Engineering
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Professor Dan Keun Sung Endows Scholarship in Honor of His Retirement
Professor Dan Keun Sung in the School of Electrical Engineering contributed a 100 million KRW scholarship fund this month to KAIST to mark his retirement after more than three decades of work.
“As my retirement date comes closer, I have been thinking about what I could do for the school. I wanted to leave something behind, even though it’s small, for my lifelong school and students. I am hoping that this scholarship fund will benefit the members of KAIST.”
This isn’t his first time making a donation to KAIST. In 2013, Professor Sung donated ten million KRW, which was his cash prize from the 9th Haedong Academic Award of The Korean Institute of Communications and Information Sciences (KICS). At that time, Professor Sung had the chance to create a scholarship fund in his name; however, he wanted to highlight that the scholarship fund was for ‘someone,’ not created by ‘someone.’ In that sense, his scholarship fund was created with no name to benefit students in the School of Electrical Engineering. His colleagues and students supported his idea. Professor Seonghwan Cho, students, and alumni also participated in fund raising efforts, which reached 55 million KRW in total.
Professor Sung emphasized, “Donations should always be remembered, no matter how small they are.” He then explained his purpose for creating the scholarship fund by saying, “Fundraising can be truly meaningful to contributors, knowing that their money is going to supporting the school and students.”
Professor Sung, a fellow of the Institute of Electrical and Electronics Engineers (IEEE) Communication Society, started his post at KAIST in 1986. For the past 30 years, he has devoted himself to fostering young scholars and studying in the area of information and communication. He also participated in developing technologies for the resource management of various future cellular components, such as satellites, switchboards, and signaling networks.
2017.08.11 View 7959 -
KAIST Researchers Receive Awards at the 13th Asian Congress on Biotechnology
(From left: Seon Young Park, Dr. So Young Choi, and Yoojin Choi)
Researchers in the laboratory of KAIST Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering swept awards at the 13th Asian Congress on Biotechnology held in Thailand last month. The conference awarded a total of eight prizes in the areas of best research and best poster presentation. This is an exceptional case in which members of one research team received almost half of the awards at an international conference.
Dr. So Young Choi received the Best Research Award, while Ph.D. candidates Yoojin Choi and Seon Young Park each received the Best Poster Presentation Award at the conference held in Khon Kaen, Thailand from July 23 to 27.
The Asian Congress on Biotechnology is an international conference in which scientists and industry experts in Asia and from around the world gather to present recent research findings in the field of biotechnology. At the conference, around 400 researchers in biotechnology from 25 countries, including Korea, gathered to present and discuss various research findings under the theme of “Bioinnovation and Bioeconomy.”
Distinguished Professor Sang Yup Lee attended the conference to give the opening plenary lecture on the topic of ‘Systems Strategies in Biotechnology.’ Professor Lee announced, “I have attended international conferences with students for the last 20 years, but this is the first in which my team received three awards at an international conference that only honors a total of eight awards, three for Best Research and five for Best Presentation.”
Dr. Choi presented research results on poly (lactate-co-glycolate) (PLGA) synthesis through a biological method using micro-organisms and received the Best Research Award. PLGA is a random copolymer of DL-lactic and glycolic acids and is a biopolymer widely used for biomedical applications. PLGA is biodegradable, biocompatible, and nontoxic, and thus has been approved by the US Food and Drug Administration (FDA) for its use in implants, drug delivery, and sutures.
Dr. Choi’s research was deemed to be innovative for synthesizing PLGA from glucose and xylose in cells through metabolic engineering of E.Coli. Dr. Choi received her Ph.D. under the supervision of Distinguished Professor Lee this February and is currently conducting post-doc research.
Ph.D. candidate Choi presented her research on the use of recombinant E.Coli for the biological synthesis of various nanoparticles and received the Best Poster Presentation award. Choi used recombinant E.Coli-expressing proteins and peptides that adsorb to heavy metals to biologically synthesize diverse metal nanoparticles such as single-nanoparticle including gold and silver, quantum dots, and magnetic nanoparticles for the first time. The synthesized nanoparticles can be used in the fields of bio-imaging, diagnosis, environment, and energy.
Ph.D. candidate Park, who also received the Best Poster Presentation award, synthesized and increased production of astanxanthin, a strong antioxidant found in nature, in E.Coli using metabolic engineering. Astanxanthin is a carotenoid pigment found in salmon and shrimp that widely used in health products and cosmetics.
2017.08.01 View 12792 -
Analysis of Gas Adsorption Properties for Amorphous Porous Materials
Professor Jihan Kim from the Department of Chemical and Biomolecular Engineering at KAIST has developed a method to predict gas adsorption properties of amorphous porous materials.
Metal-organic frameworks (MOFs) have large surface area and high density of pores, making them appropriate for various energy and environmental-related applications. And although most MOFs are crystalline, these structures can deform during synthesis and/or industrial processes, leading to loss in long-range order. Unfortunately, without the structural information, existing computer simulation techniques cannot be used to model these materials.
In this research, Professor Kim’s research team demonstrated that one can replace the material properties of structurally deformed MOFs with those of crystalline MOFs to indirectly analyze/model the material properties of amorphous materials. First, the team conducted simulations on methane gas adsorption properties for over 12,000 crystalline MOFs to obtain a large training set data, and created a resulting structure-property map. Upon mapping the experimental data of amorphous MOFs onto the structure-property map, results showed that regardless of crystallinity, the gas adsorption properties of MOFs showed congruence and consistency amongst one another.
Based on these findings, selected crystalline MOFs with the most similar gas adsorption properties as the collapsed structure from the 12,000 candidates. Then, the team verified that the adsorption properties of these similar MOFs can be successfully transferred to the deformed MOFs across different temperatures and even to different gas molecules (e.g. hydrogen), demonstrating transferability of properties.
These findings allow material property prediction in porous materials such as MOFs without structural information, and the techniques here can be used to better predict and understand optimal materials for various applications including, carbon dioxide capture, gas storage and separations.
This research was conducted in collaboration with Professor Dae-Woon Lim at Kyoto University, Professor Myunghyun Paik at Seoul National University, Professor Minyoung Yoon at Gachon University, and Aadesh Harale at Saudi Arabian Oil Company. The research was published in the Proceedings of the National Academy of Sciences (PNAS) online on 10 July and the co-first authors were Ph. D. candidate WooSeok Jeong and Professor Dae-Woon Lim.
This research was funded by the Saudi Aramco-KAIST CO2 Management Center.
(Figure 1. Trends in structure - material property map and in collapsed structures)
(Figure 2. Transferability between the experimental results of collapsed MOFs and the simulation results of crystalline MOFs)
2017.07.26 View 8547 -
Innovative Nanosensor for Disease Diagnosis
(Figure 1. Sensing Device)
(Figure 2. Protein templating route)
Breath pattern recognition is a futuristic diagnostic platform. Simple characterizing target gas concentrations of human exhaled breath will lead to diagnose of the disease as well as physical condition.
A research group under Prof. Il-Doo Kim in the Department of Materials Science has developed diagnostic sensors using protein-encapsulated nanocatalysts, which can diagnose certain diseases by analyzing human exhaled breath. This technology enables early monitoring of various diseases through pattern recognition of biomarker gases related to diseases in human exhalation.
The protein-templated catalyst synthesis route is very simple and versatile for producing not only a single component of catalytic nanoparticles, but also diverse heterogeneous intermetallic catalysts with sizes less than 3 nm. The research team has developed ever more sensitive and selective chemiresistive sensors that can potentially diagnose specific diseases by analyzing exhaled breath gases.
The results of this study, which were contributed by Dr. Sang-Joon Kim and Dr. Seon-Jin Choi as first authors were selected as the cover-featured article in the July issue of 'Accounts of Chemical Research,' an international journal of the American Chemical Society.
In human breath, diverse components are found including water vapor, hydrogen, acetone, toluene, ammonia, hydrogen sulfide, and carbon monoxide, which are more excessively exhaled from patients. Some of these components are closely related to diseases such as asthma, lung cancer, type 1 diabetes mellitus, and halitosis.
Breath analysis for disease diagnosis started from capturing exhaled breaths in a Tedlar bag and subsequently the captured breath gases were injected into a miniaturized sensor system, similar to an alcohol detector. It is possible to analyze exhaled breath very rapidly with a simple analyzing process. The breath analysis can detect trace changes in exhaled breath components, which contribute to early diagnosis of diseases.
However, technological advances are needed to accurately analyze gases in the breath, which occur at very low levels, from 1 ppb to 1 ppm. In particular, it has been a critical challenge for chemiresistive type chemical sensors to selectively detect specific biomarkers in thousands of interfering gases including humid vapor.
Conventionally, noble metallic catalysts such as platinum and palladium have been functionalized onto metal oxide sensing layers. However, the gas sensitivity was not enough to detect ppb-levels of biomarker species in exhaled breath.
To overcome the current limitations, the research team utilized nanoscale protein (apoferritin) in animals as sacrificial templates. The protein templates possess hollow nanocages at the core site and various alloy catalytic nanoparticles can be encapsulated inside the protein nanocages.
The protein nanocages are advantageous because a nearly unlimited number of material compositions in the periodic table can be assembled for the synthesis of heterogeneous catalytic nanoparticles. In addition, intermetallic nanocatalysts with a controlled atomic ratio of two different elements can be achieved using the protein nanocages, which is an innovative strategy for finding new types of catalysts. For example, highly efficient platinum-based catalysts can be synthesized, such as platinum-palladium (PtPd), platinum-nickel (PtNi), platinum-ruthenium (PtRu), and platinum-yttrium (PtY).
The research team developed outstanding sensing layers consisting of metal oxide nanofibers functionalized by the heterogeneous catalysts with large and highly-porous surface areas, which are especially optimized for selective detection of specific biomarkers. The biomarker sensing performance was improved approximately 3~4-fold as compared to the conventional single component of platinum and palladium catalysts-loaded nanofiber sensors. In particular, 100-fold resistance transitions toward acetone (1 ppm) and hydrogen sulfide (1 ppm) were observed in exhaled breath sensors using the heterogeneous nanocatalysts, which is the best performance ever reported in literature.
The research team developed a disease diagnosis platform that recognizes individual breathing patterns by using a multiple sensor array system with diverse sensing layers and heterogeneous catalysts, so that the people can easily identify health abnormalities. Using a 16-sensor array system, physical conditions can be continuously monitored by analyzing concentration changes of biomarkers in exhaled breath gases.
Prof. Kim said, “New types of heterogeneous nanocatalysts were synthesized using protein templates with sizes around 2 nm and functionalized on various metal oxide nanofiber sensing layers. The established sensing libraries can detect biomarker species with high sensitivity and selectivity.” He added, “the new and innovative breath gas analysis platform will be very helpful for reducing medical expenditures and continuous monitoring of physical conditions”
Patents related to this technology were licensed to two companies in March and June this year.
2017.07.19 View 9943 -
KAIST to Host the 2017 AI World Cup in November
KAIST, the birthplace of the Robot World Cup in 1996, now presents a new technology matchup, the AI World Cup this November, which will be held at KAIST. The event is being organized by the Machine Intelligence and Robotics Multi-Sponsored Research and Education Platform (MIR-MSREP) of KAIST. The online, simulated AI soccer game, based on rolling updates, will be a draw for avid online gamers and tech-savvy university students from around the nation.
The tournament is comprised of three events: ▲A 5 on 5 AI soccer match to be played after self-learning using AI technology in an online simulation environment ▲Commentary in which online soccer videos are analyzed and commented on, and ▲Game reporters who will write articles on online soccer event results.
The participants will undergo a month-long online practice period in October and compete in preliminary matches from November 1 through 24. The top teams that scored the highest accumulated points will compete in the finals on December 1. In the finals, each team’s AI technology implementation method will be evaluated to select the final winning team. To ensure a successful event, KAIST will host a briefing session for participants on July 28.
Technological prowess and early exposure to AI accumulated at KAIST led to the launching of this tournament. Professor Jong-Hwan Kim, the chair of the Organizing Committee of the AI World Cup, hosted the first ever Robot World Cup back in 1996. His concept has now evolved into the emerging technology of AI and the members of the Organizing Committee encompass the professors from the various departments of electrical engineering, computing, industrial and systems engineering, aerospace engineering, civil and environmental engineering, and the graduate schools of Green Transportation, Cultural Technology, and Science and Technology Policy.
In particular, ongoing convergence research initiatives incorporating AI into a wide arrays of disciplines such as bio, nano, and IT, played a crucial role for making this AI World Cup happen. Professor Kim said, “The winner of this year’s competition will be awarded a certificate and a small gift. In 2018, we aim to expand the event to an international scale by allowing international teams.”
Any undergraduate or graduate student in Korea can apply to participate in the ‘AI World Cup 2017’. KAIST will host a public trial event during the ‘Open KAIST’ event period to be held November 2-3 to help participating students understand the event better. ‘Open KAIST’ allows the general public to personally visit and experience what goes on in engineering departments and laboratories on the KAIST main campus. It is hosted by the College of Engineering every two years and is the largest event hosted by KAIST.
To participate in the ‘AI World Cup 2017,’ teams consisting of Korean undergraduates or graduate students can fill out application forms and submit them by September 30 on http://mir.kaist.ac.kr .
2017.07.14 View 9902 -
Professor Nam Jin Cho Selected as the Eugene P. Wigner Reactor Physicist Awardee
Professor Nam Jin Cho from the Department of Nuclear & Quantum Engineering was selected as the recipient of the 2017 ‘Eugene P. Wigner Reactor Physicist Award.’ The award, established in 1990 by the American Nuclear Society, honors individuals who have made outstanding contributions to the advancement of the field of reactor physics. The award is named after the late Eugene P. Wigner, a pioneer who helped nurture the nuclear age to technical maturity with his pioneering leadership in reactor design.
Professor Cho was recognized for his outstanding leadership and achievement in the field of nuclear physics, especially with his original research in analytic function expansion nodal methods, coarse-mesh angular dependent rebalance methods, and neutron transport calculations. A fellow of the ANS, Professor Cho is the first awardee from the Asian region.
Professor Cho gave all the credit to his colleagues and students at KAIST who have spared no effort while working together for three decades. “I am very grateful for the unique academic ambience which made this challenging work possible as well as the government’s continuing funding at the National Research Laboratory project.
2017.07.12 View 6133 -
Structural Insights into the Modulation of Synaptic Adhesion by MDGA for Synaptogenesis
Synapses connected by various synaptic adhesion molecules are communication spaces between neurons for transmitting information. Among various synaptic adhesion molecules, neuroligins are arguably the most widely studied class of postsynaptic adhesion molecules, which mainly interact with presynaptic neurexins to induce excitatory or inhibitory synapse development. Recently, the membrane-associated mucin (MAM) domain-containing GPI anchor protein 1 (MDGA1) has been characterized as a key suppressor of Neuroligin-2/Neurexin-1β-mediated inhibitory synapse development, but how it acts remains a mystery.
In a recent issue of Neuron, published on June 21, 2017, a research team led by Professor Ho Min Kim at the Graduate School of Medical Science and Engineering of KAIST reported the three-dimensional structure of MDGA1/Neuroligin-2 complex and mechanistic insights into how MDGAs negatively modulate synapse development governed by Neurexins/Neuroligins trans -synaptic adhesion complex.
MDGA1 consists of six Ig-like domains, fibronectin type III repeat domain, and MAM domain . The crystal structure of MDGA1/Neuroligin-2 complex reveals that they form the 2:2 hetero-tetrameric complex and only the Ig1-Ig2 domains of MDGA1 are involved in interactions with Neuroligin-2. The structural comparison between the MDGA1/Neuroligin-2 and Neurexin-1β/Neuroligin-1 complexes intriguingly indicates that the Neuroligin-2 region binding to MDGA1 largely overlaps with that of Neurexin-1β, but the interaction interface of the MDGA1/Neuroligin-2 complex is much larger than that of the Neurexin-1β/Neuroligin-1 complex. This explains why Neuroligin-2 binds stronger to MDGA1 than Neurexin-1β, and how the favored MDGA1 binding to Neuroligin-2 sterically blocks the interaction between Neuroligin-2 and Neurexin-1β, which is critical for the suppression of inhibitory synapse development.
“Although we found that MDGA Ig domains (Ig 1 and Ig 2) are sufficient to form a complex with NL2, other extracellular domains, including Ig 3–6, FN III, and MAM domains, may also contribute to stable cis-interactions between MDGA1 and Neuroligin-2 by providing conformational flexibility. Therefore, further structural analysis of full-length MDGA will be required,” Professor Kim said.
Neuroligin-2 specifically promotes the development of inhibitory synapses, whereas neuroligin-1 promotes the development of excitatory synapses. Recently, not only MDGA1, but also MDGA2 have emerged as synaptic regulators for the development of excitatory or inhibitory synapses. In vitro biochemical analysis in this research clearly demonstrates that Neuroligin-1 and Neuroligin-2 bind to both MDGA1 and MDGA2 with comparable affinity. However, pull-down assays using detergent-solubilized mouse brain membrane fractions show the specific interaction of MDGA1 with Neuroligin-2, but not with Neuroligin-1. “This suggests that unidentified processes may dictate the selective association of MDGA1 with Neuroligin-2 in vivo , ” explained Professor Jaewon Ko at the Daegu Gyeongbuk Institute of Science and Technology (DGIST).
A balance between excitatory and inhibitory synapses is crucial to healthy cognition and behavior. Mutations in neuroligins, neurexins, and MDGAs, which can disrupt the excitatory/inhibitory balance, are associated with neuropsychiatric diseases such as autism and schizophrenia. Jung A Kim at KAIST, first author in this study, said, “Our discovery from integrative investigations are an important first step both for a better understanding of Neuroligin/Neurexin synaptic adhesion pathways and MDGA-mediated regulation of synapse development as well as the development of potential new therapies for autism, schizophrenia, and epilepsy.”
2017.07.10 View 7932 -
Cooperative Tumor Cell Membrane-Targeted Phototherapy
A KAIST research team led by Professor Ji-Ho Park in the Bio and Brain Engineering Department at KAIST developed a technology for the effective treatment of cancer by delivering synthetic receptors throughout tumor tissue. The study, led by Ph.D. candidate Heegon Kim, was published online in Nature Communications on June 19.
Cancer targeted therapy generally refers to therapy targeting specific molecules that are involved in the growth and generation of cancer. The targeted delivery of therapeutics using targeting agents such as antibodies or nanomaterials has improved the precision and safety of cancer therapy.
However, the paucity and heterogeneity of identified molecular targets within tumors have resulted in poor and uneven distribution of targeted agents, thus compromising treatment outcomes.
To solve this problem, the team constructed a cooperative targeting system in which synthetic and biological nanocomponents participate together in the tumor cell membrane-selective localization of synthetic receptors to amplify the subsequent targeting of therapeutics. Here, synthetic and biological nanocomponents refer to liposomes and extracellular vesicles, respectively.
The synthetic receptors are first delivered selectively to tumor cell membranes in the perivascular region using liposomes. By hitchhiking with extracellular vesicles secreted by the cells, the synthetic receptors are transferred to neighboring cells and further spread throughout the tumor tissues where the molecular targets are limited.
Hitchhiking extracellular vesicles for delivery of synthetic receptors was possible since extracellular vesicles, such as exosomes, mediate intercellular communications by transferring various biological components such as lipids, cytosolic proteins, and RNA through a membrane fusion process. They also play a supportive role in promoting tumor progression in that tumor-derived extracellular vesicles deliver oncogenic signals to normal host cells.
The team showed that this tumor cell membrane-targeted delivery of synthetic receptors led to a uniform distribution of synthetic receptors throughout a tumor and subsequently led to enhanced phototherapeutic efficacy of the targeted photosensitizer.
Professor Park said, “The cooperative tumor targeting system is expected to be applied in treating various diseases that are hard to target.”
The research was funded by the Basic Science Research Program through the National Research Foundation funded by the Ministry of Science, ICT & Future Planning, and the National R&D Program for Cancer Control funded by the Ministry for Health and Welfare.
(Ph.D. candidates Hee Gon Kim (left) and Chanhee Oh)
Figure 1. A schematic of a cooperative tumor targeting system via delivery of synthetic receptors.
Figure 2. A confocal microscopic image of a tumor section after cooperative targeting by synthetic receptor delivery. Green and magenta represent vessels and therapeutic agents inside a tumor respectively.
2017.07.07 View 9591 -
KAIST Professors Sweep the Best Science and Technology Award
(Distinguished Professors Sang Yup Lee (left) and Kyu-Young Whang)
Distinguished Professors Sang Yup Lee from the Department of Chemical and Biomolecular Engineering and Kyu-Young Whang of the College of Computing were selected as the winners of the "2017 Korea Best Science and Technology Award" by the Ministry of Science, ICT and Future Planning (MSIP) and the Korea Federation of Science and Technology Societies.
The award, which was established in 2003, is the highest honor bestowed to the two most outstanding scientists in Korea annually. This is the first time that KAIST faculty members have swept the award since its founding.
Distinguished Professor Lee is renowned for his pioneering studies of system metabolic engineering, which produces useful chemicals by utilizing microorganisms. Professor Lee has developed a number of globally-recognized original technologies such as gasoline production using micro-organisms, a bio-butanol production process, microbes for producing nylon and plastic raw materials, and making native-like spider silk produced in metabolically engineering bacterium which is stronger than steel but finer than human hair.
System metabolism engineering was also selected as one of the top 10 promising technologies in the world in 2016 by the World Economic Forum. Selected as one of the world’s top 20 applied bioscientists in 2014 by Nature Biotechnology, he has many ‘first’ titles in his academic and research careers. He was the first Asian to win the James Bailey Award (2016) and Marvin Johnson Award (2012), the first Korean elected to both the US National Academy of Science (NAS) and the National Academy of Engineering (NAE) this year. He is the dean of KAIST institutes, a multi and interdisciplinary research institute at KAIST. He serves as co-chair of the Global Council on Biotechnology and as a member of the Global Future Council on the Fourth Industrial Revolution at the World Economic Forum.
Distinguished Professor Whang, the first recipient in the field of computer science in this award, has been recognized for his lifetime achievement and contributions to the development of the software industry and the spreading of information culture. He has taken a pioneering role in presenting novel theories and innovative technologies in the field of database systems such as probabilistic aggregation, multidimensional indexing, query, and database and information retrieval. The Odysseus database management system Professor Hwang developed has been applied in many diverse fields of industry, while promoting the domestic software industry and its technical independence.
Professor Hwang is a fellow at the American Computer Society (ACM) and life fellow at IEEE. Professor Whang received the ACM SIGMOD Contributions Award in 2014 for his work promoting database research worldwide, the PAKDD Distinguished Contributions Award in 2014, and the DASFAA Outstanding Contributions Award in 2011 for his contributions to database and data mining research in the Asia-Pacific region. He is also the recipient of the prestigious Korea (presidential) Engineering Award in 2012.
2017.07.03 View 9134 -
Professor Poong Hyun Seong Selected as Fellow of the ANS
Professor Poong Hyun Seong of the Department of Nuclear and Quantum Engineering was selected as a fellow of the American Nuclear Society.
The selection was announced at their annual meeting held in San Francisco on June 12, in recognition of Professor Seong's contributions to the field of nuclear instrumentation, control andhuman factors engineering.
Founded in 1954, the American Nuclear Society selects scholars who have made outstanding achievements and contributions to the development of the nuclear engineering field each year.
Professor Seong's researches in the field of nuclear instrumentation, control and human factors engineering have contributed to the safe operation of nuclear power plants, to the development of systems to maintain nuclear power plants safely in the event of emergency and to the enhancement of effective response capabilities of nuclear power plant operators. His researches significantly contributed to the safety improvement of nuclear power plants and have been recognized worldwide.
Professor Seong said, "Korea has emerged as a nuclear powerhouse. I think not only my academic career but our national reputation in the field of nuclear research has been well recognized by our global peers.” Professor Seong has served as president of the Korean Nuclear Society, editor in chief of Nuclear Engineering and Technology, and as a commissioner of the Korean Nuclear Safety Commission. He is currently working as a commissioner of the Korean Atomic Energy Commission.
2017.06.29 View 6484 -
Winning Best in Theme Award in NASA RASC-AL
A students team from the Department of Aerospace Engineering won the Best in Theme Award for moon exploration system design at Revolutionary Aerospace Systems Concepts - Academic Linkage (RASC-AL), an aerospace mission system design competition organized by NASA in the USA.
The KAIST team, consisting of Jaeyoul Ko, Jongeun Suh, Juseong Lee, Sukmin Choi, and Eunkwang Lee, and supervised by Professor Jaemyung Ahn, competed as a joint team with Texas Tech University and the Royal Melbourne Institute of Technology in Australia,
The joint team was selected as one of the 14 finalists after two preliminary rounds. The finals of RASC-AL Forum took place from May 30 to June 3 in Florida. The team received the top prize with their design entitled ‘Earth to Lunar Interchangeable Transportation Environment (ELITE) for Logistics Delivery Systems’, one of the four themes of the competition.
Since 2002, RASC-AL competitions, managed by NASA, have been held with themes on innovative aerospace system and missions, in which world-class undergraduate and graduate students have participated.
This year’s themes were ▲ Lightweight Exercise Suite ▲ Airlock Design ▲ Commercially Enabled LEO/Mars Habitable Module and ▲ Logistics Delivery System.
Moon exploration requires a great deal of time and supplies. The KAIST team has been researching supply delivery systems in space for long-term manned moon exploration with their joint team for the last eight months. In particular, incidents can occur during the initial stages of long-term manned moon exploration missions that are unpredictable during system design and planning. Therefore, to cope with such unpredictability in the mission, the KAIST team deduced a system and an operational concept with increased flexibility to maximize the cost effectiveness of the supply transport.
The spacecraft was divided into propulsion and transport modules based on their functionalities, and can allow the flexibility by switching the transport module according to the demands of the moon base. The operational flexibility and cost effectiveness are further increased by introducing multiple departure orbits from the Earth (e.g. low Earth orbit vs. geosynchronous Earth orbit) enabled by utilization of various launch vehicles.
Professor Ahn, the advisor for the team, said, “I am proud of the students who collaborated with the international joint teams and achieved great result.” He continued, “I believe this to be the result of continuous efforts and initiatives of the department for system design-centered education. We will keep providing high-quality system design and education through various opportunities such as international cooperation in design education.”
(Photo caption: KAIST team of the Department of Aerospace Engineering poses after winning the Best in Theme Award in NASA's RASC-AL)
2017.06.22 View 7479 -
Face Recognition System 'K-Eye' Presented by KAIST
Artificial intelligence (AI) is one of the key emerging technologies. Global IT companies are competitively launching the newest technologies and competition is heating up more than ever. However, most AI technologies focus on software and their operating speeds are low, making them a poor fit for mobile devices. Therefore, many big companies are investing to develop semiconductor chips for running AI programs with low power requirements but at high speeds.
A research team led by Professor Hoi-Jun Yoo of the Department of Electrical Engineering has developed a semiconductor chip, CNNP (CNN Processor), that runs AI algorithms with ultra-low power, and K-Eye, a face recognition system using CNNP. The system was made in collaboration with a start-up company, UX Factory Co.
The K-Eye series consists of two types: a wearable type and a dongle type. The wearable type device can be used with a smartphone via Bluetooth, and it can operate for more than 24 hours with its internal battery. Users hanging K-Eye around their necks can conveniently check information about people by using their smartphone or smart watch, which connects K-Eye and allows users to access a database via their smart devices. A smartphone with K-EyeQ, the dongle type device, can recognize and share information about users at any time.
When recognizing that an authorized user is looking at its screen, the smartphone automatically turns on without a passcode, fingerprint, or iris authentication. Since it can distinguish whether an input face is coming from a saved photograph versus a real person, the smartphone cannot be tricked by the user’s photograph.
The K-Eye series carries other distinct features. It can detect a face at first and then recognize it, and it is possible to maintain “Always-on” status with low power consumption of less than 1mW. To accomplish this, the research team proposed two key technologies: an image sensor with “Always-on” face detection and the CNNP face recognition chip.
The first key technology, the “Always-on” image sensor, can determine if there is a face in its camera range. Then, it can capture frames and set the device to operate only when a face exists, reducing the standby power significantly. The face detection sensor combines analog and digital processing to reduce power consumption. With this approach, the analog processor, combined with the CMOS Image Sensor array, distinguishes the background area from the area likely to include a face, and the digital processor then detects the face only in the selected area. Hence, it becomes effective in terms of frame capture, face detection processing, and memory usage.
The second key technology, CNNP, achieved incredibly low power consumption by optimizing a convolutional neural network (CNN) in the areas of circuitry, architecture, and algorithms. First, the on-chip memory integrated in CNNP is specially designed to enable data to be read in a vertical direction as well as in a horizontal direction. Second, it has immense computational power with 1024 multipliers and accumulators operating in parallel and is capable of directly transferring the temporal results to each other without accessing to the external memory or on-chip communication network. Third, convolution calculations with a two-dimensional filter in the CNN algorithm are approximated into two sequential calculations of one-dimensional filters to achieve higher speeds and lower power consumption.
With these new technologies, CNNP achieved 97% high accuracy but consumed only 1/5000 power of the GPU. Face recognition can be performed with only 0.62mW of power consumption, and the chip can show higher performance than the GPU by using more power.
These chips were developed by Kyeongryeol Bong, a Ph. D. student under Professor Yoo and presented at the International Solid-State Circuit Conference (ISSCC) held in San Francisco in February. CNNP, which has the lowest reported power consumption in the world, has achieved a great deal of attention and has led to the development of the present K-Eye series for face recognition.
Professor Yoo said “AI - processors will lead the era of the Fourth Industrial Revolution. With the development of this AI chip, we expect Korea to take the lead in global AI technology.”
The research team and UX Factory Co. are preparing to commercialize the K-Eye series by the end of this year. According to a market researcher IDC, the market scale of the AI industry will grow from $127 billion last year to $165 billion in this year.
(Photo caption: Schematic diagram of K-Eye system)
2017.06.14 View 15988