Dynamic pilot assignment in massive MIMO system based on user classification by Jinyan ZHANG, Feng JIN, Lixin YIN

“…Aiming at the problem of pilot contamination in massive MIMO system,a dynamic pilot assignment strategy based on user classification was proposed.The target cell user was divided into the central user and the edge user based on the variance of target cell user signal intensity.The central user used the maximum C/I algorithm to assign pilots to maximize the channel capacity of the central user.The edge user used greedy algorithm to assign pilots to improve the signal to interference and noise ratio of each edge user.Simulation results show that the proposed strategy can improve the channel capacity of the system while improving the signal to interference and noise ratio of the edge user.…”
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Program Complex for Calculation and Optimization of the Regimes of Electric Power Systems by O. I. Alexandrov, A. M. Bakanovsky, V. A. Ustimovich

“…The possibilities of modem computers have permitted to apply more advanced algorithms. The algorithm of regime calculations is based on the modified New- ton-Raphson method. …”
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Real-Time Optimally Adapting Meshes: Terrain Visualization in Games by Matthew White

“…One of the main challenges encountered by interactive graphics programmers involves presenting high-quality scenes while retaining real-time frame rates on the hardware. …”
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Robust Multi-Sensor Fusion for Localization in Hazardous Environments Using Thermal, LiDAR, and GNSS Data by Lukas Schichler, Karin Festl, Selim Solmaz

“…To evaluate the algorithm, we conduct a field test in an urban environment using a vehicle equipped with the appropriate sensor suite while simulating an outage one at a time, to demonstrate the approach’s effectiveness under real-world conditions.…”
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FedG2L: a privacy-preserving federated learning scheme base on “G2L” against poisoning attack by Mengfan Xu, Xinghua Li

“…Federated learning (FL) can push the limitation of “Data Island” while protecting data privacy has been a broad concern. …”
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Application of LSB Steganography for Encrypted Data Using Triple Transposition Vigenere on Digital Images by Eko Aribowo, Windy Sayyida Amalya, Nur Rochmah Dyah Puji Astuti

“…Grayscale images offer advantages in terms of storage and algorithm efficiency, while RGB images provide broader color diversity and versatile applications. …”
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Adaptive dimensionality reduction for neural network-based online principal component analysis. by Nico Migenda, Ralf Möller, Wolfram Schenck

“…This requires to update both the principal components and the dimensionality in every timestep. While the continuous update of the principal components is widely studied, the available algorithms for dimensionality adjustment are limited to an increment of one in neural network-based and incremental PCA. …”
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Differentiable architecture search-based automatic modulation recognition for multi-carrier signals by LI Jie, LI Jing, LYU Lu, GONG Fengkui

“…Simulation results demonstrate that the proposed algorithm improves accuracy in urban multipath channels, especially at low SNR, while simultaneously providing better robustness to modulation parameter variations and small-sample scenarios.…”
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Non-Holonomic Mobile Manipulator Obstacle Avoidance with Adaptive Prioritization by Federico Neri, Giacomo Palmieri, Massimo Callegari

“…A series of examples are proposed in simulation using Matlab and analyzed to show how the algorithm works if the obstacle interferes with the manipulator or the base. …”
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Reliable Process Tracking Under Incomplete Event Logs Using Timed Genetic-Inductive Process Mining by Yutika Amelia Effendi, Minsoo Kim

“…Experimental results using real-world event logs from a health service in Indonesia demonstrate that TGIPM achieves higher fitness, precision, and generalization compared to the sequential approach, while slightly compromising simplicity. Moreover, the TGIPM algorithm exhibits lower computational cost and more effectively captures parallelism, making it particularly suitable for large and incomplete datasets. …”
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An Improved Large Neighborhood Search for Network-Level Airport Slot Allocation Optimization by Qiangzhe Wang, Yuanyuan Ma, Yifan Xu, Zhiyuan Shen, Dan Li

“…Validated through an extensive case study involving 4,695 requests across six hub airports, the algorithm achieves solutions within a 1.7% optimality gap while reducing computation time by up to 64%.…”
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Analysis of Encrypted Network Traffic for Enhancing Cyber-security in Dynamic Environments by Faeiz Alserhani

“…User selection is accomplished through robust Deep Reinforcement Learning with the Tabu Search (DRL-TS) algorithm, while channel selection is optimized through rigorous training employing Proximal Policy Optimization (PPO). …”
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Secure Latency-Aware Task Offloading Using Federated Learning and Zero Trust in Edge Computing for IoMT by Waleed Almuseelem

“…Within FL, an improved on-policy temporal difference control algorithm is leveraged for local model training. Moreover, this algorithm determines the optimal offloading strategy based on the global model while considering trustworthiness, the heterogeneous nature of tasks, resource availability, and latency. …”
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Online Autonomous Motion Control of Communication-Relay UAV with Channel Prediction in Dynamic Urban Environments by Cancan Tao, Bowen Liu

“…Considering that in practical applications, the radio frequency (RF) channel parameters in complex urban environments are difficult to obtain in advance and are constantly changing, an estimation algorithm based on Gaussian process learning is proposed for online evaluation of the wireless channel parameters near the current position of the UAV; for the optimal relay position search problem, in order to improve the real-time performance of the method, a line search algorithm and a general gradient-based algorithm are proposed, which are used for point-to-point communication and multi-node communication scenarios, respectively, reducing the two-dimensional search to a one-dimensional search, and the stability proof and convergence conditions of the algorithm are given. …”
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Intelligent End-Edge Computation Offloading Based on Lyapunov-Guided Deep Reinforcement Learning by Xue Feng, Chi Xu, Xi Jin, Changqing Xia, Jing Jiang

“…Then, we employ deep reinforcement learning algorithm, i.e., asynchronous advantage actor-critic (A3C), and propose Lyapunov-guided A3C algorithm named LyA3C to approximate the optimal computation offloading policy. …”
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Filter Observer-Based Attitude Control for Moving Mass Satellites Under Strong Aerodynamic Torques by Yuandong Hu, Zhengliang Lu, Wenhe Liao

“…The scheme integrates a moving mass device (MMD) with the traditional reaction wheel actuator to mitigate aerodynamic torques while maintaining effectiveness at varying orbital heights. …”
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IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
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Omnidirectional Motion Trajectory Tracking Control Method for AUVs by Jiangpeng XU, Junlei WANG, Yi TANG

“…Using the Bluefin series AUV as an example, the paper designed and modified the omnidirectional motion structure and developed a trajectory generation algorithm based on the Hermite algorithm, a trajectory guidance algorithm based on the scaling factor, and a sailing-heading hybrid control algorithm. …”
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Machine Learning-Based 3D Soil Layer Reconstruction in Foundation Pit Engineering by Chenxi Zhang, Nan Li, Xiuping Dong, Bin Liu, Meilian Liu

“…Therefore, soil layer reconstruction serves as a critical step, while sparse borehole data limit the accuracy of traditional reconstruction methods. …”
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Location estimation of UWB-based wireless capsule endoscopy using TDoA in various gastrointestinal simulation models. by Sruthi Krishnan, Mohammed Abdel-Hafez, Matti Hämäläinen

“…Though the present-day wireless capsule endoscopes certified for endoscopic procedures predominantly work on the Medical Implant Communication System (MICS) band, the applications based on the Ultra-Wide Band (UWB) are gaining popularity for their immense possibilities. While received signal strength, time of arrival, phase of arrival, and angle of arrival are the basic parameters applied in research for location estimation of WCE, this paper uses a time difference of arrival (TDoA) approach using the Chan algorithm. …”
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