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To Talk or Not to Talk: Smart Speaker Determines Optimal Timing to Talk
A KAIST research team has developed a new context-awareness technology that enables AI assistants to determine when to talk to their users based on user circumstances. This technology can contribute to developing advanced AI assistants that can offer pre-emptive services such as reminding users to take medication on time or modifying schedules based on the actual progress of planned tasks.
Unlike conventional AI assistants that used to act passively upon users’ commands, today’s AI assistants are evolving to provide more proactive services through self-reasoning of user circumstances. This opens up new opportunities for AI assistants to better support users in their daily lives. However, if AI assistants do not talk at the right time, they could rather interrupt their users instead of helping them.
The right time for talking is more difficult for AI assistants to determine than it appears. This is because the context can differ depending on the state of the user or the surrounding environment.
A group of researchers led by Professor Uichin Lee from the KAIST School of Computing identified key contextual factors in user circumstances that determine when the AI assistant should start, stop, or resume engaging in voice services in smart home environments. Their findings were published in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) in September.
The group conducted this study in collaboration with Professor Jae-Gil Lee’s group in the KAIST School of Computing, Professor Sangsu Lee’s group in the KAIST Department of Industrial Design, and Professor Auk Kim’s group at Kangwon National University.
After developing smart speakers equipped with AI assistant function for experimental use, the researchers installed them in the rooms of 40 students who live in double-occupancy campus dormitories and collected a total of 3,500 in-situ user response data records over a period of a week.
The smart speakers repeatedly asked the students a question, “Is now a good time to talk?” at random intervals or whenever a student’s movement was detected. Students answered with either “yes” or “no” and then explained why, describing what they had been doing before being questioned by the smart speakers.
Data analysis revealed that 47% of user responses were “no” indicating they did not want to be interrupted. The research team then created 19 home activity categories to cross-analyze the key contextual factors that determine opportune moments for AI assistants to talk, and classified these factors into ‘personal,’ ‘movement,’ and ‘social’ factors respectively.
Personal factors, for instance, include:
1. the degree of concentration on or engagement in activities,
2. the degree urgency and busyness,
3. the state of user’s mental or physical condition, and
4. the state of being able to talk or listen while multitasking.
While users were busy concentrating on studying, tired, or drying hair, they found it difficult to engage in conversational interactions with the smart speakers.
Some representative movement factors include departure, entrance, and physical activity transitions. Interestingly, in movement scenarios, the team found that the communication range was an important factor. Departure is an outbound movement from the smart speaker, and entrance is an inbound movement. Users were much more available during inbound movement scenarios as opposed to outbound movement scenarios.
In general, smart speakers are located in a shared place at home, such as a living room, where multiple family members gather at the same time. In Professor Lee’s group’s experiment, almost half of the in-situ user responses were collected when both roommates were present. The group found social presence also influenced interruptibility. Roommates often wanted to minimize possible interpersonal conflicts, such as disturbing their roommates' sleep or work.
Narae Cha, the lead author of this study, explained, “By considering personal, movement, and social factors, we can envision a smart speaker that can intelligently manage the timing of conversations with users.”
She believes that this work lays the foundation for the future of AI assistants, adding, “Multi-modal sensory data can be used for context sensing, and this context information will help smart speakers proactively determine when it is a good time to start, stop, or resume conversations with their users.”
This work was supported by the National Research Foundation (NRF) of Korea.
Publication:
Cha, N, et al. (2020) “Hello There! Is Now a Good Time to Talk?”: Opportune Moments for Proactive Interactions with Smart Speakers. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Vol. 4, No. 3, Article No. 74, pp. 1-28. Available online at https://doi.org/10.1145/3411810
Link to Introductory Video:
https://youtu.be/AA8CTi2hEf0
Profile:
Uichin Lee
Associate Professor
uclee@kaist.ac.kr
http://ic.kaist.ac.kr
Interactive Computing Lab.
School of Computing
https://www.kaist.ac.kr
Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea
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2020.11.05 View 11958 -
Chemical Scissors Snip 2D Transition Metal Dichalcogenides into Nanoribbon
New ‘nanoribbon’ catalyst should slash cost of hydrogen production for clean fuels
Researchers have identified a potential catalyst alternative – and an innovative way to produce them using chemical ‘scissors’ – that could make hydrogen production more economical.
The research team led by Professor Sang Ouk Kim at the Department of Materials Science and Engineering published their work in Nature Communications.
Hydrogen is likely to play a key role in the clean transition away from fossil fuels and other processes that produce greenhouse gas emissions. There is a raft of transportation sectors such as long-haul shipping and aviation that are difficult to electrify and so will require cleanly produced hydrogen as a fuel or as a feedstock for other carbon-neutral synthetic fuels. Likewise, fertilizer production and the steel sector are unlikely to be “de-carbonized” without cheap and clean hydrogen.
The problem is that the cheapest methods by far of producing hydrogen gas is currently from natural gas, a process that itself produces the greenhouse gas carbon dioxide–which defeats the purpose.
Alternative techniques of hydrogen production, such as electrolysis using an electric current between two electrodes plunged into water to overcome the chemical bonds holding water together, thereby splitting it into its constituent elements, oxygen and hydrogen are very well established. But one of the factors contributing to the high cost, beyond being extremely energy-intensive, is the need for the very expensive precious and relatively rare metal platinum. The platinum is used as a catalyst–a substance that kicks off or speeds up a chemical reaction–in the hydrogen production process.
As a result, researchers have long been on the hunt for a substitution for platinum -- another catalyst that is abundant in the earth and thus much cheaper.
Transition metal dichalcogenides, or TMDs, in a nanomaterial form, have for some time been considered a good candidate as a catalyst replacement for platinum. These are substances composed of one atom of a transition metal (the elements in the middle part of the periodic table) and two atoms of a chalcogen element (the elements in the third-to-last column in the periodic table, specifically sulfur, selenium and tellurium).
What makes TMDs a good bet as a platinum replacement is not just that they are much more abundant, but also their electrons are structured in a way that gives the electrodes a boost.
In addition, a TMD that is a nanomaterial is essentially a two-dimensional super-thin sheet only a few atoms thick, just like graphene. The ultrathin nature of a 2-D TMD nanosheet allows for a great many more TMD molecules to be exposed during the catalysis process than would be the case in a block of the stuff, thus kicking off and speeding up the hydrogen-making chemical reaction that much more.
However, even here the TMD molecules are only reactive at the four edges of a nanosheet. In the flat interior, not much is going on. In order to increase the chemical reaction rate in the production of hydrogen, the nanosheet would need to be cut into very thin – almost one-dimensional strips, thereby creating many edges.
In response, the research team developed what are in essence a pair of chemical scissors that can snip TMD into tiny strips.
“Up to now, the only substances that anyone has been able to turn into these ‘nano-ribbons’ are graphene and phosphorene,” said Sang Professor Kim, one of the researchers involved in devising the process.
“But they’re both made up of just one element, so it’s pretty straightforward. Figuring out how to do it for TMD, which is made of two elements was going to be much harder.”
The ‘scissors’ involve a two-step process involving first inserting lithium ions into the layered structure of the TMD sheets, and then using ultrasound to cause a spontaneous ‘unzipping’ in straight lines.
“It works sort of like how when you split a plank of plywood: it breaks easily in one direction along the grain,” Professor Kim continued. “It’s actually really simple.”
The researchers then tried it with various types of TMDs, including those made of molybdenum, selenium, sulfur, tellurium and tungsten. All worked just as well, with a catalytic efficiency as effective as platinum’s.
Because of the simplicity of the procedure, this method should be able to be used not just in the large-scale production of TMD nanoribbons, but also to make similar nanoribbons from other multi-elemental 2D materials for purposes beyond just hydrogen production.
-ProfileProfessor Sang Ouk KimSoft Nanomaterials Laboratory (http://snml.kaist.ac.kr)Department of Materials Science and EngineeringKAIST
2020.10.29 View 8416 -
KAIST Showcases Healthcare Technologies at K-Hospital Fair 2020
KAIST Pavilion showcased its innovative medical and healthcare technologies and their advanced applications at the K-Hospital Fair 2020. Five KAIST research groups who teamed up for the Post-COVID-19 New Deal R&D Initiative Project participated in the fair held in Seoul last week.
The K-Hospital Fair is a yearly event organized by the Korean Hospital Association to present the latest research and practical innovations to help the medical industry better serve the patients. This year, 120 healthcare organizations participated in the fair and operated 320 booths.
At the fair, a research group led by Professor Il-Doo Kim from the Department of Materials Science and Engineering demonstrated the manufacturing process of orthogonal nanofibers used to develop their ‘recyclable nano-fiber filtered face mask’ introduced in March of this year. This mask has garnered immense international attention for maintaining its sturdy frame and filtering function even after being washed more than 20 times. Professor Kim is now extending his facilities for the mass production of this mask at his start-up company. While awaiting final approval from the Ministry of Food and Drug Safety to bring his product into the market, Professor Kim is developing other mask variations such as eco-friendly biodegradable masks and transparent masks to aid the hearing-impaired who rely on lip reading to communicate.
The team working under Professor Wonho Choe from the Department of Nuclear and Quantum Engineering presented two low-temperature plasma sterilizers for medical use, co-developed with Plasmapp, a start-up company founded by a KAIST alumnus. Their sterilizers are the first ones that can sterilize medical devices by diffusing hydrogen peroxide vapor into the pouch. They rapidly sterilize medical instruments and materials in just seven minutes without leaving toxic residue, while reducing sterilization time and costs by 90%.
Professor Hyung-Soon Park and his researchers from the Department of Mechanical Engineering introduced a smart protective suit ventilation system that features high cooling capacity and a slimmed-down design. For comfortable use, the suit is equipped with a technique that monitors its inner temperature and humidity and automatically controls its inner circulation accordingly. The group also presented a new system that helps a person in a contaminated suit undress without coming into contact with the contaminated outer part of the suit.
Professor Jong Chul Ye's group from the Department of Bio and Brain Engineering demonstrated AI software that can quickly diagnose an infectious disease based on chest X-ray imaging. The technique compares the differences in the severity of pneumonia in individual patients to distinguish whether their conditions fall under viral pneumonia including COVID-19, bacterial pneumonia, tuberculosis, other diseases, or normal conditions. The AI software visualizes the basis of its reasoning for each of the suspected diseases and provides them as information that can be utilized by medical personnel.
Finally, researchers of Professor Ki-Hun Jeong’s team from the Department of Bio and Brain Engineering demonstrated their ultra-high-speed sub-miniature molecular diagnostic system for the on-site diagnosis of diseases. The existing Polymerase Chain Reaction (PCR) diagnostic usually takes from 30 minutes to an hour to provide results, but their new technique using an LED light source can present results within just three minutes and it is expected to be used actively for on-site diagnosis.
Professor Choongsik Bae, the Director of the Post-COVID-19 New Deal R&D Initiative Project, said, “KAIST will build a healthy relationship amongst researchers, enterprises, and hospitals to contribute to the end of COVID-19 and build a new paradigm of Korean disease prevention and control.”
KAIST launched the Post-COVID-19 New Deal R&D Initiative in July with the support of the Ministry of Science and ICT of Korea. This unit was created to overcome the pandemic crisis by using science and technology, and to contribute to economic development by creating a new antiviral drug industry. The unit is comprised of 464 KAIST members including professors, researchers, and students as well as 503 professionals from enterprises, hospitals, and research centers.
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2020.10.26 View 14289 -
Scientist of October: Professor Jungwon Kim
Professor Jungwon Kim from the Department of Mechanical Engineering was selected as the ‘Scientist of the Month’ for October 2020 by the Ministry of Science and ICT and the National Research Foundation of Korea. Professor Kim was recognized for his contributions to expanding the horizons of the basics of precision engineering through his research on multifunctional ultrahigh-speed, high-resolution sensors. He received 10 million KRW in prize money.
Professor Kim was selected as the recipient of this award in celebration of “Measurement Day”, which commemorates October 26 as the day in which King Sejong the Great established a volume measurement system.
Professor Kim discovered that the time difference between the pulse of light created by a laser and the pulse of the current produced by a light-emitting diode was as small as 100 attoseconds (10-16 seconds). He then developed a unique multifunctional ultrahigh-speed, high-resolution Time-of-Flight (TOF) sensor that could take measurements of multiple points at the same time by sampling electric light. The sensor, with a measurement speed of 100 megahertz (100 million vibrations per second), a resolution of 180 picometers (1/5.5 billion meters), and a dynamic range of 150 decibels, overcame the limitations of both existing TOF techniques and laser interferometric techniques at the same time. The results of this research were published in Nature Photonics on February 10, 2020.
Professor Kim said, “I’d like to thank the graduate students who worked passionately with me, and KAIST for providing an environment in which I could fully focus on research. I am looking forward to the new and diverse applications in the field of machine manufacturing, such as studying the dynamic phenomena in microdevices, or taking ultraprecision measurement of shapes for advanced manufacturing.”
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2020.10.15 View 11803 -
Professor Won-Ki Cho Selected as the 2020 SUHF Young Investigator
Professor Won-Ki Cho from the Department of Biological Sciences was named one of three recipients of the 2020 Suh Kyung-Bae Science Foundation (SUHF) Young Investigator Award.
The SUHF is a non-profit organization established in 2016 and funded by a personal donation of 300 billion KRW in shares from Chairman and CEO Kyung-Bae Suh of the Amorepacific Group. The primary purpose of the foundation is to serve as a platform to nurture and provide comprehensive long-term support for creative and passionate young Korean scientists committed to pursuing research in the field of life sciences. The SUHF selects three to five scientists through an open recruiting process every year and grants each scientist a maximum of 2.5 billion KRW over a period of up to five years.
Since January this year, the foundation received 67 research proposals from scientists across the nation, especially from those who had less than five years of experience as professors, and selected the three recipients.
Professor Cho proposed research on how to observe the interactions between nuclear structures and constantly-changing chromatin monomers in four dimensions through ultra-high-resolution imaging of single living cells. This proposal was recognized as one that could help us better understand the process of transcription regulation, which remains a long-standing question in biology.
The other awards were given to Professor Soung-hun Roh of Seoul National University and Professor Joo-Hyeon Lee of the University of Cambridge.
With these three new awardees, a total of 17 scientists have been named SUHF Young Investigators to date, and the funding to support these scientists now totals 42.5 billion KRW.
Professor Inkyung Jung and Professor Ki-Jun Yoon from the Department of Biological Sciences, and Professor Young Seok Ju and Professor Jeong Ho Lee from the Graduate School of Medical Science and Engineering are the four previous winners from KAIST in the years 2017 through 2019.
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2020.10.15 View 13244 -
Slippery When Wet: Fish and Seaweed Inspire Ships to Reduce Fluid Friction
Faster ships could be on the horizon after KAIST scientists develop a slippery surface inspired by fish and seaweed to reduce the hull's drag through the water.
Long-distance cargo ships lose a significant amount of energy due to fluid friction. Looking to the drag reduction mechanisms employed by aquatic life can provide inspiration on how to improve efficiency.
Fish and seaweed secrete a layer of mucus to create a slippery surface, reducing their friction as they travel through water. A potential way to mimic this is by creating lubricant-infused surfaces covered with cavities. As the cavities are continuously filled with the lubricant, a layer is formed over the surface.
Though this method has previously been shown to work, reducing drag by up to 18%, the underlying physics is not fully understood. KAIST researchers in collaboration with a team of researchers from POSTECH conducted simulations of this process to help explain the effects, and their findings were published in the journal Physics of Fluids on September 15.
The group looked at the average speed of a cargo ship with realistic material properties and simulated how it behaves under various lubrication setups. Specifically, they monitored the effects of the open area of the lubricant-filled cavities, as well as the thickness of the cavity lids.
They found that for larger open areas, the lubricant spreads more than it does with smaller open areas, leading to a slipperier surface. On the other hand, the lid thickness does not have much of an effect on the slip, though a thicker lid does create a thicker lubricant buildup layer.
Professor Emeritus Hyung Jin Sung from the KAIST Department of Mechanical Engineering who led this study said, “Our investigation of the hydrodynamics of a lubricant layer and how it results in drag reduction with a slippery surface in a basic configuration has provided significant insight into the benefits of a lubricant-infused surface.”
Now that they have worked on optimizing the lubricant secretion design, the authors hope it can be implemented in real-life marine vehicles.
“If the present design parameters are adopted, the drag reduction rate will increase significantly,” Professor Sung added.
This work was supported by the National Research Foundation (NRF) of Korea.
Source:
Materials provided by American Institute of Physics.
Publication:
Kim, Seung Joong, et al. (2020). A lubricant-infused slip surface for drag reduction. Physics of Fluids. Available online at https://doi.org/10.1063/5.0018460
Profile:
Hyung Jin Sung
Professor Emeritus
hyungjin@kaist.ac.kr
http://flow.kaist.ac.kr/index.php
Flow Control Lab. (FCL)
Department of Mechanical Engineering
http://kaist.ac.kr
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, Republic of Korea
(END)
2020.10.12 View 7545 -
Big Ideas on Emerging Materials Explored at EMS
Renowned scholars and editors from academic journals joined the Emerging Materials e-Symposium (EMS) held at KAIST and shared the latest breakthroughs and big ideas in new material development last month. This e-symposium was organized by Professor Il-Doo Kim from the KAIST Department of Materials Sciences and Engineering over five days from September 21 through 25 via Zoom and YouTube. Professor Kim also serves as an associate editor of ACS Nano.
Esteemed scholars and editors of academic journals including ACS Nano, Nano Energy, and Energy Storage Materials made Zoom presentations in three main categories: 1) nanostructures for next-generation applications, 2) chemistry and biotechnology for applications in the fields of environment and industry, and 3) material innovation for technological applications.
During Session I, speakers including Professor John A. Rogers of Northwestern University and Professor Zhenan Bao of Stanford University led the session on Emerging Soft Electronics and 3D printing.
In later sessions, other globally recognized scholars gave talks titled Advanced Nanostructuring for Emerging Materials, Frontiers in Emerging Materials Research, Advanced Energy Materials and Functional Nanomaterials, and Latest Advances in Nanomaterials Research.
These included 2010 Nobel Prize laureate and professor at Manchester University Andre Geim, editor-in-chief of ACS Nano and professor at UCLA Paul S. Weiss, Professor Paul Alivisatos of UC Berkeley, Professor William Chueh of Stanford University, and Professor Mircea Dinca of MIT.
KAIST President Sung-Chul Shin, who is also a materials physicist, said in his opening address, “Innovation in materials science will become an important driving force to change our way of life. All the breakthroughs in materials have extended a new paradigm that has transformed our lives.”
“Creative research projects alongside global collaborators like all of you will allow the breakthroughs that will deliver us from these crises,” he added.
(END)
2020.10.06 View 15069 -
E. coli Engineered to Grow on CO₂ and Formic Acid as Sole Carbon Sources
- An E. coli strain that can grow to a relatively high cell density solely on CO₂ and formic acid was developed by employing metabolic engineering. -
Most biorefinery processes have relied on the use of biomass as a raw material for the production of chemicals and materials. Even though the use of CO₂ as a carbon source in biorefineries is desirable, it has not been possible to make common microbial strains such as E. coli grow on CO₂.
Now, a metabolic engineering research group at KAIST has developed a strategy to grow an E. coli strain to higher cell density solely on CO₂ and formic acid. Formic acid is a one carbon carboxylic acid, and can be easily produced from CO₂ using a variety of methods. Since it is easier to store and transport than CO₂, formic acid can be considered a good liquid-form alternative of CO₂.
With support from the C1 Gas Refinery R&D Center and the Ministry of Science and ICT, a research team led by Distinguished Professor Sang Yup Lee stepped up their work to develop an engineered E. coli strain capable of growing up to 11-fold higher cell density than those previously reported, using CO₂ and formic acid as sole carbon sources. This work was published in Nature Microbiology on September 28.
Despite the recent reports by several research groups on the development of E. coli strains capable of growing on CO₂ and formic acid, the maximum cell growth remained too low (optical density of around 1) and thus the production of chemicals from CO₂ and formic acid has been far from realized.
The team previously reported the reconstruction of the tetrahydrofolate cycle and reverse glycine cleavage pathway to construct an engineered E. coli strain that can sustain growth on CO₂ and formic acid. To further enhance the growth, the research team introduced the previously designed synthetic CO₂ and formic acid assimilation pathway, and two formate dehydrogenases.
Metabolic fluxes were also fine-tuned, the gluconeogenic flux enhanced, and the levels of cytochrome bo3 and bd-I ubiquinol oxidase for ATP generation were optimized. This engineered E. coli strain was able to grow to a relatively high OD600 of 7~11, showing promise as a platform strain growing solely on CO₂ and formic acid.
Professor Lee said, “We engineered E. coli that can grow to a higher cell density only using CO₂ and formic acid. We think that this is an important step forward, but this is not the end. The engineered strain we developed still needs further engineering so that it can grow faster to a much higher density.”
Professor Lee’s team is continuing to develop such a strain. “In the future, we would be delighted to see the production of chemicals from an engineered E. coli strain using CO₂ and formic acid as sole carbon sources,” he added.
-Profile:Distinguished Professor Sang Yup Leehttp://mbel.kaist.ac.krDepartment of Chemical and Biomolecular EngineeringKAIST
2020.09.29 View 11379 -
Biomarker Predicts Who Will Have Severe COVID-19
- Airway cell analyses showing an activated immune axis could pinpoint the COVID-19 patients who will most benefit from targeted therapies.-
KAIST researchers have identified key markers that could help pinpoint patients who are bound to get a severe reaction to COVID-19 infection. This would help doctors provide the right treatments at the right time, potentially saving lives. The findings were published in the journal Frontiers in Immunology on August 28.
People’s immune systems react differently to infection with SARS-CoV-2, the virus that causes COVID-19, ranging from mild to severe, life-threatening responses.
To understand the differences in responses, Professor Heung Kyu Lee and PhD candidate Jang Hyun Park from the Graduate School of Medical Science and Engineering at KAIST analysed ribonucleic acid (RNA) sequencing data extracted from individual airway cells of healthy controls and of mildly and severely ill patients with COVID-19. The data was available in a public database previously published by a group of Chinese researchers.
“Our analyses identified an association between immune cells called neutrophils and special cell receptors that bind to the steroid hormone glucocorticoid,” Professor Lee explained. “This finding could be used as a biomarker for predicting disease severity in patients and thus selecting a targeted therapy that can help treat them at an appropriate time,” he added.
Severe illness in COVID-19 is associated with an exaggerated immune response that leads to excessive airway-damaging inflammation. This condition, known as acute respiratory distress syndrome (ARDS), accounts for 70% of deaths in fatal COVID-19 infections.
Scientists already know that this excessive inflammation involves heightened neutrophil recruitment to the airways, but the detailed mechanisms of this reaction are still unclear.
Lee and Park’s analyses found that a group of immune cells called myeloid cells produced excess amounts of neutrophil-recruiting chemicals in severely ill patients, including a cytokine called tumour necrosis factor (TNF) and a chemokine called CXCL8.
Further RNA analyses of neutrophils in severely ill patients showed they were less able to recruit very important T cells needed for attacking the virus. At the same time, the neutrophils produced too many extracellular molecules that normally trap pathogens, but damage airway cells when produced in excess.
The researchers additionally found that the airway cells in severely ill patients were not expressing enough glucocorticoid receptors. This was correlated with increased CXCL8 expression and neutrophil recruitment.
Glucocorticoids, like the well-known drug dexamethasone, are anti-inflammatory agents that could play a role in treating COVID-19. However, using them in early or mild forms of the infection could suppress the necessary immune reactions to combat the virus. But if airway damage has already happened in more severe cases, glucocorticoid treatment would be ineffective.
Knowing who to give this treatment to and when is really important. COVID-19 patients showing reduced glucocorticoid receptor expression, increased CXCL8 expression, and excess neutrophil recruitment to the airways could benefit from treatment with glucocorticoids to prevent airway damage. Further research is needed, however, to confirm the relationship between glucocorticoids and neutrophil inflammation at the protein level.
“Our study could serve as a springboard towards more accurate and reliable COVID-19 treatments,” Professor Lee said.
This work was supported by the National Research Foundation of Korea, and Mobile Clinic Module Project funded by KAIST.
Figure. Low glucocorticoid receptor (GR) expression led to excessive inflammation and lung damage by neutrophils through enhancing the expression of CXCL8 and other cytokines.
Image credit: Professor Heung Kyu Lee, KAIST. Created with Biorender.com.
Image usage restrictions: News organizations may use or redistribute these figures and image, with proper attribution, as part of news coverage of this paper only.
-Publication:
Jang Hyun Park, and Heung Kyu Lee. (2020). Re-analysis of Single Cell Transcriptome Reveals That the NR3C1-CXCL8-Neutrophil Axis Determines the Severity of COVID-19. Frontiers in Immunology, Available online at https://doi.org/10.3389/fimmu.2020.02145
-Profile: Heung Kyu Lee
Associate Professor
heungkyu.lee@kaist.ac.kr
https://www.heungkyulee.kaist.ac.kr/
Laboratory of Host Defenses
Graduate School of Medical Science and Engineering (GSMSE)
The Center for Epidemic Preparedness at KAIST Institute
http://kaist.ac.kr
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, Republic of Korea
Profile: Jang Hyun Park
PhD Candidate
janghyun.park@kaist.ac.kr
GSMSE, KAIST
2020.09.17 View 16099 -
Sturdy Fabric-Based Piezoelectric Energy Harvester Takes Us One Step Closer to Wearable Electronics
KAIST researchers presented a highly flexible but sturdy wearable piezoelectric harvester using the simple and easy fabrication process of hot pressing and tape casting. This energy harvester, which has record high interfacial adhesion strength, will take us one step closer to being able to manufacture embedded wearable electronics.
A research team led by Professor Seungbum Hong said that the novelty of this result lies in its simplicity, applicability, durability, and its new characterization of wearable electronic devices.
Wearable devices are increasingly being used in a wide array of applications from small electronics to embedded devices such as sensors, actuators, displays, and energy harvesters.
Despite their many advantages, high costs and complex fabrication processes remained challenges for reaching commercialization. In addition, their durability was frequently questioned. To address these issues, Professor Hong’s team developed a new fabrication process and analysis technology for testing the mechanical properties of affordable wearable devices.
For this process, the research team used a hot pressing and tape casting procedure to connect the fabric structures of polyester and a polymer film. Hot pressing has usually been used when making batteries and fuel cells due to its high adhesiveness. Above all, the process takes only two to three minutes.
The newly developed fabrication process will enable the direct application of a device into general garments using hot pressing just as graphic patches can be attached to garments using a heat press.
In particular, when the polymer film is hot pressed onto a fabric below its crystallization temperature, it transforms into an amorphous state. In this state, it compactly attaches to the concave surface of the fabric and infiltrates into the gaps between the transverse wefts and longitudinal warps. These features result in high interfacial adhesion strength. For this reason, hot pressing has the potential to reduce the cost of fabrication through the direct application of fabric-based wearable devices to common garments.
In addition to the conventional durability test of bending cycles, the newly introduced surface and interfacial cutting analysis system proved the high mechanical durability of the fabric-based wearable device by measuring the high interfacial adhesion strength between the fabric and the polymer film. Professor Hong said the study lays a new foundation for the manufacturing process and analysis of wearable devices using fabrics and polymers.
He added that his team first used the surface and interfacial cutting analysis system (SAICAS) in the field of wearable electronics to test the mechanical properties of polymer-based wearable devices. Their surface and interfacial cutting analysis system is more precise than conventional methods (peel test, tape test, and microstretch test) because it qualitatively and quantitatively measures the adhesion strength.
Professor Hong explained, “This study could enable the commercialization of highly durable wearable devices based on the analysis of their interfacial adhesion strength. Our study lays a new foundation for the manufacturing process and analysis of other devices using fabrics and polymers. We look forward to fabric-based wearable electronics hitting the market very soon.”
The results of this study were registered as a domestic patent in Korea last year, and published in Nano Energy this month. This study has been conducted through collaboration with Professor Yong Min Lee in the Department of Energy Science and Engineering at DGIST, Professor Kwangsoo No in the Department of Materials Science and Engineering at KAIST, and Professor Seunghwa Ryu in the Department of Mechanical Engineering at KAIST.
This study was supported by the High-Risk High-Return Project and the Global Singularity Research Project at KAIST, the National Research Foundation, and the Ministry of Science and ICT in Korea.
-Publication:
Jaegyu Kim, Seoungwoo Byun, Sangryun Lee, Jeongjae Ryu, Seongwoo Cho, Chungik Oh, Hongjun Kim, Kwangsoo No, Seunghwa Ryu, Yong Min Lee, Seungbum Hong*, Nano Energy 75 (2020), 104992.
https://doi.org/10.1016/j.nanoen.2020.104992
-Profile: Professor Seungbum Hong
seungbum@kaist.ac.kr
http://mii.kaist.ac.kr/
Department of Materials Science and Engineering
KAIST
2020.09.17 View 13823 -
Before Eyes Open, They Get Ready to See
- Spontaneous retinal waves can generate long-range horizontal connectivity in visual cortex. -
A KAIST research team’s computational simulations demonstrated that the waves of spontaneous neural activity in the retinas of still-closed eyes in mammals develop long-range horizontal connections in the visual cortex during early developmental stages.
This new finding featured in the August 19 edition of Journal of Neuroscience as a cover article has resolved a long-standing puzzle for understanding visual neuroscience regarding the early organization of functional architectures in the mammalian visual cortex before eye-opening, especially the long-range horizontal connectivity known as “feature-specific” circuitry.
To prepare the animal to see when its eyes open, neural circuits in the brain’s visual system must begin developing earlier. However, the proper development of many brain regions involved in vision generally requires sensory input through the eyes.
In the primary visual cortex of the higher mammalian taxa, cortical neurons of similar functional tuning to a visual feature are linked together by long-range horizontal circuits that play a crucial role in visual information processing.
Surprisingly, these long-range horizontal connections in the primary visual cortex of higher mammals emerge before the onset of sensory experience, and the mechanism underlying this phenomenon has remained elusive.
To investigate this mechanism, a group of researchers led by Professor Se-Bum Paik from the Department of Bio and Brain Engineering at KAIST implemented computational simulations of early visual pathways using data obtained from the retinal circuits in young animals before eye-opening, including cats, monkeys, and mice.
From these simulations, the researchers found that spontaneous waves propagating in ON and OFF retinal mosaics can initialize the wiring of long-range horizontal connections by selectively co-activating cortical neurons of similar functional tuning, whereas equivalent random activities cannot induce such organizations.
The simulations also showed that emerged long-range horizontal connections can induce the patterned cortical activities, matching the topography of underlying functional maps even in salt-and-pepper type organizations observed in rodents. This result implies that the model developed by Professor Paik and his group can provide a universal principle for the developmental mechanism of long-range horizontal connections in both higher mammals as well as rodents.
Professor Paik said, “Our model provides a deeper understanding of how the functional architectures in the visual cortex can originate from the spatial organization of the periphery, without sensory experience during early developmental periods.”
He continued, “We believe that our findings will be of great interest to scientists working in a wide range of fields such as neuroscience, vision science, and developmental biology.”
This work was supported by the National Research Foundation of Korea (NRF). Undergraduate student Jinwoo Kim participated in this research project and presented the findings as the lead author as part of the Undergraduate Research Participation (URP) Program at KAIST.
Figures and image credit: Professor Se-Bum Paik, KAIST
Image usage restrictions: News organizations may use or redistribute these figures and image, with proper attribution, as part of news coverage of this paper only.
Publication:
Jinwoo Kim, Min Song, and Se-Bum Paik. (2020). Spontaneous retinal waves generate long-range horizontal connectivity in visual cortex. Journal of Neuroscience, Available online athttps://www.jneurosci.org/content/early/2020/07/17/JNEUROSCI.0649-20.2020
Profile: Se-Bum Paik
Assistant Professor
sbpaik@kaist.ac.kr
http://vs.kaist.ac.kr/
VSNN Laboratory
Department of Bio and Brain Engineering
Program of Brain and Cognitive Engineering
http://kaist.ac.kr
Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea
Profile: Jinwoo Kim
Undergraduate Student
bugkjw@kaist.ac.kr
Department of Bio and Brain Engineering, KAIST
Profile: Min Song
Ph.D. Candidate
night@kaist.ac.kr
Program of Brain and Cognitive Engineering, KAIST
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2020.08.25 View 12869 -
Deep Learning-Based Cough Recognition Model Helps Detect the Location of Coughing Sounds in Real Time
The Center for Noise and Vibration Control at KAIST announced that their coughing detection camera recognizes where coughing happens, visualizing the locations. The resulting cough recognition camera can track and record information about the person who coughed, their location, and the number of coughs on a real-time basis.
Professor Yong-Hwa Park from the Department of Mechanical Engineering developed a deep learning-based cough recognition model to classify a coughing sound in real time. The coughing event classification model is combined with a sound camera that visualizes their locations in public places. The research team said they achieved a best test accuracy of 87.4 %.
Professor Park said that it will be useful medical equipment during epidemics in public places such as schools, offices, and restaurants, and to constantly monitor patients’ conditions in a hospital room.
Fever and coughing are the most relevant respiratory disease symptoms, among which fever can be recognized remotely using thermal cameras. This new technology is expected to be very helpful for detecting epidemic transmissions in a non-contact way. The cough event classification model is combined with a sound camera that visualizes the cough event and indicates the location in the video image.
To develop a cough recognition model, a supervised learning was conducted with a convolutional neural network (CNN). The model performs binary classification with an input of a one-second sound profile feature, generating output to be either a cough event or something else.
In the training and evaluation, various datasets were collected from Audioset, DEMAND, ETSI, and TIMIT. Coughing and others sounds were extracted from Audioset, and the rest of the datasets were used as background noises for data augmentation so that this model could be generalized for various background noises in public places.
The dataset was augmented by mixing coughing sounds and other sounds from Audioset and background noises with the ratio of 0.15 to 0.75, then the overall volume was adjusted to 0.25 to 1.0 times to generalize the model for various distances.
The training and evaluation datasets were constructed by dividing the augmented dataset by 9:1, and the test dataset was recorded separately in a real office environment.
In the optimization procedure of the network model, training was conducted with various combinations of five acoustic features including spectrogram, Mel-scaled spectrogram and Mel-frequency cepstrum coefficients with seven optimizers. The performance of each combination was compared with the test dataset. The best test accuracy of 87.4% was achieved with Mel-scaled Spectrogram as the acoustic feature and ASGD as the optimizer.
The trained cough recognition model was combined with a sound camera. The sound camera is composed of a microphone array and a camera module. A beamforming process is applied to a collected set of acoustic data to find out the direction of incoming sound source. The integrated cough recognition model determines whether the sound is cough or not. If it is, the location of cough is visualized as a contour image with a ‘cough’ label at the location of the coughing sound source in a video image.
A pilot test of the cough recognition camera in an office environment shows that it successfully distinguishes cough events and other events even in a noisy environment. In addition, it can track the location of the person who coughed and count the number of coughs in real time. The performance will be improved further with additional training data obtained from other real environments such as hospitals and classrooms.
Professor Park said, “In a pandemic situation like we are experiencing with COVID-19, a cough detection camera can contribute to the prevention and early detection of epidemics in public places. Especially when applied to a hospital room, the patient's condition can be tracked 24 hours a day and support more accurate diagnoses while reducing the effort of the medical staff."
This study was conducted in collaboration with SM Instruments Inc.
Profile: Yong-Hwa Park, Ph.D.
Associate Professor
yhpark@kaist.ac.kr
http://human.kaist.ac.kr/
Human-Machine Interaction Laboratory (HuMaN Lab.)
Department of Mechanical Engineering (ME)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr/en/
Daejeon 34141, Korea
Profile: Gyeong Tae Lee
PhD Candidate
hansaram@kaist.ac.kr
HuMaN Lab., ME, KAIST
Profile: Seong Hu Kim
PhD Candidate
tjdgnkim@kaist.ac.kr
HuMaN Lab., ME, KAIST
Profile: Hyeonuk Nam
PhD Candidate
frednam@kaist.ac.kr
HuMaN Lab., ME, KAIST
Profile: Young-Key Kim
CEO
sales@smins.co.kr
http://en.smins.co.kr/
SM Instruments Inc.
Daejeon 34109, Korea
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2020.08.13 View 16326