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Model Predictive Control based Motion Cueing Algorithm for Driving Simulator

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Journal of Systems Science and Systems Engineering 2024年第5期33卷 607-626页

作者： Ayesha Hameed Ali Soltani Sharif Abadi Andrzej Ordys Institute of Automatic Control and Robotics Warsaw University of TechnologyWarsawPoland Institute of Electronic Systems Warsaw University of TechnologyWarsawPoland

Thanks to the emerging integration of algorithms and simulators, recent Driving Simulators (DS) find enormous potential in applications like advanced driver-assistance devices, analysis of driver’s behaviours, research and development of new vehicles and even for entertainment purposes. Driving simulators have been developed to reduce the cost of field studies, allow more flexible control over circumstances and measurements, and safely present hazardous conditions. The major challenge in a driving simulator is to reproduce realistic motions within hardware constraints. Motion Cueing Algorithm (MCA) guarantees a realistic motion perception in the simulator. However, the complex nature of the human perception system makes MCA implementation challenging. The present research aims to improve the performance of driving simulators by proposing and implementing the MCA algorithm as a control problem. The approach is realized using an actual vehicle model integrated with a detailed model of the human vestibular system, which accurately reproduces the driver’s perception. These perception motion signals are compared with simulated ones. A 2-DOF stabilized platform model is used to test the results from the two proposed control strategies, Proportional Integrator and Derivative (PID) and Model Predictive Control (MPC).

关键词： Driving simulator motion cueing algorithm control theory model predictive control PID

Enhancing Communication Accessibility:UrSL-CNN Approach to Urdu Sign Language Translation for Hearing-Impaired Individuals

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 689-711页

作者： Khushal Das Fazeel Abid Jawad Rasheed Kamlish Tunc Asuroglu Shtwai Alsubai Safeeullah Soomro Department of Computer Engineering Modeling Electronics and Systems EngineeringUniversity of CalabriaRende Cosenza87036Italy Department of Information Systems University of Management and TechnologyLahore54770Pakistan Department of Computer Engineering Istanbul Sabahattin Zaim UniversityIstanbul34303Turkey Department of Software Engineering Istanbul Nisantasi UniversityIstanbul34398Turkey Department of Computer Science COMSATS University IslamabadLahore CampusLahore54700Pakistan Faculty of Medicine and Health technology Tampere UniversityTampere33720Finland Department of Computer Science College of Computer Engineering and Sciences in Al-KharjPrince Sattam Bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Second Department of Computer Science College of Engineering and ComputingGeorge Mason UniversityFairfaxVA 4418USA

Deaf people or people facing hearing issues can communicate using sign language(SL),a visual *** works based on rich source language have been proposed;however,the work using poor resource language is still *** other SLs,the visuals of the Urdu Language are *** study presents a novel approach to translating Urdu sign language(UrSL)using the UrSL-CNN model,a convolutional neural network(CNN)architecture specifically designed for this *** existingworks that primarily focus on languageswith rich resources,this study addresses the challenge of translating a sign language with limited *** conducted experiments using two datasets containing 1500 and 78,000 images,employing a methodology comprising four modules:data collection,pre-processing,categorization,and *** enhance prediction accuracy,each sign image was transformed into a greyscale image and underwent noise *** analysis with machine learning baseline methods(support vectormachine,GaussianNaive Bayes,randomforest,and k-nearest neighbors’algorithm)on the UrSL alphabets dataset demonstrated the superiority of UrSL-CNN,achieving an accuracy of ***,our model exhibited superior performance in Precision,Recall,and F1-score *** work not only contributes to advancing sign language translation but also holds promise for improving communication accessibility for individuals with hearing impairments.

关键词： Convolutional neural networks Pakistan sign language visual language

Review of Fiber-Optic Localized Surface Plasmon Resonance Sensors:Geometries,Fabrication Technologies,and Bio-Applications

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Photonic Sensors 2024年第2期14卷 31-56页

作者： Mengdi LU Chen WANG Ruizhi FAN Ming LIN Jianye GUANG Wei PENG Affiliated Cancer Hospital Dalian University of TechnologyShenyang 110042China School of Physics Dalian University of TechnologyDalian 116024China

Localized surface plasmon resonance(LSPR)biosensors,which enable nanoscale confinement and manipulation of light,offer the enhanced sensitivity and electromagnetic energy *** integration of LSPR with the fiber-optic technology has led to the development of compact and versatile sensors for miniaturization and remote *** comprehensive review explores various sensor configurations,fiber types,and geometric shapes,highlighting their benefits in terms of sensitivity,integration,and performance *** techniques such as focused non-chemical bonding strategies and self-assembly of nanoparticles are discussed,providing control over nanostructure morphology and enhancing sensor ***-applications of fiber-optic LSPR(FOLSPR)sensors are detailed,specifically in biomolecular interactions and analysis of proteins,pathogens and cells,nucleic acids(DNA and RNA),and other small molecules(organic compounds and heavy metal ions).Surface modification and detection schemes are emphasized for their potential for label-free and real-time *** challenges and prospects of FOLSPR sensors are addressed,including the developments in sensitivity,fabrication techniques,and measurement *** with emerging technologies such as nanomaterials is highlighted as a promising direction for future ***,this review provides insights into the advancements and potential applications of FOLSPR sensors,paving the way for sensitive and versatile optical biosensing platforms in various fields.

关键词： Fiber-optic localized surface plasmon resonance biosensor nanoparticles geometric configuration fabrication technology

Electricity Theft Detection Method Based on Ensemble Learning and Prototype Learning

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 213-224页

作者： Xinwu Sun Jiaxiang Hu Zhenyuan Zhang Di Cao Qi Huang Zhe Chen Weihao Hu the School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengduChina Southwest University of Science and TechnologyChengduChina

With the development of advanced metering infrastructure(AMI),large amounts of electricity consumption data can be collected for electricity theft ***,the imbalance of electricity consumption data is violent,which makes the training of detection model *** this case,this paper proposes an electricity theft detection method based on ensemble learning and prototype learning,which has great performance on imbalanced dataset and abnormal data with different abnormal *** this paper,convolutional neural network(CNN)and long short-term memory(LSTM)are employed to obtain abstract feature from electricity consumption *** calculating the means of the abstract feature,the prototype per class is obtained,which is used to predict the labels of unknown *** the meanwhile,through training the network by different balanced subsets of training set,the prototype is *** with some mainstream methods including CNN,random forest(RF)and so on,the proposed method has been proved to effectively deal with the electricity theft detection when abnormal data only account for 2.5%and 1.25%of normal *** results show that the proposed method outperforms other state-of-the-art methods.

关键词： Electricity theft detection ensemble learning prototype learning imbalanced dataset deep learning abnormal level

Autonomous multi-drone racing method based on deep reinforcement learning

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Science China(Information Sciences) 2024年第8期67卷 35-48页

作者： Yu KANG Jian DI Ming LI Yunbo ZHAO Yuhui WANG Department of Automation University of Science and Technology of China Institute of Advanced technology University of Science and Technology of China Institute of Artificial Intelligence Hefei Comprehensive National Science Center College of Automation Engineering Nanjing University of Aeronautics and Astronautics

Racing drones have attracted increasing attention due to their remarkable high speed and excellent maneuverability. However, autonomous multi-drone racing is quite difficult since it requires quick and agile flight in intricate surroundings and rich drone interaction. To address these issues, we propose a novel autonomous multi-drone racing method based on deep reinforcement learning. A new set of reward functions is proposed to make racing drones learn the racing skills of human experts. Unlike previous methods that required global information about tracks and track boundary constraints, the proposed method requires only limited localized track information within the range of its own onboard sensors. Further, the dynamic response characteristics of racing drones are incorporated into the training environment, so that the proposed method is more in line with the requirements of real drone racing scenarios. In addition, our method has a low computational cost and can meet the requirements of real-time racing. Finally, the effectiveness and superiority of the proposed method are verified by extensive comparison with the state-of-the-art methods in a series of simulations and real-world experiments.

关键词： racing drone autonomous multi-drone racing sim-to-real deep reinforcement learning Markov game

On n-universal quadratic forms over dyadic local fields

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Science China Mathematics 2024年第7期67卷 1481-1506页

作者： Zilong He Yong Hu School of Computer Science and technology Dongguan University of TechnologyDongguan523808China Department of Mathematics Southern University of Science and TechnologyShenzhen518055China

Let n≥2 be an integer. We give necessary and sufficient conditions for an integral quadratic form over dyadic local fields to be n-universal by using invariants from Beli's theory of bases of norm ***, we provide a minimal set for testing n-universal quadratic forms over dyadic local fields, as an analogue of Bhargava and Hanke's 290-theorem(or Conway and Schneeberger's 15-theorem) on universal quadratic forms with integer coefficients.

关键词： integral quadratic forms n-universal quadratic forms dyadic fields 290-theorem

Local saliency consistency-based label inference for weakly supervised salient object detection using scribble annotations

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CAAI Transactions on Intelligence technology 2024年第1期9卷 239-249页

作者： Shuo Zhao Peng Cui Jing Shen Haibo Liu School of Computer Science and technology Harbin University of Science and TechnologyHarbinChina School of Computer Science and technology Harbin Engineering UniversityHarbinChina

Recently,weak supervision has received growing attention in the field of salient object detection due to the convenience of ***,there is a large performance gap between weakly supervised and fully supervised salient object detectors because the scribble annotation can only provide very limited foreground/background ***,an intuitive idea is to infer annotations that cover more complete object and background regions for *** this end,a label inference strategy is proposed based on the assumption that pixels with similar colours and close positions should have consistent ***,k-means clustering algorithm was first performed on both colours and coordinates of original annotations,and then assigned the same labels to points having similar colours with colour cluster centres and near coordinate cluster ***,the same annotations for pixels with similar colours within each kernel neighbourhood was set *** experiments on six benchmarks demonstrate that our method can significantly improve the performance and achieve the state-of-the-art results.

关键词： label inference salient object detection weak supervision

Experimental study on the dynamic response of a 3-D wedge under asymmetric impact

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Journal of Hydrodynamics 2024年第2期36卷 263-274页

作者： Saeed Hosseinzadeh Kristjan Tabri Maritime Engineering Research Group School of EngineeringUniversity of SouthamptonSouthamptonUK Department of Civil Engineering and Architecture Tallinn University of TechnologyTallinnEstonia Marine technology Competence Center Tallinn University of TechnologyKuressaareEstonia

Water entry problems represent complex multiphase flows involving air,water,and structure interaction,occurring rapidly in rough seas,and potentially effecting structural integrity of floating *** paper experimentally investigates asymmetric slamming loads acting on a 3-D elastic wedge *** specimen,featuring two different bottom plates(stiffened and unstiffened),each 4 mm thick,aims to assess the effect of structural stiffness on dynamic *** experiments are conducted at different drop heights of 25 cm and 50 cm and varying heel angles from 5°to 25°.The paper describes the experimental conditions,including wedge geometry,material properties,and the test *** study explores the influence of heel angle on impact acceleration,revealing an increase in peak acceleration with a higher inclination angle,particularly in the vertical ***,the hydrodynamic pressure resulting from asymmetric slamming is *** pressure results analyzed and compared at different locations along the length of the *** experimental findings indicate that,despite the leeward side(stiffened)experiencing a smaller hydrodynamic load,the heel angle significantly affects pressure results on the windward side(unstiffened),leading to a more pronounced dynamic *** time history of pressure results emphasizes the effect of elastic vibrations,particularly noticeable on the unstiffened bottom *** study contributes to a deeper understanding of asymmetric slamming on aluminum structures,facilitating the enhancement of mathematical models and the validation of numerical simulations.

关键词： Flexible fluid structure interactions(FFSI) experimental study asymmetric impact hydrodynamic pressure slamming loads

An improved particle filter indoor fusion positioning approach based on Wi-Fi/PDR/geomagnetic field

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Defence technology（防务技术） 2024年第2期32卷 443-458页

作者： Tianfa Wang Litao Han Qiaoli Kong Zeyu Li Changsong Li Jingwei Han Qi Bai Yanfei Chen College of Geodesy and Geomatics Shandong University of Science and TechnologyQingdao266590China Key Laboratory of Geomatics and Digital technology of Shandong Province Shandong University of Science and TechnologyQingdao266590China

The existing indoor fusion positioning methods based on Pedestrian Dead Reckoning(PDR)and geomagnetic technology have the problems of large initial position error,low sensor accuracy,and geomagnetic *** this study,a novel indoor fusion positioning approach based on the improved particle filter algorithm by geomagnetic iterative matching is proposed,where Wi-Fi,PDR,and geomagnetic signals are integrated to improve indoor positioning *** important contribution is that geomagnetic iterative matching is firstly proposed based on the particle filter *** the positioning process,an iterative window and a constraint window are introduced to limit the particle generation range and the geomagnetic matching range *** position is corrected several times based on geomagnetic iterative matching in the location correction stage when the pedestrian movement is detected,which made up for the shortage of only one time of geomagnetic correction in the existing particle filter *** addition,this study also proposes a real-time step detection algorithm based on multi-threshold constraints to judge whether pedestrians are moving,which satisfies the real-time requirement of our fusion positioning *** experimental verification,the average positioning accuracy of the proposed approach reaches 1.59 m,which improves 33.2%compared with the existing particle filter fusion positioning algorithms.

关键词： Fusion positioning Particle filter Geomagnetic iterative matching Iterative window Constraint window