Proc. International Conf. On Telecommunications, Dubai, UAE, 1994

ٍSubmitted to IEEE  International Conference on Computer Engineering & Systems (ICCES’06), 2006, Egypt

New trends in Science and Technology as a tool for Sustainable Development in Africa Workshop, Khartoum 2008.

Amer, Kauther M. ; Sharif, Sami M. ; Ashur, Ahmed S.

L. O. Widaa and S. M. Sharif,

ABSTRACT

Remotely sensed data acquired by the Landsat-7 ETM + imaging system (2000) and n old 1980 analogue map of Greater Khartoum at scale of 1:25000 were used to develop a Geographic Information System (GIS) for Greater Khartoum area. Digital land-use, land-cover and thematic maps have been produced for the study area. Object-oriented databases (OODs), which consis t of spatial and non-spatial attributes, have been

created for all maps. The developed GIS model offers great benefits to development in Sudan, where it works as a base for different fields and applications. The model with its OODs is capable of answering frequently asked questions associated with land use and land cover activities.

ABSTRACT:

Remotely sensed data acquired by the Landsat-7 ETM + imaging system (2000) and an old 1980 analogue map of Greater Khartoum at scale of 1:25000 were used to develop a Geographic Information System (GIS) for Greater Khartoum area. Digital land-use, land-cover and thematic maps have been produced for the study area. Object-oriented databases (OODs), which consis t of spatial and non-spatial attributes, have been created for all maps. The developed GIS model offers

great benefits to development in Sudan, where it works as a base for different fields and applications . The model with its OODs is capable of answering frequently asked questions associated with land use and land cover activities.

ABSTRACT

A General Regression Neural Network (iterative model) was trained and taught to predict land cover features obtained from remotely sensed data. Training patterns have been generated from bands 1 and 4 of the Landsat-7 ETM+ imaging system (2000). Traditional digital image processing techniques were used to create the training and test patterns as well as analyzing the network output results. The trained network was applied to ne

w data, for the ANN Shell (i.e. other bands of Landsat-7 and bands 2, 3, and

4 acquired by Landsat-5 TM in 1996). Reasonable outputs were obtained when the shell was applied to band 1,2,3,4,5 and 7 (Landsat-7). The trained shell failed to process most of the production patterns genera

ted from Landsat-5 image-data. The network completely failed to process all patterns generate d from spectral bands covering other areas with

different topography. Based on a long series of trial and errors, it is well recognized that, the most serious problems to achieve efficient trained networ

k are not technical, but related to training and test patterns (image data). Finally, GRNN as tested, was found to be a useful new technique for

image recognition and thematic mapping from remotely sensed data.

Sudan Engineering Society Journal, Vol. 52, No. 45 2004 pp. 17-22

20

Abstract

Because autocorrelation func tions play an important role in stochastic processes and can be used to model the traffic data practically, it is significant to study how to find a function that best fits the autocorrelation sequence of a real-traffic trace. This paper presents a asymptotic model for autocorrelation functions using Weighted non-linear least squares.

Abstract

Because autocorrelation func tions play an important role in stochastic processes and can be used to model the traffic data practically, it is significant to study how to find a function that best fits the autocorrelation sequence of a real-traffic trace. This paper presents a asymptotic model for autocorrelation functions using Weighted non-linear least squares.

Abstract

To properly model the Internet a through understanding of the characteristics of network traffic is needed. These characteristics can be obtained by measurement and anal-ysis of actual network traffic. Internet traffic is known to exhibit self-similarity and long-range dependence in both local area networks and wide area networks. This paper presents backbone Internet traffic intensities and statistics in the Sudan in the period from 17th April 2002 to 30th September 2002. The traffic measurements were carried out using MRTG (Multi Router Traffic Grapher) software at an Internet core router.

Abstract:

The attenuation introduced by rain is discussed in this paper. The rainfall rate distribution needed by the prediction models are measured and obtained for 15 stations in Sudan. The data used to find the rate distributions is collected over 20 years. For the purpose of attenua tion estimation the country is divided into five ra in zones. The attenuation statistics are computed using ITU-model for these zones. Results shows that links are avai lable for 99.9% of year time with attenuation less than 8 dB in zone 1 (at far north of country) and with attenuation less than 45 dB in zone 5 (at the far south of the country). The attenuation is computed at the x-band with spherical rain drop assumption.

An adjusted ARIMA model for internet traffic
El Hag, Huda M. A.; Sharif, Sami M.
AFRICON 2007
Volume , Issue , 26-28 Oct. 2007 Page(s):1 – 6
Digital Object Identifier   10.1109/AFRCON.2007.4401554
Summary:Traditional time series models such as ARIMA models have been proven to be inadequate for modelling traffic exhibiting long-range dependance. In this paper we present a new model the Adjusted ARIMA model for modelling long-range dependant Internet traffic. The AARIMA model is suggested to give a quick and simple way to model Internet traffic by retaining all the properties of the ARIMA models while capturing the selfsimilarity. We use the Box-Jenkins methodology as a frame work for our modelling procedure. We construct our model by building the best ARIMA model possible for a trace and then adding our adjustment to obtain the equivalent AARIMA model. We show that the AARIMA model shows an evident improvement over the ARIMA model using several goodness of fit criteria, our main goodness of fit criteria is the ability to capture the Hurst parameter of the original trace being modeled. The model should not underestimate the Hurst parameter and any overestimation should be less than or equal to 20% of H parameter of the measured trace. The Adjusted ARIMA model is shown to accurately predict Internet traffic for up to one hour in advance. The adjustment we propose to the ARIMA model is by introducing a feedback term made up of the first difference of the series being modeled. We used four Hurst parameter estimators to measure the selfsimilarity of the measured traces and both the AARIMA and ARIMA models for all measured traces. For all the estimators used the AARIMA was found to capture the long-range dependence irrespective of estimator used. We used the Adjusted ARIMA model to predict three Public Domain Internet traffic traces namely a Bellcore Internet Wide Area Network External traffic trace (length 35 hours), a Bellcore Internet Wide Area Network “purple cable“ trace (length half an hour) and a MPEG-1 compressed video traffic trace (length half an hour). We show that for the Public Domain traces the AARIMA model gives values of H parameter which are- more accurate than those given by the ARIMA model.

Abstract

— In this paper a new model the Adjusted Autoregres-

sive Integrated Moving Average (AARIMA) model for predicting

Internet traffic is introduced. The steps that can be used to obtain

the model are detailed. Real Internet traffic traces are used to

estimate and test the models. The AARIMA model is shown to

capture the local self-similarity using wavelet analysis. The model

was verified using Real Internet Public Domain traces.

 Proceedings ICMSAO’09, Sharjah, UAE January 20-22, 2009

Free and Open Source Software in Sudan workshop,  Khartoum June 2009 [PPT]

The 1st International Conference on African Digital Libraries and Archives (ICADLA-1), July 2009, Addis Ababa, Ethiopia.

Sudan Engineering Society Journals, Vol. 55, No. 53, 2009, pp: 54-63 [Arabic]

Abstract

Advances in information and communication technologies led to

the emerging of modern digital systems which facilitate sharing of information

and innovations. These systems are thus supportive to the Sudanese cultural

“collective” memory institutions as a collective memory bank of the nation

achievements and indigenous knowledge. This article aims to investigate these

digital systems in these institutions as transfer of information and communication

technology from perspectives of the users. It has reviewed and assessed

infrastructures, resources, systems and ICT readiness, which will contribute in

these institutions to adopt digital memory of Sudan. The outputs guide to carry

out reforms and rehabilitation to build capacities and revitalize infrastructure

of digital environment which affect reliance and shared resources in memory

institutions. It is concluded that these repositories which will be represented

in Sudan national digital content. Finally, the article proposes to revitalize of

the country’s cultural policies in line with the principles of cultural diversity

and development of a comprehensive strategy for long-lived digital explicit and

tacit knowledge

In proceeding of: The 9th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2011, Egypt, December 2011 , Page(s): 297 – 298

University of Khartoum Engineering Journal, Vol. 1, No. 1, 2011

submitted to IPEC 2006 The 6th International Philadelphia Engineering Conference on Computational Aspects and Their Applications in Electrical Engineering CATAEE’ 2006

Submitted to IEEE/ACM Transactions on Networking.

Abstract

High frequency propagation model for Sudan and South Sudan in term of the optimum frequency was designed based on the International Reference Ionosphere (IRI). The model simulates the effect of changing atmospheric properties during day and night on the Sudanese ionospheric links in term of the optimum frequency. More than 140 HF links in Sudan were investigated on field to verify the model. The model is intended to be integrated with the Global Ionosphere Observatory Network (GIRO).

Abstract 

Algorithms and architectures for performing modular multiplication operations are important in residue number system and cryptography. In this paper a new algorithm of Radix-4 MSB modular multiplier using 4-2 compressor is presented. The recoding rules for the radix-4 Booth’s algorithm are used to reduce the number of partial products and improve the total hardware area and time. This new algorithm avoided a carry store and feedback in some algorithms presented in the literature. It is simulated and implemented using MatLab and VHDL.