Exploring Machine Learning and Deep Learning Approaches for Battery Management Systems in EVs: A Comprehensive Review by Sathish J., Ramash Kumar K., Saraswathi D.

“…Therefore, in today’s research, machine learning and deep learning algorithms are used in EV technologies to obtain a more efficient and capable system. …”
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Exploring Different Dynamics of Recurrent Neural Network Methods for Stock Market Prediction - A Comparative Study by Ajit Mohan Pattanayak, Aleena Swetapadma, Biswajit Sahoo

“…It will take past price and process it through LSTM algorithms to take a logical decision. In the quest to broaden retail participation in the capital markets, the effort is to develop an application for novice investors who either have no time in research or are the victims of financial mis-selling and enable them to leverage the technology to their advantage.…”
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Optimizing machine learning for enhanced automated ECG analysis in cardiovascular healthcare by Keyi Tang, Shuyuan Ma, Xiaohui Sun, Dongfang Guo

“…Ultimately, the findings underscore the potential of machine learning and deep learning algorithms in advancing automated ECG analysis for improved cardiovascular healthcare.…”
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An open paradigm dataset for intelligent monitoring of underground drilling operations in coal mines by Pengzhen Zhao, Xichao Wang, Shuainan Yu, Xiangqing Dong, Baojiang Li, Haiyan Wang, Guochu Chen

“…Currently, there is no comprehensive benchmark dataset for coal mine industrial scenarios, limiting the research progress of AI algorithms in this industry. …”
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Identification of biomarkers for the diagnosis of type 2 diabetes mellitus with metabolic associated fatty liver disease by bioinformatics analysis and experimental validation by Guiling Wu, Guiling Wu, Sihui Wu, Sihui Wu, Tian Xiong, Tian Xiong, Tian Xiong, You Yao, You Yao, Yu Qiu, Yu Qiu, Yu Qiu, Liheng Meng, Cuihong Chen, Xi Yang, Xi Yang, Xi Yang, Xinghuan Liang, Yingfen Qin

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Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change by Robson Mateus Freitas Silveira, Angela Maria de Vasconcelos, Concepta McManus, Luiz Paulo Fávero, Iran José Oliveira da Silva

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Harnessing the potential of human induced pluripotent stem cells, functional assays and machine learning for neurodevelopmental disorders by Ziqin Yang, Ziqin Yang, Nicole A. Teaney, Nicole A. Teaney, Elizabeth D. Buttermore, Elizabeth D. Buttermore, Elizabeth D. Buttermore, Mustafa Sahin, Mustafa Sahin, Mustafa Sahin, Wardiya Afshar-Saber, Wardiya Afshar-Saber

“…Recent progress in machine learning (ML) algorithms also presents unprecedented opportunities to advance the NDD research process. …”
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Reinforcement Learning Solutions for Microgrid Control and Management: A Survey by Pedro I. N. Barbalho, Anderson L. Moraes, Vinicius A. Lacerda, Pedro H. A. Barra, Ricardo A. S. Fernandes, Denis V. Coury

“…It is an alternative to traditional algorithms and control methods in tasks, such as load frequency control, resource allocation, and energy management. …”
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Permanent terrestrial laser scanning for near-continuous environmental observations: Systems, methods, challenges and applications by Roderik Lindenbergh, Katharina Anders, Mariana Campos, Daniel Czerwonka-Schröder, Bernhard Höfle, Mieke Kuschnerus, Eetu Puttonen, Rainer Prinz, Martin Rutzinger, Annelies Voordendag, Sander Vos

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Early detection and analysis of accurate breast cancer for improved diagnosis using deep supervised learning for enhanced patient outcomes by Mandika Chetry, Ruiling Feng, Samra Babar, Hao Sun, Imran Zafar, Mohamed Mohany, Hassan Imran Afridi, Najeeb Ullah Khan, Ijaz Ali, Muhammad Shafiq, Sabir Khan

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Development of Smart Models to Accurately Predict Dynamic Viscosity of CO2-Saturated Polyethylene Glycol by Ayat Hussein Adhab, Morug Salih Mahdi, Bhavesh Kanabar, Anupam Yadav, Ranganathaswamy M K, Rishabh Thakur, Parveen Kumar, Braj Krishna, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

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Associations between organophosphorus pesticides exposure and age-related macular degeneration risk in U.S. adults: analysis from interpretable machine learning approaches by Yu-Xin Jiang, Si-Yu Gui, Xiao-Dong Sun

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A risk prediction system for depression in middle-aged and older adults grounded in machine learning and visualization technology: a cohort study by Jinsong Du, Jinsong Du, Jinsong Du, Xinru Tao, Le Zhu, Wenhao Qi, Xiaoqiang Min, Xiaoqiang Min, Hongyan Deng, Shujie Wei, Xiaoyan Zhang, Xiao Chang

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Control and diagnostics of faults in hardware-software complex by D. A. Pankov, L. A. Denisova

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DigiRhythm: An R package for evaluating circadian rhythmicity in animals using the degree of functional coupling by Hassan-Roland Nasser, Marianne Cockburn, Marie Schneider

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Practical Implementation of Unconditionally Secure File Transfer Application with QKD and OTP by Alin-Bogdan Popa, Bogdan-Calin Ciobanu, Pantelimon George Popescu

“…With the looming threat of quantum computers capable of breaking classical encryption and the uncertainty regarding the security of post-quantum encryption algorithms, some highly sensitive applications aim for the highest level of security in information transfer: unconditional security. …”
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Bottlenose dolphin identification using synthetic image-based transfer learning by Changsoo Kim, Byung-Yeob Kim, Dong-Guk Paeng

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A Social Media Sentiment Analysis Using Machine Learning Approaches by Noor Salah Irzooqi Al-Agele, Didem KIVANÇ TÜRELİ

“…With consideration for the most suitable models for precisely classifying sentiments within social media data, this study aims to evaluate the efficacy of machine learning algorithms in analyzing sentiment text that people post or comment on Twitter, thus bridging the research gap in the analysis of sentiment in an understudied domain. a set of machine learning algorithms was applied along with feature extraction methods, including TF-IDF and Natural Language Processing (NLP). …”
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Optimized customer churn prediction using tabular generative adversarial network (GAN)-based hybrid sampling method and cost-sensitive learning by I Nyoman Mahayasa Adiputra, Paweena Wanchai, Pei-Chun Lin

“…Utilizing a cost-sensitive learning perspective, this research aims to enhance the performance of several classical machine learning algorithms in customer churn prediction tasks. …”
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Revolutionizing climbing perch disease management: AI-Driven solutions for sustainable aquaculture by Kosit Sriputhorn, Rapeepan Pitakaso, Surasak Matitopanum, Peerawat Luesak, Surajet Khonjun, Rungwasun Kraiklang, Chakat Chueadee, Sarayut Gonwirat

“…This system uniquely combines non-population based differential evolution algorithms for optimizing the mix of image augmentation techniques, with population-based algorithms for integrating image segmentation and convolutional neural network (CNN) architectures. …”
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