• Journal of Ocean Engineering and Technology
• /
• v.24 no.2
• /
• pp.74-81
• /
• 2010

Ship STEP is the international standard for the exchange of ship modeling data between heterogeneous systems. It is expected that STEP AP218 can be used for seamless data exchange between various CAD/CAM/CAE systems used in the shipbuilding design process. Although the conformance assessment for standards would maximize the performance and confidence about data exchanges, most research has been directed toward interoperability testing. ISO SC4/TC184 only provides the method for conformance testing, and it can be used with test cases on application protocols. Even though standards have been defined for conformance assessment and testing, there is no organization or association. CAD vendors have focused on interoperability testing for evaluation of the performance of their systems. In this paper, the conformance testing criteria for AP218 have been developed with abstract test cases of ship structures. The requested STEP translator was also reviewed with a developed item pool of testing criteria. The criteria methodology would be a guideline for the development of translators and interfaces. The item pool method of testing criteria for conformance assessment would increase performance and efficiency of data translators for Ship STEP and other standards.

• Journal of Korea Society of Industrial Information Systems
• /
• v.27 no.2
• /
• pp.11-24
• /
• 2022

For the questions asked for LMS-based online evaluation the professor directly set exam questions, or use the automatic question-taking method according to the level of difficulty using the question bank divided by category. Among them, it is important to manage the difficulty of questions in an objective and efficient way, above all, in the automatic question-taking method according to difficulty. Because the questions presented to the evaluators may be different. In this paper, we propose an difficulty re-adjustment algorithm that considers not only the correct rate of a problem but also the time taken to solve the problem. For this, a logistic regression classification algorithm was used of machine learning, and a reference threshold was set based on the predicted probability value of the learning model and used to readjust the difficulty of each item. As a result, it was confirmed that there were many changes in the difficulty of each item that depended only on the existing correct rate. Also, as a result of performing group evaluation using the adjustment difficulty problem, it was confirmed that the average score improved in most groups compared to the difficulty problem based on the percentage of correct answers.