High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats by Erin McDonald, Eric Kehoe, Darcy Deines, Mary McCarthy, Brie Wright, Susan Huse

“…Our analysis uses machine learning and statistical algorithms to perform unsupervised clustering, multiple visualizations, and statistical analysis of high parameter flow cytometry data. …”
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Towards a Low-Cost Mobile Subcutaneous Vein Detection Solution Using Near-Infrared Spectroscopy by Simon Juric, Vojko Flis, Matjaz Debevc, Andreas Holzinger, Borut Zalik

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An Improved Maximum Power Point Approach for Temperature Variation in PV System Applications by Abdelkhalek Chellakhi, Said El Beid, Younes Abouelmahjoub

“…This MPPT approach can be added to numerous existing MPPT algorithms in order to enhance their tracking accuracy and response time and to reduce the power loss. …”
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Robust Data-Driven Fault Detection: An Application to Aircraft Air Data Sensors by Yunmei Zhao, Hang Zhao, Jianliang Ai, Yiqun Dong

“…Data-driven methods have claimed accurate performances which scale well to different cases, but the algorithmic structures and enclosed operations are “black,” jeopardizing its robustness. …”
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Enhancing concealed object detection in active THz security images with adaptation-YOLO by Aiguo Cheng, Shiyou Wu, Xiaodong Liu, Hangyu Lu

“…However, current object detection algorithms face many challenges when applied to THz images. …”
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Screening of multi deep learning-based de novo molecular generation models and their application for specific target molecular generation by Yishu Wang, Mengyao Guo, Xiaomin Chen, Dongmei Ai

“…With the development of deep learning techniques for the de novo generation of molecules, also known as inverse molecular design, the increasingly widespread application of various types of deep learning algorithms has led to revolutionary changes in de novo molecular generation research. …”
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Photodiagnosis and photodynamic recognition of cervical cancer with SEM and AFM images. by Sevcan Aytaç, Gürkan Özbey

“…The classification rate found by the averages of the results obtained from the DWTF_JSD, DWTF_HD and DWTF_TD algorithms for AFM and SEM cervix images are 98.29% and 97.10%, respectively. …”
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Resolving Covid-19 with Blockchain and AI by Suyogita Singh, Satya Bhushan Verma

“…In that review, many potential blockchain applications were discovered; however, the majority of them were still in their infancy, and it couldn’t yet be predicted how they could contribute to the fight against COVID-19 through the use of platforms, access kinds, and consensus algorithms. Modern innovations such as blockchain and artificial intelligence (AI) were shown to be promising in limiting the spread of a virus. …”
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Energy Efficiency of Kernel and User Space Level VPN Solutions in AIoT Networks by ALEKSANDAR JEVREMOVIC, Zona Kostic, Ivan Chorbev, Dragan Perakovic, Andrii Shalaginov, Ivan Cvitic

“…The ability to process data locally using complex algorithms is becoming increasingly important in Internet of Things (IoT) contexts. …”
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Behavior modeling for a new flexure-based mechanism by Hunger Game Search and physics-guided artificial neural network by Hieu Giang Le, Thanh-Phong Dao, Minh Phung Dang, Thao Nguyen-Trang

“…In the field of compliant mechanism modeling, there has been no research interested in applying meta-heuristics optimization algorithms to optimize the weights and biases of the neural network globally. …”
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Tool wear prediction based on XGBoost feature selection combined with PSO-BP network by Zhangwen Lin, Yankun Fan, Jinling Tan, Zhen Li, Peng Yang, Hua Wang, Weiwei Duan

“…Experimental results show that PSO outperforms other algorithms in training the tool wear prediction model, with XGBoost feature selection reducing model construction time by 57.4% and increasing accuracy by 63.57%, demonstrating superior feature selection capabilities over Decision Tree, Random Fores, Adaboost and Extra Trees. …”
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Soft computing paradigm for climate change adaptation and mitigation in Iran, Pakistan, and Turkey: A systematic review by Muhammad Talha, A. Pouyan Nejadhashemi, Kieron Moller

“…Although some articles utilized multiple techniques, classical ML methods appeared in approximately 37.3 % of the studies, neural network paradigms in about 57.5 %, and optimization or meta-heuristic algorithms in around 5.0 %. Regarding thematic focus, about 33.3 % of the articles addressed water resource management, 22.2 % focused on climate prediction, 11.1 % on land and agriculture, 9 % on ecosystem modeling, and 24.2 % on natural disaster preparedness and response. …”
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A Novel On-Ramp Merging Strategy for Connected and Automated Vehicles Based on Game Theory by Haigen Min, Yukun Fang, Runmin Wang, Xiaochi Li, Zhigang Xu, Xiangmo Zhao

“…Connected and automated vehicles (CAVs) have attracted much attention of researchers because of its potential to improve both transportation network efficiency and safety through control algorithms and reduce fuel consumption. However, vehicle merging at intersection is one of the main factors that lead to congestion and extra fuel consumption. …”
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Harnessing Artificial Intelligence for ESL Assessments: Efficiency, Challenges, and Future Directions by Seyed Reza Abedi, Farnaz Divanpour, Seyed Reza Molaee, Hailay Tesfay Gebremariam

“…Qualitative insights from 20 instructors reveal challenges, including algorithmic bias, cultural insensitivity, and concerns over data privacy. …”
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Description of route dependencies for computer-based railway signalling systems by Michał Grzybowski, Jakub Młyńczak, Lucyna Sokołowska

“…In addition, during research algorithms for automatic verification of conflicting route exclusion correctness have been designed, which allows for reduction of effort required for verification of conflicting route exclusion function. …”
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Effects of Vehicle Restriction Policies on Urban Travel Demand Change from a Built Environment Perspective by Xiaoyun Cheng, Kun Huang, Lei Qu, Tianbao Zhang, Li Li

“…To solve the multicollinearity among the variables and high-dimensional problem, this study utilizes two different penalization-based regression models, the LASSO (least absolute shrinkage and selection operator) and Elastic Net regression algorithms, to achieve the variable selection and explore the impacts of the built environment on the change of travel demand triggered by the LPR policy. …”
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Image dataset: UAV images and ground data of one ‘Bingo’ mandarin and two ‘Valencia’ orange rootstock trials conducted in FloridaAg Data CommonsAg Data Commons by Randall P. Niedz, Kim D. Bowman

“…The data will be useful for 1) visualizing the effects of different rootstock selections and varieties on scion growth, effects that may not be fully captured with single measure metrics; and 2) development of image analysis applications and segmentation algorithms that can extract data from the images that are suitable for replacing some or all the ground measures.…”
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Complex System of Vertical Baduanjin Lifting Motion Sensing Recognition under the Background of Big Data by Yan Zhang, M. M. Kamruzzaman, Lu Feng

“…In order to carry out related action recognition research on the lifting action of vertical Baduanjin, this paper uses sensor technology to collect the motion video image of vertical Baduanjin based on the background of big data and uses action recognition technology and related algorithms to obtain the action. Recognize the video image to obtain the data, get the acceleration, angular velocity, and EMG data, and count the end time and duration according to the change of the action. …”
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Webometric as diagnostic tools of digital sociology: contents, purpose, usage experience by M. V. Kibakin

“…The rules and conditions for effective use of Webometrics have been substantiated, based on the usage of content analysis methods and procedures for the development of its forms; to include usability and visibility in the analysis of technological characteristics of Internet portals; to make the research parameters used reliable by separating them from official documents of state policy and corporate strategies; to combine traditional methods of fixing primary data and computer algorithms. A specific webometric technique has been revealed in detail, which implies fixing the formal status of the Internet source under study, the content parameters of information representation of information about the implementation of state policy on the example of working with young people, the availability of services, as well as indicators of the site’s technology and ease of access to it by the population. …”
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Parameter-Efficient Vehicle Trajectory Prediction Based on Attention-Enhanced Liquid Structural Neural Model by Ruochen Wang, Yue Chen, Renkai Ding, Qing Ye

“…Trajectory prediction is a critical task to anticipate the future positions of surrounding vehicles. However, existing algorithms, such as LSTM-based and attention-based models, face challenges of high computational complexity, large parameter sizes, and limited ability to efficiently capture both temporal dependencies and spatial interactions in dynamic traffic scenarios. …”
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