Assessment and Prediction of Typhoon-Related Direct Economic Loss in Fujian Province Based on LightGBM by Zhang Zhixia, Yang Jian, Chen Sixiao, Lin Sen

“…The importance of LightGBM factors shows that the maximum daily wind speed, river network density, maximum daily precipitation, cumulative precipitation, and GDP per unit area are the primary determinants of typhoon-induced economic losses in Fujian Province. …”
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Environmental Risk Mitigation via Deep Learning Modeling of Compressive Strength in Green Concrete Incorporating Incinerator Ash by Amin Amraee, Seyed Azim Hosseini, Farshid Farokhizadeh, Mohammad Hassan Haeri

“…A database for deep learning modeling was created using Convolutional Neural Networks (CNNs) and the Multi-Verse Optimizer (MVO) algorithm. …”
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Research on entity recognition and alignment of APT attack based on Bert and BiLSTM-CRF by Xiuzhang YANG, Guojun PENG, Zichuan LI, Yangqi LYU, Side LIU, Chenguang LI

“…Objectives: In the face of the complex and changing network security environment, how to fight against Advanced Persistent Threat (APT) attacks has become an urgent problem for the entire security community. …”
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Research on entity recognition and alignment of APT attack based on Bert and BiLSTM-CRF by Xiuzhang YANG, Guojun PENG, Zichuan LI, Yangqi LYU, Side LIU, Chenguang LI

“…Objectives: In the face of the complex and changing network security environment, how to fight against Advanced Persistent Threat (APT) attacks has become an urgent problem for the entire security community. …”
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NDVI Estimation Throughout the Whole Growth Period of Multi-Crops Using RGB Images and Deep Learning by Jianliang Wang, Chen Chen, Jiacheng Wang, Zhaosheng Yao, Ying Wang, Yuanyuan Zhao, Yi Sun, Fei Wu, Dongwei Han, Guanshuo Yang, Xinyu Liu, Chengming Sun, Tao Liu

“…RGB images were used to extract conventional features, including color indices (CIs), texture features (TFs), and vegetation coverage, while convolutional features (CFs) were extracted using the deep learning network ResNet50 to optimize the model. The results indicate that the model, optimized with CFs, significantly enhanced NDVI estimation accuracy. …”
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Investigation of DC-Biased Optical OFDM With Precoding Matrix for Visible Light Communications: Theory, Simulations, and Experiments by Tao Jiang, Ming Tang, Rui Lin, Zhenhua Feng, Xi Chen, Lei Deng, Songnian Fu, Xiang Li, Wu Liu, Deming Liu

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Deep Learning Ensemble Approach for Predicting Expected and Confidence Levels of Signal Phase and Timing Information at Actuated Traffic Signals by Seifeldeen Eteifa, Amr Shafik, Hoda Eldardiry, Hesham A. Rakha

“…This architecture is combined with different deep learning methods, including Multilayer Perceptrons (MLP), Long-Short-Term Memory neural networks (LSTM), and Convolutional Long-Short-Term Memory neural networks (CNNLSTM) to form an ensemble of predictors. …”
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AI-Powered Forecasting of Environmental Impacts and Construction Costs to Enhance Project Management in Highway Projects by Joon-Soo Kim

“…ANN models benefited from cross-validation and hyperparameter tuning, achieving consistent performance across training and validation sets without overfitting (MSE = 0.06, RMSE = 0.24). The optimal ANN yielded average error rates of 29.8% for EL and 21.0% for CC at the design stage. …”
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Deep Learning-Based Prediction of Pitch Response for Floating Offshore Wind Turbines by Ruifeng Chen, Ke Zhang, Min Luo, Ye An, Lixiang Guo

“…Furthermore, the model’s optimal configurations, including memory lengths, sample sizes, and optimizer, are identified through parametric studies. …”
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Dynamic Microfluidic Synthesis of Zinc Oxide Nanowires: Impact of Channel Architecture on Growth Homogeneity and Uniformity by Mazen Erfan, Martine Gnambodoe‐Capochichi, Yasser M. Sabry, Diaa Khalil, Yamin Leprince‐Wang, Tarik Bourouina

“…This is demonstrated that the use of optimized tree‐branched microchannel networks enables excellent homogeneity, quantified by a surface coverage of 99% across the whole area of the microfluidic reactor chamber, while it is limited to 55%–78% when using conventional microfluidic chambers. …”
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Advanced Self-Driving Vehicle Model for Complex Road Navigation Using Integrated Image Processing and Sensor Fusion by Kalapraveen Bagadi, Naveen Kumar Vaegae, Visalakshi Annepu, Khaled Rabie, Shafiq Ahmad, Thokozani Shongwe

“…This paper presents a sophisticated self-driving vehicle (SDV) model that addresses the challenges of navigating complex road networks characterized by high traffic and unpredictable environments. …”
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Toward generalizable prediction of antibody thermostability using machine learning on sequence and structure features by Ameya Harmalkar, Roshan Rao, Yuxuan Richard Xie, Jonas Honer, Wibke Deisting, Jonas Anlahr, Anja Hoenig, Julia Czwikla, Eva Sienz-Widmann, Doris Rau, Austin J. Rice, Timothy P. Riley, Danqing Li, Hannah B. Catterall, Christine E. Tinberg, Jeffrey J. Gray, Kathy Y. Wei

“…Further, transferring such models for alternative physicochemical properties of scFvs can have potential applications in optimizing large-scale production and delivery of mAbs or bsAbs.…”
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Integrated Analysis Reveals Genetic Basis of Growth Curve Parameters in an F₂ Designed Pig Population Based on Genome and Transcriptome Data by Zhaoxuan Che, Jiakun Qiao, Fangjun Xu, Xinyun Li, Yunxia Zhao, Mengjin Zhu

“…Five growth parameters were estimated, including initial body weight <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mo>(</mo><mi>W</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>)</mo></mrow></semantics></math></inline-formula>, instantaneous growth rate per day (<i>L</i>), coefficient of relative growth or maturing index (<i>k</i>), body weight at inflection point <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mo>(</mo><mi>W</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>)</mo></mrow></semantics></math></inline-formula>, and average growth rate (<i>GR</i>). These five parameters were subjected to a genome-wide association study, differential gene expression analysis, and weighted gene co-expression network analysis (WGCNA). …”
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A Radiogenomic Deep Ensemble Learning Model for Identifying Radionecrosis Following Brain Metastases (BM) Stereotactic Radiosurgery in Patients With Non-small Cell Lung Cancer BM by Jingtong Zhao, MS, Eugene Vaios, MD, MBA, Evan Calabrese, MD, PhD, Zhenyu Yang, PhD, Scott Robertson, PhD, John Ginn, PhD, Ke Lu, PhD, Fang-Fang Yin, PhD, Zachary Reitman, MD, PhD, John Kirkpatrick, MD, PhD, Scott Floyd, MD, PhD, Peter Fecci, MD, PhD, Chunhao Wang, PhD

“…Clinical features and molecular features were collected. A deep neural network (DNN) was trained for radionecrosis/recurrence prediction using the 3-month post-SRS T1+c magnetic resonance imaging. …”
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Urban Recreational Space Heat-Emotion Distribution and Matching Pattern Based on Machine Learning: A Case Study of Guangzhou City by Wang Fuyuan, Zhang Zhiyu, Xie Yuanjing, Yang Xinyi, Sun Miao

“…Moreover, recreational spaces situated along waterfronts and in areas with dense road networks tend to follow a "point-axis" distribution model, with a staggering 90.45% of these spaces located within a 1 km radius of the road network. (2) The overall approval rate of urban recreational spaces in Guangzhou is significantly high, evidenced by an average positive emotion ratio of 86.99%. …”
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A novel reinforcement learning framework-based path planning algorithm for unmanned surface vehicle by Jianhui Mou, Bo Shi, Bo Wang, Chengcheng Yu, Yangwei Wang, Fusheng Zhong, Li Zheng, Jian Wang, Junjie Li

“…To solve these problems, this article proposes a novel artificial potential field-heuristic reward-averaging deep Q-network (APF-RADQN) framework-based path planning algorithm, aiming at finding optimal paths for USVs. …”
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USING A NOVEL PSYCHOSOCIAL GROUP INTERVENTION TO IMPROVE ADAPTION, COPING AND MENTAL HEALTH OUTCOMES FOLLOWING DYSVASCULAR LIMB AMPUTATIONS: A FEASIBILITY STUDY by Rosalie J. Steinberg, Lawrence R. Robinson, Oksana Kachmarchuk, Sharon Jankey, Stephanie Posa, Amanda L. Mayo, Mindy Simon, Alex Kiss, Crystal Mackay, Robert Simpson, Marina B. Wasilewski, Steven Dilkas, Sander L. Hitzig

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Performance Comparison of 10 State-of-the-Art Machine Learning Algorithms for Outcome Prediction Modeling of Radiation-Induced Toxicity by Ramon M. Salazar, PhD, Saurabh S. Nair, MS, Alexandra O. Leone, MBS, Ting Xu, PhD, Raymond P. Mumme, BS, Jack D. Duryea, BA, Brian De, MD, Kelsey L. Corrigan, MD, Michael K. Rooney, MD, Matthew S. Ning, MD, Prajnan Das, MD, Emma B. Holliday, MD, Zhongxing Liao, MD, Laurence E. Court, PhD, Joshua S. Niedzielski, PhD

“…Each data set was modeled using 11 commonly employed machine learning algorithms (elastic net, least absolute shrinkage and selection operator [LASSO], random forest, random forest regression, support vector machine, extreme gradient boosting, light gradient boosting machine, k-nearest neighbors, neural network, Bayesian-LASSO, and Bayesian neural network) by randomly dividing the data set into a training and test set. …”
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Development mechanism and practical significance of deep coalbed methane (coal rock gas) infiltration and displacement by Lihong ZHOU, Xia YAN, Hongtao LIU, Xianyue XIONG, Feng WANG, Shuguang LI, Jiyuan ZHANG, Chuanqing LIU, Xiong HU, Pu YUAN, Qianli MA, Xueguang ZHU

“…Four gas production sources and the stag’s contribution were identified, leading to four optimized strategies: dense fracture networks, differentiated well shut-ins to enhance imbibition, wettability modifiers to mitigate water blockage, and controlled-pressure extended flowback. …”
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Mechanical behavior of hybrid custom implant abutments with various crown materials: a 3D finite element analysis by Pongsakorn Poovarodom, Guilherme Faria Moura, Fabio Antonio Piola Rizzante, Chaiy Rungsiyakull, Jarupol Suriyawanakul, Pimduen Rungsiyakull

“…A 200 N load was applied, and a Finite Element Analysis (FEA) assessed peak, volume average, and distribution of von Mises stress and principal stress. …”
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