Adama University

About: Adama University is a education organization based out in Nazrēt, Ethiopia. It is known for research contribution in the topics: Population & Adsorption. The organization has 840 authors who have published 1010 publications receiving 5547 citations. The organization is also known as: Adama Science and Technology University & ቴክኖሎጂ ዩኒቨርሲቲ, አዳማ ሳይንስና ቴክኖሎጂ ዩኒቨርሲቲ.

Cascaded Hybrid Device Multilevel Converters for Wind Mill Applications

Abstract: In recent years Multilevel Converter (MLC) plays a vital role in wind power genration. In this paper, Shifted Carrier - Pulse Width Modulation (SC-PWM) based hybrid device multilevel converter configuration for 5 MW wind mill are proposed. A five level cascaded hybrid device MLC is developed and the simulations are performed using MATLAB/Simulink. The simulation results are offered and their performances are analyzed by implementing FPGA SPARTAN-3 processor. The proposed MLC reduces the THD and increases the output voltage.

Effect of spacer on size dependent plasmonic properties of triple layered spherical core-shell nanostructure

Abstract: In this paper, the plasmonic property of triple layered ZnO@M@Au (M = spacer) spherical core-shell nanostructures embedded in a dielectrics host medium is investigated by varying core size, spacer thickness, shell thickness and dielectrics function of the host medium within the framework of the qausi-static approximation method. The absorption coefficient of ZnO@M@Au spherical triple layered core-shell nanostructures is effectively studied by optimizing the parameters with range of nano-inclusion size mainly in between 18 and 23 nm. In this triple layered core-shell nanostructure two plasonic resonances are found associated with spacer@Au and Au@medium interfaces. The tunability of the plasmon resonances of the composite systems enables it to exhibit very interesting material properties in a variety of applications extending from near-UV to near-infrared spectral region.

Tree-Based Modeling Techniques

Abstract: Tree-based learning techniques are considered to be one of the best and most used supervised learning methods. Tree-based methods empower predictive models with high accuracy, stability, and ease of interpretation. Unlike linear models, they map non-linear relationships pretty well. These methods are adaptable at solving any kind of problem at hand (classification or regression). Methods like decision trees, random forest, gradient boosting are being widely used in all kinds of machine learning and data science problems. Hence, for every data analyst, it is important to learn these algorithms and use them for modeling. This chapter guide the learner to learn tree-based modeling techniques from scratch.

Nanotechnical Production and Optimization of Biofuel (Biodiesel) from an Edible Seed Oil (Palm-Olein)

Abstract: The synthesized calcium oxide nanoparticles of 24 nm size from domestic chicken eggshell was used for production of liquid fuel (biodiesel) to test its catalytic behavior, whereas the yield of liquid fuel was also ascertained and it shows varying percentage yields base on different conditions used for the production. The highest yield was found to be 80% at catalyst concentration of 1.75 ww % and temperature of 60°C, followed by 69% yield at catalyst concentration of 0.5 and temperature of 60°C, whereas the lowest yield was found to be 58% which was found to be at the exact catalyst concentration of 0.5 and temperature of 60°C.

Assimilation of IoT sensors for Data Visualization in a Smart Campus Environment

Abstract: Recently, various indoor based sensors that were formerly separated from the digital world, are now intertwined with it. The data visualization may aid in the comprehension of large amounts of information. Building on current server-based models, this study intends to display real environmental data acquired by IoT agents in the interior environment. Sensors attached to Arduino microcontrollers are used to collect environmental data for the smart campus environment, including air temperature, light intensity, and humidity. This proposed framework uses the system's server and stores sensor readings, which are subsequently shown in real time on the server platform and in the environment application. However, most current IoT installations do not make use of the enhanced digital representations of the server and its graphical display capabilities in order to improve interior safety and comfort conditions. The storage of such real-time data in a standard and organized way is still being examined even though sensor data integration with storing capacity server-based models has been studied in academics.