Aero Engine Component Fault Diagnosis Using Multi-Hidden-Layer Extreme Learning Machine with Optimized Structure by Shan Pang, Xinyi Yang, Xiaofeng Zhang

“…The proposed method is applied to handwritten recognition data set and a gas turbine engine diagnostic application and is compared with basic ELM, multi-hidden-layer ELM, and two state-of-the-art deep learning algorithms: deep belief network and the stacked denoising autoencoder. …”
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The Discriminants of Long and Short Duration Failures in Fulfillment Sortation Equipment: A Machine Learning Approach by Abed Mutemi, Fernando Bacao

“…Under a variety of hyperparameter configurations, we test and compare the outcomes of eight different machine learning classification algorithms, seven individual classifiers, and a stacked ensemble. …”
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Isolated fiber-optic transmission of IGBT UCE signals for precise HV switching analysis by Sylwester Bułka

“…This work presents the design and implementation of an isolated fiber-optic transmission system for real-time monitoring of collector-emitter voltage (UCE) in IGBT-based highvoltage (HV) stacks, with a focus on applications in industrial and accelerator environments. …”
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Collaborative altitude-adaptive reinforcement learning for active search with unmanned aerial vehicle swarms by XIAO Zijian, Chen-Chun Hsia, XU Yanggang, REN Jiyuan, CHEN Xinlei

“…The optimal strategy has to strike a balance between exploring larger areas at higher altitudes and exploiting regions of high target probability at lower altitudes. …”
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Quantum Computing and the Law: Navigating the Legal Implications of a Quantum Leap by Kasim Balarabe

“…The unique characteristics of quantum algorithms and hardware pose significant challenges for the existing patent system, necessitating a clear and consistent framework for protecting quantum innovations while fostering collaboration. …”
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Fault Diagnosis of Heavy-Loaded AGV Based on Digital Mirror by Yiwen Zhang, Yan Gao, Xinming Zhang, Linsen Song, Baoyan Zhao, Jingru Liu, Longkai Liang, Jing Jiao

“…Finally, the validity of the method was verified by comparing a factory-heavy load AGV with various other algorithms, resulting in an accuracy rate of 97.0% for fault diagnosis.…”
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ecochange: An R‐package to derive ecosystem change indicators from freely available earth observation products by Wilson Lara, Maria C. Londoño, Ivan Gonzalez, Victor H. Gutierrez‐Velez

“…Abstract Spatial resources accessible for the derivation of biodiversity indicators of the class ecosystem structure are sparse and disparate, and their integration into computer algorithms for biodiversity monitoring remains problematic. …”
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Work Place Safety: Machine Learning Techniques for Assessing Workplace Incident Severity by Munayr Hasan Khalleefah Hassan, Wagdi M. S. Khalifa

“…Analyzing a comprehensive dataset of occupational injury records from Occupational Safety and Health Administration (OSHA), this research explores the efficacy of seven distinct ML algorithms AdaBoostClassifier (ABC), K-Nearest Neighbors (KNN), Decision Tree Classifier (DTC), Extreme Learning Machine (ELM), Support Vector Classifier (SVC), Multi-Layer Perceptron (MLP), and Stacked Model (SM). …”
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Anomaly Detection of Wind Turbines Based on Deep Small-World Neural Network by Yaguang LI, Meng LI

“…Finally, two failure cases of wind turbine anomaly detection were given to demonstrate the validity and accuracy of the proposed DSWNN contrasted with the DBN and DNN algorithms.…”
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Diabetes diagnosis using a hybrid CNN LSTM MLP ensemble by Yanmin Fan

“…Convolutional neural network (CNN) is the first neural network utilized for extracting the spatial characteristics of the data, while Long Short-Term Memory (LSTM) networks—more specifically, an LSTM Stack—are used to comprehend the time-dependent flow of the data based on medical information from patients. …”
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H-DSAE: a hybrid technique to recognize heart disease by K. Uma Maheswari, A. Valarmathi

“…The next phase of the project will focus on developing more advanced classification and features algorithms. This will help improve the efficiency of the system.…”
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Demystifying multiple sclerosis diagnosis using interpretable and understandable artificial intelligence by Chadaga Krishnaraj, Khanna Varada Vivek, Prabhu Srikanth, Sampathila Niranjana, Chadaga Rajagopala, Palkar Anisha

“…Multiple sclerosis (MS) is a dangerous illness that strikes the central nervous system. The body’s immune system attacks myelin (an entity above the nerves) and impairs brain-to-body communication. …”
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Elevating Patient Care With Deep Learning: High-Resolution Cervical Auscultation Signals for Swallowing Kinematic Analysis in Nasogastric Tube Patients by Farnaz Khodami, Amanda S. Mahoney, James L. Coyle, Ervin Sejdic

“…By applying established algorithms to an unseen population, we demonstrated the utility of HRCA signals for swallowing assessment in individuals with NG tubes and showcased the generalizability of algorithms developed in our previous studies. …”
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The Adversarial Robust and Generalizable Stereo Matching for Infrared Binocular Based on Deep Learning by Bowen Liu, Jiawei Ji, Cancan Tao, Jujiu Li, Yingxun Wang

“…Despite the considerable success of deep learning methods in stereo matching for binocular images, the generalizability and robustness of these algorithms, particularly under challenging conditions such as occlusions or degraded infrared textures, remain uncertain. …”
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An Elliptic Kernel Unsupervised Autoencoder—Graph Convolutional Network Ensemble Model for Hyperspectral Unmixing by Estefania Alfaro-Mejia, Carlos J. Delgado, Vidya Manian

“…A graph convolutional network (GCN) processes stacked input-abundance maps, senders, and receivers to refine the abundance estimations. …”
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Framework for the Multi-Objective Optimization of Hybrid Fuel Cell System Design and Operation by Luis M. Winkler, Alexander Kabza, Michael A. Danzer, Herbert Palm

“…For this purpose, an open-source object-oriented FCS model was extended to include cell degradation effects at stack level and power train components at system level. …”
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Exploring subthreshold processing for next-generation TinyAI by Farid Nakhle, Antoine H. Harfouche, Antoine H. Harfouche, Hani Karam, Vasileios Tserolas

“…We propose pathways such as algorithmic analogs of subthreshold integration, including graded activation functions, dendritic-inspired hierarchical processing, and hybrid analog-digital systems to emulate the energy-efficient operations of biological neurons. …”
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Food Public Opinion Prevention and Control Model Based on Sentiment Analysis by Leiyang Chen, Xiangzhen Peng, Liang Dong, Zhenyu Wang, Zhidong Shen, Xiaohui Cui

“…This paper introduces the Food Public Opinion Prevention and Control (FPOPC) model driven by deep learning and personalized recommendation algorithms, rigorously tested and analyzed through experimentation. …”
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A hybrid mutational Northern Goshawk and elite opposition learning artificial rabbits optimizer for PEMFC parameter estimation by Pradeep Jangir, Absalom E. Ezugwu, Kashif Saleem, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Laith Abualigah

“…Other optimization algorithms including ARO, TLBO, DE and SSA are used for comparative analysis purposes. …”
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Low-Power-Management Engine: Driving DDR Towards Ultra-Efficient Operations by Zhuorui Liu, Yan Li, Xiaoyang Zeng

“…Central to our proposed DDR power-management framework is the Low-Power-Management Engine (LPME), complemented by a suite of statistical algorithms tailored for implementation within the architecture. …”
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