Real-Time Power Electronics Remote Wiring and Measurement Laboratory (PermLAB) Using 3-D Matrix Switching Algorithms

Asumadu, Johnson A.,Tanner, Ralph,Ogunley, Hakeem The Korean Institute of Power Electronics 2010 JOURNAL OF POWER ELECTRONICS Vol.10 No.6

This paper presents a new architecture, called "Power Electronics Remote Wiring and Measurement Laboratory (PermLAB)", that translates a common gateway interface (CGI) string from a remote web user to a web server connected to a 3-dimension switching matrix board, can be used to switch on and off, and to control a cluster of instruments and components. PermLAB addresses real-time connection, switching, and data acquisition over the Internet instead of using simulated data. A software procedure uses a signature system to identify each instrument and component in a complex system. The Web-server application is developed in HTML, JavaScript and Java, and in C language for the CGI interface, which resides in a controller portion of LabVIEW. The LabVIEW software fully integrates the Web sever, LabVIEW data acquisition boards and controllers, and the 3-dimensional switching matrix board. The paper will analyze a half-wave rectifier (AC - DC converter) circuit connected over the Internet using the PermLAB. PermLAB allows students to obtain real data by real-time wiring of real circuits in the laboratory using a "virtual breadboard" on the Web. The software for the Web-based 3-dimensional system is flexible, portable, can be integrated into many laboratory applications or expanded, and easily accessible worldwide.

The relationship between carbon dioxide, crop and food production index in Ghana

Samuel Asumadu Sarkodie,Phebe Asantewaa Owusu 대한환경공학회 2017 Environmental Engineering Research Vol.22 No.2

The study estimated the relationship between carbon dioxide, crop and livestock production index in Ghana: Estimating the long-run elasticities and variance decomposition by employing a time series data spanning from 1960-2013 using both fit regression and ARDL models. There was evidence of a long-run equilibrium relationship between carbon dioxide emissions, crop production index and livestock production index. Evidence from the study shows that a 1% increase in crop production index will increase carbon dioxide emissions by 0.52%, while a 1% increase in livestock production index will increase carbon dioxide emissions by 0.81% in the long-run. There was evidence of a bidirectional causality between a crop production index and carbon dioxide emissions and a unidirectional causality exists from livestock production index to carbon dioxide emissions. Evidence from the variance decomposition shows that 37% of future fluctuations in carbon dioxide emissions are due to shocks in the crop production index while 18% of future fluctuations in carbon dioxide emissions are due to shocks in the livestock production index. Efforts towards reducing pre-production, production, transportation, processing and post-harvest losses are essential to reducing food wastage which affects Ghana’s carbon footprint.

Carbon dioxide emissions, GDP per capita, industrialization and population

Samuel Asumadu-Sarkodie,Phebe Asantewaa Owusu 대한환경공학회 2017 Environmental Engineering Research Vol.22 No.1

The study makes an attempt to investigate the causal nexus between carbon dioxide emissions, GDP per capita, industrialization and population with an evidence from Rwanda by employing a time series data spanning from 1965 to 2011 using the autoregressive distributed lag model. Evidence from the study shows that carbon dioxide emissions, GDP per capita, industrialization and population are co-integrated and have a long-run equilibrium relationship. Evidence from the Granger-causality shows a unidirectional causality running from industrialization to GDP per capita, population to carbon dioxide emissions, population to GDP per capita and population to industrialization. Evidence from the long-run elasticities has policy implications for Rwanda; a 1% increase in GDP per capita will decrease carbon dioxide emissions by 1.45%, while a 1% increase in industrialization will increase carbon dioxide emissions by 1.64% in the long-run. Increasing economic growth in Rwanda will therefore reduce environmental pollution in the long-run which appears to support the validity of the environmental Kuznets curve hypothesis. However, industrialization leads to more emissions of carbon dioxide, which reduces environment, health and air quality. It is noteworthy that the Rwandan Government promotes sustainable industrialization, which improves the use of clean and environmentally sound raw materials, industrial process and technologies.

Real-Time Power Electronics Remote Wiring and Measurement Laboratory (PermLAB) Using 3-D Matrix Switching Algorithms

Johnson A. Asumadu,Ralph Tanner,Hakeem Ogunleye 전력전자학회 2010 JOURNAL OF POWER ELECTRONICS Vol.10 No.6

This paper presents a new architecture, called ”Power Electronics Remote Wiring and Measurement Laboratory (PermLAB)”, that translates a common gateway interface (CGI) string from a remote web user to a web server connected to a 3-dimension switching matrix board, can be used to switch on and off, and to control a cluster of instruments and components. PermLAB addresses real-time connection, switching, and data acquisition over the Internet instead of using simulated data. A software procedure uses a signature system to identify each instrument and component in a complex system. The Web-server application is developed in HTML, JavaScript and Java, and in C language for the CGI interface, which resides in a controller portion of LabVIEW. The LabVIEW software fully integrates the Web sever, LabVIEW data acquisition boards and controllers, and the 3-dimensional switching matrix board. The paper will analyze a half-wave rectifier (AC ? DC converter) circuit connected over the Internet using the PermLAB. PermLAB allows students to obtain real data by real-time wiring of real circuits in the laboratory using a “virtual breadboard” on the Web. The software for the Web-based 3-dimensional system is flexible, portable, can be integrated into many laboratory applications or expanded, and easily accessible worldwide.

Is there a causal effect between agricultural production and carbon dioxide emissions in Ghana?

Phebe Asantewaa Owusu,Samuel Asumadu-Sarkodie 대한환경공학회 2017 Environmental Engineering Research Vol.22 No.1

According to FAO, “agricultural sectors are particularly exposed to the effects of climate change and increases climate variability”. As a result, the study makes an attempt to answer the question: Is there a causal effect between agricultural production and carbon dioxide emissions in Ghana? By employing a time series data spanning from 1960 to 2015 using the Autoregressive Distributed Lag method. There was evidence of a long-run equilibrium relationship running from copra production, corn production, green coffee production, milled rice production, millet production, palm kernel production and sorghum production to carbon dioxide emissions. The short-run equilibrium relationship shows that, a 1% increase in copra and green coffee production will increase carbon dioxide emissions by 0.22% and 0.03%, a 1% increase in millet and sorghum production will decrease carbon dioxide emissions by 0.13% and 0.11% in the short-run while a 31% of future fluctuations in carbon dioxide emissions are due to shocks in corn production. There was bidirectional causality between milled rice production and carbon dioxide emissions, millet production and carbon dioxide emissions and, sorghum production and carbon dioxide emissions; and a unidirectional causality running from corn production to carbon dioxide emissions and carbon dioxide emissions to palm kernel production.

Radial Basis Function Neural Networks (RBFNN) and p-q Power Theory Based Harmonic Identification in Converter Waveforms

Almaita, Eyad K.,Asumadu, Johnson A. The Korean Institute of Power Electronics 2011 JOURNAL OF POWER ELECTRONICS Vol.11 No.6

In this paper, two radial basis function neural networks (RBFNNs) are used to dynamically identify harmonics content in converter waveforms based on the p-q (real power-imaginary power) theory. The converter waveforms are analyzed and the types of harmonic content are identified over a wide operating range. Constant power and sinusoidal current compensation strategies are investigated in this paper. The RBFNN filtering training algorithm is based on a systematic and computationally efficient training method called the hybrid learning method. In this new methodology, the RBFNN is combined with the p-q theory to extract the harmonics content in converter waveforms. The small size and the robustness of the resulting network models reflect the effectiveness of the algorithm. The analysis is verified using MATLAB simulations.

Radial Basis Function Neural Networks (RBFNN) and p-q Power Theory Based Harmonic Identification in Converter Waveforms

Eyad K. Almaita,Johnson A. Asumadu 전력전자학회 2011 JOURNAL OF POWER ELECTRONICS Vol.11 No.6

In this paper, two radial basis function neural networks (RBFNNs) are used to dynamically identify harmonics content in converter waveforms based on the p-q (real power-imaginary power) theory. The converter waveforms are analyzed and the types of harmonic content are identified over a wide operating range. Constant power and sinusoidal current compensation strategies are investigated in this paper. The RBFNN filtering training algorithm is based on a systematic and computationally efficient training method called the hybrid learning method. In this new methodology, the RBFNN is combined with the p-q theory to extract the harmonics content in converter waveforms. The small size and the robustness of the resulting network models reflect the effectiveness of the algorithm. The analysis is verified using MATLAB simulations.