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.

Investigation on Control Burned of Bagasse Ash on the Properties of Bagasse Ash-Blended Mortars

Abstract: In recent years, partial replacement of cement with bagasse ash has been given attention for construction application due to its pozzolanic characteristics. Sugarcane bagasse ash and fine bagasse particles are abundant byproducts of the sugar industries and are disposed of in landfills. Our study presents the effect of burning bagasse at different temperatures (300 °C and 600 °C) on the compressive strength and physical properties of bagasse ash-blended mortars. Experimental results have revealed that bagasse produced more amorphous silica with very low carbon contents when it was burned at 600 °C/2 h. The compressive strength of mortar was improved when 5% bagasse ash replaced ordinary portland cement (OPC) at early curing ages. The addition of 10% bagasse ash cement also increased the compressive strength of mortars at 14 and 28 days of curing. However, none of the bagasse ash-blended portland pozzolana cement (PPC) mortars have shown improvement on compressive strength with the addition of bagasse ash. Characterization of bagasse ash was done using XRD, DTA-TGA, SEM, and atomic absorption spectrometry. Moreover, durability of mortars was checked by measuring water absorption and apparent porosity for bagasse ash-blended mortars.

Comparative Study of Quantum Features of Radiation Generated by Nondegenerate Down-Conversion

Abstract: A comparative study of quantum properties associated with coherent correlations between the modes of light generated by a nondegenerate parametric down-conversion process is presented. Particularly, the degree of nonclassicality that can be quantified by logarithmic negativity and quantum discord is compared, and a striking similar tendency is observed. In the same manner, a comparison of the quadrature variance, the smallest eigenvalue of the symplectic matrix and Einstein-Podolsky-Rosen (EPR) steering is made whereby a significant similarity is witnessed. The highest degree of quantum features of the radiation is in general manifested near threshold, whereas the quantifying measure related to the smallest eigenvalue of the symplectic matrix is found to capture a better degree of quantumness. Since each criterion renders only sufficient condition, it is hoped that witnessing consistent outcome across different criteria enhances the chance for experimental verification and practical application.

Biological sensor performance validation using fusion technique

Abstract: Sensors are used for providing a system with needed data considering some features of interest in the environment of system. Multi-sensor fusion would provide more accurate and reliable information. Multi-sensor fusion would be beneficial in numerous ways such as timeliness, redundancy, complementarily and so on. The main purpose of the research is to examine the biological sensor performance validation using data fusion technique. The fusion or integration of simulated sensor would minimize overall uncertainty and thus helps to maximize the accuracy. It would provide redundant data and also serve to maximize reliability in terms of sensor failure or error. The implementation would be performed in two phases such as data fusion approach and neural network approach. The code would be executed in the MATLAB. Glucose sensor and sucrose sensor were used as the biological sensor. Fusion method used is the state-vector fusion method and a Kalman filter and H-infinity based filter are implemented for enhancing the performance of data fusion algorithm. Simulate the sensor network and deploy the algorithm of data fusion and use neural network for validating the faulty of the sensor network. From the analysis, it was noticed that when compared to simulated stated sensor output, the simulated fused sensor output and target performs well. It was also observed that error rate also minimal in the simulated fused sensor. Further, Future work would be based on validating the biological and cognitive sensor performance through other fusion models.