Advanced Diagnostic Techniques for Fault Detection and Maintenance in Diesel Generators: Integration of AI and Multimodal Sensing by Mahdi Goodarzi, Abdollah Abbasi

“…Comparative evaluations are presented through quantitative tables and visual figures that benchmark AI model performance based on accuracy and error metrics. Furthermore, the review addresses current limitations in data integration, sensor reliability, and standardization, proposing practical solutions and future research directions. …”
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Strain energy density criterion as failure assessment for quasi-static uni-axial tensile load by Andrea Kusch, Simone Salamina, Daniele Crivelli, Filippo Berto

“…Failure predictions, based on the critical value of the strain energy density in a well-defined volume surrounding the notch tip, show very good agreement (error minus 15%) with experimental data.…”
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Evaluation of Two Stage Modified Ridge Estimator and Its Performance by Selma Toker, Nimet Özbay

“…A real life data analysis is investigatedto prove the theoretical results in practice. …”
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Low-hit frequency-hopping communication systems for power Internet of things random access by Shu DU, Mei MA, Bo ZHAO, Qi ZENG, Xing LIU

“…The communication network is an essential component of the data acquisition and information transmission in power Internet of things (IoT).To meet the development requirements of multiple power service in the future, the wireless communication technique with flexible-access and high scalability is one of the development directions for power IoT.Due to the features of large-scale access, random access time, high security and reliability for information transmission of power IoT, a frequency-hopping (FH) technique with low-hit rate for random access was proposed.The construction algorithm of such FH pattern was based upon the combination and shift operation of conventional FH sequences.By the theoretical arithmetic and numerical simulation, the properties of the proposed FH pattern and the error-rate of the FH-based power IoT were evaluated.The analysis reveals that the new class of FH sequences and the system can meet the requirements of large-scale access and highly reliable communication for the power IoT, which has good application prospects.…”
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The effective seismic attributes in porosity prediction for different rock types: Some implications from four case studies by Abdulaziz M. Abdulaziz

“…Verification and testing error analysis is adopted for evaluating the prediction performance. …”
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Optimization of Online Moisture Prediction Model for Paddy in Low-Temperature Circulating Heat Pump Drying System with Artificial Neural Network by Yi Zuo, Abdulaziz Nuhu Jibril, Jianchun Yan, Yu Xia, Ruiqiang Liu, Kunjie Chen

“…While existing studies on drying models often rely on laboratory-scale experiments with limited data, real-time and high-frequency data collection under industrial conditions remains underexplored. …”
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NEURAL NETWORK FORECASTING OF ENERGY CONSUMPTION OF A METALLURGICAL ENTERPRISE by Anna Bakurova, Olesia Yuskiv, Dima Shyrokorad, Anton Riabenko, Elina Tereschenko

“…The following tasks have been solved: analysis of the time series of power consumption; building a model with the help of which data on electricity consumption for a historical period is processed; building the most accurate forecast of the actual amount of electricity for the day ahead; assessment of the forecast quality. …”
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Fault detection in beam structure using adaptive immune based approach by Sasmita Sahu, Shakti P. Jena

“…Later one such method has been developed in the concepts of adaptive immune based technique (Adaptive Clonal Section Algorithm-ACSA) which is the combination of an artificial immune (Clonal Selection Algorithm) and Regression Analysis (RA). The use of regression analysis makes the proposed method more adaptive and the residual error in the collection of vibration data is reduced. …”
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STRESS AND STRAIN STATE OF REPAIRING SECTION OF PIPELINE by V. V. Nikolaev

“…Comparison results shows that the calculation error is not more than 3 %.Analysis of stress-strain state change of pipeline’s section was carried out with development  of  this  model,  which  indicates  the  enlargement  of  span  deflection  in  comparison with problem’s solution in elastic approach. …”
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Interpretable Machine Learning for High-Accuracy Reservoir Temperature Prediction in Geothermal Energy Systems by Mohammadali Ahmadi

“…Accurate prediction of reservoir temperature is critical for optimizing geothermal energy systems, yet the complexity of geothermal data poses significant challenges for traditional modeling approaches. …”
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THE IMPACT OF THE PRESIDENTIAL ELECTION ON IDX COMPOSITE PREDICTIONS USING LONG SHORT TERM MEMORY by Ashilla Maula Hudzaifa, Valerie Vincent Yang, Defi Yusti Faidah

“…IDX Composite closing price forecasting was conducted using the bidirectional LSTM model to anticipate the impact. The analysis results show that this model can predict the weekly closing price of the IDX Composite with an error of 1.04%, with estimated stock price fluctuations in the next 8 weeks in the range of 6619.755 to 6812.722…”
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DETECTION OF FAULT LOCATION ON THE POWER LINES 6–35 kV WITH UNILATERAL FEED by F. A. Romaniuk, M. A. Shevaldin

“…The results of operational control of the short-circuit current for the faulted phases are the only initial data needed for the fault location algorithm. Analysis of the impact of the type of short circuit, transition resistance at the damaged point, errors of current transformers, load of the line, power and resistance of supply system, calculation errors of short-circuit currents at the beginning and at the end of the line on the performance of this algorithm is also performed. …”
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Determination of Cefoperazone Sodium in Presence of Related Impurities by Improved Classical Least Squares Chemometric Methods: A Comparative Study by Ibrahim A. Naguib, Hany W. Darwish

“…The comparison is expressed through analysis of a case study dataset of UV spectral data of Cefoperazone Sodium (CEF) and its two related impurities: in pure powder form and in pharmaceutical dosage form. …”
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Improving Georeferencing Accuracy in Drone Imagery: Combining Drone Camera Angles with High and Variable Fields of View by Vishal Nagpal, Manoj Devare

“…It offers a scalable, accurate, and less labour-intensive substitute for spatial positioning by using FOV parameters and real-time telemetry data. Improved georeferencing accuracy ensures precise spatial data integration, and supports accurate image-frame alignment. …”
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Value sets and the problem of redundancy in value set repositories. by Sigfried Gold, Harold P Lehmann, Lisa M Schilling, Wayne G Lutters

“…The results emerge from an analysis of relevant literature, reflective practice, and the field research data.…”
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Addressing Temporal RSSI Fluctuation in Passive Wi-Fi-Based Outdoor Localization by Fanchen Bao, Stepan Mazokha, Jason O. Hallstrom

“…Within this model, we compare the performance of four data transformation methods that further dampen the effect of RSSI fluctuation—basic standardization (STD), Kernel Principal Component Analysis (KPCA), Transfer Component Analysis (TCA), and Semi-Supervised TCA (SSTCA). …”
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Quantum proof biometric authentication framework using binary lattices and homomorphic encryption for secure cancelable templates by S. Aarthi, K. Geetha, N. Sasikaladevi

“…Three benchmark data sets, ORL, CASIA-Face V5 and deep funneled LFW, were used for security and performance evaluations, resulting in Error Equal Rates of 0.000714, 0.000438, and 0.006330, respectively. …”
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Machine learning and SHAP value interpretation for predicting cardiovascular disease risk in patients with diabetes using dietary antioxidants by Xinyu Zhang, Sen Lin, Qingling Zeng, Lisheng Peng, Chaoguang Yan

“…Data preprocessing involved collinearity removal, standardization, and class imbalance correction. …”
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Combination of machine learning and Raman spectroscopy for prediction of drug release in targeted drug delivery formulations by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…The key innovation lies in integrating these non-linear regression models with robust data preprocessing steps, including dimensionality reduction via Principal Component Analysis (PCA), categorical feature encoding through Leave-One-Out (LOO), and outlier detection using Isolation Forest. …”
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Effect of Board Accountability on Financial Performance of Selected SACCOs in Kiruhura District, Uganda. by Kyabarongo, Benon, Agaba, Moses, Byamukama, Eliab Mpora, Sunday, Arthur, Sekiwu, Denis

“…The obtained data for analysis was divided into two phases. First, descriptive statistics on the respondents and the preliminary data analysis were performed using SPSS version 20.0. …”
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