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Physics-based fuid simulation in computer graphics: Survey, research trends, and challenges

Computational Visual Media 2024年第5期10卷 803-858页

作者： Xiaokun Wang Yanrui Xu Sinuo Liu Bo Ren Jiri Kosinka Alexandru C.Telea Jiamin Wang Chongming Song Jian Chang Chenfeng Li Jian Jun Zhang Xiaojuan Ban Beijing Advanced Innovation Center for Materials Genome Engineering and School of Intelligence Science and Technologyand Shunde Innovation School University of Science and Technology BeijingBeijing 100083China National Center for Computer Animation Faculty of Media and CommunicationBournemouth UniversityPoole BH125BBUK. Bernoulli Institute University of GroningenGroningen 9700 AKthe Netherlands School of Computer Science Peking UniversityBeijing 100871China. TMCC College of Computer ScienceNankai UniversityTianjin 300350China Department of Information and Computing Sciences Utrecht UniversityUtrecht 3584 CCthe Netherlands. Zienkiewicz Institute for Modelling Data and AISwansea UniversitySwansea SA18ENUK. Institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang 110004China.

Physics-based fluid simulation has played an increasingly important role in the computer graphics *** methods in this area have greatly improved the generation of complex visual effects and its computational *** techniques have emerged to deal with complex boundaries,multiphase fluids,gas-liquid interfaces,and fine *** parallel use of machine learning,image processing,and fluid control technologies has brought many interesting and novel research *** this survey,we provide an introduction to theoretical concepts underpinning physics-based fuid simulation and their practical implementation,with the aim for it to serve as a guide for both newcomers and seasoned researchers to explore the field of physics-based fuid simulation,with a focus on developments in the last *** by the distribution of recent publications in the field,we structure our survey to cover physical background;discretization approaches;computational methods that address scalability;fuid interactions with other materials and interfaces;and methods for expressive aspects of surface detail and *** a practical perspective,we give an overview of existing implementations available for the above methods.

关键词： computer graphics physical simulation fluid simulation fluid coupling

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A straightforward spectral emissivity estimating method based on constructing random rough surfaces

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Light(science & Applications) 2023年第12期12卷 2577-2588页

作者： Zezhan Zhang Mengchao Chen Lichuan Zhang Hongzu Li Hairui Huang Zilong Zhang Peifeng Yu Yi Niu Shan Gao Chao Wang Jing Jiang Clean Energy Materials and Engineering Center School of Integrated Circuit Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengduChina College of Information and Communication Engineering Harbin Engineering UniversityHarbinChina Department of Precision Instrument Tsinghua UniversityBeijingChina

Spectral emissivity is an essential and sensitive parameter to characterize the radiative capacity of the solid surface in scientific and engineering applications,which would be non-negligibly affected by surface ***,there is a lack of assessment of the effect of roughness on emissivity and a straightforward method for estimating the emissivity of rough *** paper established an estimating method based on constructing random rough surfaces to predict rough surface(Geometric region)emissivity for metal *** on this method,the emissivity of ideal gray and non-gray body surfaces was calculated and *** calculated and measured spectral emissivities of GH3044,K465,DD6,and TC4 alloys with different roughness were *** results show that the emissivity increases with the roughness degree,and the enhancement effect weakens with the increase of roughness or emissivity due to the existing limit(emissivityε=1.0).At the same time,the roughness would not change the overall spectral distribution characteristics but may attenuate the local features of the spectral *** estimated results are in good agreement with the experimental data for the above alloys'rough *** study provides a new reliable approach to obtaining the spectral emissivity of rough *** approach is especially beneficial for measuring objects in extreme environments where emissivity is difficult to ***,this study promotes an understanding of surface morphology's effect mechanism on emissivity.

关键词： alloys roughness estimating

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Towards Open-Vocabulary Video Semantic Segmentation

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IEEE Transactions on Multimedia 2025年 27卷 2924-2934页

作者： Li, Xinhao Liu, Yun Sun, Guolei Wu, Min Zhang, Le Zhu, Ce University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Nankai University College of Computer Science Tianjin300350 China ETH Zurich Computer Vision Lab Zurich8092 Switzerland 138632 Singapore

Semantic segmentation in videos has been a focal point of recent research. However, existing models encounter challenges when faced with unfamiliar categories. To address this, we introduce the Open Vocabulary Video Semantic Segmentation (OV-VSS) task, designed to accurately segment every pixel across a wide range of open-vocabulary categories, including those that are novel or previously unexplored. To enhance OV-VSS performance, we propose a robust baseline, OV2VSS, which integrates a spatial-temporal fusion module, allowing the model to utilize temporal relationships across consecutive frames. Additionally, we incorporate a random frame enhancement module, broadening the model's understanding of semantic context throughout the entire video sequence. Our approach also includes video text encoding, which strengthens the model's capability to interpret textual information within the video context. Comprehensive evaluations on benchmark datasets such as VSPW and Cityscapes highlight OV-VSS's zero-shot generalization capabilities, especially in handling novel categories. The results validate OV2VSS's effectiveness, demonstrating improved performance in semantic segmentation tasks across diverse video datasets. © 1999-2012 IEEE.

关键词： Semantic Segmentation

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Efficient communication in Wireless Sensor Networks Using Optimized Energy Efficient Engroove Leach Clustering Protocol

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Tsinghua science and technology 2024年第4期29卷 985-1001页

作者： N.Meenakshi Sultan Ahmad A.V.Prabu J.Nageswara Rao Nashwan Adnan Othman Hikmat A.M.Abdeljaber R.Sekar Jabeen Nazeer SRM Institute of Science and Technology KattankulathurChennai 603203India Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharj 11942Saudi Arabia University Center for Research and Development(UCRD) Department of Computer Science and EngineeringChandigarh UniversityGharuanMohali 140413India Department of ECE Koneru Lakshmaiah Education FoundationVaddeswaramGuntur 522502India Department of Computer Science and Engineering Lakireddy Balireddy College of Engineering(A)NTR District 521230India Department of Computer Engineering College of EngineeringKnowledge UniversityErbil 44001Iraq Department of Computer Science Faculty of Information TechnologyApplied Science Private UniversityAmman 11937Jordan Department of Electronics and Communication Engineering(ECE) School of EngineeringPresidency UniversityBangalore 834001India

The Wireless Sensor Network(WSN)is a network that is constructed in regions that are inaccessible to human *** widespread deployment of wireless micro sensors will make it possible to conduct accurate environmental monitoring for a use in both civil and military *** make use of these data to monitor and keep track of the physical data of the surrounding environment in order to ensure the sustainability of the *** data have to be picked up by the sensor,and then sent to the sink node where they may be *** nodes of the WSNs are powered by batteries,therefore they eventually run out of *** energy restriction has an effect on the network life span and environmental *** objective of this study is to further improve the Engroove Leach(EL)protocol’s energy efficiency so that the network can operate for a very long time while consuming the least amount of *** lifespan of WSNs is being extended often using clustering and routing *** Meta Inspired Hawks Fragment Optimization(MIHFO)system,which is based on passive clustering,is used in this study to do *** cluster head is chosen based on the nodes’residual energy,distance to neighbors,distance to base station,node degree,and node *** on distance,residual energy,and node degree,an algorithm known as Heuristic Wing Antfly Optimization(HWAFO)selects the optimum path between the cluster head and Base Station(BS).They examine the number of nodes that are active,their energy consumption,and the number of data packets that the BS *** overall experimentation is carried out under the MATLAB *** the analysis,it has been discovered that the suggested approach yields noticeably superior outcomes in terms of throughput,packet delivery and drop ratio,and average energy consumption.

关键词： wireless sensor networks energy efficient engroove leach protocol meta inspired Hawks fragment optimization heuristic wing antfly optimization

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Classification with ensembles and case study on functional magnetic resonance imaging

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Digital communications and Networks 2022年第1期8卷 80-86页

作者： Adnan OM.Abuassba Zhang Dezheng Hazrat Ali Fan Zhang Khan Ali Department of Computer Science Arab Open University-PalestineRamallahPalestine Department of Computer Science and Communication Engineering University of Science and Technology BeijingChina and Beijing Key Laboratory of Knowledge Engineering for Materials ScienceBeijing100083China Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad CampusAbbottabadPakistan

The ensemble is a technique that strategically combines basic models to achieve better accuracy ***,combination methods,and selection topology are the main factors determining ensemble ***,it is a challenging task to design an efficient ensemble *** though numerous paradigms have been proposed to classify ensemble schemes,there is still much room for *** paper proposes a general framework for creating ensembles in the context of ***,the ensemble framework consists of four stages:objectives,data preparing,model training,and model *** is comprehensive to design diverse *** proposed ensemble approach can be used for a wide variety of machine learning *** validate our approach on real-world *** experimental results show the efficiency of the proposed approach.

关键词： Classification Ensemble learning Extreme learning machine

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A transformer generative adversarial network for multi-track music generation

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CAAI Transactions on Intelligence technology 2022年第3期7卷 369-380页

作者： Cong Jin Tao Wang Xiaobing Li Chu Jie Jiessie Tie Yun Tie Shan Liu Ming Yan Yongzhi Li Junxian Wang Shenze Huang School of Information and Communication Engineering Communication University of ChinaBeijingChina School of Information and Engineering Zhengzhou UniversityZhengzhouChina Central Conservatory of Music BeijingChina Department of computer Science University of TorontoTorontoCanada School of Data Science and Media Intelligence Communication University of ChinaBeijingChina School of Light Industry and Engineering South China University of TechnologyGuangzhouChina School of Animation and Digital Arts Communication University of ChinaBeijingChina

This study proposes a new generation network based on transformers and guided by the music theory to produce high-quality music *** this study,the decoding block of the transformer is used to learn the internal information of single-track music,and cross-track transformers are used to learn the information amongst the tracks of different musical instruments.A reward network based on the music theory is proposed,which optimizes the global and local loss objective functions while training and discriminating the network so that the reward network can provide a reliable adjustment method for the generation of the *** method of combining the reward network and cross entropy loss is used to guide the training of the generator and produce high-quality music *** with other multi-track music generation models,the experimental results verify the validity of the model.

关键词： artificial intelligence deep learning multimedia

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EMD-TCN-TimeGAN: A Data Augmentation Model for Enhancing the Accuracy of Agricultural Product Price Prediction

EMD-TCN-TimeGAN: A Data Augmentation Model for Enhancing the...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Wang, Yinbing Wang, Xingfen Li, Libo Beijing Information Science & Technology University School of Computer Beijing China Beijing Information Science & Technology University Institute of Business Intelligence Beijing China Beijing Information Science & Technology University School of Management Science and Engineering Beijing China

ISBN: (纸本)9798350362480

Accurately predicting agricultural product prices is crucial for the stability of the agricultural market. However, due to the collection intervals of agricultural price data, which are typically daily, weekly, or monthly, the data volume is relatively small. This limitation affects the accuracy of deep learning models in price prediction. Data augmentation is an effective method to improve the accuracy of agricultural price predictions. This research proposes a novel data augmentation model, EMD-TCN-TimeGAN. Based on TimeGAN, this model has been significantly improved by replacing the RNN-based components with TCN, which enhances the model's ability to capture long-term dependencies. Additionally, the model incorporates an EMD module to decompose the original price series, thereby better capturing the intrinsic structural information of the time series and further improving the quality of the generated data. Experiments conducted on a collected corn dataset show that adding the augmented data to the training set of the prediction model and retraining it significantly improves the prediction accuracy. The coefficient of determination (R2) increased from 0.928831 to 0.968742, and the mean absolute error (MAE) decreased from 0.026023 to 0.016628. Comparisons with the TimeGAN model using RNN components validate the effectiveness of replacing the components with TCN;comparisons with TCN-TimeGAN validate the effectiveness of the EMD module in further improving prediction performance. The EMD-TCN-TimeGAN proposed in this study generates sequences that better preserve the temporal dynamics of the time series data, maintaining the temporal relationships between the original variables. This improves the accuracy of small-sample agricultural price predictions, which is of significant importance and benefit to agricultural production and related activities. © 2024 IEEE.

关键词： Prediction models

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Air quality and dust level monitoring systems in hospitals using IoT

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Discover Internet of Things 2025年第1期5卷 1-18页

作者： Parkavi, A. Sowmya, B.J. Alex, Sini Anna Supreeth, S. Shruthi, G. Rohith, S. Chatterjee, Sudipta Lingaraj, K. Department of Computer Science and Engineering Ramaiah Institute of Technology Bengaluru560054 India Department of Artificial Intelligence and Data Science Ramaiah Institute of Technology Bengaluru560054 India Ramaiah Institute of Technology Bengaluru560054 India School of Computer Science and Engineering REVA University Bengaluru560064 India Department of Electronics and Communication Engineering Nagarjuna College of Engineering and Technology Bengaluru562164 India Department of Electronics and Communication Engineering Brainware University Barasat West Bengal Kolkata700125 India Department of Computer Science and Engineering Rao Bahadur Y. Mahabaleswarappa Engineering College Bellary583104 India

This system provides a comprehensive overview of hospital environments by tracking air quality, dust, temperature, and humidity simultaneously, offering a more complete picture of indoor conditions than systems that focus on fewer parameters. The use of IoT technology enables real-time monitoring and alerts, allowing hospital staff to respond immediately to any issues. Additionally, predictive analytics anticipate future changes, giving staff time to take preventive measures. The integration with a mobile app and cloud-based data storage ensures easy access to data, convenient monitoring, and the ability to scale the system across multiple hospital facilities, catering specifically to the unique needs of different healthcare environments. © The Author(s) 2025.

关键词： Indoor air pollution

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Modified TRFI Channel Estimation Scheme in OFDM-IM for 802.11p 23

Modified TRFI Channel Estimation Scheme in OFDM-IM for 802.1...

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23rd IEEE International Conference on communication technology, ICCT 2023

作者： Zhang, Si-Yu Dong, Qing-Shang Zheng, Hui Zhang, Yue-Xia Shahrrava, Behnam School of Information and Communication Engineering Beijing Information Science and Technology University Beijing China University of Windsor Department of Electrical and Computer Engineering ON Canada

ISBN: (纸本)9798350325959

IEEE 802.11p is developed to support cooperative intelligent transport systems. In such systems, channel estimation is a challenging problem due to the channel's double dispersive nature. In this paper, a modified time domain reliable test frequency domain interpolation (M-TRFI) scheme for 802.11p orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems is proposed. Unlike OFDM, OFDM-IM can achieve better performance in vehicular communication environments. However, due to the in-active subcarriers, channel estimation for OFDM-IM is more difficult than OFDM. Inspired by the OFDM TRFI and the structure of OFDM-IM, the proposed M-TRFI utilizes preambles and least square (LS) methods to fill in the missing channel information on in-active subcarriers, reducing the serious performance degradation caused by the conventional TRFI used in OFDM-IM. Simulation results show that the proposed M-TRFI achieves a similar estimation performance as that of the OFDM TRFI. Moreover, the proposed M-TRFI significantly outperforms the existing channel estimation performance designed for OFDM-IM systems. © 2023 IEEE.

关键词： IEEE 802.11p standard index modulation (IM) least square (LS) Orthogonal frequency division multiplexing (OFDM) time domain reliable test frequency domain interpolation (TRFI) vehicular channels

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Improved Deep Matrix Factorization for Signal Recovery in Random Frequency Diversity Array Radar 2

Improved Deep Matrix Factorization for Signal Recovery in Ra...

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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Guo, Dayan Lin, Zijian Huang, Tianyao Qi, Yue He, Jie Zhang, Xiao-Ping Wang, Xueqian Li, Gang University of Science and Technology Beijing School of Computer & Communication Engineering Beijing China Tsinghua Shenzhen International Graduate School Institute of Data and Information Shenzhen China Tsinghua University Department of Electronic Engineering Beijing China

ISBN: (纸本)9798331515669

Motivated by the success of recent deep learning researches on radar, we consider a deep learning based matrix factorization method for suppressing the high range-angle side-lobes in random frequency diversity array (FDA) radars. While the existing deep matrix factorization approach is designed for real-valued situations and signals of FDA radars are complex-valued cases, we propose two methods to extend the existing approach into complex-valued framework: 1) adjusting the neural network structures and activation functions for complex-valued operations, and 2) constructing a real-valued representation of the original complex-valued input. Simulation results demonstrate that the proposed methods outperform traditional ones in multi-target scenarios. © 2024 IEEE.

关键词： Matrix factorization

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