Difference between revisions of "Project Groups"
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Revision as of 12:18, 15 June 2018
ISSS608 Visual Analytics and Applications
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Project Groups
Please change Your Team name to your project topic and change student name to your own name
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Project title: Provide eyes catching title. However, it should reflect the content or/and the focus of your project Abstract The abstract should not be more than 350 words. |
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Cyber-security: you are in more danger than you can possibly imagine Abstract |
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Exploring Inequality’s Geographic Dimension Across Neighbourhoods in Singapore: Its Driving Forces & Touch Points Amidst the recent debate over growing social inequality in Singapore such as the distinct clustering of elite schools and varying access to resources, the dangers of hardening social mobility can pose as a threat for a culturally diverse nation that has upheld its values of social cohesion and racial harmony. In bonding and bridging communities, Singapore has put in place various programmes in the community and schools to nurture shared experiences and promote inter-communities mixing. More recently, inequality was highlighted to have a geographic dimension even for a densely populated city like Singapore. Using geospatial techniques in R, the dashboard serves to visualise whether geography is an important driver of inequality, by mapping the extent of social inequality and access to common spaces across neighbourhoods. This will be done via three approaches. First, we will analyse whether there exist clusters that could point towards social inequality and whether this is more pronounced in certain neighbourhoods, based on ethnic mix, age composition, and housing type. This will be done using choropleth mapping, spatial segregation index, and spatial points pattern analysis at both the subzone and dwelling unit level. Next, using the Hansen Accessibility Model, we will map out the available touch points within neighbourhoods that could facilitate social mixing, such as the ease of access to common spaces, amenities and opportunities for choice of education. This is because an important aspect of social inequality is having reasonably fair access to different resources. Lastly, by identifying centroids, we will move into solutioning and explore possible spaces such as vacant state land where upcoming public amenities can be best placed to optimise social class mixing. |
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Buy More! – Maximizing Sales Taking advantage of data is key to ensuring the survival of an e-commerce retail business. Through the visualization of the spending habits of customers and the visualization of the results from various machine learning algorithms, insights can be gathered as to which customers the retailer should target and what type of products should be kept in-stock to maximize sales. |
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Global Migration - Higher Walls or Wider Doors? Abstract |
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