Origin of Earth: A Quranic Perspective

The modern scientific concepts were clearly envisioned in the Qur'an date back to 7th century, when observational facilities were not available, mathematical principles were not discovered, primary principles (quarks) and fundamental forces  i.e. Gravitational and electromagnetic were not identified. The word earth (أرْضَARD) appears 409 times in Quran. The number of verses in which the Earth is mentioned first is quite small, e.g. Sura 2, verse 29 and sura 20, verse 4, where a reference is made to "Him Who created the earth and the high heavens". On the other hand the numbers of verses where the Heavens are mentioned before the Earth are much larger e.g. Sura-l-araf (7), Verse 54; SuraYunus (10), verse 3; SuraQaf (50), verse 38; Sura l-Hadid (79), verses 27 to 33 etc. The Quran describes itself as a book of guidance. Sura l-Baqarah, verse (67)[i] states:  قَالَ أعُوْذُ بِاللهِ اأنْ أَکُوْنَ مِنَ الْجَاهِلِيْن He said, "I seek refuge in Allah from being among the ignorant."The Qur'an does not render a coordinated description of the Earth Creation. In lieu of a continuous story of creation, there are verses dispersed all over the Quran which deal with certain aspects of the Earth Creation. These scattered verses provide information on the sequential events marking its development with varying degrees of detail. The Quran referred toward at least five points which shed light on the creation of heaven and earth.  And these points are entirely confirmed by scientific facts.    

Spatio – Temporal Data Mining Framework for Natural Resource Exploration

Technology has allowed for a substantial increase in success rate of identifying the presence of energy sources such as oil and natural gas. Data mining, an emerging technology characterized by significantly advanced analytical tools, can contribute to this success rate as it has the potential to guide or at least assist opportunists in hydrocarbon prediction. To make a prediction about presence of hydrocarbon reserve beneath the surface of earth involves geological, geochemical, seismic and microbial prospecting. The test methods involved in the mentioned process need a great deal of cost and time. This project is aimed at developing decision support system to improve the process of hydrocarbon need evaluation and reserve detection by integrating the methods and tools from data mining and potential surface analysis to approach the problem from an interdisciplinary stance. In the thesis, the world countries are classified with respect to sustainable energy development with the underlying assumption that hydrocarbon is the major source of energy all over the world. The addressed question is whether the hydrocarbon reserves in the world comply with its consumption? As a result, two possibilities arose to ensure energy sustainability: (1). To provide an optimal framework for improvement in hydrocarbon exploration process. (2). To provide a framework for improvement in hydrocarbon consumption. The study is about the aforementioned. The presence of hydrocarbon reserves beneath earth‘s surface is predicted on the basis of either (a). Surface indicators or (b). Beneath surface parameters. The surface indicators which are considered in this project may consist of geological and microbial indicators. In state of the art geological and microbial methodologies, the cost and time involved is in affordable. The research attempts to replace geological predictions with intelligent remote sensing and microbial indications with microbe data mining. But the existing techniques of data mining cannot produce desired accuracy if applied to surface indicators database. Some data mining techniques for mining temporal spatial and non spatial data related to surface indicators of hydrocarbon reserves are proposed. The model includes the classification mechanism of world countries on the basis of sustainable hydrocarbon development and then extraction of useful patterns from surface indicators to predict hydrocarbon reserve in a time and cost effective manner. A series of empirical investigations have been made to evaluate the performance of proposed techniques using different and diverse databases that show the effectiveness of methodology.