International Journal of Advanced Studies in Computer Science and Engineering (IJASCSE)

International Journal of Advanced Studies in Computer Science and Engineering (IJASCSE)
ISSN : 2278 7917
All articles published in IJASCSE are open access and freely available online, immediately upon publication.

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International journal of advanced studies in Computer Science and Engineering (IJASCSE) maintains all published papers in Open Access Database which provides open access of all listed papers to universities, researchers and scholars. It is based on OAI-PMH protocols which help to index the research papers worldwide. All Issues published are dedicated to best practices on ethical matters, errors and retractions. The prevention of publication malpractice is one of the important responsibilities of the editorial board. Any kind of unethical behavior is not acceptable, and plagiarism is not tolerated in any form. Our ethic statements are based on Elsevier recommendations and COPE's Best Practice Guidelines for Journal Editors.

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IJASCSE Volume 9 Issue 01
Performance Evaluation of Digital Modulation Techniques for Next Generation FSO
Author:
Ahsan Ali Khaskheli, Mehran University of Engineering & Technology Jamshoro 76062 Sindh Pakistan, Pakistan.
Co-Author (s) :
Faisal Ahmed Memon
Mehran University of Engineering & Technology Jamshoro 76062 Sindh Pakistan, Pakistan.
Keywords:
Free Space Optics, Next Generation Netwroks, Rain, Fog, Digital Modulation Techniqus.
e-Mail:
ahsanali@gmail.com
Abstract::
Free space optics (FSO) is a fascinating optical wireless technology providing a license-free alternative to microwave communications. In this work, we evaluate the performance of digital modulation techniques such amplitude shift keying (ASK), frequency shift keying (FSK) and phase shift keying (PSK) to send and receive signals over a distance of 5 Kms in the presence of turbulent atmospheric conditions such as rain and fog for the Hyderabad region of Pakistan. Simulations of next generation FSO link have been performed in Optisystem tool to estimate BER under different atmospheric conditions. The results show that frequency shift keying outperforms other modulation techniques providing better performance, signal quality and lower bit error rate.
Predicting Employee Satisfaction of Academics in Sri Lankan Universities: Ordinal Regression Approach
Author:
D. P. N. P. Dias; Sri Lanka Institute of Information Technology, Colombo, Sri Lanka.
Co-Author :
K. P. G. C. D. Sucharitharathna; Sri Lanka Institute of Information Technology, Colombo, Sri Lanka
Key words::
Employee Satisfaction, Academics, Demographic data, Reliability Analysis, Ordinal Regression.
e-Mail:
pnpdias@gmail.com
Abstract::
The study examined the components of job satisfaction and its predictive measures on job satisfaction of academics in Sri Lankan Universities. The study employed a descriptive research of the survey type to describe and interpret the components of job satisfaction of academics in Sri Lankan Universities. A questionnaire was used to collect information from respondents. The factors collected from the questionnaire includes demographic factors and 7 other factors namely superior behavior, co-worker behavior, job itself, physical conditions, teaching and Research, administrative duties, academic environment and freedom. Two hundred and thirty academics from various universities were responded. Haphazard Sampling was used in selecting the respondents, from state and non-state Universities. Data were analyzed using ordinal regression. Reliability analysis was applied to check the internal consistency of all the seven factors. The study revealed that, superior behavior, job itself and freedom are the significant factors for employee satisfaction.
IoT based Healthcare Monitoring System
Author :
D Kaur; Dept. of Computer Science and Engineering Jamia Hamdard New Delhi.
Co-Author: :
None.
Keywords:
Healthcare, Cloud computing
e-Mail:
dkaur@gmail.com
Analyzing Classification Results for Twitter Sentiment
Author :
Dr.Kalayan; St.Joseph's College of Engineering Chennai.
Co-author :
None.
Keywords:
Twitter, machine learning
e-Mail:
kalyan@stjosephs.ac.in
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