Deaf and hard-of-hearing (DHH) individuals encounter difficulties when engaged in group conversations with hearing individuals, due to factors such as simultaneous utterances from multiple speakers and speakers whom may be potentially out of view. We interviewed and co-designed with eight DHH participants to address the following challenges: 1) associating utterances with speakers, 2) ordering utterances from different speakers, 3) displaying optimal content length, and 4) visualizing utterances from out-of-view speakers. We evaluated multiple designs for each of the four challenges through a user study with twelve DHH participants. Our study results showed that participants significantly preferred speechbubble visualizations over traditional captions. These design preferences guided our development of SpeechBubbles, a real-time speech recognition interface prototype on an augmented reality head-mounted display. From our evaluations, we further demonstrated that DHH participants preferred our prototype over traditional captions for group conversations.

Drones offer camera angles that are not possible with traditional cameras and are becoming increasingly popular for videography. However, flying a drone and controlling its camera simultaneously requires manipulating 5-6 degrees of freedom (DOF) that needs significant training. We present ARPilot, a direct-manipulation interface that lets users plan an aerial video by physically moving their mobile devices around a miniature 3D model of the scene, shown via Augmented Reality (AR). The mobile devices act as the viewfinder, making them intuitive to explore and frame the shots. We leveraged AR technology to explore three 6DOF video-shooting interfaces on mobile devices: AR keyframe, AR continuous, and AR hybrid, and compared against a traditional touch interface in a user study. The results show that AR hybrid is the most preferred by the participants and expends the least effort among all the techniques, while the users' feedback suggests that AR continuous empowers more creative shots. We discuss several distinct usage patterns and report insights for further design.

Electric current and voltage are fundamental to learning, understanding, and debugging circuits. Although both can be measured using tools such as multimeters and oscilloscopes, electric current is much more difficult to measure because users have to unplug parts of a circuit and then insert the measuring tools in serial. Furthermore, users need to restore the circuits back to its original state after measurements have been taken. In practice, this cumbersome process poses a formidable barrier to knowing how current flows throughout a circuit. We present CurrentViz, a system that can sense and visualize the electric current flowing through a circuit, which helps users quickly understand otherwise invisible circuit behavior. It supports fully automatic, ubiquitous, and real-time collection of amperage information of breadboarded circuits. It also supports visualization of the amperage data on a circuit schematic to provide an intuitive view into the current state of a circuit.

The rise of Maker communities and open-source electronic prototyping platforms have made electronic circuit projects increasingly popular around the world. Although there are software tools that support the debugging and sharing of circuits, they require users to manually create the virtual circuits in software, which can be time-consuming and error-prone. We present CircuitSense, a system that automatically recognizes the wires and electronic components placed on breadboards. It uses a combination of passive sensing and active probing to detect and generate the corresponding circuit representation in software in real-time. CircuitSense bridges the gap between the physical and virtual representations of circuits. It enables users to interactively construct and experiment with physical circuits while gaining the benefits of using software tools. It also dramatically simplifies the sharing of circuit designs with online communities.

This paper presents a cost-effective offset cancellation structure for liquid crystal display (LCD) source driver. The proposed structure eliminates the offset voltage by three switches and a capacitor. It samples the offset and reference voltages, and cancels it out from the data voltage. The output buffer is also modified, so the proposed circuit has rail-to-rail input and output range using only 19 transistors. The whole circuits are designed using standard library by 0.18-μm process. It exhibits average offset voltage of 1.85 mV and maximum difference of 39.6 μV by Monte Carlo simulation.