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Flexible User Interface Distribution for Ubiquitous Multi-Device Interaction
< Research Group of Professor Insik Shin (center) >
KAIST researchers have developed mobile software platform technology that allows a mobile application (app) to be executed simultaneously and more dynamically on multiple smart devices. Its high flexibility and broad applicability can help accelerate a shift from the current single-device paradigm to a multiple one, which enables users to utilize mobile apps in ways previously unthinkable.
Recent trends in mobile and IoT technologies in this era of 5G high-speed wireless communication have been hallmarked by the emergence of new display hardware and smart devices such as dual screens, foldable screens, smart watches, smart TVs, and smart cars. However, the current mobile app ecosystem is still confined to the conventional single-device paradigm in which users can employ only one screen on one device at a time. Due to this limitation, the real potential of multi-device environments has not been fully explored.
A KAIST research team led by Professor Insik Shin from the School of Computing, in collaboration with Professor Steve Ko’s group from the State University of New York at Buffalo, has developed mobile software platform technology named FLUID that can flexibly distribute the user interfaces (UIs) of an app to a number of other devices in real time without needing any modifications. The proposed technology provides single-device virtualization, and ensures that the interactions between the distributed UI elements across multiple devices remain intact.
This flexible multimodal interaction can be realized in diverse ubiquitous user experiences (UX), such as using live video steaming and chatting apps including YouTube, LiveMe, and AfreecaTV. FLUID can ensure that the video is not obscured by the chat window by distributing and displaying them separately on different devices respectively, which lets users enjoy the chat function while watching the video at the same time.
In addition, the UI for the destination input on a navigation app can be migrated into the passenger’s device with the help of FLUID, so that the destination can be easily and safely entered by the passenger while the driver is at the wheel.
FLUID can also support 5G multi-view apps – the latest service that allows sports or games to be viewed from various angles on a single device. With FLUID, the user can watch the event simultaneously from different viewpoints on multiple devices without switching between viewpoints on a single screen.
PhD candidate Sangeun Oh, who is the first author, and his team implemented the prototype of FLUID on the leading open-source mobile operating system, Android, and confirmed that it can successfully deliver the new UX to 20 existing legacy apps.
“This new technology can be applied to next-generation products from South Korean companies such as LG’s dual screen phone and Samsung’s foldable phone and is expected to embolden their competitiveness by giving them a head-start in the global market.” said Professor Shin.
This study will be presented at the 25th Annual International Conference on Mobile Computing and Networking (ACM MobiCom 2019) October 21 through 25 in Los Cabos, Mexico. The research was supported by the National Science Foundation (NSF) (CNS-1350883 (CAREER) and CNS-1618531).
Figure 1. Live video streaming and chatting app scenario
Figure 2. Navigation app scenario
Figure 3. 5G multi-view app scenario
Publication: Sangeun Oh, Ahyeon Kim, Sunjae Lee, Kilho Lee, Dae R. Jeong, Steven Y. Ko, and Insik Shin. 2019. FLUID: Flexible User Interface Distribution for Ubiquitous Multi-device Interaction. To be published in Proceedings of the 25th Annual International Conference on Mobile Computing and Networking (ACM MobiCom 2019). ACM, New York, NY, USA. Article Number and DOI Name TBD.
Video Material:
https://youtu.be/lGO4GwH4enA
Profile: Prof. Insik Shin, MS, PhD
ishin@kaist.ac.kr
https://cps.kaist.ac.kr/~ishin
Professor
Cyber-Physical Systems (CPS) Lab
School of Computing
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr Daejeon 34141, Korea
Profile: Sangeun Oh, PhD Candidate
ohsang1213@kaist.ac.kr
https://cps.kaist.ac.kr/
PhD Candidate
Cyber-Physical Systems (CPS) Lab
School of Computing
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr Daejeon 34141, Korea
Profile: Prof. Steve Ko, PhD
stevko@buffalo.edu
https://nsr.cse.buffalo.edu/?page_id=272
Associate Professor
Networked Systems Research Group
Department of Computer Science and Engineering
State University of New York at Buffalo
http://www.buffalo.edu/ Buffalo 14260, USA
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2019.07.20 View 40800 -
Deciphering Brain Somatic Mutations Associated with Alzheimer's Disease
Researchers have found a potential link between non-inherited somatic mutations in the brain and the progression of Alzheimer’s disease
Researchers have identified somatic mutations in the brain that could contribute to the development of Alzheimer’s disease (AD). Their findings were published in the journal Nature Communications last week.
Decades worth of research has identified inherited mutations that lead to early-onset familial AD. Inherited mutations, however, are behind at most half the cases of late onset sporadic AD, in which there is no family history of the disease. But the genetic factors causing the other half of these sporadic cases have been unclear.
Professor Jeong Ho Lee at the Graduate School of Medical Science and Engineering and colleagues analysed the DNA present in post-mortem hippocampal formations and in blood samples from people aged 70 to 96 with AD and age-matched controls. They specifically looked for non-inherited somatic mutations in their brains using high-depth whole exome sequencing.
The team developed a bioinformatics pipeline that enabled them to detect low-level brain somatic single nucleotide variations (SNVs) – mutations that involve the substitution of a single nucleotide with another nucleotide. Brain somatic SNVs have been reported on and accumulate throughout our lives and can sometimes be associated with a range of neurological diseases.
The number of somatic SNVs did not differ between individuals with AD and non-demented controls. Interestingly, somatic SNVs in AD brains arise about 4.8 times more slowly than in blood. When the team performed gene-set enrichment tests, 26.9 percent of the AD brain samples had pathogenic brain somatic SNVs known to be linked to hyperphosphorylation of tau proteins, which is one of major hallmarks of AD.
Then, they pinpointed a pathogenic SNV in the PIN1 gene, a cis/trans isomerase that balances phosphorylation in tau proteins, found in one AD patient’s brain. They found the mutation was 4.9 time more abundant in AT8-positive – a marker for hyper-phosphorylated tau proteins– neurons in the entorhinal cortex than the bulk hippocampal tissue. Furthermore, in a series of functional assays, they observed the mutation causing a loss of function in PIN1 and such haploinsufficiency increased the phosphorylation and aggregation of tau proteins.
“Our study provides new insights into the molecular genetic factors behind Alzheimer’s disease and other neurodegenerative diseases potentially linked to somatic mutations in the brain,” said Professor Lee.
The team is planning to expand their study to a larger cohort in order to establish stronger links between these brain somatic mutations and the pathogenesis of Alzheimer’s disease.
(Figure 1. Bioinformatic pipeline for detecting low-level brain somatic mutations in AD and non-AD.)
(Figure 2. Pathogenic brain somatic mutations associated with tau phosphorylation are significantly enriched in AD brains.)
(Figure 3. A pathogenic brain somatic mutation in PIN1 (c. 477 C>T) is a loss-of-function and related functional assays show its haploinsufficiency increases phosphorylation and aggregation of tau.)
2019.07.19 View 36796 -
High-Performance Sodium Ion Batteries Using Copper Sulfide
(Prof.Yuk and his two PhD candidates Parks)
Researchers presented a new strategy for extending sodium ion batteries’ cyclability using copper sulfide as the electrode material. This strategy has led to high-performance conversion reactions and is expected to advance the commercialization of sodium ion batteries as they emerge as an alternative to lithium ion batteries.
Professor Jong Min Yuk’s team confirmed the stable sodium storage mechanism using copper sulfide, a superior electrode material that is pulverization-tolerant and induces capacity recovery. Their findings suggest that when employing copper sulfide, sodium ion batteries will have a lifetime of more than five years with one charge per a day. Even better, copper sulfide, composed of abundant natural materials such as copper and sulfur, has better cost competitiveness than lithium ion batteries, which use lithium and cobalt.
Intercalation-type materials such as graphite, which serve as commercialized anode materials in lithium ion batteries, have not been viable for high-capacity sodium storage due to their insufficient interlayer spacing. Thus, conversion and alloying reactions type materials have been explored to meet higher capacity in the anode part. However, those materials generally bring up large volume expansions and abrupt crystallographic changes, which lead to severe capacity degradation.
The team confirmed that semi-coherent phase interfaces and grain boundaries in conversion reactions played key roles in enabling pulverization-tolerant conversion reactions and capacity recovery, respectively.
Most of conversion and alloying reactions type battery materials usually experience severe capacity degradations due to having completely different crystal structures and large volume expansion before and after the reactions. However, copper sulfides underwent a gradual crystallographic change to make the semi-coherent interfaces, which eventually prevented the pulverization of particles. Based on this unique mechanism, the team confirmed that copper sulfide exhibits a high capacity and high cycling stability regardless of its size and morphology.
Professor Yuk said, “Sodium ion batteries employing copper sulfide can advance sodium ion batteries, which could contribute to the development of low-cost energy storage systems and address the micro-dust issue”
This study was posted in Advanced Science on April 26 online and selected as the inside back cover for June issue.
(Figure: Schematic model demonstrating grain boundaries and phase interfaces formations.)
2019.07.15 View 28828 -
Two Alumni Win the Korea Best Scientist and Technologist Awards
Vice Chairman Ki-Nam Kim (Left) and Distinguished Professor Sukbok Chang (Right)
<ⓒ Photo by MSIT and KOFST>
Distinguished KAIST Professor Sukbok Chang from the Department of Chemistry and Vice Chairman Ki-Nam Kim of Samsung Electronics were selected as the winners of the “2019 Korea Best Scientist and Technologist Awards” by the Ministry of Science and ICT (MSIT) and the Korean Federation of Science and Technology Societies (KOFST). The awards, which were first handed out in 2003, are the highest honor bestowed to the two most outstanding scientists in Korea every year, and this year’s awardees are of greater significance as they are both KAIST alumni.
Professor Chang was recognized for his pioneering achievements and lifetime contributions to the development of carbon-hydrogen activation strategies, especially for carbon-carbon, carbon-nitrogen, and carbon-oxygen formations. His research group has also been actively involved in the development of highly selective catalytic systems allowing the controlled defunctionalization of bio-derived platform substrates under mild conditions, and opening a new avenue for the utilization of biomass-derived platform chemicals. The results of his study have been introduced worldwide through many prestigious journals including Science, Nature Chemistry, and Nature Catalysis, making him one of the world's top 1% researchers by the number of references made to his papers by his peers over four consecutive years from 2015 to 2018.
Vice Chairman Kim, who received his M.E. degree from KAIST’s School of Electrical Engineering in 1983, has been credited with playing a leading role in the development of system semiconductors.
The awards were conferred on July 4 at the opening ceremony of the 2019 Korea Science and Technology Annual Meeting.
(END)
2019.07.09 View 13205 -
Anti-drone Technology for Anti-Terrorism Applications
(from top right clockwise: Professor Yongdae Kim,
PhD Candidates Yujin Kwon, Juhwan Noh, Hocheol Shin, and Dohyun Kim)
KAIST researchers have developed anti-drone technology that can hijack other drones by spoofing its location using fake GPS signals. This technology can safely guide a drone to a desired location without any sudden change in direction in emergency situations, and thus respond effectively to dangerous drones such as those intending to carry out acts of terrorism.
Advancements in the drone industry have led to the wider use of drones in our daily lives in areas of reconnaissance, searching and rescuing, disaster prevention and response, and delivery services. At the same time, there has also been a growing concern about privacy, safety, and security issues regarding drones, especially those arising from intrusion into private property and secure facilities. Therefore, the anti-drone industry is rapidly expanding to detect and respond to this possible drone invasion.
The current anti-drone systems used in airports and other key locations utilize electronic jamming signals, high-power lasers, or nets to neutralize drones. For example, drones trespassing on airports are often countered with simple jamming signals that can prevent the drones from moving and changing position, but this may result in a prolonged delay in flight departures and arrivals at the airports. Drones used for terrorist attacks – armed with explosives or weapons – must also be neutralized a safe distance from the public and vital infrastructure to minimize any damage.
Due to this need for a new anti-drone technology to counter these threats, a KAIST research team led by Professor Yongdae Kim from the School of Electrical Engineering has developed technology that securely thwarts drones by tricking them with fake GPS signals.
Fake GPS signals have been used in previous studies to cause confusion inside the drone regarding its location, making the drone drift from its position or path. However, such attack tactics cannot be applied in GPS safety mode. GPS safety mode is an emergency mode that ensures drone safety when the signal is cut or location accuracy is low due to a fake GPS signals. This mode differs between models and manufacturers.
Professor Kim’s team analyzed the GPS safety mode of different drone models made from major drone manufacturers such as DJI and Parrot, made classification systems, and designed a drone abduction technique that covers almost all the types of drone GPS safety modes, and is universally applicable to any drone that uses GPS regardless of model or manufacturer. The research team applied their new technique to four different drones and have proven that the drones can be safely hijacked and guided to the direction of intentional abduction within a small margin of error.
Professor Kim said, “Conventional consumer drones equipped with GPS safety mode seem to be safe from fake GPS signals, however, most of these drones are able to be detoured since they detect GPS errors in a rudimentary manner.” He continued, “This technology can contribute particularly to reducing damage to airports and the airline industry caused by illegal drone flights.”
The research team is planning to commercialize the developed technology by applying it to existing anti-drone solutions through technology transfer.” This research, featured in the ACM Transactions on Privacy and Security (TOPS) on April 9, was supported by the Defense Acquisition Program Administration (DAPA) and the Agency for Defense Development (ADD).
Image 1.
Experimental environment in which a fake GPS signal was produced from a PC and injected into the drone signal using directional antennae
Publication:
Juhwan Noh, Yujin Kwon, Yunmok Son, Hocheol Shin, Dohyun Kim, Jaeyeong Choi, and Yongdae Kim. 2019. Tractor Beam: Safe-hijacking of Consumer Drones with Adaptive GPS Spoofing. ACM Transactions on Privacy and Security. New York, NY, USA, Vol. 22, No. 2, Article 12, 26 pages. https://doi.org/10.1145/3309735
Profile: Prof. Yongdae Kim, MS, PhD
yongdaek@kaist.ac.kr
https://www.syssec.kr/
Professor
School of Electrical Engineering
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr Daejeon 34141, Korea
Profile: Juhwan Noh, PhD Candidate
juhwan@kaist.ac.kr
PhD Candidate
System Security (SysSec) Lab
School of Electrical Engineering
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr Daejeon 34141, Korea
(END)
2019.06.25 View 44832 -
Play Games With No Latency
One of the most challenging issues for game players looks to be resolved soon with the introduction of a zero-latency gaming environment. A KAIST team developed a technology that helps game players maintain zero-latency performance. The new technology transforms the shapes of game design according to the amount of latency.
Latency in human-computer interactions is often caused by various factors related to the environment and performance of the devices, networks, and data processing. The term ‘lag’ is used to refer to any latency during gaming which impacts the user’s performance.
Professor Byungjoo Lee at the Graduate School of Culture Technology in collaboration with Aalto University in Finland presented a mathematical model for predicting players' behavior by understanding the effects of latency on players. This cognitive model is capable of predicting the success rate of a user when there is latency in a 'moving target selection' task which requires button input in a time constrained situation.
The model predicts the players’ task success rate when latency is added to the gaming environment. Using these predicted success rates, the design elements of the game are geometrically modified to help players maintain similar success rates as they would achieve in a zero-latency environment. In fact, this research succeeded in modifying the pillar heights of the Flappy Bird game, allowing the players to maintain their gaming performance regardless of the added latency.
Professor Lee said, "This technique is unique in the sense that it does not interfere with a player's gaming flow, unlike traditional methods which manipulate the game clock by the amount of latency. This study can be extended to various games such as reducing the size of obstacles in the latent computing environment.”
This research, in collaboration with Dr. Sunjun Kim from Aalto University and led by PhD candidate Injung Lee, was presented during the 2019 CHI Conference on Human Factors in Computing Systems last month in Glasgow in the UK.
This research was supported by the National Research Foundation of Korea (NRF) (2017R1C1B2002101, 2018R1A5A7025409), and the Aalto University Seed Funding Granted to the GamerLab respectively.
Figure 1. Overview of Geometric Compensation
Publication:
Injung Lee, Sunjun Kim, and Byungjoo Lee. 2019. Geometrically Compensating Effect of End-to-End Latency in Moving-Target Selection Games. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI’19) . ACM, New York, NY, USA, Article 560, 12 pages. https://doi.org/10.1145/3290605.3300790
Video Material:
https://youtu.be/TTi7dipAKJs
Profile: Prof. Byungjoo Lee, MD, PhD
byungjoo.lee@kaist.ac.kr
http://kiml.org/
Assistant Professor
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr Daejeon 34141, Korea
Profile: Injung Lee, PhD Candidate
edndn@kaist.ac.kr
PhD Candidate
Interactive Media Lab
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr
Daejeon 34141, Korea
Profile: Postdoc. Sunjun Kim, MD, PhD
kuaa.net@gmail.com
Postdoctoral Researcher
User Interfaces Group
Aalto University
https://www.aalto.fi Espoo 02150, Finland
(END)
2019.06.11 View 47654 -
Autophagy in Dendritic Cells Helps Anticancer Activity
Autophagy contributes to the homeostasis of a cell and recently another function of autophagy has been reported. A KAIST research team found that the autophagy of dendritic cells supports T-cell anticancer activity.
Autophagy is a process of maintaining cell homeostasis by removing cellular waste and damaged cellular organelles; nevertheless, its role in the presentation of phagocytized tumor-associated antigens remains vague.
Meanwhile, dendritic cells are the ones that recognize pathogens or cancer antigens, and induce immune responses in T cells. When cancer cells are killed by radiation or an anticancer drug, dendritic cells absorb and remove them and present antigens on their surface to transfer them to T-cells.
Professor Heung Kyu Lee from the Graduate School of Medical Science and Engineering and his team found that the autophagy of dendritic cells plays a key role in T-cell activation and they proposed the principles of enhancing anti-cancer effects.
Their experiments showed that T-cell activation of dendritic cells as well as anticancer immune response dropped when there is a deficiency of Atg5 (autophagy-related) in dendritic cells.
Interestingly, Atg5-deficient dendritic cells significantly elevated receptor CD36 on the surface of the cells, which increased the phagocytosis of apoptotic tumor cells yet restricted the activation of T-cells.
At this time, when introducing antibodies into the system in order to block the receptor CD36, the anti-tumor T-cell response increased substantially while tumor growth declined.
Professor Lee said, “This study allowed us to explore the role of autophagy in the anti-cancer immune response of T-cells. We look forward to developing targeted anti-cancer therapies using the receptor CD36.”
This research was published in Autophagy (10.1080/15548627.2019.1596493) on March 22, 2019.
Figure 1.Mechanism of autophagy in dendritic cells
Figure 2. A role of autophagy in dendritic cells
2019.05.13 View 51582 -
The Future Mobility of the Year 2019
KAIST announced the Future Mobility of the Year (FMOTY) 2019. The winners are Volvo 360C, Toyota e-Palette, and Toyota Concept-i WALK.
FMOTY are the first awards that recognizes concept cars that exhibit innovative services and practical transportation technology in three categories: private mobility, public and commercial mobility, and personal mobility.
Figure 1. The winner in the private mobility division, the Volvo 360C
In the private mobility division, the award went to the Volvo 360C. With targeted routes of roughly 186 miles, this vehicle has an ambitious service goal to replace airplanes by traveling these routes with great comfort. Goro Okazaki, a journalist with Car and Driver Japan, said, “The Volvo 360C clearly shows how highly personalized autonomous driving can change the future.”
Figure 2. The winner in the public mobility division, the Toyota e-Palette
The Toyota e-Palette was the winning car in commercial mobility division. This vehicle provides the best solution as a mobile service platform by transforming itself into mobile hospitals, hotels, stores and food trucks. Carlo Calderón, a journalist for Autopista Spain, said, “It has a great strength in remodeling its indoor and outdoor spaces according to various commercial uses.”
Figure 3. The winner in the personal mobility division, the Toyota Concept-i WALK
In the personal mobility division, the award went to the Toyota Concept-i WALK. It was recognized for having an exquisite user environment and artificial intelligent agent, along with an excellent completion. Jun Miao, a journalist with MJ CarShow China, said, “It is aesthetically pleasing. Beyond the upright control of conventional personal mobility, it allows agile control with a joystick.”
FMOTY conducted a screening process for 45 concept cars over three months and 16 renowned automotive experts from 11 countries participated as judges for this award, including Editor in Chief of BBC Top Gear Magazine Charlie Turner and European Bureau Chief of Automobile Magazine Georg Kacher. The judges said that FMOTY was born to propose a new aspect of future mobility, and in terms of evaluating technical and social values of concept cars, FMOTY carries great significance.
Kyung-soo Kim, Dean of the Cho Chun Shik Graduate School of Green Transportation said, “Globally renowned experts in the automotive field participated as judges to elevate the prestige and fairness of the awards. KAIST members were excluded from the entire judging process. I believe that the FMOTY Awards will expand public attention from the present to the future.”
Details can be found on the official website of FMOTY ( www.fmoty.org ).
2019.03.11 View 7705 -
Noninvasive Light-Sensitive Recombinase for Deep Brain Genetic Manipulation
A KAIST team presented a noninvasive light-sensitive photoactivatable recombinase suitable for genetic manipulation in vivo. The highly light-sensitive property of photoactivatable Flp recombinase will be ideal for controlling genetic manipulation in deep mouse brain regions by illumination with a noninvasive light-emitting diode. This easy-to-use optogenetic module made by Professor Won Do Heo and his team will provide a side-effect free and expandable genetic manipulation tool for neuroscience research.
Spatiotemporal control of gene expression has been acclaimed as a valuable strategy for identifying functions of genes with complex neural circuits. Studies of complex brain functions require highly sophisticated and robust technologies that enable specific labeling and rapid genetic modification in live animals. A number of approaches for controlling the activity of proteins or expression of genes in a spatiotemporal manner using light, small molecules, hormones, and peptides have been developed for manipulating intact circuits or functions.
Among them, recombination-employing, chemically inducible systems are the most commonly used in vivo gene-modification systems. Other approaches include selective or conditional Cre-activation systems within subsets of green fluorescent protein-expressing cells or dual-promoter-driven intersectional populations of cells.
However, these methods are limited by the considerable time and effort required to establish knock-in mouse lines and by constraints on spatiotemporal control, which relies on a limited set of available genetic promoters and transgenic mouse resources.
Beyond these constraints, optogenetic approaches allow the activity of genetically defined neurons in the mouse brain to be controlled with high spatiotemporal resolution. However, an optogenetic module for gene-manipulation capable of revealing the spatiotemporal functions of specific target genes in the mouse brain has remained a challenge.
In the study published at Nature Communication on Jan. 18, the team featured photoactivatable Flp recombinase by searching out split sites of Flp recombinase that were not previously identified, being capable of reconstitution to be active. The team validated the highly light-sensitive, efficient performance of photoactivatable Flp recombinase through precise light targeting by showing transgene expression within anatomically confined mouse brain regions.
The concept of local genetic labeling presented here suggests a new approach for genetically identifying subpopulations of cells defined by the spatial and temporal characteristics of light delivery. To date, an optogenetic module for gene-manipulation capable of revealing spatiotemporal functions of specific target genes in the mouse brain has remained out of reach and no such light-inducible Flp system has been developed. Accordingly, the team sought to develop a photoactivatable Flp recombinase that takes full advantage of the high spatiotemporal control offered by light stimulation.
This activation through noninvasive light illumination deep inside the brain is advantageous in that it avoids chemical or optic fiber implantation-mediated side effects, such as off-target cytotoxicity or physical lesions that might influence animal physiology or behaviors. The technique provides expandable utilities for transgene expression systems upon Flp recombinase activity in vivo, by designing a viral vector for minimal leaky expression influenced by viral nascent promoters.
The team demonstrated the utility of PA-Flp as a noninvasive in vivo optogenetic manipulation tool for use in the mouse brain, even applicable for deep brain structures as it can reach the hippocampus or medial septum using external LED light illumination.
The study is the result of five years of research by Professor Heo, who has led the bio-imaging and optogenetics fields by developing his own bio-imaging and optogenetics technologies. “It will be a great advantage to control specific gene expression desired by LEDs with little physical and chemical stimulation that can affect the physiological phenomenon in living animals,” he explained.
2019.01.22 View 7696 -
AI ｜QC ITRC Opens at KAIST
(from left: Dean of College of Engineering Jong-Hwan Kim, Director of AI│QC ITRC June-Koo Rhee, Vice President for R&DB Heekyung Park and Director General for Industrial Policy Hong Taek Yong)
Artificial Intelligence｜The Quantum Computing Information Technology Research Center (AI｜QC ITRC) opened at KAIST on October 2.
AI｜QC ITRC, established with government funding, is the first institute specializing in quantum computing. Three universities (Seoul National University, Korea University, and Kyung Hee University), and four corporations, KT, Homomicus, Actusnetworks, and Mirae Tech are jointly participating in the center. Over four years, the institute will receive 3.2 billion KRW of research funds.
Last April, KAIST selected quantum technology as one of its flagship research areas. AI｜QC ITRC will dedicate itself to developing quantum computing technology that provides the computability required for human-level artificial intelligence. It will also foster leaders in related industries by introducing industry-academic educational programs in graduate schools.
QC is receiving a great deal of attention for transcending current digital computers in terms of computability. World-class IT companies like IBM, Google, and Intel and ventures including D-Wave, Rigetti, and IonQ are currently leading the industry and investing heavily in securing source technologies.
Starting from the establishment of the ITRC, KAIST will continue to plan strategies to foster the field of QC. KAIST will carry out two-track strategies; one is to secure source technology of first-generation QC technology, and the other is to focus on basic research that can preoccupy next-generation QC technology.
Professor June-Koo Rhee, the director of AI│QC ITRC said, “I believe that QC will be the imperative technology that enables the realization of the Fourth Industrial Revolution. AIQC ITRC will foster experts required for domestic academia and industries and build a foundation to disseminate the technology to industries.”
Vice President for R&DB Heekyung Park, Director General for Industrial Policy Hong Taek Yong from the Ministry of Science and ICT, Seung Pyo Hong from the Institute for Information & communications Technology Promotion, Head of Technology Strategy Jinhyon Youn from KT, and participating companies attended and celebrated the opening of the AI│QC ITRC.
2018.10.05 View 7300 -
The 1st Korea Toray Science and Technology Awardee, Prof. Sukbok Chang
(Distinguished Professor Sukbok Chang from the Department of Chemistry)
The Korea Toray Science Foundation (KTSF) awarded the first Korea Toray Science Technology Award in basic science to Distinguished Professor Sukbok Chang from the Department of Chemistry on September 19.
KTSF was established in January 2018, and its award goes to researchers who have significantly contributed to the development of chemistry and materials research with funds to support research projects.
Distinguished Professor Chang has devoted himself in organocatalysis research; in particular, his work on catalysts for effective lactam formation, which was an intricate problem, received great attention.
The award ceremony will take place in The Federation of Korean Industries Hall on October 31. KTFS board members, judges, and the CEO of Toray Industries Akihiro Nikkaku will attend the ceremony. Also, Dr. Ryoji Noyori, the Nobel Laureate in Chemistry, will give a talk on the role of chemistry and creative challenges as a researcher.
2018.10.04 View 9538 -
Deep Learning Predicts Drug-Drug and Drug-Food Interactions
A Korean research team from KAIST developed a computational framework, DeepDDI, that accurately predicts and generates 86 types of drug-drug and drug-food interactions as outputs of human-readable sentences, which allows in-depth understanding of the drug-drug and drug-food interactions.
Drug interactions, including drug-drug interactions (DDIs) and drug-food constituent interactions (DFIs), can trigger unexpected pharmacological effects, including adverse drug events (ADEs), with causal mechanisms often unknown. However, current prediction methods do not provide sufficient details beyond the chance of DDI occurrence, or require detailed drug information often unavailable for DDI prediction.
To tackle this problem, Dr. Jae Yong Ryu, Assistant Professor Hyun Uk Kim and Distinguished Professor Sang Yup Lee, all from the Department of Chemical and Biomolecular Engineering at Korea Advanced Institute of Science and Technology (KAIST), developed a computational framework, named DeepDDI, that accurately predicts 86 DDI types for a given drug pair. The research results were published online in Proceedings of the National Academy of Sciences of the United States of America (PNAS) on April 16, 2018, which is entitled “Deep learning improves prediction of drug-drug and drug-food interactions.”
DeepDDI takes structural information and names of two drugs in pair as inputs, and predicts relevant DDI types for the input drug pair. DeepDDI uses deep neural network to predict 86 DDI types with a mean accuracy of 92.4% using the DrugBank gold standard DDI dataset covering 192,284 DDIs contributed by 191,878 drug pairs. Very importantly, DDI types predicted by DeepDDI are generated in the form of human-readable sentences as outputs, which describe changes in pharmacological effects and/or the risk of ADEs as a result of the interaction between two drugs in pair. For example, DeepDDI output sentences describing potential interactions between oxycodone (opioid pain medication) and atazanavir (antiretroviral medication) were generated as follows: “The metabolism of Oxycodone can be decreased when combined with Atazanavir”; and “The risk or severity of adverse effects can be increased when Oxycodone is combined with Atazanavir”. By doing this, DeepDDI can provide more specific information on drug interactions beyond the occurrence chance of DDIs or ADEs typically reported to date.
DeepDDI was first used to predict DDI types of 2,329,561 drug pairs from all possible combinations of 2,159 approved drugs, from which DDI types of 487,632 drug pairs were newly predicted. Also, DeepDDI can be used to suggest which drug or food to avoid during medication in order to minimize the chance of adverse drug events or optimize the drug efficacy. To this end, DeepDDI was used to suggest potential causal mechanisms for the reported ADEs of 9,284 drug pairs, and also predict alternative drug candidates for 62,707 drug pairs having negative health effects to keep only the beneficial effects. Furthermore, DeepDDI was applied to 3,288,157 drug-food constituent pairs (2,159 approved drugs and 1,523 well-characterized food constituents) to predict DFIs. The effects of 256 food constituents on pharmacological effects of interacting drugs and bioactivities of 149 food constituents were also finally predicted. All these prediction results can be useful if an individual is taking medications for a specific (chronic) disease such as hypertension or diabetes mellitus type 2.
Distinguished Professor Sang Yup Lee said, “We have developed a platform technology DeepDDI that will allow precision medicine in the era of Fourth Industrial Revolution. DeepDDI can serve to provide important information on drug prescription and dietary suggestions while taking certain drugs to maximize health benefits and ultimately help maintain a healthy life in this aging society.”
Figure 1. Overall scheme of Deep DDDI and prediction of food constituents that reduce the in vivo concentration of approved drugs
2018.04.18 View 12636