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2nd International Conference on Frontiers of intelligent Manufacturing and Automation, CFIMA 2024

作者： Liu, Menghua Wu, Anping Bai, Kailun Yan, Haotian Yang, Xi Shi, Qing Wang, Huaping Hou, Yaozhen Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China School of Medical Technology Beijing Institute of Technology Beijing China Science and Technology on Space Physics Laboratory Beijing China

ISBN: (纸本)9798400710681

The 3D structure and microenvironmental morphology of the physical environment influence the migration pathways and modes of cancer cells, which is crucial for understanding cancer dissemination and metastasis mechanisms. However, existing microfluidic chip structures still face challenges in inducing directional migration of neuroblastoma cells along narrow tubular structures. This study introduces a microfluidic chip design featuring guidance channels and narrow drainage tubes to assess the migration capabilities of SH-SY5Y cells in narrow tubular environments. Specifically, SHSY5Y Cells Guidance Channels (SGCs) were designed and fabricated as functional zones to induce directional migration of cells, while two narrow drainage tubes were placed on either side to facilitate media drainage and alleviate channel blockages. By establishing directed flow from an initial chamber to a final chamber, cell migration along SGCs was induced. Experimental results demonstrate that the microfluidic chip with SGCs effectively evaluates cell migration in elongated tubular environments. Furthermore, increasing the initial cell density seeded into the chip significantly enhanced the number of cells undergoing directional migration. © 2024 Copyright held by the owner/author(s).

关键词： Microfluidics

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Immoral post detection using a one-dimensional convolutional neural network-based LSTM network

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Multimedia Tools and Applications 2025年 1-20页

作者： Saqia, Bibi Khan, Khairullah Rahman, Atta Ur Khan, Aurangzeb Jain, Deepak Kumar Department of Computer Science University of Science and Technology Bannu28100 Pakistan Riphah Institute of Systems Engineering Riphah International University Islamabad46000 Pakistan Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China Symbiosis Institute of Technology Symbiosis International University Pune India

In text mining and Natural Language Processing (NLP), extracting emotions from textual data is gaining rapid attraction. The proliferation of online content and the freedom of expression on social media platforms has compelled the advancement of more sophisticated methods for the automatic identification of unwanted content. The One-Dimensional Convolutional Neural Network (1D-CNN) performs best for feature extraction, while the Long Short-Term Memory Network (LSTM) is well-known for extracting sequential features and classification of textual data. This study proposes a novel solution by combining 1D-CNN with LSTM. Utilizing a context-aware model, this study aims to enhance the detection of immoral posts, including hate speech and other forms of immoral content on social media platforms. Various posts are extracted from social media, which are then processed using Glove word embedding models. It depicts the word representations in the text, which yields the form of a real-valued vector determining the words' meaning. The 1D convolution utilizes a filter window over the input time-series data to extract features. Relying on the acquired parameters of the filters, they act as feature extractors. This feature extraction technique allows the model to distinguish detailed patterns and nuances from the textual contents of posts. The sequential processing capabilities of the LSTM network enable an in-depth examination of the text, capturing temporal relationships and context, which is critical for successful content categorization. To validate the proposed model, we utilized a benchmark dataset, called the Twitter dataset. The proposed model achieved the highest accuracy of 95.37% and outperforms state-of-the-art works. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

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Modeling and Experimental Study of an Open Two-Phase Loop Driven by Osmotic Pressure and Capillary Force

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Frontiers in Heat and Mass Transfer 2025年第1期23卷 55-70页

作者： Hanli Bi Zheng Peng Chenpeng Liu Zhichao Jia Guoguang Li Yuandong Guo Hongxing Zhang Jianyin Miao National Key Laboratory of SpacecraftThermal Control Beijing Institute of Spacecraft System EngineeringChina Academy of Space TechnologyBeijing100094China School of Aeronautical Science and Engineering Beihang UniversityBeijing100083China School of Energy and Environment Engineering University of Science and Technology BeijingBeijing100083China

As space technology advances,thermal control systems must effectively collect and dissipate heat from distributed,multi-source *** heat pipe is a highly reliable two-phase heat transfer component,but it has several limitations when addressing multi-source heat *** by the transport and heat dissipation system of plants,large trees achieve stable and efficient liquid supply under the influence of two driving forces:capillary force during transpiration in the leaves(pull)and root pressure generated by osmotic pressure in the roots(push).The root pressure provides an effective liquid supply with a driving force exceeding 2 MPa,far greater than the driving force in conventional capillary-pumped two-phase *** has shown that osmotic heat pipes offer a powerful driving force,and combining osmotic pressure with capillary force has significant ***,this paper designs a multi-evaporator,dual-drive two-phase loop,using both osmotic pressure and capillary force to solve the multi-source heat dissipation ***,a transmembrane water flux model for the osmotic pressure-driven device was established to predict the maximum heat transfer capacity of the dual-drive two-phase ***,an experimental setup for a multi-evaporator“osmotic pressure+capillary force”dual-drive two-phase loop was constructed,capable of transferring at least 235 W of power under a reverse gravity condition of 20 *** study also analyzed the effects of reverse gravity height,heat load distribution among the three evaporators,startup sequence,and varying branch resistances on the performance of the dual-drive two-phase loop.

关键词： Multi-heat sources osmotic pressure two-phase loop dual-drive loop heat pipe

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Effects of aggregate size distribution and carbon nanotubes on the mechanical properties of cemented gangue backfill samples under true triaxial compression

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 311-324页

作者： Qian Yin Fan Wen Zhigang Tao Hai Pu Tianci Deng Yaoyao Meng Qingbin Meng Hongwen Jing Bo Meng Jiangyu Wu State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering China University of Mining and TechnologyXuzhou 221116China State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines Anhui University of Science and TechnologyHuainan 232001China State Key Laboratory for Geomechanics&Deep Underground Engineering China University of Mining and Technology(Beijing)Beijing 100083China Key Laboratory of Xinjiang Coal Resources Green Mining Ministry of EducationXinjiang Institute of EngineeringUrumqi 830023China

The mechanical behavior of cemented gangue backfill materials(CGBMs)is closely related to particle size distribution(PSD)of aggregates and properties of cementitious ***,the true triaxial compression tests,CT scanning,SEM,and EDS tests were conducted on cemented gangue backfill samples(CGBSs)with various carbon nanotube concentrations(P_(CNT))that satisfied fractal theory for the PSD of *** mechanical properties,energy dissipations,and failure mechanisms of the CGBSs under true triaxial compression were systematically *** results indicate that appropriate carbon nanotubes(CNTs)effectively enhance the mechanical properties and energy dissipations of CGBSs through micropore filling and microcrack bridging,and the optimal effect appears at P_(CNT)of 0.08wt%.Taking PSD fractal dimension(D)of 2.500 as an example,compared to that of CGBS without CNT,the peak strength(σ_(p)),axial peak strain(ε_(1,p)),elastic strain energy(Ue),and dissipated energy(U_(d))increased by 12.76%,29.60%,19.05%,and90.39%,***,excessive CNTs can reduce the mechanical properties of CGBSs due to CNT agglomeration,manifesting a decrease inρ_(p),ε_(1,p),and the volumetric strain increment(Δε_(v))when P_(CNT)increases from 0.08wt%to 0.12wt%.Moreover,the addition of CNTs improved the integrity of CGBS after macroscopic failure,and crack extension in CGBSs appeared in two modes:detour and pass through the ***σ_(p)and U_(d)firstly increase and then decrease with increasing D,and porosity shows the opposite ***ε_(1,p)andΔε_(v)are negatively correlated with D,and CGBS with D=2.150 has the maximum deformation parameters(ε_(1,p)=0.05079,Δε_(v)=0.01990)due to the frictional slip effect caused by coarse *** increasing D,the failure modes of CGBSs are sequentially manifested as oblique shear failure,"Y-shaped"shear failure,and conjugate shear failure.

关键词： cemented gangue backfill materials particle size distribution true triaxial compression test carbon nanotubes mechanical properties failure modes

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Modeling and Simulation of Mixed Traffic Flow Considering Autonomous Vehicles and the Impact of Trucks 24

Modeling and Simulation of Mixed Traffic Flow Considering Au...

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4th Asia-Pacific Artificial Intelligence and Big Data Forum, AIBDF 2024

作者： Kuang, Xianyan Zhang, Zuliang Jiangxi Province Key Laboratory of Multidimensional Intelligent Perception and Control Jiangxi University of Science and Technology Jiangxi Ganzhou China School of Electrical Engineering and Automation Jiangxi University of Science and Technology Jiangxi Ganzhou China

ISBN: (纸本)9798400710865

Heavy trucks play a crucial role in shaping highway traffic dynamics. Their slower speed and unique acceleration and deceleration patterns can greatly influence the efficiency and stability of mixed traffic streams. This study explores a traffic scenario involving both heavy trucks and Connected and Autonomous Vehicles (CAVs), presenting an innovative model for mixed traffic flow and establishing specific lane-changing protocols for autonomous vehicles. Utilizing numerical simulations and comparative analyses, the research explores how heavy trucks affect traffic speed and lane-changing dynamics across different levels of CAV integration and varying traffic conditions. The findings of the study indicate that with lower rates of CAV penetration, increased traffic flow heightens the frequency of vehicle interactions, resulting in more pronounced variations in traffic speed. Conversely, when CAV penetration rates are elevated, there is a marked improvement in average traffic speed, alongside a significant reduction in speed fluctuations, particularly in high-density traffic situations. © 2024 Copyright held by the owner/author(s).

关键词： Automobiles

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Kinematic Parameter Identification of Industrial Robots Based on an Improved Zebra Algorithm 16th

Kinematic Parameter Identification of Industrial Robots Base...

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16th International Conference on Modelling, Identification and control, ICMIC 2024

作者： Zhou, Houchen Gao, Guanbin Wang, Xi Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology Kunming650500 China Yunnan Key Laboratory of Intelligent Control and Application Kunming650500 China

ISBN: (纸本)9789819617760

Kinematic calibration is one of the main methods to improve the absolute positioning accuracy of industrial robots. Parameter identification is the primary step in determining the calibration effect. However, due to the large number of kinematic parameters of industrial robots and the complex coupling between parameters, the existing parameter identification methods easily fall into local optimal solutions, and it is difficult to obtain accurate kinematic parameters. Therefore, this paper proposes a Particle Swarm Somersault Foraging Zebra Optimization Algorithm (PSSFZOA) for kinematic parameter identification of industrial robots. The proposed PSSFZOA introduces the foraging strategy into the Zebra Optimization Algorithm (ZOA) and linearizes the kinematic error model so that it does not fall into the local optimum in the later stage of optimization, and improves the population diversity in the early stage. In the first stage of the algorithm, the particle swarm strategy is used to provide local optimal particles, which ensures that the algorithm achieves a balance between global search and local search. It has both the ability of deep search and the diversity of breadth search better to find the best in the complex search space. Simulations are carried out to verify the effectiveness of the method. The results show that compared with the existing Grey Wolf Optimization (GWO) and ZOA, the PSSFZOA can avoid falling into local optimum prematurely, accelerate the convergence speed of the algorithm, and improve the absolute positioning accuracy of the industrial robot after parameter identification. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Industrial robots

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Deterministic Event-Based Physical Watermarks Against Replay Attacks in Cyber-Physical Systems

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 61-69页

作者： Zhao, Xudong Xing, Wei Zhang, Junfeng Wang, Xinyu Zong, Guangdeng Zhao, Ning Hainan University School of Information and Communication Engineering Haikou570288 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian116622 China Tiangong University School of Control Science and Engineering Tianjin300387 China Bohai University College of Control Science and Engineering Jinzhou121013 China

Cyber-physical systems (CPSs) are of great importance in various applications and have garnered significant attention. Ensuring their security is a crucial concern, while this paper focuses on the security of CPSs against replay attacks during the transmission of sensor measurements over a wireless network. It is widely recognized that incorporating physical watermark signals is an effective approach to mitigate replay attacks. However, traditional physical watermarks are time-based and result in a notable degradation in the performance of Linear Quadratic Gaussian systems. With this in mind, a novel event-based physical watermarking technique is devised to address the performance degradation and detect replay attacks. The approach involves a deterministic physical watermark schedule that utilizes the innovation sequence to determine whether to incorporate physical watermarks or not. We provide evidence that the probability of successfully embedding physical watermarks increases when the system is targeted by malicious attacks. Additionally, we demonstrate that the deterministic event-based watermarking approach is more effective than the traditional time-based watermarking method. Finally, simulation examples are included to validate and illustrate the theoretical results. © 2023 IEEE.

关键词： Cyber attacks

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Giant spatial Goos-Hänchen shift achieved in superconducting hyperbolic metamaterials with graphene

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Optics Express 2025年第9期33卷 19359-19370页

作者： Yang, Junfu Xie, Zhijiang Ni, Hao Chen, Xiaoling Qin, Zhongli Zhao, Dong Zhao, Miaomiao State Key Laboratory of Mechanical Transmission for Advanced Equipment Chongqing University Chongqing400044 China College of Mechanical and Vehicle Engineering Chongqing University Chongqing400044 China School of Electronic and Information Engineering Hubei University of Science and Technology Xianning437100 China Hubei Provincial Key Laboratory of Optoelectronic Information and Intelligent Control Hubei University of Science and Technology Xianning437100 China

We have theoretically analyzed the enhancement and regulation of the Goos-Hänchen (GH) shift within hyperbolic metamaterials in the near-infrared band under low-temperature conditions. Given a fixed incident wavelength, photonic crystals constructed from graphene and superconductor present hyperbolic dispersion characteristics in the dispersion space by modulating the Fermi energy of graphene. Near the critical phase transition point from elliptic dispersion to hyperbolic dispersion, the phase of the reflection coefficient undergoes an abrupt alteration. Consequently, a remarkably large GH shift occurs precisely at the resonant state. A substantial GH shift can be effectively realized by regulating the layers of graphene, the thickness of the superconductor, and the temperature. The largest positive GH shift reaches up to 4000λ at T = 200 K. This research is anticipated to provide theoretical guidance for devising high-sensitivity temperature sensors based on the GH shift effect in hyperbolic materials within a low-temperature environment. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Metamaterials

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intelligent equalizing pressure ventilation system for coal mine: A case study of the 104 coal mining face in Shige Tai Mine

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Energy Reports 2025年 13卷 4998-5005页

作者： Geng, Feng Li, Wei Liu, Yanqing Peng, Ran Li, Zongxiang Liu, Hanwu Intelligent Control Technology Co. Ltd. Beijing100013 China Mine Intelligent Ventilation Division China Coal Research Institute Beijing100013 China Beijing Engineering and Research Center of Mine Safe Beijing100013 China National Key Laboratory of Intelligent Coal Mining and Rock Strata Control Beijing100013 China Safety Science and Engineering College Liaoning Technical University Liaoning 123000 China Beijing100083 China

This study investigates the application of an intelligent equalizing pressure ventilation system in the 104 coal mining face of the Shige Tai Mine. The relationship between the balanced pressure window opening area and the face air volume, as well as the equalizing pressure, was analyzed. A formula for calculating the local resistance of the balanced pressure window was derived. The combined regulation of the equalizing pressure local fan and the balanced pressure window was used to develop an intelligent equalizing pressure ventilation system, which can remotely and intelligently regulate the equalizing pressure of the mining face. The results show that the local wind resistance of the balanced pressure window is negatively exponentially related to its ventilation area, and the ventilation resistance of the working face is positively correlated with the air supply volume. After the combined equalizing pressure regulation, the volume fractions of CO2 and CO were significantly reduced, meeting the required air volume of the working face and achieving the expected effect of equalizing pressure ventilation. This study provides theoretical references for the intelligent equalizing pressure ventilation in coal mine mining faces. © 2025 The Authors

关键词： Coal mines

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Thermal constraint control of reversible solid oxide cell for optimal system efficiency

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International Journal of Hydrogen Energy 2025年 134卷 198-211页

作者： Xu, Yuanwu Yin, Jie Wang, Jingjing Wu, Xiao-long Peng, Jingxuan Tang, Ruifeng Zou, Suhang Fu, Xiaowei Li, Xi School of Artificial Intelligence and Automation Wuhan University of Science and Technology Hubei Wuhan430081 China School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China School of Information Engineering Nanchang University Jiangxi Nanchang330031 China School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore China-Poland Belt and Road Joint Laboratory on Measurement and Control Technology Huazhong University of Science and Technology Hubei Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen518055 China

Reversible solid oxide cell (RSOC) demonstrates considerable promise in multimodal energy conversion architectures, particularly as a technology for hydrogen-based energy storage systems. Nevertheless, under dynamic operating regimes with time-varying current inputs, realizing time-efficient and reliable transitions to steady-state operation remains difficult. This difficulty arises from the intricate coupling of thermal, electrical, and gaseous processes within the RSOC system. This study aims to address these challenges by developing a 5 kW mathematical model of the RSOC system. The proposed model enables systematic investigation of thermal safety issues arising during current switching operations while introducing a thermal constraint control strategy to enhance both system efficiency and thermal safety performance. This efficiency-driven study employs the Grid Search algorithm to identify optimal steady-state operating points for the RSOC system, ensuring strict adherence to safety constraints across varying current inputs. Furthermore, by integrating the pre-identified optimal operating points as feedforward control with Model Predictive control (MPC)-based feedback correction, this hybrid strategy effectively mitigates stack temperature gradient overshoot while synchronously ensuring optimal system efficiency throughout current transition processes. Under simulated variable current inputs, the proposed RSOC system model and control strategy demonstrate the capability to constrain stack temperature gradient overshoot within 2.3K while enhancing transient efficiency by 5 %–8 %, achieving a peak system efficiency of 85 %. It provides a novel methodology for safe and efficient working with intermittent renewable energy. © 2025 Hydrogen Energy Publications LLC

关键词： Thermal variables control

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