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Electrosprayed Micro Droplets Help Kill Bacteria and Viruses
With COVID-19 raging around the globe, researchers are doubling down on methods for developing diverse antimicrobial technologies that could be effective in killing a virus, but harmless to humans and the environment. A recent study by a KAIST research team will be one of the responses to such efforts. Professor Seung Seob Lee and Dr. Ji-hun Jeong from the Department of Mechanical Engineering developed a harmless air sterilization prototype featuring electrosprayed water from a polymer micro-nozzle array. This study is one of the projects being supported by the KAIST New Deal R&D Initiative in response to COVID-19. Their study was reported in Polymer. The electrosprayed microdroplets encapsulate reactive oxygen species such as hydroxyl radicals, superoxides that are known to have an antimicrobial function. The encapsulation prolongs the life of reactive oxygen species, which enable the droplets to perform their antimicrobial function effectively. Prior research has already proven the antimicrobial and encapsulation effects of electrosprayed droplets. Despite its potential for antimicrobial applications, electrosprayed water generally operates under an electrical discharge condition, which can generate ozone. The inhalation of ozone is known to cause damage to the respiratory system of humans. Another technical barrier for electrospraying is the low flow rate problem. Since electrospraying exhibits the dependence of droplet size on the flow rate, there is a limit for the amount of water microdroplets a single nozzle can produce. With this in mind, the research team developed a dielectric polymer micro-nozzle array to perform the multiplexed electrospraying of water without electrical discharge. The polymer micro-nozzle array was fabricated using the MEMS (Micro Electro-Mechanical System) process. According to the research team, the nozzle can carry five to 19 micro-nozzles depending on the required application. The high aspect ratio of the micro-nozzle and an in-plane extractor were proposed to concentrate the electric field at the tip of the micro-nozzle, which prevents the electrical discharge caused by the high surface tension of water. A micro-pillar array with a hydrophobic coating around the micro-nozzle was also proposed to prevent the wetting of the micro-nozzle array. The polymer micro-nozzle array performed in steady cone jet mode without electrical discharge as confirmed by high-speed imaging and nanosecond pulsed imaging. The water microdroplets were measured to be in the range of six to 10 μm and displayed an antimicrobial effect on Escherichia coli and Staphylococcus aureus. Professor Lee said, “We believe that this research can be applied to air conditioning products in areas that require antimicrobial and humidifying functions.” Publication: Jeong, J. H., et al. (2020) Polymer micro-atomizer for water electrospray in the cone jet mode. Polymer. Vol. No. 194, 122405. Available online at https://doi.org/10.1016/j.polymer.2020.122405 Profile: Seung Seob Lee, Ph.D. email@example.com http://mmst.kaist.ac.kr/ Professor Department of Mechanical Engineering (ME) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea Profile: Ji-hun Jeong, Ph.D. firstname.lastname@example.org Postdoctoral researcher Department of Mechanical Engineering (ME) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea (END)
Emeritus Professor Jae-Kyu Lee Wins the AIS LEO Award
Emeritus Professor Jae-Kyu Lee has won the Association for Information Systems LEO Award 2020. Professor Lee, the first Korean to receive the LEO Award, was recognized for his research and development in preventative cyber security, which is a major part of the efforts he leads to realize what Professor Lee has named "Bright Internet." Established in 1999, this award was named after the world’s first business application of computing, the Lyons Electronic Office and recognizes outstanding individuals in the field of information systems. The LEO Award recognized four winners including Professor Lee this year. He has been professor and HHI Chair Professor at KAIST from 1985 to 2016 since he has received his Ph.D. in information and operations management from the Wharton School, University of Pennsylvania. He served as the Dean of College of Business and supervised around 30 doctoral students. He is currently the Distinguished Professor of School of Management at Xi’an Jiaotong University. His research mainly focused on the creation of Bright Internet for preventive cybersecurity, improving relevance of research from Axiomatic Theories, and development of AI for electronic commerce and managerial decision support. He is a fellow and was the president of the Association for Information Systems, and co-chaired the International Conference on Information Systems in 2017. He was the founder of Principles for the Bright Internet and established the Bright Internet Research Center at KAIST and Xi’an Jiatong University. He also established the Bright Internet Global Summit since ICIS 2017 in Seoul, and organized the Bright Internet Project Consortium in 2019 as a combined effort of academia-industry partnership. (www.brightinternet.org.) He was a charter member of the Pacific Asia Conference in Information Systems, and served as conference chair. He was the founder editor-in-chief of the journal, Electronic Commerce Research and Applications (Elsevier), and was the founding chair of the International Conference on Electronic Commerce. In Korea, her served as president of Korea Society of Management Information Systems and Korea Society of Intelligent Information Systems. "I am honored to be designated the first Korean winner of the honorable LEO Award," Lee said. "Based on my life-long efforts for developments in the field, I will continue to contribute to the research and development of information media systems."
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)
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 Lee email@example.com http://mbel.kaist.ac.kr Department of Chemical and Biomolecular Engineering KAIST
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 firstname.lastname@example.org 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 email@example.com Department of Bio and Brain Engineering, KAIST Profile: Min Song Ph.D. Candidate firstname.lastname@example.org Program of Brain and Cognitive Engineering, KAIST (END)
Researchers Present a Microbial Strain Capable of Massive Succinic Acid Production
A research team led by Distinguished Professor Sang Yup Lee reported the production of a microbial strain capable of the massive production of succinic acid with the highest production efficiency to date. This strategy of integrating systems metabolic engineering with enzyme engineering will be useful for the production of industrially competitive bio-based chemicals. Their strategy was described in Nature Communications on April 23. The bio-based production of industrial chemicals from renewable non-food biomass has become increasingly important as a sustainable substitute for conventional petroleum-based production processes relying on fossil resources. Here, systems metabolic engineering, which is the key component for biorefinery technology, is utilized to effectively engineer the complex metabolic pathways of microorganisms to enable the efficient production of industrial chemicals. Succinic acid, a four-carbon dicarboxylic acid, is one of the most promising platform chemicals serving as a precursor for industrially important chemicals. Among microorganisms producing succinic acid, Mannheimia succiniciproducens has been proven to be one of the best strains for succinic acid production. The research team has developed a bio-based succinic acid production technology using the M. succiniciproducens strain isolated from the rumen of Korean cow for over 20 years and succeeded in developing a strain capable of producing succinic acid with the highest production efficiency. They carried out systems metabolic engineering to optimize the succinic acid production pathway of the M. succiniciproducens strain by determining the crystal structure of key enzymes important for succinic acid production and performing protein engineering to develop enzymes with better catalytic performance. As a result, 134 g per liter of succinic acid was produced from the fermentation of an engineered strain using glucose, glycerol, and carbon dioxide. They were able to achieve 21 g per liter per hour of succinic acid production, which is one of the key factors determining the economic feasibility of the overall production process. This is the world’s best succinic acid production efficiency reported to date. Previous production methods averaged 1~3 g per liter per hour. Distinguished professor Sang Yup Lee explained that his team’s work will significantly contribute to transforming the current petrochemical-based industry into an eco-friendly bio-based one. “Our research on the highly efficient bio-based production of succinic acid from renewable non-food resources and carbon dioxide has provided a basis for reducing our strong dependence on fossil resources, which is the main cause of the environmental crisis,” Professor Lee said. This work was supported by the Technology Development Program to Solve Climate Changes via Systems Metabolic Engineering for Biorefineries and the C1 Gas Refinery Program from the Ministry of Science and ICT through the National Research Foundation of Korea.
Professor Minsoo Rhu Recognized as Facebook Research Scholar
Professor Minsoo Rhu from the School of Electrical Engineering was selected as the recipient of the Systems for Machine Learning Research Awards presented by Facebook. Facebook launched the award last year with the goal of funding impactful solutions in the areas of developer tookits, compilers and code generation, system architecture, memory technologies, and machine learning accelerator support. A total of 167 scholars from 100 universities representing 26 countries submitted research proposals, and Facebook selected final 10 scholars. Professor Rhu made the list with his research topic ‘A Near-Memory Processing Architecture for Training Recommendation Systems.’ He will receive 5,000 USD in research funds at the award ceremony which will take place during this year’s AI Systems Faculty Summit at the Facebook headquarters in Menlo Park, California. Professor Rhu’s submission was based on research on ‘Memory-Centric Deep Learning System Architecture’ that he carried out for three years under the auspices of Samsung Science and Technology Foundation from 2017. It was an academic-industrial cooperation research project in which leading domestic companies like Samsung Electronics and SK Hynix collaborated to make a foray into the global memory-centric smart system semiconductor market. Professor Rhu who joined KAIST in 2018 has led various systems research projects to accelerate the AI computing technology while working at NVIDIA headquarters from 2014. (END)
What Fuels a “Domino Effect” in Cancer Drug Resistance?
KAIST researchers have identified mechanisms that relay prior acquired resistance to the first-line chemotherapy to the second-line targeted therapy, fueling a “domino effect” in cancer drug resistance. Their study featured in the February 7 edition of Science Advances suggests a new strategy for improving the second-line setting of cancer treatment for patients who showed resistance to anti-cancer drugs. Resistance to cancer drugs is often managed in the clinic by chemotherapy and targeted therapy. Unlike chemotherapy that works by repressing fast-proliferating cells, targeted therapy blocks a single oncogenic pathway to halt tumor growth. In many cases, targeted therapy is engaged as a maintenance therapy or employed in the second-line after front-line chemotherapy. A team of researchers led by Professor Yoosik Kim from the Department of Chemical and Biomolecular Engineering and the KAIST Institute for Health Science and Technology (KIHST) has discovered an unexpected resistance signature that occurs between chemotherapy and targeted therapy. The team further identified a set of integrated mechanisms that promotes this kind of sequential therapy resistance. “There have been multiple clinical accounts reflecting that targeted therapies tend to be least successful in patients who have exhausted all standard treatments,” said the first author of the paper Mark Borris D. Aldonza. He continued, “These accounts ignited our hypothesis that failed responses to some chemotherapies might speed up the evolution of resistance to other drugs, particularly those with specific targets.” Aldonza and his colleagues extracted large amounts of drug-resistance information from the open-source database the Genomics of Drug Sensitivity in Cancer (GDSC), which contains thousands of drug response data entries from various human cancer cell lines. Their big data analysis revealed that cancer cell lines resistant to chemotherapies classified as anti-mitotic drugs (AMDs), toxins that inhibit overacting cell division, are also resistant to a class of targeted therapies called epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). In all of the cancer types analyzed, more than 84 percent of those resistant to AMDs, representatively ‘paclitaxel’, were also resistant to at least nine EGFR-TKIs. In lung, pancreatic, and breast cancers where paclitaxel is often used as a first-line, standard-of-care regimen, greater than 92 percent showed resistance to EGFR-TKIs. Professor Kim said, “It is surprising to see that such collateral resistance can occur specifically between two chemically different classes of drugs.” To figure out how failed responses to paclitaxel leads to resistance to EGFR-TKIs, the team validated co-resistance signatures that they found in the database by generating and analyzing a subset of slow-doubling, paclitaxel-resistant cancer models called ‘persisters’. The results demonstrated that paclitaxel-resistant cancers remodel their stress response by first becoming more stem cell-like, evolving the ability to self-renew to adapt to more stressful conditions like drug exposures. More surprisingly, when the researchers characterized the metabolic state of the cells, EGFR-TKI persisters derived from paclitaxel-resistant cancer cells showed high dependencies to energy-producing processes such as glycolysis and glutaminolysis. “We found that, without an energy stimulus like glucose, these cells transform to becoming more senescent, a characteristic of cells that have arrested cell division. However, this senescence is controlled by stem cell factors, which the paclitaxel-resistant cancers use to escape from this arrested state given a favorable condition to re-grow,” said Aldonza. Professor Kim explained, “Before this research, there was no reason to expect that acquiring the cancer stem cell phenotype that dramatically leads to a cascade of changes in cellular states affecting metabolism and cell death is linked with drug-specific sequential resistance between two classes of therapies.” He added, “The expansion of our work to other working models of drug resistance in a much more clinically-relevant setting, perhaps in clinical trials, will take on increasing importance, as sequential treatment strategies will continue to be adapted to various forms of anti-cancer therapy regimens.” This study was supported by the Basic Science Research Program of the National Research Foundation of Korea (NRF-2016R1C1B2009886), and the KAIST Future Systems Healthcare Project (KAISTHEALTHCARE42) funded by the Korean Ministry of Science and ICT (MSIT). Undergraduate student Aldonza participated in this research project and presented the findings as the lead author as part of the Undergraduate Research Participation (URP) Program at KAIST. < Figure 1. Schematic overview of the study. > < Figure 2. Big data analysis revealing co-resistance signatures between classes of anti-cancer drugs. > Publication: Aldonza et al. (2020) Prior acquired resistance to paclitaxel relays diverse EGFR-targeted therapy persistence mechanisms. Science Advances, Vol. 6, No. 6, eaav7416. Available online at http://dx.doi.org/10.1126/sciadv.aav7416 Profile: Prof. Yoosik Kim, MA, PhD email@example.com https://qcbio.kaist.ac.kr/ Assistant Professor Bio Network Analysis Laboratory Department of Chemical and Biomolecular Engineering Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon, Republic of Korea Profile: Mark Borris D. Aldonza firstname.lastname@example.org Undergraduate Student Department of Biological Sciences Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon, Republic of Korea (END)
Professor Junil Choi Receives Stephen O. Rice Prize
< Professor Junil Choi (second from the left) > Professor Junil Choi from the School of Electrical Engineering received the Stephen O. Rice Prize at the Global Communications Conference (GLOBECOM) hosted by the Institute of Electrical and Electronics Engineers (IEEE) in Hawaii on December 10, 2019. The Stephen O. Rice Prize is awarded to only one paper of exceptional merit every year. The IEEE Communications Society evaluates all papers published in the IEEE Transactions on Communications journal within the last three years, and marks each paper by aggregating its scores on originality, the number of citations, impact, and peer evaluation. Professor Choi won the prize for his research on one-bit analog-to-digital converters (ADCs) for multiuser massive multiple-input and multiple-output (MIMO) antenna systems published in 2016. In his paper, Professor Choi proposed a technology that can drastically reduce the power consumption of the multiuser massive MIMO antenna systems, which are the core technology for 5G and future wireless communication. Professor Choi’s paper has been cited more than 230 times in various academic journals and conference papers since its publication, and multiple follow-up studies are actively ongoing. In 2015, Professor Choi received the IEEE Signal Processing Society Best Paper Award, an award equals to the Stephen O. Rice Prize. He was also selected as the winner of the 15th Haedong Young Engineering Researcher Award presented by the Korean Institute of Communications and Information Sciences (KICS) on December 6, 2019 for his outstanding academic achievements, including 34 international journal publications and 26 US patent registrations. (END)
Two Professors Receive Awards from the Korea Robotics Society
< Professor Jee-Hwan Ryu and Professor Ayoung Kim > The Korea Robotics Society (KROS) conferred awards onto two KAIST professors from the Department of Civil and Environmental Engineering in recognition of their achievements and contributions to the development of the robotics industry in 2019. Professor Jee-Hwan Ryu has been actively engaged in researching the field of teleoperation, and this led him to win the KROS Robotics Innovation (KRI) Award. The KRI Award was newly established in 2019 by the KROS, in order to encourage researchers who have made innovative achievements in robotics. Professor Ryu shared the honor of being the first winner of this award with Professor Jaeheung Park of Seoul National University. Professor Ayoung Kim, from the same department, received the Young Investigator Award presented to emerging robitics researchers under 40 years of age. (END)
KAIST and Google Jointly Develop AI Curricula
KAIST selected the two professors who will develop AI curriculum under the auspices of the KAIST-Google Partnership for AI Education and Research. The Graduate School of AI announced the two authors among the 20 applicants who will develop the curriculum next year. They will be provided 7,500 USD per subject. Professor Changho Suh from the School of Electrical Engineering and Professor Yong-Jin Yoon from the Department of Mechanical Engineering will use Google technology such as TensorFlow, Google Cloud, and Android to create the curriculum. Professor Suh’s “TensorFlow for Information Theory and Convex Optimization “will be used for curriculum in the graduate courses and Professor Yoon’s “AI Convergence Project Based Learning (PBL)” will be used for online courses. Professor Yoon’s course will explore and define problems by utilizing AI and experiencing the process of developing products that use AI through design thinking, which involves product design, production, and verification. Professor Suh’s course will discus“information theory and convergence,” which uses basic sciences and engineering as well as AI, machine learning, and deep learning.
Object Identification and Interaction with a Smartphone Knock
(Professor Lee (far right) demonstrate 'Knocker' with his students.) A KAIST team has featured a new technology, “Knocker”, which identifies objects and executes actions just by knocking on it with the smartphone. Software powered by machine learning of sounds, vibrations, and other reactions will perform the users’ directions. What separates Knocker from existing technology is the sensor fusion of sound and motion. Previously, object identification used either computer vision technology with cameras or hardware such as RFID (Radio Frequency Identification) tags. These solutions all have their limitations. For computer vision technology, users need to take pictures of every item. Even worse, the technology will not work well in poor lighting situations. Using hardware leads to additional costs and labor burdens. Knocker, on the other hand, can identify objects even in dark environments only with a smartphone, without requiring any specialized hardware or using a camera. Knocker utilizes the smartphone’s built-in sensors such as a microphone, an accelerometer, and a gyroscope to capture a unique set of responses generated when a smartphone is knocked against an object. Machine learning is used to analyze these responses and classify and identify objects. The research team under Professor Sung-Ju Lee from the School of Computing confirmed the applicability of Knocker technology using 23 everyday objects such as books, laptop computers, water bottles, and bicycles. In noisy environments such as a busy café or on the side of a road, it achieved 83% identification accuracy. In a quiet indoor environment, the accuracy rose to 98%. The team believes Knocker will open a new paradigm of object interaction. For instance, by knocking on an empty water bottle, a smartphone can automatically order new water bottles from a merchant app. When integrated with IoT devices, knocking on a bed’s headboard before going to sleep could turn off the lights and set an alarm. The team suggested and implemented 15 application cases in the paper, presented during the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2019) held in London last month. Professor Sung-Ju Lee said, “This new technology does not require any specialized sensor or hardware. It simply uses the built-in sensors on smartphones and takes advantage of the power of machine learning. It’s a software solution that everyday smartphone users could immediately benefit from.” He continued, “This technology enables users to conveniently interact with their favorite objects.” The research was supported in part by the Next-Generation Information Computing Development Program through the National Research Foundation of Korea funded by the Ministry of Science and ICT and an Institute for Information & Communications Technology Promotion (IITP) grant funded by the Ministry of Science and ICT. Figure: An example knock on a bottle. Knocker identifies the object by analyzing a unique set of responses from the knock, and automatically launches a proper application or service.
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