In this paper, a 4-bit digital step attenuator using 0.25 μm GaN HEMT technology for wideband radar systems is presented. A switched-path attenuator topology with resistive T-type attenuators and double-pole double-throw (DPDT) switches was used to achieve both low insertion loss and phase/amplitude error. The measured insertion loss of the reference state is 2.8–8.3 dB at DC-12 GHz. The input and output return loss are less than 12 dB at DC-12 GHz. An attenuation coverage of 30 dB with a least significant bit of 2 dB was achieved at DC-12 GHz. A root mean square (RMS) amplitude error of 1 dB and a phase error of 8.5° were achieved, respectively. The attenuator chip size is 2.45 mm × 1.75 mm including pads. To the best of the authors’ knowledge, this is the first demonstration of a GaN-based digital step attenuator.

Modern people can use navigation on the outside to save time and get to the destination well. Likewise, in order to find out more information about a destination building, such a system is increasingly needed both in front of the computer (on-line) of the house and after reaching the destination in the building (off-line). Accordingly, we employ Building Information System (BIS) as a system that provide users with content related to a building like BIO and BIM. The Building Information Online system (BIO) is an interactive map application designed to assist customers in finding parcels and building on a map online. The Building Information Modeling (BIM) allows nD information to be visualized simultaneously by architects, engineers and constructors to gain a synchronized understanding viewing from different perspectives. Inspired by above researches, we implement a service that provides online and offline Virtual Reality (VR) and Augmented Reality (AR) content for a building. This system can provide users outside the building with information within the building via devices with VR and AR support regardless of space restrictions. The system is designed to operate across scenarios requiring offline, online, offline-online collaboration, etc., and the corresponding experiments are carried out.

This paper presents LiftEqui, a framework that coordinates a follower-only prismatic lift shared by two serial manipulators in leader–follower bimanual teleoperation. Upon bilateral detection, LiftEqui freezes the robot state and utilizes a re-linearized compensation quadratic program (QP) to predict both arm postures across candidate heights, which are screened by joint, singularity, clearance, and residual guards. Height evidence is supplied by kinematic risk (K) and task height (G), while effort utilization (I) reweights arm protection; a smooth minimax objective then selects a single lift target without requiring replanning. The proposed framework was evaluated across 540 grasp-and-place trials. In conflicting scenarios where one arm preferred raising the lift and the other preferred lowering it, worst-arm arbitration (with effort priority disabled) significantly reduced the median post-lift worst-arm cost to 0.417, outperforming mean aggregation (0.500), task-height tracking (0.491), and manipulability maximization (0.527) ($p<0.001$, Holm-adjusted). Conversely, when both arms shared the same directional preference, the performance did not differ statistically from mean aggregation or task-height tracking. Under 1.0 and 1.5 kg loads, enabling the effort priority shifted the selected height toward the loaded arm in 69 out of 79 blocks where a height transition occurred. This priority effectively decreased the loaded-arm cost from 0.300 to 0.241, while inherently increasing both the unloaded-arm and worst-arm costs. Finally, in a separate per-arm sweep, executing the predicted compensation constrained the measured hand drift to within 20 mm across all 48 runs, achieving a median planning time of 1.59 s.