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Enhancing the spatter-removal rate in laser powder-bed fusion using a gas-intake system with dual inlets

Journal of Zhejiang University-science A(applied Physics & engineering) 2025年第3期26卷 252-265页

作者： Xin TIAN Junwei ZHONG Youwen YANG Chaolei ZHANG Long ZHAO School of Mechanical and Electrical Engineering Jiangxi University of Science and TechnologyGanzhou341000China College of Engineering and Applied Science Nanjing UniversityNanjing210089China

Mounds of spatter are generated in laser powder-bed fusion(L-PBF)additive manufacturing,which reduces build quality and laser *** to the lack of supplemental airflow above the chamber,the conventional build chamber with a single gas inlet exhibits a pronounced tendency for gas to flow upward near the *** phenomenon results in the formation of a large vortex within the build *** vortex leads to the chaotic motion trajectory of the spatter in the build *** design defects of the existing build chamber based on dual gas inlets are shown in this *** established a coupled computational fluid dynamics-discrete phase model(CFD-DPM)model to optimize the build chamber by adjusting the position and structure of the second gas *** homogeneity of the flow is increased with a distance of 379 mm between the two inlets and a wider-reaching second *** Coanda effect is also crucial in the spatter-removal *** Coanda effect is reduced by modifying the right sidewall of the build chamber and increasing the pressure difference between the inlet and ***,we found that the spatter-removal rate rose from 8.9%to 76.1%between the conventional build chamber with a single gas inlet and the optimized build chamber with two gas inlets.

关键词： Laser powder-bed fusion(L-PBF) Computational fluid dynamics(CFD) Flow field simulation Structural optimization Coanda effect

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ST-GRU: spatiotemporal gated recurrent unit for video prediction

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Multimedia Systems 2025年第3期31卷 1-14页

作者： Dong, Jing Zhang, Junzhuo Xie, Ben Zhang, Jie Liu, Chang Cheng, Wei College of Electrical Engineering and Control Science Nanjing Tech University Jiangsu Nanjing China College of Electrical and Information Engineering Zhengzhou University of Light Industry Henan Zhengzhou China College of Ocean Science and Engineering Shandong University of Science and Technology Shandong Qingdao China Beijing Institute of Applied Meteorology Beijing China

Video prediction which aims to generate future frames by learning from historical information is a challenging task due to dynamic motions and appearance changes in videos. Many existing methods are based on convolutional long short-term memory (ConvLSTM) networks or convolutional gated recurrent unit (ConvGRU) networks. PredRNN proposed recently has achieved promising results. However, the basic predictive unit of PredRNN is based on ConvLSTM, while ConvGRU which has similar performance using fewer parameters is not considered. To address this issue, we propose a novel Spatiotemporal Gated Recurrent Unit (ST-GRU) by introducing a spatiotemporal memory to ConvGRU and updating this memory using a gating mechanism. Using ST-GRU as the basic memory cell, we develop a predictive model where a spatiotemporal memory flow is applied to preserve the visual dynamics of different layers. In this case, the proposed model can extract and memorize spatial and temporal representation simultaneously. Experiments performed on several commonly used datasets demonstrate the effectiveness of the proposed model. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Convolutional gated recurrent unit PredRNN Spatiotemporal predictive learning Video prediction

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Adaptive Cooperative Quality Weight Spectrum Sensing for Mitigating Byzantine Attacks in Cognitive Radio

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IEEE Access 2025年 13卷 80930-80940页

作者： Srisomboon, Kanabadee Pipanmekaporn, Luepol Prayote, Akara Lee, Wilaiporn Division of Electrical Engineering Department of Electrical and Computer Engineering Faculty of Engineering Bangkok10800 Thailand King Mongkut’s University of Technology North Bangkok Faculty of Applied Science Department of Computer and Information Science Bangkok10800 Thailand

Spectrum sensing data falsification (SSDF) attack, i.e., Byzantine attack, is one of the critical threats of the cooperative spectrum sensing where the Byzantine attackers (BAs) forward incorrect local sensing results to mislead the fusion center on channel availability decisions. By using traditional voting rule, the cooperative spectrum sensing performance deteriorates significantly due to incorrect local sensing results. Then, reliability weight strategy becomes the popular solution to avoid incorrect sensing results from BAs and unreliable cognitive radio users (CRUs). However, it is very difficult to detect the attackers since they also occasionally provide correct sensing results to the fusion center for concealing the attack objective. Based on existing techniques, the BAs and CRUs may be assigned with low reliability weights or distinguished from the data fusion account. However, it is very difficult to detect the attackers since they also occasionally provide correct sensing results to the fusion center for concealing the attack objective. Then, existing techniques still suffer from BAs and negative impact of unreliable CRUs. In this paper, we propose the adaptive cooperative quality weight algorithm for mitigating the Byzantine attack issue by distinguishing the BAs and CRUs from the data fusion account while selecting only useful CRUs since the number of members in the account is also the important factor for cooperative spectrum sensing. In our proposed algorithm, we adopt a stable preference ordering towards ideal solution (SPOTIS) for determining the reliability of SUs which shows low computational complexity as compared to other reliability weight-based techniques. To achieve high sensing performance, our global decision threshold is adapted according to the reliability of reliable users. From the simulation results, our proposed algorithm significantly improves global detection probability and total error probability compared to the traditional votin

关键词： Sensors Reliability Barium Radio spectrum management Cooperative communication Cognitive radio Data integration Signal to noise ratio Heuristic algorithms Dynamic spectrum access

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Centripetal Intensive Deep Hashing for Remote Sensing Image Retrieval

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IEEE Journal of Selected Topics in applied Earth Observations and Remote Sensing 2025年 18卷 12439-12453页

作者： Wang, Weigang Guo, Zhongwen Cui, Ziyuan Zhao, Hailei Xian, Lintao The Faculty of Electrical Engineering and Computer Science Ocean University of China Qingdao266499 China The Department of Intelligent Medical Engineering Shandong Second Medical University Weifang261053 China

With the breakthrough of convolutional neural networks, deep hashing methods have demonstrated remarkable performance in large-scale image retrieval tasks. However, existing deep supervised hashing methods, which rely on pairwise or triplet labels, typically learn the hash function via random or hardest sample mining within training batches. This strategy primarily captures local sample similarities, causing a distribution shift and limiting retrieval performance. Furthermore, most methods emphasize global features while overlooking structural information, which is essential for understanding spatial relationships in images. To solve these limitations, we propose a Centripetal Intensive Deep Hashing (CIDH) method for remote sensing image retrieval. Initially, we design a Hybrid-Attention Guided Multiscale Refinement Network (HGMRN) that integrates channel and spatial attention to capture multiscale visual features and highlight salient regions at different scales. Subsequently, we introduce a central similarity loss via class-centered labels to optimize the spatial distribution of global samples, which can encourage hash codes with similar semantics to cluster around centroids and reduce distribution shift. Meanwhile, we incorporate a central intensive loss into the Hamming space to shorten intra-class Hamming distances, generating more compact and discriminative hash codes. Extensive experiments demonstrate the superiority of our CIDH method compared with current state-of-the-art deep hashing methods. © 2008-2012 IEEE.

关键词： Hamming distance

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Zero-dynamics attack detection based on data association in feedback pathway

Cognitive Robotics

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Cognitive Robotics 2025年 5卷 126-139页

作者： Zhang, Zeyu Li, Hongran Todo, Yuki Division of Electrical Engineering and Computer Science Kanazawa University Ishikawa Kanazawa9201192 Japan School of Computer Engineering Jiangsu Ocean University Jiangsu Lianyungang222005 China Faculty of Electrical Information and Communication Engineering Kanazawa University Ishikawa Kanazawa9201192 Japan

This paper considers the security of non-minimum phase systems, a typical kind of cyber-physical systems. Non-minimum phase systems are characterized by unstable zeros in their transfer functions, making them particularly susceptible to disturbances and attacks. The non-minimum phase systems are more vulnerable to zero-dynamics attack (ZDA) than minimum phase systems. ZDA is a stealthy attack strategy that exploits the internal dynamics of a system, remaining undetectable while causing gradual system destabilization. Recent cyber incidents have demonstrated the increasing risk of such hidden attacks in critical infrastructures, such as power grids and transportation systems. This paper first demonstrates that the existing ZDA has the limitation of falling into local convergence, and then proposes an enhanced zero-dynamics attack (EZDA), which overcomes local convergence by diverging system data. Furthermore, this paper presents an autoregressive model which can build the data association between the original data and the forged data. By observing the fluctuations in state values, the presented model can detect not only ZDA, but also EZDA. Finally, numerical simulations and an application example are provided to verify the theoretical results. © 2025

关键词： Cyber attacks

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HoloStream: a GPU-powered high-speed user interface for holographic microscopy imaging

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Optics Express 2025年第7期33卷 15648-15660页

作者： Morales, Johan Obando-Vásquez, Sofia Doblas, Ana Trujillo, Carlos Applied Optics Group School of Applied Science and Engineering EAFIT University Medellin Colombia Optical Imaging Research Lab Electrical and Computer Engineering Department University of Massachusetts Dartmouth DartmouthMA United States

This paper presents HoloStream, a GPU-powered high-speed user interface designed for holographic microscopy imaging. The platform reconstructs quantitative phase images rapidly for off-axis digital holographic microscopy (DHM) systems operating in the telecentric regime. By optimizing critical computational procedures, the HoloStream app reconstructs phase maps of 1280 × 960 pixels up to 11 frames per second (FPS) in live visualization and 90 fps for pre-recorded holographic videos. This real-time phase compensation is performed by upgrading the semi-heuristic phase compensation (SHPC) algorithm through GPU acceleration via PyCUDA. The interface also offers a user-friendly experience with flexible control over acquisition modes, visualization formats, and 3D tracking functionalities. Experimental validation demonstrates the platform’s capability to achieve fast and accurate phase imaging for live microscopy applications. The HoloStream app advances DHM technology by combining high-speed processing with ease of use, making it suitable for a wide range of DHM imaging applications. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Computer graphics equipment

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Finite time hybrid synchronization of heterogeneous duplex complex networks via time-varying intermittent control

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Chinese Physics B 2025年第4期34卷 354-363页

作者： Cheng-Jun Xie Xiang-Qing Lu College of Artificial Intelligence and Electrical Engineering Guangzhou College of Applied Science and TechnologyZhaoqing 526000China Institute of Intelligent Manufacturing Guangzhou College of Applied Science and TechnologyZhaoqing 526000China College of Computers and Technology BeiHua UniversityJilin 132021China

This paper study the finite time internal synchronization and the external synchronization(hybrid synchronization)for duplex heterogeneous complex networks by time-varying intermittent *** few study hybrid synchronization of heterogeneous duplex complex ***,we study the finite time hybrid synchronization of heterogeneous duplex networks,which employs the time-varying intermittent control to drive the duplex heterogeneous complex networks to achieve hybrid synchronization in finite *** be specific,the switch frequency of the controllers can be changed with time by devise Lyapunov function and boundary function,the internal synchronization and external synchronization are achieved simultaneously in finite ***,numerical examples are presented to illustrate the validness of theoretical results.

关键词： finite time synchronization time-varying intermittent control duplex heterogeneous networks complex networks

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Open-Gap Algorithm for Fast Reactive Collision Avoidance by Autonomous UAV using Sensor Array

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Journal of Aeronautics, Astronautics and Aviation 2025年第3期57卷 505-511页

作者： Butt, Muhammad Zohaib Nasir, Nazri Rashid, Rozeha A. Tang, Collin H.H. Department of Aeronautics Automotive and Ocean Engineering Faculty of Mechanical Engineering Universiti Teknologi Malaysia Malaysia UTM Aero Lab Institute for Vehicle Systems & Engineering Universiti Teknologi Malaysia Malaysia Department of Communication Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Malaysia Department of Applied Mechanics and Design Faculty of Mechanical Engineering Universiti Teknologi Malaysia Malaysia

This paper presents a new local reactive collision avoidance strategy for autonomous unmanned aerial vehicles (UAVs) that operate in dynamic environments. Compared to ground robots, UAVs face greater challenges in terms of faster reaction time and encounter rapid environmental changes during low-flight operations due to their higher speed. Additionally, small UAVs have limited payload capacity, restricting their flight time, computational power, and sensing capabilities. For low-altitude autonomous flights, a fast and efficient computation approach is developed to avoid moving as well as stationary obstacles. Using a circular array of sensors onboard, the algorithm detects suitable open gaps within the circular proximity of the UAV. Then, to reach the designated target location, the algorithm chooses the most suitable gap. The proposed algorithm enhances the UAV’s ability at low-altitudes to perform collision-less navigation in unstructured environments without prior knowledge of the obstacle map. A simulated environment was used to test the proposed algorithm. © 2025 The Aeronautical and Astronautical Society of the Republic of China. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Monolithic 3-D Integration of Diverse Memories: Resistive Switching (RRAM) and Gain Cell (GC) Memory Integrated on Si CMOS

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IEEE Transactions on Electron Devices 2025年第5期72卷 2685-2690页

作者： Liu, Shuhan Radway, Robert M. Wang, Xinxin Moro, Filippo Nodin, Jean-Francois Jana, Koustav Yan, Lixian Du, Shuting Upton, Luke R. Chen, Wei-Chen Kang, Jimin Chen, Jian Li, Haitong Andrieu, Francois Vianello, Elisa Raina, Priyanka Mitra, Subhasish Wong, H.-S. Philip Stanford University Department of Electrical Engineering StanfordCA94305 United States University of Pennsylvania School of Engineering and Applied Science Department of Electrical and Systems Engineering PhiladelphiaPA19104 United States Université Grenoble Alpes CEA-Leti Grenoble38058 France Purdue University Department of Electrical and Computer Engineering West LafayetteIN47907 United States

The future memory is massive, diverse, and tightly integrated with computing. This research presents tight integration, both physically and architecturally, of two on-chip memory technologies, resistive switching random access memory (RRAM) and gain cell (GC) memory. HfO2 RRAM and indium tin oxide (ITO) GC memory are monolithically integrated on 130-nm Si CMOS technology to form a joint memory that enables low-energy training and low-standby-power inference for edge devices. High-bandwidth on-chip data transfer can have a bandwidth that is 90x state-of-the-art (SoTA) HBM3E and 211x PCIe 7.0, enabled by high-density monolithic 3-D interconnections between memory arrays and high-speed transfer circuit within the integrated joint memory macro. Fabricated atomic layer deposition (ALD) ITO FET exhibits positive VTHof 0.67 V, excellent subthreshold slope (SS) of 65 mV/dec, high ON-current of 20 μA/μm, and low OFF-current of 5 x 10-18 A/μm, as extracted from >5000 s retention. The joint memory macro consumes 78% less standby power and 95% less training energy for MobileBERT compared to SRAM with iso-capacity. This RRAM-GC joint memory facilitates efficient continual learning in edge devices, addressing the challenges of a resource-constrained environment while supporting adaptive artificial intelligence (AI) model updates. © 1963-2012 IEEE.

关键词： RRAM

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A Target Tracking Node Selection Method for UWSNs Based on Dynamic Topology

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IEEE Sensors Journal 2025年第6期25卷 10345-10357页

作者： Lv, Zhaohong Zhang, Zhenkai Seet, Boon-Chong Jiangsu University of Science and Technology Ocean College Zhenjiang212003 China Auckland University of Technology Department of Electrical and Electronic Engineering Auckland1010 New Zealand

In order to improve the energy utilization efficiency of underwater wireless sensor networks (UWSNs) in target tracking, a node selection algorithm based on dynamic posterior Cramer-Rao lower bound (PCRLB) is proposed and extended to passive tracking scenarios. First, a residual correction particle filter (RCPF) algorithm is proposed to effectively reduce the interference of complex underwater noise. The RCPF algorithm is validated through simulations and real-world experiments, demonstrating its effectiveness in practical underwater conditions. Next, the mathematical relationship between the node position and the dynamic PCRLB is established. The optimal dynamic PCRLB for the node is then derived using the Lagrange multiplier method and conjugate gradient method. Finally, the node's optimal dynamic PCRLB and the mobile energy consumption are used as the criteria for node selection. By selecting nodes with better indicators to participate in target tracking, the energy efficiency of target tracking is improved. The simulation results show that the proposed algorithm can effectively improve the energy efficiency of target tracking and prolong the network lifetime, showcasing its practical value in underwater monitoring applications. © 2001-2012 IEEE.

关键词： Conjugate gradient method

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