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Exploring Innovation | ISSN:2319–6378(Online)| Reg. No.:68120/BPL/CE/12 | Published by BEIESP | Impact Factor:4.72
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Volume-4 Issue-1: Published on November 25, 2015
Volume-4 Issue-1: Published on November 25, 2015

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Volume-4 Issue-1, November 2015, ISSN:  2319–6378 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



Eralda Dhamo (Gjika), Oriana Zaçaj, Edionada Gjika

Paper Title:

Combining Econometric and Time Series Models to Project Albanian Population (Projection for Years 2015- 2023)

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.

 population projection, time series, regression, socioeconomics, accuracy


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Kenneth Sorle Nwizege, Harry, Inye H, Irimiagha Paul Gibson

Paper Title:

Implementation of Rate Adaptation Algorithms for Vehicular Simulations in OMNeT++

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.

  rate adaptation; wireless networks; OMNeT++;vehicular communication; IEEE802.11p; propagation phenomena; inetmanet


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