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.

Handwritten Amharic characters Recognition Using CNN

Abstract: Amharic has been an official language of Ethiopia since many years ago. As a consequence, there are so many handwritten documents of several types, that are written in Amharic by hand, in monasteries, libraries, museums, universities, archives and with individuals. Among them, there are documents that have been written before several years and are getting older. To preserve these documents electronically the current way of digital preservation is not sufficient. Therefore, an intelligent handwritten classifier is essential. Furthermore, we can interact with latest smart devices such as with mobile phones by writing Amharic characters by hand by integrating this Amharic character classifier with them. Because contemporary smartphones are capable of reading and recognizing inputs written by hand on their modern input devices. Amharic alphabet has about 34 families of characters and about eight members with in a family, with some exceptions. There are, a total of, 286 different characters (286 classes). For this research, I have collected 30,446 characters from about 130 different individuals. Among them 27413 are used for training and the remaining 3033 are used for testing. Convolutional Neural Network algorithm with two convolutional layers is employed to classify the aforementioned characters to 286 classes. The design is evaluated on Keras and TensorFlow frameworks. After training the system, I have got a training accuracy around 99.52% after the first epoch, which is the least of accuracies of other epochs and a testing accuracy of 99.71%, approximately. In conclusion, the result of this research can be more improved by training the system using more data and using improved Convolutional Neural Network algorithms. In addition, the system is not evaluated using many different metrices such as by changing the orientation of characters and by adding noises; even though, they are written by different individuals and different styles.

Biotechnological remediation of arsenate from aqueous solution using a novel bacterial strain: Isotherm, kinetics and thermodynamic studies.

Abstract: Arsenic is a global environmental contaminant that imposes a big health threat which requires an immediate attention to clean-up the contaminated areas. This study examined the biosorption ability of a novel Bacillus strain for the removal of arsenate (pentavalent arsenic) from aqueous solution. The optimum biosorption condition was studied as a function of biomass dosage, contact time and pH. Dubinin-Radushkevich (D-R), Freundlich, and Langmuir models were applied in describing the biosorption isotherm. The maximal biosorption capacity (92%) was obtained at 25 °C, biomass concentration 2000 mg/L at pH value of 4 and contact period of 50 min. Strain 139SI act as an admirable host to the arsenate. Thermodynamic assessment (ΔG0, ΔH0, and ΔS0) also suggested the chemisorption and feasible process of As(V) biosorption. The reuse study illustrated the highest recovery of 93% using 1 M HCl, and a decrease of 25% in recovery of As(V) ions after 10 times desorption process.

Electrotrophs and Electricigens; Key Players in Microbial Electrophysiology

Abstract: A wide range of microbes belonging to all three domains of life is known to generate electrical current and transfer electrons to anodes within a bioelectrochemical system Typically these exoelectrogens are iron-reducing bacteria (eg, Geobacter sulfurreducens) that are capable of producing high power density at moderate temperatures Under nutrient sufficient conditions, other microbes ranging from extremophiles to yeasts can also produce high current densities On the other hand, electrotrophic microbes grow on electrons derived from the cathode, but such microbes are less diverse and have uncommon traits Electrotrophs shows low current densities (well below representative exoelectrogens) and utilizes several terminal electron acceptors for cell respiration Thus, there is a vast diversity of electroactive microbes and their cultivation conditions that opens-up a new avenue for electrochemical devices particularly for H and CH production The microbial fuel cell has been considered as an eco-friendly technology to harvest electricity harvesting from a variety of carbonaceous substrates Here, microorganisms can be used as biocatalysts This chapter provides an introduction to the currently identified electricigens, their taxonomical groups, and electricity-producing abilities The mechanism of electron transfer from electricigens to electrodes is also discussed