Multimodal Detection of Agitation in People With Dementia in Clinical Settings: Observational Pilot Study by Abeer Badawi, Somayya Elmoghazy, Samira Choudhury, Sara Elgazzar, Khalid Elgazzar, Amer M Burhan

“…Facial features in video frames were anonymized using a masking tool, and a deep learning model was used for AA detection. To determine optimal performance, various machine learning and deep learning models were evaluated for both wearable and video data streams. …”
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Influence of Light Regimes on Production of Beneficial Pigments and Nutrients by Microalgae for Functional Plant-Based Foods by Xiang Huang, Feng Wang, Obaid Ur Rehman, Xinjuan Hu, Feifei Zhu, Renxia Wang, Ling Xu, Yi Cui, Shuhao Huo

“…Artificial intelligence (AI) and machine learning (ML) models have emerged as pivotal tools for intelligent microalgal cultivation. …”
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Automatic Detection and Classification of Natural Weld Defects Using Alternating Magneto-Optical Imaging and ResNet50 by Yanfeng Li, Pengyu Gao, Yongbiao Luo, Xianghan Luo, Chunmei Xu, Jiecheng Chen, Yanxi Zhang, Genxiang Lin, Wei Xu

“…Principal component analysis (PCA) is employed to extract column vector features from the downsampled defect MO images, which then serve as the input layer for the error backpropagation (BP) neural network model and the support vector machine (SVM) model. …”
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Detection of the Pigment Distribution of Stacked Matcha During Processing Based on Hyperspectral Imaging Technology by Qinghai He, Zhiyuan Liu, Xiaoli Li, Yong He, Zhi Lin

“…This study enhances pigment detection efficiency in tea processing, supports process optimization, and aids in quality control.…”
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Predicting the Rheological Performance of Self-Compacting Mortar and Concrete Using Artificial Neural Network by Andreas Kounadis, Angelos Galatis, Agapoula Papakonstantinou, Efstratios Badogiannis

“…The model architecture was optimized through multiparametric analysis, testing around 22,000 models to achieve approximately 85% prediction accuracy. …”
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βFSCM: An enhanced food supply chain management system using hybrid blockchain and recommender systems by Feiyang Sun, Peiyu Wang, Yihan Zhang, Pushpendu Kar

“…Furthermore, the integration of a recommender system is proposed to utilize data analytics and machine learning for personalizing product offerings and optimizing inventory management, aiming to boost efficiency and consumer satisfaction. …”
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A Multi-Mode Dynamic Fusion Mach Number Prediction Framework by Luping Zhao, Weihao Li, Wentao Xu

“…Although existing studies have improved prediction accuracy to some extent through machine learning methods, they generally neglect the multi-mode characteristics of complex wind tunnel systems, limiting the generalizability of the models. …”
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Research Framework and Anticipated Results of Key Technologies for Distributed Certificate-less Network Identity Systems by ZHANG Xiaosong, CAO Sheng, LU Tianbo, YANG Kun, GUI Xun, XIE Guotao, NIU Weina

“…This project provides theoretical models and technical methods for digital identity authentication that are suitable for large-scale IoT identity authentication by constructing a high-performance hardware layer and developing multi-level smart contract virtual machines. …”
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Civil Aircraft Landing Attitude Ultra-Limit Warning System Based on mRMR-LSTM by Fei Lu, Tong Jing, Chunsheng Xie, Haonan Chen

“…Subsequently, through data pretreatment methods such as data cleaning, frequency normalization, data standardization, and feature classification, the experimental dataset is transformed into a form recognizable by machine learning algorithms and neural network models. …”
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LSTM-based framework for predicting point defect percentage in semiconductor materials using simulated XRD patterns by Mehran Motamedi, Reza Shidpour, Mehdi Ezoji

“…The model’s mean absolute error at 4500 units was 0.021, the lowest among the LSTM configurations tested. …”
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Enhancing Sentiment and Emotion Classification with LSTM-Based Semi-Supervised Learning by Rochmat Husaini, Nur Heri Cahyana, Wisnalmawati Wisnalmawati, Tri Mardiana, Yuli Fauziah

“…The performance of the pseudo-labels was evaluated using Random Forest, Logistic Regression, and Support Vector Machine (SVM). The LSTM model demonstrated varying effectiveness across different datasets. …”
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Research of the Law and Control Method of Automatic Shift for Engineering Vehicle by Ying Chen

“…In order to reduce the fuel consumption rate of the engine and improve the efficiency of the transmission system, the optimal power shift path is calculated. The dynamic model of engineering vehicle transmission system is established and the dynamic shift strategy is simulated. …”
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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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Options for postoperative radiation therapy in patients with de novo metastatic breast cancer by Chaofan Li, Yusheng Wang, Biyun Fang, Mengjie Liu, Shiyu Sun, Jingkun Qu, Shuqun Zhang, Chong Du

“…Conclusion: This study is the first to propose a risk stratification strategy for postoperative RT in dnMBC, and innovatively integrates machine learning and clinical tools to provide a new paradigm for optimizing precision therapy.…”
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iSeizdiag: toward the framework development of epileptic seizure detection for healthcare by Ashish Sharma, Ashish Sharma, Akshat Saxena, Mradul Agrawal, Kunal Kishor, Deepti Kaushik, Prateek Jain, Arvind R. Yadav, Manob Jyoti Saikia, Manob Jyoti Saikia

“…Different neurological disorders are represented as different waves on EEG records.MethodThis paper involves the detection of Epilepsy which appears as rapid spiking on electroencephalogram signals, using feature extraction and machine learning techniques. Various models, such as the Support Vector Machine, K Nearest Neighbor, and random forest, have been trained, and accuracy has been analyzed to predict the seizure.ResultAn average accuracy of 95% has been claimed using the optimized model for epileptic seizure detection during training and validation. …”
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Design and Experiment of a Hard-Shell Clam Harvester by Haiyun Wu, Xiaomeng Wang, Bing Huang, Shide Li, Jincheng Hu, Shancan Fu, Lei Yang, Mengxiang Cui, Zhenwei Chen, Yanan Zeng, Yongcheng Jiang, Tao Zhang

“…To optimize the efficiency of the machine, a Discrete Element Method (DEM) simulation trial was conducted through a three-factor three-level experiment using EDEM software. …”
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A new signature associated with anoikis predicts the outcome and immune infiltration in nasopharyngeal carcinoma by Yonglin Luo, Wenyang Wei, Yaxuan Huang, Jun Li, Weiling Qin, Quanxiang Hao, Jiemei Ye, Zhe Zhang, Yushan Liang, Xue Xiao, Yonglin Cai

“…Results Three differentially expressed ARGs (CDC25C, E2F1 and RBL2) with prognostic value were identified by the intersection of multiple machine learning algorithms. A risk score based on t 3-ARG feature was developed to stratify NPC patients into two distinct risk groups using the optimal model, Random Survival Forest. …”
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Surface Soil Organic Carbon Estimation Based on Habitat Patches in Southwest China by Jieyun Xiao, Wei Zhou, Ting Wang, Yao Peng, Zhan Shi, Saibo Li, Yang Li, Tianxiang Yue

“…Utilizing multisource data and three machine learning models, we estimated soil organic carbon (SOC) content in southwest China. …”
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Mechanical behavior of material removal under various rake angle diamond tool ultra-precision cutting of titanium alloy by Lingyi Sun, Xin Cui, Chunjin Wang, Yanbin Zhang, Changhe Li

“…Understanding their material removal mechanisms enables optimization of machining parameters, enhancement of surface quality, expansion of advanced processing techniques, and fulfillment of performance demands in high-end applications. …”
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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…The collected data established relationships between visited domains, generated cookies, and captured traffic, providing a solid foundation for security and privacy analysis. Machine learning models were developed to classify suspicious web domains and predict their vulnerability to XSS attacks. …”
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