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This paper presents an object attitude estimation method using a 2D object image for a Laser Beam Control Research Testbed (LBCRT). Motivated by emerging Deep Learning (DL) techniques, a DL model that can estimate the attitude of a rotating object represented by Euler angles is developed. Instead of synthetic data for training and validation of the model, customized data is experimentally created using the laboratory testbed developed at the Naval Postgraduate School. The data consists of Short Wave Infra-Red (SWIR) images of a 3D-printed Unmanned Aerial Vehicle (UAV) model with varying attitudes and associated Euler angle labels. In the testbed, the estimated attitude is used to aim a laser beam to a specific point of the rotating model UAV object. The attitude estimation model is trained with 1684 UAV images and validated with 421 UAV images not used in the model training. The validation results show the Root-Mean-Square (RMS) angle estimation errors of 6.51 degrees in pitch, 2.74 degrees in roll, and 2.51 degrees in yaw. The Extended Kalman Filter (EKF) is also integrated to show the reduced RMS estimation errors of 1.36 degrees in pitch, 1.20 degrees in roll, and 1.52 degrees in yaw.

Multiplexed bead assays for solution‐phase biosensing often encounter cross‐over reactions during signal amplification steps, leading to unwanted false positive and high background signals. Current solutions involve complex custom‐designed and costly equipment, limiting their application in simple laboratory setup. In this study, we introduce a straightforward protocol to adapt a multiplexed single‐bead assay to standard fluorescence imaging plates, enabling the simultaneous analysis of thousands of reactions per plate. This approach focuses on the design and synthesis of bright fluorescent and magnetic microspheres (MagSiGlow) with multiple fluorescent wavelengths serving as unique detection markers. The imaging‐based, single‐bead assay, combined with a scripted algorithm, allows the detection, segmentation, and co‐localization on average of 7500 microspheres per field of view across five imaging channels in less than one second. We demonstrate the effectiveness of this method with remarkable sensitivity at low protein detection limits (100 pg/mL). This technique showed over 85 % reduction in signal cross‐over to the solution‐based method after the concurrent detection of tumor‐associated protein biomarkers. This approach holds the promise of substantially enhancing high throughput biosensing for multiple targets, seamlessly integrating with rapid image analysis algorithms. [ABSTRACT FROM AUTHOR]

Agile project management pursues repetitive and continuous management through an empirical process control method considering the complexity of the project. This study aimed to propose a collaborative Building Information Modeling (BIM)-based work process, focusing on construction coordination tasks among participants during the construction phase of a project. The theoretical framework chosen for this endeavor was the Scrum framework, selected after analyzing previous research to align with the specific characteristics of construction coordination. Using the Scrum framework as a foundation, the study employed the exCPM methodology to model the collaborative BIM-based construction coordination progress. To validate the model, it underwent a transformation into a Petri-Nets model through the marked graph building block (MGBB) along with established rules for model conversion. The converted model was then subjected to validation through reachability tree analysis. The findings of this study hold applicability to diverse collaboration processes that leverage BIM in the construction industry. [ABSTRACT FROM AUTHOR]

The development of smart cities has led to transforming modern city operations by applying emerging technologies from the fourth industrial revolution such as the Internet of Things, BIM and machine learning. To prepare for the future development of cities, it is necessary to investigate the current status of city development, research topics and the direction toward future cities. In this study, a systematic literature review was conducted following the combination of literature review guides by Kitchenham and the PRISMA statement. The review identified 141 peer-reviewed academic papers from web-based archives, such as Web of Science and SCOPUS, that were categorized into five topics related to smart cities and urban areas. The technologies applied in the research were analyzed to determine the direction future cities should take based on current smart cities and emerging technologies that will shape individuals' daily lives. However, it was discovered that research papers on critical areas, such as mobility and management, were lacking compared to those on building design and urban planning. This paper concludes with an example of a future urban area that has been transformed due to adoption of future mobility technology to address the shortcomings of the reviewed literature on building and urban environments. [ABSTRACT FROM AUTHOR]