Field Validation of the DNDC-Rice Model for Crop Yield, Nitrous Oxide Emissions and Carbon Sequestration in a Soybean System with Rye Cover Crop Management by Qiliang Huang, Nobuko Katayanagi, Masakazu Komatsuzaki, Tamon Fumoto

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Simple Imaging System for Label-Free Identification of Bacterial Pathogens in Resource-Limited Settings by Clément Douarre, Dylan David, Marco Fangazio, Emmanuel Picard, Emmanuel Hadji, Olivier Vandenberg, Barbara Barbé, Liselotte Hardy, Pierre R. Marcoux

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Cluster analysis of digital competencies among professors in higher education by Karime Chahuán-Jiménez, Eduardo Lara-Yergues, Dominique Garrido-Araya, Elena Salum-Alvarado, Paulina Hurtado-Arenas, Rolando Rubilar-Torrealba

“…Regarding the clustering analysis, specifically using the K-means clustering algorithm, four distinct clusters are identified based on the questionnaire scores, aligning with findings from Silhouette score and Quadratic error by number of clusters.DiscussionThis research reveals that professors in higher education span all four levels of competency as defined by the DigComEdu model, primarily falling within the intermediate levels of digital competencies. …”
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Personalised Affective Classification Through Enhanced EEG Signal Analysis by Joseph Barrowclough, Nonso Nnamoko, Ioannis Korkontzelos

“…This overlooks individual differences and may not accurately capture the unique emotional patterns of each person.Methods This study explored the performance of six machine learning algorithms in classifying a benchmark EEG dataset (collected with a MUSE device) for affective research. …”
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PFML: Self-Supervised Learning of Time-Series Data Without Representation Collapse by Einari Vaaras, Manu Airaksinen, Okko Rasanen

“…This issue hinders the potential application of SSL methods to new data modalities, as trying to avoid representation collapse wastes researchers’ time and effort. This paper introduces a novel SSL algorithm for time-series data called Prediction of Functionals from Masked Latents (PFML). …”
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Robust Finite-Time Trajectory Tracking Control of Quadrotor Aircraft via Terminal Sliding Mode-Based Active Antidisturbance Approach: A PIL Experiment by Omar Mechali, Jamshed Iqbal, Xiaomei Xie, Limei Xu, Abdelkader Senouci

“…Numerical simulations and processor-in-the-loop (PIL) experiments are conducted to validate and implement the designed flight control algorithm on real autopilot hardware. The novelty of the proposed research lies in hardware implementation of a sophisticated version of modern control technique that exhibits a multitude of distinguishing features including but not limited to (i) finite-time tracking stability featuring fast convergence is ensured, (ii) chattering and singularity problems in sliding mode control (SMC) are avoided, and (iii) null steady-state error is achieved along with enhanced robustness. …”
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UNCERTAINTY OF THE RESULTS OF THE RADON CONTROL IN HOUSINGS. PART 2. EXPERIMENTAL ASSESSMENT OF THE TEMPORAL VARIATIONS OF RADON by A. A. Tsapalov, S. M. Kiselev, A. M. Marennyy, K. L. Kovler, S. I. Kuvshinnikov, A. S. Yankin

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YOLO-Ssboat: Super-Small Ship Detection Network for Large-Scale Aerial and Remote Sensing Scenes by Yiliang Zeng, Xiuhong Wang, Jinlin Zou, Hongtao Wu

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SPARQ: Efficient Entanglement Distribution and Routing in Space–Air–Ground Quantum Networks by Mohamed Shaban, Muhammad Ismail, Walid Saad

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Integrating single cell analysis and machine learning methods reveals stem cell-related gene S100A10 as an important target for prediction of liver cancer diagnosis and immunothera... by Shenjun Huang, Tingting Tu

“…Notably, the XGBoost algorithm identified S100A10 as the stem cell-related gene most relevant to the prognosis of LIHC patients. …”
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Optimization Method for Combination of Residual Current Protection and Coincidence Brake Logic in a Low-Voltage Distribution System by XU Han, ZHU Sanli, ZHANG Tengfei, CHEN Shu, LIU Mingxiang

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Corrosion Rate Prediction of Buried Oil and Gas Pipelines: A New Deep Learning Method Based on RF and IBWO-Optimized BiLSTM–GRU Combined Model by Jiong Wang, Zhi Kong, Jinrong Shan, Chuanjia Du, Chengjun Wang

“…The corrosion of oil and gas pipelines represents a significant factor influencing the safety of these pipelines. The extant research on intelligent algorithms for assessing corrosion rates in pipelines has primarily focused on static evaluation methods, which are inadequate for providing a comprehensive dynamic evaluation of the complex phenomenon of corrosion in buried oil and gas pipelines. …”
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PERFORMANCE ANALYSIS OF OPTIMIZATION METHODS FOR SOLVING TRAVELING SALESMAN PROBLEM by Chandra Agung, Natalia Christine

“…The task in this study is to identify and formulate each algorithm for each method, then to run each algorithm with the same input and to get the research output: total distance, and the last to compare both methods: advantage and limitation.  …”
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Robust personalized pricing under uncertainty of purchase probabilities by Shunnosuke Ikeda, Naoki Nishimura, Noriyoshi Sukegawa, Yuichi Takano

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Low-dose computed tomography image denoising using pixel level non-local self-similarity prior with non-local means for healthcare informatics by Dawa Chyophel Lepcha, Bhawna Goyal, Ayush Dogra, Krunal Vaghela, Ashish Singh, K. S. Ravi Kumar, Durga Prasad Bavirisetti

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Conceptual Framework of Energy-and-Ecology of Indoor Plant Lighting by Sergei A. Rakut’ko

“…The author proposes an algorithm for BAT forming to be applied in indoor plant lighting. …”
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Flaxseed protein content prediction based on hyperspectral wavelength selection with fractional order ant colony optimization by Bo Wang, Junying Han, Chengzhong Liu, Jianping Zhang, Yanni Qi

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Optimizing resource allocation in industrial IoT with federated machine learning and edge computing integration by Ala'a R. Al-Shamasneh, Faten Khalid Karim, Yu Wang

“…To address these issues, a novel Lyapunov-driven optimization algorithm for device selection and bandwidth allocation is introduced. …”
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Multiagent, multitimescale aggregated regulation method for demand response considering spatial–temporal complementarity of user-side resources by Tingzhe Pan, Chao Li, Chen Yang, Zijie Meng, Zongyi Wang, Zean Zhu

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Enhancing Crowd Safety at Hajj: Real-Time Detection of Abnormal Behavior Using YOLOv9 by Amani A. Alsabei, Tahani M. Alsubait, Hosam H. Alhakami

“…Leveraging deep learning, this research accurately identifies features of abnormal behavior from the HAJJv2 dataset, specifically curated and annotated for the Hajj context. …”
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