Introducing a Novel Method for Determining the Future Price of the Financial Markets: A Case Study of the Hang Seng Index by Afreen Akashi, Md Sanadiule Ullash, Apurba Das

“…While stock market investing offers long-term profit potential, predicting future trends remains a challenge in part because of the dynamic and volatility character of financial markets. …”
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Chronic liver disease detection using ranking and projection-based feature optimization with deep learning by Sumaiya Noor, Salman A. AlQahtani, Salman Khan

“…Early detection of liver conditions is crucial, and recent advancements in machine learning (ML) have proven highly effective in predicting diseases like chronic obstructive pulmonary disease (COPD), hypertension, and diabetes. …”
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Integrating Machine Learning for Enhanced Agricultural Productivity: A Focus on Bananas and Arecanut in the Context of India’s Economic Growth by B. S. Saruk, G. Mokesh Rayalu

“…Abstract Agriculture is one of the sectors that has an important impact, taking into account the problem of sufficient food supply on a global level. The process of predicting the yield of crops is among the most challenging undertakings in the agricultural industry. …”
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A Three-Dimensional Ply Failure Model for Composite Structures by Maurício V. Donadon, Sérgio Frascino M. de Almeida, Mariano A. Arbelo, Alfredo R. de Faria

“…A fully 3D failure model to predict damage in composite structures subjected to multiaxial loading is presented in this paper. …”
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European sovereign debt control through reinforcement learning by Tato Khundadze, Willi Semmler, Willi Semmler, Willi Semmler

“…We demonstrate that the Soft Actor-Critic algorithm provides comparable or, in some cases, better solutions to multi-objective macroeconomic optimization problems, in comparison to Nonlinear Model Predictive Control (NMPC) algorithm.…”
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Mining patterns of comorbidity evolution in patients with multiple chronic conditions using unsupervised multi-level temporal Bayesian network. by Syed Hasib Akhter Faruqui, Adel Alaeddini, Carlos A Jaramillo, Jennifer S Potter, Mary Jo Pugh

“…Our findings show that the unsupervised approach has noticeably accurate predictive performance that is comparable to the best performing semi-supervised and the second-best performing supervised approaches. …”
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Role of Machine Learning in Liquid Biopsy of Brain Tumours by Zanib Javed, Saqib Kamran Bakhshi, Saad Akhtar Khan, Muhammad Shahzad Shamim

“…Multiple tumour-derived materials like circulating tumour cells (CTCs), tumour-educated platelets (TEPs), cell-free DNA (cfDNA), circulating tumour DNA (ctDNA), and miRNA are studied in CSF, blood (plasma, serum) or urine. …”
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Evaluating the spatiotemporal patterns of GPP and tree growth for their response to CO2 fertilization effects in mid-latitude forests of China by Bin Wang, Xiangqi Kong, Shaojie Bian, Ying Quan, Zechuan Wu, Jianyang Liu, Mingze Li

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Analysis of Multimedia Combination-Assisted English Teaching Mode Based on Computer Platform by Yitian Zhang, Na Li

“…It also uses the ConvLSTM algorithm and the CF algorithm to implement the active recommendation function of English knowledge. …”
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Peer-to-peer energy trading with energy trading consistency in interconnected multi-energy microgrids: A multi-agent deep reinforcement learning approach by Yang Cui, Yang Xu, Yijian Wang, Yuting Zhao, Han Zhu, Dingran Cheng

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Real-time traffic enhancement scheduling for train communication networks based on TSN by Deqiang He, Zeqian Chen, Daliang Sun, Zhenzhen Jin, Yanjun Chen, Rui Ma, Chen Liang

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Boosting Barlow Twins Reduced Order Modeling for Machine Learning‐Based Surrogate Models in Multiphase Flow Problems by T. Kadeethum, V. L. S. Silva, P. Salinas, C. C. Pain, H. Yoon

“…To address the challenge of high contrast data in multiphase flow problems due to injection wells and faults, we employ a boosting algorithm within BBT‐ROM. This algorithm sequentially trains a set of weak models (i.e., inaccurate models), improving prediction accuracy through ensemble learning. …”
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A peer-support lifestyle intervention for preventing type 2 diabetes in India: A cluster-randomized controlled trial of the Kerala Diabetes Prevention Program. by Kavumpurathu R Thankappan, Thirunavukkarasu Sathish, Robyn J Tapp, Jonathan E Shaw, Mojtaba Lotfaliany, Rory Wolfe, Pilvikki Absetz, Elezebeth Mathews, Zahra Aziz, Emily D Williams, Edwin B Fisher, Paul Z Zimmet, Ajay Mahal, Sajitha Balachandran, Fabrizio D'Esposito, Priyanka Sajeev, Emma Thomas, Brian Oldenburg

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Mathematical model of the formation of the basic statistical sample for evaluating the level of the digital competence of lecturers by Svetlana V. Avilkina, Marina A. Bakuleva, Nadezhda P. Kleynosova

“…Further researches are planned to be conducted in the sphere of automation of process of the statistical data analysis on digitalization of the population of the region, first of all in the sphere of professional education. On the basis of the mathematical model the algorithm of analytical processing of statistical data on monitoring of digital competences is developed.…”
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Two-Layer Intelligent Learning Control Using Output Recurrent Fuzzy Neural Long Short-Term Memory Broad Learning System With RMSprop by Ali Rospawan, Ching-Chih Tsai, Chi-Chih Hung

“…Simulation and experimental results validate that, compared to conventional PID, the proposed method achieves superior tracking accuracy, with the best case showing an 82% reduction in RMSE, and enhanced control efficiency, with an 85% reduction in ITAE. …”
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Quantification of evaporation water losses from nearly 5000 reservoirs in China by Yinuo Zhu, Aizhong Ye, Wei Tian

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Lightweight CNC digital process twin framework: IIoT integration with open62541 OPC UA protocol by Arivazhagan Anbalagan, Waqir Yusuf Zanhar, Shone George, Marcos Kauffman, Tengfei Long

“…This data trained five ML models to predict sensor positions with high accuracies (Random-Forest: R²(0.9994), KNN: R²(0.9998). …”
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Optimal Task Offloading Strategy for Vehicular Networks in Mixed Coverage Scenarios by Xuewen He, Yuhao Cen, Yinsheng Liao, Xin Chen, Chao Yang

“…This study employs long short-term memory networks to predict the loading status of base stations. Then, based on the prediction results, we propose an optimized task offloading strategy using the proximal policy optimization algorithm. …”
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Design and Deployment of ML in CRM to Identify Leads by Alonso Yocupicio-Zazueta, Agustin Brau-Avila, Federico Cirett-Galán, Margarita Valenzuela-Galván

“…In Jupyter Notebooks, logistic regression was utilized to design and to train a model to accurately predict whether a lead will convert into a client or not. …”
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A cellular automata coupled multi-objective optimization framework for blue-green infrastructure spatial allocation by Qinghe Hou, Hanwen Xu, Mingkun Xie, Pingjia Luo, Yuning Cheng

“…The optimized BGI allocation solutions achieved an average increase of 7.45 % in water bodies and 19.92 % in green stormwater infrastructures, alongside a 20.15 % reduction in impervious surfaces. These improvements corresponded to a 19.73 % increase in landscape objective, a 27.55 % improvement in hydrology performance, and a 26.59 % reduction in life-cycle cost (LCC). …”
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