Detection of Mycotoxin Contamination in Foods Using Artificial Intelligence: A Review by Ashish Aggarwal, Akanksha Mishra, Nazia Tabassum, Young-Mog Kim, Fazlurrahman Khan

“…The new approach demonstrated that a variety of AI technologies could be correlated. Deep learning models, machine learning algorithms, and neural networks were implemented to analyze elaborate datasets from different analytical platforms. …”
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A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems by Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada

“…Traditional energy management methods, based on static models or heuristic algorithms, often fail to handle real-time grid dynamics, leading to suboptimal energy distribution, high operational costs, and significant energy wastage. …”
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Spatial pattern and heterogeneity of green view index in mountainous cities: a case study of Yuzhong district, Chongqing, China by Aiping Gou, Xuyuan Wang, Jiangbo Wang, Chenjie Wang, Guanzheng Tan

“…The results indicate that: (1) In Yuzhong District, 58.9% of streets have a GVI within a low to moderate range, suggesting room for improvement. Higher GVI levels are generally associated with elevated Digital Elevation Models (DEM), while slope, aspect, and terrain undulation have relatively minor overall impacts on GVI. (2) The GVI is highest in the western regions and lowest in the eastern regions, with streets along the riversides exhibiting lower GVI levels. (3) GWR analysis reveals that road type and NDVI significantly influence the GVI. …”
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Automatic screening for posttraumatic stress disorder in early adolescents following the Ya’an earthquake using text mining techniques by Yuzhuo Yuan, Yuzhuo Yuan, Zhiyuan Liu, Wei Miao, Xuetao Tian

“…Meanwhile, participants completed the PTSD Checklist for DSM-5 (PCL-5). Text classification models were constructed using three supervised learning algorithms (BERT, SVM, and KNN) to identify PTSD symptoms and their corresponding behavioral indicators in each sentence of the self-narratives.ResultsThe prediction accuracy for symptom-level classification reached 73.2%, and 67.2% for behavioral indicator classification, with the BERT performing the best.ConclusionsThese findings demonstrate that self-narratives combined with text mining techniques provide a promising approach for automated, rapid, and accurate PTSD screening. …”
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Predicting Court Judgment in Criminal Cases by Text Mining Techniques by Mohammad Farhadishad, Mohammad Kazemifard, Zahra Rezaei

“…Legal judgment prediction with artificial intelligence algorithms can benefit judicial bodies, legal experts, and litigants as well as judges. …”
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Target identification of natural products in cancer with chemical proteomics and artificial intelligence approaches by Guohua Li, Qian Shi, Qibiao Wu, Xinbing Sui

“…AI-driven models, especially machine learning algorithms, have proven effective in processing complex proteomic data and predicting potential NP-protein interactions. …”
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Few-shot learning for novel object detection in autonomous driving by Yifan Zhuang, Pei Liu, Hao Yang, Kai Zhang, Yinhai Wang, Ziyuan Pu

“…Experiments on a self-driving dataset augmented with rare objects alongside the popular few-shot object detection (FSOD) benchmark, the pattern analysis, statical modeling, and computational learning PASCAL Visual Object Classes (PASCAL-VOC), demonstrate state-of-the-art accuracy in rare categories and superior inference speed compared to alternative algorithms. …”
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Disentangling High-Paced Alternating I/O in Gaze-Based Interaction by Yulia G. Shevtsova, Artem S. Yashin, Sergei L. Shishkin, Anatoly N. Vasilyev

“…By applying machine learning algorithms to gaze features and action context information, we achieved a threefold reduction in false positives, improved the quality of in-game decisions, and increased participant satisfaction with system ergonomics. …”
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Transformative applications in biology education: A case study on the efficacy of adaptive learning with numerical insights by Shin I. Aleksandrovich, Tyan Ramazan, Raissa Utegaliyeva, Balzat Sarimbayeva, Gaukhar Keubassova, Rakhima Bissalyyeva, Kuanysh Syman, Gaukhar Abdikarimova

“…Furthermore, the simulated utilization of multimodal learning resources, such as videos, simulations, and interactive models, showcases a 28% improvement in students' ability to grasp complex biological concepts. …”
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Gender Disparities in Artificial Intelligence–Generated Images of Hospital Leadership in the United States by Mia Gisselbaek, MD, Joana Berger-Estilita, MD, PhD, Laurens Minsart, MD, Ekin Köselerli, MD, Arnout Devos, PhD, Francisco Maio Matos, PhD, Odmara L. Barreto Chang, MD, PhD, Peter Dieckmann, PhD, Melanie Suppan, MD, Sarah Saxena, MD, PhD

“…Statistically significant differences were observed across models and between models and real-world demographics. …”
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Multi-source 3D point clouds fusion for potential rock mass hazard evaluation in high-steep rock slopes by W. Yuan, C. Liu, C. Liu, T. Wang, B. Adriano, H. Bao, R. Shibasaki, S. Koshimura

“…The results demonstrate that the fusion of TLS-UAV multi-source data enhances spatial coverage and point cloud density by 19%, enabling comprehensive slope modeling and improving multi-angle structural characterization of target rock masses. …”
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3Mont: A multi-omics integrative tool for breast cancer subtype stratification. by Miray Unlu Yazici, J S Marron, Burcu Bakir-Gungor, Fei Zou, Malik Yousef

“…Following that, machine learning (ML) models are constructed based on the prominent pro-groups, which enable the extraction of promising biomarkers for distinguishing BRCA sub-types. …”
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An engineering practical three-dimensional sliding cable element by Binlin Xu, Gen He, Fanbo Guo

“…Abstract Aiming at the difficulty of accurately modeling the friction slip effect in engineering calculations for multi-span continuous cable structures, it is proposed to develop a three-dimensional slip cable element USER101 by using the secondary development platform of ANSYS-UPFs combined with the catenary theory and the Euler-Eytelwein formula. …”
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Optimal Low-Carbon Scheduling for Smart Microgrids With Dynamic Thermal Capacity Constraints by Peng Xie, Hongwei Liu, Chun Chen, Mingjun Liu

“…This work develops an adaptive threshold tightening mechanism for Column-and-Constraint Generation algorithms to balance computational efficiency and solution precision. …”
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“intelligent Read Across (iRA)”- A tool for read-across-based toxicity prediction of nanoparticles by Souvik Pore, Kunal Roy

“…External validation metrics show improvements over previously reported models across all datasets. …”
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Efficient Real-Time Pathfinding for Visually Impaired Individuals by Tadeh Ghahremanians, Hossein Mahvash Mohammadi

“…Traditional methods usually focus on the detection of specific patterns or objects, requiring custom algorithms for each object of interest. In contrast, deep learning models such as instance segmentation and semantic segmentation allow for independent recognition of different elements within a scene. …”
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Failure Management Overview in Optical Networks by Sergio Cruzes

“…Emphasizing automation, it discusses how ML algorithms can streamline failure management processes, reducing manual intervention and service disruptions. …”
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Workload Forecasting Methods in Cloud Environments: An Overview by Samah Aziz, Manar Kashmoola

“…We explore more sophisticated approaches like algorithms for deep learning (DL) and machine learning (ML) in addition to more conventional approaches like analysis of time series and models of regression. …”
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Intelligent gear decision method for vehicle automatic transmission system based on data mining by Yong Wang, Jianfeng Zeng, Pengfei Du, Huachao Xu

“…Subsequently, dynamic programming algorithms are employed to optimize intelligent gear decisions. …”
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Big data transfer service architecture for cloud data centers: problems, methods, applications, and future trends by Muhammad Umar Majigi, Ismaila Idris, Shafi’i Muhammad Abdulhamid, Richard A. Ikuesan

“…After thoroughly screening selected peer-reviewed articles, the primary open issues are: incorporating a data placement module in the data transfer service, providing end-to-end safeguards for packet delivery, improving data transfer time and speed, minimizing costs and implementation overhead, ensuring secure data transfer between servers in the cloud, demonstrating effective big data transfer architectures, considering topology-specific extensions to reduce the busty nature of data centers, and enhancing data transfer services using machine learning algorithms during upload and download operations. …”
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