Towards a Digital Twin for Gas Turbines: Thermodynamic Modeling, Critical Parameter Estimation, and Performance Optimization Using PINN and PSO by Jian Tiong Lim, Achnaf Habibullah, Eddie Yin Kwee Ng

“…The results demonstrated that GTPO could be optimized with the application of conformal prediction when the true GTPO is detected to be higher than the upper range of GTPO obtained from the ANN model with a conformal prediction of a 95% confidence level. …”
Get full text

Leveraging AI to explore structural contexts of post-translational modifications in drug binding by Kirill E. Medvedev, R. Dustin Schaeffer, Nick V. Grishin

“…Recent advancements in computational power and artificial intelligence, particularly in deep learning algorithms and protein structure prediction tools like AlphaFold3, have opened new possibilities for exploring the structural context of interactions between PTMs and drugs. …”
Get full text

Data-Driven and Mechanistic Soil Modeling for Precision Fertilization Management in Cotton by Miltiadis Iatrou, Panagiotis Tziachris, Fotis Bilias, Panagiotis Kekelis, Christos Pavlakis, Aphrodite Theofilidou, Ioannis Papadopoulos, Georgios Strouthopoulos, Georgios Giannopoulos, Dimitrios Arampatzis, Evangelos Vergos, Christos Karydas, Dimitris Beslemes, Vassilis Aschonitis

“…By comparing the Mean Absolute Error (MAE) between predicted and observed cotton yield values across three ML algorithms, i.e., Random Forest (RF), XGBoost, and LightGBM, the RF model achieved the lowest error (422.6 kg/ha), outperforming XGBoost (446 kg/ha) and LightGBM (449 kg/ha). …”
Get full text

Frequency-Domain Finite Element Modeling of Seismic Wave Propagation Under Different Boundary Conditions by Ying Zhang, Haiyang Liu, Shikun Dai, Herui Zhang

Get full text

Minimal‐cost route planning via Fibonacci‐heap‐typed data structure by Wangjia Zhan, Haohao Qiu, Bo Min, Lin Lin

“…In particular, the article introduces a Fibonacci‐heap‐typed data structure to the minimal‐cost route planning algorithm, resulting in a remarkable reduction of the time complexity from O(mn) to O(m+nlogn), where m and n represent the cardinalities of the arc set and nodeset, respectively. …”
Get full text

Mathematical Modeling of Tuberculosis Transmission Dynamics With Reinfection and Optimal Control by Francis Oketch Ochieng

“…The model was fitted to historical TB incidence data for Kenya from 2000 to 2022 using lsqcurvefit algorithm in MATLAB software. The fitting algorithm yielded a mean absolute error (MAE) of 0.0069, demonstrating a close alignment between simulated and observed data. …”
Get full text

The role of advanced machine learning in COVID-19 medical imaging: A technical review by Abdul Muiz Fayyaz, Said Jadid Abdulkadir, Shahab Ul Hassan, Safwan Mahmood Al-Selwi, Ebrahim Hamid Sumiea, Lareib Fatima Talib

“…It focuses on approaches such as Deep Learning (DL) algorithms and Transfer Learning, which have demonstrated significant potential in developing automated, accurate COVID-19 detection systems. …”
Get full text

Grassland management and phenology affect trait retrieval accuracy from remote sensing observations by Maksim Iakunin, Franziska Taubert, Reimund Goss, Severin Sasso, Hannes Feilhauer, Daniel Doktor

“…This study combines radiative transfer model (RTM) and machine learning algorithms to assess the efficacy of the model inversion in predicting plant functional traits under different grassland management regimes. …”
Get full text

The powerless bosses: the working day experience of bicycle messengers and its impact on their identities and wellbeing by Iben Østin Hjelle, Helle Nordrum, Julian-Werner Wentzeck, Ali Teymoori

“…Results We discerned five themes related to the dynamics of autonomy versus algorithmic control, the reduction of workers’ identity to the courier role, lack of collegial bonding among bicycle messengers, physical demands and risks of the job, and the transitory nature of courier work. …”
Get full text

Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels by Yi-bing Li, Xue-ying Diao, Qian-hui Dong

“…Simulation results show that rank minimization interference minimization algorithm can provide more interference-free dimensions for desired signals than other rank minimization methods. …”
Get full text

Weak fault diagnosis method for rolling bearings under strong background noise based on EEMD-FK-AMCKD by XIE Guizhong, XU Shuaiqiang, DU Wenliao, LUO Shuangqiang, LI Hao, WANG Liangwen, GONG Xiaoyun

“…Next, the fast kurtogram algorithm was employed to determine the carrier frequency, bandwidth, and the layer with the maximum kurtosis value of the reconstructed signal, enabling the design of a bandpass filter for noise reduction. …”
Get full text

Species-level classification of urban trees from WorldView-2 imagery in Debrecen, Hungary: An effective tool for planning a comprehensive green network to reduce dust pollution by Vanda Eva MOLNAR, Edina SIMON, Szilárd SZABÓ

“…The best overall accuracy was achieved with the ML algorithm applied to the first four transformed bands (75.1%), and with the SVM algorithm applied to eight bands (71.0%). …”
Get full text

New timestamp mark–based energy efficient time synchronization method for wireless sensor networks by Yourui Huang, Gang Zhang, Min Kong, Fugui He

“…The group-wise pair selection algorithm is used to select the network’s pairwise synchronization nodes, and chain-type network topology is thus generated. …”
Get full text

Applications of machine learning in decision analysis for dose management for dofetilide. by Andrew E Levy, Minakshi Biswas, Rachel Weber, Khaldoun Tarakji, Mina Chung, Peter A Noseworthy, Christopher Newton-Cheh, Michael A Rosenberg

“…A reinforcement learning algorithm informed by unsupervised learning was able to predict dosing decisions with 96.1% accuracy. …”
Get full text

Development of an MRI based artificial intelligence model for the identification of underlying atrial fibrillation after ischemic stroke: a multicenter proof-of-concept analysisRes... by Zijie Zhang, Yang Ding, Kaibin Lin, Wenli Ban, Luyue Ding, Yudong Sun, Chuanliang Fu, Yihang Ren, Can Han, Xue Zhang, Xiaoer Wei, Shundong Hu, Yuwu Zhao, Li Cao, Jun Wang, Saman Nazarian, Ying Cao, Lan Zheng, Min Zhang, Jianliang Fu, Jingbo Li, Xiang Han, Dahong Qian, Dong Huang

“…Area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were calculated for model evaluation. …”
Get full text

A Bit String Content Aware Chunking Strategy for Reduced CPU Energy on Cloud Storage by Bin Zhou, ShuDao Zhang, Ying Zhang, JiaHao Tan

“…The existing chunking algorithm greatly reduces the system performance when confronted with big data and it wastes a lot of energy. …”
Get full text

The Value of Morphologic Study (MRI) of the Median Nerve in Stadialization and Treatment of the Carpal Tunnel Syndrome by Florin Gabriel PANCULESCU, Raluca STEFANESCU, Ion BORDEIANU, Iulian Catalin BRATU

“…The criterion of diameter decrease can be a benchmark in order to establish a therapeutic algorithm in carpal tunnel syndrome.…”
Get full text

Optimal design of high‐performance rare‐earth‐free wrought magnesium alloys using machine learning by Shaojie Li, Zaixing Dong, Jianfeng Jin, Hucheng Pan, Zongqing Hu, Rui Hou, Gaowu Qin

“…Abstract In this study, a small dataset of 370 datapoints of Mg alloys are selected for machine learning (ML), in which each datapoint includes five rare‐earth‐free alloying elements (Ca, Zn, Al, Mn and Sn), three extrusion parameters (extrusion speed, temperature and ratio), and three mechanical properties (yield strength [YS], ultimate tensile strength [UTS] and elongation [EL]). The ML algorithms, including support vector machine regression (SVR), artificial neural network, and other three methods, are employed, and the SVR has the best performance in predicting mechanical properties based on the components, and process parameters, with the mean absolute percentage error of YS, UTS, and EL being 6.34%, 4.19%, and 13.64% in the test set, respectively. …”
Get full text

A Self-Supervised Feature Point Detection Method for ISAR Images of Space Targets by Shengteng Jiang, Xiaoyuan Ren, Canyu Wang, Libing Jiang, Zhuang Wang

“…The experiments demonstrate that SFPD has better performance in feature point detection and feature point matching than usual algorithms.…”
Get full text

Benchmark dataset on feeding intensity of the pearl gentian grouper(Epinephelus fuscoguttatus♀×E. lanceolatus♂) by Haijing Qin, Yunchen Tian, Jianing Quan, Xueqi Cong, Qingfei Li, Jinzhu Sui

“…In addition, training on this benchmark dataset proposes an improved feeding intensity evaluation network, which achieves a good balance in prediction accuracy and parameter memory and offers the possibility of subsequent deployment of the model on mobile. …”
Get full text