Research on velocity measurement and location method based on improved Kalman filter algorithm by Zhao Zhang, Jie Yang, Jusong Jiang

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Wearable Spine Tracker vs. Video-Based Pose Estimation for Human Activity Recognition by Jonas Walkling, Luca Sander, Arwed Masch, Thomas M. Deserno

“…The FlexTail model performs better for detecting sitting and transitions, like standing up, while the camera-based model is better for activities that involve arm and hand movements.…”
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Backward–forward sweep inverse power flow for distribution line parameters estimation with metering data by Pedro C. Leal, Pedro M. S. Carvalho

“…Information about electrical line parameters is a critical part of such information. An algorithm for estimating electric line parameters of medium‐voltage distribution networks is proposed. …”
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Data-Driven Approaches to Mining Passenger Travel Patterns: “Left-Behinds” in a Congested Urban Rail Transit Network by Xing Chen, Leishan Zhou, Zixi Bai, Yixiang Yue, Bin Guo, Hanxiao Zhou

“…The methodology is applied to a case study using AFC and AVL data from the Beijing URT network during peak hours to test the proposed model and algorithm. The estimation results are consistent with the results obtained from the authorities, and this finding verifies the feasibility of our approach.…”
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<span style="font-variant: small-caps">EpiInfer</span>: A Non-Markovian Method and System to Forecast Infection Rates in Epidemics by Jovan Kascelan, Ruoxi Yang, Dennis Shasha

“…In addition, it makes use of the following information: (i) the distribution of the number of meetings per person and (ii) the transition probabilities between states and uses those estimates to forecast future infection rates. …”
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Neuro-Musculoskeletal Modeling for Online Estimation of Continuous Wrist Movements from Motor Unit Activities by Yunfei Liu, Xu Zhang, Haowen Zhao, Xiang Chen, Bo Yao

“…Following offline model calibration with a global optimization algorithm, online angle estimation results demonstrated a significant superiority of the proposed model over the state-of-the-art NMS models (p &#x003C; 0.05), yielding the lowest normalized root mean square error (<inline-formula> <tex-math notation="LaTeX">$0.10~\pm ~0.02$ </tex-math></inline-formula>) and the highest determination coefficient (<inline-formula> <tex-math notation="LaTeX">$0.87~\pm ~0.06$ </tex-math></inline-formula>). …”
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Application of Machine Learning Algorithms to Predict Gas Sorption Capacity in Heterogeneous Porous Material by Tasbiha Ibad, Syed Muhammad Ibad, Haylay Tsegab, Rabeea Jaffari

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Sentinel-1 Noise Suppression Algorithm for High-Wind-Speed Retrieval in Tropical Cyclones by Dechen Ge, Lihua Wang, Weiwei Sun, Hongmei Wang, Wenjing Jiang, Tian Feng

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Enhanced Real-Time Onboard Orbit Determination of LEO Satellites Using GPS Navigation Solutions with Signal Transit Time Correction by Daero Lee, Soon Sik Hwang

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Large Language Model-Guided SARSA Algorithm for Dynamic Task Scheduling in Cloud Computing by Bhargavi Krishnamurthy, Sajjan G. Shiva

“…The experimental results validate the inference of mathematical modeling in terms of the convergence rate and better estimation of the heuristic value to optimize the value function of the SARSA learning algorithm.…”
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Online Learning to Cache and Recommend in the Next Generation Cellular Networks by Krishnendu S. Tharakan, B. N. Bharath, Vimal Bhatia

“…We model the influence of recommendation on demands by a Probability Transition Matrix (PTM). The proposed framework consists of estimating the PTM and use them to jointly recommend and cache the files. …”
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Data-Driven Approach for Passenger Assignment in Urban Rail Transit Networks: Insights From Passenger Route Choices and Itinerary Choices by Di Wen, Hongxia Lv, Hao Yu

“…The PRCM employs a granular ball–based density peaks clustering (GB-DP) algorithm to estimate passengers’ route choices based on historical data, enhancing precision and efficiency in passenger classification and route matching. …”
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Modelling the future of cleaner energy: Explainable artificial intelligence model for green hydrogen production rate estimation by Okorie Ekwe Agwu, Saad Alatefi, Ahmad Alkouh

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Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs by Emil Attanasi, Philip Freeman, Timothy Coburn

“…We demonstrate the application of machine learning (ML) algorithms to bypass these computations to yield more rapid estimates of CO2 storage resources in reservoirs capable of hosting CO2 in a supercritical state. …”
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An Explainable Machine Learning Approach for IoT-Supported Shaft Power Estimation and Performance Analysis for Marine Vessels by Yiannis Kiouvrekis, Katerina Gkirtzou, Sotiris Zikas, Dimitris Kalatzis, Theodor Panagiotakopoulos, Zoran Lajic, Dimitris Papathanasiou, Ioannis Filippopoulos

“…The results demonstrate the robustness and interpretability of tree-based methods, offering a data-driven alternative to traditional performance estimation techniques and supporting the maritime industry’s transition toward more efficient and sustainable operations.…”
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Detecting Planetary Oblateness in the Era of JWST: A Case Study of Kepler-167e by Quanyi Liu, Wei Zhu, Yifan Zhou, Zhecheng Hu, Zitao Lin, Fei Dai, Kento Masuda, Sharon X. Wang

“…Here, we develop a new algorithm that can compute the transit light curve due to an oblate planet very efficiently and use it to study the detectability of planet oblateness (and spin obliquity) with the James Webb Space Telescope (JWST). …”
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Multiscale KF Algorithm for Strong Fractional Noise Interference Suppression in Discrete-Time UWB Systems by Liyun Su, Yuli Zhang, Yanju Ma, Jiaojun Li, Fenglan Li

“…In order to suppress the interference of the strong fractional noise signal in discrete-time ultrawideband (UWB) systems, this paper presents a new UWB multi-scale Kalman filter (KF) algorithm for the interference suppression. This approach solves the problem of the narrowband interference (NBI) as nonstationary fractional signal in UWB communication, which does not need to estimate any channel parameter. …”
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Value-difference learning based mMTC devices access algorithm in multi-cell network by Xin LI, Jun SUN

“…In the massive machine type communication scenario of 5G, the access congestion problem of massive machine type communication devices (mMTCD) in multi-cell network is very important.A double deep Q network with value-difference based exploration (VDBE-DDQN) algorithm was proposed.The algorithm focused on the solution that could reduce the collision when a number of mMTCDs accessed to eNB in multi-cell network.The state transition process of the deep reinforcement learning algorithm was modeled as Markov decision process.Furthermore, the algorithm used a double deep Q network to fit the target state-action value function, and it employed an exploration strategy based on value-difference to adapt the change of the environment, which could take advantage of both current conditions and expected future needs.Moreover, each mMTCD updated the probability of exploration according to the difference between the current value function and the next value function estimated by the network, rather than using the same standard to select the best base eNB for the mMTCD.Simulation results show that the proposed algorithm can effectively improve the access success rate of the system.…”
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Precision evaluation criteria for simulation algorithms in infinite systems: A network model-based approach by Yonglong Ding

“…This conversion strategy not only underscores the generality of this approach but also highlights its practical significance in guiding the optimization of simulation algorithms. Moreover, it offers insights into estimating microlevel information from macrolevel data. …”
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A Search for Exoplanet Candidates in TESS 2 minute Light Curves Using Joint Bayesian Detection by Jamila S. Taaki, Athol J. Kemball, Farzad Kamalabadi

“…The detector uses Bayesian priors, adaptively estimated, to model unknown systematic noise and stellar variability incorporated in a Neyman–Pearson likelihood ratio test for a candidate transit signal; a primary goal of the algorithm is to reduce overfitting. …”
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