Bridging the Gap in the Adoption of Trustworthy AI in Indian Healthcare: Challenges and Opportunities by Sarat Kumar Chettri, Rup Kumar Deka, Manob Jyoti Saikia

“…It finds that the existing studies mostly used conventional machine learning (ML) algorithms and artificial neural networks (ANNs) for a variety of tasks, such as drug discovery, disease surveillance systems, early disease detection and diagnostic accuracy, and management of healthcare resources in India. …”
Get full text

Spectral convolutional neural network chip for in-sensor edge computing of incoherent natural light by Kaiyu Cui, Shijie Rao, Sheng Xu, Yidong Huang, Xusheng Cai, Zhilei Huang, Yu Wang, Xue Feng, Fang Liu, Wei Zhang, Yali Li, Shengjin Wang

“…Abstract Optical neural networks are considered next-generation physical implementations of artificial neural networks, but their capabilities are limited by on-chip integration scale and requirement for coherent light sources. …”
Get full text

A Hybrid Prognostic Approach for Remaining Useful Life Prediction of Lithium-Ion Batteries by Wen-An Yang, Maohua Xiao, Wei Zhou, Yu Guo, Wenhe Liao

“…Empirical comparisons show that the proposed hybrid prognostic approach using the selective kernel ensemble-based RVM learning algorithm performs better than the hybrid prognostic approaches using the popular learning algorithms of feedforward artificial neural networks (ANNs) like the conventional backpropagation (BP) algorithm and support vector machines (SVMs). …”
Get full text

Research on 3D printing concrete mechanical properties prediction model based on machine learning by Yonghong Zhang, Suping Cui, Bohao Yang, Xinxin Wang, Tao Liu

“…Our study explores the fundamentals and practicality of several models, such as artificial neural networks, decision trees, random forests, support vector regression, and linear regression. …”
Get full text

Comparative use of different AI methods for the prediction of concrete compressive strength by Mouhamadou Amar

“…The simulations used artificial neural networks or deep learning, generalized linear, decision tree, random forest, support vector machine, and gradient-boosted tree models to predict the compressive strength of 8 concrete mix designs containing different SCMs. …”
Get full text

FORECASTING DEFERRED TAXES IN INTERNATIONAL ACCOUNTING WITH MACHINE LEARNING by Osman Bayri, Ahmet Çağdaş Seçkin, Feden Koç

“…Within the context of the study, the deferred tax output parameters, which companies will present in their annual financial reports in 2020, have been estimated using the following methods: the DTA value using the random forest method with an accuracy rate of 0,823, the net DTA value using the artificial neural networks method with an accuracy rate of 0,790, the DTL value using the random forest method with an accuracy rate of 0,823 and the net DTL value using the random forest method with an accuracy rate of 0,887. …”
Get full text

Data-Driven Approach to Evaluate the Level of Service (LOS) of Demand-Responsive Transport for the Disabled (DRTD) with an ANFIS Algorithm by Seohyeon Park, Sooyeon Park, Hosik Choi, Do-Gyeong Kim

“…The model was estimated using an Adaptive Neuro-Fuzzy Inference System (ANFIS), which is known to have an excellent predictive performance by combining the advantages of both artificial neural networks and fuzzy inference systems. Four variables, including the number of calls (or requests), the number of vacant vehicles, Medical Infrastructure Concentration Index (MICI), and Disabled Population Concentration Index (DPCI), were used as input variables for the ANFIS-based model. …”
Get full text

SPICE-Level Demonstration of Unsupervised Learning With Spintronic Synapses in Spiking Neural Networks by Salah Daddinounou, Anteneh Gebregiorgis, Said Hamdioui, Elena-Ioana Vatajelu

“…Spiking Neural Networks (SNNs) are Artificial Neural Networks which promise to mimic the biological brain processing with unsupervised online learning capability for various cognitive tasks. …”
Get full text

Towards the implementation of automated scoring in international large-scale assessments: Scalability and quality control by Ji Yoon Jung, Lillian Tyack, Matthias von Davier

“…The results showed that the supervised learning approach, particularly combining multiple machine translations with artificial neural networks (MMT_ANNs), showed comparable performance to human scoring. …”
Get full text

Transforming Cardiac Care: Machine Learning in Heart Condition Prediction Using Phonocardiograms by Sandra D’Souza, Niranjan Reddy S, Saikonda Krishna Tarun, Sohan P, aneesha acharya k

“…The developed models record a classification accuracy of 71% for logistic regression and 94% for the random forest model. Further, artificial neural networks (ANN) and Deep learning networks have been trained to improve performance and demonstrated an accuracy of 94.5%.…”
Get full text

An intrusion detection model based on Convolutional Kolmogorov-Arnold Networks by Zhen Wang, Anazida Zainal, Maheyzah Md Siraj, Fuad A. Ghaleb, Xue Hao, Shaoyong Han

“…Abstract The application of artificial neural networks (ANNs) can be found in numerous fields, including image and speech recognition, natural language processing, and autonomous vehicles. …”
Get full text

A Novel Hybrid Die Design for Enhanced Grain Refinement: Vortex Extrusion–Equal-Channel Angular Pressing (Vo-CAP) by Hüseyin Beytüt, Kerim Özbeyaz, Şemsettin Temiz

“…The optimization process utilized an integrated approach combining Finite Element Analysis (FEA), artificial neural networks (ANNs), and the non-dominated sorting genetic algorithm II (NSGA-II). …”
Get full text

Mathematical Modeling of Properties and Structures of Crystals: From Quantum Approach to Machine Learning by Grzegorz Matyszczak, Christopher Jasiak, Gabriela Rusinkiewicz, Kinga Domian, Michał Brzozowski, Krzysztof Krawczyk

“…., cellular automata, CA), to machine learning (e.g., artificial neural networks, ANNs).…”
Get full text

Primena veštačkih neuronskih mreža za predikciju snage na izlazu hidroelektrane by Stefan Čubonović, Aleksandar Ranković, Marko Krstić

“…U ovom istraživačkom radu sprovedena je analiza dva tipa veštačkih neuronskih mreža (Artificial Neural Network – ANN) za predikciju snage na izlazu hidroelektrane (HE). …”
Get full text

A Novel Ionospheric Inversion Model: PINN‐SAMI3 (Physics Informed Neural Network Based on SAMI3) by Jiayu Ma, Haiyang Fu, J. D. Huba, Yaqiu Jin

“…The PINN‐SAMI3 achieves good inversion results even using sparse data in comparison to the traditional artificial neural networks (ANN). The framework will contribute to advance the future space weather prediction capability with artificial intelligence (AI).…”
Get full text

Design Space Approach in Optimization of Fluid Bed Granulation and Tablets Compression Process by Jelena Djuriš, Djordje Medarević, Marko Krstić, Ivana Vasiljević, Ivana Mašić, Svetlana Ibrić

“…Percent of paracetamol released and tablets hardness were determined as critical quality attributes. Artificial neural networks (ANNs) were applied in order to determine design space. …”
Get full text

Rapid Determination of the Freshness of Lotus Seeds Using Surface Desorption Atmospheric Pressure Chemical Ionization-Mass Spectrometry with Multivariate Analyses by Yunyang Chi, Liping Luo, Xueyong Huang, Meng Cui, Ximo Dai, Yingbin Hao, Xiali Guo, Huolin Luo

“…The obtained data were processed by principal component analysis (PCA) and backpropagation artificial neural networks (BP-ANNs). The result showed that DAPCI-MS could obtain abundant chemical material information from the slice surface of lotus seeds. …”
Get full text

Intelligent Early Warning System for Construction Safety of Excavations Adjacent to Existing Metro Tunnels by Wei Tian, Jiang Meng, Xing-Ju Zhong, Xiao Tan

“…However, the trial application of artificial neural networks (ANNs) and building information modelling (BIM) for engineering projects provides a new method for solving such problems. …”
Get full text

Robust neural network filtering in the tasks of building intelligent interfaces by A. V. Vasiliev, A. O. Melnikov, S. A. Lesko

“…The possibility of using artificial neural networks to identify and suppress individual human characteristics in biological signals is demonstrated. …”
Get full text

From Baseline to Best Practice: An Advanced Feature Selection, Feature Resampling and Grid Search Techniques to Improve Injury Severity Prediction by Soukaina EL Ferouali, Zouhair Elamrani Abou Elassad, Sara Qassimi, Abdelmounaîm Abdali

“…Fourth predictive systems are employed to investigate the intricate problem of predicting the severity of injuries sustained in traffic crashes using different regression algorithms, such as Random Forest, Decision Trees, XGBoost, and Artificial Neural Networks. Compared to comparable systems without feature selection, feature resampling, and optimization methods, the results demonstrate that employing optimized XGBoost along with grid search in conjunction with SelectKBest and SMOTE strategy has resulted in greater performance, with an 89% R2 score. …”
Get full text