Data augmentation of time-series data in human movement biomechanics: A scoping review. by Christina Halmich, Lucas Höschler, Christoph Schranz, Christian Borgelt

“…This understanding is crucial for assessing the impact of the augmented data set on downstream models and evaluating the quality of the data augmentation process.…”
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A survey on key technologies of privacy protection for machine learning by Zishan LIU, Qiang CHENG, Bo LV

“…With the development of information and communication technology,large-scale data collection has vastly promoted the application of machine learning in various fields.However,the data involved in machine learning often contains a lot of personal private information,which makes privacy protection face new risks and challenges,and has attracted more and more attention.The current progress of the related laws,regulations and standards to the personal privacy protection and data safety in machine learning were summarized.The existing work on privacy protection for machine learning was presented in detail.Privacy protection algorithms usually have influence on the data quality,model performance and communication cost.Thus,the performance of the privacy protection algorithms should be comprehensively evaluated in multiple dimensions.The performance evaluation metrics for the privacy protection algorithms for machine learning were presented,given with the conclusion that the privacy preservation on machine learning needs to balance the data quality,model convergence rate and communication cost.…”
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Study of methods for extracting contours of objects on raster images of amber samples by Yu.O. Podchashynskyi, A.V. Ryzhuk

“…The use of these operators in TVS provides the most complete and reliable information for building a three-dimensional model, classifying and evaluating the quality of amber samples. The open source computer vision library was taken as the algorithmic and software basis of the conducted research. …”
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Literature review for the topic of automation of scheduling classes and exams in higher education institutions by Wadhah M Al-Gabri

“…Schedule is considered as part of the educational process support system, and, in its turn, has features of the system combining such objects as students, teachers, disciplines, and classrooms. The application of the system analysis methods allows allocating essential features of the implemented systems of timetabling, classifying and evaluating them. …”
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Adaptation of mathematical educational content in e-learning resources by Yuliya V. Vainshtein, Victoria A. Shershneva, Roman V. Esin, Tatyana V. Zykova

“…An upcoming trend in improvement the quality of studying mathematical disciplines is the development and application of adaptive electronic educational resources. …”
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Deep Learning Methods and UAV Technologies for Crop Disease Detection by S. G. Mudarisov, I. R. Miftakhov

“…The findings demonstrate that deep learning algorithms offer more accurate and earlier detection of diseases, highlighting their potential for application in plant growing. …”
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A Novel Fuzzing Method for Zigbee Based on Finite State Machine by Baojiang Cui, Shurui Liang, Shilei Chen, Bing Zhao, Xiaobing Liang

“…Further, the quality of cases of FSM-fuzzing is higher than the previous algorithms. …”
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Novel validity indices for dynamic clustering and an Improved Dynamic Fuzzy C-Means by Ramiro Saltos, Ignacio Carvajal, Fernando Crespo, Richard Weber

“…However, unlike static clustering, where a plethora of validation indices exist to assess the solution’s quality, evaluating the effectiveness of dynamic clustering algorithms remains a challenge. …”
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Improvement of Methodological Tools for Business Analysis of the Effective Company’s Performance by N. S . Plaskova

“…The practical application of the proposed adjusted procedures for calculating indicators contributes to getting a reliable and aimed assessment of the quality of the management system of organizations in the real sector of the economy. …”
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Calibration of Integrated Low-Cost Environmental Sensors for Urban Air Temperature Based on Machine Learning by Fang Nan, Chao Zeng, Huanfeng Shen, Liupeng Lin

“…Multiple linear regression (MLR) and light gradient boosting machine (LightGBM) algorithms were employed for calibration, with leave-one-out cross-validation (LOOCV) being used for model evaluation. …”
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Multimodal Classification Technique for Fall Detection of Alzheimer’s Patients by Integration of a Novel Piezoelectric Crystal Accelerometer and Aluminum Gyroscope with Vision Data... by V. Mohan Gowda, Megha P. Arakeri, Vasireddy Raghu Ram Prasad

“…Smart expert systems line up with various applications to enhance the quality of lifestyle of human beings, such as major applications for smart health monitoring systems. …”
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Artificial Intelligence for Objective Assessment of Acrobatic Movements: Applying Machine Learning for Identifying Tumbling Elements in Cheer Sports by Sophia Wesely, Ella Hofer, Robin Curth, Shyam Paryani, Nicole Mills, Olaf Ueberschär, Julia Westermayr

“…Using triaxial accelerations and rotational speeds, various ML algorithms were employed to classify and evaluate the execution of tumbling manoeuvres. …”
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Unsupervised Machine Learning Approaches for Test Suite Reduction by Anila Sebastian, Hira Naseem, Cagatay Catal

“…In this research, we conducted a Systematic Mapping Study (SMS), examining the types of unsupervised algorithms implemented in developed models and thoroughly exploring the evaluation metrics employed. …”
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Artificial intelligence-based automated breast ultrasound radiomics for breast tumor diagnosis and treatment: a narrative review by Yinglin Guo, Ning Li, Chonghui Song, Juan Yang, Yinglan Quan, Hongjiang Zhang

“…Radiomics, an emerging field, focuses on extracting high-dimensional quantitative features from medical imaging data and utilizing them to construct predictive models for disease diagnosis, prognosis, and treatment evaluation. In recent years, the integration of artificial intelligence (AI) with radiomics has significantly enhanced the process of analyzing and extracting meaningful features from large and complex radiomic datasets through the application of machine learning (ML) and deep learning (DL) algorithms. …”
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Image Preprocessing Framework for Time-domain Astronomy in the Artificial Intelligence Era by Liang Cao, Peng Jia, Jiaxin Li, Yu Song, Chengkun Hou, Yushan Li

“…Image preprocessing, which involves standardizing images for training or deployment of various AI algorithms, encompasses essential steps such as image quality evaluation, alignment, stacking, background extraction, gray-scale transformation, cropping, source detection, astrometry, and photometry. …”
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Dataset of apples for grading by sweetness, ripeness and varietyMendeley Data by Shilpa Gaikwad, Sonali Kothari, Ignisha Rajathi G

“…The resulting annotated database includes such quantitative reference points, which can be used to train supervised learning classifiers in computational classification systems.The reuse value of the dataset covers a wide range of applications such as machine learning-based fruit quality evaluation, agricultural automation and food industry examination. …”
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Comparative Analysis of Facial Expression Recognition Methods by Denys - Florin COT

“…The research not only deepens the understanding of emotion classification algorithms but also provides valuable perspectives for their application in crucial areas such as mental health and personalized medical assistance. …”
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Hybrid POF-VLC Systems: Recent Advances, Challenges, Opportunities, and Future Directions by Rola Abdallah, Mohamed Atef, Nasir Saeed

“…Furthermore, the application of machine learning, particularly neural network-based equalizers like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), is highlighted for their potential to enhance signal quality and system performance. …”
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A BERT-Based Classification Model: The Case of Russian Fairy Tales by Валерий Дмитриевич Соловьев, Марина Ивановна Солнышкина, Andrey Ten, Николай Аркадиевич Прокопьев

“…Method: We pre-train BERT using a collection of three classes of documents and fine-tune it for implementation of a specific application task. Focused on the mechanism of tokenization and embeddings design as the key components in BERT’s text processing, the research also evaluates the standard benchmarks used to train classification models and analyze complex cases, possible errors and improvement algorithms thus raising the classification models accuracy. …”
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A Quantum-Inspired Optimization Strategy for Optimal Dispatch to Increase Heat and Power Efficiency by K. Vanitha, B. Jyothi, R. Seshu Kumar, V. S. Chandrika, Arvind R. Singh, R. M. Naidoo

“…The proposed algorithm also incorporates a classical optimizer to refine the numerical evaluations acquired from the quantum operations. …”
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