Based on Gauss’ law for the electric field, new formulas were deduced, that enable for the first time the writing of an analytical formula of the built-in potential of implanted and diffused semiconductor junctions. Consequently, in this work is devised a measurement technique for the built-in potential of such junctions. Such measurement is useful because new semiconductor materials besides silicon are more and more used today, like silicon-carbide (SiC) and gallium-nitride (GaN), which have larger bandgap and junction built-in potential. Finding the built-in potential helps adjusting the computer assisted design (CAD) tools and validates the simulation of such wide-bandgap devices.
The issue of waste management in terms of environmental protection is one of the important problems facing humanity, especially in the large agglomeration areas, and in the rural area, the interests are more limited.
The present paper presents theoretical aspects regarding the implementation of an integrated waste management system in the rural area.
In this work, we present a new fuzzy second-order sliding mode controller (FSOSMC) for wind power transformation system based on a doubly-fed induction generator (DFIG) using intelligent space vector pulse width modulation (SVPWM). The proposed command strategy combines a fuzzy logic and a second order sliding mode control (SOSMC) for the DFIG command. This strategy presents attractive features such as chattering-free, compared to the conventional first and second order sliding mode techniques. The use of this method provides very satisfactory performance for the DFIG command. The effectiveness of this command strategy is proven through the simulation results.
The paper proposes the exploration, identification and development of a Java solution for extracting the sentiment related to the cryptocurrencies phenomenon, from the content of the posts of certain popular social networks.
Detecting the positive, neutral or negative character of the sentiment is adopted as a relevant method of establishing the nature of the human perception on the topical issue defined by cryptocurrencies.
Gustavo Gonçalves Coelho, Eric Henrique Moretti and João Paulo Coelho
Automation of industrial activities aims to improve the efficiency of the productive processes while reducing costs and increasing safety. In industrial laundries, detergent management is a key factor that can lead to severe economic and environmental impacts if left uncontrolled. This paper documents the solution devised for an integrated detergent control and supervision system based on Internet-of Things paradigms. This solution follows from a problem put forward by the laundry services of Santa Casa da Misericórdia de Bragança, located in Portugal, to the Polytechnic Institute of Bragança. In order to keep track of the detergent in a centralised dispensing system, a Wi-Fi based measurement system was developed which enables real-time monitoring of the chemicals level. In order to facilitate the physical installation of the developed hardware, a custom-made enclosure was designed and 3D printed. The acquired data is then sent to a database connected to a data processing web-based platform which is responsible for the analytics.
Eric Henrique Moretti, Gustavo Gonçalves Coelho and João Paulo Coelho
Development of increasingly efficient production methods is a competiveness driving factor for any company. Today, many of these improvements include the integration of technology-based solutions into processes traditionally operated by humans. In this context, the present work aims to report the controller performance of a prototype developed for semi-automatic sewing stations. This project was fostered by “Factory Play”, a Portuguese company that produces inflatable structures, under the technical supervision of the Polytechnic Institute of Bragança. At the present time, the sewing station travel speed is regulated by an embedded PID controller that has been previously tuned using classical methods. However, even if the overall performance is currently acceptable, additional experiments were made regarding the use of evolutionary based algorithms to attain a better dynamic response and flexibility. This article present the results obtained using those methods where it is possible to confirm that the use of evolutionary algorithm will simplify the design process while consistently leading to a suitable solution.
Machine-learning techniques allow to extract information from electroencephalographic (EEG) recordings of brain activity. By processing the measurement results of a publicly available EEG dataset, we were able to obtain information that could be used to train a feedforward neural network to classify two types of volunteer activities with high efficiency.
The present paper is an experimental study on the squeeze pin effect on the high pressure die cast aluminium parts, as a way of improvement of material homogenity on various and big wall thickness castings. Squeeze is used in high pressure die casting technology for optimizing homogenity of big wall thicknesses of die cast parts working as structural, mechanical and hydraulic components, made of different aluminium alloys such AlSi alloys. The objective of this research is to highlight the primary and secondary effects of squeezing on the structural homogenity of high pressure die cast aluminium parts, as well as the dependence of the effects on the squeeze pin dimensions and the operating parameters.
Soil erosion is the most important challenge of the biosphere. Soil is one of the most important and most valuable natural resources. It meets the essential needs of the world. If the soil is not well preserved, then hunger will conquer all over the globe. This article tried to identify types of erosion and provide solutions to prevent it to protect this main material by examining the effects and results.