Toward Universal Multiplexer Multiply-Accumulate Architecture in Stochastic Computing by Yang Yang Lee, Zaini Abdul Halim, Mohd Nadhir Ab Wahab, Tarik Adnan Almohamad

“…Stochastic Computing (SC) has recently gained attraction due to its inherent error tolerance and extremely simple arithmetic hardware, making it particularly effective for accelerating modern applications such as neural networks on resource-constrained devices. …”
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Modeling and Simulation of Eddy Current Dissipation Magnetic Acceleration Noise of Space Inertial Sensors by Pengxuan Li, Zhiyin Sun, Wei Gao, Bingzhang Cao, Yunzhao Li, Liyi Li, Lei Wang

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Dairy Chain Safety in the Context of Antibiotic Residues—Current Status of Confirmatory Liquid Chromatography Methods: A Review by Sandra Dluhošová, Klára Bartáková, Lenka Vorlová, Pavlína Navrátilová, Oto Hanuš, Eva Samková

“…The current trends include the reduction in the consumption of organic solvents (to reduce occupational hazards and burden to the environment) and automation, eliminating the influence of human error and optimizing the workflow. …”
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Cognitive Load Identification of Pilots Based on Physiological-Psychological Characteristics in Complex Environments by Haibo Wang, Naiqi Jiang, Ting Pan, Haiqing Si, Yao Li, Wenjing Zou

“…This research is able to provide a useful reference for preventing and reduction of human error caused by the cognitive load during flight missions. …”
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New Makeup Air Method through Ceiling for Kitchen Ventilation in Severely Cold Regions and Its Effect on Air Environment by Xiaoxu Li, Kailiang Huang, Guohui Feng, Guanyu Cao, Ainong Li, Xu Teng

“…Moreover, it increased the indoor temperature by over 11.9 °C compared with the open window makeup air scheme. The average relative error between the experimental and simulated data was within 6.1%. …”
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Threshold Successive Cancellation Flip Decoding Algorithm for Polar Codes: Design and Performance by Zhicheng Liu, Liuquan Yao, Shuai Yuan, Guiying Yan, Zhiming Ma, Yuting Liu

“…Theoretical analysis reveals that Th-SCF asymptotically delays the first error position (FEP, the first part where the SC decoder fails) with probability 1, ensuring high decoding performance. …”
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Impact of Low-dose Imaging on PET Quantitative Accuracy and Image Quality by SU Xuesong, GENG Jianhua, ZHENG Rong, WANG Xuejuan

“…Subsequently, the recovery coefficient (RC), contrast recovery coefficient (CRC), contrast-to-noise ratio (CNR), percent background variability (PBV), background coefficient of variation (BCV), and residual error (RE) of the lung insert at different image planes were calculated within the phantom. …”

Association of prognostic nutritional index with all-cause and cardiovascular mortality in adults with depression: NHANES 2005–2018 by Haiyan Ding, Xinchun Zou

“…Restricted cubic spline analyses were utilized to explore the potential nonlinear association between PNI levels and mortality.ResultsThe weighted mean PNI level was 41.89 (standard error 0.1), and the median follow-up duration was 84 months. …”
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Effectiveness of Dietary Guidelines for Reducing Free Sugar Intakes: A Randomised Controlled Trial by Lucy Boxall, Katherine M. Appleton, Emily Arden-Close, Janet James

“…There were no significant differences at baseline %FS (mean with standard error in parentheses); control with 10.36% (0.67), N with 10.15% (0.66), NF with 10.68% (0.62), and NFS with 10.19% (0.56). …”
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Coordinated Design of Power System Stabilizer and Virtual Inertia Control Using Modified Harris Hawk Optimization for Improving Power System Stability by Mohamad Almas Prakasa, Imam Robandi, Alberto Borghetti, Muhammad Ruswandi Djalal, Waseda Himawari

“…With the optimal damping ratios of 9.94% to 9.96% achieved by HHO-MSS, the overall power system stability improvements, including both local and interarea responses across 38 simulations involving sudden load changes, varying inertia, and different RES levels, are as follows: 41.17% to 70.89% frequency nadir improvement, 25.9% to 67.38% power angle deviation improvement, 84.83% to 85.26% settling time reduction, and 51.57% to 89.73% average error reduction calculated with performance indices. …”
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A new validated Lymphoedema-specific Patient Reported Outcome Measure (LYMPROM) for adults with Lymphoedema. by Melanie Thomas, Marie Gabe-Walters, Ioan Humphreys, Alan Watkins

“…Following COSMIN guidelines, validation study phases used anonymised routinely collected data to examine internal consistency, structural validity, construct validity (compared with the EQ5D-5L), measurement error, test-retest reliability and responsiveness.…”
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ADEPNET: A Dynamic-Precision Efficient Posit Multiplier for Neural Networks by Aditya Anirudh Jonnalagadda, Uppugunduru Anil Kumar, Rishi Thotli, Satvik Sardesai, Sreehari Veeramachaneni, Syed Ershad Ahmed

“…This becomes especially useful for performing error-tolerant tasks like deep learning inference computation where low latency and area are a priority. …”
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Modeling Short-Term Drought for SPEI in Mainland China Using the XGBoost Model by Fanchao Zeng, Qing Gao, Lifeng Wu, Zhilong Rao, Zihan Wang, Xinjian Zhang, Fuqi Yao, Jinwei Sun

“…Key findings reveal spatiotemporal prediction patterns: temporal-scale dependencies show all models exhibit limited capability at SPEI-1 (R²: 0.32–0.41, RMSE: 0.68–0.79) but achieve progressive accuracy improvement, peaking at SPEI-12 where CPSO-XGBoost attains optimal performance (R²: 0.85–0.90, RMSE: 0.33–0.43) with 18.7–23.4% error reduction versus baselines. Regionally, humid zones (South China/Central-Southern) demonstrate peak accuracy at SPEI-12 (R² ≈ 0.90, RMSE < 0.35), while arid regions (Northwest Desert/Qinghai-Tibet Plateau) show dramatic improvement from SPEI-1 (R² < 0.35, RMSE > 1.0) to SPEI-12 (R² > 0.85, RMSE reduction > 52%). …”
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Adaptive period decomposition network with muti-scale temporal variation learning for water level prediction by Hui Wang, LiPing Wang, QiCang Qiu, Yuyan Gao, WenJuan Li, QiuShun Wang

“…New hydrologic insights for the region:: Compared to ten other advanced prediction models, DLGNet achieved an average reduction in mean square error (MSE) by 94. 82%, 93. 35%, and 83. 13% for short-term, mid-term, and long-term predictions, respectively. …”
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NetCodeAIoT: Enhancing Augmented Intelligence of Things for Vehicle Systems in 5G Networks by Okuwudili Mathew Ugochukwu, Renata Lopes Rosa, Muhammad Saadi, Demostenes Z. Rodriguez, Frederico G. Guimaraes

“…NetCodeAIoT dynamically adjusts the sparsity level of the decoding matrix, implements unequal error protection network coding, and enables instantaneous decoding of data. …”
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An Adaptive Three-Dimensional Self-Masking Strategy for the Micro-Fabrication of Quartz-MEMS with Out-of-Plane Vibration Units by Yide Dong, Chunyan Yin, Guangbin Dou, Litao Sun

“…The unit exhibited a repeatability error below 1.13%, confirming the precision and reliability of the proposed fabrication strategy.…”
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Effect of Key Parameters on Ploughing Force Performance of Planing-Type Anti-Climbers by Zhuyao Li, Jiyou Fei, Dongxue Song, Hong He, Chang Liu, Chong Zhang

“…The results demonstrate that the model achieves ≤15% relative error compared with the simulation data and ≤5% deviation from the experimental measurements, confirming its engineering applicability. …”
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A hybrid reinforcement learning and knowledge graph framework for financial risk optimization in healthcare systems by Md Shahab Uddin, Ahsan Ahmed, Md Aktarujjaman, Mohammad Moniruzzaman, Mumtahina Ahmed, M. F. Mridha, Md. Jakir Hossen

“…Experimental results on real and synthetic healthcare datasets demonstrate that the proposed model outperforms traditional regressors, deep neural networks, and standalone RL agents across multiple evaluation metrics, including cost prediction error, diagnostic classification accuracy, cumulative reward, and average billing reduction. …”
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BDNet: Bengali Handwritten Numeral Digit Recognition based on Densely connected Convolutional Neural Networks by Abu Sufian, Anirudha Ghosh, Avijit Naskar, Farhana Sultana, Jaya Sil, M.M. Hafizur Rahman

“…So, the BDNet model gives 47.62% error reduction compared to previous state-of-the-art models. …”
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Hardware Implementation for Triaxial Contact-Force Estimation from Stress Tactile Sensor Arrays: An Efficient Design Approach by María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín, José A. Hidalgo-López

“…The calculation of force vectors on the proposed hardware required an average time of 58.68 ms, with an estimation error of 12.6% for normal forces and 7.7% for tangential forces on a 10 × 10 taxel tactile sensor array. …”
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