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2024 international conference on computer Network Security and Software Engineering, CNSSE 2024

作者： Liu, Jian Dongying Vocational Institute Shandong Dongying257091 China

ISBN: (纸本)9781510680234

With the rapid development of computer network technology, the network structure has become increasingly complex, and the number and types of network devices have also shown explosive growth. In order to better understand, manage and optimize the network, visualization of network topology has become an important research field. However, the current visualization framework and tools have some problems in the practical process, such as complicated application process, single display effect and insufficient interaction ability, which can not meet the actual needs of users. In this regard, this paper will take network topology visualization as the research object, and build a network topology visualization system based on HTML5 through Web technology to realize the innovation of network topology management. Practice has proved that the whole system adopts B/S architecture design, and the front end is mainly based on HTML5, CSS and JavaScript, combined with BootStrap layout framework to complete the design and construction. At the same time, the Canvas is used to complete the drawing and rendering of visual graphics, which greatly improves the efficiency of network monitoring, conforms to the expected goal of network management system in displaying topological functions, and has certain practical application value. © 2024 SPIE.

关键词： Network topology

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He Is Not Your Hero: Gendered Experience Unveiled Through Gameplay Videos (A Case Study Of Genji From Overwatch) 17

He Is Not Your Hero: Gendered Experience Unveiled Through Ga...

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17th international conference on Interfaces and Human computer Interaction 2023, IHCI 2023, the 17th international conference on computer graphics, visualization, computer Vision and Image Processing 2023, CGVCVIP 2023 and 16th international conference on Game and Entertainment Technologies 2023, GET 2023

作者： Zhang, Chuxuan University of Edinburgh Holland Annexe 18 Holyrood Park Road EdinburgScotland United Kingdom

ISBN: (纸本)9789898704498

The gaming industry has predominately exhibited a significant gender disparity, resulting in the portrayal of game characters, including avatars, in a manner that reinforces gender stereotypes. This study aims to investigate the impact of avatar portrayal on the overall gaming encounter among individuals with diverse gender identities. To achieve this objective, gameplay videos are analysed as valuable sources of players' experiences. The case study focuses on Genji, an avatar from the video game Overwatch (2016) and its subsequent sequel and replacement. By employing multimodal discourse analysis, the study examines the impact of avatar characteristics on player engagement in the context of Overwatch (2016) and Overwatch 2 (2022). The findings reveal that avatar characteristics significantly influence player engagement, particularly in terms of gameplay mechanics, surpassing that of the narrative. The endorsement of heteronormative representations, as the character Genji exemplifies, could conspires with the toxic environment. The research advocates that promoting gender inclusivity in the gaming industry requires the integration of a wide range of avatars that not only reflect queerness in the narrative but also in the game mechanics, thereby fostering a more inclusive gaming atmosphere. © 2023 Proceedings of the international conferences on Interfaces and Human computer Interaction 2023, IHCI 2023;computer graphics, visualization, computer Vision and Image Processing 2023, CGVCVIP 2023;and Game and Entertainment Technologies 2023, GET 2023. All rights reserved.

关键词： Human computer interaction

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Towards Robust Visual Explanations For Deep Convolutional Networks With Weight-wise Perturbations 15

Towards Robust Visual Explanations For Deep Convolutional Ne...

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15th international conference on graphics and Image Processing, ICGIP 2023

作者： Lang, Kaifan Chen, Chen Zheng, Junshuai Hu, Xiyuan Tang, Zhenmin Nanjing University of Science and Technology China

ISBN: (纸本)9781510675018

Explaining the complicated mechanisms underlying the image classification capabilities of deep Convolutional Neural Network (CNN) models, continue to pose huge challenges within the field of computer vision. To address this concern, numerous interpretability methods have been devised, aimed at clarifying the image classification process. These methods include approaches such as sensitivity maps, which involve computing the gradients of class outputs with respect to input images, and techniques like class activation mapping (CAM). Furthermore, the incorporation of noise into input images has emerged as an effective strategy for augmenting visualization quality and removing noise. In this paper, we propose two key contributions: the introduction of a novel approach that injects noise into network weights to enhance visualization, involving image gradient updates and average gradient computations;and a new indicator for evaluating interpretability - the center of gravity, and comprehensive experiments were conducted on multiple datasets and different deep neural network models. In the subsequent experimental sections, we demonstrate that our method achieves superior visualization quality and can be combined with other interpretability methods to enhance their performance. © 2024 SPIE. All rights reserved.

关键词： visualization

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Relational Structure visualization in Composition 27

Relational Structure Visualization in Composition

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27th international conference on Information Visualisation (IV) / 19th international conference computer graphics, imaging and visualization (CGiV)

作者： Chen, Kuan-Chen Hsu, Chung-Chian Chang, Teng-Wen Lee, Chang-Franw Wang, Cheng-Gang Natl Yunlin Univ Sci & Technol Grad Sch Design Touliu Yunlin Taiwan Natl Yunlin Univ Sci & Technol Dept Informat Management Touliu Yunlin Taiwan Natl Yunlin Univ Sci & Technol Dept Digital Media Design Touliu Yunlin Taiwan

ISBN: (纸本)9798350341614

This study aims to explore the visualization of relational structures in composition within visual imagery. Composition is an essential technique used by artists to manage the elements within an image, facilitating the communication and transmission of messages through the organization of visual elements. Human thinking involves a form of structural thinking, which is also triggered when appreciating works of art. This research seeks to incorporate the characteristics of human structural thinking into composition, making the relationships between compositions logical and computable. Ultimately, the study proposes a method to visualize the relationships within image compositions. The proposed method begins by inviting experts to explain the key knowledge within the artwork. This helps in understanding the content of the artwork and establishing nodes on the image to represent relevant compositional knowledge. These knowledge contents are then presented digitally and in a structured form. Next, the experiences of viewers are transformed into precise data. The gaze points generated while observing the image are connected. Finally, the data from both experts and viewers are combined to reveal the relational structures within the composition. This method helps overcome the limitations of previous understandings of artworks, which heavily relied on subjective interpretations by experts and superficial descriptions based solely on the visual organization of the image. This research aims to provide an objective perspective in interpreting composition by exploring the hidden structures organized within the image from the viewpoint of viewer attention. The research findings indicate that the compositions formed by viewers are not merely static or dynamic structures. Instead, they represent experiential, dynamic, and vital organizational structures. The results of the study can better approach the viewer's real visual experiences and confirm that composition is not just a tech

关键词： eye-tracking attention composition

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3DSPOPP-3D Scatter Plots of Octants with Projection Planes 27

3DSPOPP-3D Scatter Plots of Octants with Projection Planes

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27th international conference on Information Visualisation (IV) / 19th international conference computer graphics, imaging and visualization (CGiV)

作者： Nakamura, Shohei Okada, Yoshihiro Kyushu Univ Grad Sch Informat Sci & Elect Engn Motooka 744Nishi Ku Fukuoka Japan Kyushu Univ Kyushu Univ Lib ICER Innovat Ctr Educ Resources Cybersecur Ctr Fukuoka Japan Kyushu Univ Grad Sch ISEE Fukuoka Japan

ISBN: (纸本)9798350341614

This paper proposes a web-based visualization tool called 3DSPOPP for visualizing the relationship between sets of attributes as two data points put on separate planes and connected by a line in a 3D scatter plot. The motivation for creating this tool is to visualize darknet traffic data to find communication anomalies. Although 3D scatter plots can visualize network packet data by assigning time, source IP address and destination IP address to each axis, users can not easily understand the relationship between one set of source IP addresses and source ports and another set of destination IP addresses and destination ports. For anomaly detection, these four attributes are all significant. Therefore, the authors elongate each axis to create multiple plot zones of up to eight separate areas in 3D space, usually called octants. This tool is called 3D Scatter Plots of Octants, abbreviated as 3DSPO. Furthermore, projection planes of two octants are combined with 3DSPO to visualize the relationship between two attribute pairs of two octants such as source IP/port pair and destination IP/port pair. This combined tool is called 3DSPOPP.

关键词： 3D visualization scatter plot network traffic data darknet traffic data

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MinMax-CAM: Increasing Precision of Explaining Maps by Contrasting Gradient Signals and Regularizing Kernel Usage 17th

MinMax-CAM: Increasing Precision of Explaining Maps by Contr...

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17th international Joint conference on computer Vision, imaging and computer graphics Theory and Applications (VISIGRAPP) / 17th international conference on computer Vision Theory and Applications (VISAPP)

作者： David, Lucas Pedrini, Helio Dias, Zanoni Univ Estadual Campinas Campinas SP Brazil

ISBN: (纸本)9783031457241;9783031457258

While various AI explaining methods has been developed in the last decade, the Class Activation Map (CAM) technique (and derivations thereof) has remains a popular alternative today. Highly versatile, and sufficiently simple, CAM-based techniques have been consistently used to explain the predictions of Convolutional Neural Networks over classification problems. However, many studies conducted to assert the precision of the produced explaining maps have done so on single-label multi-class classification problems, where the task is simplified by focusing and framing the objects of interest in the foreground. In this work, we test and evaluate the efficacy of CAM-based techniques over distinct multi-label sets. We find that techniques that were created with single-label classification in mind (such as Grad-CAM, Grad-CAM++ and Score-CAM) will often produce diffuse visualization maps in multi-label scenarios, overstepping the boundaries of their explaining objects of interest onto objects of different classes. We propose a generalization of the Grad-CAM technique for the multi-label scenario that produces more focused explaining maps by maximizing the activation of a class of interest while minimizing the activation of the remaining classes present in the sample. Our results indicate that MinMax-CAM produces more focused explaining maps over different network architectures and datasets. Finally, we present a regularization strategy that encourages sparse positive weights in the last classifying, while penalizing the association between the classification of a class and the occurrence of correlated patterns, resulting in cleaner activation maps.

关键词： computer vision Multi-label Explainable artificial intelligence

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Proceedings of the international conferences on Interfaces and Human computer Interaction 2023, IHCI 2023;computer graphics, visualization, computer Vision and Image Processing 2023, CGVCVIP 2023;and Game and Entertainment Technologies 2023, GET 2023

Proceedings of the International Conferences on Interfaces a...

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ISBN: (纸本)9789898704498

The proceedings contain 36 papers. The topics discussed include: simple measurement of user response;is gesture-based interaction equally viable in manual and autonomous driving?;visual analytics for the marriage network in the Goryeo Dynasty, Korea;gradient pattern analysis applied for computer vision in medical ultrasound diagnosis;prototyping visualizations as a support for selecting representative models of petroleum reservoirs;how to teach programming with electronic games;a mobile conducting app with a switching beat-following algorithm;an augmented reality game for iOS smartphones;a gamified application for mitigating plastic pollution in coastal areas;and the impact of perceived challenge on narrative immersion in RPG video games: a preliminary study.

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Comparing Gaze, Head and Controller Selection of Dynamically Revealed Targets in Head-Mounted Displays

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IEEE TRANSACTIONS ON visualization AND computer graphics 2023年第11期29卷 4740-4750页

作者： Sidenmark, Ludwig Prummer, Franziska Newn, Joshua Gellersen, Hans Univ Toronto Toronto ON Canada Univ Lancaster Lancaster England Aarhus Univ Aarhus Denmark

This paper presents a head-mounted virtual reality study that compared gaze, head, and controller pointing for selection of dynamically revealed targets. Existing studies on head-mounted 3D interaction have focused on pointing and selection tasks where all targets are visible to the user. Our study compared the effects of screen width (field of view), target amplitude and width, and prior knowledge of target location on modality performance. Results show that gaze and controller pointing are significantly faster than head pointing and that increased screen width only positively impacts performance up to a certain point. We further investigated the applicability of existing pointing models. Our analysis confirmed the suitability of previously proposed two-component models for all modalities while uncovering differences for gaze at known and unknown target positions. Our findings provide new empirical evidence for understanding input with gaze, head, and controller and are significant for applications that extend around the user.

关键词： Mathematical models Three-dimensional displays Task analysis Resists Lenses Performance evaluation visualization Pointing Selection Performance Virtual Reality 3D Interaction

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Exploring Users Pointing Performance on Large Displays with Different Curvatures in Virtual Reality

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IEEE TRANSACTIONS ON visualization AND computer graphics 2023年第11期29卷 4535-4545页

作者： Ullah, A. K. M. Amanat Delamare, William Hasan, Khalad Univ British Columbia Okanagan BC Canada Univ Bordeaux ESTIA Inst Technol EstiaR F-64210 Bidart France

Large curved displays inside Virtual Reality environments are becoming popular for visualizing high-resolution content during analytical tasks, gaming or entertainment. Prior research showed that such displays provide a wide field of view and offer users a high level of immersion. However, little is known about users' performance (e.g., pointing speed and accuracy) on them. We explore users' pointing performance on large virtual curved displays. We investigate standard pointing factors (e.g., target width and amplitude) in combination with relevant curve-related factors, namely display curvature and both linear and angular measures. Our results show that the less curved the display, the higher the performance, i.e., faster movement time. This result holds for pointing tasks controlled via their visual properties (linear widths and amplitudes) or their motor properties (angular widths and amplitudes). Additionally, display curvatures significantly affect the error rate for both linear and angular conditions. Furthermore, we observe that curved displays perform better or similar to flat displays based on throughput analysis. Finally, we discuss our results and provide suggestions regarding pointing tasks on large curved displays in VR.

关键词： Task analysis Performance evaluation visualization Data visualization Focusing Error analysis Throughput Virtual Large Display Pointing Performance Display Curvatures Fitts Law

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Randomrewardmechanisms (Loot Boxes): Behavioral Economics As A Regulatory Solution In Brazilian Law 17

Randomrewardmechanisms (Loot Boxes): Behavioral Economics As...

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作者： Fantini, Laiane Maris Caetano PUC Minas. Centro DTIBR MG Belo Horizonte Brazil

ISBN: (纸本)9789898704498

The paper seeks to reflect on ways to create an effective regulation by understanding the aspects of random reward mechanisms in video games, also known as loot boxes. Players acquire digital assets of a game through microtransactions, and pays with in-game currency or real money. Among these digital assets, several games also offer loot boxes, which are systems of "surprise boxes" with a certain price but whose reward is unknown to the player (and is only revealed when the box is purchased and opened). A simple way of selling a digital asset has serious implications for players, mainly due to the similarity with gambling in making the reward relegated to chance. Also, adults and children players are encouraged to exhibit addictive behaviors, spending time and money without any control. Brazilian law does not have enough apparatus to protect consumers from these practices and banning loot boxes from the market does not seem to be the solution, as similar mechanisms could arise even worse. This way of marketing digital assets hides the real transaction costs and makes consumers make decisions based on heuristics, and that's why the Behavioral Economic Theory can offer better solutions to protect players. © 2023 Proceedings of the international conferences on Interfaces and Human computer Interaction 2023, IHCI 2023;computer graphics, visualization, computer Vision and Image Processing 2023, CGVCVIP 2023;and Game and Entertainment Technologies 2023, GET 2023. All rights reserved.

关键词： Human computer interaction

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