Large-area urban TomoSAR method with limited a priori knowledge and a complex deep learning model by Haoxuan Duan, Yuzhou Liu, Hong Zhang, Peifeng Ma, Zhongqi Shi, Zihuan Guo, Yixian Tang, Fan Wu, Chao Wang

“…To address the above issues, this study proposes a novel large-area urban TomoSAR method integrating limited a priori knowledge constraints with a complex-valued (CV) deep learning model. …”
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PFML: Self-Supervised Learning of Time-Series Data Without Representation Collapse by Einari Vaaras, Manu Airaksinen, Okko Rasanen

“…We demonstrate the effectiveness of PFML through complex, real-life classification tasks across three different data modalities: infant posture and movement classification from multi-sensor inertial measurement unit data, emotion recognition from speech data, and sleep stage classification from EEG data. …”
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A review on label cleaning techniques for learning with noisy labels by Jongmin Shin, Jonghyeon Won, Hyun-Suk Lee, Jang-Won Lee

“…In practice, however, labels can be corrupted by human error or mistakes, known as label noise, which degrades classification accuracy. To address this issue, recently, various works propose the algorithms to clean datasets with label noise. …”
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Approaches for handling imbalanced data used in machine learning in the healthcare field: A case study on Chagas disease database prediction. by André G Coimbra, Cleiane G Oliveira, Matheus P Libório, Hasheem Mannan, Laercio I Santos, Elisa Fusco, Marcos F S V D'Angelo

“…However, a significant issue remains unresolved in this field: the handling of imbalanced data. …”
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A Multi-Scale Feature Fusion Hybrid Convolution Attention Model for Birdsong Recognition by Lianglian Gu, Guangzhi Di, Danju Lv, Yan Zhang, Yueyun Yu, Wei Li, Ziqian Wang

“…Although feature extraction has demonstrated satisfactory performance in classification, single-scale feature extraction methods may not fully capture the complexity of birdsong, potentially leading to suboptimal classification outcomes. …”
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Motion Cognitive Decoding of Cross-Subject Motor Imagery Guided on Different Visual Stimulus Materials by Tian-jian Luo, Jing Li, Rui Li, Xiang Zhang, Shen-rui Wu, Hua Peng

“…To compare subject-specific variations of different visual stimuli, a novel cross-subject MI-EEG classification method was proposed for the three visual stimuli. …”
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Assessing the Role of EEG Biosignal Preprocessing to Enhance Multiscale Fuzzy Entropy in Alzheimer’s Disease Detection by Pasquale Arpaia, Maria Cacciapuoti, Andrea Cataldo, Sabatina Criscuolo, Egidio De Benedetto, Antonio Masciullo, Marisa Pesola, Raissa Schiavoni

“…Performance metrics, such as classification accuracy and Matthews Correlation Coefficient (MCC), are employed to assess the results. …”
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Klasifikasi Kualitas Biji Kedelai Menggunakan Transfer Learning Convolutional Neural Network Dan SMOTE by Amanda Prawita Ningrum, Sri Winarno, Vincentius Praskatama

“…However, low-quality seeds can reduce the quality of the processed products and increase production costs. To address this issue, a soybean seed quality classification system was developed using the method of Transfer Learning with CNN and SMOTE. …”
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Nursing diagnoses, interventions and outcomes in the bariatric surgery postoperative care by Rosa Aparecida Nogueira Moreira, Lívia Moreira Barros, Andrea Bezerra Rodrigues, Joselany Áfio Caetano

“… One aimed to identify the nursing diagnoses of the cardiovascular/pulmonary response class belonging to the activity/rest domain, according to the taxonomy II of NANDA-I in patients in the bariatric surgery immediate postoperative period and propose the interventions and nursing outcomes according to the Nursing Interventions Classification and the Nursing Outcomes Classification. …”
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Generating Synthetic Malware Samples Using Generative AI by Tiffany Bao, Kylie Trousil, Quang Duy Tran, Fabio Di Troia, Younghee Park

“…This enhancement ultimately leads to an overall malware classification performance of 96%, an 8% improvement. …”
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Automated Cervical Cancer Screening Using Single-Cell Segmentation and Deep Learning: Enhanced Performance with Liquid-Based Cytology by Mariangel Rodríguez, Claudio Córdova, Isabel Benjumeda, Sebastián San Martín

“…Cervical cancer (CC) remains a significant health issue, especially in low- and middle-income countries (LMICs). …”
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AVALENT AND MONOVALENT VERBS IN THE ALBANIAN LANGUAGE by Kadire Binaj Ejupi

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Revisiting the cognitive and behavioral aspects of loneliness: Insights from different measurement approaches. by Andrej Skoko, Noëmi Seewer, Marcus Mund, Tobias Krieger

“…Loneliness is increasingly recognized as a critical public health issue that profoundly affects psychological well-being and social functioning. …”
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Analyzing the Impact of Binaural Beats on Anxiety Levels by a New Method Based on Denoised Harmonic Subtraction and Transient Temporal Feature Extraction by Devika Rankhambe, Bharati Sanjay Ainapure, Bhargav Appasani, Avireni Srinivasulu, Nicu Bizon

“…Anxiety is a widespread mental health issue, and binaural beats have been explored as a potential non-invasive treatment. …”
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Opioid Crisis Detection in Social Media Discourse Using Deep Learning Approach by Muhammad Ahmad, Grigori Sidorov, Maaz Amjad, Iqra Ameer, Ildar Batyrshin

“…The findings show that our proposed methodology achieved the highest cross-validation score of 93% for binary classification and 91% for multi-class classification, demonstrating performance improvements of 9.41% and 10.98%, respectively, over the baseline model (XGB, 85% in binary class and 81% in multi-class).…”
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Explainable Model of Fusion Network With Enhanced Optimization Approach for Tuberculosis Diagnosis by C. R. Dhivyaa, K. Nithya, C. Sathiya Kumar, R. Sudhakar

“…Although advancements in healthcare have improved detection of various diseases, TB remains a global health issue, especially in developing regions. Efficient TB diagnostics can be achieved through the deep-learning-based image classification techniques. …”
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Computer Methods for the Antimicrobial Efficacy of Metal Nanoparticles Against MDR Microbes by Shanza Anzar, Ayesha Sohail, Lubna Sherin, Peter S. Kim

“…The current high mortality rate associated with infectious diseases is an alarming issue worldwide. The emergence of multidrug-resistant bacterial strains has led to the development of new ailments and the resurgence of old pathogenic infections. …”
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Ultrafast Time-Stretch Optical Coherence Tomography Using Reservoir Computing for Fourier-Free Signal Processing by Weiqing Liao, Tianxiang Luan, Yuanli Yue, Chao Wang

“…With an A-scan rate of 50 MHz, the classification model yielded 100% accuracy with a root mean square error (RMSE) of 0.2416. …”
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Developing Innovative Feature Extraction Techniques from the Emotion Recognition Field on Motor Imagery Using Brain–Computer Interface EEG Signals by Amr F. Mohamed, Vacius Jusas

“…To address the low accuracy of MI-BCI, which is a key issue faced by researchers, this study employs a new approach that has been proven to have the potential to enhance motor imagery classification accuracy. …”
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An illustration of multi-class roc analysis for predicting internet addiction among university students. by Nishat Tasnim Thity, Atikur Rahman, Adisha Dulmini, Mst Nilufar Yasmin, Rumana Rois

“…Internet addiction (IA) has become a serious public health issue worldwide. This multi-class classification study aimed to identify the potential predictors of IA by four severity levels among university students in Bangladesh. …”
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