Vibration Signal-Based Fault Diagnosis of Rotary Machinery Through Convolutional Neural Network and Transfer Learning Method by Chirag Mongia, Shankar Sehgal

“…To address this limitation, a transfer learning (TL)-based methodology has been developed for bearing fault detection, so that the model trained under some specific training conditions can perform accurately under significantly different real-time working conditions, thereby significantly improving diagnostic efficiency while reducing training time. …”
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Maize Kernel Broken Rate Prediction Using Machine Vision and Machine Learning Algorithms by Chenlong Fan, Wenjing Wang, Tao Cui, Ying Liu, Mengmeng Qiao

“…The broken rate prediction model based on machine vision and machine learning algorithms is proposed in this manuscript. …”
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A White Dwarf Catalog from LAMOST DR11 Using Deep Learning by Shengwen Zhang, Yanxia Zhang, Chao Liu

“…Our two-class classification model with multimodal data achieved an accuracy rate of 98.69% on the test set. …”
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Multi-Stage Neural Network-Based Ensemble Learning Approach for Wheat Leaf Disease Classification by Samia Nawaz Yousafzai, Inzamam Mashood Nasir, Sara Tehsin, Dania Saleem Malik, Ismail Keshta, Norma Latif Fitriyani, Yeonghyeon Gu, Muhammad Syafrudin

“…The various stages in the EL approach employ a multi-level framework to enhance feature extraction and capture complex data patterns. This improves the model’s emphasis on diseases while reducing the influence of complex backgrounds on disease identification. …”
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Particle swarm optimization with YOLOv8 for improved detection performance of tomato plants by Sarah M. Ayyad, Nada M. Sallam, Samah A. Gamel, Zainab H. Ali

“…Abstract Identification and precise classification of plants are crucial in improving plant quality and economic viability, particularly in an industrial setting. …”
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GGLA-NeXtE2NET: A Dual-Branch Ensemble Network With Gated Global-Local Attention for Enhanced Brain Tumor Recognition by Adnan Saeed, Khurram Shehzad, Shahzad Sarwar Bhatti, Saim Ahmed, Ahmad Taher Azar

“…To address these issues, we propose a Dual-Branch Ensemble and Gated Global-Local Attention network based on EfficientNetV2S and ConvNeXt (GGLA-NeXtE2NET) to improve identification accuracy and model interpretability. …”
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Aging-Invariant Sheep Face Recognition Through Feature Decoupling by Suhui Liu, Chuanzhong Xuan, Zhaohui Tang, Guangpu Wang, Xinyu Gao, Zhipan Wang

“…With the development of deep learning technology, sheep face recognition provides an efficient and contactless solution for individual sheep identification. …”
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Optimized Negative Selection Algorithm for Image Classification in Multimodal Biometric System by Monsurat Omolara Balogun, Latifat Adeola Odeniyi, Elijah Olusola Omidiora, Stephen Olatunde Olabiyisi, Adeleye Samuel Falohun

“…However, most of the existing classifiers are limited in accuracy due to false representation of image features, improper training of classifier models for newly emerging data (over-fitting or under-fitting problem) and lack of an efficient mode of generating model parameters (scalability problem). …”
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Deep-learning-based detection of large vessel occlusion: A comparison of CT and diffusion-weighted imaging by JaeYoung Kang, JunYoung Park, YoungJae Kim, BumJoon Kim, SangHee Ha, KwangGi Kim

“…Methods Computed tomography combined with clinical information and DWI data from patients diagnosed with acute ischemic stroke were collected. Three deep-learning models, convolutional neural network, EfficientNet-B2, and DenseNet121, were used to compare CT&CI and DWI for detecting anterior circulation LVO. …”
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A Comprehensive Analysis of Dropout Assisted Regularized Deep Learning Architectures for Dynamic Electricity Price Forecasting by Pooja Joshi, Stale Stordal, Gudbrand Lien, Deepti Mishra, Erik Haugom

“…As the world moves towards a sustainable future, there is a need for efficient integration of intermittent energy sources (IES) sources with intelligent energy grids. …”
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A Review of the Potential of Drone-Based Approaches for Integrated Building Envelope Assessment by Shayan Mirzabeigi, Ryan Razkenari, Paul Crovella

“…By evaluating various scanning techniques and their integration with drones, this research explores how drones can enhance data collection for defect identification, as well as digital model creation. A proposed drone-based workflow is tested through a case study in Syracuse, New York, demonstrating its feasibility and effectiveness in creating 3D models and conducting energy simulations. …”
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Application of permanent magnet synchronous direct-drive traction system on Xuzhou metro line 1 by ZENG Yun, CHEN Qihui, ZENG Xiaofan, LI Ke

“…The on-vehicle test showed that the direct-drive permanent magnet traction system has such advantages as stable motor position identification and fast response, and the traction force is stable and efficient with low adhesion on rail surface. …”
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Upscaling solid oxide electrolysis cell CFD simulations for hydrogen production by Finn Stoltze, Omkar Champhekar, Alfredo Iranzo

“…In addition, the comparison of numerical relaxation methods shows that the pseudo-transient relaxation scheme drastically improves the convergence in CFD SOEC simulations, thus enabling a higher computing performance and therefore lower SOEC development times.Highlights Successful formulation of convergence enhancing CFD solver settingIdentification of efficient meshing strategies at thermoneutral stateDirect application to small scale and industrial scale SOEC…”
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Three-dimensional visualization and navigation for micro-noninvasive uterine fibroid surgery based on MRI and ultrasound image fusion by Ting Wang, Yingang Wen, Zhibiao Wang, Zhibiao Wang, Xi Li

“…The YOLACT model achieved an accuracy greater than 95% in identifying key structures in real-time US images. …”
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Building resilience against physical risk: the role of logistics performance in risk mitigation by Abroon Qazi

“…The novelty of this research lies in its integration of logistics performance as a moderating factor within a probabilistic resilience model, which allows for the identification of how logistics alters the influence of different risk variables on national resilience—an approach not previously undertaken in resilience literature. …”
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Multispectral Integrated System with Discrete Light Sources for Material Classification by Anju Manakkakudy Kumaran, Federica Mitri, Emanuele Maiorana, Andrea De Iacovo, Lorenzo Colace

“…This system incorporates a DAQ card using the LabView program for data acquisition and system control. The proposed model achieved an identification accuracy of up to 98% using different input features and training batches. …”
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NLP-Based Approach for Identifying Quality Risk Factors in Steel Structure Construction by Yuhong Zhao, Jingyi Zhang, Enyi Mu

“…This advancement is crucial for the development of the steel structure building industry, aiding in more efficient and accurate identification and management of potential quality risks.…”
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Analyzing Problems of Decision-Making in Project Management by I. V. Balashova

“…The efficient and wide use of software has become one of key factors of development and success of companies in conditions of fierce competition.…”
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Leadership competences for the excellence of municipalities’ strategic management by Andrius Valickas, Agota Giedre Raišiene, Malvina Arimavičiūtė

“…Benchmarking, generalisation and synthesis are used as the research methods here. The model of leadership competences suggested by the authors can be used by Lithuanian municipalities seeking to establish more transparent selection of candidates for municipal posts, more objective evaluation of their activities, accurate identification of personnel professional development needs. …”
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Artificial intelligence in drug development: reshaping the therapeutic landscape by Sarfaraz K. Niazi, Zamara Mariam

“…Although, to date, no AI-generated medicinal drug has been FDA-approved, HLX-0201 for fragile X syndrome and new molecules for idiopathic pulmonary fibrosis have entered clinical trials. However, AI models are generally considered “black boxes,” making their conclusions challenging to understand and limiting the potential due to a lack of model transparency and algorithmic bias. …”
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