Improving Bahasa Indonesia writing skill: a project-based learning experimental study by Lisdwiana Kurniati, Wuri Syaputri, Yudi Efendi, Rohmah Tussolekha, Dessy Saputry

“…This approach encourages students to actively participate in language usage in real-world situations. These findings add to the wider discussion on innovative teaching methods in higher education and have implications for developing curriculum and instructional practices that aim to enhance educational results.…”
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Energy Management for Energy Harvesting-Based Embedded Systems: A Systematic Mapping Study by Xingyu Miao, Yongqi Ge

“…The results showed that the major research type of the EHES papers is validation research, accounting for 65%, which indicated research is still in the theoretical stage and many researchers focus on how to improve the efficiency of harvesting energy, develop a reasonable energy supply plan, and adapt EHES for real-world requirements. Furthermore, this work reviews the tools used for EHES. …”
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Bulk Low-Inertia Power Systems Adaptive Fault Type Classification Method Based on Machine Learning and Phasor Measurement Units Data by Mihail Senyuk, Svetlana Beryozkina, Inga Zicmane, Murodbek Safaraliev, Viktor Klassen, Firuz Kamalov

“…The classification method was evaluated using both synthetic data, generated from transient simulations of the IEEE24 test system, and real-world data from actual transient events in power systems. …”
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PegasosQSVM: A Quantum Machine Learning Approach for Accurate Fake News Detection by Mehdi Khalil, Chi Zhang, Zhiwei Ye, Peng Zhang

“…The PegasosQSVM algorithm encounters, however, some implementation issues on real world Quantum Processing Units(QPU). Noisy Intermediate-Scale Quantum era QPU are prone to noise effects that affect the computations negatively, and by extension, the results of quantum machine learning algorithms. …”
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SAILOR: perceptual anchoring for robotic cognitive architectures by Miguel Á. González-Santamarta, Francisco J. Rodrıguez-Lera, Vicente Matellan-Olivera, Virginia Riego del Castillo, Lidia Sánchez-González

“…This paper describes the proposed method and the development of the framework, as well as its integration in MERLIN2 (a hybrid cognitive architecture fully functional in robots running ROS 2) and the validation of SAILOR using public datasets and a real-world scenario.…”
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Impact of Rutting on Traffic Safety: A Synthesis of Research Findings by Ali Fares, Man-Nok Wong, Tarek Zayed, Nour Faris

“…Additionally, integrating real-world driver behavior into simulation models could improve their accuracy.…”
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Estimating the distribution of parameters in differential equations with repeated cross-sectional data. by Hyeontae Jo, Sung Woong Cho, Hyung Ju Hwang

“…Furthermore, we applied EPD to real-world datasets, capturing various shapes of parameter distributions over a normal distribution. …”
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Temporal link prediction method based on community multi-features fusion and embedded representation by Yuhang ZHU, Lixin JI, Yingle LI, Haitao LI, Shuxin LIU

“…Dynamic networks integrates time attributes on the basis of static networks, and it contains multiple connotations such as the complexity and dynamics of the network structure.It is a better thinking object for studying complex network link prediction problems in the real world.Its high application value has attracted much attention in recent years.However, most of the research objects of traditional methods are still limited to static networks, and there are problems such as insufficient utilization of network time-domain evolution information and high time complexity.Combining sociological theory, a novel temporal link prediction method was proposed based on community multi-feature fusion embedding representation.The core idea of this method was to analyze the dynamic evolution characteristics of the network, learn the embedded representation vector of nodes within the community, and effectively fuse multiple features to measure the generation probability of the connection between nodes.The network was divided into several subgraphs by using community detection with collective influence weights and the Similarity index was proposed based on the collective influence.Then, the biased random walk and the Skip-gram were used to get the embedded vectors for every node and the Similarity index was proposed based on the random walk within the community.Integrating the collective influence, multiple central features of the community, and the representation vector learned within the community, the Similarity index was proposed based on the multi-features fusion.Compared with classical temporal link prediction methods, including moving average methods, embedded representation methods, and graph neural network methods, experimental results on six real data sets show that the proposed methods based on the random walk within the community and the multi-features fusion both achieve better prediction performance under the evaluation criteria of AUC.…”
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Revolutionizing Education: Harnessing Graph Machine Learning for Enhanced Problem-Solving in Environmental Science and Pollution Technology by R. Krishna Kumari

“…By synthesizing theoretical insights with real-world applications, this research elucidates the profound transformative potential of GML, paving the way for proactive and data-driven approaches toward addressing pressing environmental challenges. …”
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How Trichoderma Enhances Plant Defense Enzymes in Food Crops: Current Insights and Future Perspectives in Asia by Hasan Albana, Nurbailis Nurbailis, Darnetty Darnetty

“…More research on changes in plant enzymes due to Trichoderma application is recommended, especially in field conditions, to assess its effectiveness in practical, real-world settings. …”
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A Hierarchical Attention Recommender System Based on Cross-Domain Social Networks by Rongmei Zhao, Xi Xiong, Xia Zu, Shenggen Ju, Zhongzhi Li, Binyong Li

“…Comprehensive experiments on four real-world datasets show the effectiveness of the proposed method.…”
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Improving Electrical Fault Detection Using Multiple Classifier Systems by José Oliveira, Dioeliton Passos, Davi Carvalho, José F. V. Melo, Eraylson G. Silva, Paulo S. G. de Mattos Neto

“…These findings highlight the importance of model diversity and ensemble strategies in improving fault classification accuracy under real-world, noisy conditions. This research emphasizes the potential of MCS techniques as a robust solution for enhancing the reliability of fault detection systems.…”
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Comprehensive analysis of adverse events associated with onasemnogene abeparvovec (Zolgensma) in spinal muscular atrophy patients: insights from FAERS database by Wenwen Zhang, Yizhen Yin, Dan Yang, Mengyuan Liu, Caixia Ye, Ruiling Yan, Ruiman Li

“…Information on its adverse drug reactions is mainly from clinical trials and real-world studies with extensive sample sizes are lacking. …”
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A Synergy of Convolutional Neural Networks for Sensor-Based EEG Brain–Computer Interfaces to Enhance Motor Imagery Classification by Souheyl Mallat, Emna Hkiri, Abdullah M. Albarrak, Borhen Louhichi

“…This advancement offers significant promise for enhancing the efficacy and versatility of BCIs in a wide range of real-world applications, from assistive technologies to neurorehabilitation, thereby providing robust solutions for individuals with motor disabilities.…”
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A New Approach to the Economic Problem of Dumping based on Game Theory with Grey Parameters by Davood Darvishi Selokolayi, Samira Heydari Gorji

“…A lot of data is needed to solve business problems and issues, and given that real-world data usually involves uncertainty, using definite methods in a real, inaccurate environment will not be suitable for optimal decision-making. …”
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Machine learning algorithms for predicting PTSD: a systematic review and meta-analysis by Masoumeh Vali, Hossein Motahari Nezhad, Levente Kovacs, Amir H Gandomi

“…It is also essential to conduct external validations of these models to ensure they are practical and relevant in real-world settings.…”
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Thermophysical analysis of time-dependent magnetized Casson hybrid nanofluid flow (Cu + GO/Kerosene Oil) using Darcy-Forchheimer and thermal radiative models for industrial cooling... by Amal F. Alharbi, Fida Mohammad, Muhammad Usman, Naseem Khan, Walid Abushiba

“…The study introduces the effects of magnetic fields and thermal radiation, along with velocity and thermal slip, to model real-world systems for enhancing heat transfer in critical industrial applications. …”
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Mortality of Post-COVID-19 Condition: 2025 Update by Giuseppe Lippi, Fabian Sanchis-Gomar

“…Background: The coronavirus disease 2019 (COVID-19) pandemic has generated profound health, societal, and economic consequences, which have been further compounded by long-term sequelae commonly referred to as post-COVID-19 or long-COVID syndrome. Understanding the real-world impact of post-COVID-19 mortality is therefore critical for effective healthcare planning and resource allocation. …”
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A Comprehensive Survey on Embodied Intelligence: Advancements, Challenges, and Future Perspectives by Fuchun Sun, Runfa Chen, Tianying Ji, Yu Luo, Huaidong Zhou, Huaping Liu

“…Embodied Intelligence, which integrates physical interaction capabilities with cognitive computation in real-world scenarios, provides a promising path to achieve Artificial General Intelligence (AGI). …”
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A CRITIC-CODAS Approach for Ranking WirelessCommunication Technologies in Precision Agriculture: Application to Irrigation System by Khadeejah Adebisi Abdulsalam, Damilare Babatunde, John Adebisi, Olubayo Babatunde

“…Further research could explore technology combinations, cost factors, and real-world testing. This systematic evaluation approach can be extended to other smart agriculture applications to optimize technology adoption. …”
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