Most systems are intelligent and the industrial world is moving now towards
technology. Most industrial systems are now computerized and offer a high speed.
However, Face recognition is a biometric system that can identify people from their
faces. For few number of people to be identified, it can be considered as a fast
system. When the number of people grew to be bigger, the system cannot be adopted
in a real-time application because its speed will degrade along with its accuracy.
However, the accuracy can be enhanced using pre-processing techniques but the
time delay is still a challenge. A series of experiments had been done on AT&TORL
database images using Enhanced Face Recognition System (EFRS) that is
adopting a Local Binary Pattern Histogram (LBPH) as feature extraction method.
During these experiments, LBP parameters and pre-processing techniques have been
changing and the results were recorded for accuracy and time for different database
sizes. The accuracy reaches 98.5% but the time delay keep increasing with the
number of people in the database.
The Limitation of Pre-processing Techniques to Enhance the Face Recognition System Based on LBP
Face Recognition
LBP
Recognition accuracy
Recognition time
Weakness
Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Theoretical And Applied Information Technology
Factors affecting global virtual teams’ performance in software projects
Today the trend is to perform software development work via distributed geographical area among team
individual or even as an organization. However
due to the global market and international presence of many companies
there is a need to implement a global virtual teams. The global virtual team members are gradually engaged in globalized business environments across space
time and organizational boundaries via information and communication technologies. A global virtual team relies on communication
collaboration
and information exchange are the most important criteria in global virtual teams’ operations. The purpose of this paper is to answer two research questions. The first research question is to identify the factors affecting global virtual teams’ performance. A systematic literature review was conducted to answer the first research question. The second research question is on what the rank of the factor affecting the global virtual teams’ performance according to their level of effect on global virtual teams’ performance. Online survey was conducted within 103 developers and IT managers from eight IT companies to answer the second research question. The Statistical Package for Social Science (SPSS 22) was used to analyze the collected data. In this study
we investigated factors that affect global virtual teams’ performance
factors considered include cultural differences
language problems
time-zone differences
team size
technical problems
lack of trust
lack of sufficient training
and ICT problems. Also the findings indicated that lack of sufficient training is the highest level of effect on global virtual teams’ performance. On the other hand
team size is the lowest level of effect on global virtual teams’ performance. © 2005 - 2016 JATIT & LLS. All rights reserved.
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