Intrusion Detection Framework for Internet of Things with Rule Induction for Model Explanation by Kayode S. Adewole, Andreas Jacobsson, Paul Davidsson

“…This study introduces an IDS framework that integrates ensemble learning with rule induction for enhanced model explainability. …”
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Knowledge-based inductive bias and domain adaptation for cell type annotation by Zhenchao Tang, Guanxing Chen, Shouzhi Chen, Haohuai He, Linlin You, Calvin Yu-Chian Chen

“…In this study, we propose KIDA, Knowledge-based Inductive bias and Domain Adaptation. The knowledge-based inductive bias constrains the prediction rules learned from the reference dataset, composed of multiple batches, to functional patterns relevant to biology, thereby enhancing the generalization of the model to unseen batches. …”
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Symbolic Machine Learning: A Different Answer to the Problem of the Acquisition of Lexical Knowledge from Corpora by Pascale Sébillot

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Measuring the Operating Condition of Induction Motor Using High-Sensitivity Magnetic Sensor by Akane Kobayashi, Kenji Nakamura, Takahito Ono

“…This study aimed to monitor the operating state of an induction motor, a type of electromagnetic motor, using a highly sensitive magnetic sensor, which could be applied for anomaly detection in the future. …”
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Fault Diagnosis of Induction Motors Using Recurrence Quantification Analysis and LSTM with Weighted BN by Dengyu Xiao, Yixiang Huang, Chengjin Qin, Haotian Shi, Yanming Li

“…To cover those shortcomings, in this paper, two manual feature learning approaches are embedded into a deep learning algorithm, and thus, a novel fault diagnosis framework is proposed for three-phase induction motors with a hybrid feature learning method, which combines empirical statistical parameters, recurrence quantification analysis (RQA) and long short-term memory (LSTM) neural network. …”
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Attention induction based on pathologist annotations for improving whole slide pathology image classifier by Ryoichi Koga, Tatsuya Yokota, Koji Arihiro, Hidekata Hontani

“…We propose a method of attention induction to improve an attention mechanism in a whole slide image (WSI) classifier. …”
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Preventing Spurious Interactions: A New Inductive Bias for Accurate Treatment Effect Estimation by Roger Pros, Jordi Vitria

“…In recent years, the use of non-linear machine learning techniques to estimate treatment effects from observational data has gained significant attention. …”
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Explainable extreme gradient boosting as a machine learning tool for discrimination of the geographical origin of chili peppers using laser ablation-inductively coupled plasma mass spectrometry, X-ray fluorescence, and near-infrared spectroscopy by Seongsoo Jeong, Yong-kyoung Kim, Suel Hye Hur, Hyojoo Bang, HoJin Kim, Hoeil Chung

“…The spectroscopic discrimination of chili pepper samples according to geographical origin was executed using analytical techniques coupled with machine learning. First, laser ablation-inductively coupled plasma mass spectrometry (LA-ICP-MS), X-ray fluorescence (XRF), and near-infrared (NIR) spectroscopy were chosen for simple and rapid sample measurements. …”
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Results of an evaluation study of induction and mentoring for beginning special education teachers: what do they need? by Ann M. Sebald, Harvey A. Rude

“… This study reviews the results from a three-year evaluation study of one local school district’s induction and mentoring program for beginning special education teachers in the United States.  …”
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Mitigating Multicollinearity in Induction Motors Fault Diagnosis Through Hierarchical Clustering-Based Feature Selection by Bassam A. Hemade, Sabbah Ataya, Attia A. El-Fergany, Nader M. A. Ibrahim

“…This paper addresses the challenge of multicollinearity among input features in induction motor (IM) fault diagnosis, which often degrades the performance and reliability of machine learning classifiers. …”
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Few-shot Remote Sensing Imagery Recognition with Compositionality Inductive Bias in Hierarchical Representation Space by Shichao Zhou, Zhuowei Wang, Zekai Zhang, Wenzheng Wang, Yingrui Zhao, Yunpu Zhang

“…In this case, the prior knowledge learned from these data-driven methods may exhibit dataset bias, resulting in inadequate generalization to the current recognition task. …”
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Symbolic Regression Method for Estimating Distance Between Two Coils of an Inductive Wireless Power Transfer System by Davide Milillo, Lorenzo Sabino, Rafiq Asghar, Francesco Riganti Fulginei

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A large-scale examination of inductive biases shaping high-level visual representation in brains and machines by Colin Conwell, Jacob S. Prince, Kendrick N. Kay, George A. Alvarez, Talia Konkle

“…Abstract The rapid release of high-performing computer vision models offers new potential to study the impact of different inductive biases on the emergent brain alignment of learned representations. …”
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Comprehensive Fault Diagnosis of Three-Phase Induction Motors Using Synchronized Multi-Sensor Data Collection by Kevin Thomas, Ahasanur Rahman, Wesam Rohouma, Md. Faysal Ahamed, Fariya Bintay Shafi, Md. Nahiduzzaman, Amith Khandakar

“…Abstract Induction motors are critical to industrial operations but are prone to mechanical and electrical faults. …”
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Double Sigmoid Activation Function for Fault Detection in Wind Turbine Generator using Artificial Neural Network by NOOR FAZLIANA FADZAIL, Samila Mat Zali, Ernie Che Mid

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I-MPN: inductive message passing network for efficient human-in-the-loop annotation of mobile eye tracking data by Hoang H. Le, Duy M. H. Nguyen, Omair Shahzad Bhatti, László Kopácsi, Thinh P. Ngo, Binh T. Nguyen, Michael Barz, Daniel Sonntag

“…In this work, we present a novel human-centered learning algorithm designed for automated object recognition within mobile eye-tracking settings. …”
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“This seems important”: A thematic analysis of reflections on a compulsory induction program for new Malaysian university teachers by Daron Benjamin Loo, Farous Izwan Abdul Aziz, Nadiah Rus Liyana Rusli, Yong Zi Hong

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Fault Diagnosis System of Induction Motors Based on Neural Network and Genetic Algorithm Using Stator Current Signals by Tian Han, Bo-Suk Yang, Won-Ho Choi, Jae-Sik Kim

“…The combination of advanced techniques reduces the learning time and increases the diagnosis accuracy. …”
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Real-time bearing fault classification of induction motor using enhanced inception ResNet-V2 by Karan Kumar K, Srihari Mandava

“…However, it is challenging to use Deep Learning techniques to identify bearing defects when the machine is not under load. …”
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Study on Electric Power Fittings Identification Method for Snake Inspection Robot Based on Non-Contact Inductive Coils by Zhiyong Yang, Jianguo Liu, Shengze Yang, Changjin Zhang

“…This method, unaffected by light intensity changes, uses machine learning to classify the magnetic induction electromotive force signals around the fittings. …”
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