Reconstruction of Temperature Distribution by Acoustic Tomography Based on Principal Component Analysis and Deep Neural Network by ZHANG Lifeng, LI Jing, WANG Zhi

“…In addition, the average relative error and root mean square error of reconstructed image are less than 0.36% and 0.85% respectively.…”
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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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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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Risk Assessment and Enhancement Suggestions for Automated Driving Systems through Examining Testing Collision and Disengagement Reports by Kuo-Wei Wu, Wen-Fang Wu, Chung-Chih Liao, Wei-Ann Lin

“…Therefore, appropriate systematic classification methods and principles need to be adopted. We follow an identification method similar to fault tree analysis (FTA) with the help of the driving reliability and error analysis method (DREAM 3.0) and the Haddon matrix to find the potential key accident factors from all disengagement data. …”
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Intelligence data acquisition based on embedded system in Chinese cuisine cooker (CCICR V1.0) by Jianbao Zhang, Deyi Wang, Shiping Bao, Xin Chang, Yi Liang

“…The weighing module demonstrates a maximum relative error of only 0.288%, while the attitude sensor experiment shows an attitude information error of just 0.22°C. …”
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Methodology for Determining the Effective Thickness of the Cemented Layer of Steel by S. G. Sandomirski, A. L. Val’ko, S. P. Rudenko

“…The technique provides a significant reduction in the influence of the structural banding of the metal and the inevitable error in measuring hardness on the result of determining the hef . …”
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On Data Selection and Regularization for Underdetermined Vibro-Acoustic Source Identification by Laixu Jiang, Jingqiao Liu, Xin Jiang, Yuezhao Pang

“…The simulation results show that selecting hologram points using the effective independence method, combined with regularization via compressed sensing, significantly reduces the reconstruction error and enhances the modal assurance criterion value. …”
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Assembly Quality Control Technologies in Forced Clamping and Compensation Processes for Large and Integrated Aeronautical Composite Structures by Feiyan Guo, Qiangwei Bao, Jialiang Liu, Xiliang Sha

“…As a result, in practical engineering, the forced method of applying a local clamping force is inevitably adopted to passively reduce and compensate for assembly errors. …”
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A Study on Crack Depth Measurement in Steel Structures Using Image-Based Intensity Differences by Ju-Yeong Jung, Hyuk-Jin Yoon, Hyun-Woo Cho

“…In addition, the validation of the intensity reduction equation obtained by the inductive method was verified, and it was confirmed that the crack depth can be predicted by the intensity value of the crack.…”
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Polynomial estimates of measurand parameters for data from bimodal mixtures of exponential distributions by S.V. Zabolotnii, V.Yu. Kucheruk, Z.L. Warsza, А.K. Khassenov

“… A non-conventional approach to finding estimates of the result of multiple measurements for a random error model in the form of bimodal mixtures of exponential distributions is proposed. …”
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Isotherms and thermodynamic properties of water adsorption in ‘Cumari-do-Pará’ pepper seeds by Karen C. Rodrigues, Hellismar W. da Silva, Isneider L. Silva, Samuel G. F. dos Santos, Daniel P. da Silva, Renato S. Rodovalho

“…The Chen-Clayton model is the one that best represents the water adsorption isotherms in ‘Cumari-do-Pará’ pepper seeds under the studied conditions, with 9.94% mean relative error, 0.40 mean estimated error and random distribution of residuals. …”
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An Algorithm for Simplifying 3D Building Models with Consideration for Detailed Features and Topological Structure by Zhenglin Li, Zhanjie Zhao, Wujun Gao, Li Jiao

“…Compared to the QEM algorithm and the other two comparison algorithms selected in this paper, the simplified model resulting from this algorithm exhibit a reduction in Hausdorff distance, mean error, and mean square error to varying degrees. …”
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Handheld motorized injection system with fiber-optic distance sensors and adaptive time-delay controller by Jintaek Im, Sukho Park, Cheol Song

“…Here, we report a handheld microinjector with two fiber-optic distance sensors and time-delay control (TDC) to mitigate nonlinear disturbances during the injection task. The conventional method exhibited a cosine error of approximately 77 μm at an angle of 45°, whereas our proposed needle reduced measurement errors to ∼6 μm. …”
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Assessing the Application Effects and Operating Conditions on Three Different Insulation Capacity Walls Using Internal Quantitative Infrared Thermography in China by Huanyu Li, Guohui Feng, Yi Pu, Han Wang

“…For uninsulated buildings, a temperature difference of 10 °C between indoor and outdoor environments is sufficient to meet testing requirements, with a testing error of only 2.28%. For conventionally insulated buildings, a temperature difference greater than 20 °C reduces the relative error to below 10%. …”
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Anthropometric Landmark Detection Network via Geodesic Heatmap on 3D Human Scan by Min Hee Cha, Jae Hyeon Park, Ji Sun Byun, Sangyeon Ahn, Gyoomin Lee, Seung Hyun Yoon, Sung In Cho

“…Moreover, we introduce a novel geodesic heatmap that effectively captures the point distribution of 3D shapes, even in the presence of variations in scanning pose. As a result, our method provides the lowest average detection error on the SHREC’14 dataset over the six anthropometric landmarks, demonstrating a maximum error reduction of 76.14%. …”
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A New Hybrid Model for Underwater Acoustic Signal Prediction by Guohui Li, Wanni Chang, Hong Yang

“…The experimental results show that the proposed new hybrid model can provide enhanced accuracy with the reduction of prediction error compared with other existing prediction methods.…”
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Motion estimation algorithm using 2 bit-depth pixel and fuzzy quantization by Chuan-ming SONG, Yan-wen GUO, Xiang-hai WANG, Dan LIU

“…To further predict the precision of the proposed algorithm, a bit resolution reduction error-motion vector precision model was built by exploiting the auto-correlation function. …”
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Prediction of Freezing Time During Hydrogen Fueling Using Machine Learning by Ji-Ah Choi, Ji-Seong Jang, Sang-Won Ji

“…This study presents a method for predicting nozzle surface temperature and the timing of frost formation during hydrogen refueling using machine learning. …”
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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

“…To address these issues, this paper proposes a collaborative strategy for high-quality shape control and surface strengthening in fixed microgrooves, an analysis of multi-dimensional fatigue regulation mechanisms, and a new method for multi-objective process optimization. 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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Autoencoder-Driven Fiducial Landmark Identification in 3D Brain MRI for Neuroimaging Alignment by G. Deepali, H. Anitha, B. P. Swathi, M. V. Suhas

“…In this work, we propose a deep learning-based framework using autoencoders to automatically detect fiducial markers in 3D brain MRI scans. The method integrates a structured preprocessing pipeline, including intensity normalization, spatial resampling, and noise reduction, to ensure data consistency. …”
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