Utilizing Principal Singular Vectors for 2D DOA Estimation in Single Snapshot Case with Uniform Rectangular Array by Yuntao Wu, Xiaobing Pei, Hing Cheung So

“…Using the principal singular vectors of the observed data matrix, an iterative procedure based on the linear prediction property, and weighted least squares is proposed for finding the DOAs with lower computational complexity. …”
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Improved Mixture Cure Model Using Machine Learning Approaches by Huina Wang, Tian Feng, Baosheng Liang

“…When combined with mixture cure models, they can effectively improve the performance of mixture cure models, distinguish between susceptible and non-susceptible individuals, and accurately predict the influencing factors and their magnitude of incidence and latency.…”
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Regression-based investigation of latency in automated networks by Urooj Khan, Tariq Soomro, M.N. Brohi

“…Regression analysis of such a system has predicted that the performance gap will persist with varying network nodes and increasing time limits. …”
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A comparison of several intrusion detection methods using the NSL-KDD dataset by hazem salim abdullah

“…This research investigates the way to classify and predict cyber-attacks on the NSL-KDD dataset using intrusion detection methods the investigation contrasts the capabilities of various algorithms, including RNN, MLP, CNN-LSTM, and ANN, in recognizing attacks. …”
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Optimising Daily Fantasy Sports Teams with Artificial Intelligence by Beal Ryan, Norman Timothy J., Ramchurn Sarvapali D.

“…Specifically, we focus on the National Football League (NFL) and predict the performance of real-world players to form the optimal fantasy team using mixed-integer programming. …”
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Estimation of CO₂ Emissions in Transportation Systems Using Artificial Neural Networks, Machine Learning, and Deep Learning: A Comprehensive Approach by Seval Ene Yalçın

“…The findings of this study indicate that the aforementioned models can be effectively implemented to predict transport emissions, concluding that they have valuable and practical applications in this field.…”
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Integrated metabolomic-lipidomic profiling reveals novel biomarkers and therapeutic targets for alcohol use disorder with cognitive impairment by Li Shi, Li Shi, Li Shi, Xiaofang Chen, Bojie Zhou, Bojie Zhou, Shanghao Yang, Shanghao Yang, Qinglin Ou, Qinglin Ou, Xuhui Zhou, Xuhui Zhou

“…AUD-CI patients exhibited 49 unique lipid alterations, notably 70% reduction of phosphatidylcholine PC (42:4) versus HCs (p=0.002), strongly correlated with synaptic protein markers (r=0.82, p<0.001).ConclusionOur findings characterize a dysregulated liver-gut-brain metabolic axis in AUD-CI pathogenesis, highlighting the mTORC1-sphingolipid pathway as a promising therapeutic target. …”
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Continual Learning With Neuromorphic Computing: Foundations, Methods, and Emerging Applications by Mishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah Awwad, Osman Hasan, Muhammad Shafique

“…It also covers optimization techniques including SNN operations reduction, weight quantization, and knowledge distillation. …”
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Utility of positron emission tomography–computed tomography in the evaluation of fever of unknown origin in a resource-limited tropical nation by Sohini Das, Sowmya Sathyendra, Julie Hephzibah, Reka Karuppusami, Karthik Gunasekaran, Nylla Shanthly, Angel Miraclin, Ramya Iyadurai

“…Sensitivity, specificity, and positive and negative predictive value of PET-CT scans were 76.9% (20/26), 33.3% (2/6), 83% (20/24), and 25% (2/8), respectively. …”
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Interpretable machine learning for depression recognition with spatiotemporal gait features among older adults: a cross-sectional study in Xiamen, China by Shaowu Lin, Sicheng Li, Ya Fang

“…The developed machine learning models with high predictive accuracy, suggest the potential of Kinect-based gait assessment as a real-time and cost-effective screening tool for older adults with depressive symptoms.…”
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Forecasting COVID-19 cases based on mobility by Mehmet Şahin

“…In this context, various machine learning algorithms are implemented to obtain accurate predictions. …”
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A method for measuring carbon emissions from power plants using a CNN-LSTM-Attention model with Bayesian optimization by Jiacheng Chen, Li Zheng, Wenyan Che, Li Liu, Hui Huang, Jun Liu, Chang Xing, Penghua Qiu

“…Accurate measurement of CO2 emissions from coal-fired power plants is crucial for achieving China's “carbon neutrality” goal; however, traditional CO2 emission measurement methods have several limitations, and emerging prediction models rarely utilize real-time monitoring data from power plants at the micro level. …”
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Conceptualizing an AI-based Police Robot for Preventing Online Child Sexual Exploitation and Abuse: by Nina Sunde, Inger Marie Sunde

“…Given the advancements in machine learning algorithms, PrevBOT may provide predictions concerning age and gender behind online aliases engaged in sexualized speech with children and assist the police in identifying former CSEA offenders who resume the criminal activity online. …”
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Energy Consumption Optimization for an Electric Delivery Vehicle by Andrzej Łebkowski

“…This publication proposes an electronic Energy Consumption Optimizer (ECO) that predictively uses information about the shape of the route and speed limits on its individual sections to control the motor speed and gear changes in the gearbox. …”
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Confidence-Guided Frame Skipping to Enhance Object Tracking Speed by Yun Gu Lee

“…The proposed method determines the need for intervention by the robust algorithm based on the predicted confidence level. …”
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Deep Learning-Based Economic Forecasting for the New Energy Vehicle Industry by Bowen Cai

“…With the rapid development of science and technology, deep learning continues to make breakthroughs, and, in the field of economy with huge information data, we have more powerful weapons available to predict and research important economic data with infinite value, which can not only provide reference information to policy makers but also help enterprises and even economic markets to develop more healthily and sustainably. …”
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Digital transformation of modern corporation management tools: the current state and development paths by V. A. Laptev, S. Yu. Chucha, D. R. Feyzrakhmanova

“…The authors distinguish three types of digital corporate governance: remote management (exercised by human individuals), smart management (based on algorithms designed by human engineers), and artificial intelligence (AI) management (that does not require human involvement). …”
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Utilizing Artificial Intelligence (AI) for the optimal design of geothermal cogeneration systems in zero energy building by Ehsanolah Assareh, Mohammad Zoghi, Ali Zare, Hassan Bazazzadeh, Adnan Alboghobeysh, Saleh Mobayen, Nima Izadyar, Siamak Hoseinzadeh

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Composite Mapping for Peptide‐Based Data Storage with Higher Coding Density and Fewer Synthesis Cycles by Anxun Zhang, Longjie Wang, Xiaowei Zhai, Yao Xiao, Yanchan Wu, Yongxi Zhao, Kai Liu, Ji‐Shen Zheng, Dong Chen

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Exploration of heterogeneity of treatment effects across exercise-based interventions for knee osteoarthritis by Paul A. Dennis, Livia Anderson, Cynthia J. Coffman, Sara Webb, Kelli D. Allen

“…Three metalearners with three machine learning algorithms each and a simple interpretable model-based regression tree were used to identify subgroups with differential treatment effects. …”
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