by jsendak | Jul 9, 2024 | Computer Science
arXiv:2407.04959v1 Announce Type: cross
Abstract: Open data is an important basis for open science and evidence-based policymaking. Governments of many countries disclose government-related statistics as open data. Some of these data are provided as CSV files. However, since CSV files are plain texts, we cannot ensure the integrity of a downloaded CSV file. A popular way to prove the data’s integrity is a digital signature; however, it is difficult to embed a signature into a CSV file. This paper proposes a method for embedding a digital signature into a CSV file using a data hiding technique. The proposed method exploits a redundancy of the CSV format related to the use of double quotes. The experiment revealed we could embed a 512-bit signature into actual open data CSV files.
Embedding Digital Signatures into CSV Files: Enhancing Open Data Integrity
Open data has emerged as a crucial component of open science and evidence-based policymaking, allowing governments to disclose government-related statistics to the public. However, one challenge in utilizing open data is ensuring its integrity, particularly for data provided in CSV format. As CSV files are plain texts, there is a need to guarantee the integrity of downloaded files. This paper proposes a novel method for embedding digital signatures into CSV files, effectively addressing this issue.
The proposed method leverages a data hiding technique that takes advantage of a redundancy present in the CSV format, specifically the use of double quotes. By strategically manipulating the placement and formatting of double quotes within the CSV file, a digital signature can be embedded without modifying the data itself. This approach ensures the integrity of the CSV file while maintaining its compatibility with existing systems and tools that operate on the CSV format.
The experiment conducted to assess the feasibility of the proposed method demonstrated its effectiveness in embedding a 512-bit digital signature into actual open data CSV files. This successful embedding process indicates the potential of the technique to be implemented on a larger scale, providing a means to verify the integrity of open data without compromising its usability and accessibility.
From a multidisciplinary perspective, this research combines concepts from various fields such as data security, information retrieval, and multimedia information systems. The use of data hiding techniques draws upon the principles of steganography, a branch of information security concerned with concealing information within seemingly innocuous data. By applying steganographic principles to the CSV format, this research bridges the gap between data integrity and open data, contributing to the wider field of multimedia information systems.
Furthermore, this study holds relevance to related fields such as animations, artificial reality (AR), augmented reality (AR), and virtual realities (VR). As these technologies heavily rely on the manipulation and integration of digital data, the ability to embed digital signatures into CSV files enhances the integrity and reliability of the underlying data used in these systems. The proposed method can serve as an additional layer of trust and security, ensuring that the data utilized in multimedia applications, animations, and virtual environments is authentic and unaltered.
In conclusion, the embedding of digital signatures into CSV files using the proposed method presents a valuable contribution to the field of open data integrity. By addressing the challenge of guaranteeing the integrity of open data while preserving its usability, this research provides a practical solution that can be implemented by governments and organizations worldwide. The multi-disciplinary nature of the concepts involved, coupled with its relevance to multimedia information systems and related technologies, further solidifies the significance of this research in the broader context of data security and authenticity.
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by jsendak | Jul 9, 2024 | Computer Science
As an expert commentator, I find this article fascinating as it explores the idea of using predicted information as an energy source for autonomous learning. The concept of recycling the energy derived from successful predictions to drive the enhancement of AI agents’ predictive capabilities is a novel approach that has the potential to revolutionize the field of AI.
The authors suggest that by making certain meta-architectural adjustments, any unsupervised learning apparatus could achieve complete independence from external energy sources. This idea is intriguing, as it implies that AI systems could become self-sustaining physical systems with a strong intrinsic drive for continual learning.
The use of the autoencoder as an exemplification of this concept is particularly interesting. Autoencoders are widely used models for unsupervised efficient coding. By demonstrating how progressive paradigm shifts can profoundly alter our understanding of learning and intelligence, the authors make a strong case for reconceptualizing learning as an energy-seeking process.
The article also raises an important point about bridging the gap between algorithmic concepts and physical models of intelligence. By viewing learning as an energy-seeking process, the authors propose a way to achieve true autonomy in learning systems. This perspective has the potential to revolutionize the field and push the boundaries of AI research.
In conclusion, this article presents a fascinating concept of using predicted information as an energy source for autonomous learning. By making adjustments to unsupervised learning apparatus and reconceptualizing learning as an energy-seeking process, the authors propose a way to achieve true autonomy in AI systems. While still theoretical, this idea has the potential to significantly impact the field of AI and push the boundaries of learning and intelligence.
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by jsendak | Jul 8, 2024 | Computer Science
arXiv:2407.03860v1 Announce Type: new
Abstract: Prior research has explored potential applications of video games in programming education to elicit computational thinking skills. However, existing approaches are often either too general, not taking into account the diversity of genres and mechanisms between video games, or too narrow, selecting tools that were specifically designed for educational purposes. In this paper we propose a more fundamental approach, defining beneficial connections between individual design patterns present in video games and computational thinking skills. We argue that video games have the capacity to elicit these skills and even to potentially train them. This could be an effective method to solidify a conceptual base which would make programming education more effective.
Exploring the Relationship Between Video Games, Design Patterns, and Computational Thinking Skills
In recent years, there has been growing interest in exploring the use of video games as a means to enhance programming education and develop computational thinking skills. While previous research has touched upon this topic, the approaches thus far have been either too general or too narrow to fully capture the potential of video games in this context. However, a more fundamental approach that focuses on the connections between design patterns present in video games and computational thinking skills shows promise.
The field of multimedia information systems encompasses the study of various forms of media, including video games, animations, artificial reality, augmented reality, and virtual realities. By examining the multidisciplinary nature of these concepts, we can gain a deeper understanding of how they relate to programming education and computational thinking.
Design patterns in video games refer to the recurring solutions to common problems that game developers employ to create engaging gameplay experiences. These patterns can vary widely depending on the genre and mechanics of the game. By identifying and analyzing these design patterns, we can begin to uncover the cognitive processes and problem-solving skills that video games tap into.
Computational thinking skills, on the other hand, are a set of cognitive abilities that enable individuals to solve problems using computer science principles. These skills include algorithmic thinking, pattern recognition, decomposition, abstraction, and logical reasoning. The goal of programming education is to cultivate these skills in students, enabling them to become effective programmers and problem solvers.
By establishing connections between specific design patterns in video games and computational thinking skills, this research opens up new possibilities for using video games as educational tools. By immersing students in gameplay experiences that require the use of these skills, programming education can become more engaging and effective.
The use of video games to train computational thinking skills not only holds potential for formal education settings but also for self-study and informal learning. With the increasing popularity of gaming platforms and the accessibility of video games, this approach has the potential to reach a wider audience and make programming education more accessible to those who may not have access to traditional educational resources.
Furthermore, considering the wider field of multimedia information systems, this research highlights the importance of interdisciplinary approaches. The study of video games and their connections to computational thinking skills brings together concepts from computer science, education, psychology, and game design. This interdisciplinary perspective allows for a richer exploration of the potential benefits of leveraging video games for programming education.
The Future of Video Games and Programming Education
Looking ahead, there are several exciting directions for future research in this field. One avenue to explore is the development of specific video game-based interventions that target the cultivation of computational thinking skills. By designing games that intentionally incorporate and reinforce these skills, educators can create purpose-built learning experiences that go beyond the incidental learning that may occur when playing existing games.
Another area of interest is the evaluation of the effectiveness of video game-based interventions in programming education. Researchers can design experiments and studies to measure the impact of these interventions on students’ computational thinking abilities, coding proficiency, and overall motivation and engagement with programming. Such empirical evidence can help inform the design of future interventions and provide insights into the optimal integration of video games in programming curricula.
Finally, as technology continues to advance, new opportunities arise for the development of immersive and interactive virtual reality experiences. By harnessing the power of virtual reality, educators can create simulated environments that bring complex programming concepts to life. These VR experiences can provide hands-on learning opportunities that bridge the gap between theory and practice, further enhancing students’ understanding and mastery of programming principles.
In conclusion, the exploration of the relationship between video games, design patterns, and computational thinking skills opens up exciting possibilities for the future of programming education. By recognizing the multidisciplinary nature of multimedia information systems and leveraging video games as educational tools, we can create more engaging and effective learning experiences. As the field continues to evolve, it is crucial to prioritize interdisciplinary research and collaboration to fully tap into the potential of this approach.
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by jsendak | Jul 8, 2024 | Computer Science
Exploring Negative Shaping Order K in Set Shaping Theory
The Set Shaping Theory has long been used to extend the length of data strings, improving their testability and compressibility through the use of positive shaping order K. However, a paradigm shift is proposed in this paper by introducing the concept of negative shaping order K, which aims to shorten data strings and potentially enhance compression efficiency. While this approach shows promise, it also raises some theoretical implications, practical benefits, and challenges that need to be considered.
Theoretical Implications
The introduction of negative shaping order K challenges the traditional understanding of Set Shaping Theory. By shortening data strings, we can potentially reduce the storage requirements and improve data transfer speeds. However, this approach sacrifices the local testability of the data, which could have implications for error detection and correction mechanisms. It is crucial to explore the trade-offs between compression efficiency and data integrity in this new paradigm.
Practical Benefits
The potential benefits of using negative shaping order K are noteworthy. By shortening data strings, we can save storage space, reduce memory and bandwidth requirements, and potentially achieve faster data transfer rates. This could be particularly advantageous in contexts where storage or transmission resources are limited, such as in mobile devices or IoT applications. Additionally, the shortened data strings could lead to faster processing times, enabling real-time analysis and decision-making.
Challenges
While the idea of negative shaping order K offers enticing possibilities, it also presents several challenges that need to be addressed. One of the main concerns is the potential loss of local testability, which can impact the ability to detect and correct errors in the data. Additionally, the implementation of negative shaping order K may require significant changes to existing compression algorithms and protocols. Ensuring compatibility with legacy systems and establishing interoperability standards would be essential to the successful adoption of this methodology.
Conclusion
The exploration of negative shaping order K in Set Shaping Theory opens up intriguing possibilities for improving compression efficiency by shortening data strings. However, it is important to carefully consider the theoretical implications, practical benefits, and challenges associated with this new methodology. Further research and experimentation are needed to evaluate the trade-offs between compression efficiency and data integrity in various contexts. With proper consideration and adaptation, negative shaping order K could potentially revolutionize data compression and storage techniques.
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by jsendak | Jul 4, 2024 | Computer Science
arXiv:2407.02773v1 Announce Type: new
Abstract: We present OpenVNA, an open-source framework designed for analyzing the behavior of multimodal language understanding systems under noisy conditions. OpenVNA serves as an intuitive toolkit tailored for researchers, facilitating convenience batch-level robustness evaluation and on-the-fly instance-level demonstration. It primarily features a benchmark Python library for assessing global model robustness, offering high flexibility and extensibility, thereby enabling customization with user-defined noise types and models. Additionally, a GUI-based interface has been developed to intuitively analyze local model behavior. In this paper, we delineate the design principles and utilization of the created library and GUI-based web platform. Currently, OpenVNA is publicly accessible at url{https://github.com/thuiar/OpenVNA}, with a demonstration video available at url{https://youtu.be/0Z9cW7RGct4}.
Expert Commentary: OpenVNA – Advancing Language Understanding Systems Evaluation
In the field of multimedia information systems, the evaluation of language understanding systems is a complex task that requires the consideration of various factors. OpenVNA, an open-source framework, presents a significant development in this area by providing researchers with a comprehensive toolkit for analyzing the behavior of multimodal language understanding systems under noisy conditions. This framework offers both batch-level robustness evaluation and on-the-fly instance-level demonstration, thereby enabling researchers to assess the system’s performance in different scenarios.
The multi-disciplinary nature of the concepts covered in OpenVNA is noteworthy. It encompasses elements from the fields of machine learning, natural language processing, and human-computer interaction. This integration illustrates the importance of considering these aspects to obtain a holistic understanding of language understanding systems.
The benchmark Python library provided by OpenVNA is a valuable resource for assessing the global model robustness of language understanding systems. With its high flexibility and extensibility, researchers can customize the library by incorporating user-defined noise types and models. This capability allows for a more comprehensive evaluation of system performance by simulating real-world scenarios where noise and variations are prevalent.
Furthermore, OpenVNA includes a GUI-based interface that simplifies the analysis of local model behavior. This feature enhances the usability of the framework by providing an intuitive way to explore and visualize the system’s response to different inputs. Researchers can easily observe and interpret how the language understanding model interacts with various noisy conditions, gaining insights into its strengths and weaknesses.
In the broader context of multimedia information systems, OpenVNA aligns with the advancements in technologies such as animations, artificial reality, augmented reality, and virtual realities. Language understanding systems are increasingly being integrated into these technologies, and evaluating their performance in realistic environments is crucial for improving user experiences. OpenVNA’s focus on robustness evaluation under noisy conditions contributes to this objective by enabling researchers to identify and address potential limitations of language understanding systems in these multimedia contexts.
Overall, OpenVNA represents a significant contribution to the field of language understanding systems evaluation. Its open-source nature, combined with the multi-disciplinary approach and the provision of both a benchmark Python library and a GUI-based interface, make it a valuable tool for researchers looking to analyze and enhance the robustness of multimodal language understanding systems.
References:
- OpenVNA. (n.d.). Retrieved from https://github.com/thuiar/OpenVNA
- OpenVNA Demo Video. (n.d.). Retrieved from https://youtu.be/0Z9cW7RGct4
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by jsendak | Jul 4, 2024 | Computer Science
Expert Commentary:
The increasing demand for dynamic behaviors in automotive use cases has led to the emergence of Software Defined Vehicles (SDVs) as a promising solution. SDVs bring dynamic onboard service management capabilities, allowing users to request a wide range of services during vehicle operation. However, this dynamic environment presents challenges in efficiently allocating onboard resources to meet mixed-criticality onboard Quality-of-Service (QoS) network requirements while ensuring an optimal user experience.
One of the key challenges in this context is the activation of on-the-fly cooperative Vehicle-to-Everything (V2X) services in response to real-time road conditions. These services require careful resource allocation to ensure they can run efficiently while not compromising the user experience. Furthermore, the ever-evolving real-time network connectivity and computational availability conditions further complicate this process.
To address these challenges, the authors propose a dynamic resource-based onboard service orchestration algorithm. This algorithm takes into account real-time in-vehicle and V2X network health, as well as onboard resource constraints, to select degraded modes for onboard applications and maximize the user experience. It introduces the concept of Automotive eXperience Integrity Level (AXIL), which expresses a runtime priority for non-safety-critical applications.
The algorithm presented in this article aims to produce near-optimal solutions while significantly reducing execution time compared to straightforward methods. The simulation results demonstrate the effectiveness of this approach in enabling efficient onboard execution for a user experience-focused service orchestration.
Overall, this article highlights the importance of efficient resource allocation in Software Defined Vehicles to meet mixed-criticality onboard QoS network requirements. The proposed dynamic resource-based onboard service orchestration algorithm, leveraging the concept of AXIL, addresses this challenge and paves the way for improved user experiences in SDVs.
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