Workplace Preference Analytics Among Graduates by Sin-Yin Ong, Choo-Yee Ting, Hui-Ngo Goh, Albert Quek, Chin-Leei Cham

“…Notably so, results from this study demonstrate that using Random Forest Algorithm resulted in better performance in predicting employment status with an accuracy rate of 99.40%, predicting company type with 66.60% and lastly predicting company sector with 30.80% when compared to other predictive models utilized during our research work's project lifecycle phase.…”
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Evaluation of Machine Learning Applications for the Complex Near-Critical Phase Behavior Modelling of CO₂–Hydrocarbon Systems by Daulet Magzymov, Meruyert Makhatova, Zhasulan Dairov, Murat Syzdykov

“…The objective of this study was to evaluate the capability of machine learning models to accurately predict complex near-critical phase behavior in CO₂–hydrocarbon systems, which are crucial for enhanced oil recovery and carbon storage applications. …”
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AI-driven model for optimized pulse programming of memristive devices by Benjamin Spetzler, Markus Fritscher, Seongae Park, Nayoun Kim, Christian Wenger, Martin Ziegler

“…Here, we present a computationally efficient AI model for predicting the weight update of memristive devices and guiding device programming. …”
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Gas permeability, diffusivity, and solubility in polymers: Simulation-experiment data fusion and multi-task machine learning by Brandon K. Phan, Kuan-Hsuan Shen, Rishi Gurnani, Huan Tran, Ryan Lively, Rampi Ramprasad

“…To address this challenge, we present a multi-tiered multi-task learning framework empowered with advanced machine-crafted polymer fingerprinting algorithms and data fusion techniques. This framework combines scarce “high-fidelity” experimental data with abundant diverse “low-fidelity” simulation or synthetic data, resulting in predictive models that display a high level of generalizability across novel chemical spaces. …”
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Power System Operation Stability Assessment Method Based on Deep Convolutional Neural Network by Jinman Luo, Yuqing Li, Qile Wang, Liyuan Liu

“…Compared with other algorithm reference models, this model has a higher evaluation accuracy of 98.39%, far exceeding other comparison models. …”
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Small fixed-wing UAV Precision Aerial Drop capability development by Antonić Vuk, Trifković Milenko, Molović Vojimir, Milenković-Babić Miodrag

“…Precision aerial drop software module is presented, focusing on the automated payload drop algorithm with continually calculated impact point prediction (CCIP) and UAV guidance to the continually calculated release point (CCRP). …”
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Forecast-Aided Converter-Based Control for Optimal Microgrid Operation in Industrial Energy Management System (EMS): A Case Study in Vietnam by Yeong-Nam Jeon, Jae-ha Ko

“…The forecasted load data is then used to optimize charge/discharge schedules for energy storage systems (ESS) using a Particle Swarm Optimization (PSO) algorithm. The strategy is validated using real-site data from a Vietnamese industrial complex, where the proposed method demonstrates enhanced load prediction accuracy, cost-effective ESS operation, and multi-microgrid flexibility under weather variability. …”
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Modeling Spatial Data with Heteroscedasticity Using PLVCSAR Model: A Bayesian Quantile Regression Approach by Rongshang Chen, Zhiyong Chen

“…Computational efficiency is achieved through a modified reversible-jump MCMC algorithm incorporating adaptive movement steps to accelerate chain convergence. …”
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Research on intelligent routing with VAE-GAN in the internet of body. by Song Qian, Tianping Zhang, Siping Hu

“…The traditional artificial intelligence routing algorithm cannot deal with the low model prediction accuracy and poor generalization ability caused by large noise and small data volume. …”
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Lymph Node Assessment in Endometrial Cancer: Towards Personalized Medicine by Fabien Vidal, Arash Rafii

“…Finally, the use of peroperative algorithm for risk determination could improve patient's staging with a reduction of lymphadenectomy-related morbidity.…”
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Modeling Chaotic Behavior of Chittagong Stock Indices by Shipra Banik, Mohammed Anwer, A. F. M. Khodadad Khan

“…In this paper, a comparative study has been conducted to predict stock index values using soft computing models and time series model. …”
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Ultrafast silicon photonic reservoir computing engine delivering over 200 TOPS by Dongliang Wang, Yikun Nie, Gaolei Hu, Hon Ki Tsang, Chaoran Huang

“…Experimental results demonstrate state-of-the-art performance in prediction, emulation, and classification tasks across various machine learning applications. …”
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Parametric Studies of Laminated Cooling Configurations: Overall Cooling Effectiveness by Chen Wang, Chunhua Wang, Jingzhou Zhang

“…Moreover, based on the numerical results, an empirical correlation is developed to predict the overall cooling efficiency in a specific range, and a genetic algorithm is applied to determine the empirical parameters. …”
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Hybrid solver with deep learning for transport problem in porous media by Vladislav Trifonov, Egor Illarionov, Anton Voskresenskii, Musheg Petrosyants, Klemens Katterbauer

“…Extensive experiments with dynamic and static reservoir features revealed that improving predictive accuracy does not necessarily improve fluid modeling. …”
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A Reduced-Order Model for Active Suppression Control of Vehicle Longitudinal Low-Frequency Vibration by Donghao Hao, Changlu Zhao, Ying Huang

“…Establishing a prediction model, with linearity and few dof (degree of freedom), is a key step for the design of a control algorithm based on the modern control theory. …”
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Automatic Fault Classification for Journal Bearings Using ANN and DNN by Narendiranath Babu THAMBA, Arun ARAVIND, Abhishek RAKESH, Mohamed JAHZAN, Rama Prabha DURAISWAMY, Ramalinga Viswanathan MANGALARAJA

“…Proper analysis of the various bearing faults and predicting the modes of failure beforehand are essential to increase the working life of the bearing. …”
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Graph Knowledge Structure for Attentional Knowledge Tracing With Self-Supervised Learning by Zhaohui Liu, Sainan Liu, Weifeng Gu

“…In addition, we incorporate the improved representation algorithm into the loss function to handle data sparsity, thereby improving prediction accuracy. …”
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Bearing clearance test and lifetime analysis for EMU traction motor by GENG Min, ZHAO Pengyu, LI Xiaoyang, LEI Guanbiao, WANG Xilian

“…The mechanical load is the only factor of influence considered in the traditional bearing lifetime prediction algorithm. However, for the traction motor of the electric multiple units (EMUs) in actual working conditions, its bearing is also subject to the additional electromagnetic load derived from the additional radial electromagnetic force acting on its rotor, which is under effect of bearing clearance. …”
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Analysis of crop disease and pest occurrences: Insights from Japan's national surveys. by Jianqiang Sun, Sunao Ochi, Takehiko Yamanaka

“…However, the prediction error remained substantial, with an RMSE of 6.2 ± 19.6. …”
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RIM-MAC:a receiver initiated multi-session MAC protocol for underwater acoustic networks by Chao LI, Yong-jun XU, Bo-yu DIAO, Feng WANG, Qi WANG

“…,neighboring nodes’ propagation delay maps and expected transmission schedules) to launch multiple simultaneous sessions.RIM-MAC increases the chances of concurrent transmissions in the underwater channel and achieve the channel reuse at both the sender and receiver side,improving the overall throughput at least 36% compared to the typical MAC protocols.Moreover,a traffic prediction based adaptive data polling scheme named fair traffic algorithm (FTA) guarantees fairness across multiple contending nodes.Extensive simulation results have confirmed that the RIM-MAC protocol outperforms existing MAC protocols and provides fair medium access in representative long propagation delay scenarios.…”
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