Analytic elasticity solution of bi-modulus beams under combined loads

A unified stress function for bi-modulus beams is proposed based on its mechanic sense on the boundary of beams. Elasticity solutions of stress and displacement for bi-modulus beams under combined loads are derived. The example analysis shows that the maximum tensile stress using the same elastic modulus theory is underestimated if the tensile elastic modulus is larger than the compressive elastic modulus. Otherwise, the maximum compressive stress is underestimated. The maximum tensile stress using the material mechanics solution is underestimated when the tensile elastic modulus is larger than the compressive elastic modulus to a certain extent. The error of stress using the material mechanics theory decreases as the span-to-height ratio of beams increases, which is apparent when L/h ≤ 5. The error also varies with the distributed load patterns.

Improving Sensor-free Detection of Programming Difficulties Using Deep Learning

Programming difficulties are one of the common problems faced by software engineering students,which can lead to a rapid decline in motivation and even drop out.Probing students’programming difficulties is a crucial step in understanding their current programming situation and implementing appropriate instructional interventions.However,how to detect students’programming difficulties accurately without students’awareness remains a big challenge.Address the issues above;this paper adopts a sensor-free difficulties detecting method based on a deep neural network which employs a recurrent neural network(RNN)model and uses the sequential timing data from programming behaviour.The method can detect students’programming difficulties in real-time with 93%accuracy without interference in the programming process.In the long term,this method is the first step for establishing an automated intelligent programming environment.At the same time,it can assist teachers in noticing the difficulties that students encounter.Then,teachers can adjust their teaching plans and provide manual tutoring intervention more quickly.

Network Function Virtualization Technology:Progress and Standardization

Network innovation and business transformation are both necessary for telecom operators to adapt to new situations, but operators face challenges in terms of network bearer complexity, business centralization, and IT/CT integration. Network function virtualization （NFV） may inspire new development ideas, but many doubts still exist within industry, especially about how to introduce NFV into an operator＇ s network. This article describes the latest progress in NFV standardization, NFV requirements and hot technology issues, and typical NFV applications in an operator networks.