Crowd Evacuation in Stadiums Using Fire Alarm Prediction by Afnan A. Alazbah, Osama Rabie, Abdullah Al-Barakati

“…This study introduces an AI-driven predictive fire alarm and evacuation model that leverages machine learning algorithms and real-time environmental sensor data to anticipate fire hazards before ignition, improving emergency response efficiency. …”
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A XGBoost-Based Prediction Method for Meat Sheep Transport Stress Using Wearable Photoelectric Sensors and Infrared Thermometry by Ruiqin Ma, Runqing Chen, Buwen Liang, Xinxing Li

“…The results show that SVC and GBDT algorithms are more effective and the overall model classification accuracy reached 86.44% and 91.53%. …”
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Siamese Denoising Autoencoders for Enhancing Adversarial Robustness in Medical Image Analysis by Jaesung Shim, Kyuri Jo

“…Experiments on Chest X-ray, Brain MRI, Retina, and Skin images, using FGSM, PGD, DeepFool, CW, SPSA, and AutoAttack adversarial algorithms, demonstrate that the Siamese-DAE, trained to remove noise, effectively eliminates perturbations, leading to improved classification accuracy compared not only to the standard classification model but also to relevant denoising defense models.…”
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Monitoring of vegetation chlorophyll content in photovoltaic areas using UAV-mounted multispectral imaging by Ming Li, Weiyi Wang, Haoran Li, Zekun Yang, Jianjun Li

“…Moreover, the fusion of vegetation indices and texture features effectively improved the accuracy of chlorophyll inversion models; among the six regression algorithms tested, the multilayer perceptron model achieved the highest performance (R² = 0.874, RMSE = 3.725, MAPE = 3.982%). …”
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Fault analysis of railway track superstructure using time-frequency method from vibrational data by Shahzor Memon, Imtiaz Hussain, Lubna Moin

“…The safety and operational efficiency of railroads could be improved by further research that combines these time-frequency characteristics with machine learning algorithms to increase fault detection accuracy and create monitoring systems for more effective proactive maintenance.…”
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Estimating Self-Confidence in Video-Based Learning Using Eye-Tracking and Deep Neural Networks by Ankur Bhatt, Ko Watanabe, Jayasankar Santhosh, Andreas Dengel, Shoya Ishimaru

“…The outcomes of this research pave the way for more personalized and effective educational interventions, ultimately contributing to improved learning experiences and outcomes.…”
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PTK6 mediated immune signatures revealed by single cell transcriptomic and multi omics big data analysis in cervical cancer by Fen Zhao, Huanxin Zhong, Lifang You, Yi Du, Changchang Huang

“…Fifteen machine learning algorithms constructed prognostic models using immune infiltration-related genes. …”
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Enhancing SQL Learning: Gamified tutorials and flipped classroom synergy by Sandor Kiraly, Tamas Balla, Dora Kiraly, Geoffrey Vaughan

“…Teaching students to think algorithmically is a common goal for school educators; however, SQL's declarative nature demands a distinct approach to problem-solving. …”
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Facilitating real-time LED-based photoacoustic imaging with DenP2P: An optimized conditional generative adversarial deep learning solution by Avijit Paul, Srivalleesha Mallidi

“…Signal quality can be improved by traditional noise removal algorithms, but deep learning models outperform non-learning methods. …”
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Obesity Status Prediction Through Artificial Intelligence and Balanced Label Distribution Using SMOTE by Arif Riyandi, Mahazam Afrad, M Yoka Fathoni, Yogo Dwi Prasetyo

“…Despite these improvements, KNN remained the least effective. The findings underscore the critical role of SMOTE in improving AI model accuracy for obesity prediction and highlight Random Forest as the most reliable algorithm for clinical decision-making. …”
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Direction of Arrival Estimation for Coherent Signals’ Method Based on LSTM Neural Network by Thanh Han-Trong, Nam Ngo Duc, Hung Tran Van, Hung Pham-Viet

“…In this study, we propose a method to estimate the DOA by using the simulated signal dataset obtained at the linear antenna array (ULA) and the suitable Long Short-Term Memory (LSTM) network model. The performance of the method is evaluated based on the root mean square error (RMSE) parameter and then is compared with 2 other algorithms, multiple signal classification (MUSIC) and deep neural network (DNN) in different cases such as deviation of incoming signals, variation of signal-to-noise ratio (SNR), and coherent incoming signals. …”
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Predicting Survival Rates in Brain Metastases Patients from Non‐Small Cell Lung Cancer Using Radiomic Signatures Associated with Tumor Immune Heterogeneity by Fuxing Deng, Gang Xiao, Guilong Tanzhu, Xianjing Chu, Jiaoyang Ning, Ruoyu Lu, Liu Chen, Zijian Zhang, Rongrong Zhou

“…Bidirectional stepwise logistic regression is employed to identify significant variables, facilitating the construction of a prognostic model, which is benchmarked against four machine learning algorithms. …”
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Study on the Trajectory Planning Method for High Bearing Capacity of Joint Manipulator by Tang Runzhi, Li Tiejuni, Yang Dongi

“…Aiming at the problem of low deadweight ratio of load in joint manipulator，two trajectory planning methods to improve the bearing capacity of the joint manipulator are proposed. …”
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Keyword spotting system for broadcast news by ZHANG Peng-yuan, SHAO Jian, ZHAO Qing-wei, YAN Yong-hong

“…A two-step keyword spotting strategy was presented.This strategy allowed to change keyword list conven-iently.Different from the previous systems,search space was generated based on all Chinese syllables,not specifically for keywords.Phoneme recognition was performed without any lexical constraints.With 1-best phoneme sequence and keyword list,which generated keyword hypotheses.At last,two confidence measures were introduced adopted in the sys-tem: one based on acoustic model and the other based on phoneme lattice.For a decoded speech frame aligned to an HMM state,the acoustic confidence was calculated.The lattice confidence made use of phoneme lattices generated by a phoneme recognizer.These two confidence measures were combined using a weighting factor to obtain a hybrid confi-dence as they had different dynamic scales.Experiments show that the proposed algorithms significantly improve the system performance on the broadcast news task.…”
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Keyword spotting system for broadcast news by ZHANG Peng-yuan, SHAO Jian, ZHAO Qing-wei, YAN Yong-hong

“…A two-step keyword spotting strategy was presented.This strategy allowed to change keyword list conven-iently.Different from the previous systems,search space was generated based on all Chinese syllables,not specifically for keywords.Phoneme recognition was performed without any lexical constraints.With 1-best phoneme sequence and keyword list,which generated keyword hypotheses.At last,two confidence measures were introduced adopted in the sys-tem: one based on acoustic model and the other based on phoneme lattice.For a decoded speech frame aligned to an HMM state,the acoustic confidence was calculated.The lattice confidence made use of phoneme lattices generated by a phoneme recognizer.These two confidence measures were combined using a weighting factor to obtain a hybrid confi-dence as they had different dynamic scales.Experiments show that the proposed algorithms significantly improve the system performance on the broadcast news task.…”
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A DSP–FPGA Heterogeneous Accelerator for On-Board Pose Estimation of Non-Cooperative Targets by Qiuyu Song, Kai Liu, Shangrong Li, Mengyuan Wang, Junyi Wang

“…Instruction-level control supports model generalization, while a weight concatenation strategy improves resource utilization during convolution. …”
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MISHTI study evaluating hepatic fibrosis in type 2 diabetes patients in India by Debasis Datta, Krishna G. Seshadri, Samit Ghosal

“…Logistic regression highlighted BMI, AST, and HbA1c as key predictors of fibrosis, emphasising the need to combine non-invasive tools with clinical variables for more accurate risk stratification and improved management of MASLD. Future research should focus on refining diagnostic algorithms to better address the burden of significant fibrosis in at-risk populations.…”
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Obfuscated malicious traffic detection based on data enhancement by Ke Ye, Tao Zeng, Yubing Duan, Jun Han, Guoxin Zhong, Zhi Chen, Yulong Wang

“…By introducing noise during the training phase, the robustness of the model is improved. To validate the effectiveness of RobustDetector, we conducted extensive experiments using public datasets. …”
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The Influence of Process and Slag Parameters on the Liquid Slag Layer in Continuous Casting Mold for Large Billets by Zhijun Ding, Chao Wang, Xin Wang, Pengcheng Xiao, Liguang Zhu, Shuhuan Wang

“…To optimize the flow and heat transfer behavior in the mold, a three-dimensional numerical model was developed based on the VOF multiphase flow model, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>k</mi><mo>−</mo><mi>ϵ</mi></mrow></semantics></math></inline-formula> RNG turbulence model, and DPM discrete phase model, employing the finite volume method with SIMPLEC algorithm for solution. …”
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Machine learning-based prediction method for open-pit mining truck speed distribution in manned operation by Changyou XU, Gang CHEN, Qiuxia ZHANG, Bo WANG, Hongwang ZHANG, Hongrui LI, Weiwei QIN, Muyang LI

“…Among these models, the Random Forest-based model exhibited lower mean squared error and a higher coefficient of determination, outperforming the XGBoost-based model. …”
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