Considerable research has been performed on smart working environments in the architecture, engineering, and construction industry, with building information modeling considered as a critical element for implementing intelligent working systems. Although much software has been developed, a lack of understanding inhibits a user-centered approach to the application of building information modeling in architectural design offices. This study focuses on usability factors for the development of software and proposes a direction for the adoption of building information modeling in architectural design offices. This study adopts a persona method that focuses on user experience, starting with a survey conducted in two large domestic architectural offices. For developing the persona scenarios, this study provides a conceptual framework of usability, identifies user demands, and characterizes user experience. Four representative personas were developed for the representative types of users in smart working environments. The persona scenarios provide a basis that directly reflects user needs and experiences regarding the use of building information modeling software in architectural design offices. Two implications of the application of building information modeling are proposed based on the scenarios: a user-friendly working environment for smart workflows and a customized training program focusing on user experience for the use of building information modeling software.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9025912 | PMC |
| http://dx.doi.org/10.3390/s22082871 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
COX-2 Inhibitor Prediction With KNIME: A Codeless Automated Machine Learning-Based Virtual Screening Workflow.
J Comput Chem
January 2025
Pharmaceutical Chemistry Research Laboratory 1, Department of Pharmaceutical Engineering & Technology, Indian Institute of Technology (Banaras Hindu University), Varanasi, India.
Cyclooxygenase-2 (COX-2) is an enzyme that plays a crucial role in inflammation by converting arachidonic acid into prostaglandins. The overexpression of enzyme is associated with conditions such as cancer, arthritis, and Alzheimer's disease (AD), where it contributes to neuroinflammation. In silico virtual screening is pivotal in early-stage drug discovery; however, the absence of coding or machine learning expertise can impede the development of reliable computational models capable of accurately predicting inhibitor compounds based on their chemical structure.
View Article and Find Full Text PDFPreclinical Identification of Poorly Controlled COPD: Patients with a Single Moderate Exacerbation Matter Too.
J Clin Med
December 2024
Centro de Salud Malilla, Carrer de Malilla 52D, Quatre Carreres, 46026 Valencia, Spain.
Chronic obstructive pulmonary disease (COPD) remains a critical global health challenge, characterized by high morbidity, mortality, and healthcare costs. Current guidelines may overlook patients who present with only one moderate exacerbation or with frequent short-acting beta-agonist (SABA) use. Building on findings from the Seleida study, this research refines the criteria for poor COPD control to include these patients, aiming to improve early identification of high-risk cases in primary care.
View Article and Find Full Text PDFCharacterization of Hazelnut Trees in Open Field Through High-Resolution UAV-Based Imagery and Vegetation Indices.
Sensors (Basel)
January 2025
Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy.
The increasing demand for hazelnut kernels is favoring an upsurge in hazelnut cultivation worldwide, but ongoing climate change threatens this crop, affecting yield decreases and subject to uncontrolled pathogen and parasite attacks. Technical advances in precision agriculture are expected to support farmers to more efficiently control the physio-pathological status of crops. Here, we report a straightforward approach to monitoring hazelnut trees in an open field, using aerial multispectral pictures taken by drones.
View Article and Find Full Text PDFAttention Score-Based Multi-Vision Transformer Technique for Plant Disease Classification.
Sensors (Basel)
January 2025
Department of AI & Big Data, Honam University, Gwangju 62399, Republic of Korea.
This study proposes an advanced plant disease classification framework leveraging the Attention Score-Based Multi-Vision Transformer (Multi-ViT) model. The framework introduces a novel attention mechanism to dynamically prioritize relevant features from multiple leaf images, overcoming the limitations of single-leaf-based diagnoses. Building on the Vision Transformer (ViT) architecture, the Multi-ViT model aggregates diverse feature representations by combining outputs from multiple ViTs, each capturing unique visual patterns.
View Article and Find Full Text PDFKnowledge Distillation-Enhanced Behavior Transformer for Decision-Making of Autonomous Driving.
Sensors (Basel)
January 2025
Key Laboratory of Automotive Power Train and Electronics, Hubei University of Automotive Technology, Shiyan 442002, China.
Autonomous driving has demonstrated impressive driving capabilities, with behavior decision-making playing a crucial role as a bridge between perception and control. Imitation Learning (IL) and Reinforcement Learning (RL) have introduced innovative approaches to behavior decision-making in autonomous driving, but challenges remain. On one hand, RL's policy networks often lack sufficient reasoning ability to make optimal decisions in highly complex and stochastic environments.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!