Recurrent Neural Based Electricity Load Forecasting of G-20 Members

Forecasting the actual amount of electricity with respect to the need/demand of the load is always been a challenging task for each power plants based generating stations. Due to uncertain demand of electricity at receiving end of station causes several challenges such as: reduction in performance parameters of generating and receiving end stations, minimization in revenue, increases the jeopardize for the utility to predict the future energy need for a company etc. With this issues, the precise forecasting of load at the receiving end station is very consequential parameter to establish the impeccable balance between supply and demand chain. In this paper, the load forecasting of G-20 members have been performed utilizing the Recurrent Neural Network coupled with sliding window approach for data generation. During the experimentation we have achieved Mean Absolute Test Error of 16.2193 TWh using LSTM.

Embedded Systems and Computer Vision Techniques utilized in Spray Painting Robots: A Review

The advent of the era of machines has limited human interaction and this has increased their presence in the last decade. The requirement to increase the effectiveness, durability and reliability in the robots has also risen quite drastically too. Present paper covers the various embedded system and computer vision methodologies, techniques and innovations used in the field of spray painting robots. There have been many advancements in the sphere of painting robots utilized for high rise buildings, wall painting, road marking paintings, etc. Review focuses on image processing, computational and computer vision techniques that can be applied in the product to increase efficiency of the performance drastically. Image analysis, filtering, enhancement, object detection, edge detection methods, path and localization methods and fine tuning of parameters are being discussed in depth to use while developing such products. Dynamic system design is being deliberated by using which results in reduction of human interaction, environment sustainability and better quality of work in detail. Embedded systems involving the micro-controllers, processors, communicating devices, sensors and actuators, soft-ware to use them; is being explained for end-to-end development and enhancement of accuracy and precision in Spray Painting Robots.