Low latency Montgomery multiplier for cryptographic applications by khalid javeed, Muhammad Huzaifa, Safiullah Khan, Atif Raza Jafri

“…Usually, this operation is performed by integer multiplication (IM) followed by a reduction modulo M. However, the reduction step involves a long division operation that is expensive in terms of area, time and resources. …”
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Komparasi Data Mining Naive Bayes dan Neural Network memprediksi Masa Studi Mahasiswa S1 by Azahari Azahari, Yulindawati Yulindawati, Dewi Rosita, Syamsuddin Mallala

“…By using the data mining algorithm Naive bayes and neural network, the student graduation in STMIK Widya Cipta Dharma (WiCiDa) can be predicted. …”
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Using machine learning to simultaneously quantify multiple cognitive components of episodic memory by Soroush Mirjalili, Audrey Duarte

“…Using a machine learning algorithm known as “transfer learning”, we leveraged visual perception, sustained attention, and selective attention brain states to better predict episodic memory performance from trial-to-trial encoding electroencephalography (EEG) activity. …”
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Simulation of the Performance of a Centrifugal Chiller by Luo Yi, Zhang Libiao, Hang Bingbing, Gong Chengcheng

“…The simulation software successfully predicts various parameters, such as chilled water temperatures, cooling water temperatures, and flow rates of the centrifugal chiller under different loads.…”
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A hybrid unsupervised machine learning model with spectral clustering and semi-supervised support vector machine for credit risk assessment. by Tao Yu, Wei Huang, Xin Tang, Duosi Zheng

“…Furthermore, a multi-view combined unsupervised method is designed to thoroughly mine data and enhance the robustness of label predictions. This method mitigates discrepancies in prediction outcomes from three distinct perspectives. …”
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Comprehensive assessment on estimating the thermodynamic and mechanical properties of multicomponent Fe–Cr-based alloys using machine learning techniques by Ahed Habib, Bashar Alibrahim, Mahdi Z. Alnunu, Hussein Moussa, Maan Habib

“…This study investigates the performance of 11 different machine learning algorithms to predict the mixing enthalpy, Young’s modulus, and the shear-to-bulk modulus ratio of Fe–Cr alloys with additions of Ni, Mo, Al, W, V, and Nb. …”
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Estimating the Compressive Strength of Cement-Based Materials with Mining Waste Using Support Vector Machine, Decision Tree, and Random Forest Models by Hongxia Ma, Jiandong Liu, Jia Zhang, Jiandong Huang

“…The SVM model can obtain the minimum RMSE, while the BAS algorithm is inefficient in DT and RF models. The SVM, DT, and RF models can be used to predict the compressive strength of cement-based materials using solid mining waste as aggregate effectively and accurately, with high R values and lower RMSE values. …”
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Damage Detection in Railway Truss Bridges Employing Data Sensitivity under Bayesian Framework: A Numerical Investigation by Kanta Prajapat, Samit Ray-Chaudhuri

“…Further, in a Bayesian algorithm, it can be quite beneficial if a damage localization algorithm is first used to localize damage in the structure. …”
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Supply chain finance credit risk assessment using support vector machine–based ensemble improved with noise elimination by Ying Liu, Lihua Huang

“…Then, we obtained the final classification results by combining finally individual prediction through AdaBoosting algorithm on the new sample set. …”
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Numerical Simulation Study on the Strengthening Mechanism of Rock Materials under Impact Loads by Xin Liu, Kai Wang, Chunan Tang, Xikun Qian

“…Inhomogeneities and inertial effects of rock materials are the fundamental reasons for the increase in the dynamic strength of rock materials. A reduction in inertial effects is the main reason for strength reduction in rock samples with hole defects.…”
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Developing a Multisensor-Based Machine Learning Technology (Aidar Decompensation Index) for Real-Time Automated Detection of Post–COVID-19 Condition: Protocol for an Observational... by Jenny Mathew, Jaclyn A Pagliaro, Sathyanarayanan Elumalai, Lauren K Wash, Ka Ly, Alison J Leibowitz, Varsha G Vimalananda

“…Using appropriate algorithmic techniques, the study expects the model to have a sensitivity of >80% and a positive predicted value of >70%. …”
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Modification of IPI Method for Extraction of Short-Term and Imminent OLR Anomalies and Case Study of Two Large Earthquakes by Maoning Feng, Pan Xiong, Weixi Tian, Yue Liu, Changhui Ju, Cheng Song, Yongxian Zhang

“…The Pattern Informatics Method (PI) was initially developed for medium-to-long-term earthquake prediction by analyzing changes in seismic activity. …”
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“Dictionary of immune responses” reveals the critical role of monocytes and the core target IRF7 in intervertebral disc degeneration by Peichuan Xu, Peichuan Xu, Kaihui Li, Jinghong Yuan, Jinghong Yuan, Jiangminghao Zhao, Jiangminghao Zhao, Huajun Pan, Huajun Pan, Chongzhi Pan, Chongzhi Pan, Wei Xiong, Wei Xiong, Jianye Tan, Jianye Tan, Tao Li, Tao Li, Guanfeng Huang, Guanfeng Huang, Xiaolong Chen, Xiaolong Chen, Xinxin Miao, Dingwen He, Xigao Cheng, Xigao Cheng

“…Eight small-molecule drugs were predicted to have therapeutic potential for IDD.ConclusionThese findings offer a multidimensional understanding of the pathogenesis of IDD, pinpointing monocytes and key genes as potential diagnostic and therapeutic targets. …”
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IoT-based personal thermal comfort control for livable environment by Miao Zang, Zhiqiang Xing, Yingqi Tan

“…In the prediction stage, we introduce the cuckoo search algorithm, which converges rapidly, to solve the air temperature and air velocity with the learnt thermal comfort level. …”
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Monthly Electricity Generatıon Forecast in Solar Power Plants with LSTM by Ali Hakan Isık, Ömer Çetin

“…In the study, predictions and analyses were made using the LSTM (Long Short-Term Memory) method, which is one of the artificial neural networks. …”
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Research Progress of Finite Element Technology in Wood Processing by Maosen Wang, Lin Yang

“…In material property analysis, FEA technology accurately models the anisotropy and heterogeneity of wood, predicting its mechanical responses under different loading conditions. …”
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Artificial Intelligence—What to Expect From Machine Learning and Deep Learning in Hernia Surgery by Robert Vogel, Björn Mück

“…The term AI incorporates various technologies including ML, Neural Networks (NN), and DL. Classical ML algorithms depend on structured, labeled data for predictions, requiring significant human oversight. …”
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Computational Estimation of Football Player Wages by Yaldo L., Shamir L.

“…Experimental results using data from 6,082 players show that the Pearson correlation between the predicted and actual salary of the players is ~0.77 (p < .001). …”
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Artificial Intelligence and Machine Learning Approaches for Target-Based Drug Discovery: A Focus on GPCR-Ligand Interactions by M. O. Otun

“…The advent of artificial intelligence (AI) and machine learning (ML) has revolutionized target-based drug discovery, offering innovative approaches to predict GPCR-ligand interactions with enhanced accuracy and efficiency. …”
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Binary atom search optimisation approaches for feature selection by Jingwei Too, Abdul Rahim Abdullah

“…Atom Search Optimisation (ASO) is a recently proposed metaheuristic algorithm that has proved to work effectively on several benchmark tests. …”
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