检索结果-内蒙古大学图书馆

Effectiveness of a fish scales-derived chitosan coating for corrosion protection of carbon steel

Egyptian Journal of Petroleum 2022年第1期31卷 25-31页

作者： Gapsari, Femiana Hidayatullah, Syarif Hadi Setyarini, Putu Madurani, Kartika A. Hermawan, Hendra Department of Mechanical Engineering Faculty of Engineering Brawijaya University MT Haryono 167 Malang 65145 Indonesia Laboratory of Instrumentation and Analytical Sciences Chemistry Department Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Arief Rahman Hakim Surabaya 60111 Indonesia Department of Mining Metallurgical and Materials Engineering Laval University Quebec City G1V 0A6 Canada

Many naturally-derived organic coating has been proposed for corrosion protection of carbon steel, but its effectiveness is challenged by poor coating adhesion. In this work, chitosan was extracted from Nila tilapia fish scales and coated onto ASTM A36 carbon steel surface by using electrophoretic deposition (EPD) and dip coating (DC) techniques. The work aims at determining the coating technique and process parameters that result in effective corrosion protection of carbon steel in acid solution. The effectiveness of corrosion protection was determined by calculating inhibition efficiency from corrosion parameters obtained by polarization test and electrochemical impedance spectroscopy. Results showed that each coating technique provides different mechanism of corrosion protection. The DC-made coating showed a physisorption mechanism where the steel's corrosion rate increases as the temperature increased. The EPD-coated specimens demonstrated a chemisorption mechanism with its minor change in corrosion rates than those of DC-coated specimens. The DC technique resulted in a higher inhibition (73 %) efficiency and lower corrosion rate than that of EPD (41 %) with some degree of stability over increasing temperature. © 2022 Egyptian Petroleum Research Institute

关键词： Chitosan Corrosion Dip coating Electrophoretic deposition Fish scale Organic coating

来源：评论

学校读者我要写书评

暂无评论

Shadow Vanishing Point Detection Via Combined Human/Shadow Adaptive Modulation

SSRN

引用

SSRN 2023年

作者： Wan, Jin Liu, Zhihao Yin, Hui Wu, Zhenyao Wu, Xinyi Wang, Song Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing100044 China Key Laboratory of Beijing for Railway Engineering Beijing Jiaotong University Beijing100044 China Department of Computer Science and Engineering University of South Carolina ColumbiaSC29201 United States

A set of parallel lines in 3D space intersect at a common vanishing point when projected to a 2D image. Vanishing point detection plays an important role in 3D computer vision and previous works are usually focused on the parallel lines in man-made structures, such as buildings, railways, and lanes. Under sunlight, shadow directions of many instances, especially standing persons, are largely parallel on the ground. The detection of human/shadow vanishing points in 2D images can well complement others for 3D information, especially in scenes that lack man-made structures. However, this is a very challenging problem since human shadows do not present explicit parallel line features along the shadow directions. In this paper, we propose a new ShadowVPNet for shadow vanishing point detection, which consists of a combined human/shadow detector, a feature extractor and a vanishing point classifier. Adaptive modulation modules conditioned on the combined human/shadow priors are incorporated into the feature extractor for modulating the extracted features. We construct a new shadow vanishing point image dataset, as well as all the needed ground-truth annotations, for network training and testing. Experimental results demonstrate the effectiveness of the proposed method on shadow vanishing point detection. © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

USED: Universal Speaker Extraction and Diarization

IEEE Transactions on Audio, Speech and Language Processing

引用

IEEE Transactions on Audio, Speech and Language Processing 2024年 33卷 96-110页

作者： Junyi Ao Mehmet Sinan Yıldırım Ruijie Tao Meng Ge Shuai Wang Yanmin Qian Haizhou Li Shenzhen Research Institute of Big Data School of Data Science The Chinese University of Hong Kong Shenzhen China Department of Electrical and Computer Engineering National University of Singapore Singapore Saw Swee Hock School of Public Health National University of Singapore Singapore Shenzhen Research Institute of Big Data Shenzhen China Auditory Cognition and Computational Acoustics Lab Department of Computer Science and Engineering and the MoE Key Laboratory of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China

Speaker extraction and diarization are two enabling techniques for real-world speech applications. Speaker extraction aims to extract a target speaker's voice from a speech mixture, while speaker diarization demarcates speech segments by speaker, annotating ‘who spoke when’. Previous studies have typically treated the two tasks independently. In practical applications, it is more meaningful to have knowledge about ‘who spoke what and when’, which is captured by the two tasks. The two tasks share a similar objective of disentangling speakers. Speaker extraction operates in the frequency domain, whereas diarization is in the temporal domain. It is logical to believe that speaker activities obtained from speaker diarization can benefit speaker extraction, while the extracted speech offers more accurate speaker activity detection than the speech mixture. In this paper, we propose a unified model called Universal Speaker Extraction and Diarization (USED) to address output inconsistency and scenario mismatch issues. It is designed to manage speech mixtures with varying overlap ratios and variable number of speakers. We show that the USED model significantly outperforms the competitive baselines for speaker extraction and diarization tasks on LibriMix and SparseLibriMix datasets. We further validate the diarization performance on CALLHOME, a dataset based on real recordings, and experimental results indicate that our model surpasses recently proposed approaches.

关键词： Speech recognition data mining Training Multitasking Speech enhancement Time-domain analysis Recording Predictive models Particle separators Oral communication

来源：评论

学校读者我要写书评

暂无评论

ZuantuSet: A Collection of Historical Chinese Visualizations and Illustrations 25

ZuantuSet: A Collection of Historical Chinese Visualizations...

引用

2025 CHI Conference on Human Factors in Computing Systems, CHI 2025

作者： Mei, Xiyao Zhang, Yu Yang, Chaofan Shi, Rui Yuan, Xiaoru Peking University Beijing China University of Oxford Oxford United Kingdom National Key Laboratory of General Artificial Intelligence School of Intelligence Science and Technology Peking University China Department of Computer Science University of Oxford United Kingdom Center for Research on Ancient Chinese History Peking University China National Engineering Laboratory for Big Data Analysis and Application Peking University China PKU-WUHAN Institute for Artificial Intelligence China

ISBN: (纸本)9798400713941

Historical visualizations are a valuable resource for studying the history of visualization and inspecting the cultural context where they were created. When investigating historical visualizations, it is essential to consider contributions from different cultural frameworks to gain a comprehensive understanding. While there is extensive research on historical visualizations within the European cultural framework, this work shifts the focus to ancient China, a cultural context that remains underexplored by visualization researchers. To this aim, we propose a semi-automatic pipeline to collect, extract, and label historical Chinese visualizations. Through the pipeline, we curate ZuantuSet, a dataset with over 71K visualizations and 108K illustrations. We analyze distinctive design patterns of historical Chinese visualizations and their potential causes within the context of Chinese history and culture. We illustrate potential usage scenarios for this dataset, summarize the unique challenges and solutions associated with collecting historical Chinese visualizations, and outline future research directions. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Flow visualization

来源：评论

学校读者我要写书评

暂无评论

Towards Intelligent Transportation with Pedestrians and Vehicles In-the-Loop: A Surveillance Video-Assisted Federated Digital Twin Framework

引用

IEEE Network 2025年

作者： Li, Xiaolong Wei, Jianhao Wang, Haidong Dong, Li Chen, Ruoyang Yi, Changyan Cai, Jun Niyato, Dusit Shen, Xuemin Hunan Provincial General University Key Laboratory of IoT Intelligent Sensing and Distributed Collaborative Optimization Hunan University of Technology and Business Xiangjiang Laboratory Changsha410205 China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology China University of Concordia Department of Electrical and Computer Engineering Montreal Canada Nanyang Technological University College of Computing and Data Science Singapore Singapore University of Waterloo Department of Electrical and Computer Engineering Canada

In intelligent transportation systems (ITSs), integrating pedestrians and vehicles into traffic management models is essential for developing realistic and safe solutions. However, current systems often fail to simulate complex, real-world scenarios due to the absence of a comprehensive digital twin framework across diverse traffic environments and effective modeling of pedestrian-vehicle interactions. In this article, we propose a surveillance video-assisted federated digital twin (SV-FDT) framework to enhance ITSs by incorporating pedestrians and vehicles into the control loop. SV-FDT improves computational efficiency and communication performance by transmitting only semantic data and agent parameters, rather than raw video streams. The proposed framework adopts three-layer architecture and constructs detailed pedestrian-vehicle interaction models using multi-source traffic surveillance videos. The three-layer architecture includes: (i) an end layer that collects surveillance videos from multiple sources;(ii) an edge layer that performs self-supervised semantic segmentation to extract interactions, converts them into executable traffic codes, and generates local digital twin systems (LDTSs) for regional traffic modeling;and (iii) a cloud layer that integrates LDTSs into a real-time global digital twin model. Key design considerations, challenges, and practical implementation guidelines are discussed for SV-FDT, and a testbed evaluation is used to show that SV-FDT improves traffic flow, reduces mirroring delay, and enhances recognition accuracy and system efficiency compared to traditional terminal-server frameworks. Finally, we outline open challenges and potential directions for future research in digital twin-enabled ITS. © 1986-2012 IEEE.

关键词： Air traffic control

来源：评论

学校读者我要写书评

暂无评论

CTourLLM: enhancing LLMs with Chinese tourism knowledge

引用

Cluster Computing 2025年第6期28卷 1-13页

作者： Wei, Qikai Yang, Mingzhi Wang, Jinqiang Mao, Wenwei Xu, Jiabo Ning, Huansheng School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Key Laboratory of Xinjiang Coal Resources Green Mining Ministry of Education Xinjiang Institute of Engineering Urumqi China Guangxi Tourism Development One-Click Tour Digital Cultural Tourism Industry Co. Ltd Guangxi China Beijing Engineering Research Center for Cyberspace Data Analysis and Applications Beijing China

Recently, large language models (LLMs) have demonstrated their effectiveness in various natural language processing (NLP) tasks. However, the lack of tourism knowledge limits the performance of LLMs in tourist attraction presentations and travel planning. To address this challenge, we constructed a supervised fine-tuning dataset for the Chinese culture and tourism domain, named Cultour. This dataset consists of three parts: tourism knowledge base data, travelogues data, and tourism QA data. Additionally, we propose CTourLLM, a Qwen-based model supervised fine-tuned with Cultour, to improve the quality of information about attractions and travel planning. To evaluate the performance of CTourLLM, we proposed a human evaluation criterion named RRA (Relevance, Readability, Availability), and employed both automatic and human evaluation. The experimental results demonstrate that CTourLLM outperforms ChatGPT, achieving an improvement of 1.21 in BLEU-1 and 1.54 in Rouge-L, thereby validating the effectiveness of the response outcomes. Our proposed Cultour is accessible at https://***/mrweiqk/Cultour .

关键词： Tourism

来源：评论

学校读者我要写书评

暂无评论

Numerical Analysis of Bi-fluid PV/T Hybrid Collector Using the Finite Difference Method 6th

Numerical Analysis of Bi-fluid PV/T Hybrid Collector Using t...

引用

6th International Conference on Wireless Technologies, Embedded and Intelligent Systems, WITS 2020

作者： El Manssouri, Oussama Hajji, Bekkay Gagliano, Antonio Tina, Giuseppe Marco Renewable Energy Embedded System and Data Processing Laboratory National School of Applied Sciences Mohamed First University Oujda Morocco DIEEI: Department of Electric Electronic and Computer Engineering University of Catania Catania Italy

ISBN: (纸本)9789813368927

The PV/T is called as a hybrid bi-fluid type solar collector when both fluids (water and air) are used as working fluids. This type of collector provide a wide range of thermal applications and several modes can be executed depending on energy needs and applications: air mode, water mode and simultaneous mode (air and water). This paper presents a numerical analysis of PV/T bi-fluid collector using the finite difference method. Energy balance equations were established for each layer and solved using the Gauss–Seidel iteration method. The performance of the PV/T hybrid is evaluated according to the operating mode of the fluid (independently and simultaneously). The simulation results are compared with literature (Modeling and performances assessments of PV/T bifluid hybrid collector: Three cooling modes operation case. https://***/10.1109/iceit48248.2020.9113233, [10]), and indicate that when both fluids are used simultaneously, the overall electrical and thermal performance of the hybrid collector is considered satisfactory compared to the situation where two fluids operate independently. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Finite difference method

来源：评论

学校读者我要写书评

暂无评论

D4M: dataset Distillation via Disentangled Diffusion Model

D4M: Dataset Distillation via Disentangled Diffusion Model

引用

Conference on computer Vision and Pattern Recognition (CVPR)

作者： Duo Su Junjie Hou Weizhi Gao Yingjie Tian Bowen Tang UCAS School of Computer Science and Technology Research Center on Fictitious Economy and Data Science CAS Key Laboratory of Big Data Mining and Knowledge Management CAS UCAS Sino-Danish College Department of Computer Science NCSU UCAS School of Economics and Management UCAS MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation CAS Institute of Computing Technology

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

dataset distillation offers a lightweight synthetic dataset for fast network training with promising test accuracy. To imitate the performance of the original dataset, most approaches employ bi-level optimization and the distillation space relies on the matching architecture. Nevertheless, these approaches either suffer significant computational costs on large-scale datasets or experience performance decline on cross-architectures. We advocate for designing an economical dataset distillation framework that is independent of the matching architectures. With empirical observations, we argue that constraining the consistency of the real and synthetic image spaces will enhance the cross-architecture generalization. Motivated by this, we introduce dataset Distillation via Disentangled Diffusion Model (D 4 M), an efficient framework for dataset distillation. Compared to architecture-dependent methods, D 4 M employs latent diffusion model to guarantee consistency and incorporates label information into category prototypes. The distilled datasets are versatile, eliminating the need for repeated generation of distinct datasets for various architectures. Through comprehensive experiments, D4M demonstrates superior performance and robust generalization, surpassing the SOTA methods across most aspects.

关键词： Training computer vision Computational modeling Prototypes computer architecture Diffusion models Pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Achieving Enhanced Bi-Linear Attention Network for Teaching Manner Analysis over Edge Cloud-assisted AIoT: Voice-Body Coordination Perspective

引用

IEEE Transactions on Cloud Computing 2025年

作者： Zhou, Yu Zou, Sai Wu, Bochun Ni, Wei Du, Xiaojiang Guizhou University Micro-nano and Intelligent Manufacturing Engineering Research Centre of Ministry of Education College of Big Data and Information Engineering China Fudan University State Key Laboratory of Integrated Chips and Systems Shanghai200433 China Data61 CSIRO Australia Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States

Edge computing, an advanced extension of cloud computing, provides superior computational capabilities and lowlatency processing at the network edge, facilitating its availability for real-time data analysis in resource-limited settings. When applied to the analysis of teaching methodologies, edge computing enables the seamless integration of vocal and physical cues, facilitating collaborative, dynamic, and real-time evaluations of teaching quality. However, the inherent complexity of human perception and multimodal interactions impose great challenges to the analysis of these aspects in Artificial Intelligence of Things (AIoT). This paper introduces an innovative mathematical model and a measurement index specifically designed to assess changes in voice-body coordination over time. To achieve this, we propose a cloud-enabled enhanced Bi-Linear Attention Network incorporating entropy and Fourier transforms (BAN-E-FT), which leverages both temporal and frequencydomain features. Specifically, by harnessing the computational and storage capabilities of edge computing, BAN-E-FT facilitates distributed training, expedites large-scale data processing, and enhances model scalability, where entropy measures and Fourier transforms capture modality dynamics, enhancing BAN's fusion capabilities. Moreover, a conditional domain adversarial network is embedded to address regional teaching variations, improving model generalizability. We also verify the robustness of BAN-EFT with accuracy and convergence through convex optimization analysis. Experiments on the eNTERFACE'05 dataset demonstrate 81% accuracy in assessing teaching adaptability, while real-world test at Guizhou University confirms 78% accuracy when using BAN-E-FT, matching human expert assessments. © 2013 IEEE.

关键词： data integration

来源：评论

学校读者我要写书评

暂无评论

Safe and Reliable Training of Learning-Based Aerospace Controllers 43

Safe and Reliable Training of Learning-Based Aerospace Contr...

引用

43rd AIAA DATC/IEEE Digital Avionics Systems Conference, DASC 2024

作者： Mandal, Udayan Amir, Guy Wu, Haoze Daukantas, Ieva Newell, Fletcher Lee Ravaioli, Umberto Meng, Baoluo Durling, Michael Hobbs, Kerianne Ganai, Milan Shim, Tobey Katz, Guy Barrett, Clark Stanford University Center for Ai Safety Stanford United States School of Cs & Engineering The Hebrew University of Jerusalem Jerusalem Israel It University of Copenhagen Department of Computer Science Copenhagen Denmark Google Mountain View United States Ge Aerospace Research Niskayuna United States Us Air Force Air Force Research Laboratory Dayton United States Stanford University Department of Computer Science Stanford United States Stanford University Department of Data Science Stanford United States

ISBN: (纸本)9798350349610

In recent years, deep reinforcement learning (DRL) approaches have generated highly successful controllers for a myriad of complex domains. However, the opaque nature of these models limits their applicability in aerospace systems and sasfety-critical domains, in which a single mistake can have dire consequences. In this paper, we present novel advancements in both the training and verification of DRL controllers, which can help ensure their safe behavior. We showcase a design-for-verification approach utilizing k-induction and demonstrate its use in verifying liveness properties. In addition, we also give a brief overview of neural Lyapunov Barrier certificates and summarize their capabilities on a case study. Finally, we describe several other novel reachability-based approaches which, despite failing to provide guarantees of interest, could be effective for verification of other DRL systems, and could be of further interest to the community. © 2024 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：