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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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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Calibration of Integrated Low-Cost Environmental Sensors for Urban Air Temperature Based on Machine Learning by Fang Nan, Chao Zeng, Huanfeng Shen, Liupeng Lin

“…This study focuses on an internet of things (IoT) application in Wuhan, China, aiming to enhance the quality of long-term hourly air temperature data collected by low-cost sensors through on-site calibration. …”
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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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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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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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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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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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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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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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Enhancing Latent Defect Detection in Built-In Spindle Assembly Lines Through Vibration Data Analysis by Kuo-Hao Li, Chao-Nan Wang, Yao-Chi Tang

“…The inclusion of the DBI in the k-means++ clustering algorithm facilitated an objective evaluation of cluster quality, ensuring that the selected number of clusters accurately represents the underlying data patterns. …”
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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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A review of machine learning and deep learning for Parkinson’s disease detection by Hajar Rabie, Moulay A. Akhloufi

“…We discuss the preprocessing methods applied, the state-of-the-art models utilized, and their performance. Our evaluation included different algorithms such as support vector machines (SVM), random forests (RF), convolutional neural networks (CNN). …”
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A Workflow for Integrated Geological Modeling for Shale Gas Reservoirs: A Case Study of the Fuling Shale Gas Reservoir in the Sichuan Basin, China by Xiaofei Shang, Huawei Zhao, Shengxiang Long, Taizhong Duan

“…Moreover, the workflow involves multiple model integration processes, which is the key to model quality. The selection and optimization of modeling methods, the innovation and development of modeling algorithms, and the evaluation techniques for model uncertainty are areas where breakthroughs may be possible in the geological modeling of shale gas reservoirs. …”
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Diagnostic models for sepsis-associated encephalopathy: a comprehensive systematic review and meta-analysis by Tengfei Zhou, Tengfei Zhou, Xinming Tian, Wei Wang, Zhe Chu

“…All models showed a high risk of bias according to the PROBAST evaluation, mainly due to the lack of external validation and methodological shortcomings.ConclusionCurrent SAE prediction models demonstrate moderate discriminatory ability, but their methodological quality remains poor, and they are not yet suitable for routine clinical application. …”
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Detection of soluble solid content in table grapes during storage based on visible-near-infrared spectroscopy by Yuan Su, Ke He, Wenzheng Liu, Jin Li, Keying Hou, Shengyun Lv, Xiaowei He

“…The soluble solid content (SSC) in grapes significantly influences their flavour and plays an integral role in evaluation of the quality and consumer acceptance. This study employed visible near-infrared (Vis-NIR) spectroscopy to rapidly quantify SSC in table grapes during storage. …”
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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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Spectral Fingerprinting of Tencha Processing: Optimising the Detection of Total Free Amino Acid Content in Processing Lines by Hyperspectral Analysis by Qinghai He, Yihang Guo, Xiaoli Li, Yong He, Zhi Lin, Hui Zeng

“…However, traditional chemical analysis methods are often time-consuming and costly, limiting their application in real-time quality control. Hyperspectral imaging (HSI) has shown significant effectiveness as a component detection tool in various agricultural applications. …”
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Multiobjective Design Optimization of Grillage Systems according to LRFD-AISC by Tugrul Talaslioglu

“…Hence, while the computational performances of these four optimization algorithms are compared using different combinations of optimizer-related parameters, the various strengths of grid members are also evaluated. …”
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Artificial intelligence-assisted capsule endoscopy for detecting lesions in Crohn’s disease: a systematic review and meta-analysis by Yuling Bin, Rumei Peng, Yaqian Lee, Zhijie Lee, Yang Liu

“…However, given the limitations and heterogeneity of current research, more high-quality, large-sample studies are needed to comprehensively and thoroughly evaluate the practical application value of AI in CD diagnosis, thereby promoting its widespread adoption and optimization in clinical practice.…”
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