From Tables to Computer Vision: Transforming HPDC Process Data into Images for CNN-Based Deep Learning by A. Burzyńska

“…Utilizing a combination of statistical pre-processing, intelligent generative models, visual data transformations and deep learning, the methodology offers a comprehensive approach to enhancing production efficiency, ensuring superior process control and improving the quality of HPDC products. This development signifies a significant advancement in the field of intelligent systems for manufacturing process optimization, aligning with the principles of Industry 4.0 and Quality 4.0.…”
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An Intelligent Method for C++ Test Case Synthesis Based on a Q-Learning Agent by Serhii Semenov, Oleksii Kolomiitsev, Mykhailo Hulevych, Patryk Mazurek, Olena Chernyk

“…However, test suites in open-source libraries often grow large, redundant, and difficult to maintain. Most traditional test suite optimization methods treat test cases as atomic units, without analyzing the utility of individual instructions. …”
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Thermoluminescence Properties of Plagioclase Mineral and Modelling of TL Glow Curves with Artificial Neural Networks by Mehmet Yüksel, Emre Ünsal

“…In addition, an artificial neural network (ANN) model was developed to predict TL glow curves using three optimization algorithms, including Levenberg–Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG). …”
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Proactive dynamic flooding regulations for river basins in China’s arid and semi-arid region of Xinjiang by Xintong Gong, Qiang Zhang, Senlin Tang, Yungang Bai, Vijay P. Singh, Zhenlin Lu

“…We used an improved pre-release constraint algorithm, such as the long-short-series mean correction method, and evaluated the flood stage potential during the aforementioned three intervals. …”
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A New Support Vector Machine Based on Convolution Product by Wei-Chang Yeh, Yunzhi Jiang, Shi-Yi Tan, Chih-Yen Yeh

“…., convolutional neural networks (CNNs)) are the two most famous algorithms in small and big data, respectively. …”
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Methodological Tools for Evaluating Effectiveness of Capital Construction Projects of Oil Producing Enterprises by E. L. Chazov, V. P. Grakhov, O. L. Simchenko

“…Due to the fact that most of the large oil fields in Russia, characterized by high production costs, are at the final stage of development; the issue of cost optimization has become increasingly important in recent years. …”
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Deep learning-based identification of patients at increased risk of cancer using routine laboratory markers by Vivek Singh, Shikha Chaganti, Matthias Siebert, Sowmya Rajesh, Andrei Puiu, Raj Gopalan, Jamie Gramz, Dorin Comaniciu, Ali Kamen

“…For most screening programs, age and clinical risk factors such as family history are part of the initial risk stratification algorithm. …”
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Energy-Efficient User Association Strategy for Hyperdense Heterogeneous Networking in the Fifth Generation Systems by Lei Li, Hao Jin, Zhipeng Yan, Changqing Yang, Yong Wu

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A New Contact Structure and Dielectric Recovery Characteristics of the Fast DC Current-Limiting Circuit Breaker by Zhiyong Lv, Xiangjun Wang, Jinwu Zhuang, Zhuangxian Jiang, Zhifang Yuan, Jin Wu, Luhui Liu

“…The optimization results show that the maximum arc energy of the finger contact is only 19.07% of the total arc energy, which greatly reduces the arc energy of the contact and improves the post-arc recovery ability of the contact.…”
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Estimation of Optimum Dilution in the GMAW Process Using Integrated ANN-GA by P. Sreeraj, T. Kannan, Subhashis Maji

“…In this study, artificial neural network (ANN) and genetic algorithm (GA) techniques were integrated and labeled as integrated ANN-GA to estimate optimal process parameters in GMAW to get optimum dilution.…”
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Uncertainty quantification with graph neural networks for efficient molecular design by Lung-Yi Chen, Yi-Pei Li

“…Using benchmarks from the Tartarus and GuacaMol platforms, our results show that UQ integration via probabilistic improvement optimization (PIO) enhances optimization success in most cases, supporting more reliable exploration of chemically diverse regions. …”
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On the academic ideology of “Sorting the gangue is sorting the images” by Hongwei MA, Ye ZHANG, Peng WANG, Xiangang CAO, Zhen NIE, Xiaorong WEI, Wenjian ZHOU, Mingzhen ZHANG

“…Coal gangue sorting is the most basic, effective, and important technical measure to improve coal quality. …”
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Low power IoT device communication through hybrid AES-RSA encryption in MRA mode by Qiang Chang, Tianqi Ma, Wenzhong Yang

“…This modification optimizes computational efficiency and strengthens security.Furthermore, we investigate the feasibility of integrating the RSA and AES algorithms and propose a novel RSA-AES hybrid algorithm MRA. …”
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Student employment forecasting model based on random forest and multi-features fusion by Zhenguo Xing, Xiao Wu, Jiangjiang Li

“…Secondly, in order to improve the accuracy of the prediction model, a feature selection model combining principal component analysis and random forest algorithm is used to select the optimal subset from the original features. …”
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Modeling Worldwide Tree Biodiversity Using Canopy Structure Metrics from Global Ecosystem Dynamics Investigation Data by Jin Xu, Kjirsten Coleman, Volker C. Radeloff, Melissa Songer, Qiongyu Huang

“…With the launch of NASA’s Global Ecosystem Dynamics Investigation (GEDI), we evaluated the efficacy of space-borne lidar metrics in predicting tree species richness globally and explored whether integrating spectral vegetation metrics with space-borne lidar data could improve model performances. Using Forest Global Earth Observatory (ForestGEO) data, we developed three models using the random forest algorithm to predict global tree species richness across climate zones, including a dynamic habitat index (DHI)-only model, a GEDI-only model, and a combined GEDI-DHI model. …”
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Effects of the lavage through fistula in treatment of spontaneous esophageal rupture by combined thoracoscopic and gastroscopic management by Zhao Huang, Penglong Zhao, Bingmei Qiu, Chuan Gao, Zhao Chen, Nan Yang, Yang Xu, Zhiqiang Zou, Yi Shen, Liwen Hu

“…Conclusions The Lavage-Drainage approach enhanced the drainage efficiency, reduced the inflammation level, and improved the prognosis of SER. However, this study has some limitations, and further multi-center prospective studies are needed to optimize the treatment and reduce costs.…”
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On the Choice of System Strength Metrics for the Allocation and Sizing of Synchronous Condensers in Power Grids by Shereefdeen Oladapo Sanni, Olatunji Obalowu Mohammed, Suprava Chakraborty, Ayodele Isqeel Abdullateef, Abdulrahaman Okino Otuoze, Olumoroti Ikotun, Ephraim Bonah Agyekum

“…Although the NRSCR-based method significantly improved system performance during faults—offering faster voltage recovery post-fault and higher fault current contributions—it resulted in a cost increase of approximately 7 times. …”
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A novel bivariate regression model derived from the clayton copula and the Odd Dagum-G family and its application by Julius Kwaku Adu-Ntim, Akoto Yaw Omari-Sasu, Maxwell Akwasi Boateng, Isaac Adjei Mensah

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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…Additionally, clustering algorithms enabled user segmentation based on cookie data, identification of behavioral patterns, enhanced personalized web recommendations, and browsing experience optimization. …”
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Rice Growth Parameter Estimation Based on Remote Satellite and Unmanned Aerial Vehicle Image Fusion by Jiaqi Duan, Hong Wang, Yuhang Yang, Mingwang Cheng, Dan Li

“…The results indicate the following: (1) The fusion of satellite and UAV images, combined with spectral information and textural features, can significantly improve the estimation accuracy of LAI and SPAD compared to using only spectral information or textural features. (2) Sparrow search algorithm-optimized extreme gradient boosting (SSA-XGBoost) regression achieved the highest accuracy, with R² and RMSE of 0.904 and 0.183 in LAI estimation and 0.857 and 0.882 in SPAD estimation, respectively. …”
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