Identifying Heart Attack Risk in Vulnerable Population: A Machine Learning Approach by Subhagata Chattopadhyay, Amit K Chattopadhyay

“…Assimilating outcomes from five clustering techniques applied to the ‘Kaggle heart attack risk’ dataset, the study categorizes distinct subpopulations against varying risk profiles and then divides the population into ‘at-risk’ (AR) and ‘not-at-risk’ (NAR) groups using clustering algorithms. The GMM algorithm outperforms its competitors (with clustering accuracy and Silhouette coefficient scores of 84.24% and 0.2623, respectively). …”
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Optimizing Concrete Mix Design for Cost and Carbon Reduction Using Machine Learning by Angga T. Yudhistira, Arief S. B. Nugroho, Iman Satyarno, Tantri N. Handayani, Malindu Sandanayake, Rimba Erlangga, Jonathan Lianto, Alfa Rosyid Ernanto

“…XGBoost Machine Learning Algorithm is used to make predictions, and PSO is used to obtain the optimal mixture. …”
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Scalable quality control on processing of large diffusion-weighted and structural magnetic resonance imaging datasets. by Michael E Kim, Chenyu Gao, Nancy R Newlin, Gaurav Rudravaram, Aravind R Krishnan, Karthik Ramadass, Praitayini Kanakaraj, Kurt G Schilling, Blake E Dewey, David A Bennett, Sid O'Bryant, Robert C Barber, Derek Archer, Timothy J Hohman, Shunxing Bao, Zhiyuan Li, Bennett A Landman, Nazirah Mohd Khairi, Alzheimer’s Disease Neuroimaging Initiative, HABS-HD Study Team

“…Most efforts to reduce data QC time rely on quantitative outlier detection, which cannot capture every instance of algorithm failure. Thus, there is a need to visually inspect every output of data processing pipelines in a scalable manner. …”
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Integrated energy microgrid bi-level game scheduling optimization taking into account electricity-heat-hydrogen enriched compressed natural gas coupling and shared energy storage by Changgang Wang, Xiaoning Sun

“…Additionally, tiered carbon trading mechanisms, integrated demand response strategies, and shared energy storage are introduced to optimize carbon reduction on both the demand and storage sides while effectively constraining energy emissions. …”
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Mechanical Design of McKibben Muscles Predicting Developed Force by Artificial Neural Networks by Michele Gabrio Antonelli, Pierluigi Beomonte Zobel, Muhammad Aziz Sarwar, Nicola Stampone

“…The results demonstrate the effectiveness of ML techniques in predicting the behavior of MKMs while offering flexibility for integrating additional parameters. …”
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Generalising Rescue Operations in Disaster Scenarios Using Drones: A Lifelong Reinforcement Learning Approach by Jiangshan Xu, Dimitris Panagopoulos, Adolfo Perrusquía, Weisi Guo, Antonios Tsourdos

“…The combined contributions allows the RL algorithm to adapt to new environments, whilst ensuring fast convergence, critical for rescue missions. …”
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The development of an intelligent comprehensive detection instrument for circuit breakers in power systems and its key technologies by Weimin Guan, Han Hu, Chao Sun, Jie Ji

“…Additionally, this study optimizes the fault diagnosis algorithm, enhancing detection stability and robustness. …”
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Deep Learning-Based Detection of Aflatoxin B1 Contamination in Almonds Using Hyperspectral Imaging: A Focus on Optimized 3D Inception–ResNet Model by Md. Ahasan Kabir, Ivan Lee, Sang-Heon Lee

“…A feature selection algorithm was employed to enhance processing efficiency and reduce spectral dimensionality while maintaining high classification accuracy. …”
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Prediction Model of Household Carbon Emission in Old Residential Areas in Drought and Cold Regions Based on Gene Expression Programming by Shiao Chen, Yaohui Gao, Zhaonian Dai, Wen Ren

“…Experimental results demonstrated that the model achieved an R² value of 0.81, reducing RMSE by 77.1% compared to conventional GEP models and by 60.4% compared to BP neural networks, while significantly improving stability. By combining data dimensionality reduction with adaptive evolutionary algorithms, this model overcomes the limitations of traditional methods in capturing complex nonlinear relationships. …”
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Depressive symptoms among patients with schizophrenia in acute and remission phases by Peljto Amir, Pešić Danilo, Christodoulou Nikos G., Lečić-Toševski Dušica

“…Targeted, patient oriented, and algorithm-based approach for treatment management, with taking into account different phenotypic expressions of the disorder (patients with and without affective symptoms) is warranted in patients with schizophrenia.…”
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Reversible Adversarial Examples with Minimalist Evolution for Recognition Control in Computer Vision by Shilong Yang, Lu Leng, Ching-Chun Chang, Chin-Chen Chang

“…To achieve zero-bit error restoration, we utilize the differential evolution algorithm to optimize adversarial perturbations while minimizing distortion. …”
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Refined Assessment Method of Offshore Wind Resources Based on Interpolation Method by Wenchuan Meng, Zaimin Yang, Zhi Rao, Shuang Li, Xin Lin, Jingkang Peng, Yuwei Cao, Yingquan Chen

“…To enhance the prediction accuracy of offshore wind speed, this study employs an interpolation algorithm to improve spatial resolution based on the ERA5 reanalysis dataset. …”
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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

“…An explicit synthesis algorithm constructs new test cases by selecting API calls from a learned policy encoded in a Q-table. …”
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Linear B-cell epitope prediction for SARS and COVID-19 vaccine design: Integrating balanced ensemble learning models and resampling strategies by Fatih Gurcan

“…Hyperparameter optimization for the classifiers was conducted using GridSearchCV, while feature selection was performed with the recursive feature elimination (RFE) algorithm. …”
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Reconstruction for Scanning LiDAR with Array GM-APD on Mobile Platform by Di Liu, Jianfeng Sun, Wei Lu, Sining Li, Xin Zhou

“…This method avoids the need for field-of-view registration, improves data utilization, and reduces the complexity of the algorithm while eliminating the effect of LiDAR motion. …”
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A deep decentralized privacy-preservation framework for online social networks by Samuel Akwasi Frimpong, Mu Han, Emmanuel Kwame Effah, Joseph Kwame Adjei, Isaac Hanson, Percy Brown

“…Our methodology employs a two-tier architecture: the first tier uses an elitism-enhanced Particle Swarm Optimization and Gravitational Search Algorithm (ePSOGSA) for optimizing feature selection, while the second tier employs an enhanced Non-symmetric Deep Autoencoder (e-NDAE) for anomaly detection. …”
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Bayesian Architecture for Predictive Monitoring of Unbalance Faults in a Turbine Rotor–Bearing System by Banalata Bera, Shyh-Chin Huang, Po Ting Lin, Yu-Jen Chiu, Jin-Wei Liang

“…Specifically, the Metropolis algorithm is employed to systematically evaluate the range of acceptable parameter values within the framework. …”
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Sequence-Aware Vision Transformer with Feature Fusion for Fault Diagnosis in Complex Industrial Processes by Zhong Zhang, Ming Xu, Song Wang, Xin Guo, Jinfeng Gao, Aiguo Patrick Hu

“…By fusing global features from the classification token with local features from the encoder, the algorithm significantly enhances complex fault diagnosis. …”
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Ac-computing enabled SWIPT communications for multi-user iot networks by Eman Sadik, Mona Shokair, Maha Elsabrouty, Mohamed S. Hassan, Ahmed M. Benaya

“…We study rate maximization while ensuring the harvesting of necessary power for both the operation and battery charging of the IoT devices. …”
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Vetoing all the Higgs imposters in $$H\rightarrow \ell ^-\ell ^+ Z$$ H → ℓ - ℓ + Z by Seong Youl Choi, Jaehoon Jeong, Dong Woo Kang

“…Abstract We develop an effective and methodical algorithm for the construction of general covariant four-point $$H\ell \ell Z$$ H ℓ ℓ Z vertices, accommodating leptons $$\ell =e, \mu $$ ℓ = e , μ , and designed to handle a boson H of any integer spin, not merely confined to spins up to 2. …”
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