Reliability and Quality of Complex Systems by I.V. Peshkov, V.A. Zhigulin, N.A. Fortunova

“…The results obtained demonstrate the correctness of the operation of the obtained hardware and software models, and also indicate the effectiveness of the calibration method used – an increase in the resolution of the direction finding algorithms is observed on the graphs. This improvement is maintained at different angles of arrival of the signal and when the SNR changes. …”

Balancing Predictive Performance and Interpretability in Machine Learning: A Scoring System and an Empirical Study in Traffic Prediction by Fabian Obster, Monica I. Ciolacu, Andreas Humpe

“…Further research should extend this analysis to unstructured data, explore different interpretability methods, and develop new metrics for evaluating the trade-off across diverse contexts.…”
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BLE phase-based ranging: accuracy and capability under strong Wi-Fi interference by Igor Kravets, Nazarii Kotliar, Oleksandr Karpin, Andriy Luchechko

“…This overlap often leads to interference that affects the performance of BLE systems. This work evaluates the effect of Wi-Fi interference on the phasebased ranging distance estimate for different BLE to Wi-Fi signal power ratios. …”
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Reference gene selection for qPCR is dependent on cell type rather than treatment in colonic and vaginal human epithelial cell lines. by Annette V Jacobsen, Bisrat T Yemaneab, Jana Jass, Nikolai Scherbak

“…In this study we used quantitative polymerase chain reaction data and applied four different algorithms (geNorm, BestKeeper, NormFinder, and comparative ΔCq) to evaluate eleven different genes as to their suitability as endogenous controls for use in studies involving colonic (HT-29) and vaginal (VK2/E6E7) human mucosal epithelial cells treated with probiotic and pathogenic bacteria. …”
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Intelligent Fault Diagnosis of Hydraulic System Based on Multiscale One-Dimensional Convolutional Neural Networks with Multiattention Mechanism by Jiacheng Sun, Hua Ding, Ning Li, Xiaochun Sun, Xiaoxin Dong

“…Finally, the proposed method is evaluated and experimentally compared using the UCI hydraulic system dataset. …”
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Integrating Machine Learning and Deep Learning for Predicting Non-Surgical Root Canal Treatment Outcomes Using Two-Dimensional Periapical Radiographs by Catalina Bennasar, Antonio Nadal-Martínez, Sebastiana Arroyo, Yolanda Gonzalez-Cid, Ángel Arturo López-González, Pedro Juan Tárraga

“…After incorporating the DL-based predictive variable, the ML algorithm that demonstrated the best performance was logistic regression (LR), differing from the previous study, where random forest (RF) was the top performer. …”
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Lesion assessment in multiple sclerosis: a comparison between synthetic and conventional fluid-attenuated inversion recovery imaging by Roald Ruwen Essel, Britta Krieger, Barbara Bellenberg, Dajana Müller, Theodoros Ladopoulos, Ralf Gold, Ruth Schneider, Carsten Lukas, Carsten Lukas

“…Lesion segmentation was performed using the Lesion Prediction Algorithm within the Lesion Segmentation Toolbox. For the assessment of spatial differences between lesion segmentations from both sequences, all lesion masks were registered to a brain template in the standard space. …”
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Multi‐objective digital circuit block optimisation based on cell mapping in an industrial electronic design automation flow by Linan Cao, Simon J. Bale, Martin A. Trefzer

“…It specifically tunes drive strength mapping, prior to physical implementation, through MO population‐based search algorithms. Designs are evaluated with respect to their power, performance and area (PPA). …”
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Context Aware Task Orchestration With Deep Reinforcement Learning in Real Time Fog Computing Simulation Environment by Alp Gokhan Hossucu, Suat Ozdemir

“…The proposed approach offers substantial advantages in terms of task succession, energy efficiency, and resource utilization. The system was evaluated in a simulation developed under different fog computing environmental conditions in terms of edge device and task density. …”
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IMPLEMENTATION OF K-MEDOIDS AND K-PROTOTYPES CLUSTERING FOR EARLY DETECTION OF HYPERTENSION DISEASE by Hardianti Hafid, Selvi Annisa

“…Overall, the K-Medoids and K-Prototypes algorithms can detect early hypertension risk by dividing patients into different risk groups. …”
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CLASSIFICATION OF IRRIGATION MANAGEMENT PRACTICES IN MAIZE HYBRIDS USING MULTISPECTRAL SENSORS AND MACHINE LEARNING TECHNIQUES by João L. G de Oliveira, Dthenifer C. Santana, Izabela C de Oliveira, Ricardo Gava, Fábio H. R. Baio, Carlos A da Silva Junior, Larissa P. R. Teodoro, Paulo E. Teodoro, Job T de Oliveira

“…Three accuracy metrics were utilized to evaluate the algorithms in the classification of irrigation management: correct classifications (CC), Kappa coefficient and F-Score. …”
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Coronary CT angiography: First comparison of model-based and hybrid iterative reconstruction with the reference standard invasive catheter angiography for CAD-RADS reporting by Aiste Matuleviciute-Stojanoska, Julia Sautier, Verena Bauer, Martin Nuessel, Volha Nizhnikava, Christian Stumpf, Thorsten Klink

“…Background: The purpose of this study was to compare CCTA images generated using HIR and IMR algorithm with the reference standard ICA, and to determine to what extend further improvements of IMR over HIR can be expected. …”
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TraitBertGCN: Personality Trait Prediction Using BertGCN with Data Fusion Technique by Muhammad Waqas, Fengli Zhang, Asif Ali Laghari, Ahmad Almadhor, Filip Petrinec, Asif Iqbal, Mian Muhammad Yasir Khalil

“…This study fuses the two datasets (essays and myPersonality) to overcome the bias and generalize the model across different domains. We fine-tuned our TraitBertGCN model on the fused dataset and then evaluated it on both datasets individually to assess its adaptability and accuracy in varied contexts. …”
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Integrated approach to land degradation risk assessment in arid and semi-arid Ecosystems: Applying SVM and eDPSIR/ANP methods by Ehsan Moradi, Hassan Khosravi, Pouyan Dehghan Rahimabadi, Bahram Choubin, Zlatica Muchová

“…To predict LD hazard, the Support Vector Machine (SVM) algorithm was used with 179 LD locations and twelve variables, including land use, lithology, rainfall, temperature, distance to the stream, elevation, aspect, slope, curvature, distance to the road, Normalized Difference Moisture Index (NDMI), and population density. …”
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FLAML version 2.3.3 model-based assessment of gross primary productivity at forest, grassland, and cropland ecosystem sites by J. Lai, J. Lai, Y. Zhang, A. Wang, W. Fei, Y. Diao, R. Li, J. Wu

“…However, the variables and algorithms related to environmental limiting factors differ significantly across various LUE models, leading to high uncertainty in GPP estimation. …”
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A systematic review of UAV and AI integration for targeted disease detection, weed management, and pest control in precision agriculture by Iftekhar Anam, Naiem Arafat, Md Sadman Hafiz, Jamin Rahman Jim, Md Mohsin Kabir, M.F. Mridha

“…The focus of this study is on the incorporation of machine learning and deep learning algorithms into these UAV systems. We have conducted a thorough analysis of recent studies, particularly 2022–24, to evaluate the effectiveness of different unmanned aerial vehicle models, sensor types, and computational methods to improve crop monitoring and disease control strategies. …”
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Continuous Real-Time Acoustic Monitoring of endangered bird species in Hawai‘i by Melissa Weidlich-Rau, Amanda K. Navine, Patrick T. Chaopricha, Felix Günther, Stefan Kahl, Thomas Wilhelm-Stein, Raymond C. Mack, Hendrik Reers, Aaron N. Rice, Maximilian Eibl, Patrick J. Hart, Patrick Wolff, Holger Klinck, Lena D. Schnell, Rogelio Doratt, Michael Loquet, Tiana Lackey

“…The system is based on the BirdNET algorithm and was evaluated with over 16,000 soundscape recordings from Hawai‘i. …”
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Marine soundscape forecasting: A deep learning-based approach by Shashidhar Siddagangaiah

“…Despite the rapid development of anomaly detection algorithms and deep-learning models for forecasting, their application to marine soundscapes remains unexplored. …”
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SPCB-Net: A Multi-Scale Skin Cancer Image Identification Network Using Self-Interactive Attention Pyramid and Cross-Layer Bilinear-Trilinear Pooling by Xin Qian, Tengfei Weng, Qi Han, Chen Wu, Hongxiang Xu, Mingyang Hou, Zicheng Qiu, Baoping Zhou, Xianqiang Gao

“…Deep convolutional neural networks have made some progress in skin lesion classification and cancer diagnosis, but there are still some problems to be solved, such as the challenge of small inter-class feature differences and large intra-class feature differences, which might limit the classification performance of the model as high-level and low-level features are not properly utilized. …”
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Handheld NIR Spectroscopy Combined with a Hybrid LDA-SVM Model for Fast Classification of Retail Milk by Francesco Maria Tangorra, Annalaura Lopez, Elena Ighina, Federica Bellagamba, Vittorio Maria Moretti

“…Among them, near-infrared (NIR) spectroscopy is valued for its non-destructive and rapid analysis capabilities. This study evaluates the effectiveness of a miniaturized NIR device combined with support vector machine (SVM) algorithms and LDA feature selection to discriminate between four commercial milk types: high-quality fresh milk, milk labeled as mountain product, extended shelf-life milk, and TSG hay milk. …”
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