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Hanmaeum Education Corps Invites Multicultural Families
About 100 graduates from the Multicultural Mother Schools and their families visited the KAIST campus on October 29 at the invitation of the Hanmaeum Education Corps of KAIST. The Hanmanum Education Corps is a volunteering organization composed of KAIST faculty and students. Many retired KAIST faculties are also members of the corps. Byong Kyu Choi, an Emeritus Professor from the Department of Industrial and Systems Engineering, is the director of the corps and has been leading the event since 2015. With the support of a KAIST educational volunteering organization called SEED(Social Education Embracing Diversity), this year’s event offered various activities including a treasure hunt and convergent science programs. Participants had the opportunity to experience KAIST’s educational environment and enjoyed the perfect autumn weather during outdoor activities with student volunteers. Children enjoyed making illumination-music stickers with the KAIST students, even though it was tough to learn at first. While the children engaged themselves in the science program, parents visited the chrysanthemum fair and some of KAIST’s cafeterias. Hanmaeum Education Corps opened the Multicultural Mother Schools to support multicultural mothers so that they can have more interest in and help their children more with their education. Since its establishment in 2015, the Multicultural Mother Schools have been expanding throughout the country. The corporation hopes that visiting a renowned university will encourage children from multicultural families to study hard in addition to offering self-enrichment opportunities through career exploration and science activities.
KAIST AI Academy for LG CNS Employees
The Department of Industrial & Systems Engineering (Graduate School of Knowledge Service Engineering) at KAIST has collaborated with LG CNS to start a full-fledged KAIST AI Academy course after the two-week pilot course for employees of LG CNS, a Korean company specializing in IT services. Approximately 100 employees participated in the first KAIST AI Academy course held over two weeks from August 24 to September 1. LG CNS is planning to enroll a total of 500 employees in this course by the end of the year. Artificial intelligence is widely recognized as essential technology in various industries. In that sense, the KAIST AI Academy course was established to reinforce both the AI technology and the business ability of the company. In addition, it aims at leading employees to develop new business using novel technologies. The main contents of this course are as follows: i) discussing AI technology development and its influence on industries; ii) understanding AI technologies and acquiring the major technologies applicable to business; and iii) introducing cases of AI applications and deep learning. During the course, seven professors with expertise in AI deep learning from the Department of Industrial & Systems Engineering (Graduate School of Knowledge Service Engineering), including Jae-Gil Lee and Jinkyoo Park will be leading the class, including practical on-site educational programs. Based on the accumulated business experience integrated with the latest AI technology, LG CNS has been making an effort to find new business opportunities to support companies that are hoping to make digital innovations. The company aims to reinforce the AI capabilities of its employees and is planning to upgrade the course in a sustainable manner. It will also foster outside manpower by expanding the AI education to its clients who pursue manufacturing reinforcement and innovation in digital marketing. Seong Wook Lee, the Director of the AI and Big Data Business Unit said, “As AI plays an important role in business services, LG CNS decided to open the KAIST AI Academy course to deliver better value to our clients by incorporating our AI-based business cases and KAIST’s up-to-date knowledge.”
FinTech Conference by KAIST, EDHEC-Risk Institute, Princeton, and Tsinghua
KAIST will partner with EDHEC-Risk Institute, Princeton University, and Tsinghua University to host a series of annual rotation conference on FinTech. The inaugural conference will be held in Princeton on April 26 and is entitled ‘Four-University Rotating FinTech Conference: Wealth Management Systems for Individual Investors.’ The conference will facilitate discussion among all interest parties of academics, practitioners, and regulators from around the world. Professor Woo Chang Kim of the Department of Industrial & Systems Engineering will represent KAIST. Professor Kim is also the head of the Center for Wealth Management Technologies at KAIST. In addition to Professor Kim, leading experts from the US, Asia, and Europe will present at the conference, including Andrew Yao (Turing Award recipient and founder of IIIS FinTech Center at Tsinghua University), John Bogle (founder of the Vanguard Group, and president of the Bogle Financial Markets Research Center), Lionel Martellini (director of EDHEC-Risk Institute), John Mashey (Bell Labs/Silicon Valley computer scientist/corporate executive), and John Mulvey (professor and founding member of the Bendheim Center for Finance at Princeton University). This year’s conference will feature following sessions: · Mass-Customization of Goal-Based Investment Solutions: The New Frontier in Digital Wealth Management Services · Goal-Based Investment via Multi-Stage Stochastic Goal Programming for Robo-Advisor Services · Big Data – Yesterday, Today and Tomorrow · Applying Machine Learning Concepts for Asset Allocation and ALM · FinTech: Drawing Strengths from Computing Theories · Savings and Investing to Achieve Retirement Goals: An Update Given Current Market Assumptions · The Rise of Robo-Advisors: A Threat or an Opportunity for the Wealth Management Industry? The conference will include the participation of official partner Samsung Asset Management.
Improving Traffic Safety with a Crowdsourced Traffic Violation Reporting App
KAIST researchers revealed that crowdsourced traffic violation reporting with smartphone-based continuous video capturing can dramatically change the current practice of policing activities on the road and will significantly improve traffic safety. Professor Uichin Lee of the Department of Industrial and Systems Engineering and the Graduate School of Knowledge Service Engineering at KAIST and his research team designed and evaluated Mobile Roadwatch, a mobile app that helps citizen record traffic violation with their smartphones and report the recorded videos to the police. This app supports continuous video recording just like onboard vehicle dashboard cameras. Mobile Roadwatch allows drivers to safely capture traffic violations by simply touching a smartphone screen while driving. The captured videos are automatically tagged with contextual information such as location and time. This information will be used as important evidence for the police to ticket the violators. All of the captured videos can be conveniently reviewed, allowing users to decide which events to report to the police. The team conducted a two-week field study to understand how drivers use Mobile Roadwatch. They found that the drivers tended to capture all traffic risks regardless of the level of their involvement and the seriousness of the traffic risks. However, when it came to actual reporting, they tended to report only serious traffic violations, which could have led to car accidents, such as traffic signal violations and illegal U-turns. After receiving feedback about their reports from the police, drivers typically felt very good about their contributions to traffic safety. At the same time, some drivers felt pleased to know that the offenders received tickets since they thought these offenders deserved to be ticketed. While participating in the Mobile Roadwatch campaign, drivers reported that they tried to drive as safely as possible and abide by traffic laws. This was because they wanted to be as fair as possible so that they could capture others’ violations without feeling guilty. They were also afraid that other drivers might capture their violations. Professor Lee said, “Our study participants answered that Mobile Roadwatch served as a very useful tool for reporting traffic violations, and they were highly satisfied with its features. Beyond simple reporting, our tool can be extended to support online communities, which help people actively discuss various local safety issues and work with the police and local authorities to solve these safety issues.” Korea and India were the early adaptors supporting video-based reporting of traffic violations to the police. In recent years, the number of reports has dramatically increased. For example, Korea’s ‘Looking for a Witness’ (released in April 2015) received more than half million reported violations as of November 2016. In the US, authorities started tapping into smartphone recordings by releasing video-based reporting apps such as ICE Blackbox and Mobile Justice. Professor Lee said that the existing services cannot be used while driving, because none of the existing services support continuous video recording and safe event capturing behind the wheel. Professor Lee’s team has been incorporating advanced computer vision techniques into Mobile Roadwatch for automatically capturing traffic violations and safety risks, including potholes and obstacles. The researchers will present their results in May at the ACM CHI Conference on Human Factors in Computing Systems (CHI 2017) in Denver, CO, USA. Their research was supported by the KAIST-KUSTAR fund. (Caption: A driver is trying to capture an event by touching a screen. The Mobile Radwatch supports continuous video recording and safe event captureing behind the wheel.)
A Volunteer Project by Students: The Surprise Bus!
GoGeeks, one of the undergraduate student clubs at KAIST, plans to run a bus to take volunteers to places where help is needed such as nursing homes, orphanages, and community centers. This volunteer project is called “Surprise Bus!” Students interested in participating in the project can apply online via a social funding website, http://tumblbug.com, until December 5, 2014. Up to 150 students will be selected. A total of five buses will leave from Seoul on December 20, 2014 to several places nationwide. Participants will not know their final destination until they arrive at the scene where they will work. GoGeeks was inspired by the “Do Good Bus” project, a volunteer organization that started in the US, through which people meet, and while performing their volunteer activities, they get to know each other. Bum-Kyu Lee, the President of GoGeeks, who is a senior in the Department of Industrial and Systems Engineering, said, “I’ve encountered many students who want to volunteer, but they are not sure where to go to start. The “Surprise Bus!” is a wonderful volunteer opportunity, and I think participants will have fun and, at the same time, will have a meaningful time. The Christmas season is also an excellent time to do something good for our communities and neighborhoods.”
An Exploratory Study on Smartphone Abuse among College Students
Professor Uichin Lee Professor Uichin Lee of the Department of Knowledge Service Engineering, KAIST, and his research team developed a system that automatically diagnoses the levels of smartphone addiction based on an analysis of smartphone use records. Professor Lee investigated the usage patterns of 95 smartphone users (college students) by conducting surveys and interviews and collecting logged data. The research team divided participants into “risk” and “non-risk” groups based on a self-reported rating scale to evaluate their abuse of smartphones. As a result, 36 students were categorized as “high risk” and 59 were categorized as “low risk.” The researchers collected over 50,000 hours of smartphone use encompassing power levels, screen, battery status, application use, internet use, calling, and texting. The results showed that the “high risk” group used only 1~2 applications, focusing on mobile messengers (Kakotalk, etc.) and SNS (Facebook, etc.). In addition, a relationship was found between alarm function and addiction levels. Users who set alarms for Kakaotalk messages and SNS comments used smartphones for an additional 38 minutes per day on average. Results also showed that “high risk” students were on their smartphones for 4 hours and 13 minutes per day, 46 minutes longer than “low risk” students who used smartphones for 3 hours and 27 minutes. The difference was prevalent during 6 am and noon, and 6pm and midnight. In addition, “high risk” students accessed their smartphones 11.4 times more than “low risk” students. Based on the collected data, Professor Lee developed an automatic system that distinguished users into “high risk” or “low risk” categories with 80% accuracy. The new system is expected to give an early diagnosis of addiction to smartphone users, thereby allowing for early treatment and intervention before the user becomes addicted. Professor Lee commented that, "the conventional addiction analysis based on self-analysis surveys did not provide real-time data and were largely inaccurate. The new system overcomes these limitations through data science and personal big data analysis" and that he is "developing an application that monitors smartphone abuse." Figure 1. Usage amount: overall and application-specific results Figure 2. Usage frequency: overall and application-specific results Figure 3. Overall diurnal usage time and frequency
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