An integrated strain-level analytic pipeline utilizing longitudinal metagenomic data by Boyan Zhou, Chan Wang, Gregory Putzel, Jiyuan Hu, Menghan Liu, Fen Wu, Yu Chen, Alejandro Pironti, Huilin Li

“…It concurrently leverages the information on proportions of mapped reads for individual strains and genome-wide SNVs to enhance the efficiency and accuracy of strain identification. Our method helps to understand strains’ dynamic changes and their association with genome-wide variants. …”
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Hybrid HDBSCAN-FHMM Approach for Energy Disaggregation in Non-Intrusive Load Monitoring (NILM) Systems by Leonce W. Tokam, Sena K. Apeke, Sanoussi S. Ouro-Djobo

“…Our methodology consisted of two main phases: an appliance operating state identification phase using the HDBSCAN algorithm, followed by an energy disaggregation phase based on a modified FHMM (Factorial Hidden Markov Model). …”
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Tomato yellow leaf curl virus detection based on cross-domain shared attention and enhanced BiFPN by Henghui Mo, Linjing Wei

“…Moreover, the introduction of Inner-CIOU with a scale factor-controlled auxiliary bounding box optimizes the precision and regression efficiency in detecting small target features. Experimental results demonstrate that the model achieves an average accuracy of 88.25%, a recall rate of 86.59%, and a Mean Average Precision (mAP) of 85.34%, significantly outperforming the original YOLOv8n and mainstream detection models such as YOLOv5s, SSD, and Faster-RCNN. …”
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Ambient Vibration Testing for Story Stiffness Estimation of a Heritage Timber Building by Kyung-Won Min, Junhee Kim, Sung-Ah Park, Chan-Soo Park

“…The proposed methodology of story stiffness is estimation based on an eigenvalue problem derived from a vibratory rigid body model. Using the identified natural frequencies, the eigenvalue problem is efficiently solved and uniquely yields story stiffness. …”
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Laboratory access recognition based on MAML and radio frequency fingerprint by Qun Zhu, Qingxin Lin

“…Abstract Addressing the efficiency and accuracy issues of radio frequency fingerprint recognition in laboratory access control, this paper presents a recognition model based on model-agnostic meta-learning and radio frequency fingerprint. …”
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Improved lightweight DeepLabV3+ for bare rock extraction from high-resolution UAV imagery by Pengde Lai, Chao Lv, Lv Zhou, Shengxiong Yang, Jiao Xu, Qiulin Dong, Meilin He

“…Meanwhile, the improved model had a parameter count of 6.98 M and a computational complexity of 7.24G, achieving enhanced accuracy while maintaining computational efficiency. …”
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Study on the fusion of improved YOLOv8 and depth camera for bunch tomato stem picking point recognition and localization by Guozhu Song, Jian Wang, Rongting Ma, Yan Shi, Yaqi Wang

“…To address these challenges, this paper proposes an enhanced YOLOv8 model integrated with a depth camera for string tomato fruit stalk picking point identification and localization research. …”
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Classifying early apple scab infections in multispectral imagery using convolutional neural networks by Alexander J. Bleasdale, J. Duncan Whyatt

“…The models achieved scab-prediction accuracies of 97.13 % and 97.57 % for MobileNetV2 and EfficientNetV2L, respectively, on the secondary data but only achieved accuracies of 74.12 % and 78.91 % when applied to the multispectral dataset in isolation. …”
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Development and Validation of Quantile Regression Forests for Prediction of Reference Quantiles in Handgrip and Chair‐Stand Test by Giulia Giordano, Luca Mastrantoni, Francesco Landi, The Lookup 8+ Study Group

“…These models hold promise for integration into clinical practice, facilitating cost‐effective and time‐efficient early identification of individuals at elevated risk of sarcopenia. …”
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Approaches to discern if microbiome associations reflect causation in metabolic and immune disorders by Marijana Basic, Dominique Dardevet, Peter Michael Abuja, Silvia Bolsega, Stéphanie Bornes, Robert Caesar, Francesco Maria Calabrese, Massimo Collino, Maria De Angelis, Philippe Gérard, Miguel Gueimonde, François Leulier, Eva Untersmayr, Evelien Van Rymenant, Paul De Vos, Isabelle Savary-Auzeloux

“…We hope this review will facilitate important considerations for appropriate animal model selection.…”
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Magnetic Resonance Imaging Brain Segmentation Using Bi-Directional Convolutional Long Short-Term Memory U-Net With Densely Connected Convolutions by Meshari D. Alanazi, Amna Maraoui, Imen Werda, Ahmed Ben Atitallah, Turki M. Alanazi, Mohammed Albekairi, Anis Sahbani, Amr Yousef

“…With 8.81 million parameters and 60.34 GFLOPs, our model also greatly lowers complexity by up to 15% and balances accuracy with efficiency. …”
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Optimized Hybrid Deep Learning Framework for Early Detection of Alzheimer’s Disease Using Adaptive Weight Selection by Karim Gasmi, Abdulrahman Alyami, Omer Hamid, Mohamed O. Altaieb, Osama Rezk Shahin, Lassaad Ben Ammar, Hassen Chouaib, Abdulaziz Shehab

“…Methods: We present an enhanced hybrid deep learning framework that amalgamates the EfficientNetV2B3 with Inception-ResNetV2 models. The models were integrated using an adaptive weight selection process informed by the Cuckoo Search optimization algorithm. …”
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Fast Prediction for Roll Motion of a Damaged Ship Based on SVR by LIU Han, SU Yan, ZHANG Guoqiang

“…Finally, a fast prediction model for rolling motion is constructed and validated, offering a significant improvement in the prediction efficiency compared with traditional computational fluid dynamics models.…”
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Detecting Anomalies in Attributed Networks Through Sparse Canonical Correlation Analysis Combined With Random Masking and Padding by Wasim Khan, Mohammad Ishrat, Ahmad Neyaz Khan, Mohammad Arif, Anwar Ahamed Shaikh, Mousa Mohammed Khubrani, Shadab Alam, Mohammed Shuaib, Rajan John

“…Our approach is the first of its kind to provide a novel remedy to the fundamental problems preventing efficient and accurate anomaly identification, thereby establishing a new standard in this field. …”
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FingerUNeSt++: Improving Fingertip Segmentation in Contactless Fingerprint Imaging Using Deep Learning by Laurenz Ruzicka, Bernhard Kohn, Clemens Heitzinger

“…Extensive data augmentation and an optimized model architecture contribute to its robustness and efficiency. …”
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Crack Detection Method of Sleeper Based on Cascade Convolutional Neural Network by Liming Li, Shubin Zheng, Chenxi Wang, Shuguang Zhao, Xiaodong Chai, Lele Peng, Qianqian Tong, Ji Wang

“…This work presents a new method for sleeper crack identification based on cascade convolutional neural network (CNN) to address the problem of low efficiency and poor accuracy in the traditional detection method of sleeper crack identification. …”
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Machine Learning Identifies the Emotion Climate During Naturalistic Conversations Using Speech Features and Affect Dynamics by Ghada Alhussein, Mohanad Alkhodari, Leontios J. Hadjileontiadis

“…Nevertheless, ERC so far has mainly focused on the identification of each interlocutor’s emotions. Here, for the first time, we consider the concept of emotion climate (EC), that is, the emotion reciprocally established by the peers during a naturalistic conversation, and we introduce machine learning (ML) models that efficiently perform emotion climate recognition (ECR). …”
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Deep Learning-Based Fault Diagnosis via Multisensor-Aware Data for Incipient Inter-Turn Short Circuits (ITSC) in Wind Turbine Generators by Qinglong Wang, Shihao Cui, Entuo Li, Jianhua Du, Na Li, Jie Sun

“…The experimental results demonstrate that deep learning models outperform machine learning algorithms in terms of precision and stability, achieving an mAP of 99.25% in fault identification, with three-phase current signals emerging as the most reliable indicator of generator faults compared to vibration and electromagnetic data. …”
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Development and Application of an Integrated Index for Occupational Safety Evaluation by Paulo Silva, Mariana Carneiro, Nélson Costa, Isabel Loureiro, Paula Carneiro, Abel Pires, Cátia Ferreira

“…Models integrating safety, ergonomics, and operational efficiency in risk management are non-existent, especially in the food retail sector. …”
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Test Platform Design of Integrated Controller for Electric Vehicle Based onUDS Protocol by XIONG Gang, WANG Wenming, XIE Yongbo, FENG Ba

“…A pure digital representation method of data identification (DID) is designed for detection model, and the collection of this model is used as the detection configuration file to achieve the universality of the detection platform. …”
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