Considerations for ethics review of big data health research: A scoping review. by Marcello Ienca, Agata Ferretti, Samia Hurst, Milo Puhan, Christian Lovis, Effy Vayena

“…The methodological novelty and computational complexity of big data health research raises novel challenges for ethics review. …”
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A Fuzzy-Decision Based Approach for Composite Event Detection in Wireless Sensor Networks by Shukui Zhang, Hao Chen, Qiaoming Zhu, Juncheng Jia

“…The Composite event judgment mechanism which is based on fuzzy-decision holds the superiority of the fuzzy-logic based algorithm; moreover, it does not need the support of a huge rule base and its computational complexity is small. Compared to CollECT algorithm and CDS algorithm, this algorithm improves the detection accuracy and reduces the traffic.…”
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Low-Complexity Timing Correction Methods for Heart Rate Estimation Using Remote Photoplethysmography by Chun-Chi Chen, Song-Xian Lin, Hyundoo Jeong

“…Through a comparative analysis, this study offers insights into efficient timing correction techniques for enhancing HR estimation from rPPG, particularly suitable for edge-computing applications where low computational complexity is essential. Cubic interpolation can provide robust performance in reconstructing signals but requires higher computational resources, while linear and filter interpolation offer more efficient solutions. …”
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Large-scale multiobjective competitive swarm optimizer algorithm based on regional multidirectional search by Xuenan Zhang, Debao Chen, Fangzhen Ge, Feng Zou, Lin Cui

“…Considering the algorithm’s computational complexity, the strategy selects the optimal individual within each subregion and constructs four-directional search vectors based on the lower limit of the global decision variables and the upper limit of the individual decision variables within the subregion. …”
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A Novel Efficient Passive Spatial Orientation Detection Method of UMT Enabled by ISB by Zhengqiang Xiong, Tao Sun, Zhengxing Wang, Yuhao Wu, Jie Yin

“…Without high computational complexity in any Transform Domain, the time consumption of ECOD is largely reduced, which is especially critical for underwater intrusion detection, territorial waters protection, and many other real-time underwater applications. …”
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A novel graph convolution and frequency domain filtering approach for hyperspectral anomaly detection by Yang Ding, Hao Yan, Jingyuan He, Juanjuan Yin, A. Ruhan

“…The key contributions of this work include: 1) the use of a graph-based model for HSI that effectively integrates both spatial and spectral dimensions, 2) employing KNN for edge construction to include distant pixels and mitigate noise, 3) spatial feature extraction via graph convolution to provide detailed insights into spatial interconnections and variations, enhancing the detection process, and 4) leveraging the beta wavelet filter to handle the ’right-shift’ spectral phenomenon and reduce computational complexity. Experimental evaluations on four benchmark datasets show that the proposed method achieves outstanding performance with AUC scores of 0.9986, 0.9975, 0.9859, and 0.9988, significantly outperforming traditional and state-of-the-art anomaly detection techniques.…”
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Probe Selection and Power Weighting in Multiprobe OTA Testing: A Neural Network-Based Approach by Yong Li, Hao Sun, Xingyu Chen, Lijian Xin, Xiang Zhang

“…., the well-known multishot algorithm, the proposed NN-based approach can yield similar channel emulation accuracy with significantly reduced computational complexity.…”
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Control of Magnetic Manipulator Using Reinforcement Learning Based on Incrementally Adapted Local Linear Models by Martin Brablc, Jan Žegklitz, Robert Grepl, Robert Babuška

“…While all of the approximation methods were successful, MGGP achieved the best results at the cost of higher computational complexity. Index Terms–AI-based methods, local linear regression, nonlinear systems, magnetic manipulation, model learning for control, optimal control, reinforcement learning, symbolic regression.…”
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A Robust k-Means Clustering Algorithm Based on Observation Point Mechanism by Xiaoliang Zhang, Yulin He, Yi Jin, Honglian Qin, Muhammad Azhar, Joshua Zhexue Huang

“…The theoretical analysis and experimental results show that the proposed clustering algorithm has the lower computational complexity and better robustness in comparison with k-means clustering algorithm, thus demonstrating the feasibility and effectiveness of our proposed clustering algorithm.…”
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Three-Dimensional Microwave Imaging for Concealed Weapon Detection Using Range Stacking Technique by Weixian Tan, Pingping Huang, Zengshu Huang, Yaolong Qi, Wenqin Wang

“…For the 3D image reconstruction under two-dimensional (2D) planar aperture condition, most of current imaging algorithms focus on decomposing the 3D free space Green function by exploiting the stationary phase and, consequently, the accuracy of the final imagery is obtained at a sacrifice of computational complexity due to the need of interpolation. …”
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Reactive power optimization via deep transfer reinforcement learning for efficient adaptation to multiple scenarios by Congbo Bi, Di Liu, Lipeng Zhu, Chao Lu, Shiyang Li, Yingqi Tang

“…Existing reinforcement learning algorithms alleviate the computational complexity in optimization but suffer from the inefficiency of model retraining for different operating scenarios. …”
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LHB-YOLOv8: An Optimized YOLOv8 Network for Complex Background Drop Stone Detection by Anjun Yu, Hongrui Fan, Yonghua Xiong, Longsheng Wei, Jinhua She

“…Finally, a bidirectional feature pyramid network (BiFPN) is introduced in the neck to effectively reduce the parameters and computational complexity and improve the overall performance of rockfall detection. …”
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Power Converter Fault Detection Using MLCA–SpikingShuffleNet by Li Wang, Feiyang Zhu, Fengfan Jiang, Yuwei Yang

“…This paper first designs an efficient SpikingShuffle Unit that integrates grouped convolutions and channel shuffle techniques, effectively reducing the model’s computational complexity by optimizing feature extraction and channel interaction. …”
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Identifying vital spreaders in large-scale networks based on neighbor multilayer contributions by Weiwei Zhu, Xuchen Meng, Jiaye Sheng, Dayong Zhang

“…These tests demonstrated the effectiveness of our proposed algorithm in identifying influential spreaders accurately.DiscussionFurthermore, computational complexity analysis indicates that our algorithm consumes less time compared to existing methods, suggesting it can be efficiently applied to large-scale networks.…”
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RWA-BFT: Reputation-Weighted Asynchronous BFT for Large-Scale IoT by Guanwei Jia, Zhaoyu Shen, Hongye Sun, Jingbo Xin, Dongyu Wang

“…To address these limitations, RWA-BFT adopts a two-layer blockchain architecture; the first layer leverages reputation-based filtering to reduce computational complexity by excluding low-reputation nodes, while the second layer employs an asynchronous consensus mechanism to ensure efficient and secure communication among high-reputation nodes, even under network delays. …”
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PilotCareTrans Net: an EEG data-driven transformer for pilot health monitoring by Kun Zhao, Xueying Guo

“…PilotCareTrans Net was evaluated on multiple public EEG datasets, including MODA, STEW, SJTUEmotion EEG, and Sleep-EDF, where it outperformed state-of-the-art models in key metrics.Results and discussionThe experimental results demonstrate the model's ability to not only enhance prediction accuracy but also reduce computational complexity, making it suitable for real-time applications in resource-constrained settings. …”
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Compressive Sensing Based Bayesian Sparse Channel Estimation for OFDM Communication Systems: High Performance and Low Complexity by Guan Gui, Li Xu, Lin Shan, Fumiyuki Adachi

“…To improve the estimation performance, we proposed a compressive sensing based Bayesian sparse channel estimation (BSCE) method which cannot only exploit the channel sparsity but also mitigate the unexpected channel uncertainty without scarifying any computational complexity. The proposed method can reveal potential ambiguity among multiple channel estimators that are ambiguous due to observation noise or correlation interference among columns in the training matrix. …”
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Graphon Neural Networks-Based Detection of False Data Injection Attacks in Dynamic Spatio-Temporal Power Systems by Rachad Atat, Abdulrahman Takiddin, Muhammad Ismail, Erchin Serpedin

“…This allows to leverage the learning by transference on the graphs to address the computational complexity and environmental concerns of training on large-scale systems, and the dynamicity resulting from the spatio-temporal evolution of power systems. …”
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Rapid Fluid Velocity Field Prediction in Microfluidic Mixers via Nine Grid Network Model by Qian Li, Yuwei Chen, Taotao Sun, Junchao Wang

“…Traditionally, the simulation of these mixers relies on the finite element method (FEM), which, although effective, presents challenges due to its computational complexity and time-consuming nature. To address this, we propose a nine-grid network (NGN) model theory with a centrally symmetric structure.The NGN uses a symmetric structure similar to a 3 × 3 grid to partition the fluid space to be predicted. …”
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Novel and Efficient Randomized Algorithms for Feature Selection by Zigeng Wang, Xia Xiao, Sanguthevar Rajasekaran

“…We conduct theoretical computational complexity analysis and further explain our algorithms’ generic parallelizability. …”
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