Innovation of Urban Circular Economy Growth Path Based on Neural Network by Weifeng Qiu, Yi Yang

“…Moreover, it has obvious advantages over the traditional algorithm in terms of error and recall rate. Compared with the actual economic data, the economic data predicted by the model is quite consistent, and the prediction of future data by the model basically accords with the development goal of the regional master plan. …”
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The role of artificial intelligence in promoting health and developing preventive strategies for diabetes by Ameneh Marzban

“…Dear Editor Diabetes remains a significant public health challenge, and the integration of artificial intelligence (AI) presents remarkable opportunities to enhance early diagnosis, personalized treatment, and effective prevention strategies.1 AI algorithms, including supervised learning and convolutional neural networks, can efficiently analyze large datasets to identify patterns and risk factors associated with diabetes, surpassing the capabilities of traditional methods.2 This advanced analysis enables healthcare providers to predict the likelihood of diabetes in individuals and populations, facilitating timely interventions and customized prevention strategies. …”
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Preface to Special Issue on AI-Based Future Intelligent Networks and Communication Security by Sunil Kumar, Glenford Mapp, Abhay Bansal, Korhan Cengiz

“… Recent advancements in science focus on the study and development of algorithms that can learn from and make predictions and decisions based on data collected through intelligent devices. …”
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Identification of biomarkers associated with inflammatory response in Parkinson's disease by bioinformatics and machine learning. by Yatan Li, Wei Jia, Chen Chen, Cheng Chen, Jinchao Chen, Xinling Yang, Pei Liu

“…LASSO, SVM-RFE and Random Forest algorithms were used to screen biomarker genes. Then, ROC curves were drawn and PD risk predicting models were constructed on the basis of the biomarker genes. …”
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Efficient topology control for time-varying spacecraft networks with unreliable links by Wei Zhang, Hong Ma, Tao Wu, Xueshu Shi, Yiwen Jiao

“…In this article, we investigate the topology control problem in spacecraft networks where the time-varying topology can be predicted. We first develop a model that formalizes the time-varying spacecraft network topologies as a directed space–time graph. …”
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A novel deep learning approach to identify embryo morphokinetics in multiple time lapse systems by Guillaume Canat, Antonin Duval, Nina Gidel-Dissler, Alexandra Boussommier-Calleja

“…Today, most of the literature has characterized algorithms that predict pregnancy, ploidy or blastocyst quality, leaving to the side the task of identifying key morphokinetic events. …”
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Analysis of the Influence of Software and Hardware Noise on the Results of Digital Signal Processing by A. V. Sharamet

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Acute Respiratory Infections Identification With Cough Sounds and Overlapping Patch Modulated Vision Transformers by P. V. V. Kishore, D. Anil Kumar, Pasupuleti Sasikiran, Kaja Krishna Mohan, P. Praveen Kumar, Mogadala Vinod Kumar

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Analisis Buku “Mari Belajar Matematika” Karya Dewi Nuharini dan Sulis Priyanto Tahun 2017 by Arum Weni, Ryky Mandar Sary, Veryliana Purnamasari

“…This study aims to determine how complete the material in the textbook for the subject "Let's Learn Mathematics (Mathematics Education for Grade V SD/MI)" is by Dewi Nuharini and Sulis Priyanto in 2017. …”
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Multimorbidity of cardiometabolic diseases: a cross-sectional study of patterns, clusters and associated risk factors in sub-Saharan Africa by Charles Agyemang, Frederick Wekesah, Calistus Wilunda, Gershim Asiki, Peter Otieno, Richard E Sanya, Welcome Wami

“…Being female (PR=1.7, 95% CI (1.5 to 2.0), middle-aged (35–54 years) (3.9 (95% CI 3.2 to 4.8)), compared with age 15–34 years, employed (1.2 (95% CI 1.1 to 1.4)), having tertiary education (2.5 (95% CI 2.0 to 3.3)), vs no formal education and clustering of physical inactivity and obesity (2.4 (95% CI 2.0 to 2.8)) were associated with a higher likelihood of cardiometabolic multimorbidity.Conclusion Our findings show that cardiometabolic multimorbidity and lifestyle risk factors cluster in distinct patterns with a disproportionate burden among women, middle-aged, persons in high socioeconomic positions, and those with sedentary lifestyles and obesity. …”
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Recognition and management of auditory verbal hallucinations in borderline personality disorder by M. B. A. Niemantsverdriet, M. B. A. Niemantsverdriet, C. W. Slotema, C. W. Slotema, I. H. A. Franken, J. Brandsma, M. J. P. M. Verbraak, M. L. Deen, J. D. Blom, J. D. Blom, J. D. Blom, M. Van der Gaag

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Bean leaf image dataset annotated with leaf dimensions, segmentation masks, and camera calibrationMendeley Data by Karla Gabriele Florentino da Silva, Paulo Victor de Magalhães Rozatto, Kaio de Oliveira e Sousa, Lucas Dias Hudson, Artur Welerson Sott Meyer, Alemilson Fabiano Silva, Igor Tibiriçá Mendes, Alex Rodrigues Borges, Leandro Elias Morais, Luiz Maurílio da Silva Maciel, Saulo Moraes Villela, Helio Pedrini, Marcelo Bernardes Vieira

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The hermeneutic circle as a means of illustration of the understanding problem when teaching didactic communications by E. E. Neupokoeva, N. K. Chapaev

“…The digitalisation of the education system has increased the importance of acquiring digital competencies. …”
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An Optimal Internet of Things-Driven Intelligent Decision-Making System for Real-Time Fishpond Water Quality Monitoring and Species Survival by Saima Kanwal, Muhammad Abdullah, Sahil Kumar, Saqib Arshad, Muhammad Shahroz, Dawei Zhang, Dileep Kumar

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Modelling and Output Power Estimation of a Combined Gas Plant and a Combined Cycle Plant Using an Artificial Neural Network Approach by Vasileios Xezonakis, Olusegun David Samuel, Christopher Chintua Enweremadu

“…Researchers, academicians, and stakeholders have been unable to predict, ensure effective operation, and prevent power outages in COGAS due to the nonlinearity. …”
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Network archaeology: uncovering ancient networks from present-day interactions. by Saket Navlakha, Carl Kingsford

“…Finally, we infer plausible parameters for the model, thereby predicting the relative probability of various evolutionary events. …”
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Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…Machine Learning algorithms are widely used in various fields due to their strong capability to extract and display high-level features of training samples. …”
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Homogenization of Heterogeneous Tissue Scaffold: A Comparison of Mechanics, Asymptotic Homogenization, and Finite Element Approach by Z. Fang, C. Yan, W. Sun, A. Shokoufandeh, W. Regli

“…Actual prediction of the effective mechanical properties of tissue scaffolds is very important for tissue engineering applications. …”
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Prevalence estimates of trafficking in persons using statistical definitions: a cross-sectional high-risk community survey in Cape Town, South Africa by Rumi Kato Price, Annah K Bender, Floriana H Milazzo, Edna G. Rich, Nicolette V. Roman, Sheldon X Zhang, Erica L Koegler

“…Several screener items were shown less predictive of the PRIF statistical definition criteria than others.Conclusions Prevalence estimates of probable TIP were higher than those reported elsewhere. …”
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The role of hypoxia-senescence co-related molecular subtypes and prognostic characteristics in hepatocellular carcinoma by Fuqing Chen, Yifan Cai, Xiangmei Chen, Changzhou Chen, Qinliang Fang, Jianming Liu, Yibin Zhang, Jianyin Zhou

“…The prediction model based on HSCRGs was established by LASSO, univariate and multivariate COX regression analysis. …”
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