Electricity Theft Detection Using Rule-Based Machine Leaning (rML) Approach by Sheyda Bahrami, Erol Yumuk, Alper Kerem, Beytullah Topçu, Ahmetcan Kaya

“…Even though consumption-based models have been applied extensively to the detection of power theft, it can be difficult to reliably identify theft instances based only on patterns of usage. In this paper, a novel rule-based combined machine learning (rML) technique is developed for power theft detection to address the drawbacks of systems that rely just on consumption patterns. …”
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A continuous real-world dataset comprising wearable-based heart rate variability alongside sleep diaries by Aitolkyn Baigutanova, Sungkyu Park, Marios Constantinides, Sang Won Lee, Daniele Quercia, Meeyoung Cha

“…The dataset aims to benchmark in-the-wild HRV recordings, enable future analyses in the field, and support the development of predictive analytics that use sleep patterns and wearable data as health indicators.…”
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Computer Based Body Exposure in Adolescents With Anorexia Nervosa: A Study Protocol by Valeska Stonawski, Lena Sasse, Gunther Moll, Oliver Kratz, Stefanie Horndasch

“…Body dissatisfaction is a core feature of eating disorders (EDs) and plays an essential role in the development and maintenance of anorexia nervosa (AN). …”
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User authentication of industrial internet based on HHT transform of mouse behavior by Yigong ZHANG, Qian YI, Jian LI, Congbo LI, Aijun YIN, Shuping YI

“…The rapid development of the industrial internet had caused widespread concern about the network security, and the end-user authentication technology was considered a research hotspot.According to the characteristics of human-computer interaction in industrial internet, an experimental website was designed.24 users' mouse behavior data in an uncontrolled environment were collected within 2.5 years to conduct case studies.Hilbert-Huang transform (HHT) was used to extract frequency domain features of mouse behavior signals, combined with time domain features to form a time-frequency joint domain feature matrix of 163-dimensional to characterize user mouse behavior patterns.Bagged tree, support vector machine (SVM), Boost tree and K-nearest neighbor (KNN) were used to build a user authentication model， and the comparison result showed that the Bagged tree had the best internal detection effect in this case, with an average false acceptance rate (FAR) of 0.12% and an average false rejection rate (FRR) of 0.28%.In external detection, the FAR was 1.47%.Compared with the traditional mouse dynamics method, the frequency domain information of mouse behavior extracted by HHT can better realize the user authentication, and provide technical support the security of the industrial internet.…”
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Interpretability Study of Gradient Information in Individual Travel Prediction by Ziheng Su, Pengfei Zhang, Xiaohui Song, Yifan Li

“…Descending-order masking strategies exhibit the strongest impact, highlighting nonlinear interactions among features. Contribution maps visualize how gradients capture regular patterns and anomalies. …”
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Innovative Techniques for Enhancing the Reliability of Machine Learning Classifiers in Protein-Protein Interaction Hotspot Prediction by M. O. Otun

“…Key approaches include advanced feature engineering, integration of multi-omics data, ensemble learning methods, and the application of deep learning architectures. …”
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Defect Detection and Correction in OpenMP: A Static Analysis and Machine Learning-Based Solution by Norah A. Al-Johany, Fathy E. Eassa, Sanaa A. Sharaf, Eynas H. Balkhair, Sara M. Assiri

“…To enhance predictive accuracy, the tool incorporates machine learning classifiers—Naive Bayes (NB), Decision Tree (DT), Random Forest (RF), and Linear Support Vector Machine (LSVM)—trained on various feature combinations, including Abstract Features (AF), Halstead Features (HF), and Semantic Features (SF). …”
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SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

“…However, dense planting patterns and complex environments within greenhouses present challenges for accurately detecting growth stages. …”
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Improved YOLOv8-Based Method for the Carapace Keypoint Detection and Size Measurement of Chinese Mitten Crabs by Ke Chen, Zhuquan Chen, Changbo Wang, Zhifan Zhou, Maohua Xiao, Hong Zhu, Dongfang Li, Weimin Liu

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Deep learning identification of reward-related neural substrates of preadolescent irritability: A novel 3D CNN application for fMRI by Johanna C. Walker, Conner Swineford, Krupali R. Patel, Lea R. Dougherty, Jillian Lee Wiggins

“…Regression activation mapping (RAM) was employed to extract feature maps of brain regions most predictive of irritability severity from the model. …”
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Emotional Interactive Simulation System of English Speech Recognition in Virtual Context by Dan Li

“…Hidden Markov style has been widely used in English speech semantic recognition. The experiments of feature extraction and pattern recognition of speech samples prove that Hidden Markovian has higher recognition rate and better recognition effect in speech emotion recognition. …”
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A review of the FIVA project: Novel windows employing vacuum glazing products by Ulrich J. Pont, Peter Schober, Magdalena Wölzl, Matthias Schuss, Jakob Haberl

“…Four different designs were developed that not only integrated vacuum glass products, but also featured unusual opening patterns, the latest generation of electrically driven fitting products, and specific seals. …”
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Optimizing Personalized and Context-Aware Recommendations in Pervasive Computing Environments by A. C. Kaladevi, V. Vinoth Kumar, T. R. Mahesh, Suresh Guluwadi

“…Though various recommendation techniques exist, there is a need to develop a unique technique for capturing latent factors and patterns from sparse and high-dimensional data in pervasive environments, specifically for optimizing dynamic recommendations. …”
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Dementia Scale Score Classification Based on Daily Activities Using Multiple Sensors by Akira Minamisawa, Shogo Okada, Ken Inoue, Mami Noguchi

“…We analyzed the effects of different types of sensor data, such as time spent in an individual room according to human motion sensors, location in a facility, and sleep patterns, on dementia detection. We then developed a feature extraction method related to daily activity patterns based on a clustering algorithm and analyzed its effectiveness. …”
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Remote Sensing Identification of Major Crops and Trade-Off of Water and Land Utilization of Oasis in Altay Prefecture by Gaowei Yan, Luguang Jiang, Ye Liu

“…Within this fragile balance lies a critical opportunity: efficient water resource management could pave the way for sustainable development across the entire arid oasis regions. This study uses a decision tree model based on a feature threshold to map the spatial distribution of major crops in the Altay Prefecture oasis, assess their water requirements, and identify the coupling relationships between agricultural water and land resources. …”
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3D mesh segmentation of historic buildings for architectural surveys by Borja Javier Herráez, Eduardo Vendrell

“…The developed method has proved to be effective for feature detection and suitable for inclusion in architectural surveying applications.…”
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Self-Adaptive Deep Learning Framework for Non-Intrusive Load Monitoring: Addressing Aging Appliance Challenges With Transfer Learning and Pseudo Labeling by W. A. Yasodya, S. M. L. Arampola, M. S. K. Nisakya, V. Logeeshan, S. Kumarawadu, Chathura Wanigasekara

“…Unlike traditional NILM models, this approach incorporates a unique self-adaptive feature that enables the model to automatically adapt to changing power patterns resulting from aging appliances. …”
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Applications of gene pair methods in clinical research: advancing precision medicine by Changchun Wu, Xueqin Xie, Xin Yang, Mengze Du, Hao Lin, Jian Huang

“…To bridge methodological development with practical implementation, we establish a reproducible analytical pipeline incorporating feature selection, classifier construction, and model evaluation modules using real-world benchmark datasets from pulmonary tuberculosis studies. …”
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Classification of Toraja Wood Carving Motif Images Using Convolutional Neural Network (CNN) by Nurilmiyanti Wardhani, Billy Eden William Asrul, Antonius Riman Tampang, Sitti Zuhriyah, Abdul Latief Arda

“…By understanding the meaning of each Toraja carving, both tourists and the local community can gain knowledge about Toraja culture, thereby preserving and maintaining the culture amidst modern developments. Image processing approaches, particularly the development of Convolutional Neural Networks (CNN), offer a solution for extracting information from the diverse and intricate patterns of Toraja wood carvings. …”
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Sql injection detection using Naïve Bayes classifier: A probabilistic approach for web application security by Lu Zhexi

“…Feature extraction is later employed to identify patterns and characteristics commonly associated with SQL injection, such as certain SQL clauses and logical operators. …”
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