Distribution Network Security Situation Awareness Method Based on the Distribution Network Topology Layered Model by Yuhong Ouyang, Man Li, Wenqian Kang, Xiangbei Che, Ruixian Ye

“…The long- and short-term memory network is then used to predict the operation trend of the distribution network under normal operation and fault disturbance. …”
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Models for a Fast Computation of Internal Overvoltages in Medium-Frequency Transformers by Bastian Korthauer, Jurgen Biela

“…Simulation and measurement results show that the proposed models can compute internal overvoltages more than 500 times faster than FEA, while predicting the maximum overvoltage with an error of less than <inline-formula><tex-math notation="LaTeX">$7 \%$</tex-math></inline-formula>. …”
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Human-AI collaboration is not very collaborative yet: a taxonomy of interaction patterns in AI-assisted decision making from a systematic review by Catalina Gomez, Sue Min Cho, Shichang Ke, Chien-Ming Huang, Mathias Unberath

“…Determining what information AI should provide to aid humans is vital, a concept underscored by explainable AI's efforts to justify AI predictions. However, how the information is presented, e.g., the sequence of recommendations and solicitation of interpretations, is equally crucial as complex interactions may emerge between humans and AI. …”
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Winter arctic sea ice volume decline: uncertainties reduced using passive microwave-based sea ice thickness by Clement Soriot, Martin Vancoppenolle, Catherine Prigent, Carlos Jimenez, Frédéric Frappart

“…Abstract Arctic sea ice volume (SIV) is a key climate indicator and memory source in sea ice predictions and projections, yet suffering from large observational and model uncertainty. …”
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Design and Optimization of a Piezoelectric Stick-Slip Actuator with Distributed Compliance by Tingting Ye, Zhao Feng, Yangmin Li

“…Then, its dominant performances are predicted through finite element analysis, including the step size and the first natural frequency. …”
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Determination of disintegration time using formulation data for solid dosage oral formulations via advanced machine learning integrated optimizer models by Mohammed Ghazwani, Umme Hani

“…Data preprocessing involved Min-Max normalization, outlier detection via Elliptic Envelope, and feature selection using Conditional Mutual Information, with hyperparameters optimized through the Water Cycle Algorithm. Performance was assessed using R², RMSE, and MAE across train, validation, and test sets, with 95% confidence intervals confirming robust predictions. …”
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The Face and number plate recognition for car anti-theft by Quoc Bao Truong, Tan-Loc Tran, Thanh Tan-Kiet Nguyen, Huu Cuong Nguyen

“…The system automatically predicts whether the driver is valid with the registration number plate. …”
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In Silico identification and modelling of FDA-approved drugs targeting T-type calcium channels. by Pedro Fong, Susana Roman Garcia, Melanie I Stefan, David C Sterratt

“…We used the automated docking suite GOLD v5.5 with the genetic algorithm to simulate molecular docking and predict the protein-ligand binding modes, and the ChemPLP empirical scoring function to estimate the binding affinities of 2,115 FDA-approved drugs to the human Cav3.1 channel. …”
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Machine Learning Classification of 3D Intracellular Trafficking Using Custom and Imaris-Derived Motion Features by Oleg Kovtun

“…<b>Methods:</b> This study extends a previously established two-dimensional, machine learning-based diffusional fingerprinting approach into a three-dimensional framework to overcome this limitation. It presents an algorithm that predicts intracellular motion types based on a comprehensive feature set, including custom statistical descriptors and standard Imaris-derived trajectory features, which capture subtle variations in individual trajectories. …”
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YOLO Model-Based Eye Movement Detection During Closed-Eye State by Shigui Zhang, Junhui He, Yuanwen Zou

“…Our tracker achieved a mean distance error of 0.77 mm, with 90% of predicted eye position distances having an error of less than 1.67 mm, enabling real-time tracking at 30 frames per second. …”
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The Impact of Road Functions on Road Congestions Based on POI Clustering: An Empirical Analysis in Xi’an, China by Hui Zhu, Kaiqi Zhang, Changjun Wang, Lujin Jia, Siyu Song

“…Moreover, the POIs with flexible traffic flows increase road congestion, while the POIs with predicted traffic flows have no statistically significant correlation with road congestion. …”
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The Face and number plate recognition for car anti-theft by Quoc Bao Truong, Tan-Loc Tran, Thanh Tan-Kiet Nguyen, Huu Cuong Nguyen

“…The system automatically predicts whether the driver is valid with the registration number plate. …”
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A Novel Hybrid Model for Short-Term Forecasting in PV Power Generation by Yuan-Kang Wu, Chao-Rong Chen, Hasimah Abdul Rahman

“…Moreover, five types of forecasting modules were developed and utilized to predict the one-hour-ahead PV output. They include the ARIMA, SVM, ANN, ANFIS, and the combination models using GA algorithm. …”
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The Fault-Tolerant Control Strategy for the Steering System Failure of Four-Wheel Independent By-Wire Steering Electric Vehicles by Qianlong Han, Chengye Liu, Jingbo Zhao, Haimei Liu

“…The front wheel controller predicts the necessary steering angle in accordance with a linear model and addresses the requirements of the front wheels and additional torque. …”
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Cost-Effective, Time-Efficient Passenger Rail System for the Eastern United States by James Mathias, Dal Hyung Kim

“…The results of the program predicted a passenger starting at the farthest point of the system boards the train at 16:02 on average and arrives at a different point of the system at 07:57 on average the following day, assuming the train travels an average speed of 70 mph. …”
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Correlation analysis of m6A-modified regulators with immune microenvironment infiltrating cells in lung adenocarcinoma. by Wei Ye, Tianpeng Huang

“…The m6A score was constructed using the principal component analysis algorithm to quantify the m6A modification mode of a single tumor.…”
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Vegetation Classification and Survey: five years and looking ahead by Idoia Biurrun, Jürgen Dengler, Wolfgang Willner

“…For articles that performed a plot-based classification, we provide information on classification approach, plot size, importance value, taxonomic coverage, number of plots, and classification algorithm. We also analyze the bibliometric performance of VCS across the five years and predict a CiteScore of 3.6 and a Journal Impact Factor of 2.7 for 2024 (to be published in 2025). …”
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Optimization of Railway Equipment Maintenance Plan Based on Intelligent Patrol Inspection System by MA Yunlong

“…In order to overcome the shortcomings of poor accuracy, control absence and difficult implementation in the process of conventional railway equipment maintenance, this paper proposes an intelligent patrol inspection system solution, which integrates intelligent inspection and maintenance collectors, intelligent patrol inspection instruments and video monitors, and leverages microcontrollers, host computers, networked communication and other advanced technologies, as well as the developed equipment maintenance software,to realize the information-based and intellectualized patrol inspection on equipment.Thus this system functions to generate maintenance plans through algorithm calculation and software analysis, analyze the mechanisms and causes of the equipment failures identified in railway maintenance, and estimate and predict failure rates based on the failure mode modeling, and enable dynamic adjustment of patrol inspection plans. …”
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Machining effects and multi-objective optimization in Inconel 718 turning with unitary and hybrid nanofluids under MQL by Paresh Kulkarni, Satish Chinchanikar

“…The cutting parameters were optimized by combining the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) and genetic algorithm. The study reveals an average error of less than 10% between experimental and predicted responses from the proposed optimization model. …”
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Detecting Fraudulent Transaction in Banking Sector Using Rule-Based Model and Machine Learning by Cut Dinda Rizki Amirillah

“…The precision data of 99% indicates that the model’s predictions of anomalies are indeed anomalies, while a recall value of 1.0 shows that the model successfully identified all anomalies in the dataset. …”
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