Gaze-based human-computer interaction (HCI) via the internet includes temporal delays with unpredictable "jitter," degrading usability including the sense of agency – the feeling of control over one's actions and subsequent outcomes. Using a sense of agency experiment paradigm, we present a novel method to test jitter's effect on user sensation. Our methodology simulates internet-based delays, obtaining data to predict a critical parameter and delay to degrade user sensation. The task was a letter visual search with biresolution gaze-contingent window (high-resolution foveal, blurred peripheral), manipulating consistent and jittery delays between eye movements and display updates. This paradigm effectively manipulated participants’ sense of agency, eliciting systematic bias in authorship responses by manipulating the minimum jittery delay and jitter variability. This suggests that the proposed method provides a powerful tool for understanding the interplay of delays, eye and other body movements, and the sense of agency, with/without neuroimaging, with internet-originated delays in HCI.

This demo abstract introduces a new light-weight programming language koa which is suitable for blockchain system design and implementation. In this abstract, the basic features of koa are introduced including working system (with playground), architecture, and virtual machine operations. Rum-time execution of software implemented by koa will be presented during the session.

This paper proposes a reliable and self-adaptive operating system management policy for CCTV-based security applications which controls arrival image compression rates. After receiving image sequences via CCTV cameras, the system enqueues the sequences of images and processes them for face recognition. High compression rates in CCTV-recorded images provide low recognition performance due to quantization while it is beneficial in terms of queue stability. On the other hand, low compression rates in the images provide high recognition performance while it may introduce queue overflows. Therefore, this paper designs a queue-aware, self-adaptive, and reliable operating system management scheme which aims at face identification performance maximization while avoiding queue overflow by controlling CCTV-recorded image compression rates based on the theory of Lyapunov optimization.