With the continuous development of data storage, analysis, processing and other technologies, people are eager to visualize the mining process of complex data, and data mining visualization technology is gradually app...
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This paper outlines the development of an interactive visualization tool, 'A Good Life,' which emerged out of a collaborative project between design researchers and practitioners from the University of Technol...
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ISBN:
(纸本)9798350307160
This paper outlines the development of an interactive visualization tool, 'A Good Life,' which emerged out of a collaborative project between design researchers and practitioners from the University of Technology Sydney and Northcott, an Australian disability services organisation. Northcott provides supported accommodation services for people living in group homes (up to 6 people) with moderate to severe intellectual and physical disabilities requiring 24-hour support. Supported accommodation provides housing for marginalised and vulnerable people, often with limited resources. Working in this environment can be challenging but also rewarding. However, residents face even greater challenges because decisions made by others primarily determine their quality of life. These decisionmakers can include family members or long-term support workers who have a deep understanding of the resident, allied health professionals who interact with the resident regularly but have a limited perspective, and government officials who lack a personal relationship with the resident but formulate policies that consequently have a profound effect on them. A significant issue for people with disability is the lack of visibility or understanding regarding how decisions affect their quality of life. To address this issue, the tool visualizes how decisions can restrict or enhance opportunities for people with disabilities. Additionally, it seeks to improve levels of communication by better expressing the will and preferences of the residents.
Personalized learning, science education, and public understanding of science are linked in many ways. Studies of public understanding of science suggest that citizen science literacy is not just about reforming schoo...
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ISBN:
(数字)9781665494212
ISBN:
(纸本)9781665494212
Personalized learning, science education, and public understanding of science are linked in many ways. Studies of public understanding of science suggest that citizen science literacy is not just about reforming school science curricula. Understanding statistics is a challenge for many people, and customized learning methods are required. Statistics are useful for keeping records, calculating probabilities, and providing knowledge. Basically, they help us understand the world a little better through numbers and other quantitative information. Motivated by the overall goal of promoting understanding of statistical concepts and minimizing misinformation, thirteen gamification and data physicalization initiatives help us to offer ten challenges. They allow players to record, update, and explore the characteristics and differences between different statistical concepts. This work combines dynamic physical visualization and gamification to explain linear and exponential functions and a set of distributions using analog explicable cubes as a means of representation.
To date, the comparison of Statistical Shape Models (SSMs) is often solely performance-based, carried out by means of simplistic metrics such as compactness, generalization, or specificity. Any similarities or differe...
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ISBN:
(纸本)9798350318920;9798350318937
To date, the comparison of Statistical Shape Models (SSMs) is often solely performance-based, carried out by means of simplistic metrics such as compactness, generalization, or specificity. Any similarities or differences between the actual shape spaces can neither be visualized nor quantified. In this paper, we present a new method to qualitatively compare two linear SSMs in dense correspondence by computing approximate intersection spaces and set-theoretic differences between the (hyper-ellipsoidal) allowable shape domains spanned by the models. To this end, we approximate the distribution of shapes lying in the intersection space using Markov chain Monte Carlo and subsequently apply Principal Component Analysis (PCA) to the posterior samples, eventually yielding a new SSM of the intersection space. We estimate differences between linear SSMs in a similar manner;here, however, the resulting spaces are no longer convex and we do not apply PCA but instead use the posterior samples for visualization. We showcase the proposed algorithm qualitatively by computing and analyzing intersection spaces and differences between publicly available face models, focusing on gender-specific male and female as well as identity and expression models. Our quantitative evaluation based on SSMs built from synthetic and real-world data sets provides detailed evidence that the introduced method is able to recover ground-truth intersection spaces and differences accurately.
This paper presents a preliminary analysis of an Indoor Positioning System (IPS) designed for forklifts using Wi-Fi signal fingerprinting and the K-Nearest Neighbors (KNN) algorithm. The system utilizes M5stack (ESP32...
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Breast Cancer is a disease that widely affects millions. A widely recognized approach for diagnosing breast cancer is through the analysis of histopathological images. In order to achieve notable results with these im...
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The field of human-robot interaction has been rapidly advancing in recent years, as robots are increasingly being integrated into various aspects of human life. However, for robots to effectively collaborate with huma...
ISBN:
(纸本)9798350336702
The field of human-robot interaction has been rapidly advancing in recent years, as robots are increasingly being integrated into various aspects of human life. However, for robots to effectively collaborate with humans, it is crucial that they have a deep understanding of the environment in which they operate. In particular, the ability to predict traversability and detect tactile information is crucial for enhancing the safety and efficiency of human-robot interactions. To address this challenge, this paper proposes a method called "Feel the Point Clouds" that use point clouds to predict traversability and detect tactile terrain information for a tracked rescue robot. This information can be used to adjust the robot's behavior and movements in real-time, allowing it to interact with the environment in a more intuitive and safe manner. The experimental results of the proposed method are evaluated in various scenarios and demonstrate its effectiveness in improving human-robot interaction and visualization for a more accurate and intuitive understanding of the environment.
Mutation testing is a potentially effective method to assess test suite adequacy. Researchers have made mutation testing more computationally efficient, and new frameworks are regularly emerging. However, there is sti...
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ISBN:
(数字)9798400712487
ISBN:
(纸本)9798400712487
Mutation testing is a potentially effective method to assess test suite adequacy. Researchers have made mutation testing more computationally efficient, and new frameworks are regularly emerging. However, there is still limited adoption of mutation testing in industry. We hypothesize that such adoption is hindered by a lack of guidance on how to effectively and efficiently utilize mutation testing in a development workflow. To that end, we have conducted an industrial case study exploring the technical challenges of implementing mutation testing in continuous integration, what information from mutation testing is of use to developers, and how that information should be presented (in textual and visual form). Our results reveal five technical challenges of integrating mutation testing and nine key findings regarding how the results of mutation testing are used and presented. We also offer a dashboard to visualize mutation testing results, as well as 16 recommendations for making effective use of mutation testing in practice(1).
The rapid evolution of wireless communications in the Fifth Generation (5G) has seen many practical use cases. One important use case, which is a potential candidate for the Sixth Generation (6G) is sensing and tracki...
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ISBN:
(纸本)9798350374247;9798350374230
The rapid evolution of wireless communications in the Fifth Generation (5G) has seen many practical use cases. One important use case, which is a potential candidate for the Sixth Generation (6G) is sensing and tracking and this holds much promise in the development of Integrated Sensing and Communications (ISAC). This paper focuses on the utilization of the 5G synchronization signal blocks (SSBs) which are emitted periodically to perform detection. Our post-processing involves extracting Channel State information (CSI) estimates from the Inphase / Quadrature (IQ) samples collected over the air interface from a 5G Base Station (BS) to a User Equipment (UE) and use this data as input into a deep learning model to perform person presence detection. This demonstration provides a complete pipeline showcasing data collection, post-processing, model classification and visualization for person detection. Detection can be achieved for other objects such ground or aerial vehicles etc. but this paper will be focused on person detection.
In order to more accurately analyze the actual state of the bridge, building an accurate model is one of the effective technical means. For this reason, this paper puts forward the research on three-dimensional visual...
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