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Pacific (formerly Asia-Pacific APVIS) visualization Symposium

作者： Leni Yang Aoyu Wu Wai Tong Xian Xu Zheng Wei Huamin Qu Hong Kong University of Science and Technology Hong Kong University of Science and Technology Guangzhou

data storytelling explores how to communicate data insights to the general public engagingly and effectively. It combines the power of data visualizations and storytelling techniques and is popular in various media such as newspapers, interactive websites, and videos. Recently, virtual reality has brought new opportunities to enhance data storytelling with an incomparable sense of immersion. However, there exists a limited understanding of data stories in virtual reality (VR) as they are still in the early stage. In this paper, we investigated the idea of VR data videos by drawing inspiration from popular 3D data videos and studying how to transfer them from screens to VR. We systematically analyzed 100 highly-watched 3D data videos from Youtube and Tiktok channels to derive their design space. We then conducted a user study with 12 participants to explore the effects of four design factors on user experience, including varying camera angles, showing chart overview, animation, and using anchors. Specifically, participants watched 3D data videos in desktop and VR environments. We collected and analyzed their quantitative and qualitative feedback regarding the story’s understandability, memorability, engagement, and emotional effects. Results suggested that data videos in VR were significantly more appreciated than on desktops. We concluded with design implications for future applications and research on VR data videos.

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Assessing Protected Areas for Migratory Birds in Uruguay Using Correlation Analysis

Assessing Protected Areas for Migratory Birds in Uruguay Usi...

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ieee URUCON

作者： Agustina Ramirez Lucía de León Juan Sebastian Blandon Nelcy N. Atehortua-Sanchez Artificial Intelligence Applications Group - ARIA Agro-Environmental Engineering Instituto Tecnológico Regional Centro Sur - IAGRO ITR CS Universidad Tecnológica de Uruguay - UTEC Durazno Uruguay

ISBN: (数字)9798350355383

ISBN: (纸本)9798350355390

Analyzing the distribution and richness of migratory birds is essential to understanding the adverse effects of climate change scenarios. Species monitoring data can quantify those effects. Citizen science platforms such as eBird provide valuable information for species management and preservation. This study evaluated protected areas recognized by the National System of Protected Areas between 2014 and 2023, using Pearson’s correlation coefficient to identify changes in the distribution of migratory birds. The results identified Laguna de Rocha as a site of high migratory avian biodiversity through the developed data analysis and visualization methodology. In addition, significant fluctuations appeared over the years, underlining the importance of strengthening Citizen science initiatives. This work will contribute to designing conservation strategies, capturing habitat changes and seasonal variations, and promoting tourism.

关键词： Protected areas Correlation coefficient Correlation Fluctuations Habitats data visualization Birds Environmental management Monitoring Meteorology

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Knowledge Graph Based Augmented Reality Work Instruction for Wire Harness Final Assembly on Formboard

Knowledge Graph Based Augmented Reality Work Instruction for...

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ieee International Conference on Automation science and Engineering (CASE)

作者： Junfeng Wang Ting Shi Maoding Liu Ke Jiang Department of Industrial and Manufacturing System Engineering Huazhong University of Science and Technology Wuhan Hubei China Beijing Institute of Mechanical Equipment Beijing China

The final assembly of wire harness on formboard is an important phase for harness development of modern mechatronic products. Process visualization based on augmented reality (AR) can superimposes the information in front of the workers' view to facilitate their work. An framework for wire harness final assembly (WHFA) based on AR visualization is proposed in this paper. The assembly process information and its visualization format are studied in this paper for wire harness final assembly. A unified description of assembly process is presented based on knowledge graph method, which provides a formal framework for consistent modeling of the wire harness data for information integration. In order to assistant the wire harness assembly tasks, different visual assets are design to deliver the required assembly information. The visual assets can help the workers to localize the object/position, understand the operating procedure and display the important digital number. A XML file which are generated from the knowledge graph is used to describe the wire harness assembly step and the corresponding AR visualization format for shop floor work instruction on formboard. An experimental AR based wire harness final assembly instruction system is developed. Examples are given to show the augmented assembly information instruction of a wire harness final assembly on formboard by using a common monitor display at a fixed workstation with a static overhead camera.

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T-FinKB: A Platform of Temporal Financial Knowledge Base Construction 39

T-FinKB: A Platform of Temporal Financial Knowledge Base Con...

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39th ieee International Conference on data Engineering, ICDE 2023

作者： Zhu, Xinyi Wang, Liping Xin, Hao Wang, Xiaohan Jia, Zhifeng Wang, Jiyao Ma, Chunming Zengt, Yuxiang Guangzhou China The Hong Kong University of Science and Technology Hong Kong The Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9798350322279

In recent years, domain-specific knowledge bases (KBs) have attracted more attention in academics and industry because of their expertise and in-depth representation in a specific domain. However, when constructing a domain-specific KB, one needs to address not only the challenges in constructing a general KB, but also the difficulties raised by the nature of domain-specific raw data. Considering the usability of financial Knowledge Bases (KBs) in many downstream applications, such as financial risk analysis and fraud detection, we aim to build a Temporal Financial KB. However, the complex, time-varying financial knowledge and the volatile financial market evolution make construction quite challenging. Thus, we propose a Platform for Temporal Financial KB Construction, T-FinKB Platform 1. This platform consists of three fundamental modules, i.e., evolved knowledge extraction module, temporal record linkage and conflicts resolution module, and dynamic knowledge update module designed for financial knowledge. Generated temporal financial KBs (T-FinKBs) from T-FinKB Platform can be updated automatically. T-FinKB has been successfully applied to a downstream application, stock trend prediction with backtesting evaluation. In addition, T-FinKB Platform provides several APIs for visualization, queries and analytics. © 2023 ieee.

关键词： Risk assessment

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HoneyTrack: An improved honeypot

HoneyTrack: An improved honeypot

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ieee Students' Conference on Electrical, Electronics and Computer science (SCEECS)

作者： Atharva Auti Shrawani Pagar Vivek Mishra Jay Makwana Shwetambari Borade Department of Cybersecurity Shah And Anchor Kutchhi Engineering College Mumbai India

With the tremendous growth of cyber-attacks, the loss of private or sensitive data has risen to a peak. Honeypots are one of the most concerned topics in the field of cyber security currently. HoneyTrack is a honeypot that uses various technologies like Docker, Shell Scripts, Python, Elastic Search, Kibana, and Filebeats which protect an organization's database as well it backtracks the hacker when it intrudes the target network. Information about the attacker will be gathered by the bot in the honeypot which will help us reach the roots of the attacker. The target networks could be varied and cause a lot of damage when sensitive data will be lost/stolen. However, this honeypot is like a traditional honeypot but quite updated with new-generation technology and their needs related to cyber-security.

关键词： Computer hacking data visualization Passwords Planning Servers Ransomware Security

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Vision Transformer (ViT)-based Applications in Image Classification

Vision Transformer (ViT)-based Applications in Image Classif...

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ieee International Conference on Big data Security on Cloud (BigdataSecurity), High Performance and Smart Computing (HPSC) and Intelligent data and Security (IDS)

作者： Yingzi Huo Kai Jin Jiahong Cai Huixuan Xiong Jiacheng Pang School of Computer Science and Engineering Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology Xiangtan China the College of Computer Science and Electronics Engineering Hunan University Changsha China

In recent years, the ViT model has been widely used in the field of computer vision, especially for image classification tasks. This paper summarizes the application of ViT in image classification tasks, first introduces the image classification imple- mentation process and the basic architecture of the ViT model, then analyzes and summarizes the image classification methods, including traditional image classification methods, CNN-based image classification methods, and ViT-based image classification methods, and provides a comparative analysis of CNN and ViT. Subsequently, this paper outlines the application prospects of ViT in image classification and its future development and also outlines some shortcomings of ViT and its solutions.

关键词： Representation learning Analytical models visualization Computational modeling Transformers Reservoirs data models

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NetViz: A Tool for Netlist Security visualization

NetViz: A Tool for Netlist Security Visualization

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ieee International Symposium on Quality Electronic Design

作者： James Geist Travis Meade Shaojie Zhang Yier Jin Department of Computer Science University of Central Florida Department of Electrical and Computer Engineering University of Florida

Algorithmic analysis of gate level netlists has become an important technique in hardware security. Algorithms can help detect malicious hardware injected into a design, or lock a design against reverse engineering or malicious modification. Many analysis tools have come from the research and commercial communities; however, it is currently the job of the analyst to make these tools work together and interpret the results. Typically tools are text-based, and require error-prone editing of input files in different formats. The analyst must interpret textual results, and sometimes transform them into other formats for use in third party visualization tools. These tasks are repetitive overhead that take time and effort that could better be spent on investigating the netlist. In this paper we introduce NetViz, a visual hardware security environment. NetViz is a meta-tool which combines other analysis tools, automates the task of transferring data between them, and helps with interpretation of results by providing graphical representations of the data.

关键词： visualization Reverse engineering data visualization Transforms Logic gates Task analysis

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Proposal of a Support System for visualization of Acquired Skills Using iCD in Project-Based Learning for Software Development and How to Acquire its data

Proposal of a Support System for Visualization of Acquired S...

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Conference on Software Engineering Education & Training (CSEE&T)

作者： Hane Kondo Hiroaki Hashiura Atsuo Hazeyama Graduate School of Education Tokyo Gakugei University Tokyo Japan Faculty of Advanced Engineering Nippon Institute of Technology Saitama Japan Dept. Information Science Tokyo Gakugei University Tokyo Japan

There have been many practices using software development as a subject for Project-Based Learning (PBL). While PBL for software development has high educational effects, it is difficult for learners to realize many of its educational effects because they overly focus on the activities themselves. Therefore, this paper proposes a support system for visualization of acquired skills in PBL for software development using i-Competency Dictionary. We also describe the data acquisition method for the realization of the system.

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AAC-WGAN: A Novel Attention-Enhanced GAN Framework for SSVEP Augmentation and Classification

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ieee ACCESS 2024年 12卷 182627-182639页

作者： Liu, Junjie Xie, Jun Tao, Qing Zhang, Huanqing Wang, Hu Hu, Bo Xinjiang Univ Sch Mech Engn Aramqi 830049 Peoples R China Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Peoples R China Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian 710049 Peoples R China

The rapid advancement of brain-computer interface (BCI) technology has created interest in steady-state visual evoked potential (SSVEP)-based BCIs, which are valued for their high information transfer rates and ability to manage multiple targets. Nonetheless, the efficacy of SSVEP decoding is often constrained by the volume and duration of user calibration data, limiting its practical application. Generative adversarial networks (GANs) have shown promise in synthesizing SSVEP electroencephalogram (EEG) data. However, they face challenges, such as low signal-to-noise ratio and capturing both temporal and spatial features. To address the need for high-quality data generation, the Attention-Aided Classifier Wasserstein GAN (AAC-WGAN) is proposed, which is a novel GAN model that combines an Attention Mechanism and an Auxiliary Classifier to improve data quality and classification performance. Our experiments on the Direction and Dial datasets reveal that our model performs obviously better, particularly with a training set ratio of 25% synthetic data and 75% real data. It achieves a classification accuracy of 91.65% on the Direction dataset, which is a significant improvement over the baseline accuracy of 84.32% (p =0.008) and outperforms other comparable models (p <0.05 for all comparisons). On the Dial dataset, our model achieves a classification accuracy of 83.48%, outperforming both the baseline of 80.86% and other models. Additional analyses, such as t-SNE visualization and FFT, confirm our model's effectiveness in feature representation and frequency domain characteristics, with significant improvements in both data quality and classification stability. This work advances the state of SSVEP generation and classification, resulting in significant improvements in data quality and accuracy. It also represents a significant step forward in the development of BCI technologies.

关键词： Electroencephalography Brain modeling Feature extraction data models Accuracy Generators Attention mechanisms Noise visualization Brain-computer interface (BCI) generative adversarial network (GAN) data augmentation global attention mechanism auxiliary classifier steady-state visual evoked potential (SSVEP) steady-state visual evoked potential (SSVEP)

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Explaining AI-Informed Network Intrusion Detection with Counterfactuals

Explaining AI-Informed Network Intrusion Detection with Coun...

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ieee Conference on Computer Communications Workshops, INFOCOM Wksps

作者： Gang Liu Meng Jiang Department of Computer Science and Engineering University of Notre Dame Notre Dame Indiana USA

Artificial intelligence (AI) methods have been widely applied for accurate network intrusion detection (NID). However, the developers and users of the NID systems could not understand the systems' correct or incorrect decisions due to the complexity and black-box nature of the AI methods. This is a two-page poster paper that presents a new demo system that offers a number of counterfactual explanations visually for any data example. The visualization results were automatically generated: users just need to provide the index of a data example and do not edit anything on the graph. In the future, we will extend the detection task from binary classification to multi-class classification.

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