State-Space Analysis and Complexity Assessment of Puzzle Games Using Colored Petri Nets by Ahmad Taghinezhad-Nia, Saeid Pashazadeh

“…By synthesizing model-checking techniques with ML-based algorithmic implementations, we develop an optimized search strategy for traversing the state space graph, enabling the derivation of quantitative complexity metrics. …”
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AI-driven precision diagnosis and treatment in Parkinson’s disease: a comprehensive review and experimental analysis by Bhekisipho Twala

“…The integration of multiple data modalities and advanced machine learning algorithms enables earlier detection, more accurate monitoring, and optimized therapeutic interventions. …”
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ECHS1 as a Lipid Metabolism Biomarker for Pediatric Focal Segmental Glomerulosclerosis. by Chao He, Wei Peng, Sheng Li, Can Xu, Xiuping Chen, Yuanhan Qin

“…Protein-protein interaction networks were constructed using Cytoscape, and five hub DELMRGs (enoyl-CoA hydratase, short chain 1 [ECHS1], EHHADH, IDH1, SUCLG1, and ALDH3A2) were identified using multiple algorithms. We assessed the diagnostic performance using receiver operating characteristic curves and expression levels from the GSE121233 dataset, and found that ECHS1 and ALDH3A2 showed strong diagnostic potential. …”
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A predictive healthcare model using machine learning and psychological factors for medication adherence by Junwu Dong, Minyi Chu, Yirou Xu

“…Five machine learning algorithms – multiple logistic regression, decision tree, adaptive boosting, random forest and support vector machine (SVM) – were utilized to identify MAB levels and assess feature importance. …”
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New <i>μ</i>-Synchronization Criteria for Nonlinear Drive–Response Complex Networks with Uncertain Inner Couplings and Variable Delays of Unknown Bounds by Anran Zhou, Chongming Yang, Chengbo Yi, Hongguang Fan

“…Moreover, numerical experiments and image encryption algorithms are carried out to verify our theoretical results’ effectiveness.…”
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The innovation path of VR technology integration into music classroom teaching in colleges and universities by Yupeng Han, Lin Han, Chun Zeng, Wei Zhao

“…To explore these possibilities, this study proposes an Intelligent Interactive Music Teaching (IIMT) model that combines VR technology with Deep Convolutional Generative Adversarial Networks and Deep Deterministic Policy Gradient algorithms. The study utilizes publicly available music teaching videos and virtual environment interaction data. …”
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Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification. by Jaipriya D, Sriharipriya K C

“…Traditional EEG pattern recognition algorithms typically involve two key steps: feature extraction and feature classification, both crucial for accurate operation. …”
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A comprehensive analysis of deep learning and transfer learning techniques for skin cancer classification by Manishi Shakya, Ravindra Patel, Sunil Joshi

“…This research investigates three approaches for classifying skin cancer images. (1) Utilizing three fine-tuned pre-trained networks (VGG19, ResNet18, and MobileNet_V2) as classifiers. (2) Employing three pre-trained networks (ResNet-18, VGG19, and MobileNet v2) as feature extractors in conjunction with four machine learning classifiers (SVM, DT, Naïve Bayes, and KNN). (3) Utilizing a combination of the aforementioned pre-trained networks as feature extractors in conjunction with same machine learning classifiers. All these algorithms are trained using segmented images which are achieved by using the active contour approach. …”
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Microphysical detection of nano-ice nuclei to ice crystals: a platform for ice nucleation research by Devendra Pal, Ryan Hall, Yevgen Nazarenko, Leonard Barrie, Parisa A. Ariya

“…This platform enables real-time detection and differentiation of ice crystals and supercooled droplets, providing microphysical information into their spherical or non-spherical morphology, surface roughness, and phase characteristics, particularly for ice particles smaller than 500 nm. Automated algorithms facilitate the differentiation of individual and aggregated ice crystals within a size range of 390 nm to 100 µm, supporting time-resolved analyses of ice nucleation processes. …”
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Integrating Mobile Devices and Wearable Technology for Optimal Sleep Conditions by You-Kwang Wang, Chien-Yu Chen

“…This project uses cloud storage technology and cloud software algorithms to enable data sharing and real-time feedback. …”
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Machine learning based classification of catastrophic health expenditures: a cross-sectional study of Korean low-income households by Seok Min Ji, Jeewuan Kim, Kyu Min Kim

“…The classification model was developed using four machine learning algorithms: Random Forest, Gradient boosting, Decision tree, Ridge regression, Neural network, and AdaBoost. …”
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Critical considerations and computational tools in plant genome editing by Dipnarayan Saha, Alok Kumar Panda, Subhojit Datta

“…Computational tools and algorithms play a crucial role in construct design and gRNA selection to minimize off-target effects and also to optimize their delivery techniques. …”
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Distinguishing Human Journalists from Artificial Storytellers Through Stylistic Fingerprints by Van Hieu Tran, Yakub Sebastian, Asif Karim, Sami Azam

“…<b>Methods/Approach</b>: We used machine learning algorithms and trained five classifiers to distinguish journalistic news articles from their AI-generated counterparts based on various lexical, syntactic, and readability features. …”
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IRWT-YOLO: A Background Subtraction-Based Method for Anti-Drone Detection by Xueqi Cheng, Fan Wang, Xiaopeng Hu, Xinrong Wu, Min Nuo

“…To effectively separate low-contrast weak drone objects from complex backgrounds, the IRWT-YOLO model is proposed, in which image segmentation algorithms are leveraged to reduce background interference. …”
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MetaboLabPy—An Open-Source Software Package for Metabolomics NMR Data Processing and Metabolic Tracer Data Analysis by Christian Ludwig

“…This includes a choice of algorithms for automated phase correction, segmental alignment, spectral scaling, variance stabilisation, export to various software platforms, and analysis of metabolic tracing data. …”
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High-throughput image-based monitoring of cell aggregation and microspheroid formation. by Thomas Deckers, Toon Lambrechts, Stefano Viazzi, Gabriella Nilsson Hall, Ioannis Papantoniou, Veerle Bloemen, Jean-Marie Aerts

“…As opposed to existing algorithms, our methodology was not only able to automatically monitor compact spheroids but also the aggregation process of individual spheroids, and this in an accurate and high-throughput manner. …”
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Improving the Reliability of DC-DC Power Supply by Reserving Feedback Signals by V. A. Shpenst, E. A. Orel

“…The proposed method does not require any digital signal processing algorithms or microprocessor control modules and can be implemented on the basis of cheap, widely available analog chips that perform pulse-width control of the output voltage. …”
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Low-Complexity Adaptive Chromatic Dispersion Estimation Scheme Using Machine Learning for Coherent Long-Reach Passive Optical Networks by Jin Li, Danshi Wang, Min Zhang

“…To add comparisons, the performances of CD estimation schemes using other two well-known machine learning algorithms including the k-nearest neighbor (KNN) and the decision tree (DT) have also been investigated. …”
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Analysis of the effectiveness of selection of women for coronarography in real clinical practice by N. V. Izmozherova, A. A. Popov, V. E. Sherstobitov

“…The obtained data reflect the relevance of the development of more effective algorithms for diagnosis of coronary artery disease in women, since the gender peculiarities of the formation of coronary atherosclerosis have been clearly confirmed in a number of large studies.Conclusion. …”
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Selection and validation of stable reference genes in potato infected by Pectobacterium atrosepticum using real-time quantitative PCR by Lijuan Hou, Haixia Zhu, Wenrong Xian, Yongqiang Ma

“…To accurately evaluate the expression levels of genes involved in potato (Solanum tuberosum) responses to P. atrosepticum infection, seven candidate reference genes (EF1α, eIF5A3, Tubulin, Ubiquitin, GAPDH, Actin, and CYP3) were systematically assessed for their expression stability at 1, 3, and 5 days after inoculation (dai) using the geNorm, NormFinder, BestKeeper, ∆Ct, and RefFinder algorithms. The results demonstrated that EF1α exhibited the highest stability among all experimental conditions, followed by eIF5A3 and Tubulin, whereas Ubiquitin displayed the least stability. …”
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