Coupled Dynamics of Vehicle-Bridge Interaction System Using High Efficiency Method by Lu Sun, Xingzhuang Zhao

“…This paper studies the accuracy and efficiency of discretizing the beam in space as lumped masses using the flexibility method and as finite elements using the stiffness method. Computational complexity analysis is carried out along with a numerical case study to compare the accuracy and efficiency of both methods against the analytical solutions. …”
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Constellation Optimization for MIMO VLC System With Signal-Dependent Noise: Receiver-Side Design and Lookup Table Establishment by Jiaqi Wei, Yuan Wang, Nuo Huang, Yan-Yu Zhang, Yi-Jun Zhu, Wenliang Hao, Chen Gong

“…For the scenario where receiver randomly moves, the constellation lookup table is proposed to transform real-time optimization into table lookup operation, which effectively reduces the real-time computational complexity. Simulation results show that the optimized constellation leads to lower symbol error rate (SER) than the method of maximizing minimum Euclidean distance. …”
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Fast Video Encoding Algorithm for the Internet of Things Environment Based on High Efficiency Video Coding by Jong-Hyeok Lee, Kyung-Soon Jang, Byung-Gyu Kim, Seyoon Jeong, Jin Soo Choi

“…In this paper, a fast intraprediction unit decision method is proposed to reduce the computational complexity of the HEVC RExt encoder. To design intramode decision algorithm, Local Binary Pattern (LBP) of the current prediction unit is used as texture feature. …”
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Mixed Multinomial Probit Model Accommodating Flexible Covariance Structure and Random Taste Variation: An Application to Commute Mode Choice Behavior by Ke Wang, Xin Ye, Hongcheng Gan

“…Compared with the MMNL model, the MMNP model can accommodate more random coefficients without increasing computational complexity.…”
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AFF-LightNet: A Lightweight Ship Detection Architecture Based on Attentional Feature Fusion by Yingxiu Yuan, Xiaoyan Yu, Xianwei Rong, Xiaozhou Wang

“…The experimental results show that compared with the standard YOLOv8n, the improved network has an average accuracy of 98.8%, an increase of 0.4%, a reduction of 1.9 G in computational complexity, and a reduction of 0.19 M in parameter count.…”
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Channel Mixer Layer: Multimodal Fusion Toward Machine Reasoning for Spatiotemporal Predictive Learning of Ionospheric Total Electron Content by Peng Liu, Tatsuhiro Yokoyama, Takuya Sori, Mamoru Yamamoto

“…Experiment results suggest that the multimodal fusion prediction of existing model backbones by proposed method improves the prediction accuracy up to 15% with almost the same computational complexity compared to that of graphic prediction without auxiliary factors input, having the real‐time inference speed of 34 frames/second and minimum mean absolute error of 0.94/2.63 TEC unit during low/high solar activity period respectively. …”
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Achieving Faster and Smarter Chest X-Ray Classification With Optimized CNNs by Hassen Louati, Ali Louati, Khalid Mansour, Elham Kariri

“…However, building accurate and efficient deep learning models for X-ray image classification remains challenging, requiring both optimized architectures and low computational complexity. In this paper, we present a three-stage framework to enhance X-ray image classification using Neural Architecture Search (NAS), Transfer Learning, and Model Compression via filter pruning, specifically targeting the ChestX-Ray14 dataset. …”
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Multichannel Filtered-X Error Coded Affine Projection-Like Algorithm with Evolving Order by J. G. Avalos, A. Rodriguez, H. M. Martinez, J. C. Sanchez, H. M. Perez

“…However, their high computational complexity can restrict their use in certain practical applications. …”
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Study on the Detection of Dairy Cows’ Self-Protective Behaviors Based on Vision Analysis by Jia Li, Pei Wu, Feilong Kang, Lina Zhang, Chuanzhong Xuan

“…By combining the morphological features of head, leg, and tail movements, this method effectively reduces the number of Shi-Tomasi points, eliminates interference from background movement, reduces the computational complexity of the algorithm, and improves detection accuracy. …”
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Experimental Results of Novel DoA Estimation Algorithms for Compact Reconfigurable Antennas by Henna Paaso, Aki Hakkarainen, Nikhil Gulati, Damiano Patron, Kapil R. Dandekar, Mikko Valkama, Aarne Mämmelä

“…We study how the computational complexity and the performance of the algorithms depend on number of selected radiation patterns. …”
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Anomaly detection solutions: The dynamic loss approach in VAE for manufacturing and IoT environment by Praveen Vijai, Bagavathi Sivakumar P

“…The proposed model addresses key challenges, including data imbalance, interpretability issues, and computational complexity. By leveraging the bidirectional capability of BiLSTM in the encoder and decoder, the model captures comprehensive temporal dependencies, enabling more effective anomaly detection. …”
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Approximate CNN Hardware Accelerators for Resource Constrained Devices by P Thejaswini, Gautham Suresh, V. Chiraag, Sukumar Nandi

“…Implementation of Convolutional Neural Networks (CNNs) on edge devices require reduction in computational complexity. Leveraging optimization techniques or approximate computing techniques can reduce the overhead associated with hardware implementation. …”
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A proximal policy optimization based deep reinforcement learning framework for tracking control of a flexible robotic manipulator by Joshi Kumar V, Vinodh Kumar Elumalai

“…Hence, in this study, we adopt the PPO technique which utilizes first-order optimization to minimize the computational complexity and devise a DRL scheme for a partially observable flexible link robot manipulator system. …”
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Feature selection based on Mahalanobis distance for early Parkinson disease classification by Mustafa Noaman Kadhim, Dhiah Al-Shammary, Ahmed M. Mahdi, Ayman Ibaida

“…Standard classifiers struggle with high-dimensional datasets due to increased computational complexity, difficulty in visualization and interpretation, and challenges in handling redundant or irrelevant features. …”
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Optimized PID controller and model order reduction of reheated turbine for load frequency control using teaching learning-based optimization by Anurag Singh, Shekhar Yadav, Nitesh Tiwari, Dinesh Kumar Nishad, Saifullah Khalid

“…Abstract Load frequency control (LFC) systems in power grids face challenges in maintaining stability while managing computational complexity. This research presents an optimized approach combining model order reduction techniques with Teaching Learning-Based Optimization (TLBO) for PID controller tuning in single-area LFC systems. …”
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Joint Active/Passive Beamforming Optimization via RWMMSE and Gradient Projection for Downlink IRS-Aided MU-MISO Systems by Seraphin F. Kimaryo, Eduard E. Bahingayi, Kyungchun Lee

“…The proper reconfiguration of its elements, which is the primary task towards achieving these prospects, has been previously explored by many researchers, where most proposals are characterized by high computational complexity. This study builds upon previous research on downlink IRS-assisted multi-user multiple-input single-output (MISO) systems by introducing innovative methods to accelerate their operations. …”
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TBF-YOLOv8n: A Lightweight Tea Bud Detection Model Based on YOLOv8n Improvements by Wenhui Fang, Weizhen Chen

“…To solve the problem of the high computational complexity of deep learning detection models, we developed the Tea Bud DSCF-YOLOv8n (TBF-YOLOv8n)lightweight detection model. …”
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A Modified WASPAS Method for the Evaluation of E-Commerce Websites Based on Pythagorean Fuzzy Information by Xiufang Ou, Bingbin Chen

“…The proposed approach significantly enhanced performance and reduced computational complexity, making it a promising tool for real-time detection and prediction of the efficiency of employees in various organizations and a tool for growth.…”
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Improving Industrial Quality Control: A Transfer Learning Approach to Surface Defect Detection by Ângela Semitela, Miguel Pereira, António Completo, Nuno Lau, José P. Santos

“…The results revealed that the two illumination modes employed widened the type of defects that could be identified with this system, while maintaining its lower computational complexity by performing multi-modal fusion at the decision level. …”
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Improved printed circuit board defect detection scheme by Lufeng Bai, Wen Hao Xu

“…Furthermore, in order to further enhance the interaction and fusion of multi-scale features, we also add a SlimNeck module to the neck structure, which realizes efficient information transfer through streamlined design and reduces computational complexity at the same time. In addition, we draw on the advanced BiFPN structure, which enables the bidirectional flow of feature information between multiple layers and greatly improves the capture and integration of small target features. …”
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