Enhancing Autonomous Driving in Urban Scenarios: A Hybrid Approach with Reinforcement Learning and Classical Control by Rodrigo Gutiérrez-Moreno, Rafael Barea, Elena López-Guillén, Felipe Arango, Fabio Sánchez-García, Luis M. Bergasa

“…This paper aims to provide a realistic implementation of a hybrid Decision Making module in an Autonomous Driving stack, integrating the learning capabilities from the experience of Deep Reinforcement Learning algorithms and the reliability of classical methodologies. …”
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Instrumenting Parkrun: Usefulness and Validity of Inertial Sensors by Rachel Mason, Yunus Celik, Gill Barry, Alan Godfrey, Samuel Stuart

“…Temporal gait characteristics—gait cycle, ground contact time, swing time, and duty factor—were extracted using zero-crossing algorithms. The data were analyzed for correlations between the running performance, foot strike type, and fatigue-induced changes in temporal gait characteristics. …”
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Prediction of birthweight with early and mid-pregnancy antenatal markers utilising machine learning and explainable artificial intelligence by Manohar Pavanya, Krishnaraj Chadaga, Vennila J, Akhila Vasudeva, Bhamini Krishna Rao, Srikanth Prabhu, Shashikala K Bhat

“…Multiple ML classifiers were employed. We developed a stacked ensemble model that integrated various algorithms, including a custom-stacked ensemble approach and three XAI methodologies: Shapley Additive Explanations (SHAP), Local Interpretable Model-agnostic Explanations (LIME), and Anchor. …”
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On Analysis of Traffic Flow Demultiplexing Effectiveness by Evgeniy P. Stepanov

“…The routes constructed with these algorithms were used both for the network performance analysis with demultiplexed flows and in the case of balancing non-demultiplexed flows.…”
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SNN-Based Semantic Segmentation Method Using Adaptive Threshold and Multi-Feature Fusion by HUANG Yongbin, LI Chen, DONG Wenbo, LIU Shunlian

“…Additionally, the proposed method consumed less energy compared to ANN-based semantic segmentation algorithms.…”
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Characterizing the Inter-Core Qubit Traffic in Large-Scale Quantum Modular Architectures by Sahar Ben Rached, Isaac Lopez Agudo, Santiago Rodrigo, Medina Bandic, Artur Garcia-Saez, Sebastian Feld, Hans van Someren, Eduard Alarcon, Carmen G. Almudever, Sergi Abadal

“…This would provide insights to improve the software and hardware stack for multi-core quantum computers. To this aim, we present a characterization of the spatio-temporal inter-core qubit traffic for different large-scale quantum algorithms. …”
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Soft Sensor Modeling of Key Effluent Parameters in Wastewater Treatment Process Based on SAE-NN by Yousuf Babiker M. Osman, Wei Li

“…In this research work, we propose a soft sensor model based on deep learning which combines stacked autoencoders with neural network (SAE-NN). …”
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Fast quantitative time lapse displacement imaging of endothelial cell invasion. by Christian Steuwe, Marie-Mo Vaeyens, Alvaro Jorge-Peñas, Célie Cokelaere, Johan Hofkens, Maarten B J Roeffaers, Hans Van Oosterwyck

“…In order to unravel rapid mechano-chemical feedback mechanisms in sprouting angiogenesis, we combine selective plane illumination microscopy (SPIM) and tailored image registration algorithms - further referred to as SPIM-based displacement microscopy - with an in vitro model of angiogenesis. …”
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Comparative study on the drying mechanisms and characteristic changes of fabrics according to heat transfer principles by Jiyul Lee, Jaeyong Cho, Suhyun Lee

“…The findings of this study are expected to help develop automatic drying algorithms for household dryers.…”
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Implementasi Algoritma AES 256 CBC, BASE 64, Dan SHA 256 dalam Pengamanan dan Validasi Data Ujian Online by Ferzha Putra Utama, Gusman Wijaya, Ruvita Faurina, Arie Vatresia

“…This study proposes applying several cryptographic methods to secure and ensure the authenticity of online exam data using AES 256 CBC, Base 64, and SHA 256 algorithms. This research resulted in a website-based online exam application built using MERN Stack technology. …”
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DPD-v2: Generalised deep particle diffusometry for varied particle shapes and experimental conditions by Pranshul Sardana, Steven T. Wereley

“…The performance of DPD-v2 models increases with crop size and the use of multiple stacks of images. The outputs of the DPD-v2 models were compared against the outputs from conventional algorithms on Gaussianised experimental no flow datasets, which provided < 0.5 $\unicode{x03BC}$ m2s−1 mean absolute difference. …”
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Nonintrusive Load Disaggregation Based on Attention Neural Networks by Shunfu Lin, Jiayu Yang, Yi Li, Yunwei Shen, Fangxing Li, Xiaoyan Bian, Dongdong Li

“…In the regression subnetwork, stacked dilated convolutions are utilized to extract multiscale features. …”
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Detection of breast cancer using machine learning and explainable artificial intelligence by Tharunya Arravalli, Krishnaraj Chadaga, H Muralikrishna, Niranjana Sampathila, D. Cenitta, Rajagopala Chadaga, K. S. Swathi

“…The stacked ensemble model, which combines the strengths of different models, obtained an F1-score performance of 83%. …”
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Design Improvement of Permanent Magnet Motor Using Single- and Multi-Objective Approaches by Cvetkovski Goga, Petkovska Lidija

“…In this case, optimising the efficiency of the motor, reducing cogging torque, and minimising the total weight of active materials are defined as possible objective functions. Genetic algorithms are nature based algorithms that are commonly used in engineering to find optimal solutions to complex problems, including those with multiple objectives. …”
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Modeling, description, and characterization of fractal pore via mathematical morphology by Lay Lian Teo, B. S. Daya Sagar

“…The aim of this paper is to provide description of fast, simple computational algorithms based upon mathematical morphology techniques to extract descriptions of pore channels—throats—and bodies and to represent them in 3D space, and to produce statistical characterization of their descriptions. …”
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Reconstructing 3D Tree Models Using Motion Capture and Particle Flow by Jie Long, Michael D. Jones

“…Recovering tree shape from motion capture data is a first step toward efficient and accurate animation of trees in wind using motion capture data. Existing algorithms for generating models of tree branching structures for image synthesis in computer graphics are not adapted to the unique data set provided by motion capture. …”
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Enhancing Mobile App Recommendations With Crowdsourced Educational Data Using Machine Learning and Deep Learning by Naadiya Mirbahar, Kamlesh Kumar, Asif Ali Laghari

“…Although the CF techniques suffer from temporal dynamics and data sparsity, even the KNNBasic stands out among all CF algorithms with the lowest MAE of 0.548 and RMSE of 0.754, demonstrating the highest predictive accuracy.…”
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Vibration-based gait analysis via instrumented buildings by Ellis Kessler, Vijaya VN Sriram Malladi, Pablo A Tarazaga

“…Signal-energy-based algorithms detect the heel strike of each step during trials. …”
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AIPerf: Automated Machine Learning as an AI-HPC Benchmark by Zhixiang Ren, Yongheng Liu, Tianhui Shi, Lei Xie, Yue Zhou, Jidong Zhai, Youhui Zhang, Yunquan Zhang, Wenguang Chen

“…The plethora of complex Artificial Intelligence (AI) algorithms and available High-Performance Computing (HPC) power stimulates the expeditious development of AI components with heterogeneous designs. …”
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Hospital-wide natural language processing summarising the health data of 1 million patients. by Daniel M Bean, Zeljko Kraljevic, Anthony Shek, James Teo, Richard J B Dobson

“…Recently, Natural Language Processing (NLP) algorithms have reached a level of performance suitable for large scale and accurate information extraction from clinical text. …”
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