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Institution

Adama University

EducationNazrēt, Ethiopia
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.


Papers
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Proceedings ArticleDOI
01 Dec 2017
TL;DR: In this article, the optimal placement of EV aggregator in power distribution network is proposed using Worldwide Interoperability for Microwave Access (WiMAX) or 802.16 protocol.
Abstract: Vehicle to Grid (V2G) is a viable solution to meet the grid requirements with present developments in electric vehicle (EV) technology and power grid. In this paper wireless access infrastructure for optimal placement of EV aggregator in power distribution network is proposed using Worldwide Interoperability for Microwave Access (WiMAX) or 802.16 protocol. The load flow studies were carried out for IEEE 14 bus system and the physical layer of WiMAX protocol was modeled and simulated using MATLAB/SIMULINK. The results demonstrate that timely placement of GEV aggregator will result in substantial reduction of active power loss.
Journal ArticleDOI
TL;DR: In this paper, the quality of the groundwater in the study area was evaluated through various water quality indexes for drinking and irrigation purposes, and the results indicated that groundwater of the area is approaching an alarming stage of its suitability for drinking purpose because a major percentage (i.e., 56% of samples are within poor category.
Journal ArticleDOI
30 Jul 2019
TL;DR: In this article, the authors assess the level of environmental sustainability awareness of some schools in Mubi, a locality in the extreme North-Eastern part of Nigeria with its unique cultures and attitudes towards the subject.
Abstract: The implementation of effective public awareness programs for environmental sustainability depends on certain symbolic steps that require the contribution and participation of each stakeholder. This aspect is generally believed to be to a larger extent based on the understanding of the cultural, economic, political and environmental realities of the domain under consideration. This article assesses the level of environmental sustainability awareness of some schools in Mubi, a locality in the extreme North-Eastern part of Nigeria with its unique cultures and attitudes towards the subject. The teacher and his students were targeted in the survey since this is one important institution upon which the future of societies is based. The survey conducted reveals the level of practice of environmental sustainability among this strong media of information dissemination (primary and secondary schools). Areas of concern in the result of the assessment were highlighted. Recommendations in areas of further improvements were suggested.
DOI
01 Jan 2018
TL;DR: Out of the 5 machine learning algorithms that random forest yields the highest accuracy in predicting activities correctly, results showed the accuracy of 100%.
Abstract: Wearable computation is getting integrated into our daily life. It has got wide acceptance due to their small sizes, and reasonable computation power. These wearable devices loaded with sensors are good candidates to monitor user’s daily behavior (walking, jogging, sleeping…). Human Activity Recognition (HAR) has the potential to benefit the development of assistive technologies in order to support care of the chronically ill and people with special needs. Activity recognition can be used to provide information about patients’ routines to support the development of e-health systems, like Ambient Assisted Living (AAL). Despite human activity recognition being an active field for more than a decade; the development of context-aware systems, there are still key aspects that, if addressed, would constitute a significant turn in the way people interact with mobile devices. The study discusses the principal issues and challenges of HAR systems. A general and data acquisition architecture for HAR systems are presented. HAR systems made use of machine learning techniques and tools, which are helpful to build patterns to describe, analyze, and predict data. Since a human activity recognition system should return a label such as walking, sitting, running, etc., most HAR systems work in a supervised fashion. The objective of proposed study is applying multiple machine learning algorithms on the HAR dataset from Groupware. Out of the 5 machine learning algorithms that random forest yields the highest accuracy in predicting activities correctly, results showed the accuracy of 100%. All the models were also ensembled to improve overall accuracy.

Authors

Showing all 856 results

NameH-indexPapersCitations
Delfim F. M. Torres6070114369
Trilok Singh5437310286
Dattatray J. Late4620511647
Jung Ho Je403286264
Gobena Ameni372074732
Jong Heo372555289
Mahendra A. More362684871
Gyanendra Singh322483198
Dilip S. Joag301273014
Tesfaye Biftu281293225
Salmah Ismail22792151
Rabab Mohammed21921785
Mooha Lee1649821
T. Ganesh1526735
Pandi Anandakumar1518777
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20239
202226
2021332
2020203
2019125
2018101