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Cerebral aneurysm is a weakness in a blood vessel that may enlarge and bleed into the surrounding area, which is a life-threatening condition. Therefore, early and accurate diagnosis of aneurysm is highly required to help doctors to decide the right treatment. This work aims to implement a real-time automated segmentation technique for cerebral aneurysm on the Zynq system-on-chip (SoC), and virtualise the results on a 3D plane, utilizing virtual reality (VR) facilities, such as Oculus Rift, to create an interactive environment for training purposes. The segmentation algorithm is designed based on hard thresholding and Haar wavelet transformation. The system is tested on six subjects, for each consists 512 × 512 DICOM slices, of 16 bits 3D rotational angiography. The quantitative and subjective evaluation show that the segmented masks and 3D generated volumes have admitted results. In addition, the hardware implement results show that the proposed implementation is capable to process an image using Zynq SoC in an average time of 5.2 ms.

The amount of raw data related to electricity consumption is increasing rapidly with the increase of construction sites, population and Qatar preparation for 2022 world cup. By this increase, managers will find difficulties in studying the data and keeping track of the consumption. Thus, taking actions and future planning will be a hard task and the decisions taken might not be beneficial because of the miss understanding of data. In this project, a customized web application is developed to visualize the data on an interactive map. The idea behind the project is to help decision makers to take actions in an efficient and easy way based on the data visualized thus, it supports Qatar's 2030 vision for saving time and electricity. Instead of reading big tables with huge incomprehensible numbers, the application easily visualizes the average consumption on the map. It also provides different chart types to help the user in comparing the data and consequently take the right decision. The rapid increase of data challenges the ability of using such data in decision-making, the challenge also extends to the ability of avoiding the risk of getting lost in these big numbers. Reading such data and trying to analyze it could be wasteful in terms of time and money. Moreover, it could cut down industrial and scientific opportunities. The current solution in Qatar for electric consumption analysis is using Microsoft Excel. The stakeholders only use professional software for operational purposes, but not for analyzing the data. As a result, they are going to see what they asked for only and they would waste any opportunity for deeper insight into these data. Visual analytics is a powerful tool to visualize and transparent processes to provide a means of communicating about them rather than providing results. Data visualization is an effective tool for communication regardless of the communicators’ expertise. It is also viewed as an important analytical tool for effective research communication. It is not limited to the display of raw data sets, but rather all static and interactive visual representations of research data, which may include interactive charts, queries, etc. Combining the visualization aspect with the analytics of big data will significantly help resolving the problem of reading the electricity consumption data. One of the project's goals is to improve the readability of data insights and unlock the ultimate power of data visualization; the data presentation element is where alternative representations will be used to test the persuasive power of visualization. The project aims to make data understandable using data visualization techniques. It provides several features such as an interactive map that indicates the average consumption. The zooming levels are divided into three levels: 1) The Whole Country 2) Municipalities 3) Areas level. In addition, the data is visualized using different graph types: line graphs, pie charts, bar charts and others. This helps the managers and decision makers to effectively analyze the data and compare between different areas and the average consumption through years. Furthermore, it provides different utilities such as emailing the results, printing, saving and showing the table.

No abstract