Research on data-driven and correlation-based electric energy error analysis method by RONG Xueqin, DING Yingying, LIU Yong

“…A supplementary strategy is proposed to use operational errors as a reliable source of load point errors in traditional methods, in response to the problem of insufficient detection of load points in electric energy meters and the inability of some load point errors to fully represent the full range measurement characteristics caused by the limited load point calibration method. …”
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A Novel Energy Control Digital Twin System with a Resource-Aware Optimal Forecasting Model Selection Scheme by Jin-Woo Kwon, Anwar Rubab, Won-Tae Kim

“…The system dynamically selects optimal forecasting models by integrating statistical features of the input time series with available resources. …”
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Using Partial Differential Equation Face Recognition Model to Evaluate Students’ Attention in a College Chinese Classroom by Xia Miao, Ziyao Yu, Ming Liu

“…The partial differential equation learning model is applied to another high-level visual-processing problem: face recognition. A novel feature selection method based on partial differential equation learning model is proposed. …”
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Incidence of acute intestinal infections in Saint Petersburg during COVID-19 pandemic by T. V. Potapova, K. D. Ermolenko, A. V. Kholin, A. V. Stalevskaya, S. A. Gordeeva, I. V. Razdyakonova

“…The article reflects current trends in the frequency of detection of acute intestinal infections of viral and bacterial etiology, in particular, the growing prevalence of norovirus infection is shown. …”
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Character generation and visual quality enhancement in animated films using deep learning by Weiran Cao, Zhongbin Huang

“…Meanwhile, to address the image distortion problem caused by severe pose changes, a repainting image repair module is proposed. …”
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Incremental learning with SVM for multimodal classification of prostatic adenocarcinoma. by José Fernando García Molina, Lei Zheng, Metin Sertdemir, Dietmar J Dinter, Stefan Schönberg, Matthias Rädle

“…Robust detection of prostatic cancer is a challenge due to the multitude of variants and their representation in MR images. …”
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Beyond binary: multi-class skin lesion classification with AlexNet transfer learning-towards enhanced dermatological diagnosis by Abida Noaman, Reyaz Ahmad, Muhammad Farhan Khan, Abdul Salam Mohammed, Muhammad Farooq, Khan Muhammad Adnan

“…Abstract Problem Skin lesions are the major indicator for diagnosing different skin diseases, which are caused by the abnormal growth of skin cells. …”
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Climate change, extreme heat, and outdoor thermal comfort in urban areas: Case of İzmir, Turkey by Sevim Pelin Öztürk, Pelin Özden, Müge Tikik

“…Recently, environmental problems, urban population growth, the expansion of urban areas, and climate-insensitive planning practices have significantly increased the effects of the climate crisis in urban areas. …”
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Seismic phase recognition model with low SNR based on U-net by Jianxian Cai, Zhongjie Sun, Mengying Zhang, Fenfen Yan, Li Wang, Ling Li

“…Aiming at the problem of low recognition accuracy and high missed detection rate of seismic phase recognition of low signal-to-noise ratio seismic signals, a new seismic phase recognition model UBAN (U-net-Bidirectional Gated Recurrent Unit-Attention Network) is designed based on U-net neural network framework, combined with Bi-GRU bidirectional gated recurrent unit and Attention attention mechanism. …”
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Enhancing Digital Twin Fidelity Through Low-Discrepancy Sequence and Hilbert Curve-Driven Point Cloud Down-Sampling by Yuening Ma, Liang Guo, Min Li

“…This paper addresses the critical challenge of point cloud down-sampling for digital twin creation, where reducing data volume while preserving geometric fidelity remains an ongoing research problem. We propose a novel down-sampling approach that combines Low-Discrepancy Sequences (LDS) with Hilbert curve ordering to create a method that preserves both global distribution characteristics and local geometric features. …”
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Spatiotemporal Flood Hazard Classification in Bangkok Using Graph Convolutional Network and Temporal Fusion Transformer by Pakpoom Chaimook, Nirattaya Khamsemanan, Cholwich Nattee, Alice Sharp

“…Traditional flood prediction models often fail to capture spatial correlations across districts and the temporal patterns within different types of features. To address this problem, this study proposes a hybrid deep learning framework combining Graph Convolution Network (GCN) and the Temporal Fusion Transformer (TFT) for predicting flood hazard levels in 50 Bangkok districts. …”
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Development of a portable low-cost PC-independent accelerometer for multiple purposes by Erick Montoya

“…This is a major difficulty when studying the dynamic response of buildings to earthquakes since usually large arrays of seismographs are needed to carry out such a study, making the affordability of this type of research in developing countries (regions where old or porrly-constructed buildings are more common) virtually impossible. In view of this problem, in this paper the prototype (named MiSismo) for an inexpensive PC-independent seismograph is presented, along with its most outstanding features (such as backup power system, sample rate selection, earthquake detection and email service), proposed applications and drawbacks. …”
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STABILITY OF DEVELOPMENT OF FUTURE PROFESSIONALS’ EMOTIONAL INTELLIGENCE by A. M. Beloborodov, E. E. Symaniuk

“…Gilford’s Social Intelligence Test and also the authors’ set of toolkits (tasks for recognition of facial expression and detection of the active dictionary of emotions) were applied.Results and scientific novelty. …”
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Understanding the flowering process of litchi through machine learning predictive models by SU Zuanxian, NING Zhenchen, WANG Qing, CHEN Houbin

“…The low or unstable yield caused by unstable flowering is a prominent problem in litchi production, and the flowering time affects not only the maturity of fruit, but also the flowering rate and yield of litchi. …”
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Clinical and Epidemiological Manifestations of Ixodic Tick-Borne Borreliosis Foci in the Tomsk region by O. V. Voronkova, E. N. Ilyinskikh, A. A. Rudikov, T. N. Poltoratskaya, I. E. Esimova, L. V. Lukashova, M. R. Karpova

“…In the Tomsk region for many years, the average long-term incidence of Ixodic tick-borne borreliosis exceeds the Russian one by more than 3 times. Aim. Identify features the features of the clinical and epidemiological manifestations of the Ixodic tick borne borreliosis foci in the Tomsk region; to identify priority areas for carrying out problem-oriented research in the field of ecology, epidemiology and the clinic of borreliosis infection in the Tomsk region. …”
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Multiclass Incremental Learning for Fault Diagnosis in Induction Motors Using Fine-Tuning with a Memory of Exemplars and Nearest Centroid Classifier by Magdiel Jiménez-Guarneros, Jonas Grande-Barreto, Jose de Jesus Rangel-Magdaleno

“…This article presents a multiclass incremental learning (MCIL) framework based on 1D convolutional neural network (CNN) for fault detection in induction motors. The presented framework tackles the forgetting problem by storing a representative exemplar set from past data (known faults) in memory. …”
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Multi-target personnel tracking algorithm for coal mine based on improved YOLOv7 and ByteTrack by Pengcheng QU, Jingzhao LI, Zechao LIU

“…In order to solve the problems of low accuracy and poor real-time performance of existing target tracking algorithms in the complex environment of coal mines, a YOLO-FasterNet+ByteTrack coal mine personnel tracking algorithm was proposed based on the Tracking by Detection (TBD) paradigm. …”
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Analysis of Internet Marketing Forecast Model Based on Parallel K-Means Algorithm by Xiaolei Chen, Sikun Ge

“…At the same time, to solve the problem of insufficient data sets of Internet marketing nodes, the Internet data sets are artificially generated and used for detector training. …”
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A Robust Approach to Vision-Based Terrain-Aided Localization by Dan Navon, Ehud Rivlin, Hector Rotstein

“…The SFM problem can be solved using existing techniques such as feature detection, matching, and triangulation wrapped with a bundle adjustment algorithm. …”
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Comparative characteristics of pneumonia caused by <i>Mycoplasma pneumoniae</i> in children by S. L. Bevza, O. V. Molochkova, O. B. Kovalev, O. V. Shamsheva, A. A. Sakharova, A. A. Korsunsky, M. V. Parshina, K. G. Burkova, E. A. Labuzova, N. V. Sokolova

“…The urgency of the problem of community-acquired pneumonia in children is due to the high incidence rate. …”
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