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PROJECT TOPIC:  DNA CLUSTERING METRIC FOR ACCOMMODATION ALLOCATION IN A DENSELY POPULATED SETTLEMENT
Department:  Computer Science
AMOUNT:  3000
FORMART:   MS WORD
PAGES:  82 pages, abstract, chapter 1-5 , APENDIX A source code and APENDIX B output, well reserached and supervised
  information system
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Abstract

The rate of data creation at present has increased so much that 90% of the data in the world today has been created in frequent times which posed challenges to users especially the internal displaced persons IDP. Clustering is one of the important data mining issues especially for allocations analysis. This research work is aimed at developing a DNA clustering metric for accommodation allocation in a densely populated IDP settlement. The proposed system adopted object oriented analysis and design methodology (OOADM).The proposed system was designed and implemented using an object oriented programming language PHP5, HTML5, CSS3, and MSQL data base. The proposed system is developed to assist in accommodation allocation problems.

 

 

CHAPTER ONE

1.0 Introduction

Wikipedia stated that an internally displaced person (IDP) is someone who is forced to flee his or her home but who remains within his or her country's borders. They are often referred to as refugees, although they do not fall within the legal definitions of a refugee. While clustering in the other hand is a fundamental operation in the analysis of biological sequence data. New DNA sequencing technologies have dramatically increased the rate at which we can generate data, resulting in datasets that cannot be efficiently analyzed by traditional clustering methods. Therefore this work is going to look at a computer based data collection of internally displaced people for proper accommodation and allocation settlement within Nigeria.

1.1Background of Study

Clustering is a division of data into groups of similar objects in a group called cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups.

Understanding large and complex information data sets is commonly seen almost in all fields of   human endeavour. The ability to remove useful hidden knowledge in a data and to act on it is becoming an important issue virtually in all works of life which the IDPs is considered to be one of such Abbas , K. (2008). 

It is very difficult to get accurate figures for internally displaced persons because populations aren't constant.  IDPs may be returning home while others are fleeing, others may periodically return to IDP camps to take advantage of humanitarian aid. While the case of IDPs   in large camps such as those in Darfur, western Sudan, are relatively well-reported, it is very difficult to assess those IDPs who flee to larger towns and cities according to Ayodele, B. (2004). It is necessary in many instances to supplement official figures with additional information obtained from operational humanitarian organizations on the ground. Thus, the 24.5 million figures must be treated as an estimate. Additionally, most official figures only include those displaced by conflict or natural disasters. Development-induced IDPs often are not included in assessments. It has been estimated that between 70 and 80% of all IDPs are women and children.

 


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