Science communication revision requires writers to dynamically balance scientific exposition and narrative engagement - a process where writers often struggle with competing directions. Existing LLM-assisted tools help with co-writing, but offer limited support for navigating this iterative, multi-directional revision process. To address this gap, we designed Spatial Balancing, an exploratory revision environment that maps rhetorical goals and revision strategies onto a two-dimensional spatial canvas for experienced science communication creators with domain expertise but lacking formal professional training. By building a design space of communication strategies and embedding them into a spatial exploratory canvas, our system treats feedback as navigational cues rather than prescriptive judgments. Our findings show that this integrated revision environment helps writers stay focused on writing goals, reason about revision as trajectories, and explore alternatives, which supports greater metacognitive control and confidence without increasing workload. This work highlights the value of spatially externalized revision environments for supporting iterative, reflective thinking during LLM-assisted writing.

Young adults often take breaks from screen-intensive work by consuming digital content on mobile phones, which undermines rest through visual fatigue and inactivity. We introduce a design framework that embeds light break activities into media content on AR smart glasses, balancing engagement and recovery, which employs three strategies: (1) seamlessly guiding users by embedding activity cues aligned with media elements; (2) transitioning to audio-centric formats to reduce visual load while sustaining immersion; and (3) structuring sessions with "rise-peak-closure"pacing for smooth transitions. In a within-subjects study (N=16) comparing passive viewing, reminder-based breaks, and non-narrative activities, InteractiveBreak instantiated from our framework seamlessly guided activities, sustained engagement, and enhanced break quality. These findings demonstrate wearable AR's potential to support restorative relaxation by transforming breaks into engaging, meaningful experiences. © 2026 the owner/author(s).

Unlike the free exploration of childhood, the demands of daily life reduce our motivation to explore our surroundings, leading to missed opportunities for informal learning. Traditional tools for knowledge acquisition are reactive, relying on user initiative and limiting their ability to uncover hidden interests. Through formative studies, we introduce AiGet, a proactive AI assistant integrated with AR smart glasses, designed to seamlessly embed informal learning into low-demand daily activities (e.g., casual walking and shopping). AiGet analyzes real-time user gaze patterns, environmental context, and user profiles, leveraging large language models to deliver personalized, context-aware knowledge with low disruption to primary tasks. In-lab evaluations and real-world testing, including continued use over multiple days, demonstrate AiGet's effectiveness in uncovering overlooked yet surprising interests, enhancing primary task enjoyment, reviving curiosity, and deepening connections with the environment. We further propose design guidelines for AI-assisted informal learning, focused on transforming everyday moments into enriching learning experiences. © 2025 Copyright held by the owner/author(s).

Optical see-through head-mounted displays (OHMDs) blend digital content with the physical world, presenting unique color management challenges. Previous literature suggests using green as the main color, but this severely limits creative freedom. To address this, we conducted an empirical study with 30 participants, evaluating 216 colors under various OHMD usage conditions. Based on the results, we propose color guidelines indicating each hue's clear and comfortable saturation and brightness ranges, along with clarity and comfort scores across hues for different devices and lighting conditions. Our color guidelines expand the usable color palette, offering designers a wider range of color options. These guidelines were used and iteratively refined through feedback in a workshop with 12 designers, integrating them into practical design workflows. The resulting comprehensive color guide provides a valuable resource for OHMD interface designers, enhancing both the aesthetic possibilities and functional effectiveness of augmented reality experiences.

While effective for recording and sharing experiences, traditional in-context writing tools are relatively passive and unintelligent, serving more like instruments rather than companions. This reduces primary task (e.g., travel) enjoyment and hinders high-quality writing. Through formative study and iterative development, we introduce PANDALens, a Proactive AI Narrative Documentation Assistant built on an Optical See-Through Head Mounted Display that supports personalized documentation in everyday activities. PANDALens observes multimodal contextual information from user behaviors and environment to confirm interests and elicit contemplation, and employs Large Language Models to transform such multimodal information into coherent narratives with significantly reduced user effort. A real-world travel scenario comparing PANDALens with a smartphone alternative confirmed its effectiveness in improving writing quality and travel enjoyment while minimizing user effort. Accordingly, we propose design guidelines for AI-assisted in-context writing, highlighting the potential of transforming them from tools to intelligent companions.

Interactions with digital devices during social settings can reduce social engagement and interrupt conversations. To overcome these drawbacks, we designed ParaGlassMenu, a semi-transparent circular menu that can be displayed around a conversation partner’s face on Optical See-Through Head-Mounted Display (OHMD) and interacted subtly using a ring mouse. We evaluated ParaGlassMenu with several alternative approaches (Smartphone, Voice assistant, and Linear OHMD menus) by manipulating Internet-of-Things (IoT) devices in a simulated conversation setting with a digital partner. Results indicated that the ParaGlassMenu offered the best overall performance in balancing social engagement and digital interaction needs in conversations. To validate these findings, we conducted a second study in a realistic conversation scenario involving commodity IoT devices. Results confirmed the utility and social acceptance of the ParaGlassMenu. Based on the results, we discuss implications for designing attention-maintaining subtle interaction techniques on OHMDs.

In this paper, we propose a straightforward method to select the parameters of the PI controllers in Field Oriented Control (FOC) scheme for Permanent Magnet Synchronous Motor (PMSM) based on geometric model reduction and structured H∞-synthesis. The main contribution of this paper is that, by recognizing the essential linear system structure of PMSM model and using mature robust control method, the six parameters for PI controllers in FOC can be computed offline without resorting to trial and error online manual tuning. In addition, we also simulate the rotor speed tracking example to demonstrate the validity of the proposed parameter selection method.

Due to a strong appealing for environment protection and energy saving, electric vehicles (EVs) receive more attention nowadays. Those equipped with permanent magnet synchronous in-wheel motors (PMSIMs) are regarded having an efficient structure that can transmit electrical energy to mechanical energy directly. To optimize vehicle performance, a new energy management strategy is proposed in this work to identify the optimal working points of the EVs analytically. The most important contribution of this work is to provide an analytical method for determining the optimal working points of the EV, which is of interest to both EV designers and users. With the proposed modeling, the coupling effects between PMSIMs performance and EV working status are analyzed using Pontryagin's Minimum Principle. To solve the mathematically hard-to-solve Hamiltonian, a numerical scanning approach is also proposed to determine the optimal working points of the EV. Simulation results are demonstrated to verify that the analytical optimal working point achieved by Pontryagin's Minimum Principle has the least energy consumption rate, compared to other cases, with the model of DC motors or non-optimal working points.

In this paper we design a linear time-invariant (LTI) two-input-two-output (TITO) controller for the Permanent Magnet Synchronous Motor (PMSM). First the nonlinear system of a PMSM is approximated using a linear system with structured uncertainties according to the PMSM geometric structures. We then design a linear controller for the approximated linear system using a standard μ-synthesis robust control method. The main contribution of this paper is that a unified LTI controller is designed for the nonlinear PMSM plant using mature modern control theory, without referring to classical PID control. Thus largely reducing the design effort. The newly designed robust controller is not only easy to calculate, it is also easy to implement and requires less sensors. By virtue of modern robust control theory, it responds fast to exogenous inputs, and robust against parameter uncertainties as well.

In recent years, hybrid energy storage system (HESS) has been studied a lot. Due to the complementary characteristics embraced by each component in the HESS, it is believed that the power supply quality can be improved. Frequently discussed HESS refers to battery-ultracapacitor hybridization, which can be promisingly used as the power supply for Electric Vehicles (EV) where a power train that drives PMSM is generally involved. In this paper, an on-line energy flow split strategy (EFSS) is proposed to timely tune the amount of energy supplements from battery and ultracapacitor respectively. Major contribution of this paper is an EFSS considering the relationship between HESS and PMSM under the influence of SVPWM (Space Vector Pulse Width Modulation) of inverter is proposed, which fits directly into real engineering applications. The proposed EFSS is synthesized with PMSM control algorithm into a TMS320 F28335 based DSP test platform to verify the effectiveness of proposed EFSS. Experiment results show that the proposed EFSS can work well with real PMSM driving system under the presence of load variations.