An oral microbiota-based deep neural network model for risk stratification and prognosis prediction in gastric cancer by Xue-Feng Gao, Can-Gui Zhang, Kun Huang, Xiao-Lin Zhao, Ying-Qiao Liu, Zi-Kai Wang, Rong-Rong Ren, Geng-Hui Mai, Ke-Ren Yang, Ye Chen

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Grey wolf optimization for enhanced performance in wind power system with dual-star induction generators by Katia Benamara, Hocine Amimeur, Yanis Hamoudi, Maher G. M. Abdolrasol, Umit Cali, Umit Cali, Taha Selim Ustun

“…This study investigates strategies for enhancing the performance of dual-star induction generators in wind power systems by optimizing the full control algorithm. The control mechanisms involved include the PID (Proportional-Integral-Derivative) controller for speed regulation and the PI (Proportional-Integral) controller for flux, DC-link voltage, and grid connection control. …”
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Decentralized coordinated emergency frequency control strategy for renewables-rich power systems based on multi-agent reinforcement learning by Zhenglong Sun, Junpeng Han, Weihan Chen, Rui Zhang, Yong Liu, Yoash Levron, Juri Belikov

“…Combined with the system frequency response (SFR) model parameter identification method, the grid frequency regulation capability of different fault conditions is evaluated. A MADRL algorithm with integrated SFR model is developed to overcome the problem of inaccurate assessment of centralized action values in the MADRL algorithm used for EFC, and a decentralized and cooperative EFC strategy is realized. …”
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Predictive Modeling of Climate-Driven Crop Yield Variability Using DSSAT Towards Sustainable Agriculture by Safa E. El-Mahroug, Ayman A. Suleiman, Mutaz M. Zoubi, Saif Al-Omari, Qusay Y. Abu-Afifeh, Heba F. Al-Jawaldeh, Yazan A. Alta’any, Tariq M. F. Al-Nawaiseh, Nisreen Obeidat, Shahed H. Alsoud, Areen M. Alshoshan, Fayha M. Al-Shibli, Rakad Ta’any

“…These findings emphasize the value of integrating well-calibrated crop models with climate projections and machine learning tools to support climate-resilient agricultural planning. …”
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Analytical Methods for Wind-Driven Dynamic Behavior of Pear Leaves (<i>Pyrus pyrifolia</i>) by Yunfei Wang, Weidong Jia, Shiqun Dai, Mingxiong Ou, Xiang Dong, Guanqun Wang, Bohao Gao, Dengjun Tu

“…The results indicated that SAM2-FT effectively captured the dynamic behavior of leaves by integrating spatiotemporal information, achieving Precision and AP50/% values exceeding 97%. …”
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On-Orbit Life Prediction and Analysis of Triple-Junction Gallium Arsenide Solar Arrays for MEO Satellites by Huan Liu, Chenjie Kong, Yuan Shen, Baojun Lin, Xueliang Wang, Qiang Zhang

“…Through a combination of theoretical and data-driven methods, it conducts research on anti-radiation design verification and life prediction. This study integrates the Long Short-Term Memory (LSTM) algorithm into the full life cycle management of MEO satellite solar arrays, providing a solution that combines theory and engineering for the design of high-reliability energy systems. …”
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Predictive risks assessment of power supply interruption to oil production consumers, taking into account changes in significant factors by V. M. Levin, N. P. Guzhov

“…As a result of solving the problems, the values of the structural reliability indicators of the studied distribution electrical network are calculated under the most likely scenarios of changes in its operational composition and technical condition of equipment, the features of the integrated assessment of the technical condition of objects of voltage class 6 kV in their operating conditions are considered. …”
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RSNC-YOLO: A Deep-Learning-Based Method for Automatic Fine-Grained Tuna Recognition in Complex Environments by Wenjie Xu, Hui Fang, Shengchi Yu, Shenglong Yang, Haodong Yang, Yujia Xie, Yang Dai

“…Tuna accounts for 20% of the output value of global marine capture fisheries, and it plays a crucial role in maintaining ecosystem stability, ensuring global food security, and supporting economic stability. …”
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Sustainability index analysis of the black soldier fly (Hermetia illucens) cultivation from food waste substrate by A.D. Santoso, T. Handayani, R.A. Nugroho, A.I. Yanuar, N. Nadirah, E.S. Rohaeni, E. Widjaja, M.A.M. Oktaufik, U. Ayuningtyas, Y.P. Erlambang, R. Herdioso, M.N. Rofiq, R. Hutapea, A.L. Sihombing, B. Rustianto, I.M.A.D Susila, D. Irawan, D. Iskandar, S. Indrijarso, G.D. Widiarta

“…Therefore, study should be encouraged to effectively integrate black soldier fly biomass as a value-added component in an ideal environmental, social, economic, and technical system. …”
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Predictive exploratory data analysis of shopfloor CNC machine operation through a machine learning model by Tarique Ameer, Omid Fatahi Valilai

“…A framework has been developed to create value across the supply chain process using data analytics and integrated business decision-making. …”
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External barycentric coordinates for arbitrary polygons and an approximate method for calculating them by Ivan S. Polyansky

“…The author of the article hopes that the detailed results of the algorithmic implementation of the calculation of external barycentric coordinates will arouse interest and make the publication material more accessible to a wide range of readers, which will lead to the development of the barycentric method in solving boundary and initial boundary value problems of mathematical physics.…”
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A Method of the Vibration Information Detection for Rotating Machinery Based on the Rolling-Shutter CMOS and Digital Image Processing by Yonggong Yuan, Ji Zhang, Nanwangdi Li, Haifeng Wang, Yuxin Hu, Yilong Wang, Ning Mei, Han Yuan

“…Comparative analysis of the diagnostic results using the K-Nearest Neighbor, AdaBoost, CatBoost, and Random Forest algorithms revealed that the Random Forest algorithm achieved the highest diagnostic accuracy, exceeding 98%. …”
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An AI-Based Deep Learning with K-Mean Approach for Enhancing Altitude Estimation Accuracy in Unmanned Aerial Vehicles by Prot Piyakawanich, Pattarapong Phasukkit

“…This research presents an innovative approach to enhance altitude estimation accuracy for UAVs weighing under 2 kg without cameras, utilizing advanced AI Deep Learning algorithms. The primary novelty of this study lies in its unique integration of unsupervised and supervised learning techniques. …”
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Dual Strategy Based Improved Swarm Intelligence and Stacked LSTM With Residual Connection for Land Use Land Cover Classification by Vinaykumar Vajjanakurike Nagaraju, Ananda Babu Jayachandra, Andrzej Stateczny, Swathi Holalu Yogesh, Raviprakash Madenur Lingaraju, Balaji Prabhu Baluvaneralu Veeranna

“…The DSBES and stacked LSTM with residual connection achieve higher accuracy values of 99.71&#x0025;, 98.66&#x0025;, 97.59&#x0025;, and 99.24&#x0025; for UCM, AID, NWPU, and EuroSAT datasets, respectively, as compared to VGG19 and optimal guidance whale optimization algorithm&#x2013;bidirectional long short-term memory.…”
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Automated irrigation of apple trees based on dendrometer sensors by Thainná Waldburger, Thomas Anken, Marianne Cockburn, Achim Walter, Matthias Hatt, Camilo Chiang, Hassan-Roland Nasser

“…The FAO method tended to overestimate water requirements, while the MODEL method showed promise for dynamic irrigation adjustment based on climatic conditions and dendrometer values. Overall, the findings highlight the advantage of integrating plant-based sensors, such as dendrometers, for more precise irrigation management in orchard systems, leading to more sustainable water use without compromising crop yield.…”
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Synergistic SAPSO-sinusoidal decay empirical formula for ship motion forecasting in waves by Jianwei Wang, Xinyu Han, Jiachen Chai, Wenlei Li, Ze He, Minghua Yue

“…This study proposes a hybrid Simulated Annealing Particle Swarm Optimization (SAPSO) algorithm that achieves superior wave-induced ship motion prediction through innovative simplification of memory terms in radiation potential integral equations into fitness functions. …”
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Detection of the Pigment Distribution of Stacked Matcha During Processing Based on Hyperspectral Imaging Technology by Qinghai He, Zhiyuan Liu, Xiaoli Li, Yong He, Zhi Lin

“…Firstly, a quantitative relationship between HSI data of tea and their pigment contents was developed based on regression analysis, and the results showed that exceptional prediction performance was achieved by the partial least squares regression (PLSR) algorithm combined with the feature band algorithm of competitive adaptive reweighting (CARS), and the R_p² values of detection models of chlorophyll a, chlorophyll b and carotenoids were 0.90465, 0.92068 and 0.62666, respectively. …”
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Multi-Objective-Based Multi-Heterogeneous- Agent Deep Reinforcement Learning for Minimization of Voltage Deviation and Operation Cost in Active Distribution System by Anurak Deanseekeaw, Watcharakorn Pinthurat, Boonruang Marungsri

“…The proposed framework employs a multi-objective optimization approach, integrating three advanced algorithms: multi-agent proximal policy optimization (MAPPO), multi-agent asynchronous actor-critic (MAA2C), and multi-agent twin delayed deep deterministic policy gradient (MATD3). …”
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An Optimization Framework for Waste Treatment Center Site Selection Considering Nighttime Light Remote Sensing Data and Waste Production Fluctuations by Junbao Xia, Yanping Liu, Haozhong Yang, Guodong Zhu

“…Using Beijing as a case study, the gradient boosting regression algorithm yielded a prediction accuracy of 92%. Furthermore, in light of the substantial costs associated with waste recovery route planning and site selection for treatment facilities, this research further devised a location and distribution framework for waste treatment centers based on high-precision predictions of waste production while employing multi-objective evolutionary algorithms (MOEAs) alongside the non-dominated sorting genetic algorithm II (NSGA-II) for optimization. …”
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Predicting future morphological changes of lesions from radiotracer uptake in 18F-FDG-PET images. by Ulas Bagci, Jianhua Yao, Kirsten Miller-Jaster, Xinjian Chen, Daniel J Mollura

“…The radiotracer accumulation in patients' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. …”
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