Sinusoidal Neural Networks: Towards ANN that Learns Faster by Tekin Evrim Ozmermer

“…According to the experiments, the proposed neural network can reach high accuracy rates faster than the standard neural networks, while an interesting generalization capacity is obtained for the developed algorithm. …”
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Antistray, Learning Smart: Creating Indoor Positioning Learning Environment for Augmenting Self-Regulated Learning by Tien-Chi Huang

“…Furthermore, to passively avoid students being lost while they were learning in a real environment and to actively channel students into ideal learning topic, this study proposes an indoor positioning algorithm which is able to calculate the current position of the learner and further enables learners to find out where he/she is and which learning subjects he/she will learn. …”
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Optimizing Spatial Complexity of the Hard Decision Decoder Based on Hash and Syndrome Decoding (HSDec) by Seddiq El Kasmi Alaoui, Tarik Chanyour, Hamza Faham, Said Nouh

“…In this article, we aim to reduce the spatial complexity of the HSDec decoding algorithm while preserving its error correction capabilities. …”
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Wide Parallax Image Stitching With Balanced Alignment-Naturalness by Tao Song, Qian Li, Peiguo Hou, Ning Li, Wenhao Liu, Zeheng Xia

“…Achieving precise alignment while maintaining natural visual aesthetics is a challenging task. …”
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Cross-Layer Scheduling and Resource Allocation for Heterogeneous Traffic in 3G LTE by Richard Musabe, Hadi Larijani

“…Using simulations, our proposed algorithm improved the performance of real-time traffic based on throughput, VoIP delay, and VoIP packet loss ratio metrics while PF improved the performance of best-effort traffic based on FTP traffic received, FTP packet loss ratio, and FTP throughput metrics.…”
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Dynamically optimal models of atmospheric motion by A. G. Voronovich

“…</p></li><li> <p id="d2e91">The spatial resolution can be adjusted locally while executing calculations.</p></li><li> <p id="d2e95">By using a set of tetrahedra as finite elements the algorithm ensures a better representation of the topography (piecewise linear rather than staircase).…”
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Classification-based point cloud denoising and 3D reconstruction of roadways by Denghong CHEN, Ning PANG, Wen NIE, Juqiang FENG, Jiliang KAN, Jinjing ZHANG

“…The reconstruction algorithm could reduce holes effectively while maintaining the accuracy and smoothness of the roadway model. …”
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Normalized Intrinsic Deep Features Based Zero-Watermarking Scheme for Remote Sensing Images Using U-Net and K-Means by Jie Zhang, Xu Xi, Jinglong Du, Xin He, Mingkang Wu, Yi Wei

“…To address the issue, a novel zero-watermarking algorithm based on U-Net and K-means is proposed. The algorithm employs a neural network to extract intrinsic deep features from remote sensing images to construct zero-watermarks, thereby enhancing the algorithm&#x2019;s security while ensuring adaptability to different types of remote sensing images. …”
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A Fuzzy-Logic-Based Approach for Eliminating Interference Lines in Micro Rain Radar (MRR-2) by Kwonil Kim, GyuWon Lee

“…While there is a slight tendency to eliminate some weak precipitation, results indicate that the algorithm effectively removes interference lines while preserving the majority of genuine precipitation signals, even in complex scenarios where both interference and precipitation signals are present. …”
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Optimal estimation of cloud properties from thermal infrared observations with a combination of deep learning and radiative transfer simulation by H. Huang, Q. Wang, C. Liu, C. Zhou

“…<p>While traditional thermal infrared retrieval algorithms based on radiative transfer models (RTMs) could not effectively retrieve the cloud optical thickness of thick clouds, machine-learning-based algorithms were found to be able to provide reasonable estimations for both daytime and nighttime. …”
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Active Control of Nonlinear Suspension System Using Modified Adaptive Supertwisting Controller by Jagat J. Rath, Kalyana C. Veluvolu, Michael Defoort

“…The objective of any control action provided to the suspension is to improve ride comfort while ensuring road holding for the vehicle. In this work, a robust higher order sliding mode algorithm combining the merits of the modified supertwisting algorithm and the adaptive supertwisting algorithm has been proposed for the nonlinear active suspension system. …”
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Adaptive federated learning secure aggregation scheme based on threshold homomorphic encryption by Zhuo MA, Jiayu JIN, Yilong YANG, Yang LIU, Zuobin YING, Teng LI, Junwei ZHANG

“…Aiming at the communication bottleneck problem when the current federated learning security aggregation algorithm was applied in a complex network environment, an adaptive federated learning secure aggregation scheme based on threshold homomorphic encryption was proposed.While protecting gradient privacy, users adaptively compress gradients based on the current available bandwidth, greatly reduced communication overhead for federated users.Furthermore, the new dynamic decryption task distribution algorithm and gradient combination algorithm were designed in the phase of aggregation gradient decryption, which relieved the user’s uplink communication pressure.The experimental results show that the proposed scheme can sharply reduce the amount of communication to 4% compared with the existing federated learning scheme with a trivial model accuracy loss of 1%.…”
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Estimation Approach of Road Friction Coefficient Based on Nonlinear Observer by DING Xiying, PEI Yanliang, ZHANG Hongyue, YU Hua

“…In this paper, an algorithm for estimating road friction coefficient based on nonlinear observer is proposed. …”
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基于萤火虫神经网络的轴承性能退化程度评估 by 刘永前, 徐强, 田德, 龙泉

“…Precise assessment of bearing performance degradation is the foundation and key of predictive maintenance for rotating machinery,and also a new research area nowadays.An optimized BP neural network based on glowworm swarm optimization algorithm is proposed and applied for the first time in the performance degradation assessment of bearings.The glowworm swarm optimization algorithm is applied to obtain the initial weights and thresholds of BP neural network,while power spectral entropy,wavelet entropy,box dimension,correlation dimension,kurtosis and skewness are selected as the fault features.Experiments show that the glowworm swarm optimization algorithm has improved the prediction accuracy of network and the proposed method can precisely assess the performance degradation of rolling bearings,the effectiveness and accuracy of the proposed method in engineering application is validated.…”
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Basketball teaching methods based on 3D-Convolutional neural network by Chao Huang, Xian Wu

“…The results revealed that the improved single-lens multi-box detector algorithm processed images faster and with higher accuracy and F value compared to the other algorithms. …”
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Application of Distributed Acoustic Sensing in Anchor Damage Monitoring on Submarine Cables by ZHANG Hong, WU Mingnian, WANG Daogen, MU Zhangjian, XIE Shuhong, WU Zhengming, LI Songlin, CHEN Qingqing

“…The algorithm enables feature-threshold-based identification of anchor hazards in data-scarce scenarios, circumventing the high costs associated with anchor damage data acquisition while enhancing the algorithm's broad applicability.…”
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Channel shortening in IFDMA-SIMO system by XU Lan, WANG Zong-xin

“…In high-speed IFDMA systems,the increase of channel memory can lead to serious multi-path interference.After a brief introduction to IFDMA system,a new channel shortening algorithm based on the presented IFDMA-SIMO system model was proposed.Simulation results show that the proposed algorithm can effectively suppress multi-path in-terference while maintaining the orthogonality among the signals from different users.…”
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Reinforcement learning meets technical analysis: combining moving average rules for optimal alpha by Javier H. Ospina-Holguín, Ana M. Padilla-Ospina

“…This study expands on a model-free algorithm inspired by reinforcement learning to address the challenge of reconciling trading signals while taking transaction costs into account. …”
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Inferring regulatory networks by combining perturbation screens and steady state gene expression profiles. by Ali Shojaie, Alexandra Jauhiainen, Michael Kallitsis, George Michailidis

“…In the first step, the algorithm determines causal orderings of the genes that are consistent with the perturbation data, by combining an exhaustive search method with a fast heuristic that in turn couples a Monte Carlo technique with a fast search algorithm. …”
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Adaptive Exploration Artificial Bee Colony for Mathematical Optimization by Shaymaa Alsamia, Edina Koch, Hazim Albedran, Richard Ray

“…In a variable-sized problem (n = 10), the traditional ABC algorithm converged to 3.086 × 10⁶, while AEABC achieved a convergence of 2.0596 × 10⁻²⁵⁵, highlighting its robust performance. …”
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