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Jasmine Jones

Publications and source records attributed to Jasmine Jones.

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Investigating Remote Hands-On Assistance for Collaborative Development of Embedded Systems

Developing embedded systems is a complex endeavor that frequently requires collaborative teamwork. With the rise of freelance work and the global shift towards remote work, the need for effective remote collaboration has become crucial for many developers and their clients. However, current communication and coordination tools are predominantly tailored for software development rather than hardware-focused tasks. This study investigates the potential for remote support tools specifically designed for embedded systems development. Through interviews with 12 experienced embedded systems developers, we explored their existing remote work practices, challenges, and requirements. We also conducted a user enactment study featuring a custom-designed remote manipulation agent, Handy, as a theoretical assistant, to identify the kinds of support developers would value in a collaborative setting. Our findings highlight the scenarios and strategies employed in remote work, the specific support needs, and the challenges related to information exchange, coordination, and execution. Additionally, we explore concerns around privacy, control, and trust when using remote physical manipulation tools. This research contributes to the field by integrating the development of embedded systems with the remote, on-demand collaboration and assistance typical of software environments, offering a solid empirical foundation for future research on remote manipulation agents in this area.

cs.HC

Applying Text Mining to Protest Stories as Voice against Media Censorship

Data driven activism attempts to collect, analyze and visualize data to foster social change. However, during media censorship it is often impossible to collect such data. Here we demonstrate that data from personal stories can also help us to gain insights about protests and activism which can work as a voice for the activists. We analyze protest story data by extracting location network from the stories and perform emotion mining to get insight about the protest.

cs.SI