Arbitrary Waveform Voltage Measuring Converter for Wideband AC Voltmeter by O. V. Dvornikov, U. N. Bakhur, A. G. Bakhir, U. M. Lazouski, V. A. Tchekhovski

“…The aim of the paper was to develop a measuring AC RMS-DC converter of arbitrary shape voltage in which special attention is paid to modernization of the TEC and reduction of the AC RMS-DC converter error using corection of the frequency response of the input amplifier and introduction automatic calibration of the output voltage. …”
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Dynamic order selection analysis in adaptive polynomial Kalman filtering: implementation and integration of sensor data and hybrid image processing for bio-inspired needle systems by Dileep Sivaraman, Branesh M. Pillai, Cholatip Wiratkapun, Jackrit Suthakorn, Songpol Ongwattanakul

“…Initial simulations showed that the standard APKF significantly outperformed traditional Kalman Filtering (KF), achieving an average reduction of 46.9% in Root Mean Square Error (RMSE), 57.8% in Mean Absolute Error (MAE), and 64.5% in Median Absolute Deviation (MAD). …”
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Research on Denoising of Bridge Dynamic Load Signal Based on Hippopotamus Optimization Algorithm–Variational Mode Decomposition–Singular Spectrum Analysis Method by Zhengqiang Zhong, Zhen Li, Jinlong Wang, Cong Tang, Yu Liu, Kaijun Guo

“…The simulation results show that compared with other methods, the root mean square error (RMSE), signal-to-noise ratio (SNR), mean square error (MSE), and mean absolute error (MAE) of the denoised signals achieve on average 16.22% reduction, 2.51% improvement, 62.02% diminution, and 43.74% decrease, respectively, across varying noise levels. …”
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Evaluating Predictive Accuracy of Regression Models with First-Order Autoregressive Disturbances: A Comparative Approach Using Artificial Neural Networks and Classical Estimators by Rauf I. Rauf, Masad A. Alrasheedi, Rasheedah Sadiq, Abdulrahman M. A. Aldawsari

“…The analysis is structured into three phases: the first phase examines predictive accuracy across methods using Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE); the second phase evaluates the efficiency of parameter estimation based on standard errors across methods; and the final phase visually assesses the closeness of predicted values to actual values through scatter plots. …”
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Algorithmic Support of Adaptive Automatic Control Systems with Data Compression by V. V. Alekseev, E. M. Antonyuk, I. E. Varshavskiy

“…Automatic criteria-based selection and reduction of measurement information continuously supplied by multi-parameter sources characterizing the objects under study require algorithms ensuring reconfiguration of automatic control systems during operation. …”
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Performance of M-QAM MIMO PNC Based on MRC and ZR Techniques by Alaa A. Yassin, Ebtihal H. G. Yousif, Rashid A. Saeed, Hashim Elshafie, Abdullah Alenizi, Hesham Alhumyani

“…The obtained result demonstrates the reduction of symbol error rate in addition to enhancement of the normalized throughput, capacity, and sum rate when increasing the number of antenna at the relay node.…”
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Machine Learning Using Approximate Computing by Padmanabhan Balasubramanian, Syed Mohammed Mosayeeb Al Hady Zaheen, Douglas L. Maskell

“…Approximate computation has emerged as a promising alternative to accurate computation, particularly for applications that can tolerate some degree of error without significant degradation of the output quality. …”
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Sustainable energy: Advancing wind power forecasting with grey wolf optimization and GRU models by Zainab Al-Ibraheemi, Samaher Al-Janabi

“…The proposed approach addresses both larger datasets and the impact of noise samples on prediction errors. Additionally, an MLDDR model was introduced to predict DC power generated from wind datasets, encompassing five stages: Data Preparation, Feature Selection, Data Compression, GRU-Based Predictions, and Rate of Reduction. …”
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Nanosecond Laser Etching of Surface Drag-Reducing Microgrooves: Advances, Challenges, and Future Directions by Xulin Wang, Zhenyuan Jia, Jianwei Ma, Wei Liu

“…The aim is to control the geometric accuracy error of the prepared surface microgrooves within 5% and to enhance the fatigue life of the substrate by more than 20%, breaking through the technical bottleneck of separating “drag reduction design” from “fatigue resistance manufacturing”, and providing theoretical support for the integrated manufacturing of “drag reduction-fatigue resistance” in aircraft skins.…”
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Development of mean wind retrieval methodology for the Generalized Velocity Track Display by Tsung-Jung Lee, Shao-Chin Huang, Wen-Chau Lee, Ben Jong-Dao Jou, Chih-Chien Tsai, Yi-Chiang Yu, Yu-Cheng Kao, Ting-Yu Cha

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The Treatment of Hospital Wasterwater Electrocoagulation Using Iron Electrodes: Analysis by Response Surface Methodology by Darmadi M. Yusuf, Mirna Rahmah Lubis, Adisalamun Adisalamun

“…The reduction percentage is TSS 72.45%.…”
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Channel estimation method of massive MIMO-OFDM system based on adaptive compressed sensing by Yiyang HU, Lina QI

“…Massive multiple-input multiple-output (MIMO) is a solution for efficiently providing connection services for a variety of machine equipment in the Internet of things (IoT), and efficient connection services require accurate channel estimation.Aimed at the problems of high pilot overhead and poor performance of normalized mean square error (NMSE) estimation in downlink channel estimation of massive MIMO systems, based on the compressed sensing (CS) theory, the common sparsity of the channel space domain was combined while using the feature of lower sparsity of adjacent time slot differential channel impulse response (CIR), which leaded to a significant reduction in pilot overhead.In the reconstruction algorithm, a two-stage differential estimation algorithm, which divided the channel estimation in consecutive time slots with time correlation into two stages, was proposed and the idea of adaptive compressed sensing was combined to achieve fast and accurate CIR estimate.The simulation results show that the proposed two-stage differential channel estimation algorithm not only has a significant improvement in the estimated NMSE performance and data transmission rate compared to the existing CS-based multiple measurement vector (MMV) algorithm, but also show a certain reduction in runtime complexity.…”
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Determination of the Shortest Hamiltonian Paths in an Arbitrary Graph of Distributed Databases by E. G. Andrianova, V. K. Raev, D. I. Filgus

“…A method has been developed for finding the shortest Hamiltonian path in an arbitrary graph based on the rank approach, which provides high efficiency and a significant reduction in the error in solving the problem of organizing the process of managing multiple transactions and queries when they are implemented in network databases. …”
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Framework for Integrating Requirements Engineering and DevOps Practices in Robotic Process Automation with a Focus on Optimizing Human–Computer Interaction by Leonel Patrício, Leonilde Varela, Zilda Silveira

“…Key results include an 83% reduction in processing time, an 81.25% decrease in error rates, and an 80% reduction in manual tasks, alongside improved compliance and scalability. …”
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Forgery Detection in Dynamic Signature Verification by Entailing Principal Component Analysis by Shohel Sayeed, S. Andrews, Rosli Besar, Loo Chu Kiong

“…Calculation of the sum of mean squares of Euclidean distance has been used to project the advantage of our proposed method. 3.1% and 7.5% of equal error rates for 14 and 5 channels further reiterate the effectiveness of this technique.…”
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Numerical study of a copper oxide-based thermochemical heat storage system by Zhen Cao, Bas Joris de Leeuw, Tianchao Xie, Abhishek K. Singh

“…Similarly, increasing the furnace temperature during the reduction process (reduction temperature) also increases the output temperature and accelerates the reaction. …”
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Nonnegative Matrix Factorization Based Adaptive Noise Sensing over Wireless Sensor Networks by Kwang Myung Jeon, Hong Kook Kim, Sung Joo Lee, Yun Keun Lee

“…In addition, the proposed method is applied to an automatic speech recognition (ASR) system, which is a typical speech-based application, and then the average word error rate (WER) of the ASR is compared with that employing either a Wiener filter, or a conventional NMF-based noise reduction method using only a priori noise basis matrix.…”
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Denoising of acoustic emission signals from rock failure processes through ICEEMDAN combined with multiple criteria and wavelet transform by Tao Wang, Weiwei Ye, Liyuan Liu, Zhihui Zhao, Wei Huang

“…Compared to traditional wavelet denoising methods, the proposed method exhibits higher signal-to-noise ratio (SNR) improvement, as well as varying degrees of reduction in mean squared error (MSE) and total harmonic distortion (THD). …”
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Vulnerability Testing and Analysis on Websites and Web-Based Applications in the XYZ Faculty Environment Using Acunetix Vulnerability by Mifthahul Rahmi, Yuhandri Yunus, Sumijan Sumijan

“…Following a recapitulation process, several web alerts were identified for optimization, including Cross-Site Scripting (XSS), Blind SQL Injection, Application error message, HTML form without CSRF protection, Development configuration file, Directory listing, Error message on page, and User credentials sent in clear text. …”
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Enhanced SOC estimation method for lithium-ion batteries using Bayesian-optimized TCN–LSTM neural networks by Taotao Hu, Xiting Zhu, Maokai Tian

“…Experimental results demonstrate the effectiveness of the proposed method, achieving a coefficient of determination (R2) of 0.996, a mean absolute error of 0.146%, and a root mean square error of 0.207%. …”
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