Sequence Graphics to Impart Drawing Skills in an Upper Extremity Anatomy Course

Background: Sequence graphics could be used to address the lacunae of drawing skill development in medical undergraduates. Objectives: The present study aimed to use sequence graphics to evaluate medical undergraduates in terms of drawing moderately complex diagrams. Methods: This pilot study was conducted on six medical students, and four moderately complex diagrams were evaluated regarding the usefulness of sequence graphics. Core and accessory components were identified before asking the students to draw the diagram. In a conventional drawing exercise, the students were asked to draw four diagrams consecutively during the dissection hour. On the next day, videos of sequence graphics were projected on the screen, and the students were asked to draw the diagrams simultaneously. Results: While using the conventional drawing method, the students took significantly more time to complete the diagram, the outcomes were not uniform, and several missing core and accessory components were detected. Using sequence graphics, all the students traced the diagrams in tandem with the projected videos. The videos would be paused and replayed an average of six times each; the mean duration of the videos was 95 seconds. The students started and ended the drawing at the same time, and immediate feedback revealed that they all agreed that sequence graphics could impart better drawing skills, thereby leading to the ease of drawing the diagrams. Conclusions: According to the results, sequence graphics resulted in uniform, centered, labelled, large diagrams with defined core and accessory components drawn in lesser time compared to conventional drawing.

Application of the Improved Grey Model in Power Load Forecasting

This paper presents an improved grey model used in power load forecasting. In order to overcome the limitation of the traditional grey model GM(1,1), vector θ is introduced to modify the calculating formula for background sequence value in grey model and build a more adaptable model. Using artificial fish school algorithm can solve the value of vector θ . It reflects that the improved model has higher accuracy of load forecasting and has wider application by cases analysis.