Mapping the Impact of Spontaneous Streetscape Features on Social Sensing in the Old City of Quanzhou, China: Based on Multisource Data and Machine Learning by Keran Li, Yan Lin

“…This paper combined the mobile collection of street view images (SVIs) and a machine learning algorithm to calculate eight types of spontaneous streetscape elements and integrated two online platforms (Dianping and Sina Weibo) to map the distribution of economic vitality and social media perception, respectively. …”
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Artificial-intelligence-guided design of ordered gas diffusion layers for high-performing fuel cells via Bayesian machine learning by Jing Sun, Pengzhu Lin, Lin Zeng, Zixiao Guo, Yuting Jiang, Cailin Xiao, Qinping Jian, Jiayou Ren, Lyuming Pan, Xiaosa Xu, Zheng Li, Lei Wei, Tianshou Zhao

“…Abstract Rational design of gas diffusion layers (GDL) is an example of a long-standing pursuit to increase the power density and reduce the cost of proton exchange membrane fuel cells (PEMFC). …”
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A survey on PSO based meta-heuristic scheduling mechanism in cloud computing environment by Arabinda Pradhan, Sukant Kishoro Bisoy, Amardeep Das

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Video-Driven Artificial Intelligence for Predictive Modelling of Antimicrobial Peptide Generation: Literature Review on Advances and Challenges by Jielu Yan, Zhengli Chen, Jianxiu Cai, Weizhi Xian, Xuekai Wei, Yi Qin, Yifan Li

“…By integrating video analysis with computational modelling, researchers can visualise and quantify AMP–microbe interactions at unprecedented levels of detail, thereby informing both experimental design and the refinement of predictive algorithms. This review provides a comprehensive overview of these emerging techniques, highlights major breakthroughs, addresses critical challenges, and ultimately emphasises the powerful synergy between video-driven pattern recognition, AI-based modelling, and experimental validation in the pursuit of next-generation antimicrobial strategies.…”
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Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review by Anastasios Anastasiadis, Antonios Koudonas, Georgios Langas, Stavros Tsiakaras, Dimitrios Memmos, Ioannis Mykoniatis, Evangelos N. Symeonidis, Dimitrios Tsiptsios, Eliophotos Savvides, Ioannis Vakalopoulos, Georgios Dimitriadis, Jean de la Rosette

“…Conclusion: AI represents a useful tool that provides urologists with numerous amenities, which explains the fact that it has gained ground in the pursuit of stone disease management perfection. The effectiveness of diagnosis and therapy can be increased by using it as an alternative or adjunct to the already existing data. …”
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GPT-NAS: Neural Architecture Search Meets Generative Pre-Trained Transformer Model by Caiyang Yu, Xianggen Liu, Yifan Wang, Yun Liu, Wentao Feng, Xiong Deng, Chenwei Tang, Jiancheng Lv

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Study of high-speed malicious Web page detection system based on two-step classifier by Zheng-qi WANG, Xiao-bing FENG, Chi ZHANG

“…In view of the increasing number of new Web pages and the increasing pressure of traditional detection methods,the naive Bayesian algorithm and the support vector machine algorithm were used to design and implement a malicious Web detection system with both efficiency and function,TSMWD ,two-step malicious Web page detection.The first step of detection system was mainly used to filter a large number of normal Web pages,which was characterized by high efficiency,speed,update iteration easy,real rate priority.After the former filter,due to the limited number of samples,the main pursuit of the second step was the detection rate.The experimental results show that the proposed scheme can improve the detection speed of the system under the condition that the overall detection accuracy is basically the same,and can accept more detection requests in certain time.…”
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Assessing Data Fusion in Sensory Devices for Enhanced Prostate Cancer Detection Accuracy by Jeniffer Katerine Carrillo Gómez, Carlos Alberto Cuastumal Vásquez, Cristhian Manuel Durán Acevedo, Jesús Brezmes Llecha

“…The combination of an electronic nose and an electronic tongue represents a significant advance in the pursuit of effective detection methods for prostate cancer, a widespread form of cancer affecting men across the globe. …”
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AI-Based Prediction of Visual Performance in Rhythmic Gymnasts Using Eye-Tracking Data and Decision Tree Models by Ricardo Bernardez-Vilaboa, F. Javier Povedano-Montero, José Ramon Trillo, Alicia Ruiz-Pomeda, Gema Martínez-Florentín, Juan E. Cedrún-Sánchez

“…Background/Objective: This study aims to evaluate the predictive performance of three supervised machine learning algorithms—decision tree (DT), support vector machine (SVM), and k-nearest neighbors (KNN) in forecasting key visual skills relevant to rhythmic gymnastics. …”
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A Review of Stall Detection in Subsonic Axial Compressors by Kellie N. Wilson, Golam Gause Jaman, Anish Thapa, Amirthavarshini Vivekananda, Mitchell Lowe, Zachary Grima, Marco P. Schoen

“…This paper reviews the major contributions in these listed pursuits and presents the latest methods and algorithms for stall precursor detection in low-speed axial compressors. …”
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Hybrid precoding method for mmWave massive MIMO systems based on LFM by Haoyi CHEN, Yifan DING, Ying CHENG

“…Analog-digital hybrid precoding is a key technology for millimeter wave massive MIMO systems that reduce hardware costs while balancing system performance.However,the traditional hybrid precoding scheme often needed to find a suitable codebook for precoding,and some codebooks were not easy to obtain or had deviations in actual situations.An analog-digital hybrid precoding method based on latent factor model (LFM) in machine learning without codebook was proposed for this problem.The LFM decomposition and stochastic gradient descent method were used to approximate the designed precoding matrix to the optimal full digital precoding matrix for good performance.The simulation results show that compared with the hybrid precoding design method based on orthogonal matching pursuit (OMP) algorithm,this method not only does not need a codebook,but also has better performance than the hybrid precoding algorithm based on OMP algorithm,which is closer to optimal full digital precoding method.…”
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Multi-targets device-free localization based on sparse coding in smart city by Min Zhao, Danyang Qin, Ruolin Guo, Guangchao Xu

“…Compared with three typical machine learning algorithms: deep learning based on auto encoder, K -nearest neighbor, and orthogonal matching pursuit, experimental results show that the proposed sparse coding-based iterative shrinkage threshold algorithm and subspace sparse coding-based iterative shrinkage threshold algorithm can achieve high localization accuracy and low time cost simultaneously, so as to be more practical and applicable for the development of smart city.…”
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Massive unsourced multiple access scheme based on block sequence codebook and compressed sensing by Jing ZHANG, Lin MA, Chulong LIANG, Hongxu GAO

“…A massive unsourced multiple access scheme based on block sequence codebook and compressed sensing was proposed for sporadic burst scenario in massive machine type communication (mMTC).Firstly, a large-capacity spreading codebook generation scheme was designed according to a specific shift pattern, thus the codebook space was expanded.Secondly, the sparse structure of uplink signal was combined with multi-carrier technology to support overlapping transmission of multi-user data on some subcarriers, thus the spectral efficiency was improved.Finally, a multi-carrier CS-MUD model was established, and a group orthogonal matching pursuit algorithm based on codebook sequence blocks was designed to achieve the joint detection of active users and their uplink data.Simulation results show that the proposed scheme can effectively reduce the bit error rate of massive random access.…”
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UNVEILING FAKE NEWS DETECTION MODELS AND THEIR INTEGRATION INTO WEB SYSTEMS: AN EXTENSIVE INVESTIGATION by Vimal Gaur, Naman Veerwal, Ujjwal Chaudhary, Sparsh Kadian

“…Powered by Multinomial Naive Bayes and Passive Aggressive Classifier algorithms, Fake News Detection System ensures accurate classification. …”
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Prospective identification of extracellular triacylglycerol hydrolase with conserved amino acids in Amycolatopsis tolypomycina’s high G+C genomic dataset by Supajit Sraphet, Bagher Javadi

“…Utilizing knowledge from genome and machine learning algorithms, prospective ETH genes/enzymes were identified. …”
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A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade by Attila Kovari

“…Artificial intelligence tools, in particular machine learning, natural language processing and recommender algorithms, facilitate collaborative learning by enabling personalized learning through feedback and group work. …”
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Application and prospect of artificial intelligence in empowering the operation and managment of oil and gas pipelines by Qi LIAO, Chunying LIU, Jian DU, Hao LAN, Yongtu LIANG, Haoran ZHANG

“…Conclusion Amidst the emerging wave of advancing AI technologies, the pursuit of smart operation of oil and gas pipelines mandates further explorations, including bolstering the application of various methods to integrate vast multi-source heterogeneous data, deepening research on few-shot and zero-shot learning techniques, advocating the convergence of augmented intelligence and artificial intelligence, refining the amalgamation of causal inference and machine learning, and concentrating on life-cycle management anchored in digital twin technology. …”
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Equity in Digital Mental Health Interventions in the United States: Where to Next? by Athena Robinson, Megan Flom, Valerie L Forman-Hoffman, Trina Histon, Monique Levy, Alison Darcy, Toluwalase Ajayi, David C Mohr, Paul Wicks, Carolyn Greene, Robert M Montgomery

“…For products with artificial intelligence/machine learning, maintaining a “human in the loop” as well as prespecified and adaptive analytic frameworks to monitor and remediate potential algorithmic bias can reduce the risk of increasing inequity. …”
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