Optimal Model-Free Mean-Square Consensus for Multi-Agents with Markov Switching Topology by Ruoxun Ma, Lipo Mo, Bokang Zhou

“…The concept of mean-square consensus is introduced, and the relationship between consensus error and tracking error to achieve mean-square consensus is studied. …”
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DIB‐BOT: An Open‐Source Hardware Approach for Plate‐Integrated Droplet Interface Bilayer Deposition by Alexander F Mason, Shelley FJ Wickham, Matthew AB Baker

“…Compared to manual fabrication, DIB‐BOT shows a 10‐fold reduction in droplet volume error, a threefold reduction in positional error, and 100% droplet yield. …”
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The Role of Visual Performance in Fine Motor Skills by Pilar Granados-Delgado, Miriam Casares-López, Francesco Martino, Rosario González Anera, José Juan Castro-Torres

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Monte Carlo Dropout Neural Networks for Forecasting Sinusoidal Time Series: Performance Evaluation and Uncertainty Quantification by Unyamanee Kummaraka, Patchanok Srisuradetchai

“…Results indicate that MCDO NNs consistently outperform SARIMA in terms of root mean square error, mean absolute percentage error, and the coefficient of determination, while also producing more reliable prediction intervals. …”
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Fixed-Time Cooperative Tracking Control With Novel Finite-Time Parameter Estimation Algorithm for Nonlinear Multi-Agent Systems by Ibrahim Bako Abdulhamid, Muhammad Nasiruddin Mahyuddin

“…Cooperative control of multi-agent systems (MASs) has gained significant attention due to its applications in autonomous vehicles, robotics, and distributed sensor networks. …”
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Optimization of Laser-Induced Hybrid Hardening Process Based on Response Surface Methodology and WOA-BP Neural Network by Qunli Zhang, Jianan Ling, Zhijun Chen, Guolong Wu, Zexin Yu, Yangfan Wang, Jun Zhou, Jianhua Yao

“…The WOA-BPNN model outperforms the RSM model, achieving superior predictive accuracy with R² values exceeding 0.995 for both depth and hardness, with a root mean square error (RMSE) for depth of 0.099 mm and of 1.734 HV_0.3 for hardness, and with mean absolute percentage error (MAPE) of 0.697% and 0.7867%, respectively. …”
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A Regularization of the Backward Problem for Nonlinear Parabolic Equation with Time-Dependent Coefficient by Pham Hoang Quan, Le Minh Triet, Dang Duc Trong

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Advanced Hybrid RNN Architectures for Real-time Cryptocurrency Forecasting and Strategic Trading Optimization by Kehelwala Dewage Gayan Maduranga, Shamima Nasrin Tumpa

“…Extensive experiments are conducted, and the models are evaluated using key performance metrics, such as Mean Squared Error (MSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). …”
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Next-Generation Sequencing Methods to Determine the Accuracy of Retroviral Reverse Transcriptases: Advantages and Limitations by Javier Martínez del Río, Luis Menéndez-Arias

“…Retroviruses, like other RNA viruses, mutate at very high rates and exist as genetically heterogeneous populations. The error-prone activity of viral reverse transcriptase (RT) is largely responsible for the observed variability, most notably in HIV-1. …”
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A transformer-based framework for enterprise sales forecasting by Yupeng Sun, Tian Li

“…The experimental results demonstrated that our proposed method surpasses conventional machine learning models, achieving reduced mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE), as well as higher R2 values of nearly 0.95. …”
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Compact and Real-Time Radiation Dosimeter Using Silicon Photomultipliers for In Vivo Dosimetry in Radiation Therapy by Jeongho Kim, Jeehoon Park, Byungdo Park, Yonghoon Kim, Beomjun Park, So Hyun Park

“…Existing dosimeters for radiation therapy are typically large, and their performance in in vivo system applications has not been assessed. This study develops a compact real-time dosimeter using silicon photomultipliers, plastic scintillators, and optical fibers and evaluates its in vivo applicability for radiation therapy. …”
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FPGA‐Based Design of Ultra‐Efficient Approximate Adders for High‐Fidelity Image Processing: A Logic‐Optimized Approach by Ramakrishna Reddy Eamani, N. Vinodhkumar, Ambe Harrison, Wulfran Fendzi Mbasso

“…ABSTRACT Emerging as a promising paradigm for improving energy efficiency in error‐tolerant applications including image processing, neural networks, and embedded vision systems is approximative computing. …”
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Enhancing energy management in battery electric vehicles: A novel approach based on fuzzy Q-learning controller by Salma Ariche, Zakaria Boulghasoul, Abdelhafid El Ouardi, Abdelhadi Elbacha, Abdelouahed Tajer, Stéphane Espié

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Fusion-Based Localization System Integrating UWB, IMU, and Vision by Zhongliang Deng, Haiming Luo, Xiangchuan Gao, Peijia Liu

“…Accurate indoor positioning services have become increasingly important in modern applications. Various new indoor positioning methods have been developed. …”
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EXPLORING TEACHERS AND STUDENTS’ PERSPECTIVES TOWARD NEGOTIATED SYLLABUS IN ENGLISH LEARNING FOR SENIOR HIGH SCHOOL by Imam Ghozali, Banun Havifah Cahyo Khosiyono, Muhammad Ulil Abror

“…Ensuring both teachers and students’ needs what and how their teaching and learning are applicable, negotiated syllabus can be proposed in teaching-learning processes. …”
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Extended ball convergence for a seventh order derivative free class of algorithms for nonlinear equations by I.K. Argyros, D. Sharma, C.I. Argyros, S.K. Parhi, S.K. Sunanda, M.I. Argyros

“…Additionally, we offer error distances and convergence radius together with the region of uniqueness for the solution. …”
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ACCURACY ANALYSIS ON THE EMPIRICAL EQUATION OF FINITE THICKNESS SEMI-ELLIPTICAL SURFACE CRACK BASED ON INTERACTION INTEGRAL METHOD by HOU Shuai, ZHU YouLi, QIU Ji, SUN XiaoFeng

“…Based on the analysis, the applicable range of the empirical equation is presented.…”
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Path Following of Autonomous Vehicle in 2D Space Using Multivariable Sliding Mode Control by Daxiong Ji, Jian Liu, Hongyu Zhao, Yiqun Wang

“…An error integration element is added into the “tanh” function of the traditional sliding mode control. …”
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Finite element analysis of cardiovascular stent frames: identifying appropriate mesh discretization by Brandon A. Lurie, Stuart Kari, Marc Horner, Christopher A. Basciano, Santhosh Kumar Murugadass, Nuno Rebelo

“…The methodology includes estimating the exact solution for the numerical model, calculating the discretization error and computational cost for various mesh discretization options, and considering the error and cost when selecting one of the options. …”
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Comparative Assessment of the Effect of Positioning Techniques and Ground Control Point Distribution Models on the Accuracy of UAV-Based Photogrammetric Production by Muhammed Enes Atik, Mehmet Arkali

“…For all six models, all techniques have an error value of sub-decimeter. The PPP-AR technique yields error values that are comparable to those of the other techniques. …”
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