检索结果-内蒙古大学图书馆

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Jian, Zhongquan Wang, Yancheng Wu, Weichao Yao, Junfeng Wang, Meihong Wu, Qingqiang School of Informatics Xiamen University Xiamen China School of Film Xiamen University Xiamen China School of Computing and Data Science Xiamen University Malaysia Selangor Malaysia School of Mechanics and Civil Engineering China University of Mining & Technology Beijing China Xiamen Key Laboratory of Intelligent Storage and Computing School of Informatics Xiamen University Xiamen China Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism Xiamen China

ISBN: (纸本)9798350368741

Recognizing emotions in dialogues is vital for effective human-computer interaction, yet remains a challenging task in Natural Language Processing (NLP). Previous studies in Emotion Recognition in Conversation (ERC) have primarily focused on contextual features, while overlooking the importance of emotional features in emotion recognition. To address this gap, we focus on the role of emotional features in ERC and propose a novel method, Emotional Knowledge Self-Distillation (EmoKSD1), to enhance the model's emotional sensitivity. In EmoKSD, utterances are enriched with implicit 〈mask〉 tokens to represent conveyed emotions, allowing the distillation of emotional knowledge from explicit emotional tokens to implicit 〈mask〉 tokens, thereby enhancing the model's ability to perceive subtle emotions within the dialogue. Through thorough evaluations on two public ERC datasets (i.e., IEMOCAP and MELD) using proposed coarse-grained utterance distillation and fine-grained token distillation techniques, EmoKSD demonstrates superior performance compared to existing methods, highlighting the significance of emotional features in ERC. © 2025 IEEE.

关键词： Dialogue System Emotion Recognition in Conversation Knowledge Distillation Natural Language Processing

来源：评论

学校读者我要写书评

暂无评论

Roll for Robot: A Tabletop Role-Playing Game for Designing Socially Assistive Robots for Depression Management 16th

Roll for Robot: A Tabletop Role-Playing Game for Designing ...

引用

16th International Conference on Social Robotics, ICSR + AI 2024

作者： Collins, Sawyer Henkel, Kenna Baugus Henkel, Zachary Śabanović, Selma Luddy School of Informatics Computing and Engineering Indiana University Bloomington BloomingtonIN United States College of Computer Science and Engineering Mississippi State University Mississippi State StarkvilleMS United States

ISBN: (纸本)9789819635214

Imagining and creating a future with a robot tailored to an individual’s needs and wants provides a unique challenge to both designers and perspective users. Using both an existing base zoomorphic robot, TherabotTM in a specially designed tabletop role-playing game, we have explored what it would look like for someone living with depression to go through a "day in the life" with their newly designed robot companion. Inspired by this collaborative co-design technique, eight participants explained their own relationship with depression, identified a character that they connected with, and chose the physical form, sensors, and abilities for a socially assistive robot. Using this character and robot, participants described how they might overcome depression symptoms and identified uses when managing depression symptoms for the robot. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Machine design

来源：评论

学校读者我要写书评

暂无评论

Holistic Cyber Threat Modeling for Machine Learning-Based Systems: A Case Study in Healthcare

Holistic Cyber Threat Modeling for Machine Learning-Based Sy...

引用

18th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2025

作者： Jaal, Janno Bahsi, Hayretdin Department of Software Science Tallinn University of Technology Tallinn Estonia Cybernetica AS Tallinn Estonia School of Informatics Computing and Cyber Systems Northern Arizona University United States

Considering the immense pace in machine learning (ML) technology and related products, it may be difficult to imagine a software system, including healthcare systems, without any subsystem containing an ML model in the near future. However, ensuring the resiliency of these ML-based systems against cyber attacks is vital for more seamless and widespread technology usage. The secure-by-design principle, considering security from the early stages of development, is a cornerstone to achieving sufficient security at a reasonable cost. The realization of this principle starts with conducting threat modeling to understand the relevant security posture and identify cyber security requirements before system design. Although threat modeling of software systems is widely known, it is unclear how to apply it to software systems with machine learning models. Although adversarial machine learning is a widely studied research topic, it has yet to be thoroughly researched how adversarial and conventional cybersecurity attacks can be holistically considered to identify applicable cyber threats at the early stage of a software development life cycle. This paper adapts STRIDE, a widely-known threat modeling method, for the holistic cyber threat analysis of an ML-based healthcare system. © 2025 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Models for Network Traffic Behavioral Analysis in IoT Systems

Models for Network Traffic Behavioral Analysis in IoT System...

引用

23rd International Conference on informatics in Economy, IE 2024

作者： Zamfiroiu, Alin Floroiu, Iustin Savu, Daniel Bătăgan, Lorena Ghai, Anupriya Sharma National Institute for Research & Development in Informatics Bucharest Romania Bucharest University of Economic Studies Bucharest Romania School of Computing Graphic Era Hill University Dehradun India

ISBN: (纸本)9789819601608

In today's interconnected world, the proliferation of Internet of Things (IoT) devices has revolutionized the way we interact with technology. From smart homes and wearable devices to industrial sensors and autonomous vehicles, IoT systems have permeated nearly every aspect of our daily lives. However, with this exponential growth in IoT adoption comes a host of challenges, particularly concerning the security and performance of these interconnected networks. One of the key methodologies employed to address these challenges is network traffic behavioral analysis. Moreover, network traffic behavioral analysis plays a crucial role in threat intelligence and incident response. By aggregating and analyzing network data over time, organizations can identify recurring attack patterns and indicators of compromise. This rich contextual information enhances their ability to anticipate and preempt future cyber threats. Additionally, in the event of a security incident, network traffic analysis provides invaluable forensic evidence, allowing investigators to reconstruct the sequence of events, attribute responsibility, and mitigate the impact of the breach. In this paper, we propose some models for the network traffic generated by sensors and actuators in IoT systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Computer forensics

来源：评论

学校读者我要写书评

暂无评论

Enhancing Classification Algorithm Recommendation in Automated Machine Learning: A Meta-Learning Approach Using Multivariate Sparse Group Lasso

引用

Computer Modeling in Engineering & Sciences 2025年第2期142卷 1611-1636页

作者： Irfan Khan Xianchao Zhang Ramesh Kumar Ayyasamy Saadat M.Alhashmi Azizur Rahim School of Software Dalian University of TechnologyDalian116620China Faculty of Information and Communication Technology Universiti Tunku Abdul RahmanKampar31900Malaysia College of Computing and Informatics University of SharjahSharjah27272United Arab Emirates Department of Computer Systems Engineering University of Engineering and Applied SciencesSwat19200Pakistan

The rapid growth of machine learning(ML)across fields has intensified the challenge of selecting the right algorithm for specific tasks,known as the Algorithm Selection Problem(ASP).Traditional trial-and-error methods have become impractical due to their resource *** Machine Learning(AutoML)systems automate this process,but often neglect the group structures and sparsity in meta-features,leading to inefficiencies in algorithm recommendations for classification *** paper proposes a meta-learning approach using Multivariate Sparse Group Lasso(MSGL)to address these *** method models both within-group and across-group sparsity among meta-features to manage high-dimensional data and reduce multicollinearity across eight meta-feature *** Fast Iterative Shrinkage-Thresholding Algorithm(FISTA)with adaptive restart efficiently solves the non-smooth optimization *** validation on 145 classification datasets with 17 classification algorithms shows that our meta-learning method outperforms four state-of-the-art approaches,achieving 77.18%classification accuracy,86.07%recommendation accuracy and 88.83%normalized discounted cumulative gain.

关键词： Meta-learning machine learning automated machine learning classification meta-features

来源：评论

学校读者我要写书评

暂无评论

Understanding the Student Experience Better: Analyzing Remote Learning Tools Through Engagement, Participation, and Liveness Concepts

Understanding the Student Experience Better: Analyzing Remot...

引用

17th International Conference on Computer Supported Education, CSEDU 2025

作者： Gomes, Genildo Silva, Paulo Magalhães, Sâmila Galvão, Leandro Lauschner, Tanara Steinmacher, Igor Conte, Tayana Gadelha, Bruno Institute of Computing Federal University of Amazonas AM Manaus Brazil Department of Design and Graphic Expression Federal University of Amazonas AM Manaus Brazil School of Informatics Computing and Cyber Systems Nothern Arizona University FlagstaffAZ United States

ISBN: (纸本)9789897587467

Technologies have changed how students engage and participate during remote classes, whether by encouraging interaction via chat on platforms such as Google Meet or by using voting features such as Poll. Our research aims to better understand the role of these tools in the educational context and how their interactive features influence student experience through the lens of engagement, participation, and liveness. In this sense, we address the following question: How can educational technologies be classified by the Engagement, Participation, and Liveness lens? To explore the relationship between the lens and the interactive features of Mentimeter, Google Meet, and Google Presentations, we conducted a study with three independent evaluations, measuring agreement using Cohen's Kappa coefficient. Our results suggest that these interactive features can be used as a lens to understand different types of experiences and how they can be applied to promote various dynamics, such as competitive and collaborative activities. Our results expand the professor's perspective on the student experience, providing ways for professors to understand the emotional and student behavioral reactions from using interactive tools in remote learning environments. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Latency Insensitivity Testing for Dataflow HLS Designs 25

Latency Insensitivity Testing for Dataflow HLS Designs

引用

33rd ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, FPGA 2025

作者： Cheng, Jianyi Wang, Lianghui Jiang, Zijian Bao, Yungang Shi, Kan School of Informatics The University of Edinburgh Edinburgh United Kingdom Institute of Computing Technology Chinese Academy of Sciences University of Science and Technology of China Beijing China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798400713965

Dataflow high-level synthesis (HLS) tools automatically map a high-level software program to a dataflow hardware design. When testing the design, the HLS tool takes a testing function written in the same software language and translates it into the corresponding hardware testbench for cycle-accurate simulation. However, the generated testbench only follows a fixed schedule to feed inputs and collect outputs, without considering external dynamic behaviors of the test data (also known as latency insensitivity testing). Overlooking these test cases could miss bugs introduced by the designer that occur in certain events, such as late input arrival and output backpressure, leading to higher debugging costs. In this paper, we present an HLS testing toolflow named PEDIA that automatically generates testbenches to detect latency insensitivity bugs. We expand the test space from varying input values to varying input delays. PEDIA automatically determines an efficient test space of input delays based on the HLS schedule for better scalability;and tests the HLS design on a parallel hardware testing platform for high performance. Over two representative sets of existing benchmarks, we show that PEDIA can help identify potential bugs missed by existing approaches and achieves an average speedup of 4.53× on running 1500 test cases. © 2025 Copyright held by the owner/author(s).

关键词： Software testing

来源：评论

学校读者我要写书评

暂无评论

PaintingScapeVR: Exploring Gamified Interaction in Virtual Galleries 1st

PaintingScapeVR: Exploring Gamified Interaction in Virtual ...

引用

1st International Conference on Extended Reality, ICXR 2024

作者： Cai, Dongning Ren, Le Chang, Yaqi Li, Xiaodan Lin, Yuxin Yao, Junfeng Center for Digital Media Computing School of Film School of Informatics Xiamen University Xiamen361005 China Institute of Artificial Intelligence Xiamen University Xiamen361005 China Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism New Taipei City Taiwan School of Informatics Xiamen University Xiamen361005 China

ISBN: (纸本)9789819636785

In reality, galleries usually display paintings in a protective manner, partly to delay the damage to the original artwork and ensure the long-term preservation of the artwork. On the other hand, it also hinders visitors’ deep appreciation and learning of the artwork. In the face of this challenge, our research aims to provide users with immersive viewing and entertainment, as well as interactive gaming experiences with artwork, through the use of virtual reality technology. So the paper proposes PaintingScapeVR, which is based on a virtual gallery and reproduces the three-dimensional scenes corresponding to different paintings. Visitors can freely explore in this virtual environment and gain a deeper understanding of the meaning and artistic value of artworks through interaction with them. Our results indicate that the reproduction of 3D scenes and gamified interactive design can not only significantly enhance visitors’ appreciation of painting art, but also leave a deeper learning impression. This immersive experience stimulates visitors’ desire to appreciate and explore, prompting them to actively delve into the background and techniques of art works, thereby enhancing their artistic appreciation abilities. At the same time, this work also demonstrates its potential in enhancing visitors’ understanding of painting works, allowing more people to explore the joy of painting and art. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Interactive gamification Three-dimensional displays Virtual reality

来源：评论

学校读者我要写书评

暂无评论

Identity-Based Signature from Lattices Without Trapdoors 26th

Identity-Based Signature from Lattices Without Trapdoors

引用

26th International Conference on Information and Communications Security, ICICS 2024

作者： Luo, Pingbin Chen, Xinjian Susilo, Willy Huang, Qiong College of Mathematics and Informatics South China Agricultural University Guangzhou China Guangzhou Key Laboratory of Intelligent Agriculture Guangzhou510642 China School of Computing and Information Technology University of Wollongong Wollongong Australia

ISBN: (纸本)9789819788002

Currently, the majority of lattice-base identity-based signature (LB-IBS) schemes rely on lattice trapdoor technique introduced by Gentry, Peikert, and Vaikuntanathan. However, this approach significantly impacts computational efficiency. In light of this, we present an alternative method for constructing LB-IBS that does not rely on lattice trapdoors and preimage sampling function. We construct an IBS scheme by employing Lyubashevsky’s signature twice, which is essentially a public key delegation from concatenated Schnorr signatures. In order to optimize the signature size, we describe an adaptation of our scheme in module lattices setting and compression technique. Moreover, our new LB-IBS can combine with Dilithium naturally so that it could carry the advantages of the latter such as side-channel attacks protection. We demonstrate that our construction is provably secure against existential forgery on adaptively chosen message and identity attacks in random oracle model. In comparison with the most efficient LB-IBS scheme (to the best of our knowledge), the signature size of our scheme is 52% smaller and runtime of our scheme is up to 32% faster. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Quantum cryptography

来源：评论

学校读者我要写书评

暂无评论

Chance-Constrained Sampling-Based MPC for Collision Avoidance in Uncertain Dynamic Environments

arXiv

引用

arXiv 2025年

作者： Mohamed, Ihab S. Ali, Mahmoud Liu, Lantao The Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States

Navigating safely in dynamic and uncertain environments is challenging due to uncertainties in perception and motion. This letter presents C2U-MPPI, a robust sampling-based Model Predictive Control (MPC) framework that addresses these challenges by leveraging the Unscented Model Predictive Path Integral (U-MPPI) control strategy with integrated probabilistic chance constraints, ensuring more reliable and efficient navigation under uncertainty. Unlike gradient-based MPC methods, our approach (i) avoids linearization of system dynamics and directly applies non-convex and nonlinear chance constraints, enabling more accurate and flexible optimization, and (ii) enhances computational efficiency by reformulating probabilistic constraints into a deterministic form and employing a layered dynamic obstacle representation, enabling real-time handling of multiple obstacles. Extensive experiments in simulated and real-world human-shared environments validate the effectiveness of our algorithm against baseline methods, showcasing its capability to generate feasible trajectories and control inputs that adhere to system dynamics and constraints in dynamic settings, enabled by unscented-based sampling strategy and risk-sensitive trajectory evaluation. A supplementary video is available at: https://***/FptAhvJlQm8. © 2025, CC BY.

关键词： Predictive control systems

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：