Leveraging LSTM and ensemble classifiers for enhanced food waste classification by Khalaf Alsalem

“…Abstract A long short-term memory (LSTM)-enhanced feature extraction technique was combined with ensemble classifiers (gradient boosting, logistic regression, random forest, and support vector machine (SVM)) to improve waste classification outcomes. …”
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Intelligent Functions Development on Autonomous Electric Vehicle Platform by Ruxin WANG, Raivo SELL, Anton RASSOLKIN, Tauno OTTO, Ehsan MALAYJERDI

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Artificial intelligence and robotics in education: Advances, challenges, and future perspectives by Javier Fombona, Jose-Manuel Sáez, Susana Sánchez

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Big Data in Neuroscience: Transforming Research and the Understanding of Brain Function by Adina DZIŢAC

“…Since the year 2000, artificial intelligence and machine learning have transformed neuroscience research and have revolutionized data analysis and made it possible for researchers to discover complex patterns in brain activity, relating this to neurological disorders and cognitive functions. …”
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Mind wandering in sensory cortices by Shao-Min Hung, Po-Jang Hsieh

“…Unique patterns in classification were revealed in different individuals, pointing to individual variances in our phenomenal experiences.…”
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Definition of innovation problems in organizations using data analysis tasks from hybrid sources: social networks and organizational databases by Ana Gutiérrez, Jose Aguilar, Ana Ortega, Edwin Montoya

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Identification and validation of glycosylation-related gene signatures for prognostic stratification in sepsis by Chunyang Li, Haiyan Xue, Haiyan Xue, Lihe Chen, Fengxue Zhu, Jie Li

“…This study explored the role of glycosylation-related genes in sepsis through bioinformatics analysis and machine learning, and validated the expression value of the key genes. …”
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Socioeconomic status (SES) and cognitive outcomes are predicted by resting-state EEG in school-aged children by Julie M. Schneider, Jeahong Kim, Sonali Poudel, Yune S. Lee, Mandy J. Maguire

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Explainable and Interpretable Model for the Early Detection of Brain Stroke Using Optimized Boosting Algorithms by Yogita Dubey, Yashraj Tarte, Nikhil Talatule, Khushal Damahe, Prachi Palsodkar, Punit Fulzele

“…The stroke pre-diction using optimized boosting machine learning algorithms is supported with explainable AI using LIME and SHAP. …”
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Enhancing Cloud Job Failure Prediction With a Novel Multilayer Voting-Based Framework by Ahmed Elkaradawy, Ayman Elshenawy, Hany Harb

“…To address this challenge, researchers have progressively developed machine learning and deep learning techniques that examine cloud logs to identify patterns linked to such failures. …”
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Application of Discrete Element Method to Potato Harvesting Machinery: A Review by Yuanman Yue, Qian Zhang, Boyang Dong, Jin Li

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Landslide data sample augmentation and landslide susceptibility analysis in Nyingchi City based on the MCMC model by Lianchen Liu, Peiqing Wang, Libin Su, Feng Li

“…The quality of the generated samples was validated using a Support Vector Machine (SVM) classifier. Further sensitivity analysis and susceptibility modeling were conducted using both the original and augmented datasets. …”
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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

“…Recent advances in artificial intelligence—especially machine learning (ML), deep learning (DL), and pattern recognition—offer game-changing opportunities to accelerate AMP design and validation. …”
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Hybrid Android Malware Detection and Classification Using Deep Neural Networks by Muhammad Umar Rashid, Shahnawaz Qureshi, Abdullah Abid, Saad Said Alqahtany, Ali Alqazzaz, Mahmood ul Hassan, Mana Saleh Al Reshan, Asadullah Shaikh

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Study of ESG transformation of the region by the artificial intelligence system by Nikolay I. Lomakin, Tatyana I. Kuzmina, Maxim S. Maramygin, Olga V. Yurova, Oksana A. Minaeva, Aleksey A. Polozhentsev, Tamila D. Eliseeva

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Epigenetic profiling for prognostic stratification and personalized therapy in breast cancer by Xiao Guo, Chuanbo Feng, Jiaying Xing, Yuyan Cao, Tengda Liu, Wenchuang Yang, Runhong Mu, Tao Wang

“…Epigenetic changes play a critical role in breast cancer progression and therapy responses, providing a foundation for prognostic model development.MethodsWe developed the Machine Learning-derived Epigenetic Model (MLEM) to identify prognostic epigenetic gene patterns in breast cancer. …”
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A 36-year geospatial analysis of urbanization dynamics and surface urban heat island effect: Case study of the Bangkok Metropolitan Region by Nattapong Puttanapong, Nithima Nuengjumnong, JoJinda SaeJung, Sitthisak Moukomla

“…(3) How effectively can machine learning models classify LULC changes and provide insights to support sustainable urban planning? …”
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Neural network analysis of mortality risk predictors in patients after acute coronary syndrome by D. A. Shvets, A. Yu. Karasev, M. V. Smolyakov, S. V. Povetkin, V. I. Vishnevsky

“…To predict mortality risk, the machine learning method and neural network analysis was used. …”
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Automated Cough Analysis with Convolutional Recurrent Neural Network by Yiping Wang, Mustafaa Wahab, Tianqi Hong, Kyle Molinari, Gail M. Gauvreau, Ruth P. Cusack, Zhen Gao, Imran Satia, Qiyin Fang

“…In this study, we developed a machine learning model for the detection and classification of cough sounds. …”
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Analysis to Predict the Number of New Students At UNU Pasuruan using Arima Method by Fachri Ayudi Fitrony, Laksmita Dewi Supraba, Tessa Rantung, I Made Artha Agastya, Kusrini Kusrini

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