circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression data by Petr Ryšavý, Alikhan Anuarbekov, Michaela Dostálová Merkerová, Jiří Kléma

“…However, validation data for RNA interactions are often sparse and predicted interactions contain many false positives. …”
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Analysis of global stock market development-Integration of clustering, classification, and shapley values. by Marcin Stawarz

“…Shapley Values are employed to interpret the contribution of individual variables to the model's predictions, considering all possible combinations of features. …”
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Twenty First Century’s Challenges, Changing Trends and Urdu Novel: A Critical Analysis by Mehroona Leghari

“…The trend of predicting the future is growing day by day. Now a strange situation is knocking on human beings doors. …”
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Eulerian Oil Spills Model Using Finite-Volume Method with Moving Boundary and Wet-Dry Fronts by Ehsan Sarhadi Zadeh, Kourosh Hejazi

“…For validation of oil spill model, predicted results are compared with experimental data from a physical modeling of oil spill in a laboratory wave basin under controlled conditions.…”
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Privacy-preserving location-based traffic density monitoring by Lei Wu, Xia Wei, Lingzhen Meng, Shengnan Zhao, Hao Wang

“…Traffic density monitoring is an important method to predict road traffic conditions, which can bring some convenience to people's travel in daily life. …”
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Graph attention networks based multi-agent path finding via temporal-spatial information aggregation. by Qingling Zhang, Peng Wang, Cui Ni, Xianchang Liu

“…An effective Multi-Agent Path Finding (MAPF) algorithm must efficiently plan paths for multiple agents while adhering to constraints, ensuring safe navigation from start to goal. …”
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Enhancing precision in multiple sclerosis lesion segmentation: A U-net based machine learning approach with data augmentation by Oezdemir Cetin, Berkay Canel, Gamze Dogali, Unal Sakoglu

“…This study proposes a robust machine learning algorithm designed to identify MS lesions using both single-modal and multi-modal MRI data. …”
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Tracking and climbing behavior recognition of heavy-duty trucks on roadways by Lei Tang, Jingchi Jia, Zongtao Duan, Jingyu Ma, Xin Wang, Weiwei Kong

“…The spatiotemporal information of trucks from trajectory tracking and motions learnt from behavior analysis can be employed to predict possible driving risks and generate safe motion to avoid roadway accidents. …”
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An indoor positioning method based on bluetooth array/PDR fusion using the SVD-EKF by Chenhui Li, Jie Zhen, Jianxin Wu

“…The dynamic test results in the room show that after SVD-EKF algorithm optimization, the positioning error is reduced by 0.05m, which is equivalent to the EKF algorithm. …”
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Model-Based Offline Reinforcement Learning for AUV Path-Following Under Unknown Ocean Currents with Limited Data by Xinmao Li, Lingbo Geng, Kaizhou Liu, Yifeng Zhao

“…To address this, we propose a conservative offline model-based Q-learning (CMQL) algorithm. This algorithm is robust to unknown disturbance and efficient in data utilization. …”
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Disulfidptosis-related classification patterns and tumor microenvironment characterization in skin cutaneous melanoma by Li Yang, Zi-jian Cao, Yuan Zhang, Jin-ke Zhou, Jun Tian

“…The consensus clustering algorithm was applied to categorize SKCM patients into different DRG subtypes. …”
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Modular Mobile Charging Facility Layout Optimization Method and Deployment Strategy by Jiajun ZHENG, Xiaoyu DUAN, Zechun HU, Xiaorui HU, Bin ZHU

“…Firstly, an electric vehicle user travel mechanism model is established to predict the spatial and temporal distribution of charging demand at the node level. …”
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Study on Vibration Characteristic of Trilobe Raceway Cylindrical Roller Bearing with Elastic Support by Sun Xue, Deng Sier, Zhang Yuanjun, Chen Guoding

“…Based on dynamics analysis of rolling bearing,the dynamics differential equations for cylindrical roller bearing with trilobe raceway and elastic support are established. By using the predict-correct integer algorithm with variable step,the dynamics equation is solved,and the influence of structural parameters of elastic support and working conditions on the vibration characteristics of the bearing is investigated. …”
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Quantitative Structure-Activity Relationship Studies for Potential Rho-Associated Protein Kinase Inhibitors by Giovanna Cardoso Gajo, Tamiris Maria de Assis, Letícia Cristina Assis, Teodorico Castro Ramalho, Elaine Fontes Ferreira da Cunha

“…Furthermore, analyzing the descriptors it was possible to propose new compounds that predicted higher inhibitory concentration values than the most active compound of the series.…”
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Numerical simulation of cavitating two-phase gas-liquid three-dimensional flow in a duct of varying cross-section based on homogenous mixture model by Nguyen The Duc

“…The numerical method uses artificial compressibility algorithm extended to unsteady flows with dual-time technique. …”
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Formation of Scattering Characteristics for Acoustical Ray Tracing Simulation by Srđan BOJIČIĆ, Dragana ŠUMARAC-PAVLOVIĆ, Miomir MIJIĆ

“…Ray tracing simulation of sound field in rooms is a common tool in room acoustic design for predicting impulse response. There are numerous commercial engineering tools utilising ray tracing simulation. …”
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Reducing Unnecessary Handovers Using Logistic Regression in 5G Networks by Alison M. Fernandes, Hermes I. Del Monego, Bruno S. Chang, Anelise Munaretto

“…This paper proposes using machine learning in 5G mobile networks, employing a Logistic Regression algorithm to predict handovers. Considering selection criteria like Reference Signal Received Power, Signal-to-Interference-Plus-Noise Ratio, Received Signal Strength Indicator, and distance, our proposal shows that it can significantly reduce the consequences of frequent handovers and provide a better quality of service to the user, together with low computational complexity. …”
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SAB: Self-Adaptive Bias by Suchan Choi, Jinyoung Oh, Jeong-Won Cha

“…We use entropy to select data samples with less consistent predictions and automatically determine the warming-up period based on the characteristics of the data. …”
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Cascade Machine Learning Approach Applied to Short-Term Medium Horizon Demand Forecasting by Bruno Brentan, Ariele Zanfei, Martin Oberascher, Robert Sitzenfrei, Joaquin Izquierdo, Andrea Menapace

“…The LSTM model estimates, utilizing a univariate approach, the hourly forecasting of water demand for the entire available dataset and the minimum night flow. The algorithm considers various time series sizes for each DMA and predicts the water demand values for each hour throughout the week. …”
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Machine-learning certification of multipartite entanglement for noisy quantum hardware by Andreas J C Fuchs, Eric Brunner, Jiheon Seong, Hyeokjea Kwon, Seungchan Seo, Joonwoo Bae, Andreas Buchleitner, Edoardo G Carnio

“…After training a model on randomly generated quantum states, entangled in different partitions and of varying purity, we verify the accuracy of its predictions on simulated test data, and finally apply it to states prepared on IBM quantum computing hardware.…”
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