The design of and training for complex systems requires in-depth understanding of task demands imposed on users. In this project, we used the knowledge engineering approach (Bowles et al., 2004) to assess the task of mowing in a citrus grove. Knowledge engineering is divided into four phases: (1) Establish goals. We defined specific goals based on the stakeholders involved. The main goal was to identify operator demands to support improvement of the system. (2) Create a working model of the system. We reviewed product literature, analyzed the system, and conducted expert interviews. (3) Extract knowledge. We interviewed tractor operators to understand their knowledge base. (4) Structure knowledge. We analyzed and organized operator knowledge to inform project goals. We categorized the information and developed diagrams to display the knowledge effectively. This project illustrates the benefits of knowledge engineering as a qualitative research method to inform technology design and training.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.apergo.2012.04.002 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Debus-Radziszewski Reaction Inspired In Situ "One-Pot" Approach to Construct Luminescent Zirconium-Organic Frameworks.
Inorg Chem
January 2025
Hoffmann Institute of Advanced Materials, Shenzhen Polytechnic University, 7098 Liuxian Blvd, Nanshan District, Shenzhen 518055, P. R. China.
Metal-organic frameworks have received extensive development in the past three decades, which are generally constructed via the reaction between inorganic building units and commercially available or presynthesized organic linkers. However, the presynthesis of organic linkers is usually time-consuming and unsustainable due to multiple-step separation and purification. Therefore, methodology development of a new strategy is fundamentally important for the construction and further exploration of the applications of MOFs.
View Article and Find Full Text PDFThe impact of COVID-19 pre-university education on first-grade medical students. A performance study of students of a Department of Histology.
Anat Sci Educ
January 2025
Tissue Engineering Group, Department of Histology, Medical School, University of Granada, Granada, Spain.
The recent coronavirus disease (COVID-19) forced pre-university professionals to modify the educational system. This work aimed to determine the effects of pandemic situation on students' access to medical studies by comparing the performance of medical students. We evaluated the performance of students enrolled in a subject taught in the first semester of the medical curriculum in two pre-pandemic academic years (PRE), two post-pandemic years (POST), and an intermediate year (INT) using the results of a final multiple-choice exam.
View Article and Find Full Text PDFCOX-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 PDFMunsell Soil Colour Prediction from the Soil and Soil Colour Book Using Patching Method and Deep Learning Techniques.
Sensors (Basel)
January 2025
School of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW 2795, Australia.
Soil colour is a key indicator of soil health and the associated properties. In agriculture, soil colour provides farmers and advises with a visual guide to interpret soil functions and performance. Munsell colour charts have been used to determine soil colour for many years, but the process is fallible, as it depends on the user's perception.
View Article and Find Full Text PDFLeveraging Segment Anything Model (SAM) for Weld Defect Detection in Industrial Ultrasonic B-Scan Images.
Sensors (Basel)
January 2025
Phillip M. Drayer Electrical Engineering Department, Lamar University, Beaumont, TX 77705, USA.
Automated ultrasonic testing (AUT) is a critical tool for infrastructure evaluation in industries such as oil and gas, and, while skilled operators manually analyze complex AUT data, artificial intelligence (AI)-based methods show promise for automating interpretation. However, improving the reliability and effectiveness of these methods remains a significant challenge. This study employs the Segment Anything Model (SAM), a vision foundation model, to design an AI-assisted tool for weld defect detection in real-world ultrasonic B-scan images.
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!