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Long Economic Depressions and Disparities Loom in the Wake of the COVID-19
"Global Cooperation for Managing Data Key to Mitigating the Impacts Around the World" <Full recorded video of the GSI-IF2020> The COVID-19 pandemic will lead to long economic depressions around the entire world. Experts predicted that the prevalent inequities among the countries, regions, and individuals will aggravate the economic crisis. However, crises always come with new opportunities and international cooperation and solidarity will help creating a new normal in the post-coronavirus era. In a very basic but urgent step, global cooperation for managing data is the key to respond to COVID-19 since medicine and healthcare are intertwined with data science, said experts during an online international forum hosted by the Global Strategy Institute at KAIST on April 22. KAIST launched its think-tank, the Global Strategy Institute (GSI), in February. The GSI aims to identify global issues proactively and help make breakthroughs well aligned with solid science-based policies. The inaugural forum of the GSI focused on how the COVID-19 pandemic would impact socio-economic, scientific, and political landscapes, under the theme “Global Cooperation in the Coronavirus Era.” In his opening remarks, KAIST President Sung-Chul Shin stressed that future global governance will be dominated by the power of science and technology. “If we can implement efficient policies together with troubleshooting technology for responding to future crises, we will emerge stronger than before,” he said. President Shin said ‘the Korean model’, which is being recognized as a shining example for dealing with the pandemic, is the result of collaborations combining the creativity of the private sector, the public sector’s strong infrastructure, and the full support of the citizens. He added, “Without the technological prowess coming from the competent R&D power of Korea, we could not achieve these impressive results.” “Creative collaboration among the private and public sectors, along with research universities from around the world, will help shore up global resilience against the epidemic. We should work together to build a world of growing prosperity,” President Shin said. Prime Minister Sye-Kyun Chung, who is in charge of the Central Disaster and Safety Countermeasures Headquarters in Korea, stressed global solidarity in his welcoming remarks, saying that “We need to share information and rely on the strength of our connections, rather than retreating into nationalistic isolation.” Peter Lee, Vice President of the Microsoft Healthcare, pointed out in his welcoming remarks three critical sectors for global cooperation: medicine and healthcare, public health and prevention, and life and the economy. He emphasized the rule of thumb for managing data, saying that data in these fields should be open, standardized, and shared among countries to combat this global pandemic. During a keynote session, Director General of the International Vaccine Institute (IVI) Jerome Kim described the challenges that go along with developing a vaccine. Dr. Kim said that only 7% of vaccine candidates go through the clinical trial stages, and it will take five to 10 years to completely prove a new vaccine’s safety after completing three stages of clinical tests. “It’s very challenging to develop the vaccine for COVID-19 within 12 to 15 months,” said Dr. Kim. He added that 78 out of 115 candidates are currently undergoing clinical trials around the world. There are five groups, including Moderna, Inovio, Jenner Institute, CanSino, and the Beijing Institute of Biological Products, who are doing clinical trials in phases 1 and 2. “Given the fact that COVID-19 is a totally new type of virus, various stakeholders’ participation, such as the National Immunization Technical Advisory Groups, the WHO, and UNICEF, is needed to work together to benefit the entire world,” he pointed out. Professor Edward Yoonjae Choi from the Graduate School of AI at KAIST shared how AI and data sciences are being utilized to interpret the major trends of the epidemic. His group mainly focuses on deep learning to model electronic health records (EHR) for disease predictions. Professor Choi said AI and machine learning would be crucial solutions and collaborative research projects will surely accelerate how quickly we can overcome the pandemic. In addition, Dr. Kijung Shin’s group is interpreting the SIR (Susceptible, Infected, and Recovered) model in Korea to predict the number of infections and when people were infected. However, researchers noticed that they could not see the typical modeling in Korea for predicting the number of infections since the model disregarded the new variable of humans’ efforts to stop the spread the virus. According to research by Professor Steven Whang’s group on social distancing and face mask distribution among vulnerable age groups, people in their 20s, 60s, and 70s followed the social distancing guidelines the most strictly. The research team analyzed the data provided by SK Telecom in the Gangnam district of Seoul. The data provided on people in their 70s, a group that accounted for half of all fatalities, showed that masks were generally well distributed nationwide. Dr. Alexandros Papaspyrids, Tertiary Education Industry Director of the Asia region of Microsoft, said that despite all the disadvantages and problems related to remote education, we shouldn’t expect to return to the days before the COVID-19 any time soon. “We should accept the new normal and explore new opportunities in the new educational environment,” he said. Hongtaek Yong, Deputy Minister at the Office of R&D Policy at the Ministry of Science and ICT presented the Korean government’s disease prevention and response policy and how they tried to mitigate the economic and social impact. He stressed the government’s fast testing, tracing, and openness for successfully flattening the curve, adding that the government used an ICT-based approach in all aspects of their response. From early this year when the first patient was reported, the government aggressively encouraged the biotech industry to develop diagnostic kits and novel therapeutic medications. As a result, five companies were able to produce genetic diagnostic reagents through the emergency approval. More notably, four of them are conducting massive R&D projects sponsored by the government and this is the result of the government’s continuous investment in R&D. Korea is the leader in R&D investment among the OECD countries. According to Yong, the government’s big data project that was launched in 2017 continuously traces the trends of epidemics in Korea. The epidemiological studies based on the paths taken by suspected patients using credit card transaction made the difference in predicting the spread of the coronavirus and implementing countermeasures. The data has been provided to the Korea’s Center for Disease Control (CDC). “In addition to the epidemics, we have so many other pending issues arising from digital and social equities, un-contact services, and job security. We are very open to collaborate and cooperate with other countries to deal with this global crisis,” Yong said. During the subsequent panel discussions, David Dollar, a senior fellow at the Brookings Institution, said, “The global economy in the coronavirus era will not have a rapid V-shaped recovery, but rather will fall into a long depression for at least two years.” He pointed out that if countries practice protectionism like they did during the Great Depression, the recession will be even worse. Hence, he urged the international community, especially developed nations, to avoid protectionism, consider the economic difficulties of developing countries, and provide them with financial support. Co-Director of the Center for Universal Education at the Brookings Institution Rebecca Winthrop raised concerns over the recent shift to online teaching and learning, claiming that insufficient infrastructures in low-income families in developing nations are already causing added educational disparities and provoking the inequity issue around the world. “The ways to provide quality education equally through faster and more effective means should be studied,” she said. Professor Joungho Kim, the director of the KAIST GSI and the forum’s organizer, concluded the event by saying that this forum will be a valuable resource for everyone who is providing assistance to those in need, both during and after the COVID-19 pandemic. (END)
AI to Determine When to Intervene with Your Driving
(Professor Uichin Lee (left) and PhD candidate Auk Kim) Can your AI agent judge when to talk to you while you are driving? According to a KAIST research team, their in-vehicle conservation service technology will judge when it is appropriate to contact you to ensure your safety. Professor Uichin Lee from the Department of Industrial and Systems Engineering at KAIST and his research team have developed AI technology that automatically detects safe moments for AI agents to provide conversation services to drivers. Their research focuses on solving the potential problems of distraction created by in-vehicle conversation services. If an AI agent talks to a driver at an inopportune moment, such as while making a turn, a car accident will be more likely to occur. In-vehicle conversation services need to be convenient as well as safe. However, the cognitive burden of multitasking negatively influences the quality of the service. Users tend to be more distracted during certain traffic conditions. To address this long-standing challenge of the in-vehicle conversation services, the team introduced a composite cognitive model that considers both safe driving and auditory-verbal service performance and used a machine-learning model for all collected data. The combination of these individual measures is able to determine the appropriate moments for conversation and most appropriate types of conversational services. For instance, in the case of delivering simple-context information, such as a weather forecast, driver safety alone would be the most appropriate consideration. Meanwhile, when delivering information that requires a driver response, such as a “Yes” or “No,” the combination of driver safety and auditory-verbal performance should be considered. The research team developed a prototype of an in-vehicle conversation service based on a navigation app that can be used in real driving environments. The app was also connected to the vehicle to collect in-vehicle OBD-II/CAN data, such as the steering wheel angle and brake pedal position, and mobility and environmental data such as the distance between successive cars and traffic flow. Using pseudo-conversation services, the research team collected a real-world driving dataset consisting of 1,388 interactions and sensor data from 29 drivers who interacted with AI conversational agents. Machine learning analysis based on the dataset demonstrated that the opportune moments for driver interruption could be correctly inferred with 87% accuracy. The safety enhancement technology developed by the team is expected to minimize driver distractions caused by in-vehicle conversation services. This technology can be directly applied to current in-vehicle systems that provide conversation services. It can also be extended and applied to the real-time detection of driver distraction problems caused by the use of a smartphone while driving. Professor Lee said, “In the near future, cars will proactively deliver various in-vehicle conversation services. This technology will certainly help vehicles interact with their drivers safely as it can fairly accurately determine when to provide conversation services using only basic sensor data generated by cars.” The researchers presented their findings at the ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp’19) in London, UK. This research was supported in part by Hyundai NGV and by the Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT. (Figure: Visual description of safe enhancement technology for in-vehicle conversation services)
Tungsten Suboxide Improves the Efficiency of Platinum in Hydrogen Production
< PhD Candidate Jinkyu Park and Professor Jinwoo Lee > Researchers presented a new strategy for enhancing catalytic activity using tungsten suboxide as a single-atom catalyst (SAC). This strategy, which significantly improves hydrogen evolution reaction (HER) in metal platinum (pt) by 16.3 times, sheds light on the development of new electrochemical catalyst technologies. Hydrogen has been touted as a promising alternative to fossil fuels. However, most of the conventional industrial hydrogen production methods come with environmental issues, releasing significant amounts of carbon dioxide and greenhouse gases. Electrochemical water splitting is considered a potential approach for clean hydrogen production. Pt is one of the most commonly used catalysts to improve HER performance in electrochemical water splitting, but the high cost and scarcity of Pt remain key obstacles to mass commercial applications. SACs, where all metal species are individually dispersed on a desired support material, have been identified as one way to reduce the amount of Pt usage, as they offer the maximum number of surface exposed Pt atoms. Inspired by earlier studies, which mainly focused on SACs supported by carbon-based materials, a KAIST research team led by Professor Jinwoo Lee from the Department of Chemical and Biomolecular Engineering investigated the influence of support materials on the performance of SACs. Professor Lee and his researchers suggested mesoporous tungsten suboxide as a new support material for atomically dispersed Pt, as this was expected to provide high electronic conductivity and have a synergetic effect with Pt. They compared the performance of single-atom Pt supported by carbon and tungsten suboxide respectively. The results revealed that the support effect occurred with tungsten suboxide, in which the mass activity of a single-atom Pt supported by tungsten suboxide was 2.1 times greater than that of single-atom Pt supported by carbon, and 16.3 times higher than that of Pt nanoparticles supported by carbon. The team indicated a change in the electronic structure of Pt via charge transfer from tungsten suboxide to Pt. This phenomenon was reported as a result of strong metal-support interaction between Pt and tungsten suboxide. HER performance can be improved not only by changing the electronic structure of the supported metal, but also by inducing another support effect, the spillover effect, the research group reported. Hydrogen spillover is a phenomenon where adsorbed hydrogen migrates from one surface to another, and it occurs more easily as the Pt size becomes smaller. The researchers compared the performance of single-atom Pt and Pt nanoparticles supported by tungsten suboxide. The single-atom Pt supported by tungsten suboxide exhibited a higher degree of hydrogen spillover phenomenon, which enhanced the Pt mass activity for hydrogen evolution up to 10.7 times compared to Pt nanoparticles supported by tungsten suboxide. Professor Lee said, “Choosing the right support material is important for improving electrocatalysis in hydrogen production. The tungsten suboxide catalyst we used to support Pt in our study implies that interactions between the well-matched metal and support can drastically enhance the efficiency of the process.” This research was supported by the Ministry of Science and ICT and introduced in the International Edition of the German journal Angewandte Chemie. Figure. Schematic representation of hydrogen evolution reaction (HER) of pseudo single-atom Pt supported by tungsten suboxide Publication: Jinkyu Park, Dr. Seonggyu Lee, Hee-Eun Kim, Ara Cho, Seongbeen Kim, Dr. Youngjin Ye, Prof. Jeong Woo Han, Prof. Hyunjoo Lee, Dr. Jong Hyun Jang, and Prof. Jinwoo Lee. 2019. Investigation of the Support Effect in Atomically Dispersed Pt on WO3−x for Utilization of Pt in the Hydrogen Evolution Reaction. International Edition of Angewandte Chemie. Volume No. 58. Issue No. 45. 6 pages. https://doi.org/10.1002/anie.201908122 Link to download the full-text paper: https://onlinelibrary.wiley.com/doi/epdf/10.1002/anie.201908122 Profile: Prof. Jinwoo Lee, MS, PhD firstname.lastname@example.org http://cens.kaist.ac.kr Professor Convergence of Energy and Nano Science Laboratory Department of Chemical and Biomolecular Engineering Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea Profile: Jinkyu Park, PhD Candidate email@example.com (END)
Object Identification and Interaction with a Smartphone Knock
(Professor Lee (far right) demonstrate 'Knocker' with his students.) A KAIST team has featured a new technology, “Knocker”, which identifies objects and executes actions just by knocking on it with the smartphone. Software powered by machine learning of sounds, vibrations, and other reactions will perform the users’ directions. What separates Knocker from existing technology is the sensor fusion of sound and motion. Previously, object identification used either computer vision technology with cameras or hardware such as RFID (Radio Frequency Identification) tags. These solutions all have their limitations. For computer vision technology, users need to take pictures of every item. Even worse, the technology will not work well in poor lighting situations. Using hardware leads to additional costs and labor burdens. Knocker, on the other hand, can identify objects even in dark environments only with a smartphone, without requiring any specialized hardware or using a camera. Knocker utilizes the smartphone’s built-in sensors such as a microphone, an accelerometer, and a gyroscope to capture a unique set of responses generated when a smartphone is knocked against an object. Machine learning is used to analyze these responses and classify and identify objects. The research team under Professor Sung-Ju Lee from the School of Computing confirmed the applicability of Knocker technology using 23 everyday objects such as books, laptop computers, water bottles, and bicycles. In noisy environments such as a busy café or on the side of a road, it achieved 83% identification accuracy. In a quiet indoor environment, the accuracy rose to 98%. The team believes Knocker will open a new paradigm of object interaction. For instance, by knocking on an empty water bottle, a smartphone can automatically order new water bottles from a merchant app. When integrated with IoT devices, knocking on a bed’s headboard before going to sleep could turn off the lights and set an alarm. The team suggested and implemented 15 application cases in the paper, presented during the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2019) held in London last month. Professor Sung-Ju Lee said, “This new technology does not require any specialized sensor or hardware. It simply uses the built-in sensors on smartphones and takes advantage of the power of machine learning. It’s a software solution that everyday smartphone users could immediately benefit from.” He continued, “This technology enables users to conveniently interact with their favorite objects.” The research was supported in part by the Next-Generation Information Computing Development Program through the National Research Foundation of Korea funded by the Ministry of Science and ICT and an Institute for Information & Communications Technology Promotion (IITP) grant funded by the Ministry of Science and ICT. Figure: An example knock on a bottle. Knocker identifies the object by analyzing a unique set of responses from the knock, and automatically launches a proper application or service.
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