Cost-Effective Multitask Active Learning in Wearable Sensor Systems by Asiful Arefeen, Hassan Ghasemzadeh

“…CSS identifies clustered mini-batches of samples, optimizing budget utilization and maximizing performance. …”
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3D evolutionarily designed metamaterials for scattering maximization by Dmitry Dobrykh, Konstantin Grotov, Anna Mikhailovskaya, Dmytro Vovchuk, Vladyslav Tkach, Mykola Khobzei, Anton Kharchevskii, Aviel Glam, Pavel Ginzburg

“…The resonance cascading is engineered with the aid of multi-objective optimization, implemented on top of a genetic algorithm, operating in a large search space, encompassing over 100 independent variables. …”
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Dose enhancement effects of different-sized nanoparticles on tumors and surrounding tissues using Geant4 track structure simulation by Tuğrul Taylan

“…This study offers valuable insights into nanoparticle-assisted radiation applications, including optimal nanoparticle size and applicable energy levels. …”
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Forecasting outbound student mobility: A machine learning approach. by Stephanie Yang, Hsueh-Chih Chen, Wen-Ching Chen, Cheng-Hong Yang

“…<h4>Methods</h4>To analyze outbound student mobility in Taiwan using time series methods, this study aims to propose a hybrid approach FSDESVR which combines feature selection (FS) and support vector regression (SVR) with differential evolution (DE). FS and a DE algorithm were used for selecting reliable input features and determining the optimal initial parameters of SVR, respectively, to achieve high forecast accuracy.…”
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Robust Beamfocusing for Secure NFC with Imperfect CSI by Weijian Chen, Zhiqiang Wei, Zai Yang

“…Additionally, we decompose the robust optimization problem of the two schemes into two sub-problems, with one that can be solved using generalized Rayleigh quotient methods and the other that can be addressed through semi-definite programming (SDP). …”
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Online Tool Wear Monitoring via Long Short-Term Memory (LSTM) Improved Particle Filtering and Gaussian Process Regression by Hui Xu, Hui Xie, Guangxian Li

“…However, traditional Gaussian Process Regression (GPR) models are constrained by linear assumptions, while conventional filtering algorithms struggle in noisy environments with low signal-to-noise ratios. …”
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The balance between traffic control and economic development in tourist cities under the context of COVID-19: A case study of Xi'an, China. by Wang Xiang, Zezhi Wang, Xin Pan, Xiaobing Liu, Xuedong Yan, Li Chen

“…After determining the functional relationship between the control intensity and the number of tourists and the cumulative number of confirmed cases, the NSGA-II algorithm is employed to perform multi-objective optimization with consideration of the requirements for epidemic prevention and control and for economic development to get an appropriate traffic control intensity and suggest scientific traffic control measures. …”
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ACQUIRED HAEMOPHILIA A: AN INTRIGUING DISEASE by Maria Gabriella Mazzucconi, Erminia Baldacci, Antonietta Ferretti, Cristina Santoro

“…The disease is idiopathic in   44%-63% of cases, while in the others etiological factors are present. …”
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RL-MAB-Based Resource Allocation for Efficient Bandwidth Utilization in Industrial IoT Networks by Dongyeong Seo, Kidong Nam, Kwansoo Jung

“…To address these challenges, this paper proposes a resource reallocation and scheduling update scheme that identifies and reallocates unutilized redundant resources by employing the Multi-Armed Bandit (MAB) algorithm-one of the representative reinforcement learning techniques focused on reward optimization-in IWSN environment where mobile and fixed devices are deployed together. …”
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A novel mechanism-guided residual network for accurate modelling of scroll expander under noisy and sparse data conditions by Xiaoshuang Lv, Xin Ma, Wei Peng, Ke Li, Chengdong Li

“…This framework is based on the architecture of residual network, where the mechanistic laws are embedded as constraints in the training of the network through an improved loss function. Then, a hybrid optimization algorithm is detailed, which can achieve efficient and accurate updating of the parameters of the network and mechanistic equations. …”
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Dynamic externalities of basic medical insurance compensation, health capital accumulation, and economic growth by Xinyue Yuan, Xujin Yang

“…BackgroundA strong healthcare system plays a vital role in reducing the financial burden on households while simultaneously promoting sustainable economic development. …”
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On the Combination of Harmonics and Polynoms in Econometric Modeling of RUB/AZN Exchange Rate by L. M. Mamedova

“…By breaking up the empirical analysis of given time series into time-scale polynomial and time-frequency components. Combinations of the optimal degree of variants of polynomials up to the 11th degree and the number of harmonics of sines and cosines of all possible discrete frequencies were revealed.Conclusion. …”
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River floating object detection with transformer model in real time by Chong Zhang, Jie Yue, Jianglong Fu, Shouluan Wu

“…The RT-DETR, a member of the DETR family, has notably addressed the speed limitations of its predecessors by utilizing a high-performance hybrid encoder that optimizes query selection. Building upon this foundation, we introduce the LR-DETR, a lightweight evolution of RT-DETR for river floating object detection. …”
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A probability integral method modified model for accurately characterizing subsidence at the boundary of a mining area by Bang Zhou, Shengcai Li, Jianrong Kang, Lu Zhang, Jinman Zhang, Ming Li

“…In response to this engineering issue, this paper analyzes the influence of PIM’s parameters change on the prediction results, based on which, the probability integral method modified model (PIM-MM) is established, the decreasing step fruit flies optimization algorithm (DS-FOA) used for parameters inversion is also proposed, which realizes the accurate subsidence prediction for the boundary of a mining area. …”
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Integrated Thermal Management Strategy Using High-Value Prioritized Experience Replay Deep Reinforcement Learning for Battery Electric Vehicles by Yongqiang Jia, Guanghui Cao, Jinrui Gao

“…In low-temperature environments, electric vehicles rely on effective thermal management strategies (TMS) to rapidly heat the battery to its optimal operating temperature while maintaining cabin temperature within a comfortable range. …”
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Robust Sandstorm Image Restoration via Adaptive Color Correction and Saturation Line Prior-Based Dust Removal by Shan Zhou, Fei Shi, Zhenhong Jia, Guoqiang Wang, Jian Huang

“…Enhancing the visibility of outdoor images under sandstorm conditions remains a significant challenge in computer vision due to the complex atmospheric interference caused by dust particles. While existing image enhancement algorithms perform well in mild sandstorm scenarios, they often struggle to produce satisfactory results in more severe conditions, where residual color casts and chromatic artifacts become pronounced. …”
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The potential &amp; limitations of monoplotting in cross-view geo-localization conditions by Bradley J. Koskowich, Michael J. Starek, Scott A. King

“…Classical keypoint matching methods find the extreme pose transitions between cameras present in a CVGL configuration challenging to operate in, while deep neural networks demonstrate superb capacity in this area. …”
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Unveiling nature's secrets: Deep learning for enhanced biogenic emission resolution by Antonio Giganti

“…For instance, understanding gas emissions from crops can help farmers optimize their activities, reducing fertilizer and pesticide use while improving yields. …”
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Revolutionizing total hip arthroplasty: The role of artificial intelligence and machine learning by Umile Giuseppe Longo, Sergio De Salvatore, Alice Piccolomini, Nathan Samuel Ullman, Giuseppe Salvatore, Margaux D'Hooghe, Maristella Saccomanno, Kristian Samuelsson, Rocco Papalia, Ayoosh Pareek

“…Abstract Purpose There has been substantial growth in the literature describing the effectiveness of artificial intelligence (AI) and machine learning (ML) applications in total hip arthroplasty (THA); these models have shown the potential to predict post‐operative outcomes using algorithmic analysis of acquired data and can ultimately optimize clinical decision‐making while reducing time, cost and complexity. …”
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Adaptive multi-agent reinforcement learning for dynamic pricing and distributed energy management in virtual power plant networks by Jian-Dong Yao, Wen-Bin Hao, Zhi-Gao Meng, Bo Xie, Jian-Hua Chen, Jia-Qi Wei

“…Our proposed MARL framework enables adaptive, decentralized decision-making for both the distribution system operator and individual VPPs, optimizing economic efficiency while maintaining grid stability. …”
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