Scalable and Privacy-Preserving Inter-AS Routing Through Machine-Learning-Based Graph Pruning by Davide Andreoletti, Cristina Rottondi, Silvia Giordano, Andrea Bianco

“…Extensive experiments performed in multiple scenarios (varying topologies and number of nodes) indicate a major reduction of computational complexity (up to 75%) and communication complexity (up to 85%), at the expense of an acceptable increase in the average path cost (at most by 16%).…”
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Dynamic analysis and comparison of the performance of linear and nonlinear controllers applied to a nonlinear non-interactive and interactive process by José M. Campos-Salazar, Pablo Lecaros, Rodrigo Sandoval-García

“…The comparative study was conducted through simulations in MATLAB/Simulink environments, where each controller's performance was assessed based on transient response, robustness to disturbances, and computational complexity. The results indicate that while the PI compensator and LQR provide satisfactory performance under linearized assumptions, the SMC demonstrates superior robustness and precision in managing the nonlinearities inherent in the IS configuration. …”
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Two-layer optimization model of distribution network line loss considering the uncertainty of new energy access by Xiping Ma, Xiping Ma, Xiaoyang Dong, Haitao Xiao, Yaxin Li, Rui Xu, Kai Wei, Juanjuan Cai, Juan Wei

“…Moreover, existing distribution network optimization methods face high computational complexity, low efficiency, and susceptibility to local optima. …”
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Improving multi-talker binaural DOA estimation by combining periodicity and spatial features in convolutional neural networks by Reza Varzandeh, Simon Doclo, Volker Hohmann

“…Additionally, the PD feature reduction stage in the proposed system improves DOA estimation accuracy while significantly reducing computational complexity compared to a baseline system without this stage, demonstrating its effectiveness for multi-talker DOA estimation.…”
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Spiking Neural Networks for Energy-Efficient Acoustic Emission-Based Monitoring by Federica Zonzini, Wenliang Xiang, Luca de Marchi

“…More specifically, both the continuous and the discrete WT alternatives have been explored to find the best compromise between time-frequency resolution and computational complexity in view of extreme edge deployments. …”
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Height Measurement Method for Meter-Wave Multiple Input Multiple Output Radar Based on Transmitted Signals and Receive Filter Design by Cong Qin, Qin Zhang, Guimei Zheng, Xiaolong Fu, He Zheng

“…Compared to the GMUSIC and ML algorithms, it demonstrates superior performance in terms of computational complexity and multi-target elevation estimation.…”
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Vehicle speed measurement method using monocular cameras by Hao Lian, Meian Li, Ting Li, Yongan Zhang, Yanyu Shi, Yikun Fan, Wenqian Yang, Huilin Jiang, Peng Zhou, Haibo Wu

“…By leveraging the characteristics of the speed measurement problem, the complex three-dimensional positioning problem is simplified into a two-dimensional model, reducing the overall computational complexity of the positioning problem. Finally, the algorithm is combined with You Only Look Once version 7 (YOLOv7) and Deep Simple Online and Realtime Tracking (DeepSORT) algorithms, integrating multiple model structures to optimize the network, achieving precise multi-target speed measurement. …”
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Towards Privacy in Decentralized IoT: A Blockchain-Based Dual Response DP Mechanism by Kai Zhang, Pei-Wei Tsai, Jiao Tian, Wenyu Zhao, Xinyi Cai, Longxiang Gao, Jinjun Chen

“…Differential Privacy (DP) stands as a secure and efficient mechanism for privacy preservation, offering enhanced data utility without compromising computational complexity. Its adaptability is evidenced by its integration into blockchain-based Internet of Things (IoT) contexts, including smart wearables, smart homes, etc. …”
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Quadratic descriptors and reduction methods in a two-layered model for compound inference by Jianshen Zhu, Naveed Ahmed Azam, Shengjuan Cao, Ryota Ido, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu

“…Furthermore, we introduce different methods to reduce descriptors, aiming to avoid computational complexity and overfitting issues during the learning process caused by the large number of quadratic descriptors. …”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Compared to the baseline YOLOv8n model, YOLORM achieved a 7.43% increase in detection accuracy and a 15.21% reduction in computational complexity. Moreover, YOLORM exhibited significant reductions in parameter count and computational cost while maintaining or enhancing detection performance relative to state-of-the-art algorithms. …”
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A Generalized Bandsplit Neural Network for Cinematic Audio Source Separation by Karn N. Watcharasupat, Chih-Wei Wu, Yiwei Ding, Iroro Orife, Aaron J. Hipple, Phillip A. Williams, Scott Kramer, Alexander Lerch, William Wolcott

“…We additionally exploit the information-sharing property of a common-encoder setup to reduce computational complexity during both training and inference, improve separation performance for hard-to-generalize classes of sounds, and allow flexibility during inference time with detachable decoders. …”
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Progressive Bitwidth Assignment Approaches for Efficient Capsule Networks Quantization by Mohsen Raji, Amir Ghazizadeh Ahsaei, Kimia Soroush, Behnam Ghavami

“…PTQ strategies employ Power-of-Two (PoT) scaling factors to simplify computations, effectively utilizing hardware shifts and significantly reducing the computational complexity. This technique not only reduces the memory footprint but also maintains accuracy by introducing a range clipping method tailored to the hardware’s capabilities, obviating the need for data preprocessing. …”
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SP-YOLO: A Real-Time and Efficient Multi-Scale Model for Pest Detection in Sugar Beet Fields by Ke Tang, Yurong Qian, Hualong Dong, Yuning Huang, Yi Lu, Palidan Tuerxun, Qin Li

“…The model demonstrates remarkable robustness on other pest datasets while maintaining a manageable parameter size and computational complexity suitable for edge devices.…”
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Algorithm and Hardware Design of a Fast Intra Frame Mode Decision Module for H.264/AVC Encoders by Daniel Palomino, Guilherme Corrêa, Cláudio Diniz, Sergio Bampi, Luciano Agostini, Altamiro Susin

“…In the rate-distortion optimization (RDO), the process of choosing the best prediction mode is performed through exhaustive executions of the whole encoding process, increasing significantly the encoder computational complexity. Considering H.264/AVC intra frame prediction, there are several modes to encode a macroblock (MB). …”
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A Low-Complexity Diversity-Preserving Universal Bit-Flipping Enhanced Hard Decision Decoder for Arbitrary Linear Codes by Praveen Sai Bere, Mohammed Zafar Ali Khan, Lajos Hanzo

“…By contrast, soft-decision decoding retains diversity order, albeit at the cost of increased computational complexity. We introduce a novel enhanced hard-decision decoder termed as the Diversity Flip decoder (DFD) designed for preserving the diversity order. …”
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LUneXt: Simple and Efficient U-shaped Network Design for Medical Image Segmentation with Nonlinear Activation by Guanghong Deng, Bing Yu, Wenlong Jing, Yong Li, Xiaodan Zhao

“…While improving model performance, it does not introduce higher computational complexity and does not have a major impact on the processing speed of a single image.…”
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Facies-Constrained Kriging Interpolation Method for Parameter Modeling by Zhenbo Nie, Bo Feng, Huazhong Wang, Chengliang Wu, Rongwei Xu, Chao Ning

“…Furthermore, the FC-Kriging method does not introduce additional computational complexity, making it convenient to implement in a 3D situation. …”
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Bidimensionally partitioned online sequential broad learning system for large-scale data stream modeling by Wei Guo, Jianjiang Yu, Caigen Zhou, Xiaofeng Yuan, Zhanxiu Wang

“…By doing so, the scale and computational complexity of the original high-order model are substantially diminished, thus significantly improving its learning efficiency and usability for large-scale complex learning tasks. …”
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A measure of the difference between test sets for generating controlled random tests by V. N. Yarmolik, V. V. Petrovskaya, I. Mrozek

“…The main attention is paid to binary test sets, when the task of calculating given difference metric is reduced to the classical assignment problem using the Hungarian algorithm. The computational complexity of the Hungarian algorithm is estimated by the relation O(n4). …”
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Temporal Convolutional Network Approach to Secure Open Charge Point Protocol (OCPP) in Electric Vehicle Charging by Ikram Benfarhat, Vik Tor Goh, Chun Lim Siow, Muhammad Sheraz, Teong Chee Chuah

“…Additionally, we conducted a comparative analysis with a hybrid model, demonstrating that the proposed TCN delivers superior performance with lower computational complexity, fewer parameters, a smaller model size, and shorter computation times. …”
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