AdaGram in Python: An AI Framework for Multi-Sense Embedding in Text and Scientific Formulas by Arun Josephraj Arokiaraj, Samah Ibrahim, André Then, Bashar Ibrahim, Stephan Peter

“…Originally implemented in Julia, AdaGram has seen limited adoption due to ecosystem fragmentation and the comparative scarcity of Julia’s machine learning tooling compared to Python’s mature frameworks. …”
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Severity analysis of property damage in highway accidents by Yucong Hu, Wenhan Shi, Hu Wei, Qiang Zeng

“…The spatial correlation among adjacent accidents was addressed using a spatial generalized ordered Probit model, which employed varying association distance thresholds. An XGBoost machine learning algorithm was developed to estimate the model parameters, and the SHAP (SHapley Additive exPlanations) method was employed to elucidate the model outputs. …”
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ACE2: accurately learning subseasonal to decadal atmospheric variability and forced responses by Oliver Watt-Meyer, Brian Henn, Jeremy McGibbon, Spencer K. Clark, Anna Kwa, W. Andre Perkins, Elynn Wu, Lucas Harris, Christopher S. Bretherton

“…Here we present ACE2 (Ai2 Climate Emulator version 2) and its application to reproducing atmospheric variability over the past 80 years on timescales from days to decades. ACE2 is a 450M-parameter autoregressive machine learning emulator, operating with 6-hour temporal resolution, 1° horizontal resolution and eight atmospheric vertical layers. …”
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Cocoa bean quality identification using a computer vision-based color and texture feature extraction by Basri Basri, Indrabayu Indrabayu, Andani Achmad, Intan Sari Areni

“…This study used 15 features with the highest correlation. Machine Learning models using Support Vector Machine (SVM) with some parameter variation value alongside an RBF kernel. …”
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Sensing-Assisted Secure Communications over Correlated Rayleigh Fading Channels by Martin Mittelbach, Rafael F. Schaefer, Matthieu Bloch, Aylin Yener, Onur Günlü

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Impact of beam asymmetries at the Future Circular Collider e^{+}e^{-} by Peter Kicsiny, Xavier Buffat, Khoi Le Nguyen Nguyen, Tatiana Pieloni, Mike Seidel

“…We present and assess the sensitivity and required precision of the nominal beam parameters in a potential real-life operation by providing first estimates of the tolerances in the initial asymmetry of several machine parameters, with respect to the 3D flip-flop mechanism, obtained from parameter scan simulations.…”
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GEAR FAULT IDENTIFICATION OF RVM BASED ON LCD BASE-SCALE ENTROPY by CHEN Qing

“…Thus the complexity metric in different scales of the original signal was gained, which was consequently taken as the feature parameter to describe different gear states. The feature parameters were then put into relevance vector machine（RVM） for diagnosing the gear faults. …”
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Acoustic filters with a perforated tube by Gerard BRZÓZKA

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GENERALIZED ALGORITHM OF COMBINE PROCESS ADJUSTMENT BASED ON FUZZY KNOWLEDGE MODELS by Valery Petrovich Dimitrov, Lyudmila Victorovna Borisova

“…The specific feature of the proposed problem-solving algorithm is the hypothesis testing of emerging combining process non-conformances under the machine parameter variations. In this case, the validity of the exception condition generation when an additional breakdown in the technological process occurs is checked. …”
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A Hybrid Fault Diagnosis Model for Rolling Bearing With Optimized VMD and Fuzzy Dispersion Entropy by Xin Xia, Xiaolu Wang, Weilin Chen

“…To improve the efficiency of feature extraction and fault diagnosis, a hybrid model based on optimized variational mode decomposition (VMD), fuzzy dispersion entropy (FDE), and a support vector machine (SVM) is proposed. Firstly, a parameter optimization method using the sparrow search algorithm (SSA) was applied to VMD to improve the decomposition ability. …”
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Detecting Signatures of Criticality Using Divergence Rate by Tenzin Chan, De Wen Soh, Christopher Hillar

“…Oftentimes in a complex system it is observed that as a control parameter is varied, there are certain intervals during which the system undergoes dramatic change. …”
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High throughput assessment of blueberry fruit internal bruising using deep learning models by Chenjiao Tan, Changying Li, Penelope Perkins-Veazie, Heeduk Oh, Rui Xu, Massimo Iorizzo

“…Furthermore, the mean bruising ratio was negatively correlated with mechanical texture parameter, Young’s modulus 20% Burst Strain. Overall, this study presents an effective and efficient approach with a user-friendly interface to evaluate blueberry internal bruising using deep learning models, which could facilitate the breeding of blueberry genotypes optimized for machine harvesting. …”
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Physical exertion does not lead to a change in the time taken to correctly recognize stereoscopic stimuli in changing horizontal disparity levels by Florian Frisch, Wolfgang Mehringer, Matthias Ring, Björn Eskofier, Georg Michelson

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Design and Experiment of Obstacle Avoidance Mower in Orchard by Yi Yang, Yichuan He, Zhihui Tang, Hong Zhang

“…On the premise of simplifying the inter-plant obstacle avoidance mechanism into a two-dimensional model for kinematics analysis, the motion parameters of the key components of the machine were determined. …”
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Analisa Sentimen Financial Technology Peer To Peer Lending Pada Aplikasi Koinworks by Rousyati Rousyati, Windu Gata, Dany Pratmanto, Nia Kusuma Wardhani

“…Algoritma SVM dengan Cross Validation + Parameter Optimization menghasilkan Accuracy 91,03% precision tertinggi yaitu dengan 96,73%% , recall 85,34% dan AUC  tertinggi yaitu 0,986 yang termasuk dalam excellent classification.   …”
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IoT‐Based Elderly Health Monitoring System Using Firebase Cloud Computing by Adhan Efendi, Muhammad Imam Ammarullah, Indra Griha Tofik Isa, Meli Puspita Sari, Jasmine Nurul Izza, Yohanes Sinung Nugroho, Hamid Nasrullah, Denny Alfian

“…In addition, a supervised machine learning technology is implemented to conduct prediction task of the observed user whether in “stable” or “not stable” condition based on real‐time parameter. …”
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Micro-spring force sensors using conductive photosensitive resin fabricated via two-photon polymerization by Ningning Hu, Yucheng Deng, Lujia Ding, Lijun Men, Wenjun Zhang, Ruixue Yin

“…Using a support vector machine model in machine learning techniques, we optimized the polymerizability of the resin under varied laser parameters, achieving a predictive accuracy of 92.66%. …”
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Edge computing based english translation model using fuzzy semantic optimal control technique. by Na Wang

“…RL and PPO aim to improve a machine translation system's translation policy depending on a predetermined reward signal or quality parameter. …”
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An Efficient and Fast Model Reduced Kernel KNN for Human Activity Recognition by Zongying Liu, Shaoxi Li, Jiangling Hao, Jingfeng Hu, Mingyang Pan

“…With accumulation of data and development of artificial intelligence, human activity recognition attracts lots of attention from researchers. Many classic machine learning algorithms, such as artificial neural network, feed forward neural network, K-nearest neighbors, and support vector machine, achieve good performance for detecting human activity. …”
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Microstructure and Mechanical Properties of Dissimilar Resistance Spot Welded Zn-Coated DP800–TBF1180 Automotive Steels Using MFDC Technology by M. Hıdıroğlu, T.A. Başer, N. Kahraman

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