Φ-OTDR disturbance localization of communication optical cable based on moving variance average and spectral subtraction by Wei SHEN, Xin HU, Ze ZHANG, Ling JU, Jian WU, Yi HUANG

“…The results demonstrate that spectral subtraction significantly outperforms the other two algorithms in localization effectiveness, achieving an SNR improvement exceeding 20 dB while maintaining a computational time as low as 0.58 s.…”
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Architecture and Field Operation of a Portable Digital Holographic Microscope for In Situ Measurements of Bacterial Motility by J. Kent Wallace, Manuel Bedrossian, Stephanie Rider, Dylan McKeithen, Felipe Fregoso, Frank Loya, Scott M. Perl

“…This technology, identical to the proposed design for spaceflight instruments, will aid in the search for life on icy moons by improving our understanding of bacterial behavior in extreme conditions. …”
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The use of phase voltage modules to select the damaged phase in case of single-phase earth faults by V. A. Shabanov, A. V. Sorokin

“…Describe algorithms in which the voter will act selectively both with metal damages and with damages through fault resistance.…”
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The Electricity Load Prediction Model for Residential Buildings: A Critical Review of Output Types, Prediction Methods and Driving Factors by Zhenjing Wu, Min Qi, Weiling Zhang, Xudong Zhang, Qiang Yang, Wenyuan Zhao, Bin Yang, Zhihan Lyu, Faming Wang, Zhichao Wang

“…By summarizing the driving factors, the influence of improving the prediction accuracy according to the characteristics of output types on selecting the driving factors correctly was discussed. …”
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A Coaxial Triboelectric Fiber Sensor for Human Motion Recognition and Rehabilitation via Machine Learning by Qicheng Ding, Aamir Rasheed, Haonan Zhang, Sara Ajmal, Ghulam Dastgeer, Kamoladdin Saidov, Olim Ruzimuradov, Shavkat Mamatkulov, Wen He, Peihong Wang

“…The incorporation of 1T phase MoS₂ into the PVDF-HFP matrix significantly improves the sensor’s output owing to its electron capture capabilities. …”
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Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma by Kevin Atsou, Anne Auperin, Jôel Guigay, Sébastien Salas, Sebastien Benzekry

“…This model demonstrated unbiased OS4 prediction, suggesting its potential for improving HNSCC treatment evaluation. Trial Registration: ClinicalTrials.gov identifier: NCT02268695.…”
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Behavior Analysis With Integrated Visual-Motor Tracking for Developmental Coordination Disorder by Ruimin Li, Hong Fu, Yang Zheng, Shuiping Gou, Jane Jie Yu, Xiaowei Kong, Hongmin Wang

“…In addition to increasing the amount of time spent on concentrating, we should focus on improving children’s attention levels.…”
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Water desalination using waste heat recovery of thermal power plant in tropical climate; optimization by AI by Ehsanolah Assareh, Mohammad Firoozzadeh, Mohammad Zoghi, Ali Zare, Yasaman Ghazi, Ali Shahin-Banna

“…From exergy point of view, the exergy efficiency of the system has been enhanced from 31.1 % for the conventional state to 41.7 % as the best optimized case (10.6 % improvement). In the suggested system, outlet gas exergy, with an amount of 136.9 MW, is recovered. …”
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Design of experiments for the stochastic unit commitment with economic dispatch models by Nahal Sakhavand, Jay Rosenberger, Victoria C.P. Chen, Harsha Gangammanavar

“…The results obtained from this approach attest to the significant improvement in the computational performance of the DACE approach over the traditional L-shaped method.…”
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FedDBO: A Novel Federated Learning Approach for Communication Cost and Data Heterogeneity Using Dung Beetle Optimizer by Dongyan Wang, Limin Chen, Xiaotong Lu, Yidi Wang, Yue Shen, Jingjing Xu

“…Finally, experiments indicate that when simulating various data heterogeneous environments on datasets, FedDBO exhibits higher accuracy and better stability compared to three other algorithms: FedAvg, FedShare, and FedPSO.…”
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Deep learning-based crop health enhancement through early disease prediction by Venkata Santhosh Yakkala, Krishna Vamsi Nusimala, Badisa Gayathri, Sriya Kanamarlapudi, S. S. Aravinth, Ayodeji Olalekan Salau, S. Srithar

“…This approach holds the promise of vastly improving the accuracy and efficiency of disease forecasting within the agricultural domain.…”
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Long-Term Simulation of Daily Streamflow Using Radar Rainfall and the SWAT Model: A Case Study of the Gamcheon Basin of the Nakdong River, Korea by Huiseong Noh, Jongso Lee, Narae Kang, Dongryul Lee, Hung Soo Kim, Soojun Kim

“…In recent years, with the increasing need for improving the accuracy of hydrometeorological data, interests in rain-radar are also increasing. …”
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A Machine Learning Implementation to Predictive Maintenance and Monitoring of Industrial Compressors by Ahmad Aminzadeh, Sasan Sattarpanah Karganroudi, Soheil Majidi, Colin Dabompre, Khalil Azaiez, Christopher Mitride, Eric Sénéchal

“…Integrating machine learning algorithms leveraged by advanced data acquisition systems is emerging as a pivotal approach in predictive maintenance. …”
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The potential of machine learning in classifying relapse and non-relapse in children with clubfoot based on movement patterns by Lianne Grin, Sieglinde Bogaert, Saskia Wijnands, Arnold Besselaar, Marieke van der Steen, Jesse Davis, Benedicte Vanwanseele

“…The findings demonstrated the potential of subject classification based on kinematic movement patterns, where combining dynamic activities improves sensitivity in distinguishing children with relapsed clubfoot from children with non-relapsed clubfoot. …”
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Immunological biomarkers and gene signatures predictive of radiotherapy resistance in non-small cell lung cancer by Jie Lv, Chun-yang Yu, Yao-zu Xiong, Ting-ting Dai, Xiao-chu Hu, Peng Pan, Shun Yue, Chang-hua Yu

“…Using advanced machine learning techniques like SVM-RFE, LASSO regression, and random forest algorithms, four pivotal genes—TGFBI, FAS, PTK6, and FA2H—were identified. …”
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Artificial intelligence-based assessment of surgical skills in laparoscopic right hemicolectomy for colon cancer by WEI Pengyu, GAO Jiale, JI Maotong, TAN Yuanyuan, YAO Hongwei

“…This advancement holds significant clinical value and societal importance by improving long-term patient outcomes and fostering more equitable distribution of medical resources.…”
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MTGNet: Multi-Agent End-to-End Motion Trajectory Prediction with Multimodal Panoramic Dynamic Graph by Yinfei Dai, Yuantong Zhang, Xiuzhen Zhou, Qi Wang, Xiao Song, Shaoqiang Wang

“…This approach not only captures global relationships but also enhances the focus on local features within the scene, thereby improving the model’s sensitivity to local information. …”
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Artificial Intelligence in Chest Radiography—A Comparative Review of Human and Veterinary Medicine by Andrea Rubini, Roberto Di Via, Vito Paolo Pastore, Francesca Del Signore, Martina Rosto, Andrea De Bonis, Francesca Odone, Massimo Vignoli

“…In human medicine, AI has been extensively studied, improving the identification of thoracic abnormalities, diagnostic precision in emergencies, and the classification of complex conditions such as tuberculosis, pneumonia, and COVID-19. …”
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Application of Hybrid Attention Mechanisms in Lithological Classification with Multisource Data: A Case Study from the Altay Orogenic Belt by Dong Li, Jinlin Wang, Kefa Zhou, Jiantao Bi, Qing Zhang, Wei Wang, Guangjun Qu, Chao Li, Heshun Qiu, Tao Liao, Chong Zhao, Yingpeng Lu

“…However, traditional deep learning algorithms fail to distinguish the importance of different features effectively during fusion, leading to insufficient focus in the model. …”
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Explainability Feature Bands Adaptive Selection for Hyperspectral Image Classification by Jirui Liu, Jinhui Lan, Yiliang Zeng, Wei Luo, Zhixuan Zhuang, Jinlin Zou

“…Aiming at the problems of poor interpretability of feature classification algorithms for hyperspectral images, multiple feature dimensions, and difficulty in effectively improving classification accuracy, this paper proposes a feature band adaptive selection method for hyperspectral images. …”
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