Economic Evaluation of the Investment in Sensor Equipment Based on Data Valuation in Prediction Model by Jeong-Gi Lee, Deok-Joo Lee

“…On the other hand, MIBM is advantageous in scenarios where computational efficiency and robustness are prioritized. To support method selection, we also analyze the computational complexity of both approaches and derive error bounds. …”
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A comparative study of ultra-massive MIMO intelligent receivers with adversarial robustness and energy efficiency for 6G applications by Pushkar Nidagundi, Advesh Darvekar, Malik Amber, Ramesh R

“…Ultra-Massive Multiple Input Multiple Output (UM-MIMO) systems are pivotal for 6G wireless networks, enabling unprecedented data rates and spectral efficiency. However, optimizing these systems requires a careful balance between energy efficiency, spectral efficiency, and Bit Error Rate (BER) performance. …”
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Optimizing Machine Learning Models with Data-level Approximate Computing: The Role of Diverse Sampling, Precision Scaling, Quantization and Feature Selection Strategies by Ayad M. Dalloo, Amjad J. Humaidi

“…In this paper, we propose a framework that uses data-level approximate computing techniques, including by diverse sampling strategies, precision scaling, quantization, and feature selection methods, to evaluate the impact of these techniques on the computational efficiency and accuracy of KNN and SVM models. …”
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Improving inverter efficiency for electric vehicles: Experimental validation of the neural network-based SHE technique using RT-LAB by Seyf Eddine Bechekir, Mokhtaria Jbilou, Mostefa Brahami, Fatima Zohra Boudjella, Imen Souhila Bousmaha, Mimouna Oukli, Said Nemmich

“… Inverters are essential for converting direct current to alternating current in electric vehicles, relying on pulse width modulation (PWM) for efficiency. This study presents a real-time Selective Harmonic Elimination PWM (SHE-PWM) algorithm using artificial neural networks, validated with the OP5600 RT LAB simulator. …”
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Sequence-based engineering of pH-sensitive antibodies for tumor targeting or endosomal recycling applications by Wanlei Wei, Traian Sulea

“…This method, called Sequence-based Identification of pH-sensitive Antibody Binding (SIpHAB), was trained on 3D-structure-based calculations of 3,490 antibody-antigen complexes with solved experimental structures. SIpHAB was parametrized to enhance preferential binding either toward or against the acidic pH, for selective targeting of solid tumors or for antigen release in the endosome, respectively. …”
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Fast real-time detection and counting of thrips in greenhouses with multi-level feature attention and fusion by Zhangzhang He, Xinyue Chen, Ying Gao, Yu Zhang, Yuheng Guo, Tong Zhai, Xiaochen Wei, Huan Li, Haipeng Zhu, Yongkun Fu, Zhiliang Zhang, Zhiliang Zhang

“…Compared to existing methods, TCD-Net achieves higher thrips counting and detection accuracy with lower computational complexity. …”
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HERCULE: High-Efficiency Resource Coordination Using Kubernetes and Machine Learning in Edge Computing for Improved QoS and QoE by Garrik Brel Jagho Mdemaya, Miguel Landry Foko Sindjoung, Milliam Maxime Zekeng Ndadji, Mthulisi Velempini

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Transforming Retinal Photographs to Entropy Images in Deep Learning to Improve Automated Detection for Diabetic Retinopathy by Gen-Min Lin, Mei-Juan Chen, Chia-Hung Yeh, Yu-Yang Lin, Heng-Yu Kuo, Min-Hui Lin, Ming-Chin Chen, Shinfeng D. Lin, Ying Gao, Anran Ran, Carol Y. Cheung

“…Entropy images, representing the complexity of original fundus photographs, may strengthen the contrast between diabetic retinopathy (DR) lesions and unaffected areas. …”
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Performance Analysis of Maximum Likelihood Detection in Cooperative DF MIMO Systems with One-Bit ADCs by Tae-Kyoung Kim

“…Although joint maximum likelihood detection can efficiently mitigate error propagation by leveraging probabilistic information from a source-to-relay link, its computational complexity is impractical. …”
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Increasing efficiency and sustainability: A comparative analysis of concrete 3D printing and traditional methods based on case studies by Karamara Merve, Bogdanski Moritz-Ole, Zöller Raphael, Albrecht Sophie Viktoria, Linner Thomas, Bock Thomas, Braml Thomas

“…Concrete 3D printing offers several significant advantages, including the ability to create complex geometries, increased material efficiency, faster build times and cost savings. …”
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Visual Detection on Aircraft Wing Icing Process Using a Lightweight Deep Learning Model by Yang Yan, Chao Tang, Jirong Huang, Zhixiong Cen, Zonghong Xie

“…High transparency and blurred edges of icing areas in wing images pose challenges to wing icing detection by machine vision. To address these challenges, this study proposes a detection model, Wing Icing Detection DeeplabV3+ (WID-DeeplabV3+), for efficient and precise aircraft wing leading edge icing detection under natural lighting conditions. …”
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Surface Damage Detection in Hydraulic Structures from UAV Images Using Lightweight Neural Networks by Feng Han, Chongshi Gu

“…However, existing deep learning (DL) models often lack architectural adaptations for the visual complexities of UAV imagery, including low-texture contrast, noise interference, and irregular crack patterns. …”
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Lightweight multidimensional feature enhancement algorithm LPS-YOLO for UAV remote sensing target detection by Yong Lu, Minghao Sun

“…LPS-YOLO offers an effective solution for multi-target detection in UAVs.…”
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Advancing Software Vulnerability Detection with Reasoning LLMs: DeepSeek-R1′s Performance and Insights by Wenting Qin, Lijie Suo, Liangchen Li, Fan Yang

“…The increasing complexity of software systems has heightened the need for efficient and accurate vulnerability detection. …”
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Prioritizing image processing and big data analytics factors for software development using DEMATEL-choquet method in bipolar complex fuzzy context by Ruimin Ma

“…The causal effects indicate that feature extraction, automation and efficiency, as well as object detection, are critical causal factors, whereas image enhancement, security, and segmentation are dependent effects. …”
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Optimizing concrete crack detection an echo state network approach with improved fish migration optimization by Zhichun Fang, Xiuhong Wang, Jiaojiao Gao, Behrooz Eskandarpour

“…However, there are many models available for concrete crack detection, an efficient approach is needed because the existing methods often have flaws like overfitting, high computational complexity, and noise sensitivity, which can lead to accurate crack detection and classification. …”
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The application of deep learning technology in smart agriculture: Lightweight apple leaf disease detection model by Luo Man

“…These advancements make it robust, efficient, and practical for real-time disease detection in intelligent agricultural environments.…”
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DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

“…Simulation results confirm that the DTHC method achieves a spectrum hole detection accuracy of 99%, with a miss-detection probability below 0.9%, demonstrating its effectiveness in enhancing CRN performance while maintaining low complexity.…”
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LArcNet: Lightweight Neural Network for Real-Time Series AC Arc Fault Detection by Kamal Chandra Paul, Chen Chen, Yao Wang, Tiefu Zhao

“…Detecting series ac arc faults in diverse residential loads is challenging due to variations in load characteristics and noise. …”
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Improved method of targeted user interface updates for enhancing the efficiency of web applications based on reactive streams and virtual DOM by M.V. Havatiuk, I.O. Saiapina

“…By integrating the strengths of the aforementioned technologies, the method significantly enhances performance, reduces browser load, and improves interface responsiveness even in complex application logic scenarios. Special attention is given to the architectural structure of the solution, the mechanisms for detecting changes, and the evaluation of dependencies between state and UI components. …”
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