Easy Data Augmentation untuk Data yang Imbalance pada Konsultasi Kesehatan Daring by Anisa Nur Azizah, Misbachul Falach Asy'ari, Ifnu Wisma Dwi Prastya, Diana Purwitasari

“…We employ the Indonesian thesaurus for changing synonyms in the EDA and do empirical experiments on parameters required by the algorithm to obtain optimal results of text augmentation. …”
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Unsupervised Feature Selection via a Dual-Graph Autoencoder with <inline-formula><math display="inline"><semantics><mrow><msub><mi mathvariant="bold-script">l</mi><mrow><mn mathvar... by Zhichao Song, Meiling Chen, Liang Xie, Xi Fang

“…This paper proposes a novel unsupervised feature selection algorithm based on a dual-graph autoencoder (DGA), which combines the powerful data reconstruction capability of autoencoders with the structural preservation strengths of graph regularization. …”
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Interpretable Multi-Sensor Fusion of Optical and SAR Data for GEDI-Based Canopy Height Mapping in Southeastern North Carolina by Chao Wang, Conghe Song, Todd A. Schroeder, Curtis E. Woodcock, Tamlin M. Pavelsky, Qianqian Han, Fangfang Yao

“…Crucially, SHapley Additive exPlanations (SHAP) revealed the multi-seasonal red-edge spectral bands of Sentinel-2 as dominant predictors across models, while volume scattering from UAVSAR emerged as a key driver in tree-based algorithms. …”
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LensNet: Enhancing Real-time Microlensing Event Discovery with Recurrent Neural Networks in the Korea Microlensing Telescope Network by Javier Viaña, Kyu-Ha Hwang, Zoë de Beurs, Jennifer C. Yee, Andrew Vanderburg, Michael D. Albrow, Sun-Ju Chung, Andrew Gould, Cheongho Han, Youn Kil Jung, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Hongjing Yang, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge

“…We demonstrate a classification accuracy above 87.5% and anticipate further improvements as we expand our training set and continue to refine the algorithm.…”
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Discovery, design, and engineering of enzymes based on molecular retrobiosynthesis by Ancheng Chen, Xiangda Peng, Tao Shen, Liangzhen Zheng, Dong Wu, Sheng Wang

“…The shift from traditional experiment‐driven models to data‐driven and computationally driven intelligent models is already underway. …”
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An enhanced pivot-based neural machine translation for low-resource languages by Danang Arbian Sulistyo, Aji Prasetya Wibawa, Didik Dwi Prasetya, Fadhli Almuíini Ahda

“…The principal objective of this research is to enhance translation precision and uniformity among these low-resource languages, hence advancing machine translation models for underrepresented languages. The data collecting approach entailed extracting parallel texts from internet sources, followed by pre-processing through tokenization, normalization, and stop-word elimination algorithms. …”
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Increment of Academic Performance Prediction of At-Risk Student by Dealing With Data Imbalance Problem by Nguyen Giap Cu, Thi Lich Nghiem, Thi Hoai Ngo, Manh Tuong Lam Nguyen, Hong Quan Phung

“…This study presents two new methods of handling data imbalance based on the original algorithms SMOTE and adaptive synthetic sampling (ADASYN), called Improved SMOTE (I_SMOTE) and Improved ADASYN (I_ADASYN). …”
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Biophysical and nutritional combination treatment for myosteatosis in patients with sarcopenia: a study protocol for single-blinded randomised controlled trial by Maoyi Tian, Ling Qin, Simon Kwoon Ho Chow, Wing Hoi Cheung, A A Welch, Can Cui, Parco M Siu, Meng Chen Michelle Li, Yu Kin Cheng, Ronald Man Yeung Wong, Timothy CY Kwok, Minghui Yang, Clinton Rubin, Sheung Wai Law

“…Previous studies showed that β-hydroxy β-methylbutyrate (HMB) supplement and vibration treatment (VT) enhanced muscle quality, while the coapplication of the two interventions had further improved muscle mass and function in sarcopenic mice model. …”
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Enhanced cardiovascular risk prediction in the Western Pacific: A machine learning approach tailored to the Malaysian population. by Sazzli Kasim, Putri Nur Fatin Amir Rudin, Sorayya Malek, Nurulain Ibrahim, Xue Ning Kiew, Nafiza Mat Nasir, Khairul Shafiq Ibrahim, Raja Ezman Raja Shariff

“…<h4>Conclusions</h4>These findings underscore the effectiveness of ML models in improving CVD risk stratification and decision-making in Malaysia and beyond.…”
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High-precision prediction of non-resonant high-order harmonics energetic particle modes via stacking ensemble strategies by Sheng Liu, Zhenzhen Ren, Weihua Wang, Kai Zhong, Jinhong Yang, Hongwei Ning

“…The evaluation results indicate that the performance of the proposed model surpasses most supervised learning algorithms. …”
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Optimal sensor placement of bridge structure based on sensitivity‐effective independence method by Wenhao Chai, Yaxun Yang, Haibo Yu, Fuli Yang, Zhikui Yang

“…It is an effective optimal sensor placement algorithm for the bridge structure.…”
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Enhancing deep learning methods for brain metastasis detection through cross-technique annotations on SPACE MRI by Tassilo Wald, Benjamin Hamm, Julius C. Holzschuh, Rami El Shafie, Andreas Kudak, Balint Kovacs, Irada Pflüger, Bastian von Nettelbladt, Constantin Ulrich, Michael Anton Baumgartner, Philipp Vollmuth, Jürgen Debus, Klaus H. Maier-Hein, Thomas Welzel

“…Leveraging cross-technique ground truth annotations during training improved the accuracy of DL models in detecting and segmenting BMs. …”
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YOLOv10n-Based Defect Detection in Power Insulators: Attention Enhancement and Feature Fusion Optimization by Zhihao Wei, Yan Wei

“…The experimental results show that the mAP@50 of the improved model reaches 94.2%, which is 2.4% higher than that of the baseline model YOLOv10n, and better than the mainstream algorithms such as YOLOv5 (93.1%) and YOLOv8n (93.2%).…”
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Predictive utilities of lipid traits, lipoprotein subfractions and other risk factors for incident diabetes: a machine learning approach in the Diabetes Prevention Program by Samuel Dagogo-Jack, Søren Brunak, Carlos Lorenzo, Kieren J Mather, Marinella Temprosa, Tibor V Varga, Jinxi Liu, Ronald B Goldberg, Guannan Chen, Xavier Pi-Sunyer

“…Across all algorithms, models with baseline 2-hour glucose performed the best (max MCC=0.36). …”
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Delta-radiomics Entropy Based on Tumor Heterogeneity Concept – Response Predictor to Irradiation for Unresectable/recurrent Glioblastoma by Camil Ciprian MIRESTEAN, Roxana Irina IANCU, Dragos Teodor IANCU

“…The aim of the study is to propose a delta-radiomic based on entropy algorithm to allow the non-invasive pre-therapeutic identification of patients with unresectable or recurrent multiform glioblastoma who will benefit from irradiation and/or salvage re-irradiation. …”
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A Public Dataset of Annotated Orcinus orca Acoustic Signals for Detection and Ecotype Classification by K. J. Palmer, Emma Cummings, Michael G. Dowd, Kait Frasier, Fabio Frazao, Alex Harris, April Houweling, Jasper Kanes, Oliver S. Kirsebom, Holger Klinck, Holly LeBlond, Lauren Laturnus, Craig Matkin, Olivia Murphy, Hannah Myers, Dan Olsen, Caitlin O’Neill, Bruno Padovese, James Pilkington, Lucy Quayle, Amalis Riera Vuibert, Krista Trounce, Svein Vagle, Scott Veirs, Val Veirs, Jen Wladichuk, Jason Wood, Tina Yack, Harald Yurk, Ruth Joy

“…This curated dataset aims to improve the accuracy of killer whale detection algorithms, support conservation efforts, and advance our understanding of killer whale acoustic communication across different populations.…”
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Systems Biology of Human Microbiome for the Prediction of Personal Glycaemic Response by Nikhil Kirtipal, Youngchang Seo, Jangwon Son, Sunjae Lee

“…We explore how the gut microbiota affects glucose metabolism and insulin sensitivity by examining a variety of -omics data, including genomics, transcriptomics, epigenomics, proteomics, metabolomics, and metagenomics. Machine learning algorithms and genome-scale modeling are now being applied to find microbiological biomarkers associated with diabetes risk, predicted disease progression, and guide customized therapy. …”
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INFLUENCE OF MAIN GEAR RATIO ON CAR FUEL EFFICIENCY IN THE DRIVE CYCLE by S. A. Gorozhankin, N. V. Savenkov, V. V. Ponyakin

“…The article presents the improvement efficiency of fuel and economic properties of the vehicle in WLTC driving cycle by means of the main gear ratio changing. …”
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RESEARCH ON THE OPTIMAL DESIGN METHOD OF U-SHAPED SECTION CONTAINMENT RING

“…U-shaped containment ring is usually used as protection device for turbine starters.Under the condition that the turbine rotor is contained,structural optimization of the U-shaped section containment ring was carried out to obtain a light and inclusive structure,which improved aircraft safety and thrust-to-weight ratio.An optimal design method for U-shaped cross section containment ring was proposed.The method adopted the optimal Latin hypercube design,numerical simulation,response surface modeling,and multi-island genetic algorithm to achieve the optimal design of multiple parameters of containment rings cross section.By combining simulation and experiment,the influence weights of different structural parameters on the residual kinetic energy of debris and the volume of containment rings were analyzed.The influence of different structural parameters of Ushaped containment ring on the containment results was studied.Containment test was carried out to verify the optimized containment ring.The results show that the thickness of the containment ring has the greatest influence on the residual kinetic energy of the debris,and the weight ratio is 38%.The main structural parameters affect the inclusion effect are thickness and groove depth.The error of inclusion ring deformation is less than 2%in the comparison between simulation and test results,which indicates that the optimization design method proposed is reasonable and reliable.The research results can provide prior knowledge and optimization methods for the quality reduction of U-shaped containment ring structures.…”
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Time-triggered stream scheduling method combining no-wait and time-slot mapping reuse by HE Qian, GUO Yanan, ZHAO Baokang, PAN Qi, WANG Yong

“…Finally, several time-triggered stream scheduling optimization functions were given and solved based on an improved multi-objective genetic algorithm. The correctness and feasibility of NW-TSMR is verified through experiments, and the average gate control list length is reduced by 59.7%.…”
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