Assessing ChatGPT's Educational Capabilities and Application Potential

Purpose:ChatGPT is a generative artificial intelligence(Al)technology that can solve multiple complex tasks.ChatGPT-4 can facilitate educational empowerment in China through technology to understand and generate Chinese text.Although ChatGPT's benefits have been widely discussed,its educational capabilities have not been systematically assessed.This study provides evidence of and insights into the educational applications of Al tools in China.Design/Approach/Methods:This study uses various tests to systematically assess the latest iteration of the Al chatbot ChatGPT-4,including the Watson-Glaser Critical Thinking Appraisal(WGCTA),Five Core Competencies Questionnaire,and written test of China's 2022 National Teacher Certificate Examination(NTCE).Findings:The WGCTA results suggest that ChatGPT requires strong critical thinking.Compared with the other four competencies,the tool showed a lower aptitude for creativity.Regarding its educational applications,ChatGPT performed well on the 2022 NTCE written test.As technology enhances,ChatGPT and similar Al tools have potential applications in China for lesson planning,student self-learning,classroom interaction,and checking assignments.OriginalityNalue:This study systematically tested ChatGPT at a logical level and assessed its core competencies and educational applications.The study innovatively used 2022 NTCE data to test ChatGPT,with results providing support for the application of generative Al in future curricula and instruction in China.

Modeling and Assessing a New Warship Maintenance System

The authors developed a prototype of a warship maintenance system. The process started by defining the maintenance requirements of warship equipment. Next, a planning scheme was development for a maintenance network. An optimization target for the plan and indexes for assessment were established. Based on the above work, a simulation model was proposed with two layers: a base and a workshop. Dispatching rules were then formulated for the simulation. Experimental results proved the validity of the model and the dispatching algorithm. It was found that the model can solve the capacity evaluation problem for maintenance systems and provides a scientific basis for decision-maker to make decisions regarding equipment maintenance.

Concept and evaluation method of equipment system of systems contribution rate

To scientifically evaluate the equipment system of systems(SoS)contribution rate,a contribution rate calculation method based on a structural equation model(SEM)is proposed in this paper.The connotation and evaluation process of the equipment SoS contribution rate were redefined and standardized.To solve the existing problems in the application of the original contribution rate formula,a modified contribution rate calculation formula is proposed.Finally,the contribution rate evaluation index was divided into latent and explicit variables.The measurement and structural equations in the SEM were used to calculate and analyze the latent variables.The simulation results show that the number of defense lines of air defense weapon equipment has a greater impact on the linear configuration than the group configuration.When the number of K-type air defense weapons is sufficient,the two-layer linear configuration should be adopted with 20 air defense weapon systems.When the number of K-type air defense weapons is insufficient,the single-layer group configuration should be adopted with 12 air defense weapon systems.

Assessment of the capability of CMIP6 global climate models to simulate Arctic cyclones

Arctic cyclones are one of the important synoptic-scale systems that affect weather variability over the Arctic and can cause intense weather phenomena and disasters.Thus,research on the assessment of the climate characteristics,activity laws,and variability trends of Arctic cyclones using climate models has practical significance.On the basis of the fifth-generation European Center for Medium-Range Weather Forecasts reanalysis(ERA5)data,the spatiotemporal variations of Arctic cyclones during 1981–2014 are analyzed by detecting and tracking cyclones using the Lagrangian method.Then,the simulation results of 14 global climate models from the Coupled Model Intercomparison Project Phase 6(CMIP5)are compared with the results of ERA5.Both the individual models and their ensemble mean can simulate the spatial distribution of the density of cyclone tracks with reasonable capability,the correlation coefficients of track density are approximately 0.6.Furthermore,in boreal winter,the Atlantic zonal negative bias of track density is stronger than that in summer.By contrast,in boreal summer,the negative bias over the Arctic Ocean region is stronger than that in winter.Moreover,the simulations of density-field-related variables(i.e.,cyclolysis,cyclogenesis,track,and lowest center pressure densities)of Arctic cyclones are generally better in winter than in summer,and the models can simulate well that the number of external Arctic cyclones entering the Arctic region from the midlatitudes is more than the internal Arctic cyclones generated inside the Arctic region(60°‒90°N).Furthermore,we show that the capability of models to capture Arctic cyclones with a short lifespan(<3 d)is somewhat poor.Except for the simulation of the minimum pressure of Arctic cyclones,the performance of high-resolution models is better than that of low-resolution models.The simulation of Arctic cyclone radius is poor among all of the variables related to Arctic cyclones,and the observed trends of intensities are not well simulated.In general,the simulation of location-field-related variables(i.e.,intensity,radius,deepening rate,and center pressure)of Arctic cyclones is better in winter than in summer.