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A Model for Clustering Social Media Data for Electronic Learning
Issue:
Volume 1, Issue 1, December 2017
Pages:
1-4
Received:
21 April 2017
Accepted:
11 May 2017
Published:
3 July 2017
DOI:
10.11648/j.ajai.20170101.11
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Abstract: Through Social media, people are able to write short messages on their walls to express their sentiments using various social media like Twitter and Facebook. Through these messages also called status updates, they share and discuss things like news, jokes, business issues and what they go through on a daily basis. Tweets and other updates have become so important in the world of information and communication because they have a great potential of passing information very fast. They enable interaction among vast groups of people including students, businesses and their clients. These numerous amounts of information can be extracted, processed and properly utilized in areas like marketing and electronic learning. This paper reports on the successful development of a way of searching, filtering, organizing and storing the information from social media so that it can be put to some good use in an electronic learning environment. This helps in solving the problem of losing vital information that is generated from the social media. It addresses this limitation by using the data from twitter to cluster students and by so doing support group electronic learning.
Abstract: Through Social media, people are able to write short messages on their walls to express their sentiments using various social media like Twitter and Facebook. Through these messages also called status updates, they share and discuss things like news, jokes, business issues and what they go through on a daily basis. Tweets and other updates have bec...
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Defect Identification and Maturity Detection of Mango Fruits Using Image Analysis
Dameshwari Sahu,
Ravindra Manohar Potdar
Issue:
Volume 1, Issue 1, December 2017
Pages:
5-14
Received:
2 May 2017
Accepted:
16 May 2017
Published:
11 July 2017
DOI:
10.11648/j.ajai.20170101.12
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Abstract: The image processing and computer vision systems have been widely used for identification, classification, grading and quality evaluation in the agriculture area. Defect identification and maturity detection of mango fruits are challenging task for the computer vision to achieve near human levels of recognition. The proposed framework is useful in the supermarkets and can be utilized in computer vision for the automatic sorting of fruits from a set, consisting of different kind of fruits. The objective of this work is to develop an automated tool, which can be capable of identifying defect and detect maturity of mango fruits based on shape, size and color features by digital image analysis. MATLAB have been used as the programming tool for identification and classification of fruits using Image Processing toolbox. Proposed method can be used to detect the visible defects, stems, size and shape of mangos, and to grade the mango in high speed and precision.
Abstract: The image processing and computer vision systems have been widely used for identification, classification, grading and quality evaluation in the agriculture area. Defect identification and maturity detection of mango fruits are challenging task for the computer vision to achieve near human levels of recognition. The proposed framework is useful in ...
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Architecture Trends of Adaptive Educational Hypermedia Systems: The Case of the MATHEMA
Issue:
Volume 1, Issue 1, December 2017
Pages:
15-28
Received:
11 May 2017
Accepted:
26 May 2017
Published:
18 July 2017
DOI:
10.11648/j.ajai.20170101.13
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Abstract: The aim of this article is to present the general architecture trends of Web-based Adaptive Educational Hypermedia Systems (AEHSs) and to give a complete description of architecture of the AEHS MATHEMA. In the beginning, a related work on the architecture trends of Web-based AEHSs is presented. Then, a description of the aspects of the MATHEMA is done regarding both its pedagogical and technological part. Next, one-on-one unit is presented separately and their functions are generally described with respect to the adaptive Web technologies used. Research has shown that students of high schools increase their performance by studying through the AEHS MATHEMA. Also, the formative evaluation of AEHS MATHEMA by students of the Department of Informatics and Telecommunications of the University of Athens, Greece, has shown, with the exception of other things, that all its functions are useful and easy to use.
Abstract: The aim of this article is to present the general architecture trends of Web-based Adaptive Educational Hypermedia Systems (AEHSs) and to give a complete description of architecture of the AEHS MATHEMA. In the beginning, a related work on the architecture trends of Web-based AEHSs is presented. Then, a description of the aspects of the MATHEMA is d...
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Human Face Detection Using Skin Color Segmentation and Watershed Algorithm
Abdulganiyu Abdu Yusuf,
Fatma Susilawati Mohamad,
Zahraddeen Sufyanu
Issue:
Volume 1, Issue 1, December 2017
Pages:
29-35
Received:
15 May 2017
Accepted:
6 June 2017
Published:
24 July 2017
DOI:
10.11648/j.ajai.20170101.14
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Abstract: Face detection receives immense interest in computer vision to improve security and authenticity of a particular system. Color provides useful information at the early stage of face detection in a complex view. Such detection involves many complexities such as background, illumination, and poses. This study provides depth analysis on most prominent color models. The use of those color models can handle well-defined problems in face detection such as occlusions, poses, and illumination conditions. The application areas, techniques used, remarks as well as statistical conversion of the color models from Red Green Blue (RGB) color model are demonstrated. Moreover, a new framework for efficient face detection using skin color segmentation is proposed. The process involves transforming the face images from RGB to the selected color models; then segmentation is carried out by selecting a threshold value for each of the color models. Watershed algorithm is applied to isolate the facial feature from the background. Finally, lips area is localized as it may be missing during the detection process. Detection rate of up to 97.22% was obtained using standard database. The proposed framework targets a range of applications such as PC login security, passport authentication, and pornography filtering.
Abstract: Face detection receives immense interest in computer vision to improve security and authenticity of a particular system. Color provides useful information at the early stage of face detection in a complex view. Such detection involves many complexities such as background, illumination, and poses. This study provides depth analysis on most prominent...
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An Intelligent System for Traffic Control in Smart Cities: A Case Study
Okene David Ese,
Okhueleigbe Emmanuel Ighodalo
Issue:
Volume 1, Issue 1, December 2017
Pages:
36-43
Received:
1 May 2017
Accepted:
26 May 2017
Published:
3 August 2017
DOI:
10.11648/j.ajai.20170101.15
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Abstract: Current traffic light systems use a fixed time delay for different traffic directions and do follow a particular cycle while switching from one signal to another. This creates unwanted congestion during peak hours, loss of man-hours and eventually decline in productivity. In addition to this, the current traffic light systems encourage extortion by corrupt traffic officials as commuters often violate traffic rules because of the insufficient time allocated to their lanes or may want to avoid a long waiting period for their lanes to come up. This research is aimed at tackling the afore-mentioned problems by adopting a density based traffic control approach using Jakpa Junction, one of the busiest junctions in Delta State, Nigeria as a case study. The developed system uses a microcontroller of PIC89C51 microcontroller duly interfaced with sensors. The signal timing changes automatically based on the traffic density at the junction, thereby, avoiding unnecessary waiting time at the junction. The sensors used in this project were infra-red (IR) sensors and photodiodes which were placed in a Line of Sight configuration across the loads to detect the density of the traffic signal. The density of the vehicles is measured in three zones i.e., low, medium and high based on which timings were allotted accordingly. The developed system has proven to be smart and intelligent and capable of curbing incidences of traffic malpractices and inefficiencies that have been the bane of current traffic congestion control systems in emerging cities of the third world.
Abstract: Current traffic light systems use a fixed time delay for different traffic directions and do follow a particular cycle while switching from one signal to another. This creates unwanted congestion during peak hours, loss of man-hours and eventually decline in productivity. In addition to this, the current traffic light systems encourage extortion by...
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Predicting the Seroprevalence of HBV, HCV, and HIV Based on National Blood of Addis Ababa Ethiopia Using Data Mining Technology
Haftom Gebregziabher,
Million Meshasha,
Patrick Cerna
Issue:
Volume 1, Issue 1, December 2017
Pages:
44-55
Received:
14 May 2017
Accepted:
1 June 2017
Published:
30 August 2017
DOI:
10.11648/j.ajai.20170101.16
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Abstract: Recent advancements in communication technologies, on the one hand, and computer hardware and database technologies, on the other hand, have made it easy for organizations to collect, store and manipulate massive amounts of data. As the volume of data increases, the proportion of information in which people could understand decreases substantially. The applications of learning algorithms in knowledge discovery are promising and they are relevant area of research offering new possibilities and benefits in real-world applications such as blood bank data warehouse. The availability of optimal blood in blood banks is a critical and important aspect in a Blood transfusion service. Blood banks are typically based on a healthy person voluntarily donating blood used for transfusions. The ability to identify regular blood donors enables blood bank and voluntary organizations to plan systematically for organizing blood donation camps in an efficient manner. The objective of this study was to explore the immense applicability of data mining technology in the Ethiopian national blood bank service by developing a predictive model that could help in the donor recruitment strategies by identifying donors that are at risk of TTIs which can help in the collection of safe blood group which in turn assists in maintaining optimal blood. The analysis has been carried out on 14575 blood donor’s dataset that has at least one pathogen using the J48 decision tree and Naive bayes algorithm implemented in Weka. J48 decision tree algorithm with the overall model accuracy of 94% has offered interesting rules. From the total of 156729 consecutive blood donors, 14757 (9.41%) had serological evidence of infection with at least one pathogen and 29 (0.19%) had multiple infections. The overall seroprevalence of HIV, HBV and HCV was 2.29%, 5.23%, and 2.30% respectively. The seropositivity of TTIs was significant in business owners, students, civil servants, unemployed individuals, drivers and age groups 25 to 34 and 35 to 44 years.
Abstract: Recent advancements in communication technologies, on the one hand, and computer hardware and database technologies, on the other hand, have made it easy for organizations to collect, store and manipulate massive amounts of data. As the volume of data increases, the proportion of information in which people could understand decreases substantially....
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Robust Fuzzy Control for 2-DOF Manipulator System
Issue:
Volume 1, Issue 1, December 2017
Pages:
56-61
Received:
26 April 2017
Accepted:
25 July 2017
Published:
28 November 2017
DOI:
10.11648/j.ajai.20170101.17
Downloads:
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Abstract: Robot manipulators have become increasingly important in the field of automation. So modelling and control of robots in automation will be very important. This paper presents a study of robust control approach employing fuzzy logic control technique for two degree of freedom (2-DOF) manipulator robot. A learning control system is designed so that its “learning mechanism” has the ability to improve the performance of the closed-loop system by generating command inputs to the plant and utilizing feedback information from the plant. It is well known that robotic manipulators are highly nonlinear coupling dynamic systems. A fuzzy logic rule base is designed, using the knowledge obtained from the operator. Simulation is performed to demonstrate the effectiveness of control strategy. Furthermore, the parameters of the controllers were optimized using MATLAB and simulations' result reveals that control scheme is working satisfactorily.
Abstract: Robot manipulators have become increasingly important in the field of automation. So modelling and control of robots in automation will be very important. This paper presents a study of robust control approach employing fuzzy logic control technique for two degree of freedom (2-DOF) manipulator robot. A learning control system is designed so that i...
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