To assist Java programming learning of novice students, we have developed the web-based Java Programming Learning Assistant System (JPLAS). It provides various exercise problems to cultivate code reading and code writing skills to support studies at various levels. The code writing problem (CWP) asks a student to write a source code to pass the given test code where the correctness is verified by running them on JUnit. Previously, we implemented the answer platform for students to solve CWP assignments with the automatic runs. However, the teacher needs to manually run them one by one to verify a lot of source codes from students. In this paper, we implement the answer code validation program that automatically verifies all the source codes for one test code and reports the number of tests that each code passed with the CSV file. For evaluations, we applied the program to a total of 999 source codes from 12-43 students for a total of 45 test codes that were assigned in the Java programming course in Okayama university, including for final examinations. The application results confirm the validity and effectiveness of the proposal.
The retina is harmed by diabetic retinopathy (DR), a consequence of diabetes. Up to, 80% of people who have had diabetes for ten or more years are affected by this type of medical issue. Where the need for diabetic retinopathy identification is greatest, there is frequently a shortage of the necessary knowledge and tools. The majority of research in the area of diabetic retinopathy has relied on manual feature extraction or disease identification. So, the goal of this research is to make a deep learning neural network that can identify the disease in all of its forms. The suggested system enables a DR classification that accounts for normal eyes, mild DR, moderate DR, severe DR, and proliferative DR, which may aid ophthalmologists in making a preliminary decision. Our accuracy rates for estimating the degree of diabetic retinopathy from an image were 90% and 92% respectively, using the pre-trained Convolutional Neural Network (CNN) VGG-16 and MobileNet-V2.
The students in vocational colleges are weak in mathematical calculation, which affects the teaching quality of Engineering Mechanics. In order to improve teaching quality, the research team propose a solution strategy combining simulation calculation and mathematical integral calculation. This article carried on the teaching practice starting from a typical problem raised by the students. The finite element model was established and simulated on a computer. The Mises stress nephogram and date were obtained by the simulation calculation, which solved the students’ doubts. These visual materials provide support for the students to understand the abstract concepts of Engineering Mechanics. However, the simulation only described the final results and the students could not get the specific calculation process from the finite element model. Subsequently, the detailed integral calculation process was sorted out by the teachers, which helped the students understand the strain accumulation of the prism. The result of integral calculation is 0.1143 mm, which is very close to the result of the simulation (0.1123 mm). The finite element analysis and calculus calculation process were sorted into the teaching materials of Engineering Mechanics. Subsequently, a teaching practice was applied to a class of 35 students. Teaching evaluation shows that teaching quality has been significantly improved. On the one hand, digital materials such as stress nephogram have the characteristics of visualization, which provides convenience for students to understand complex mechanics concepts. On the other hand, students’ interest in learning has been enhanced, and classroom interaction has increased significantly. This study provides a new way to answer complex questions in Engineering Mechanics teaching, which should be paid more attention and explored by more scholars.
With the development of technology in recent years, teachers, in educational settings, are more accessible to utilize various digital media tools in teaching procedures than ever before. Micro-learning has been referred to enhance foreign language learning and performance in the most efficient and effective method possible through short pieces of content. However, few studies investigated the effect of micro-learning on English word learning for those who are ESL learners using a specific mobile application. Therefore, this study aims to find out what factors affect the English wording learning of College students using Superstar, which is a mobile application with micro-learning. Evaluating how micro-learning promotes the capacity, motivation, and satisfaction of English word learning than the traditional learning method. Mixed methods research was used to collect data from 84 freshman in China. The results indicate that using Superstar to learn English vocabulary help to improve the capacity and motivation of college students in English word learning. Superstar as a mobile application for English word learning might be helpful for ESL learners as well.
The liver is an important organ because it produces vitamins & substances necessary for the survival of the decaying body, including iron, toxins, proteins, & carbs. It aids in vitamin and mineral metabolism, tubular muscle growth, and blood coagulation. Factors including alcohol intake, opioid painkiller usage, poor nutrition, and underlying medical disorders have all been linked to the development of liver disease. The results of a patient's blood tests and physical exam may help physicians determine risk factors for liver disease. Data mining methods may help speed up the process of identifying liver illness. When more information is utilized, the vaccination becomes more precise. This design aims to address this issue by incorporating a method of device mastery into the process of evaluating liver disease. The primary motive of this system is to apply a wide angles set of concepts to perceive healthy folks that are honestly affected by liver disease. The design of this system also aims to evaluate and contrast different bracketing algorithms according to their operational characteristics. A Python-based graphical interface for Stoner is now being development to aid clinicians in the assessment of liver issues. The user interface may be used by soothsayers and medical interpreters as a web application for liver trials.
