Volume-4 Issue-1, November 2015 – International Journal of Emerging Science and Engineering (IJESE) https://www.ijese.org Exploring Innovation | ISSN: 2319–6378(Online) | A Periodical Journal | Reg. No.: C/1383209 | Published by BEIESP Fri, 17 Sep 2021 07:09:23 +0000 en-US hourly 1 https://wordpress.org/?v=7.1.2 https://www.ijese.org/wp-content/uploads/2020/06/cropped-IJESE-Logo2s-32x32.jpg Volume-4 Issue-1, November 2015 – International Journal of Emerging Science and Engineering (IJESE) https://www.ijese.org 32 32 A1045114115 https://www.ijese.org/portfolio-item/a1045114115/ https://www.ijese.org/portfolio-item/a1045114115/#respond Fri, 17 Sep 2021 07:06:51 +0000 https://www.ijese.org/?post_type=portfolio&p=5680 The International Journal of Emerging Science and Engineering (IJESE) is an open-access, peer-reviewed, monthly international journal with an ISSN 2319-6378 (online). It is published by the Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) periodically in January, February, March, April, May, June, July, August, September, October, November, and December since 2012.
The International Journal of Emerging Science and Engineering (IJESE) aspires to circulate top-notch, peer-reviewed original articles in Engineering and Technology, shrouding Computer Science and Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, and all related interdisciplinary associates.

The post A1045114115 appeared first on International Journal of Emerging Science and Engineering (IJESE).

]]> The International Journal of Emerging Science and Engineering (IJESE) is an open-access, peer-reviewed, monthly international journal with an ISSN 2319-6378 (online). It is published by the Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) periodically in January, February, March, April, May, June, July, August, September, October, November, and December since 2012.
The International Journal of Emerging Science and Engineering (IJESE) aspires to circulate top-notch, peer-reviewed original articles in Engineering and Technology, shrouding Computer Science and Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, and all related interdisciplinary associates.

Implementation of Rate Adaptation Algorithms for Vehicular Simulations in OMNeT++
Kenneth Sorle Nwizege1, Harry, Inye H2, Irimiagha Paul Gibson3
1Kenneth Sorle Nwizege, School of Engineering Elect/Elect Engineering Dept. Ken Saro-Wiwa Polytechnic Bori, Nigeria.
2Harry, Inye H, School of Engineering Elect/Elect Engineering Dept. Ken Saro-Wiwa Polytechnic Bori, Nigeria.
3Irimiagha Paul Gibson, School of Engineering Elect/Elect Engineering Dept. Ken Saro-Wiwa Polytechnic Bori, Nigeria.
Manuscript received on November 12, 2015. | Revised Manuscript received on November 21, 2015. | Manuscript published on November 25, 2015. | PP: 5-8 | Volume-4 Issue-1, November 2015. | Retrieval Number: A1045114115
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Rate adaptation (RA) is the process of dynamically switching data rates to match the channel conditions, with the goal of selecting the rate that will give a good throughput for the given channel condition. The two fundamental issues when designing a rate adaptation scheme are “when to increase and decrease the transmission rate”. Rate Adaptation is a technique that enhances network performance. It is a process of alerting network nodes to change rate in respect to channel condition. Constant Bit Rate (CBR), Adaptive Auto Rate Fallback (AARF) , and Auto Rate Fallback (ARF) are the only Rate Adaptation Algorithms (RAAs) implemented in OMNeT++. In this paper, we implement, Onoe as new RAAs in OMNeT++ simulator. This is credit-based RAA that changes rate based on credit threshold accumulated.
Keywords: Rate adaptation; wireless networks; OMNeT++;vehicular communication; IEEE802.11p; propagation phenomena; inetmanet

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]]> https://www.ijese.org/portfolio-item/a1045114115/feed/ 0 A1044114115 https://www.ijese.org/portfolio-item/a1044114115/ https://www.ijese.org/portfolio-item/a1044114115/#respond Fri, 17 Sep 2021 06:47:44 +0000 https://www.ijese.org/?post_type=portfolio&p=5677 The International Journal of Emerging Science and Engineering (IJESE) is an open-access, peer-reviewed, monthly international journal with an ISSN 2319-6378 (online). It is published by the Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) periodically in January, February, March, April, May, June, July, August, September, October, November, and December since 2012.
The International Journal of Emerging Science and Engineering (IJESE) aspires to circulate top-notch, peer-reviewed original articles in Engineering and Technology, shrouding Computer Science and Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, and all related interdisciplinary associates.

The post A1044114115 appeared first on International Journal of Emerging Science and Engineering (IJESE).

]]> The International Journal of Emerging Science and Engineering (IJESE) is an open-access, peer-reviewed, monthly international journal with an ISSN 2319-6378 (online). It is published by the Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) periodically in January, February, March, April, May, June, July, August, September, October, November, and December since 2012.
The International Journal of Emerging Science and Engineering (IJESE) aspires to circulate top-notch, peer-reviewed original articles in Engineering and Technology, shrouding Computer Science and Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, and all related interdisciplinary associates.

Combining Econometric and Time Series Models to Project Albanian Population (Projection for Years 2015- 2023)
Eralda Dhamo (Gjika)1, Oriana Zaçaj2, Edionada Gjika3
1Eralda Dhamo (Gjika), Department of Applied Mathematics, Faculty of Natural Science, University of Tirana, Tirana, Albania.
2Oriana Zaçaj, Department of Mathematics, Faculty of Mathematics and Physic Engineering, Polytechnic University Tirana, Albania.
3Edionada Gjika, Department of Biotechnology, Faculty of Natural Science, University of Tirana, Tirana, Albania.
Manuscript received on November 12, 2015. | Revised Manuscript received on November 21, 2015. | Manuscript published on November 25, 2015. | PP: 1-4 | Volume-4 Issue-1, November 2015. | Retrieval Number: A1044114115
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Albania is a small country in the Balkan region but with a key geographical position in the demographic movements in the region and in Europe. In the recent years the political and economic changes in Europe have significantly affected demographic indicators of the country. The population projection is one of the important issues in this moment. The number of births is decreasing, by other hand number of emigrants is increasing rapidly. At this moment population forecasting techniques are seen with interest. In this work we study many socioeconomic variables that may affect the total number of population in Albania. We propose two models which may be used to projected population in the upcoming years. The models combine multiple regression and time series models. The most important variables in the model were selected based on many indicators of the model (AIC, MAPE, MSE etc.) and graphical tests. The final model was selected based on several measures of accuracy and bias, and formal statistical tests of differences in errors by technique.
Keywords: Population projection, time series, regression, socioeconomics, accuracy

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