Deep Anomaly Detection with Attention (DADA): A Novel Approach for Identifying Multipath Interference in Radar Signals by Kang Yan, Weidong Jin, Yingkun Huang, Zhenhua Li, Pucha Song, Ligang Huang

“…However, in practice, anomalous samples (multipath interference signals) may be scarce and highly imbalanced (i.e., mostly normal samples). To address this problem, we propose a deep anomaly detection with attention (DADA) for semisupervised detection of multipath radar signals. …”
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Studying and Analyzing Regional Inequalities (case study: cities of Ardabil province, Iran 2006 – 2011) by Bahram Imani, Roghayyeh Farshi, Reza Hashemi Masoomabad

“…Furthermore, according to the conducted analyses it is concluded that there is an imbalanced regional inequality on city scale in Ardabil province; there is a meaningful and positive relationship between the population of a city and the degree of its development; finally there is a meaningful and positive relationship between the distance from the provincial capital and the degree of its development.…”
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Gut Dysbiosis and Muscle Aging: Searching for Novel Targets against Sarcopenia by Anna Picca, Francesca Fanelli, Riccardo Calvani, Giuseppina Mulè, Vito Pesce, Alex Sisto, Cecilia Pantanelli, Roberto Bernabei, Francesco Landi, Emanuele Marzetti

“…“Inflammaging,” an age-related chronic inflammatory process, is a common trait of several conditions, including sarcopenia. Interestingly, imbalanced intestinal microbial community has been suggested to contribute to inflammaging. …”
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Optimization of Job Scheduling in the Cloud Computing Environment Using the Fuzzy Particle Swarm Optimization Algorithm by Shabnam Gharaeian, Khosrow Amirizadeh

“…Hence, total load on the cloud environment could become imbalanced, which reduces system’s efficiency. In this research, PSO and fuzzy logic is used for job scheduling. …”
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Unveiling diabetes onset: Optimized XGBoost with Bayesian optimization for enhanced prediction. by Muhammad Rizwan Khurshid, Sadaf Manzoor, Touseef Sadiq, Lal Hussain, Mohammed Shahbaz Khan, Ashit Kumar Dutta

“…While accurately predicting diabetes onset or progression remains challenging due to complex and imbalanced datasets, recent advancements in machine learning offer potential solutions. …”
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Arrhythmia Classification Techniques Using Deep Neural Network by Ali Haider Khan, Muzammil Hussain, Muhammad Kamran Malik

“…The primary concerns that affect the success of the developed arrhythmia detection systems are (i) manual features selection, (ii) techniques used for features extraction, and (iii) algorithm used for classification and the most important is the use of imbalanced data for classification. This study focuses on the recent trends in arrhythmia classification techniques, and through extensive simulations, the performance of the various arrhythmia classification and detection models has been evaluated. …”
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Schedule-based analysis of airborne transmission risk in public transportation systems by Jiali Zhou, Haris N. Koutsopoulos

“…Increasing frequency can mitigate risk, but cannot fully compensate for increases in infection rates. Imbalanced passenger distribution on different cars of a train increases the overall system-wide infection probability. …”
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Application of an improved LightGBM hybrid integration model combining gradient harmonization and Jacobian regularization for breast cancer diagnosis by Xiaoyan Sun

“…Developing the LightGBM hybrid integration model to ensure the accuracy and stability of model diagnosis on diverse and imbalanced datasets. The effectiveness of the proposed method has been comprehensively compared and verified through the dataset in the UCI machine learning repository, and the results show that the proposed method has achieved good diagnostic performance in all indicators. …”
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Normalization-Guided and Gradient-Weighted Unsupervised Domain Adaptation Network for Transfer Diagnosis of Rolling Bearing Faults Under Class Imbalance by Hao Luo, Xinyue Wang, Li Zhang

“…Experiments conducted across three imbalanced scenarios using the Case Western Reserve University (CWRU) and Paderborn University (PU) datasets demonstrate that NG-UDAN is effective in both single-source and mixed-source domain adaptation. …”
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StreetSurfaceVis: a dataset of crowdsourced street-level imagery annotated by road surface type and quality by Alexandra Kapp, Edith Hoffmann, Esther Weigmann, Helena Mihaljević

“…As the frequency distribution of road surface types and qualities is highly imbalanced, we propose a sampling strategy incorporating various external label prediction resources to ensure sufficient images per class while reducing manual annotation. …”
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Semantic-Based Classification of Long Texts on Higher Education in China by Chun Li, Yanying Fei

“…Besides, the effect of direct classification is rather poor because HE texts tend to be long and exist as an imbalanced dataset. To solve these problems, this paper improves the convolutional neural network (CNN) into the HE-CNN classification model for HE texts. …”
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Gut Microbiota Composition and Structure of the Ob/Ob and Db/Db Mice by Mingsheng Yang, Yixin Liu, Hengchang Xie, Zhengzheng Wen, Yunxia Zhang, Changjing Wu, Li Huang, Jie Wu, Chensheng Xie, Tao Wang, Weifeng Peng, Shangqi Liu, Long Chen, Xiaomeng Liu

“…The high abundance of Bacteroidetes and Firmicutes in microbiota composition and their imbalanced ratio in both model mice reflect the state of metabolic disorders of these mice. …”
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GLBR: A novel global load balancing routing scheme based on intelligent computing in partially disconnected wireless sensor networks by Zeyu Sun, Guisheng Liao, Cao Zeng, Lan Lan, Guozeng Zhao

“…Load balancing is of great significance to extend the longevity of wireless sensor networks, due to the inherent imbalanced energy overhead in such networks. However, existing solutions cannot balance the load distribution in partially disconnected wireless sensor networks. …”
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Loading and Skeletal Development and Maintenance by P. Bergmann, J. J. Body, S. Boonen, Y. Boutsen, J. P. Devogelaer, S. Goemaere, J. Kaufman, J. Y. Reginster, S. Rozenberg

“…Disuse results in osteocytes apoptosis and rapid imbalanced bone resorption, leading to severe osteoporosis. …”
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Diagnostic classification in toxicologic pathology using attention-guided weak supervision and whole slide image features: a pilot study in rat livers by Philip Zehnder, Jeffrey Feng, Trung Nguyen, Philip Shen, Ruth Sullivan, Reina N. Fuji, Fangyao Hu

“…We propose an innovative weakly supervised learning method that leverages minimal annotations, a state-of-the-art self-supervised vision transformer for embedding extraction, and a novel guided attention mechanism that is better suited for heavily imbalanced datasets typical in toxicologic pathology. …”
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Research on Wood Defects Feature Imbalance Optimization and Recognition by Xiao Wang

“…In this study, the problems are attributed to imbalanced feature distribution of wood defects which are rich in diversity. …”
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Model Optimization Analysis of Customer Churn Prediction Using Machine Learning Algorithms with Focus on Feature Reductions by Seyed Mohammad Sina Mirabdolbaghi, Babak Amiri

“…In light of the evaluation metrics, our model shows a significant improvement in handling imbalanced datasets in churn prediction. Finally, in this paper, interpretability and how the features affect the model’s output are presented by the SHAP method. …”
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Exploring mechanisms of insulin action and strategies to treat diabetes by Takayoshi Sasako

“…Aging is regulated by adipokines as well, and it should be considered that aging could be accelerated by ‘imbalanced adipokines’ in patients with a genetic background of progeria. …”
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Evaluation of Agronomic Management Practices on Farmers’ Fields under Rice-Wheat Cropping System in Northern India by Dinesh Kumar Singh, Purushottam Kumar, A. K. Bhardwaj

“…Balanced fertilization incurred additional cost of $38 over the imbalanced fertilization and provided additional returns of $180/ha. …”
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Relieving popularity bias in recommendation via debiasing representation enhancement by Junsan Zhang, Sini Wu, Te Wang, Fengmei Ding, Jie Zhu

“…Abstract The interaction data used for training recommender systems often exhibit a long-tail distribution. Such highly imbalanced data distribution results in an unfair learning process among items. …”
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