Difference between revisions of "Project Groups"
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− | [[ | + | <center>[[IS428_2016_17T1_GlobalWarming|Team Valor]]</center><br/> |
+ | [[File:Team_Valor_Logo.png|center|250px]] | ||
|| | || | ||
− | ''' | + | '''Visualizing Global Warming and Climate Change''' |
− | |||
− | |||
+ | Recent president candidate of the US, Mr Donald Trump thinks that climate change is a hoax. That is really worrying, especially when current polls are showing that he is having a real chance in winning the election. Our team seeks to validate the climate change's truthfulness by exploring and visualizing ocean, land and weather data. Thus, we hope through this project, we settle the fact once and for all. Moreover, this serves as a tool to raise the awareness and understanding of our mother Earth's health status. How the climate has changed over time, which stage are we in and how many years does Singapore has left to stay above the sea level. | ||
|| | || | ||
− | *[[ | + | *[[IS428_2016_17T1_Team_Valor|Proposal]] |
− | *[[ | + | *[[IS428_2016_17T1_Team_Valor_Poster|Poster]] |
− | *[[ | + | *[[IS428_2016_17T1_Team_Valor_Application|Application]] |
− | *[[ | + | *[[IS428_2016_17T1_Team_Valor_Report|Report]] |
|| | || | ||
− | * | + | * Nguyen Duy Loc |
− | * | + | * Nguyen Luong Thanh Minh |
|- | |- | ||
|| | || | ||
− | [[Staying Vigilant, Confronting Terrorism | | + | <center>[[Staying Vigilant, Confronting Terrorism |Vigilante]]</center><br/> |
+ | [[File:Group7 TeamLogo.png|center|250px]] | ||
|| | || | ||
'''Visualizing Terrorism Threats & Activities''' | '''Visualizing Terrorism Threats & Activities''' | ||
− | The threat of terrorism is growing everyday and many countries have taken steps to mitigate the risks of terrorism. Over the past few years, there is a rise in research on terrorist organizations and the activities they have performed throughout the years. However, more still needs to be done to analyze past terrorist activities and gain insights from it easily so that all countries could better prepare for a worst case scenario. In this project, we are interested to find out and understand | + | The threat of terrorism is growing everyday and many countries have taken steps to mitigate the risks of terrorism. Over the past few years, there is a rise in research on terrorist organizations and the activities they have performed throughout the years. However, more still needs to be done to analyze past terrorist activities and gain insights from it easily so that all countries could better prepare for a worst case scenario. <br/> |
+ | In this project, we are interested to find out and understand more information about each terrorists’ organization and their attack patterns (e.g. bombing, assassination, shooting) regionally/globally. Also, we hope to be able to identify possible linkages between the number of terrorist activities occurring in each country and its development status. | ||
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− | [[ | + | <center>[[CATalytics]]</center> |
+ | [[File:CATALYTICS_Logo.jpg|300px|center]] | ||
|| | || | ||
− | + | <b> Times Higher Education (THE) World University Rankings</b><br> | |
− | + | According to a [https://www.timeshighereducation.com/world-university-rankings/news/university-rankings-most-important-factor-for-international-students/ survey] of more than 14,000 international students in Australia and the UK, 77% of students listed both university and subject rankings as “very important” when deciding a place to study. However, most rankings systems online merely list out the universities and their rankings relative to each other, without delving into the breakdown of performance indicators that may affect the rankings. This makes it difficult for anyone to truly visualize the information being displayed and how various factors interact with each other. As such, given the importance of these rankings in decision-making, this project hopes to provide an interactive outlet to aid students in their decision-making process. Furthermore, we hope that the dynamic visual created not only provides interactivity between performance indicators but also reveals trends and hidden patterns of associations (that tabular formats might miss out) to aid in future decision making. | |
|| | || | ||
− | *[[ | + | *[[CATalytics|Proposal]] |
− | *[[ | + | *[[CATalytics_Poster|Poster]] |
− | *[[ | + | *[[CATalytics_Application|Application]] |
− | *[[ | + | *[[CATalytics_Research Paper|Report]] |
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* Albert Bingei | * Albert Bingei | ||
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|- | |- | ||
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− | [[JJJ]] | + | <center>[[JJJ: Proposal|J3.ds]]</center><br/> |
+ | [[File:Logo.png|center|250px]] | ||
+ | |||
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− | - | + | '''Life of those who work far from home''' |
+ | |||
+ | If you are staying in the east, will you be willing to travel to the west? Singapore’s increasing population and land scarcity makes urban planning increasingly relevant to policy makers. Commuter patterns give insight to assess the current situation in Singapore. In this project, we seek to uncover commuter patterns and better visualize them for easy understanding to aid formulation of policies to improve our living standards. Although many companies have been introducing various methods to eliminate commuting time, there is a proportion of people who still have to commute over long distances. (http://www.enterpriseinnovation.net/article/singapore-workers-beat-commuting-woes). Some insights to understanding commuter patterns across regions can help LTA and bus service operators to think about how to improve the bus routes. The commuters that this project mainly focuses on would be those who need to travel to work in the morning (Mon - Fri, 5-9am). | ||
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*[[JJJ: Poster|Poster]] | *[[JJJ: Poster|Poster]] | ||
*[[JJJ: Application|Application]] | *[[JJJ: Application|Application]] | ||
− | *[[JJJ: | + | *[[JJJ: Research Paper|Report]] |
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* Joachim Fu | * Joachim Fu | ||
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[[TheBigScreen]] | [[TheBigScreen]] | ||
+ | [[File:Capture.PNG|300px|center]] | ||
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− | Is it possible to predict how good a movie will be before it even screens? This is a subjective question. While some rely on movie critics and early reviews, others depend on instinct. However, we know reviews can take a long time to gather and human instinct is simply unreliable. Thousands of movies are produced every year and all of them our clamouring for the $11 we spend on movie tickets! Our group wants to know | + | '''Visualization of Movie Data''' |
+ | |||
+ | Is it possible to predict how good a movie will be before it even screens? | ||
+ | This is a subjective question. While some rely on movie critics and early reviews, others depend on instinct. However, we know reviews can take a long time to gather and human instinct is simply unreliable. Thousands of movies are produced every year and all of them our clamouring for the $11 we spend on movie tickets! | ||
+ | |||
+ | And this information is not just for consumers like us. The entertainment industry has always stayed strong despite economical factors. Investors are always looking for opportunities such as purchasing the rights to produce themed goods or services based on popular movies. If only looking for a deal after the movie is successful, why not predict their success and make a move first? | ||
+ | |||
+ | Not stopping there, movie sponsors are getting popular these recent years. Remember the Chevrolet cars all over the Transformer movies, Bumblebee? That was marketing done right, where all eyes are fixated on the battle machines bearing a real company's brand name. But what kinds of movie should your brand appear in? Maybe through this project, we can discover some trends that may help lead to an answer. | ||
+ | |||
+ | Our group wants to know which movies are worth you spending your money and time on. | ||
|| | || | ||
− | *[[TheBigScreen | + | *[[TheBigScreen|Proposal]] |
− | *[[ | + | *[[TheBigScreen_Poster|Poster]] |
− | *[[ | + | *[[TheBigScreen_Application|Application]] |
− | *[[ | + | *[[TheBigScreen_Research_Paper|Report]] |
|| | || | ||
* Heng Yi Teng Mabel | * Heng Yi Teng Mabel | ||
* Chen Huiyan | * Chen Huiyan | ||
* Tee Yu Xuan | * Tee Yu Xuan | ||
+ | |||
+ | |- | ||
+ | |- | ||
+ | || | ||
+ | <center>[[Slamdunkers_Proposal|SlamDunkers]]</center> | ||
+ | [[File:Slamdunkers-logo.jpg|300px|center]] | ||
+ | |||
+ | || | ||
+ | '''Who are the best NBA players?''' | ||
+ | |||
+ | In attempt to win the championship each season, NBA teams often scout top performing players to join them. These scouts often sit in the games to monitor and evaluate players’ performances, skills and techniques. Putting all these information together, they get an overview of all the players capabilities and their standing against other players. | ||
+ | |||
+ | With the rise in data and technology, there becomes a new way for scouts to evaluate players. They can leverage on this new data to get a more detailed understanding of players’ performances. For example, they would be able to know from what distance is the player most comfortable shooting from. These new insights can offer scouts a more accurate assessment on the players. | ||
+ | || | ||
+ | *[[Slamdunkers_Proposal|Proposal]] | ||
+ | *[[Slamdunkers_Poster|Poster]] | ||
+ | *[[Slamdunkers_Application|Application]] | ||
+ | *[[Slamdunkers_Research|Report]] | ||
+ | || | ||
+ | * Lee Wai Tong Arnold | ||
+ | * Lim Lai Ho | ||
+ | * Tan Yong Kiong, Alson | ||
+ | |||
+ | |- | ||
+ | |- | ||
+ | || | ||
+ | <center>[[TSL International]]</center> | ||
+ | [[File:Logovisualgroupproject.PNG|300px|center]] | ||
+ | || | ||
+ | '''A Time-series Comparison and Drilldown Visualization of Economies Worldwide ''' | ||
+ | |||
+ | Ever wondered how one country's economy was doing compared to another? What about the effects of current events or economic policies over time? | ||
+ | |||
+ | For the curious economist, job seeker or migrant, this visualization aims to aid you in knowing the changes in economy over time - globally, regionally and by country. We want to let you make an informed decision by: | ||
+ | |||
+ | * Intuitively knowing which countries and its industries are in growth/decline compared to the region and other countries and | ||
+ | * Having clarity on the economic effects of policies or current events of one nation on another | ||
+ | |||
+ | || | ||
+ | *[[IS428_2016_17T1_TSL_International_Proposal|Proposal]] | ||
+ | *[[IS428_2016_17T1_TSL_International_Poster|Poster]] | ||
+ | *[[IS428_2016_17T1_TSL_International_Application|Application]] | ||
+ | *[[IS428_2016_17T1_TSL_International_Report|Report]] | ||
+ | || | ||
+ | * Margot Stelleman | ||
+ | * Li Wei Qiao | ||
+ | * Thomas Thio | ||
+ | |||
+ | |||
+ | |- | ||
+ | |||
+ | || | ||
+ | [[Forensic Ninja]] | ||
+ | [[File:GroupLogo.png|250px|center]] | ||
+ | |||
+ | || | ||
+ | '''Email Header Analysis and Visualisation''' | ||
+ | |||
+ | From Yahoo scanning its users’ incoming emails on behalf of FBI<sup>[http://www.bbc.com/news/technology-37574648]</sup>to emails exchanges between two founders of a Syracuse development company being used in the court<sup>[http://www.syracuse.com/crime/index.ssf/2016/09/read_the_emails_that_resulted_in_bribery_charges_against_cor_executives.html]</sup>, emails are often used for investigations to uncover foul play of various types. Since many insights can be derived from human to human communication, analysing emails allow us to uncover “never before seen” patterns and correlation. Whether it is fraud or missing employees, emails can definitely provide more information about the current situation, and allow us to find out the main players in these occurrences. | ||
+ | |||
+ | || | ||
+ | *[[Forensic_Ninja|Proposal]] | ||
+ | *[[Forensic_Ninja_Poster|Poster]] | ||
+ | *[[Forensic_Ninja_Application|Application]] | ||
+ | *[[Forensic_Ninja_Report|Report]] | ||
+ | || | ||
+ | * Lim Hui Ting | ||
+ | * Jonathan Eduard Chua Lim | ||
+ | |||
+ | |- | ||
+ | |||
+ | |||
+ | || | ||
+ | [[TEN Project Proposal|TEN]] | ||
+ | || | ||
+ | '''Insights to the tourism sector''' | ||
+ | |||
+ | The tourism is a big source of revenue for Singapore, with the total contribution of the Travel and Tourism industry making up 10.1% of the country’s GDP in year 2014. It is therefore crucial for those in the country to understand how the tourism industry is performing, as well as the effectiveness of various events in stimulating the tourism industry in the country, in order to improve the industry performance. | ||
+ | |||
+ | However, available information about the industry performance is often represented in the format of data tables in the worst case, or simple line, bar or pie charts in the best of cases. These methods of visualization are often insufficient to accurately represent the complex nature of the industry, and thus provides limited utility to readers. | ||
+ | |||
+ | Our group therefore intends to use various visualization methods such as high-dimensional visualization methods like tree or heat maps and time-series visualization methods like cycle plots to visualize and express important information and trends about the industry to readers. These information could be used to show the effectiveness of various strategies to boost tourism like the F1 Race, as well as to explain trends like the drop in tourism in year 2015. | ||
+ | |||
+ | |||
+ | || | ||
+ | *[[TEN Project Proposal|Proposal]] | ||
+ | *[[TEN Poster|Poster]] | ||
+ | *[[TEN Application|Application]] | ||
+ | *[[TEN Report|Report]] | ||
+ | || | ||
+ | * Liu Bowei | ||
+ | * Teo Hui Min | ||
+ | * Wang Jingxuan | ||
+ | |||
+ | |- | ||
+ | |||
+ | || | ||
+ | <center>[[Cupid_Minions]]</center> | ||
+ | [[File:Cupid Minions.png|250px|center]] | ||
+ | || | ||
+ | '''Speed Dating Experiment'''<br><br> | ||
+ | |||
+ | What influence love at the first sight? Also, what attributes influence the selection of romantic partner? These two might be the questions which most of the match making companies would like to ask. In the modern society, more and more young adults choose to attend speed dating events for seeking their possible future partners. However, not all cases are successful. Also , we are seeing the low marriage rate and increasing divorce rate issues in the developed world. One of the reasons for causing these issues is the wrong selection of marriage partner. Some couples only know that they don’t suit each other after marriage. This creates social issues like increaing divorce rate and domestic violence. Therefore, choosing the correct marriage partner is a prompt need for the young adults nowadays. In order to increase the successful matching rate for couples and make sure people can get the most satisfied partners, there is a need to understand these partner-seeking people’s characterstics, demographics, habits and lifestyle informations, etc. From the insight brought by the data, we could suggest the factors which contribute to successful and rapid matching and as a result help the partner-seekers. | ||
+ | || | ||
+ | *[[Cupid_Minions|Proposal]] | ||
+ | *[[Team_Cupid_Minions_Poster|Poster]] | ||
+ | *[[Team_Cupid_Minions_Application|Application]] | ||
+ | *[[Team_Cupid_Minions_Report|Report]] | ||
+ | || | ||
+ | * Zheng Xiye | ||
+ | * Yang Chengzhen | ||
+ | * Liang Bing | ||
+ | |||
+ | |- | ||
+ | || | ||
+ | <center> | ||
+ | [[File:ACVT8_logo.png|center|200px]] | ||
+ | [[Air Traffic Visualisers|Air Traffic Visualisers]]</center> | ||
+ | || | ||
+ | '''Visualizing Air Traffic and Accidents''' | ||
+ | |||
+ | The airplane industry is a very volatile industry. Various events can occur that would lead to the whole airline industry to go into a downward spiral. Clear examples of this events are the September 11 Terrorist Attacks and the 2009 Financial Crisis. However, how much of airline industry is affected due to commercial airplane crashes, and how badly does it affect the number of passengers travelling within the United States. In this project, our team intend to make use of data visualisation techniques to help correlate between airplane crashes and the number of passengers travelling within the United States. We intend to answer various questions such as, the impact of an airplane crash that occurred in US compared to an airplane crash that occurred outside of the US and other questions such as, what should companies do when such an incident happened. | ||
+ | |||
+ | |||
+ | || | ||
+ | *[[Air Traffic Visualisers|Proposal]] | ||
+ | *[[Air Traffic Visualisers: Poster|Poster]] | ||
+ | *[[Air Traffic Visualisers: Application|Application]] | ||
+ | *[[Air Traffic Visualisers: Report|Report]] | ||
+ | || | ||
+ | *Aaron Mak Kang Sheng | ||
+ | *Ong Ming Hao | ||
+ | |||
+ | |||
+ | |- | ||
+ | || | ||
+ | <center> | ||
+ | [[File:Kabak.jpg|center|250px]] | ||
+ | [[Kabak]]</center> | ||
+ | || | ||
+ | '''Visualizing Electricity Consumption in Singapore ''' | ||
+ | |||
+ | As a country with no natural resources, the government has always been vested in encouraging Singaporeans to reduce energy consumption and wastage in Singapore. For example, the National Environment Agency (NEA) has the energy label scheme which requires goods such as Air-conditioner, Refrigerator, Clothes Dryer and Television to be affixed with an energy label sticker depicting how much electricity they consume when used. | ||
+ | More recently in August 2016, Singapore Power (SP) has redesigned the utilities bill in a bid to help fellow Singaporeans track and take steps to reduce their energy and water consumption. | ||
+ | While there are data and statistics available on the Energy Market Authority with regards to the energy consumption by household, it is in quite a raw form with some visualization and basic interactivity to aid users in better understanding energy consumption in Singapore. The statistics or data provided also does not link to other factors such as the population demographics, which perhaps could provide interesting insights on the usage patterns of Singaporean households. As such. while these data exist, it is not being used to allow the public to visualize the energy consumption and to make sense out of it. | ||
+ | |||
+ | |||
+ | || | ||
+ | *[[Kabak: Proposal|Proposal]] | ||
+ | *[[Kabak: Poster|Poster]] | ||
+ | *[[Kabak: Application|Application]] | ||
+ | *[[Kabak: Report|Report]] | ||
+ | || | ||
+ | *Au Loong Zer Kirby | ||
+ | *Audrey Jee Zhi Ying | ||
+ | *Bong Jun Hao | ||
+ | |||
+ | |||
+ | |- | ||
+ | |||
+ | || | ||
+ | <center> | ||
+ | [[File:Team_Collision_Logo.png|center|250px]] | ||
+ | [[Team Collision | Team Collision]]</center> | ||
+ | || | ||
+ | '''UK Road Traffic Accident Visual Analysis''' | ||
+ | |||
+ | In United Kingdom (UK), road traffic accidents have resulted in 1,732 deaths in the year 2015, which is a 2% dip as compared to the year 2014. Despite the drop in the number of deaths, the casualties across all severities remained at an alarming figure of 186,130. As there is an increasing demand for the use of public roads, there is a strong need for us to prevent road traffic accidents and make the public roads as safe as possible. In order to prevent such accidents, it is therefore crucial to understand what are the different factors that contribute to road traffic accidents, and these understandings may then be used to prevent road traffic accidents from occurring. | ||
+ | || | ||
+ | *[[Team Collision|Proposal]] | ||
+ | *[[Team Collision Poster|Poster]] | ||
+ | *[[Team Collision Application|Application]] | ||
+ | *[[Team Collision Research Paper|Report]] | ||
+ | || | ||
+ | *Chua Feng Ru | ||
+ | *Dina Heng Li Gwek | ||
+ | *Lim Ting Zhi | ||
+ | |||
+ | |- | ||
+ | || | ||
+ | <center>[[Team Shooting Stars | Team Shooting Stars]]</center><br/> | ||
+ | [[File:Group4_teamlogo.jpg|center|250px]] | ||
+ | || | ||
+ | '''Data Visualization on NBA players' statistics and teams' performances''' | ||
+ | |||
+ | In recent years, some NBA(National Basketball Association of America) journalists and basketball experts claimed that NBA is in a new era of game plays. Decrease in physical plays and increase in shootings has made NBA games become boring and ugly. A few of them even said NBA players had turned to be soft in defensive side. Traditional position of center has been threatened, many teams are trying to remove the role of center. Are these claims valid based on the trend of past game data? Or indeed these are wrong observations which had no link between history data. As such, this project would focus on the relationship between an NBA team's performance and player's statistics, which might directly or indirectly indicate the current NBA playing features and patterns. Additionally, we would also try to find how those good NBA teams adopt playing strategies: are they offensive oriented, defensive oriented or more balanced between offense and deffense. | ||
+ | |||
+ | || | ||
+ | *[[Team Shooting Stars: Proposal|Proposal]] | ||
+ | *[[Team Shooting Stars: Poster|Poster]] | ||
+ | *[[Team Shooting Stars: Application|Application]] | ||
+ | *[[Team Shooting Stars: Report|Report]] | ||
+ | || | ||
+ | * Wu Wei | ||
+ | * Wang Ziteng | ||
+ | * Manas Mohapatra | ||
+ | |||
+ | |- | ||
+ | |||
+ | || | ||
+ | [[File:GAStech-Logo.png|center|250px]] | ||
+ | <br/> | ||
+ | <center>[[GAStech Jr. Crimebusters | GAStech Jr. Crimebusters]]</center><br/> | ||
+ | || | ||
+ | |||
+ | GAStech is a Tethys-based company that operates in the natural gas production site in the island country of Kronos for at least the past 20 years. In light of their success, GAStech held a celebration for their newfound wealth in January 2014. During which, found that several of their employees had just disappeared. | ||
+ | |||
+ | The scenario depicted has been derived from a 2014 VAST Challenge, a competition held annually in hopes of advancing the field of visual analytics. This project will focus on the mini challenge 2, which involves geospatial, temporal, and transaction data analysis. Even though the datasets provided are fictitious and found to be lacking in areas in terms of missing values, precision limitations and ambiguities, this level of quality is likely a common and prominent occurrence across most datasets found in real life. Nonetheless, when equipped with the appropriate tools and visualizations, critical information can be identified quickly and accurately, allowing for precise judgments and decisions by law enforcement. | ||
+ | || | ||
+ | *[[GAStech_Jr._Crimebusters|Proposal]] | ||
+ | *[[GAStech Jr. Crimebusters Application|Application]] | ||
+ | *[[GAStech Jr. Crimebusters Research Paper|Research Paper]] | ||
+ | *[[GAStech Jr. Crimebusters Poster|Poster]] | ||
+ | || | ||
+ | * Joanne Ong Shi Ying | ||
+ | * Rachel Tay | ||
|- | |- | ||
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|width="10%"|<!-- Team --> [[JJJ|JJJ]] | |width="10%"|<!-- Team --> [[JJJ|JJJ]] | ||
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|colspan="3"|<!-- Second team member --> Jouta Lim | |colspan="3"|<!-- Second team member --> Jouta Lim | ||
|colspan="3"|<!-- Third team member --> James Chua | |colspan="3"|<!-- Third team member --> James Chua | ||
+ | |||
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− | |width="10%"|<!-- Team --> [[ | + | |width="10%"|<!-- Team --> [[Forensic Ninja|Forensic Ninja]] |
− | |colspan="3"|<!-- First team member --> | + | |colspan="3"|<!-- First team member --> Lim Hui Ting |
− | |colspan="3"|<!-- Second team member --> | + | |colspan="3"|<!-- Second team member --> Jonathan Eduard Chua Lim |
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− | |width="10%"|<!-- Team --> [[ | + | |width="10%"|<!-- Team --> [[Cupid_Minions|Cupid Minions]] |
− | |colspan="3"|<!-- First team member --> | + | |colspan="3"|<!-- First team member --> Zheng Xiye |
− | |colspan="3"|<!-- Second team member --> | + | |colspan="3"|<!-- Second team member --> Yang Chengzhen |
− | |colspan="3"|<!-- Third team member --> | + | |colspan="3"|<!-- Third team member --> Liang Bing |
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Latest revision as of 08:57, 23 November 2016
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Project Groups
Please change Your Team name to your project topic and change student name to your own name
Project Team | Project Title/Description | Project Artifacts | Project Member |
---|---|---|---|
|
Visualizing Global Warming and Climate Change Recent president candidate of the US, Mr Donald Trump thinks that climate change is a hoax. That is really worrying, especially when current polls are showing that he is having a real chance in winning the election. Our team seeks to validate the climate change's truthfulness by exploring and visualizing ocean, land and weather data. Thus, we hope through this project, we settle the fact once and for all. Moreover, this serves as a tool to raise the awareness and understanding of our mother Earth's health status. How the climate has changed over time, which stage are we in and how many years does Singapore has left to stay above the sea level. |
| |
|
Visualizing Terrorism Threats & Activities The threat of terrorism is growing everyday and many countries have taken steps to mitigate the risks of terrorism. Over the past few years, there is a rise in research on terrorist organizations and the activities they have performed throughout the years. However, more still needs to be done to analyze past terrorist activities and gain insights from it easily so that all countries could better prepare for a worst case scenario. |
| |
|
Times Higher Education (THE) World University Rankings |
| |
|
Life of those who work far from home If you are staying in the east, will you be willing to travel to the west? Singapore’s increasing population and land scarcity makes urban planning increasingly relevant to policy makers. Commuter patterns give insight to assess the current situation in Singapore. In this project, we seek to uncover commuter patterns and better visualize them for easy understanding to aid formulation of policies to improve our living standards. Although many companies have been introducing various methods to eliminate commuting time, there is a proportion of people who still have to commute over long distances. (http://www.enterpriseinnovation.net/article/singapore-workers-beat-commuting-woes). Some insights to understanding commuter patterns across regions can help LTA and bus service operators to think about how to improve the bus routes. The commuters that this project mainly focuses on would be those who need to travel to work in the morning (Mon - Fri, 5-9am). |
| |
Visualization of Movie Data Is it possible to predict how good a movie will be before it even screens? This is a subjective question. While some rely on movie critics and early reviews, others depend on instinct. However, we know reviews can take a long time to gather and human instinct is simply unreliable. Thousands of movies are produced every year and all of them our clamouring for the $11 we spend on movie tickets! And this information is not just for consumers like us. The entertainment industry has always stayed strong despite economical factors. Investors are always looking for opportunities such as purchasing the rights to produce themed goods or services based on popular movies. If only looking for a deal after the movie is successful, why not predict their success and make a move first? Not stopping there, movie sponsors are getting popular these recent years. Remember the Chevrolet cars all over the Transformer movies, Bumblebee? That was marketing done right, where all eyes are fixated on the battle machines bearing a real company's brand name. But what kinds of movie should your brand appear in? Maybe through this project, we can discover some trends that may help lead to an answer. Our group wants to know which movies are worth you spending your money and time on. |
| ||
|
Who are the best NBA players? In attempt to win the championship each season, NBA teams often scout top performing players to join them. These scouts often sit in the games to monitor and evaluate players’ performances, skills and techniques. Putting all these information together, they get an overview of all the players capabilities and their standing against other players. With the rise in data and technology, there becomes a new way for scouts to evaluate players. They can leverage on this new data to get a more detailed understanding of players’ performances. For example, they would be able to know from what distance is the player most comfortable shooting from. These new insights can offer scouts a more accurate assessment on the players. |
| |
|
A Time-series Comparison and Drilldown Visualization of Economies Worldwide Ever wondered how one country's economy was doing compared to another? What about the effects of current events or economic policies over time? For the curious economist, job seeker or migrant, this visualization aims to aid you in knowing the changes in economy over time - globally, regionally and by country. We want to let you make an informed decision by:
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Email Header Analysis and Visualisation From Yahoo scanning its users’ incoming emails on behalf of FBI[1]to emails exchanges between two founders of a Syracuse development company being used in the court[2], emails are often used for investigations to uncover foul play of various types. Since many insights can be derived from human to human communication, analysing emails allow us to uncover “never before seen” patterns and correlation. Whether it is fraud or missing employees, emails can definitely provide more information about the current situation, and allow us to find out the main players in these occurrences. |
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Insights to the tourism sector The tourism is a big source of revenue for Singapore, with the total contribution of the Travel and Tourism industry making up 10.1% of the country’s GDP in year 2014. It is therefore crucial for those in the country to understand how the tourism industry is performing, as well as the effectiveness of various events in stimulating the tourism industry in the country, in order to improve the industry performance. However, available information about the industry performance is often represented in the format of data tables in the worst case, or simple line, bar or pie charts in the best of cases. These methods of visualization are often insufficient to accurately represent the complex nature of the industry, and thus provides limited utility to readers. Our group therefore intends to use various visualization methods such as high-dimensional visualization methods like tree or heat maps and time-series visualization methods like cycle plots to visualize and express important information and trends about the industry to readers. These information could be used to show the effectiveness of various strategies to boost tourism like the F1 Race, as well as to explain trends like the drop in tourism in year 2015.
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Speed Dating Experiment What influence love at the first sight? Also, what attributes influence the selection of romantic partner? These two might be the questions which most of the match making companies would like to ask. In the modern society, more and more young adults choose to attend speed dating events for seeking their possible future partners. However, not all cases are successful. Also , we are seeing the low marriage rate and increasing divorce rate issues in the developed world. One of the reasons for causing these issues is the wrong selection of marriage partner. Some couples only know that they don’t suit each other after marriage. This creates social issues like increaing divorce rate and domestic violence. Therefore, choosing the correct marriage partner is a prompt need for the young adults nowadays. In order to increase the successful matching rate for couples and make sure people can get the most satisfied partners, there is a need to understand these partner-seeking people’s characterstics, demographics, habits and lifestyle informations, etc. From the insight brought by the data, we could suggest the factors which contribute to successful and rapid matching and as a result help the partner-seekers. |
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Visualizing Air Traffic and Accidents The airplane industry is a very volatile industry. Various events can occur that would lead to the whole airline industry to go into a downward spiral. Clear examples of this events are the September 11 Terrorist Attacks and the 2009 Financial Crisis. However, how much of airline industry is affected due to commercial airplane crashes, and how badly does it affect the number of passengers travelling within the United States. In this project, our team intend to make use of data visualisation techniques to help correlate between airplane crashes and the number of passengers travelling within the United States. We intend to answer various questions such as, the impact of an airplane crash that occurred in US compared to an airplane crash that occurred outside of the US and other questions such as, what should companies do when such an incident happened.
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Visualizing Electricity Consumption in Singapore As a country with no natural resources, the government has always been vested in encouraging Singaporeans to reduce energy consumption and wastage in Singapore. For example, the National Environment Agency (NEA) has the energy label scheme which requires goods such as Air-conditioner, Refrigerator, Clothes Dryer and Television to be affixed with an energy label sticker depicting how much electricity they consume when used. More recently in August 2016, Singapore Power (SP) has redesigned the utilities bill in a bid to help fellow Singaporeans track and take steps to reduce their energy and water consumption. While there are data and statistics available on the Energy Market Authority with regards to the energy consumption by household, it is in quite a raw form with some visualization and basic interactivity to aid users in better understanding energy consumption in Singapore. The statistics or data provided also does not link to other factors such as the population demographics, which perhaps could provide interesting insights on the usage patterns of Singaporean households. As such. while these data exist, it is not being used to allow the public to visualize the energy consumption and to make sense out of it.
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UK Road Traffic Accident Visual Analysis In United Kingdom (UK), road traffic accidents have resulted in 1,732 deaths in the year 2015, which is a 2% dip as compared to the year 2014. Despite the drop in the number of deaths, the casualties across all severities remained at an alarming figure of 186,130. As there is an increasing demand for the use of public roads, there is a strong need for us to prevent road traffic accidents and make the public roads as safe as possible. In order to prevent such accidents, it is therefore crucial to understand what are the different factors that contribute to road traffic accidents, and these understandings may then be used to prevent road traffic accidents from occurring. |
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Data Visualization on NBA players' statistics and teams' performances In recent years, some NBA(National Basketball Association of America) journalists and basketball experts claimed that NBA is in a new era of game plays. Decrease in physical plays and increase in shootings has made NBA games become boring and ugly. A few of them even said NBA players had turned to be soft in defensive side. Traditional position of center has been threatened, many teams are trying to remove the role of center. Are these claims valid based on the trend of past game data? Or indeed these are wrong observations which had no link between history data. As such, this project would focus on the relationship between an NBA team's performance and player's statistics, which might directly or indirectly indicate the current NBA playing features and patterns. Additionally, we would also try to find how those good NBA teams adopt playing strategies: are they offensive oriented, defensive oriented or more balanced between offense and deffense. |
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GAStech is a Tethys-based company that operates in the natural gas production site in the island country of Kronos for at least the past 20 years. In light of their success, GAStech held a celebration for their newfound wealth in January 2014. During which, found that several of their employees had just disappeared. The scenario depicted has been derived from a 2014 VAST Challenge, a competition held annually in hopes of advancing the field of visual analytics. This project will focus on the mini challenge 2, which involves geospatial, temporal, and transaction data analysis. Even though the datasets provided are fictitious and found to be lacking in areas in terms of missing values, precision limitations and ambiguities, this level of quality is likely a common and prominent occurrence across most datasets found in real life. Nonetheless, when equipped with the appropriate tools and visualizations, critical information can be identified quickly and accurately, allowing for precise judgments and decisions by law enforcement. |
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Team | Members | |||||||||||||||||
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JJJ | Joachim Fu | Jouta Lim | James Chua | |||||||||||||||
Forensic Ninja | Lim Hui Ting | Jonathan Eduard Chua Lim | ||||||||||||||||
Cupid Minions | Zheng Xiye | Yang Chengzhen | Liang Bing |