Building materials and components are much larger and heavier than many industrial materials. Ceiling glass is a type of building material for interior finishing. The demand for larger ceiling glass has increased along with the number of high-rise buildings and an increased interest in interior design. The objective of the study is to introduce robotic technology for installing ceiling glass on construction site. Robotically installed ceiling glass is receiving special attention because of the difficulties in moving to high installation positions and handling fragile building materials. Below, we describe the design of a ceiling glass installation robot. After analyzing a target project, we establish a design concept for a proposed robot. Finally, we describe the detailed design of the robot.

Building materials and components are much larger and heavier than general industrial materials. A glass panel is a type of building material used for interior finishing. The demand for larger glass panels has increased along with the number of high-rise buildings and an increased interest in interior design. The objective of this study is to introduce robotic technology for installing a glass panel on a high ceiling. After job definition, we established a design concept for the proposed robot. Finally, we described the detailed design of the robot in a past symposium. In this paper, the control algorithm relating the human-robot cooperation to which the hardware of the integrated system is to be applied, is presented. Also, the task planning for robotized construction is applied.

Background: Several recent studies have reported that deep learning reconstruction “TrueFidelity” (TF) improves computed tomography (CT) image quality. However, no study has compared adaptive statistical repeated reconstruction (ASIR-V) using TF in pediatric cardiac CT angiography (CTA) with a low peak kilovoltage. Objective: This study aimed to determine whether ASIR-V or TF CTA image quality is superior in children with congenital heart disease (CHD). Materials and methods: Fifty children (median age, 2 months; interquartile range, 0–5 months; 28 men) with CHD who underwent CTA were enrolled between June and September 2020. Images were reconstructed using 2 ASIR-V blending factors (80% and 100% [AV-100]) and 3 TF settings (low, medium, and high [TF-H] strength levels). For the quantitative analyses, 3 objective image qualities (attenuation, noise, and signal-to-noise ratio [SNR]) were measured of the great vessels and heart chambers. The contrast-to-noise ratio (CNR) was also evaluated between the left ventricle and the dial wall. For the qualitative analyses, the degree of quantum mottle and blurring at the upper level to the first branch of the main pulmonary artery was assessed independently by 2 radiologists. Results: When the ASIR-V blending factor level and TF strength were higher, the noise was lower, and the SNR was higher. The image noise and SNR of TF-H were significantly lower and higher than those of AV-100 ( P < .01), except for noise in the right atrium and left pulmonary artery and SNR of the right ventricle. Regarding CNR, TF-H was significantly better than AV-100 ( P < .01). In addition, in the objective assessment of the degree of quantum mottle and blurring, TF-H had the best score among all examined image sets ( P < .01). Conclusion: TF-H is superior to AV-100 in terms of objective and subjective image quality. Consequently, TF-H was the best image set for cardiac CTA in children with CHD.

No abstract

No abstract