Bridging Plant Biotechnology and Additive Manufacturing: A Multicriteria Decision Approach for Biopolymer Development by Aarthi S., Raja S., Maher Ali Rusho, Simon Yishak

“…A multicriteria decision-making (MCDM) approach, integrated with machine learning (ML) algorithms, is suggested to enable optimal material selection based on printability, biodegradability, and mechanical properties. …”
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Multi-Source Attention U-Net: A Novel Deep Learning Framework for the Land Use and Soil Salinization Classification of Keriya Oasis in China with RADARSAT-2 and Landsat-8 Data by Yang Xiang, Ilyas Nurmemet, Xiaobo Lv, Xinru Yu, Aoxiang Gu, Aihepa Aihaiti, Shiqin Li

“…Moreover, the MS + SAR MSA-U-Net, in comparison to traditional machine learning methods and the baseline model, improved the OA and Kappa coefficient by 8.24% to 12.55% and 0.08 to 0.15, respectively. …”
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Individual Travel Knowledge Graph-Based Public Transport Commuter Identification: A Mixed Data Learning Approach by Song Hu, Jiancheng Weng, Quan Liang, Wei Zhou, Peizhao Wang

“…Then, the model performance is compared with the other five machine learning models further. …”
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Controlling nonergodicity in quantum many-body systems by reinforcement learning by Li-Li Ye, Ying-Cheng Lai

“…Previous control methods relied largely on theoretical model of the target quantum system, but invertible model approximations and inaccuracies can lead to control failures. …”
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Exploring Symbolic Regression and Genetic Algorithms for Astronomical Object Classification by Fabio Ricardo Llorella, José Antonio Cebrian

“…A genetic algorithm was then employed to optimize the hyperparameters of the expression, refining the model’s performance. …”
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Artificial intelligence for screening and early diagnosis of pancreatic neoplasms in the context of centralization of the laboratory service in the region by S. I. Panin, V. A. Suvorov, A. V. Zubkov, S. A. Bezborodov, A. A. Panina, N. V. Kovalenko, A. R. Donsckaia, I. G. Shushkova, A. V. Bykov, Ya. A. Marenkov

“…Determination of the optimal machine learning model for the creation of software for screening and early diagnosis of pancreatic neoplasms in the context of centralization of the laboratory service in the region. …”
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Hierarchical Behavior Planning Framework for Networked MSV Systems in Inland Waterway Traffic Separation Schemes by Wei Tao, Lizheng Wang, Jian Tan, Man Zhu, Yuanqiao Wen

“…The proposed framework integrates a hierarchical conditional state machine with chance-constrained model predictive control, allowing NMSVs to handle complex traffic situations while complying with safety regulations. …”
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Analyzing the contributions of biofuels, biomass, and bioenergy to sustainable development goals by Raghu Raman, Aswathy Sreenivasan, Naveen V. Kulkarni, M. Suresh, Prema Nedungadi

“…Using the PRISMA framework, machine learning-based SDG mapping and BERTopic modeling, the analysis identifies two thematic clusters: one focused on sustainable energy and climate resilience (SDGs 7, 12, and 13) and the other on socioeconomic development and equity (SDGs 1, 8, and 15). …”
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High entropy powering green energy: hydrogen, batteries, electronics, and catalysis by Guotao Qiu, Tianhao Li, Xiao Xu, Yuxiang Liu, Maya Niyogi, Katie Cariaga, Corey Oses

“…We highlight the role of computational methods, such as density functional theory and machine learning, in accelerating the discovery and optimization of HEMs. …”
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Improving Sustainability of EDM Sector by Implementing Unconventional Competitive Manufacturing Approach by K. G Sagar, P. K. Anjani, Manju Shree Raman, N. S. M. P. Latha Devi, Kamakshi Mehta, Jose Luis Arias Gonzales, Nellore Manoj Kumar, Venkatesan S

“…The experimental results revealed that improvement in material removal rate (MRR) was due to the bridging effect; reduction in tool wear rate (TWR) owing to the expansion of spark gap and enhancement in the surface roughness (Ra) was due to the complete flushing of machined debris. The interaction impact was analysed using the contour plot and with the aid of mathematical modelling experimental fits that were identified and the results were validated utilizing the sensitivity analysis. …”
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Direction matters: Comparing post-editing and human translation effort and quality. by Sanjun Sun, Hao Wang, Yanfang Jia

“…Our findings have important implications for translator training, workflow optimization, and fair compensation models that account for both translation mode and direction.…”
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Integrating holographic counterparts for intelligent IoT consumer devices by M. Rajesh, M. Usha, Sathishkumar Veerappampalayam Easwaramoorthy

“…Advancements in quantum algorithms for predictive learning, self-optimization through more integrated machine learning models, and the development of standardised interoperability protocols to facilitate wider industrial usage are all areas that will be investigated in future research.…”
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A Review of Research on Flight Delay Propagation: Current Situation and Prospect by N. Li, H. G. Yao

“…Among the methods for predicting delay propagation, models based on machine learning algorithms account for a large proportion and have shown good prediction performance. …”
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Monitoring of vegetation chlorophyll content in photovoltaic areas using UAV-mounted multispectral imaging by Ming Li, Weiyi Wang, Haoran Li, Zekun Yang, Jianjun Li

“…Based on the optimal model, a spatiotemporal distribution map of chlorophyll content within the study area was generated. …”
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Analisis Algoritma Klasifikasi Untuk Mengidentifikasi Potensi Risiko Kesehatan Ibu Hamil by Jajang Jaya Purnama, Nina Kurnia Hikmawati, Sri Rahayu

“…From several classification results carried out analysis and evaluation shown that the Random Forest classification algorithm provided optimal performance with an accuracy of 82,15%. These findings confirmed that the model created could identify complex patterns and relationships between features relevant to the classification of potential health risks for pregnant women at high, medium and low levels. …”
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A neural network based approach for thrust prediction in cold gas propulsion systems by Morteza Farhid, Mohammad Reza Ghavidel Aghdam, Moharram Shameli

“…Abstract In this paper, we present a machine learning method to accurately predict thrust in a cold gas thruster using a feedforward neural network (FFNN). …”
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Next-generation diabetes diagnosis and personalized diet-activity management: A hybrid ensemble paradigm. by Muhammad Sajid, Kaleem Razzaq Malik, Ali Haider Khan, Sajid Iqbal, Abdullah A Alaulamie, Qazi Mudassar Ilyas

“…This research proposes an optimized approach by harnessing machine learning classifiers, including Random Forest, Support Vector Machine, and XGBoost, to develop a robust framework for accurate diabetes prediction. …”
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MAT-FHE: arbitrary dimension matrix multiplication scheme for floating point over fully homomorphic encryption by Yatao Yang, Zhaofu Li, Yucheng Ding, Man Hu

“…However, it has not come up with an optimal solution for modern machine learning frameworks, partially due to a lack of efficient matrix computation mechanisms. …”
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Step-by-step causal analysis of EHRs to ground decision-making. by Matthieu Doutreligne, Tristan Struja, Judith Abecassis, Claire Morgand, Leo Anthony Celi, Gaël Varoquaux

“…Without causal thinking, machine learning is not enough for optimal clinical decision on an individual patient level. …”
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Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression by Chaitanya Pallerla, Yihong Feng, Casey M. Owens, Ramesh Bahadur Bist, Siavash Mahmoudi, Pouya Sohrabipour, Amirreza Davar, Dongyi Wang

“…The classification results show that NAS-WD can classify the three WB levels with an overall accuracy of 95 %, outperforming the traditional machine learning model, and the regression correlation between the spectral data and hardness was 0.75, which performs significantly better than traditional regression models.…”
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