPGAs

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IEEE Transactions on computers 2025年第7期74卷 2515-2528页

作者： Karabulut, Emre Malik, Arsalan Ali Awad, Amro Aysu, Aydin University of Oxford Department of Electrical Engineering United Kingdom North Carolina State University Department of Electrical and Computer Engineering RaleighNC27606 United States

Using correct design metrics and understanding the limitations of the underlying technology is critical to developing effective scheduling algorithms. Unfortunately, existing scheduling techniques used incorrect metrics and had un-realistic assumptions for fair scheduling of multi-tenant FPGAs where each tenant is aimed to share approximately the same number of resources both spatially (in space) and temporally (in time). This paper proposes an improved fair scheduling algorithm that fixes earlier issues with metrics and assumptions for ‘fair’ multi-tenant FPGA use. Specifically, we claim three improvements. First, we consider both spatial and temporal aspects to provide spatiotemporal fairness—this improves a recent prior work that assumed all tasks would have the same latency. Second, we add the energy dimension to fairness: by calibrating the scheduling decision intervals and including their energy overhead, our algorithm offers trading off energy efficiency for fairness. Third, we consider previously ignored facts about FPGA multi-tenancy, such as the existence of heterogeneous regions and the inflexibility of run-time merging/splitting of partially reconfigurable *** develop and evaluate our improved fair scheduling algorithm with these three enhancements. Inspired by the Greek goddess of law and personification of justice, we name our fair scheduling solution THEMIS: Time, Heterogeneity, and Energy Minded Scheduling. We implemented our solution on Xilinx Zedboard XC7Z020 with real hardware workloads and used real measurements on the FPGA to quantify the savings of our approach. Compared to previous algorithms, our improved scheduling algorithm enhances fairness between 24.2–98.4% and allows a trade-off between 55.3× in energy vs. 69.3× in fairness. The paper thus informs cloud providers about future scheduling optimizations for fairness with related challenges and opportunities. © 1968-2012 IEEE.

关键词： Scheduling algorithms

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Scheduling Policies in a Multi-Source Status Update System with Dedicated and Shared Servers

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IEEE Internet of Things Journal 2025年第13期12卷 22772-22785页

作者： Liyanaarachchi, Sahan Ulukus, Sennur Akar, Nail University of Maryland Department of Electrical and Computer Engineering College ParkMD20742 United States Bilkent University Electrical and Electronics Engineering Department Ankara Turkey

Use of multi-path network topologies has become a prominent technique to assert timeliness in terms of age of information (AoI) and to improve resilience to link disruptions in communication systems. However, establishing multiple dedicated communication links among network nodes is a costly endeavor. Therefore, quite often, these secondary communication links are shared among multiple entities. Moreover, these multi-path networks come with the added challenge of out-of-order transmissions. In this paper, we study an amalgamation of the above two aspects, i.e., multi-path transmissions and link sharing. In contrast to the existing literature where the main focus has been scheduling multiple sources on a single shared server, we delve into the realm where each source sharing the shared server is also supplemented with its dedicated server so as to improve its timeliness. In this multi-path link sharing setting with generate-at-will transmissions, we first present the optimal probabilistic scheduler, and then propose several heuristic-based cyclic scheduling algorithms for the shared server, to minimize the weighted average age of information of the sources. © 2014 IEEE.

关键词： Servers Probabilistic logic Optimal scheduling Out of order Queueing analysis Relay networks Moon Monitoring Job shop scheduling Information age

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Data delivery delay and cross-layer packet size analysis for reliable transmission of Licklider transmission protocol in space networks

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Science China(Information Sciences) 2024年第9期67卷 229-244页

作者： Guannan YANG Ruhai WANG Kanglian ZHAO Wenfeng LI Dong YAN School of Information Engineering Nanjing University of Finance and Economics Drayer Department of Electrical and Computer Engineering Lamar University School of Electronic Science and Engineering Nanjing University Beijing Aircraft Overall Design Department

Delay/disruption tolerant networking(DTN) is proposed as a networking architecture to overcome challenging space communication characteristics for reliable data transmission service in presence of long propagation delays and/or lengthy link disruptions. Bundle protocol(BP) and Licklider Transmission Protocol(LTP) are the main key technologies for DTN. LTP red transmission offers a reliable transmission mechanism for space networks. One of the key metrics used to measure the performance of LTP in space applications is the end-to-end data delivery delay, which is influenced by factors such as the quality of spatial channels and the size of cross-layer packets. In this paper, an end-to-end reliable data delivery delay model of LTP red transmission is proposed using a roulette wheel algorithm, and the roulette wheel algorithm is more in line with the typical random characteristics in space networks. The proposed models are validated through real data transmission experiments on a semi-physical testing platform. Furthermore, the impact of cross-layer packet size on the performance of LTP reliable transmission is analyzed, with a focus on bundle size, block size, and segment size. The analysis and study results presented in this paper offer valuable contributions towards enhancing the reliability of LTP transmission in space communication scenarios.

关键词： Licklider transmission protocol DTN bundle protocol cross-layer packets size space communication

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CEEO: an innovative Coulomb-enhanced Equilibrium Optimizer for task scheduling of cloud services in IoT environments

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Computing 2025年第6期107卷 1-24页

作者： Ebrahimi Mood, Sepehr Souri, Alireza İnanç, Nihat Li, Kuan-Ching Department of Computer Science Yazd University Yazd Iran Department of Computer Engineering Faculty of Engineering Haliç University Istanbul34060 Turkey Department of Electrical and Electronics Engineering Faculty of Engineering Haliç University Istanbul34060 Turkey Department of computer science and information engineering Providence University Taichung43301 Taiwan

In this paper, we address the multi-objective task scheduling problem in cloud computing environments for IoT-generated tasks, focusing on minimizing makespan, load imbalance, energy consumption, and CO2 emissions. We propose a novel load imbalance metric tailored for this specific context and introduce an enhanced Equilibrium Optimizer (EO) algorithm, termed CEEO. The CEEO integrates a Coulomb operator inspired by Coulomb’s law to improve exploration and escape local optima in multimodal optimization problems. The algorithm’s performance is evaluated using standard benchmark functions from CEC2017, where it demonstrates significant improvements over existing optimization algorithms in terms of convergence speed and solution quality. In addition, the CEEO is applied to a simulated cloud computing task scheduling environment, considering varying numbers of tasks and virtual machines. The results reveal that CEEO consistently outperforms other scheduling algorithms, reducing makespan and improving load balancing, energy consumption, and CO2 emissions. Statistical analysis using the Friedman test confirms the statistical significance of these improvements. This research provides an efficient and robust solution for multi-objective task scheduling in cloud computing, offering substantial improvements in operational costs, execution time, and overall service quality. © The Author(s) 2025.

关键词： Scheduling algorithms

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Photobiomodulation Therapy;Survey and Principal Study Leading to Design Rules for Implants

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IEEE Transactions on biomedical engineering 2025年第7期72卷 2237-2248页

作者： Kaffash, Zohreh Saha, Reepa Mirbozorgi, S. Ali Faezipour, Miad Mirbozorgi, S. Abdollah University of Alabama at Birmingham Electrical and Computer Engineering Department BirminghamAL United States Purdue University School of Engineering Technology Electrical and Computer Engineering Technology West LafayetteIN United States Birjand University Mechanical Engineering Department Birjand Iran

Photobiomodulation (PBM) therapy using red- and near-infrared (NIR) light has shown beneficial regenerative effects on cell functionalities and consequently on health applications. Light parameter values, particularly power density, significantly affect the treatment outcomes. The limited use of light in transcutaneous applications is due to the power attenuation challenge, which restricts the transmission of light energy to deeper tissues. However, the potential of light therapy to restore cellular function presents a promising strategy for regenerating of cells in internal human organs. We have 1) studied the mechanism and impact of red light at the cellular level, 2) reviewed the literature and classified the research done using light therapy, indicating the positive and negative effects associated with the light power density and exposure time levels, and 3) proposed a design rule for designing PBM implants targeting interior organs. Therefore, this work leads to 1) designing safe and efficient implantable devices by extracting the necessary light parameters, and 2) expanding the applications of light therapy. The range of the red-light power density used in different studies starts from 10 mW-cm2 to as big as 5000 mW-cm2 in a few cases, and from 10 s to 3000 s for different exposure times. According to the light parameters, we have tested different types of off-the-shelf LEDs to experimentally find the correlation between the generated light power densities at different distances from light sources and the LEDs' input electrical power. We have found that for an average light power density of 100 mW-cm2 over an area of 1 cm2, the input power of 18 mW must be delivered to the LED, which is achievable safely via wireless inductive links for delivering sufficient power deep in the body with under 1.6 W-kg of specific absorption rate (SAR). A design rule and approach are provided in this work as a starting point for designing PBM implants. © 1964-2012 IEEE.

关键词： Laser beams

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Survivability evaluation for networks carrying complex traffic flows

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Digital Communications and Networks 2023年第2期9卷 534-544页

作者： Amin Jamali Mehdi Berenjkoub Hossein Saidi Behrouz Shahgholi Ghahfarokhi Faculty of Computer Engineering University of IsfahanIsfahan***Iran Department of Electrical and Computer Engineering Isfahan University of TechnologyIsfahan***Iran

The capability of a system to fulfill its mission promptly in the presence of attacks,failures,or accidents is one of the qualitative definitions of *** this paper,we propose a model for survivability quantification,which is acceptable for networks carrying complex traffic *** network traffic is considered as general multi-rate,heterogeneous traffic,where the individual bandwidth demands may aggregate in complex,nonlinear *** probability is the chosen measure for survivability *** study an arbitrary topology and some other known topologies for the *** and dependent failure scenarios as well as deterministic and random traffic models are ***,we provide survivability evaluation results for different network *** results show that by using about 50%of the link capacity in networks with a relatively high number of links,the blocking probability remains near zero in the case of a limited number of failures.

关键词： Blocking probability Complex traffic Link failure Network survivability Disaster recovery Information assurance

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Bayesian Active Learning-Based Soft Data Space Calibration for System-Wise Aggregate Flexibility Characterization

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IEEE Transactions on Smart Grid 2025年第4期16卷 3017-3029页

作者： Wang, Shengyi Du, Liang Chen, Xin Temple University Department of Electrical and Computer Engineering PhiladelphiaPA19122 United States Texas A and M University Department of Electrical and Computer Engineering College StationTX77843 United States

There have been growing interests in characterizing system-wide aggregate flexibility to support transmission-side ancillary services and promote large-scale integration of distributed energy resources (DERs). However, accurately characterizing the power flexibility region (PFR) at the substation interface is computationally challenging due to the heterogeneity of the DER devices and the need to satisfy network constraints, resulting in a nonlinear and unpredictable geometry. Therefore, this paper proposes a network-aware, near-optimal, and sample-efficient data-driven method. First, a bus-level PFR estimation model is proposed to aggregate local DER devices at each bus into an inner-box approximated region. Second, a feeder-level PFR estimation model is proposed to aggregate all bus-level PFRs into an outer-box approximated region. A Bayesian active learning- based soft calibration strategy is proposed to iteratively and interactively learn a decision boundary of the binary classifier as an improved feeder-level PFR while providing trustworthy measurement to system operators. Case studies on a small, illustrative IEEE system and modified IEEE 123 bus test feeder validate effectiveness of the proposed methods. © 2010-2012 IEEE.

关键词： Distributed energy

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Computational defocus correction in spatial frequency domain imaging 16

Computational defocus correction in spatial frequency domain...

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Optical Tomography and Spectroscopy of Tissue XVI 2025

作者： Dao, Dylan Jiao, Jie Kuramoto, Lindsay Levi, Ofer Department of Electrical and Computer Engineering University of Toronto Canada Institute of Biomedical Engineering University of Toronto Canada

ISBN: (纸本)9781510683761

In spatial frequency domain imaging (SFDI), tissue optical properties are estimated by projecting spatial frequencies on the tissue and measuring back-scattered reflectance. We characterize the measurement error in camera-defocused SFDI and evaluate 1) dividing the defocus response and 2) cubic phase mask approaches in recovering SFDI performance. Camera-defocused SFDI underestimates tissue optical properties and loses spatial resolution. Both methods are shown to double the object distance range over which optical property measurements are within 25% of best focus values, though spatial resolution is lost. This work extends SFDI’s potential applications to remotely monitoring cardiovascular health in clinics and homes. © 2025 SPIE.

关键词： Aberrations

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A Self-Aware Digital Memory Framework Powered by Artificial Intelligence

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3579-3594页

作者： Chakraborty, Prabuddha Bhunia, Swarup University of Maine Department of Electrical & Computer Engineering OronoME04469 United States University of Florida Department of Electrical & Computer Engineering GainesvilleFL32603 United States

Edge computing devices in Internet-of-Things (IoT) systems are being widely used in diverse application domains including industrial automation, surveillance, and smart housing. These applications typically employ a large array of sensors, store a high volume of data, and search within the stored data for specific patterns using machine intelligence. Due to this heavy reliance on data in these applications, optimizing the memory performance in edge devices has become an important research focus. In this work, we note (based on some preliminary quantitative studies) that the memory requirements of such application-specific systems tend to differ drastically from traditional general-purpose computing systems. Inspired by these findings and also through drawing inspiration from the human brain (which excels at being highly adaptive), we design a digital memory framework that can continually adapt to the specific needs of different edge devices. This adaption is made possible through a continual reinforcement-based learning methodology, and it aims at creating a digital memory framework that is always self-aware of the data it hold and queries being made. Through a methodical implementation of the framework, we demonstrate its effectiveness for different use-cases, settings, and hyperparameters in comparison with traditional content-addressable memory. © 2020 IEEE.

关键词： Internet of things

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