CES
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KAIST’s unmanned racing car to race in the Indy Autonomous Challenge @ CES 2023 as the only contender representing Asia
- Professor David Hyunchul Shim of the School of Electrical Engineering, is at the Las Vegas Motor Speedway in Las Vegas, Nevada with his students of the Unmanned Systems Research Group (USRG), participating in the Indy Autonomous Challenge (IAC) @ CES as the only Asian team in the race.
Photo 1. Nine teams that competed at the first Indy Autonomous Challenge on October 23, 2021. (KAIST team is the right most team in the front row)
- The EE USRG team won the slot to race in the IAC @ CES 2023 rightly as the semifinals entree of the IAC @ CES 2022’ held in January of last year
- Through the partnership with Hyundai Motor Company, USRG received support to participate in the competition, and is to share the latest developments and trends of the technology with the company researchers
- With upgrades from last year, USRG is to race with a high-speed Indy racing car capable of driving up to 300 km/h and the technology developed in the process is to be used in further advancement of the high-speed autonomous vehicle technology of the future.
KAIST (President Kwang Hyung Lee) announced on the 5th that it will participate in the “Indy Autonomous Challenge (IAC) @ CES 2023”, an official event of the world's largest electronics and information technology exhibition held every year in Las Vegas, Nevada, of the United States from January 5th to 8th.
Photo 2. KAIST Racing Team participating in the Indy Autonomous Challenge @ CES 2023 (Team Leader: Sungwon Na, Team Members: Seongwoo Moon, Hyunwoo Nam, Chanhoe Ryu, Jaeyoung Kang)
“IAC @ CES 2023”, which is to be held at the Las Vegas Motor Speedway (LVMS) on January 7, seeks to advance technology developed as the result of last year's competition to share the results of such advanced high-speed autonomous vehicle technology with the public.
This competition is the 4th competition following the “Indy Autonomous Challenge (IAC)” held for the first time in Indianapolis, USA on October 23, 2021. At the IAC @ CES 2022 following the first IAC competition, the Unmmaned Systems Research Group (USRG) team led by Professor David Hyunchul Shim advanced to the semifinals out of a total of nine teams and won a spot to participate in CES 2023. As a result, the USRG comes into the challenge as the only Asian team to compete with other teams comprised of students and researchers of American and European backgrounds where the culture of motorsports is more deep-rooted.
For CES 2022, Professor David Hyunchul Shim’s research team was able to successfully develop a software that controlled the racing car to comply with the race flags and regulations while going up to 240 km/h all on its on.
Photo 3. KAIST Team’s vehicle on Las Vegas Motor Speedway during the IAC @ CES 2022
In the IAC @ CES 2023, the official racing vehicle AV-23, is a converted version of IL-15, the official racing car for Indy 500, fully automated while maintaining the optimal design for high-speed racing, and was upgraded from the last year’s competition taking up the highest speed up to 300 km/h.
This year’s competition, will develop on last year’s head-to-head autonomous racing and take the form of the single elimination tournament to have the cars overtake the others without any restrictions on the driving course, which would have the team that constantly drives at the fastest speed will win the competition.
Photo 4. KAIST Team’s vehicle overtaking the Italian team, PoliMOVE’s vehicle during one of the race in the IAC @ CES 2022
Professor Shim's team further developed on the CES 2022 certified software to fine tune the external recognition mechanisms and is now focused on precise positioning and driving control technology that factors into maintaining stability even when driving at high speed.
Professor Shim's research team won the Autonomous Driving Competition hosted by Hyundai Motor Company in 2021. Starting with this CES 2023 competition, they signed a partnership contract with Hyundai to receive financial support to participate in the CES competition and share the latest developments and trends of autonomous driving technology with Hyundai Motor's research team.
During CES 2023, the research team will also participate in other events such as the exhibition by the KAIST racing team at the IAC’s official booth located in the West Hall.
Professor David Hyunchul Shim said, “With these competitions being held overseas, there were many difficulties having to keep coming back, but the students took part in it diligently, for which I am deeply grateful. Thanks to their efforts, we were able to continue in this competition, which will be a way to verify the autonomous driving technology that we developed ourselves over the past 13 years, and I highly appreciate that.”
“While high-speed autonomous driving technology is a technology that is not yet sought out in Korea, but it can be applied most effectively for long-distance travel in the Korea,” he went on to add. “It has huge advantages in that it does not require constructions for massive infrastructure that costs enormous amount of money such as high-speed rail or urban aviation and with our design, it is minimally affected by weather conditions.” he emphasized.
On a different note, the IAC @ CES 2023 is co-hosted by the Consumer Technology Association (CTA) and Energy Systems Network (ESN), the organizers of CES. Last year’s IAC winner, Technische Universität München of Germany, and MIT-PITT-RW, a team of Massachusetts Institute of Technology (Massachusetts), University of Pittsburgh (Pennsylvania), Rochester Institute of Technology (New York), University of Waterloo (Canada), with and the University of Waterloo, along with TII EuroRacing - University of Modena and Reggio Emilia (Italy), Technology Innovation Institute (United Arab Emirates), and five other teams are in the race for the win against KAIST.
Photo 5. KAIST Team’s vehicle on the track during the IAC @ CES 2022
The Indy Autonomous Challenge is scheduled to hold its fifth competition at the Monza track in Italy in June 2023 and the sixth competition at CES 2024.
2023.01.05 View 7122 -
KAIST to showcase a pack of KAIST Start-ups at CES 2023
- KAIST is to run an Exclusive Booth at the Venetian Expo (Hall G) in Eureka Park, at CES 2023, to be held in Las Vegas from Thursday, January 5th through Sunday, the 8th.
- Twelve businesses recently put together by KAIST faculty, alumni, and the start-ups given legal usage of KAIST technologies will be showcased.
- Out of the participating start-ups, the products by Fluiz and Hills Robotics were selected as the “CES Innovation Award 2023 Honoree”, scoring top in their respective categories.
On January 3, KAIST announced that there will be a KAIST booth at Consumer Electronics Show (CES) 2023, the most influential tech event in the world, to be held in Las Vegas from January 3 to 8.
At this exclusive corner, KAIST will introduce the technologies of KAIST start-ups over the exhibition period.
KAIST first started holding its exclusive booth in CES 2019 with five start-up businesses, following up at CES 2020 with 12 start-ups and at CES 2022 with 10 start-ups. At CES 2023, which would be KAIST’s fourth conference, KAIST will be accompanying 12 businesses including start-ups by the faculty members, alumni, and technology transfer companies that just began their businesses with technologies from their research findings that stands a head above others.
To maximize the publicity opportunity, KAIST will support each company’s marketing strategies through cooperation with the Korea International Trade Association (KITA), and provide an opportunity for the school and each startup to create global identity and exhibit the excellence of their technologies at the convention.
The following companies will be at the KAIST Booth in Eureka Park:
The twelve startups mentioned above aim to achieve global technology commecialization in their respective fields of expertise spanning from eXtended Reality (XR) and gaming, to AI and robotics, vehicle and transport, mobile platform, smart city, autonomous driving, healthcare, internet of thing (IoT), through joint research and development, technology transfer and investment attraction from world’s leading institutions and enterprises.
In particular, Fluiz and Hills Robotics won the CES Innovation Award as 2023 Honorees and is expected to attain greater achievements in the future.
A staff member from the KAIST Institute of Technology Value Creation said, “The KAIST Showcase for CES 2023 has prepared a new pitching space for each of the companies for their own IR efforts, and we hope that KAIST startups will actively and effectively market their products and technologies while they are at the convention. We hope it will help them utilize their time here to establish their name in presence here which will eventually serve as a good foothold for them and their predecessors to further global commercialization goals.”
2023.01.04 View 9729 -
KAIST Offers Hope to Musicians with Dystonia
< Photo 1. Conductor and Pianist João Carlos Martins before the Recital at the Carnegie Hall preparing with his bionic gloves >
KAIST’s neuroscientist and professor, Dr. Daesoo Kim attended the “Conference for Musicians with Dystonia” supported by the World Health Organization (WHO) and the Carnegie Hall concert of legendary pianist João Carlos Martins, who is also a dystonia patient, to announce his team’s recent advancements toward finding a cure for dystonia.
On November 19, 2022, a “miracle concert” was held in Carnegie Hall. João Carlos Martins was a renowned world-class pianist in the 70s and 80s, but he had to put an end to his musical career due to focal dystonia in his fingers. But in 2020, he began using a bionic glove developed by industrial designer Ubiratã Bizarro Costa and after years of hard work he was back in Carnegie Hall as an 82-year-old man.
During the concert, he conducted the NOVUS NY orchestra in a performance of Bach, and later even played the piano himself. In particular, between his performances, he gave shout-outs to scientists studying dystonia including KAIST Professor Daesoo Kim, asking them to continue working towards curing rare diseases for musicians.
< Photo 2. Professor Daesoo Kim with Conductor and Pianist João Carlos Martins >
Musician’s dystonia affects 1-3% of musicians around the world and musicians make up approximately 5% of the total number of dystonia patients. Musicians who are no longer able to practice music due to the disease often experience stress and depression, which may even lead to suicide in extreme cases. Musicians are known to be particularly prone to such diseases due to excessive practice regimens, perfectionism, and even genetics. Currently, botulinum toxin (Botox) is used to suppress abnormal muscles, but muscle function suppression ultimately means that the musician is no longer able to play the instrument. João Carlos Martins himself underwent several Botox procedures and three brain surgeries, but saw no therapeutic results. This is why a new treatment was necessary.
Professor Daesoo Kim’s research team at KAIST took note of the fact that abnormal muscle tension is caused by excessive stress, and developed NT-1, a treatment that blocks the development of the symptoms of dystonia from the brain, allowing patients to use their muscles as they normally would. The research team published their findings in Science Advances in 2021, and João Carlos Martins invited Professor Daesoo Kim to the UN conference and his concert after reading this paper.
< Photo 3. Professor Daesoo Kim (3rd from the left) photographed with other guests at the recital including Dr. Dévora Kestel, the Director of the Mental Health and Substance Use at WHO, sharing the center with Conductor and Pianist João Carlos Martins >
During the UN conference held the day prior to the Carnegie Hall concert, Dr. Dévora Kestel, Director of the Mental Health and Substance Use at WHO, said, “Although dystonia is not as well-known, it is a common disease around the world, and needs our society’s attention and the devotion of many researchers.” Professor Daesoo Kim said, “NT-1 is a drug that blocks the cause of dystonia in the brain, and will allow musicians to continue practicing music. We aim to attain clinical approval in Korea by 2024.”
NT-1 is currently under development by NeuroTobe, a faculty-led start-up company at KAIST, headed by Professor Daesoo Kim as the CEO. The synthesis of the drug for clinical testing has been successfully completed, and it has shown excellent efficacy and safety through various rounds of animal testing. Unlike Botox, which takes a few days to show its therapeutic effects after receiving the procedure from a hospital, NT-1 shows its therapeutic effects within an hour after taking it. As a so-called “edible Botox”, it is expected to help treat various muscular diseases and ailments.
2022.12.27 View 8341 -
See-through exhibitions using smartphones: KAIST develops the AR magic lens, WonderScope
WonderScope shows what’s underneath the surface of an object through an augmented reality technology.
< Photo 1. Demonstration at ACM SIGGRAPH >
- A KAIST research team led by Professor Woohun Lee from the Department of Industrial Design and Professor Geehyuk Lee from the School of Computing have developed a smartphone “appcessory” called WonderScope that can easily add an augmented reality (AR) perspective to the surface of exhibits
- The research won an Honorable Mention for Emerging Technologies Best in Show at ACM SIGGRAPH, one of the largest international conferences on computer graphics and interactions
- The technology was improved and validated through real-life applications in three special exhibitions including one at the Geological Museum at the Korea Institute of Geoscience and Mineral Resources (KIGAM) held in 2020, and two at the National Science Museum each in 2021 and 2022
- The technology is expected to be used for public science exhibitions and museums as well as for interactive teaching materials to stimulate children’s curiosity
A KAIST research team led by Professor Woohun Lee from the Department of Industrial Design and Professor Geehyuk Lee from the School of Computing developed a novel augmented reality (AR) device, WonderScope, which displays the insides of an object directly from its surface. By installing and connecting WonderScope to a mobile device through Bluetooth, users can see through exhibits as if looking through a magic lens.
Many science museums nowadays have incorporated the use of AR apps for mobile devices. Such apps add digital information to the exhibition, providing a unique experience. However, visitors must watch the screen from a certain distance away from the exhibited items, often causing them to focus more on the digital contents rather than the exhibits themselves. In other words, the distance and distractions that exist between the exhibit and the mobile device may actually cause the visitors to feel detached from the exhibition. To solve this problem, museums needed a magic AR lens that could be used directly from the surface of the item.
To accomplish this, smartphones must know exactly where on the surface of an object it is placed. Generally, this would require an additional recognition device either on the inside or on the surface of the item, or a special pattern printed on its surface. Realistically speaking, these are impractical solutions, as exhibits would either appear overly complex or face spatial restrictions.
WonderScope, on the other hand, uses a much more practical method to identify the location of a smartphone on the surface of an exhibit. First, it reads a small RFID tag attached to the surface of an object, and calculates the location of the moving smartphone by adding its relative movements based on the readings from an optical displacement sensor and an acceleration sensor. The research team also took into consideration the height of the smartphone, and the characteristics of the surface profile in order to calculate the device’s position more accurately. By attaching or embedding RFID tags on exhibits, visitors can easily experience the effects of a magic AR lens through their smartphones.
For its wider use, WonderScope must be able to locate itself from various types of exhibit surfaces. To this end, WoderScope uses readings from an optical displacement sensor and an acceleration sensor with complementary characteristics, allowing stable locating capacities on various textures including paper, stone, wood, plastic, acrylic, and glass, as well as surfaces with physical patterns or irregularities. As a result, WonderScope can identify its location from a distance as close as 4 centimeters from an object, also enabling simple three-dimensional interactions near the surface of the exhibits.
The research team developed various case project templates and WonderScope support tools to allow the facile production of smartphone apps that use general-purpose virtual reality (VR) and the game engine Unity. WonderScope is also compatible with various types of devices that run on the Android operating system, including smartwatches, smartphones, and tablets, allowing it to be applied to exhibitions in many forms.
< Photo 2. Human body model showing demonstration >
< Photo 3. Demonstration of the underground mineral exploration game >
< Photo 4. Demonstration of Apollo 11 moon exploration experience >
The research team developed WonderScope with funding from the science and culture exhibition enhancement support project by the Ministry of Science and ICT. Between October 27, 2020 and February 28, 2021, WonderScope was used to observe underground volcanic activity and the insides of volcanic rocks at “There Once was a Volcano”, a special exhibition held at the Geological Museum in the Korea institute of Geoscience and Mineral Resources (KIGAM). From September 28 to October 3, 2021, it was used to observe the surface of Jung-moon-kyung (a bronze mirror with fine linear design) at the special exhibition “A Bronze Mirror Shines on Science” at the National Science Museum. And from August 2 to October 3, 2022 it was applied to a moon landing simulation at “The Special Exhibition on Moon Exploration”, also at the National Science Museum. Through various field demonstrations over the years, the research team has improved the performance and usability of WonderScope.
< Photo 5. Observation of surface corrosion of the main gate >
The research team demonstrated WonderScope at the Emerging Technologies forum during ACM SIGGRAPH 2022, a computer graphics and interaction technology conference that was held in Vancouver, Canada between August 8 and 11 this year. At this conference, where the latest interactive technologies are introduced, the team won an Honorable Mention for Best in Show. The judges commented that “WonderScope will be a new technology that provides the audience with a unique joy of participation during their visits to exhibitions and museums.”
< Photo 6. Cover of Digital Creativity >
WonderScope is a cylindrical “appcessory” module, 5cm in diameter and 4.5cm in height. It is small enough to be easily attached to a smartphone and embedded on most exhibits. Professor Woohun Lee from the KAIST Department of Industrial Design, who supervised the research, said, “WonderScope can be applied to various applications including not only educational, but also industrial exhibitions, in many ways.” He added, “We also expect for it to be used as an interactive teaching tool that stimulates children’s curiosity.”
Introductory video of WonderScope: https://www.youtube.com/watch?v=X2MyAXRt7h4&t=7s
2022.10.24 View 6983 -
Phage resistant Escherichia coli strains developed to reduce fermentation failure
A genome engineering-based systematic strategy for developing phage resistant Escherichia coli strains has been successfully developed through the collaborative efforts of a team led by Professor Sang Yup Lee, Professor Shi Chen, and Professor Lianrong Wang. This study by Xuan Zou et al. was published in Nature Communications in August 2022 and featured in Nature Communications Editors’ Highlights. The collaboration by the School of Pharmaceutical Sciences at Wuhan University, the First Affiliated Hospital of Shenzhen University, and the KAIST Department of Chemical and Biomolecular Engineering has made an important advance in the metabolic engineering and fermentation industry as it solves a big problem of phage infection causing fermentation failure.
Systems metabolic engineering is a highly interdisciplinary field that has made the development of microbial cell factories to produce various bioproducts including chemicals, fuels, and materials possible in a sustainable and environmentally friendly way, mitigating the impact of worldwide resource depletion and climate change. Escherichia coli is one of the most important chassis microbial strains, given its wide applications in the bio-based production of a diverse range of chemicals and materials. With the development of tools and strategies for systems metabolic engineering using E. coli, a highly optimized and well-characterized cell factory will play a crucial role in converting cheap and readily available raw materials into products of great economic and industrial value.
However, the consistent problem of phage contamination in fermentation imposes a devastating impact on host cells and threatens the productivity of bacterial bioprocesses in biotechnology facilities, which can lead to widespread fermentation failure and immeasurable economic loss. Host-controlled defense systems can be developed into effective genetic engineering solutions to address bacteriophage contamination in industrial-scale fermentation; however, most of the resistance mechanisms only narrowly restrict phages and their effect on phage contamination will be limited.
There have been attempts to develop diverse abilities/systems for environmental adaptation or antiviral defense. The team’s collaborative efforts developed a new type II single-stranded DNA phosphorothioation (Ssp) defense system derived from E. coli 3234/A, which can be used in multiple industrial E. coli strains (e.g., E. coli K-12, B and W) to provide broad protection against various types of dsDNA coliphages. Furthermore, they developed a systematic genome engineering strategy involving the simultaneous genomic integration of the Ssp defense module and mutations in components that are essential to the phage life cycle. This strategy can be used to transform E. coli hosts that are highly susceptible to phage attack into strains with powerful restriction effects on the tested bacteriophages. This endows hosts with strong resistance against a wide spectrum of phage infections without affecting bacterial growth and normal physiological function. More importantly, the resulting engineered phage-resistant strains maintained the capabilities of producing the desired chemicals and recombinant proteins even under high levels of phage cocktail challenge, which provides crucial protection against phage attacks.
This is a major step forward, as it provides a systematic solution for engineering phage-resistant bacterial strains, especially industrial bioproduction strains, to protect cells from a wide range of bacteriophages. Considering the functionality of this engineering strategy with diverse E. coli strains, the strategy reported in this study can be widely extended to other bacterial species and industrial applications, which will be of great interest to researchers in academia and industry alike.
Fig. A schematic model of the systematic strategy for engineering phage-sensitive industrial E. coli strains into strains with broad antiphage activities. Through the simultaneous genomic integration of a DNA phosphorothioation-based Ssp defense module and mutations of components essential for the phage life cycle, the engineered E. coli strains show strong resistance against diverse phages tested and maintain the capabilities of producing example recombinant proteins, even under high levels of phage cocktail challenge.
2022.08.23 View 9036 -
KAIST Research Team Proves How a Neurotransmitter may be the Key in Controlling Alzheimer’s Toxicity
With nearly 50 million dementia patients worldwide, and Alzheimers’s disease is the most common neurodegenerative disease. Its main symptom is the impairment of general cognitive abilities, including the ability to speak or to remember. The importance of finding a cure is widely understood with increasingly aging population and the life expectancy being ever-extended. However, even the cause of the grim disease is yet to be given a clear definition.
A KAIST research team in the Department of Chemistry led by professor Mi Hee Lim took on a lead to discovered a new role for somatostatin, a protein-based neurotransmitter, in reducing the toxicity caused in the pathogenic mechanism taken towards development of Alzheimer’s disease. The study was published in the July issue of Nature Chemistry under the title, “Conformational and functional changes of the native neuropeptide somatostatin occur in the presence of copper and amyloid-β”.
According to the amyloid hypothesis, the abnormal deposition of Aβ proteins causes death of neuronal cells. While Aβ agglomerations make up most of the aged plaques through fibrosis, in recent studies, high concentrations of transitional metal were found in the plaques from Alzheimer’s patients.
This suggests a close interaction between metallic ions and Aβ, which accelerates the fibrosis of proteins. Copper in particular is a redox-activating transition metal that can produce large amounts of oxygen and cause serious oxidative stress on cell organelles. Aβ proteins and transition metals can closely interact with neurotransmitters at synapses, but the direct effects of such abnormalities on the structure and function of neurotransmitters are yet to be understood.
Figure 1. Functional shift of somatostatin (SST) by factors in the pathogenesis of Alzheimer's disease.
Figure 2. Somatostatin’s loss-of-function as neurotransmitter. a. Schematic diagram of SST auto-aggregation due to Alzheimer's pathological factors. b. SST’s aggregation by copper ions. c. Coordination-prediction structure and N-terminal folding of copper-SST. d. Inhibition of SST receptor binding specificity by metals.
In their research, Professor Lim’s team discovered that when somatostatin, the protein-based neurotransmitter, is met with copper, Aβ, and metal-Aβ complexes, self-aggregates and ceases to perform its innate function of transmitting neural signals, but begins to attenuate the toxicity and agglomeration of metal-Aβ complexes.
Figure 3. Gain-of-function of somatostatin (SST) in the dementia setting. a. Prediction of docking of SST and amyloid beta. b. SST making metal-amyloid beta aggregates into an amorphous form. c. Cytotoxic mitigation effect of SST. d. SST mitigating the interaction between amyloid beta protein with the cell membrane.
This research, by Dr. Jiyeon Han et al. from the KAIST Department of Chemistry, revealed the coordination structure between copper and somatostatin at a molecular level through which it suggested the agglomeration mechanism, and discovered the effects of somatostatin on Aβ agglomeration path depending on the presence or absence of metals. The team has further confirmed somatostatin’s receptor binding, interactions with cell membranes, and effects on cell toxicity for the first time to receive international attention.
Professor Mi Hee Lim said, “This research has great significance in having discovered a new role of neurotransmitters in the pathogenesis of Alzheimer’s disease.” “We expect this research to contribute to defining the pathogenic network of neurodegenerative diseases caused by aging, and to the development of future biomarkers and medicine,” she added.
This research was conducted jointly by Professor Seung-Hee Lee’s team of KAIST Department of Biological Sciences, Professor Kiyoung Park’s Team of KAIST Department of Chemistry, and Professor Yulong Li’s team of Peking University.
The research was funded by Basic Science Research Program of the National Research Foundation of Korea and KAIST.
For more information about the research team, visit the website: https://sites.google.com/site/miheelimlab/1-professor-mi-hee-lim.
2022.07.29 View 10401 -
A System for Stable Simultaneous Communication among Thousands of IoT Devices
A mmWave Backscatter System, developed by a team led by Professor Song Min Kim is exciting news for the IoT market as it will be able to provide fast and stable connectivity even for a massive network, which could finally allow IoT devices to reach their full potential.
A research team led by Professor Song Min Kim of the KAIST School of Electrical Engineering developed a system that can support concurrent communications for tens of millions of IoT devices using backscattering millimeter-level waves (mmWave).
With their mmWave backscatter method, the research team built a design enabling simultaneous signal demodulation in a complex environment for communication where tens of thousands of IoT devices are arranged indoors. The wide frequency range of mmWave exceeds 10GHz, which provides great scalability. In addition, backscattering reflects radiated signals instead of wirelessly creating its own, which allows operation at ultralow power. Therefore, the mmWave backscatter system offers internet connectivity on a mass scale to IoT devices at a low installation cost.
This research by Kangmin Bae et al. was presented at ACM MobiSys 2022. At this world-renowned conference for mobile systems, the research won the Best Paper Award under the title “OmniScatter: Sensitivity mmWave Backscattering Using Commodity FMCW Radar”. It is meaningful that members of the KAIST School of Electrical Engineering have won the Best Paper Award at ACM MobiSys for two consecutive years, as last year was the first time the award was presented to an institute from Asia.
IoT, as a core component of 5G/6G network, is showing exponential growth, and is expected to be part of a trillion devices by 2035. To support the connection of IoT devices on a mass scale, 5G and 6G each aim to support ten times and 100 times the network density of 4G, respectively. As a result, the importance of practical systems for large-scale communication has been raised.
The mmWave is a next-generation communication technology that can be incorporated in 5G/6G standards, as it utilizes carrier waves at frequencies between 30 to 300GHz. However, due to signal reduction at high frequencies and reflection loss, the current mmWave backscatter system enables communication in limited environments. In other words, it cannot operate in complex environments where various obstacles and reflectors are present. As a result, it is limited to the large-scale connection of IoT devices that require a relatively free arrangement.
The research team found the solution in the high coding gain of an FMCW radar. The team developed a signal processing method that can fundamentally separate backscatter signals from ambient noise while maintaining the coding gain of the radar. They achieved a receiver sensitivity of over 100 thousand times that of previously reported FMCW radars, which can support communication in practical environments. Additionally, given the radar’s property where the frequency of the demodulated signal changes depending on the physical location of the tag, the team designed a system that passively assigns them channels. This lets the ultralow-power backscatter communication system to take full advantage of the frequency range at 10 GHz or higher.
The developed system can use the radar of existing commercial products as gateway, making it easily compatible. In addition, since the backscatter system works at ultralow power levels of 10uW or below, it can operate for over 40 years with a single button cell and drastically reduce installation and maintenance costs.
The research team confirmed that mmWave backscatter devices arranged randomly in an office with various obstacles and reflectors could communicate effectively. The team then took things one step further and conducted a successful trace-driven evaluation where they simultaneously received information sent by 1,100 devices.
Their research presents connectivity that greatly exceeds network density required by next-generation communication like 5G and 6G. The system is expected to become a stepping stone for the hyper-connected future to come.
Professor Kim said, “mmWave backscatter is the technology we’ve dreamt of. The mass scalability and ultralow power at which it can operate IoT devices is unmatched by any existing technology”. He added, “We look forward to this system being actively utilized to enable the wide availability of IoT in the hyper-connected generation to come”.
To demonstrate the massive connectivity of the system, a trace-driven evaluation of 1,100 concurrent tag transmissions are made. Figure shows the demodulation result of each and every 1,100 tags as red triangles, where they successfully communicate without collision.
This work was supported by Samsung Research Funding & Incubation Center of Samsung Electronics and by the ITRC (Information Technology Research Center) support program supervised by the IITP (Institute of Information & Communications Technology Planning & Evaluation).
Profile: Song Min Kim, Ph.D.Professorsongmin@kaist.ac.krhttps://smile.kaist.ac.kr
SMILE Lab.School of Electrical Engineering
2022.07.28 View 7635 -
CXL-Based Memory Disaggregation Technology Opens Up a New Direction for Big Data Solution Frameworks
A KAIST team’s compute express link (CXL) provides new insights on memory disaggregation and ensures direct access and high-performance capabilities
A team from the Computer Architecture and Memory Systems Laboratory (CAMEL) at KAIST presented a new compute express link (CXL) solution whose directly accessible, and high-performance memory disaggregation opens new directions for big data memory processing. Professor Myoungsoo Jung said the team’s technology significantly improves performance compared to existing remote direct memory access (RDMA)-based memory disaggregation.
CXL is a peripheral component interconnect-express (PCIe)-based new dynamic multi-protocol made for efficiently utilizing memory devices and accelerators. Many enterprise data centers and memory vendors are paying attention to it as the next-generation multi-protocol for the era of big data.
Emerging big data applications such as machine learning, graph analytics, and in-memory databases require large memory capacities. However, scaling out the memory capacity via a prior memory interface like double data rate (DDR) is limited by the number of the central processing units (CPUs) and memory controllers. Therefore, memory disaggregation, which allows connecting a host to another host’s memory or memory nodes, has appeared.
RDMA is a way that a host can directly access another host’s memory via InfiniBand, the commonly used network protocol in data centers. Nowadays, most existing memory disaggregation technologies employ RDMA to get a large memory capacity. As a result, a host can share another host’s memory by transferring the data between local and remote memory.
Although RDMA-based memory disaggregation provides a large memory capacity to a host, two critical problems exist. First, scaling out the memory still needs an extra CPU to be added. Since passive memory such as dynamic random-access memory (DRAM), cannot operate by itself, it should be controlled by the CPU. Second, redundant data copies and software fabric interventions for RDMA-based memory disaggregation cause longer access latency. For example, remote memory access latency in RDMA-based memory disaggregation is multiple orders of magnitude longer than local memory access.
To address these issues, Professor Jung’s team developed the CXL-based memory disaggregation framework, including CXL-enabled customized CPUs, CXL devices, CXL switches, and CXL-aware operating system modules. The team’s CXL device is a pure passive and directly accessible memory node that contains multiple DRAM dual inline memory modules (DIMMs) and a CXL memory controller. Since the CXL memory controller supports the memory in the CXL device, a host can utilize the memory node without processor or software intervention. The team’s CXL switch enables scaling out a host’s memory capacity by hierarchically connecting multiple CXL devices to the CXL switch allowing more than hundreds of devices. Atop the switches and devices, the team’s CXL-enabled operating system removes redundant data copy and protocol conversion exhibited by conventional RDMA, which can significantly decrease access latency to the memory nodes.
In a test comparing loading 64B (cacheline) data from memory pooling devices, CXL-based memory disaggregation showed 8.2 times higher data load performance than RDMA-based memory disaggregation and even similar performance to local DRAM memory. In the team’s evaluations for a big data benchmark such as a machine learning-based test, CXL-based memory disaggregation technology also showed a maximum of 3.7 times higher performance than prior RDMA-based memory disaggregation technologies.
“Escaping from the conventional RDMA-based memory disaggregation, our CXL-based memory disaggregation framework can provide high scalability and performance for diverse datacenters and cloud service infrastructures,” said Professor Jung. He went on to stress, “Our CXL-based memory disaggregation research will bring about a new paradigm for memory solutions that will lead the era of big data.”
-Profile: Professor Myoungsoo Jung Computer Architecture and Memory Systems Laboratory (CAMEL)http://camelab.org School of Electrical EngineeringKAIST
2022.03.16 View 19655 -
Scientist Discover How Circadian Rhythm Can Be Both Strong and Flexible
Study reveals that master and slave oscillators function via different molecular mechanisms
From tiny fruit flies to human beings, all animals on Earth maintain their daily rhythms based on their internal circadian clock. The circadian clock enables organisms to undergo rhythmic changes in behavior and physiology based on a 24-hour circadian cycle. For example, our own biological clock tells our brain to release melatonin, a sleep-inducing hormone, at night time.
The discovery of the molecular mechanism of the circadian clock was bestowed the Nobel Prize in Physiology or Medicine 2017. From what we know, no one centralized clock is responsible for our circadian cycles. Instead, it operates in a hierarchical network where there are “master pacemaker” and “slave oscillator”.
The master pacemaker receives various input signals from the environment such as light. The master then drives the slave oscillator that regulates various outputs such as sleep, feeding, and metabolism. Despite the different roles of the pacemaker neurons, they are known to share common molecular mechanisms that are well conserved in all lifeforms. For example, interlocked systems of multiple transcriptional-translational feedback loops (TTFLs) composed of core clock proteins have been deeply studied in fruit flies.
However, there is still much that we need to learn about our own biological clock. The hierarchically-organized nature of master and slave clock neurons leads to a prevailing belief that they share an identical molecular clockwork. At the same time, the different roles they serve in regulating bodily rhythms also raise the question of whether they might function under different molecular clockworks.
Research team led by Professor Kim Jae Kyoung from the Department of Mathematical Sciences, a chief investigator at the Biomedical Mathematics Group at the Institute for Basic Science, used a combination of mathematical and experimental approaches using fruit flies to answer this question. The team found that the master clock and the slave clock operate via different molecular mechanisms.
In both master and slave neurons of fruit flies, a circadian rhythm-related protein called PER is produced and degraded at different rates depending on the time of the day. Previously, the team found that the master clock neuron (sLNvs) and the slave clock neuron (DN1ps) have different profiles of PER in wild-type and Clk-Δ mutant Drosophila. This hinted that there might be a potential difference in molecular clockworks between the master and slave clock neurons.
However, due to the complexity of the molecular clockwork, it was challenging to identify the source of such differences. Thus, the team developed a mathematical model describing the molecular clockworks of the master and slave clocks. Then, all possible molecular differences between the master and slave clock neurons were systematically investigated by using computer simulations. The model predicted that PER is more efficiently produced and then rapidly degraded in the master clock compared to the slave clock neurons. This prediction was then confirmed by the follow-up experiments using animal.
Then, why do the master clock neurons have such different molecular properties from the slave clock neurons? To answer this question, the research team again used the combination of mathematical model simulation and experiments. It was found that the faster rate of synthesis of PER in the master clock neurons allows them to generate synchronized rhythms with a high level of amplitude. Generation of such a strong rhythm with high amplitude is critical to delivering clear signals to slave clock neurons.
However, such strong rhythms would typically be unfavorable when it comes to adapting to environmental changes. These include natural causes such as different daylight hours across summer and winter seasons, up to more extreme artificial cases such as jet lag that occurs after international travel. Thanks to the distinct property of the master clock neurons, it is able to undergo phase dispersion when the standard light-dark cycle is disrupted, drastically reducing the level of PER. The master clock neurons can then easily adapt to the new diurnal cycle. Our master pacemaker’s plasticity explains how we can quickly adjust to the new time zones after international flights after just a brief period of jet lag.
It is hoped that the findings of this study can have future clinical implications when it comes to treating various disorders that affect our circadian rhythm. Professor Kim notes, “When the circadian clock loses its robustness and flexibility, the circadian rhythms sleep disorders can occur. As this study identifies the molecular mechanism that generates robustness and flexibility of the circadian clock, it can facilitate the identification of the cause of and treatment strategy for the circadian rhythm sleep disorders.” This work was supported by the Human Frontier Science Program.
-PublicationEui Min Jeong, Miri Kwon, Eunjoo Cho, Sang Hyuk Lee, Hyun Kim, Eun Young Kim, and Jae Kyoung Kim, “Systematic modeling-driven experiments identify distinct molecularclockworks underlying hierarchically organized pacemaker neurons,” February 22, 2022, Proceedings of the National Academy of Sciences of the United States of America
-ProfileProfessor Jae Kyoung KimDepartment of Mathematical SciencesKAIST
2022.02.23 View 7118 -
Team KAIST Makes Its Presence Felt in the Self-Driving Tech Industry
Team KAIST finishes 4th at the inaugural CES Autonomous Racing Competition
Team KAIST led by Professor Hyunchul Shim and Unmanned Systems Research Group (USRG) placed fourth in an autonomous race car competition in Las Vegas last week, making its presence felt in the self-driving automotive tech industry.
Team KAIST, beat its first competitor, Auburn University, with speeds of up to 131 mph at the Autonomous Challenge at CES held at the Las Vegas Motor Speedway. However, the team failed to advance to the final round when it lost to PoliMOVE, comprised of the Polytechnic University of Milan and the University of Alabama, the final winner of the $150,000 USD race.
A total of eight teams competed in the self-driving race. The race was conducted as a single elimination tournament consisting of multiple rounds of matches. Two cars took turns playing the role of defender and attacker, and each car attempted to outpace the other until one of them was unable to complete the mission.
Each team designed the algorithm to control its racecar, the Dallara-built AV-21, which can reach a speed of up to 173 mph, and make it safely drive around the track at high speeds without crashing into the other.
The event is the CES version of the Indy Autonomous Challenge, a competition that took place for the first time in October last year to encourage university students from around the world to develop complicated software for autonomous driving and advance relevant technologies. Team KAIST placed 4th at the Indy Autonomous Challenge, which qualified it to participate in this race.
“The technical level of the CES race is much higher than last October’s and we had a very tough race. We advanced to the semifinals for two consecutive races. I think our autonomous vehicle technology is proving itself to the world,” said Professor Shim.
Professor Shim’s research group has been working on the development of autonomous aerial and ground vehicles for the past 12 years. A self-driving car developed by the lab was certified by the South Korean government to run on public roads.
The vehicle the team used cost more than 1 million USD to build. Many of the other teams had to repair their vehicle more than once due to accidents and had to spend a lot on repairs. “We are the only one who did not have any accidents, and this is a testament to our technological prowess,” said Professor Shim.
He said the financial funding to purchase pricy parts and equipment for the racecar is always a challenge given the very tight research budget and absence of corporate sponsorships.
However, Professor Shim and his research group plan to participate in the next race in September and in the 2023 CES race.
“I think we need more systemic and proactive research and support systems to earn better results but there is nothing better than the group of passionate students who are taking part in this project with us,” Shim added.
2022.01.12 View 8177 -
AI Weather Forecasting Research Center Opens
The Kim Jaechul Graduate School of AI in collaboration with the National Institute of Meteorological Sciences (NIMS) under the National Meteorological Administration launched the AI Weather Forecasting Research Center last month.
The KAIST AI Weather Forecasting Research Center headed by Professor Seyoung Yoon was established with funding from from the AlphaWeather Development Research Project of the National Institute of Meteorological Sciences. KAIST was finally selected asas the project facilitator.
AlphaWeather is an AI system that utilizes and analyzes approximately approximately 150,000 ,000 pieces of weather information per hour to help weather forecasters produce accurate weather forecasts. The research center is composed of three research teams with the following goals: (a) developdevelop AI technology for precipitation nowcasting, (b) developdevelop AI technology for accelerating physical process-based numerical models, and (c) develop dAI technology for supporting weather forecasters. The teams consist of 15 staff member members from NIMS and 61 researchers from the Kim Jaechul Graduate School of AI at KAIST.
The research center is developing an AI algorithm for precipitation nowcasting (with up to six hours of lead time), which uses satellite images, radar reflectivity, and data collected from weather stations. It is also developing an AI algorithm for correcting biases in the prediction results from multiple numerical models. Finally, it is Finally, it is developing AI technology that supports weather forecasters by standardizing and automating repetitive manual processes. After verification, the the results obtained will be used by by the Korean National Weather Service as a next-generation forecasting/special-reporting system intelligence engine from 2026.
2022.01.10 View 4728 -
Team KAIST to Race at CES 2022 Autonomous Challenge
Five top university autonomous racing teams will compete in a head-to-head passing competition in Las Vegas
A self-driving racing team from the KAIST Unmanned System Research Group (USRG) advised by Professor Hyunchul Shim will compete at the Autonomous Challenge at the Consumer Electronic Show (CES) on January 7, 2022. The head-to-head, high speed autonomous racecar passing competition at the Las Vegas Motor Speedway will feature the finalists and semifinalists from the Indy Autonomous Challenge in October of this year. Team KAIST qualified as a semifinalist at the Indy Autonomous Challenge and will join four other university teams including the winner of the competition, Technische Universität München.
Team KAIST’s AV-21 vehicle is capable of driving on its own at more than 200km/h will be expected to show a speed of more than 300 km/h at the race.The participating teams are:1. KAIST2. EuroRacing : University of Modena and Reggio Emilia (Italy), University of Pisa (Italy), ETH Zürich (Switzerland), Polish Academy of Sciences (Poland) 3. MIT-PITT-RW, Massachusetts Institute of Technology, University of Pittsburgh, Rochester Institute of Technology, University of Waterloo (Canada)4.PoliMOVE – Politecnico di Milano (Italy), University of Alabama 5.TUM Autonomous Motorsport – Technische Universität München (Germany)
Professor Shim’s team is dedicated to the development and validation of cutting edge technologies for highly autonomous vehicles. In recognition of his pioneering research in unmanned system technologies, Professor Shim was honored with the Grand Prize of the Minister of Science and ICT on December 9.
“We began autonomous vehicle research in 2009 when we signed up for Hyundai Motor Company’s Autonomous Driving Challenge. For this, we developed a complete set of in-house technologies such as low-level vehicle control, perception, localization, and decision making.” In 2019, the team came in third place in the Challenge and they finally won this year.
For years, his team has participated in many unmanned systems challenges at home and abroad, gaining recognition around the world. The team won the inaugural 2016 IROS autonomous drone racing and placed second in the 2018 IROS Autonomous Drone Racing Competition. They also competed in 2017 MBZIRC, ranking fourth in Missions 2 and 3, and fifth in the Grand Challenge.
Most recently, the team won the first round of Lockheed Martin’s Alpha Pilot AI Drone Innovation Challenge. The team is now participating in the DARPA Subterranean Challenge as a member of Team CoSTAR with NASA JPL, MIT, and Caltech.
“We have accumulated plenty of first-hand experience developing autonomous vehicles with the support of domestic companies such as Hyundai Motor Company, Samsung, LG, and NAVER. In 2017, the autonomous vehicle platform “EureCar” that we developed in-house was authorized by the Korean government to lawfully conduct autonomous driving experiment on public roads,” said Professor Shim.
The team has developed various key technologies and algorithms related to unmanned systems that can be categorized into three major components: perception, planning, and control. Considering the characteristics of the algorithms that make up each module, their technology operates using a distributed computing system.
Since 2015, the team has been actively using deep learning algorithms in the form of perception subsystems. Contextual information extracted from multi-modal sensory data gathered via cameras, lidar, radar, GPS, IMU, etc. is forwarded to the planning subsystem. The planning module is responsible for the decision making and planning required for autonomous driving such as lane change determination and trajectory planning, emergency stops, and velocity command generation. The results from the planner are fed into the controller to follow the planned high-level command. The team has also developed and verified the possibility of an end-to-end deep learning based autonomous driving approach that replaces a complex system with one single AI network.
2021.12.17 View 8386