Short-Term Electricity Price Forecasting Using the Empirical Mode Decomposed Hilbert-LSTM and Wavelet-LSTM Models by Kunal Shejul, R. Harikrishnan, Amit Kukker

“…The proposed techniques show better performance in terms of rank correlation, mean square error, and root mean square error compared to the existing algorithms of LSTM and CNN-LSTM. The prediction results achieved with wavelet-LSTM and Hilbert-LSTM (1-month dataset of 8 years) are rank correlation 0.9746 and 0.9749, MSE 0.2962 and 0.1363, and RMSE 0.5443 and 0.3692, respectively. …”
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Leveraging machine learning techniques to analyze nutritional content in processed foods by K. A. Muthukumar, Soumya Gupta, Doli Saikia

“…The findings reveal that the SVR model is particularly effective in predicting nutrient retention, outperforming the RF model. …”
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Climatic variables determining <i>Rhododendron</i> sister taxa distributions and distributional overlaps in the Himalayas by Madan Krishna Suwal, Ole Reidar Vetaas

“…We used Generalized Linear Modelling to select variables, and modelled the distribution of each species using Random Forest algorithms, predicting their potential distribution in current and future climates. …”
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Machine Learning and Digital-Twins-Based Internet of Robotic Things for Remote Patient Monitoring by Sehat Ullah, Sangeen Khan, David Vanecek, Inam Ur Rehman

“…The system was also tested in the clinical setting to collect patient data and the best-performing algorithm (KNN) was used for status prediction, obtaining 98% accuracy.…”
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Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005–2018 by Xiangling Deng, Lifei Ma, Pin Li, Mengyang He, Ruyue Jin, Yuandong Tao, Hualin Cao, Hengyu Gao, Wenquan Zhou, Kuan Lu, Xiaoye Chen, Wenchao Li, Huixia Zhou

“…Furthermore, an optimal predictive model was developed for CKD using ten machine learning algorithms and enhanced model interpretability with the Shapley Additive Explanations (SHAP) method. …”
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6G Technology for Indoor Localization by Deep Learning with Attention Mechanism by Chien-Ching Chiu, Hung-Yu Wu, Po-Hsiang Chen, Chen-En Chao, Eng Hock Lim

“…CNN with SA demonstrates a 50% reduction in RMSE compared to CNN by capturing spatial dependencies more effectively.…”
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An Optimization Method for Iteration Path Search of Large-Scale Power Grid Unit Commitment State by CUI Yiyang, PAN Dounan, LI Canbing, LIU Jianzhe

“…To address the computational challenge posed by the “curse of dimensionality” inherent in traditional branch and bound algorithms for large-scale power grid unit commitment problems, an optimization method for iteration path search of unit commitment state is proposed. …”
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Robust Model-Free Identification of the Causal Networks Underlying Complex Nonlinear Systems by Guanxue Yang, Shimin Lei, Guanxiao Yang

“…Due to the complexity of system modeling, the way in which universal and feasible inference algorithms are studied is a key challenge for network reconstruction. …”
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Facilitate integrated analysis of single cell multiomic data by binarizing gene expression values by Rohan Misra, Alexander Ferrena, Deyou Zheng

“…The popular and standard workflow for single cell RNA-seq (scRNA-seq) data analysis applies feature selection, dimensional reduction, and clustering on the gene expression values quantified by read counts, but alternative approaches using a simple classification of a gene to “on” and “off” (i.e., binarization of the gene expression) have been proposed for clustering cells and other downstream analyses. …”
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ST-YOLO: A defect detection method for photovoltaic modules based on infrared thermal imaging and machine vision technology. by Hanfei Xie, Baoxi Yuan, Chengyu Hu, Yujie Gao, Feng Wang, Chunlan Wang, Yuqian Wang, Peng Chu

“…This algorithm is based on YOLOv8s. First, it introduces the C2f-SCconv convolution module, which is based on SCconv convolution. …”
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Rapid detection of wheel tread defects for YOLO-v5 trains based on residual attention by ZHANG Changfan, XU Yifu, HE Jing, YANG Haonan

“…Finally, hundreds of real defect images of wheel treads were collected and contrasted with five classic detection models to verify the superiority of the algorithm. The results show that the algorithm can achieve 77.9% accuracy and 72.3% recall; in addition, the proposed algorithm can detect 125 images per second, and the model weight is only 15.1 MB. …”
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Optimization of Toolpath Planning and CNC Machine Performance in Time-Efficient Machining by Arbnor Pajaziti, Orlat Tafilaj, Afrim Gjelaj, Besart Berisha

“…We propose a method that integrates advanced algorithms to identify and eliminate redundant movements, optimize the toolpaths, and improve the machining strategies. …”
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OT-PCA: New Key-Recovery Plaintext-Checking Oracle Based Side-Channel Attacks on HQC with Offline Templates by Haiyue Dong, Qian Guo

“…Our method addresses critical challenges in optimizing key-related information extraction, including maximizing decryption output entropy and ensuring error pattern independence, through the use of genetic-style algorithms. Extensive simulations demonstrate that our new attack method significantly reduces the required number of oracle calls, achieving a 2.4-fold decrease for hqc-128 and even greater reductions for hqc-192 and hqc-256 compared to current state-of-the-art methods. …”
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Discriminative graph regularized representation learning for recognition. by Jinshan Qi, Rui Xu

“…Specifically, DGRL first integrates dimension reduction into ridge regression rather than treated them as two irrelevant steps, which enables us to capture the underlying subspace structure and correlation patterns among classes. …”
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Indoor Multidimensional Reconstruction Based on Maximal Cliques by Yongtong Zhu, Lei Li, Na Liu, Qingdu Li, Ye Yuan

“…Applying deep learning models to obtain stereoscopic scene information, accompanied by algorithms such as target detection and semantic segmentation to obtain finer labels of things, is the dominant paradigm for robots. …”
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Optimising Grid-Connected PV-Battery Systems for Energy Arbitrage and Frequency Containment Reserve by Rodolfo Dufo-López, Juan M. Lujano-Rojas, Jesús S. Artal-Sevil, José L. Bernal-Agustín

“…By applying genetic algorithms (GA), the optimal configurations of PV generators, inverters/chargers, and batteries were determined, focusing on maximising the net present value (NPV). …”
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Modelling protein-protein interactions for the design of vaccine chimeric antigens with protective epitopes. by Marinela Contreras, Marta Rafael, Isidro Sobrino, Consuelo Almazán, Juan J Pastor Comín, James J Valdés, Carlos Roberto Prudencio, Daniel Ferreira de Lima Neto, Veniamin A Borin, Pratul K Agarwal, Paul D Kasaija, Rubén Fernández-Melgar, Justus Rutaisire, José de la Fuente

“…Vaccine formulations with tick antigens such as BM86/BM95 (BM) and Subolesin (SUB) have shown reduction in tick fitness and infestation in immunized hosts. …”
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Adaptive information-constrained mapping for feature compression in edge AI and federated systems by Viacheslav Kovtun

“…Efficient projection-gradient optimisation algorithms have been developed, suitable for implementation in constrained computational environments. …”
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An Innovative Priority-Aware Mission Planning Framework for an Agile Earth Observation Satellite by Guangtong Zhu, Zixuan Zheng, Chenhao Ouyang, Yufei Guo, Pengyu Sun

“…Experimental results demonstrate the framework’s superior performance, achieving a 94% coverage rate and a 99.5% reduction in computation time compared to traditional scheduling methods, such as linear programming and genetic algorithms.…”
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Integrated photonic programmable random matrix generator with minimal active components by Kevin Zelaya, Mostafa Honari-Latifpour, Mohammad-Ali Miri

“…In quantum information processing, random unitary operations are essential to boson sampling algorithms for multiphoton states in linear photonic circuits. …”
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