Profs. Sukyoung Ryu, Sung-Ju Lee, Junehwa Song, an..
Profs. Sukyoung Ryu, Sung-Ju Lee, Junehwa Song, and Min H. Kim＇s research projects were selected to be presented in KAIST Breakthroughs. Prof. Sukyoung Ryu: HybriDroid: Static analysis framework for android hybrid applications http://breakthroughs.kaist.ac.kr/?post_no=1027 Prof. Sung-Ju Lee & Junehwa Song: Zaturi: Create an audiobook for your baby using time that slips by http://breakthroughs.kaist.ac.kr/?post_no=1029 Prof. Min H. Kim: Compact hyperspectral imaging at low cost http://breakthroughs.kaist.ac.kr/?post_no=1026 Congratulations on being accepted for KAIST Breakthroughs 2018 Spring！...Read more
ICSE 2018 Paper acceptance
KAIST team has newly suggested the unit testing of C programs that can find errors automatically while minimizing false alarms. Prof. Moonzoo Kim and Dr. Yoon Ho Kim wrote a paper "Precise Concolic Unit Testing of C Programs with Alarm Filtering Using Symbolic Calling Contexts" in collaboration with Prof. Yoon Ja Choi at Kyung-Buk University. Their paper has been accepted to ACM/IEEE ICSE (Intl. Conf. on Software Engineering) which is one of the most prestigious conferences in the Software Engineering field. Congratulations！...Read more
Two papers accepted at ACM POPL 2018, a top intern..
Two papers from the KAIST School of Computing got accepted for ACM POPL 2018, a top international conference on programming languages. The first paper is “On Automatically Proving the Correctness of math.h Implementations“ authored by Mr Wonyeol Lee in the school and his colleagues in Microsoft and Stanford (Sharma and Aiken). The second paper is “Denotational Validation of Higher-Order Bayesian Inference“ written by Prof Hongseok Yang in the school and his colleagues in Oxford, Cambridge, Tubingen and Edinburgh (Scibior, Kammar, Vakar, Staton, Cai, Ostermann, Moss, Heunen, Ghahramani)....Read more
Prof. Sung-Ju Lee＇s SCAN and Prof. Alice Oh＇s Elip..
Prof. Sung-Ju Lee's SCAN and Prof. Alice Oh's Eliph system were selected to be presented in KAIST Breakthroughs. Prof. Sung-Ju Lee's SCAN system (http://breakthroughs.kaist.ac.kr/?post_no=913) Prof. Alice Oh's Eliph system (http://breakthroughs.kaist.ac.kr/?post_no=908) Congratulations on both teams！...Read more
Prof. Hongseok Yang presented a keynote at QONFEST..
KAIST SoC Prof. Hongseok Yang presented a keynote at QONFEST’17 as a joint invited speaker for CONCUR, QUEST, and FORMATS. Prof. Hongseok Yang at the KAIST School of Computing presented a keynote talk on probabilistic programming at QONFEST’17, as a joint invited speaker for CONCUR, QUEST, and FORMATS. QONFEST’17 is the umbrella event of the four major international conferences CONCUR, QEST, FORMATS, and EPEW, whose topics jointly cover theory, formal modeling, verification, performance evaluation and engineering of concurrent, timed and other systems. QONFEST '17 was held in Berlin, Germany from September 4, 2017, until September 9, 2017....Read more
Prof. Sang Kil Cha’s paper accepted by IEEE／ACM AS..
IEEE/ACM ASE 2017 (Automated Software Engineering), a top international conference on software engineering, accepted a paper from School of Computing’s Graduate School of Information Security. Professor Sang Kil Cha, alongside Soomin Kim and KAIST Cyber Security Research Center, worked on the paper, “Testing Intermediate Representations for Binary Analysis”. The research was a part of Prof. Cha’s project with the Ministry of Science and ICT, a R&D project carried out since 2016 in cooperation with KAIST Cyber Security Research Center. The project is on comparing the expressiveness of existing intermediate representations used for binary analysis. The paper will be presented at IEEE/ACM ASE 2017 conference, held Oct. 30 to Nov. 3 at Illinois, US. Reference: http://ase2017.org...Read more
Prof. Dongman Lee Unveils “Placeness Data Mining a..
ㅁ KAIST Professors Dongman Lee, Wonjae Lee, Juyong Park, Meeyoung Cha, and their respective research teams unveiled their “Placeness Data Mining and Inference”, a part of their research on the development of core technologies for placeness based data mining for use in real time intelligent information suggestion services in the context of smart spaces. ㅇ The API is available at placeness.kaist.ac.kr:8080/, with the wiki on relevant information available at placeness.kaist.ac.kr/wiki ㅇ The development of core technologies for placeness based data mining for use in real time intelligent information suggestion services in the context of smart space was a government funded R&D effort, running from 2015 July to 2017 Aug, supported by the Ministry of Science and ICT (former Ministry of Science, ICT, and Future Planning). ㅇ This research analyzes the vast amounts of geotagged multimedia and text data generated by online social networking services to garner the purpose and social context of specific commercial locations’ visitors, and through this data infer the social actions, emotion, and the relationship the user has with the location. ㅇ The recently unveiled API relies on data collected and analyzed from the current major R&D objective locations (e.g. COEX, IPark Mall) and their constituent locations. Social multimedia data collected from the locations are analyzed to provide locational context from various perspectives (passers-by, visitor, time, emotion, etc). A REST API allows access via HTTP requests for the general public, providing the placeness information of the major spaces. ㅁ The above API provides 4 different inferences arising from the process of placeness inference: 1) placeness of the location of which this place is a constituent of, 2) placeness of the location within the context of the aforementioned parent location, 3) emotion based inference on the location and its parent location’s ambience, and 4) the user-location relationship. ㅇ The 4 inferences include the following information: - Fundamental technology for real time placeness matching via the analysis of users’ social context within the locality - Fundamental technology for the inference of granular placeness inference via the application of standardized data structures - Fundamental technology for the inference of placeness for reflecting the user’s diachronic / immediate context, thereby presenting a multidimensional relationship connectivity graph between localities and users - Fundamental technology for emotion inference for real time location suggestion and user specific locality emotion score output based on the inference ㅇ The information provided enables developers to improve the accuracy and satisfaction of location suggestion services, as well as mine social data for social contexts and the resultant public visitation patterns and changes in preferences, with which specific locations can be suggested, and advertising and coupons created for the purpose of promoting the consumption of specific contents within the locality. ㅁ Prof. Dongman Lee (Project Lead) claims the API developed during the research effort improves the quality of existing geography based location search and suggestion services, automatically providing changing location suggestions based on urban visitors’ changing location visit trends. The research is expected to form the core of technologies to overcome the limitations in the previous non-standardized text data analysis, harnessing both image and text simultaneously to infer the social information of the location, leading to a leap in existing location based suggestion services and AI based personal assistant services. ㅁ Placeness data mining and inference technology is applicable in various location based information search and suggestion service providers and location based social commerce services, allowing information search companies and mobile coupon providers to offer intelligent information suggestion functionalities and their improvement....Read more
CCA 2017 Held
From July 24 to 28, KAIST’s School of Computing organized and hosted the 14th International Conference on Computability and Complexity in Analysis (CCA2017) and Workshop on Real Verification: http://complexity.kaist.edu/CCA2017 48 leading senior experts, rising young scientists, and eager students have attended and contributed to this unique event. They came from all over the world: Amsterdam, Birmingham, Brussels, Buenos Aires, Bulgaria, Cambridge, Connecticut, Cornell, Darmstadt, Hagen, Kyoto, Maastricht, Munich, Nagoya, Okinawa, Pohang, Pretoria, Saarbrücken, Seoul, Singapore, Tokyo, Trier, and Versailles. Over the course of five days we had 33 presentations of recent research, discussions of current challenges, and explorations of future developments in the Algorithmic Foundations of Numerics. The organizers gratefully acknowledge generous financial support from KAIST's School of Computing, from the International Relations Team (IRT), and from the National Research Foundation of Korea (NRF). Co-located with CCA 2017, a Workshop on Real Verification was organized by Prof. Gyesik Lee (Hankyong National University) and Prof. Martin Ziegler (KAIST) with invited speakers from Yonsei University, INRIA, Aston University, Trier University, KAIST, SNU, and AdaCore. For many participants this was the first time to visit Korea: They have particularly enjoyed the impressive experience of this technologically advanced country as well as of its warm hospitality, culinary richness, and cultural heritage. In fact, as part of a joint NRF/EU H2020 project, five conference participants continue staying at KAIST throughout August for further collaborative research...Read more
KAIST SoC Associate Prof. Jinah Park Presents the ..
KAIST School of Computing Associate Professor Jinah Park presented the keynote at the 21st Medical Image Understanding and Analysis Conference (MIUA 2017) last July 11 through 13, held at John McIntyre Centre, Pollock Halls, Edinburgh, UK. The presentation was on “model-based approach to 3D shape recovery and analysis.” MIUA 2017 is a medical image analysis forum for experts in the field held every year in the UK, boasting attendees from various European countries as well as the US, Australia, and Asia. This year, of the 150 organizations attending the conference, 46 were not from the UK, and out of the 105 papers and 22 clinical abstracts submitted, 82 were from overseas. KAIST SoC Prof. Jinah Park was invited as a keynote presenter alongside Prof. Ingela Nyström (Uppsala University) and Prof. Daniel Rueckert (Imperial College London). The conference also invited Sir Michael Brady, a Professor at the University of Oxford, as the Honorary Guest Speaker. Prof. Jinah Park’s lecture was on her 3 dimensional modeling technique for extracting clinical understanding from clinical imaging data, a subject she has worked on for two decades....Read more
KAIST Computer Graphics enters world top 20
KAIST became the first Korean university to have one of the world’s top 20 Computer Graphics research institutes, based on the number of papers published in the last 2 years in the top 3 CG conferences. KAIST School of Computing undergraduate CG lecture professors (CS380, by professors Min H. Kim, Jinah Park, and Sungeui Yoon) participated in a survey to mark this occasion. The survey was presented at Eurographics 2017, one of the top 3 graphics conferences alongside ACM SIGGRAPH and SIGGRAPH Asia. The presentation contained content from Prof. Kim’s undergraduate level lecture, which can be found at http://vclab.kaist.ac.kr/cs380/. We extend our most sincere congratulations. [Reference] [Reference] “What we are teaching in Introduction to Computer Graphics”, Balreira, Dennis G.; Walter, Marcelo; Fellner, Dieter W., Proc. Eurographics 2017, The Eurographics Association, http://diglib.eg.org/handle/10.2312/eged20171019 [Eurographics Presentation] http://wiki.inf.ufrgs.br/What_we_are_Teaching_in_Introduction_to_Computer_Graphics...Read more
Three KAIST SoC papers presented at ACM CSCW 2017
Three papers by KAIST SoC students Jung Guk Park (Doctorate, advisor: Prof. Alice Oh), Chunjong Park (M.S., advisor: Prof. Sung-Ju Lee), and Bumsoo Kang (Doctorate, advisor: Prof. Junehwa Song) were presented at CSCW 2017. The 20th ACM Conference on Computer-Supported Cooperative Work and Social Computing, held from last Feb. 25th to Mar. 1st, is one of the best conferences in HCI (Human Computer Interaction) and Social Computing. CSCW focuses on research on designing and utilizing technologies for groups and communities, and has a long history of being considered one of the best conferences for HCI and Social Computing. KAIST School of Computing led global research efforts in said fields, presenting three papers this year. The paper from Prof. Alice Oh’s lab was by Jung Guk Park, presenting a system that shows how a piece of code was written, letter by letter, for students that have problems understanding others’ code during SoC class peer assessments. The paper received an Honorable Mention Award. Alumnus Chunjong Park presented a technology to detect breaks between social activities via various smartphone sensors, and notify the user of such events. This was in an effort to prevent smartphones from becoming inconveniences hampering social interaction. The paper was a collaboration between the labs of Professors Sung-Ju Lee, Dongman Lee, and Juho Kim. Bumsoo Kang presented a mobile app that reads books to babies in their parent’s voice, using the small bits of unused time during a working day. This paper was a collaboration between the labs of Professors Junehwa Song, Sung-Ju Lee, and an IBM lab in the US. Eliph: Effective Visualization of Code History for Peer Assessment in Programming Education Jungkook Park, Yeong Hoon Park, Suin Kim, and Alice Oh “Don’t Bother Me. I’m Socializing！”: A Breakpoint-Based Smartphone Notification System Chunjong Park, Junsung Lim, Juho Kim, Sung-Ju Lee, and Dongman Lee Zaturi: We Put Together the 25th Hour for You. Create a Book for Your Baby Bumsoo Kang, Chulhong Min, Wonjung Kim, Inseok Hwang, Chunjong Park, Seungchul Lee, Sung Ju Lee, and Junehwa Song...Read more
Crowdsourcing based global indoor localization sys..
School of Computing Intelligent Service Lab (Prof. Dong-Soo Han) announced that they have developed a system for providing global indoor localization using Wi-Fi signals. The technology uses numerous smartphones to collect fingerprints of location data and label them automatically, greatly reducing the cost of constructing an indoor localization system while maintaining high accuracy. The method can be used in any building in the world, provided the floor plan is available, and there are Wi-Fi fingerprints to collect. To accurately collect and label the location information of collected fingerprints, the research team analyzed indoor space utilization. This led to a technology that classified indoor space in to places used for stationary tasks (resting spaces), and spaces used to reach said places (transient spaces), and separate algorithms to optimally and automatically collect location labelling data. A few years ago, the team has also implemented a means of automatically labelling resting space locations from collected signals in various contexts such as homes, shops, and offices via the users’ address information. The latest one allows for the automatic labelling of transient spaces’ locations such as hallways, lobbies, and stairs using unsupervised learning, also without any additional location information. Testing in KAIST’s N5 building and the 7th floor of N1 building proved the technology is capable of 3 to 4 meter accuracy given enough training data. The accuracy is comparable to technology using manually labeled location information. Google, MS, and other multinational corporations collected tens of thousands of floor plans for their indoor localization projects. Indoor signal map collection was also attempted but proved more difficult. As a result, existing indoor localization services were often plagued by inaccuracies. In Korea, COEX, Lotte World Tower, and other landmarks provide comparatively accurate indoor localization, but most buildings suffer from the lack of signal maps, preventing indoor localization services. Professor Dong-Soo Han claims that “This technology allows easy deployment of highly accurate indoor localization system in any building in the world. In the near future, most indoor spaces will provide localization services, just like outdoor spaces.” He further added that although smartphone collected fingerprints were left unutilized and discarded to date, the development of an application for the data will create a new field of wireless LAN big data fingerprinting. This new indoor navigation technology is likely to be valuable to Google, Apple, or other global firms providing indoor localization information for the whole world. Nonetheless the technology will also be valuable for Korean localization service firms for domestic localization services. Prof. Han added that “the new global indoor localization system deployment technology will be added to KAILOS, KAIST’s indoor localization system.” KAILOS was released in 2014 as KAIST’s open platform for indoor localization service, allowing anyone in the world to add floor plans to KAILOS, and add the building’s signal fingerprint data to help create a universal indoor localization service. As localization accuracy improves in indoor environs, despite the absence of GPS signals, applications such as location based SNS, location based IoT, and location based O2O are expected to take off, leading to various improvements in convenience and safety. Integrated indoor-outdoor navigation service is also visible on the horizon, fusing vehicular navigation technology with indoor navigation. [그림] 무선랜 핑거프린트 기반 스마트폰 실내 위치인식 [그림] 불특정 다수의 스마트폰을 통해서 수집된 핑거프린트의 수집 위치를 자동으로 라벨링하는 자율학습 기법 [그림] KAIST Indoor Locating System (KAILOS) 응용 서비스 및 관련 기술...Read more
HCI＠KAIST Research Society
The first seminar by HCI＠KAIST Research Society was held last Thursday (October 13th). HCI＠KAIST Research Society was organized by the School of Computing Future Planning Committee with the goal of providing a platform for cooperation between HCI labs in KAIST, and facilitate HCI education and research. Currently, 11 labs in KAIST are participating in the program. The society will be holding biweekly seminars, open workshops, and open house, and is operated with the help of Golfzon and the School of Computing. The first seminar started off with previews of two papers to be published in the UIST 2016 conference, and the second seminar is to be presented by guest speaker Professor Krzysztof Gajos from Harvard University....Read more
Professor Dong Soo Han’s laboratory in KAIST School of Computing developed an on-campus indoor/outdoor navigation system called, ‘Campus Atlas’. The system provides a direction to the destination by simply getting a visitor’s name or the room number of the building. For more information, please refer to the news article in Korean: http://www.dt.co.kr/contents.html?article_no=2015090302109976731002...Read more
IEEE ／ ACM International Conference on Automated S..
A paper published from Software Testing and Verification Group (SWTV; Professor Moonzoo Kim’s Laboratory) has been accepted to IEEE/ACM International Conference on Automated Software Engineering (ASE), one of the best conferences in computer science. Congratulations for the approval！ S. Hong, B. Lee, T. Kwak, Y. Jeon, B. Ko, Y. Kim, and M. Kim, Mutation-based Fault Localization for Real-world Multilingual Programs, IEEE/ACM International Conference on Automated Software Engineering (ASE), Nov 9-13, 2015 (acceptance rate: 21％)...Read more
Professor Sung-Ju Lee has been appointed as a Tech..
Sung-Ju Lee, the professor of KAIST School of Computing, has been appointed as a Technical Program Chair of the IEEE International Conference on Computer Communications (IEEE INFOCOM 2016). Started in 1992, INFOCOM is a prestigious international conference that covers various networking topics such as the Internet, wireless networking, mobility, datacenters, and others. Professor Lee is appointed as a TPC chair of INFOCOM for his contribution to the networking communications research; he is the first Korean to chair the TPC of the conference. He will select 650 technical program committee members who will review more than 1,600 paper submissions. Professor Lee is a leading researcher in wireless mobile networking systems. He is a Fellow of IEEE, and was the General Chair of ACM MobiCom 2014 (International Conference on Mobile Computing and Networking). He also serves on the editorial board of IEEE TMC (Transactions on Mobile Computing) and IEEE Internet of Things Journal. The 34th IEEE International Conference on Computer Communications will be held in April 2016 in San Francisco, California, USA....Read more
Identifying Digital Image Forgery Becomes Easy
The following news reports are about the national first image forensic tool developed in Professor Heung-Kyu Lee’s Laboratory, which is on a web service for testing at 'http://forensic.kaist.ac.kr'. Don’t Even Think About Faking a Picture with Photoshop！ – Donga Science 2015-06-12 The Research Team of Professor Heung-Kyu Lee in KAIST Developed ‘Digital Image Forgery Identification Technology’ In 2008, Iran announced that they launched ‘Shahab-3,’ a medium-range ballistic missile, and gave away the picture of launching four missiles for the proof. However, after revealing the picture, there was a rumor that the picture is a fake. Iran government made no comment about the rumor. Recently, a national research team developed an image forgery detector and verified the image. As a result, the detector found out three suspicious areas on the image, including smoke trails from three missiles. The research team of the professor Heung-Kyu Lee in KAIST developed an image forgery detection tool and created a webpage (forensic.kaist.ac.kr) for testing the tool. For example, if a picture of banana has modified by coloring light green on the top of the banana to make it fresh, the tool notifies the user by highlighting the modified area. Another example is that rafting people on a river; the tool even finds out that the picture is fake, a combined picture of a river and a rafting people. Professor Lee’s Team observed the statistical changes on the picture’s small dots (pixels) when modifying pictures. Using those changes, they developed the technology to find out the image forgery, such as copy-and-paste or retouches. It only takes a few seconds to find out. The research team commented that it would be helpful on research ethics or medical problems by applying the technology to pictures on academic papers, or medical videos. Professor Lee said, “The research on an image forgery detection is important, but there is a lack of research on it,” and he added, “We are planning to research on verifying various images successfully from the testing period.” Daejeon = Reporter Seung Min Jeon of Donga Science, enhanced＠donga.com "Identifying a Picture from Photoshop"… On a KAIST Research Team’s Website – Chosun Ilbo 2015-06-11 By Gun Hyung Park As many people generally use digital pictures, it gets easy to modify pictures using photo editors, such as Photoshop. Modifying pictures can be critical if the picture is used for an evidence on a criminal investigation. A national research team developed an image forgery detection tool and opened to the public. Heung-Kyu Lee, a professor of KAIST School of Computing, said, “We opened a web service detects an image forgery from a digital picture, which is not noticeable to the human eye.” Lee said, “An image forgery technology has been on a research worldwide for more than ten years, but there was an issue on accuracy,” and said, “This technology can identify the forgery with a success rate of 90~95％.” The service is available on the website (forensic.kaist.ac.kr) for anyone, for free. The research team of Professor Lee developed a software application by using three image analyzing techniques introduced in the world. The basic technology is ‘Digital Multimedia Pixel Analysis’ technique. When modifying a picture, the digital image’s small dots (pixel; a smallest element in an image) rapidly cut off or smash. If there is such area, then the image is a fake. The tool also uses the technique detects a pattern generated by Photoshop by analyzing ‘compression’ and ‘restore,’ called, ‘format-based detection’ technique, and a unique pattern generated from each camera, called, a ‘camera-based detection.’ Using this tool, the research team demonstrated the picture of launching ‘Shahab-3’, a medium-range ballistic missile announced by Iran government, is a forgery. At that time, Iran government modified a different picture and announced it to hide the failure to launch the missile. However, the tool detects the alteration successfully. Professor Lee said, “When a user uploads a picture, the tool analyzes and highlights the suspicious area of the image with three analysis techniques in about a minute,” and said, “We believe that we can increase the accuracy by opening this technique to the public.”...Read more
The proposal, ˝(SW Star Lab) Nearest Query Softwar..
The proposal from Scalable Graphics/Geometric Algorithm Lab. (Professor Sungeui Yoon), with the name of, “(SW Star Lab) Nearest Query Software Development for Mass Image Search and Prototype Rendering,” has successfully accepted. The proposal is about developing and extending “Proximity Computing” technology into various practical fields and opening the related software applications into public. The project will be supported up to 8 years with a fund of 0.3 billion KRW (＄0.27 million USD) per year. Also, they will cooperate with Professor Otfried Cheong’s team to develop a strong technology on theory. Please refer to the attached document for more information about SW Star Lab. Government Plans to Raise National SW Technology up to 80％ of the United States 2015.04.12 / PM 02:13 To make a competitive global software company, government enhanced supporting research and development (R&D); government made an objective to improve the software technology of Korea from 73％ up to 80％ of the United States. In addition, government plans to increase the number of global open-source software applications from 2 to 5, and global professional software companies from 20 to 50. On May 12th, MSIP (the Ministry of Science, ICT and Future Planning) prepared for ‘K-ICT SW Global Leadership Strategy’ to create software-driven society and made sure to support for creating a global software company. The strategy is one of the ‘three-year plan on economy,’ to transform the SW R&D project into focusing on raising national software industry to lead the international software markets. ▲ MSIP’s K-ICT SW global leadership strategy K-ICT SW Global Leadership Strategy is classified into three areas: ▲ the main source area ▲ application development area ▲ SW R&D creation of outcome. In the main source area, they select eight main-source areas on software technology, and nominate some graduate school laboratories into ‘SW StarLab’ and support up to 8 years. The eight main-source areas are operating systems, machine learning, intelligent software, database management systems, and others. They designated 10 Star Labs in this year and planning to increase the number up to 25. In an application development area, they support SW R&D project through stages by changing the project into a free competition under the policy that the proposer and performer must be the same. SW R&D project has simplified the applying procedures to help creative and challengeable startups, who have won from contest or the creative economy town, to commercialize and launch new products quickly. They plan to shorten the processing period from 4.5 months ∼ a year to 2.5 months. For developing companies, government is planning to introduce the MOS (Market Oriented SW) project in this year, using the market-selecting and incubating capability of investment companies, including global venture capitals. The GCS (Global Creative SW) project, which is for globalizing companies, will change the process to support R&D and overseas expansions within one-stop. They will announce in April after changing the system from government-leading project to a free competition. To accelerate taking the outcome of the SW R&D project, they reorganize the overall system of the project, such as tasks, evaluations, and maintenance (including quality assurance). They also plan to avoid external performance indicators such as the number of patents and support qualitative indicators, such as the capability of software quality management, the practical use open source software. Also, they apply the open-evaluation to professionalize the evaluation and plan to support improving the capability of software quality management. Yanghee Choi, the Minister of Science, ICT and Future Planning said, “This strategy is for the globalization of the national software industries by transforming the SW R&D project from deployment-oriented project into the achievement-oriented project. Translated the news report from: ZDNet Korea...Read more
ACM Interactions： Day in the Lab： “KAIST’s Human-C..
Interactions, a bi-monthly magazine published by the Association for Computing Machinery (ACM), the largest educational and scientific computing society in the world, features an article that introduces the Human-Computer Interaction (HCI) Lab at KAIST in its latest issue of March and April 2015 (http://interactions.acm.org/archive/view/march-april-2015/human-computer-interaction-lab-kaist). The HCI Lab (http://hcil.kaist.ac.kr/) is run by Professor Geehyuk Lee of the Computer Science Department at KAIST. Started in 2002, the lab conducts various research projects to improve the design and operation of physical user interfaces and develop new interaction techniques for new types of computers. For the article, please go to the link below: ACM Interactions, March and April 2015 Day in the Lab: Human-Computer Interaction Lab ＠ KAIST http://interactions.acm.org/archive/view/march-april-2015/human-computer-interaction-lab-kaist...Read more
Research on MapReduce Triangle Enumeration
[Prof. U Kang] The triangle enumeration problem is regarded as one of the fundamental graph mining problems. Its various applications include measuring content quality in social networks and finding spam pages on the Web. With massive input graphs, issues related to the performance of the network and to system failure may arise. To address the issues, this paper describes a new multi-round MapReduce randomized algorithm for enumerating all triangles. The experimental evaluation shows the scalability of the proposed approach – that it can significantly increase the size of data sets that can be processed. [Acknowledgement] · This work was supported by the IT R&D program of MSIP/IITP. [10044970, Development of Core Technology for Human-like Self-taught Learning based on Symbolic Approach]. [Publication] · This was presented at ACM International Conference on Information Knowledge Management (CIKM 2014), which is the most prestigious conference in the field of data mining. [Reference] · Ha-Myung Park, Francesco Silvestri, U Kang, Rasmus Pagh (2014), "MapReduce Triangle Enumeration With Guarentees," ACM International Conference on Information and Knowledge Management (CIKM), 2014...Read more
Artificial Intelligence and Machine Learning
[Prof. Kee-Eung Kim] The ultimate goal of artificial intelligence (AI), which is in essence building intelligent systems, requires computational and mathematical frameworks for intelligent behaviors. At the core of these frameworks lies the principle of rationality, and the decision theory provides a classical but effective tool for building intelligent systems as well as understanding the behavior of humans and animals. My research group at KAIST has been devoted to designing and developing decision-theoretic representations and algorithms for AI. Research Results My research group is working on representations and algorithms for decision theoretic planning problems, including large scale Markov decision processes (MDPs) and partially observable MDPs (POMDPs). Decision theory is one of the most important approaches to understanding and implementing the rational and intelligent behavior. 1. MDPs and POMDPs The classical MDP/POMDP representation has been a useful tool for modeling intelligent behaviors for decades. However, we often encounter the need to extend the standard representation to effectively capture real-world problems. For example, how can we naturally specify the constraints on the properties of desired solutions, or handle the uncertainty in the parameters of the model? As we extend the standard model, how can we address the computational challenges in designing efficient algorithms? We have addressed some of these theoretical issues and presented at top-tier AI conferences. 2. Machine learning of behavioral data The standard way of machine learning for the intelligent behavior is the reinforcement learning (RL). However, the standard setting in RL algorithms assumes prescribed reward functions, which is not an easy task to specify them in practice. Inferring the reward function from the behavior data is referred to as the inverse reinforcement learning (IRL), and its significance has emerged from the connection among RL and other disciplines such as neurophysiology, behavioral neuroscience, and economics. IRL is an important problem for understanding human and animal behaviors, and we have presented our algorithms at a top-tier machine learning conference and journal. 3. Applications Besides theoretical research on representations and algorithms, our group also worked on applications to demonstrate the usefulness of the decision-theoretic AI approach. Our work on applications include spoken dialogue systems and brain-computer interface systems. Awards 1. 2nd place in the POMDP track of the International Probabilistic Planning Competition (IPPC), 2011 2. Best poster award at the Pacific-Rim Conference on Artificial Intelligence (PRICAI), 2010 References Published papers 1. Jaedeug Choi and Kee-Eung Kim,“MAP Inference for Bayesian Inverse Reinforcement Learning”In: Proceedings of Neural Information Processing Systems (NIPS 2011). [Accepted] 2. Jaeyoung Park, Kee-Eung Kim, and Yoon-Kyu Song,“A POMDP-based Optimal Control of P300-based Brain-Computer Interfaces”In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) NECTAR Track. 2011. [8th Korean AAAI paper] 3. Dongho Kim, Jaesong Lee, Kee-Eung Kim, and Pascal Poupart,“Point-Based Value Iteration for Constrained POMDPs”In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). 2011. [5th Korean IJCAI paper] 4. Eunsoo Oh and Kee-Eung Kim,“A Geometric Traversal Algorithm for Reward-Uncertain MDPs”In: Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI). 2011. [1st Korean UAI paper] 5. Pascal Poupart, Kee-Eung Kim, and Dongho Kim,“Closing the Gap: Towards Provably Optimal POMDP Solutions”In: Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS). 2011. [1st Korean ICAPS paper] 6. Jaedeug Choi and Kee-Eung Kim,“Inverse Reinforcement Learning in Partially Observable Environments”Journal of Machine Learning Research (JMLR), 12. 2011. [2nd Korean JMLR paper] 7. Dongho Kim, Jin Hyung Kim, and Kee-Eung Kim,“Robust Performance Evaluation of POMDP-Based Dialogue Systems”IEEE Transactions on Audio, Speech, and Language Processing (TASLP), 19(4). 2011. 8. Youngwook Kim and Kee-Eung Kim,“Point-Based Bounded Policy Iteration for Decentralized POMDPs”In: Proceedings of Pacific-Rim Conference on Artificial Intelligence (PRICAI) / Lecture Notes in Computer Science (LNCS) 6230. 2010. [Best poster award] 9. Jaeyoung Park, Kee-Eung Kim, and Sungho Jo,“A POMDP Approach to P300-Based Brain-Computer Interfaces”In: Proceedings of the ACM International Conference on Intelligent User Interfaces (IUI). 2010. 10. U.S. Patent Application 20110152710,“Adaptive Brain-Computer Interface Device”...Read more
Developing a hyperspectral 3D imaging system and s..
[Prof. Min H. Kim] 3D imaging techniques have been broadly used in manufacturing, entertainment and military industries. However, current 3D imaging systems have been limited to capturing and representing only trichromatic 3D objects. This research project extends the spectral dimension of 3D imaging techniques beyond the trichromatic spectrum. It is the first approach to build a complete 3D scanning system that measures the hyperspectral reflectance of solid objects. This research project includes the design and building of a 3D imaging system, the development of 3D imaging algorithms, and several 3D software applications to visualize such hyperspectral 3D image data. The research outcome of this project could be broadly adapted to physically meaningful measurements of hyperspectral material appearance of 3D solid objects in natural science and bio-medical engineering. Schematic overview of the 3D imaging spectroscopy system (ACM Trans. on Graphics, 31(4), 38:1-11, SIGGRAPH 2012) Research Funding ㆍ This work was supported by the National Research Foundation (NRF) of Korea, Samsung Electronics and Microsoft Research Asia additionally. Research Results ㆍ This imaging system was introduced for the first time in ACM Transactions on Graphics, 2012, the top journal in computer graphics. The associated visualization software application was published in ACM Journal on Computing and Cultural Heritage, 2014 such that this work was received a best paper award in 2012 at the International Symposium on Virtual Reality, Archaeology and Cultural Heritage (VAST 2012). References ㆍ M. H. Kim, T. A. Harvey ,D. S. Kittle, H. Rushmeier, J. Dorsey, R. O. Prum, D. J. Brady (2012), "3D Imaging Spectroscopy for Measuring Hyperspectral Patterns on Solid Objects," ACM Transactions on Graphics (Proc. SIGGRAPH 2012), 31(4), July 2012, pp. 38:1-11 (IF=3.361) ㆍ M. H. Kim, H. Rushmeier, J. ffrench, I. Passeri, D. Tidmarsh (2014), "Hyper3D: 3D Graphics Software for Examining Cultural Artifacts," ACM Journal on Computing and Cultural Heritage, 7(3), February, pp. 1:1-19...Read more
Analysis on Media Characteristics of Twitter
[Prof. Sue Bok Moon] Via quantitative analysis with the not-sampled, but complete data, we show media-like characteristics of Twitter. Online communication has emerged as a new form of media, and our work is one of the first to demonstrate a quantitative approach for new media research. Research Results Online Social Network (OSN) services are creating a sea of new products and services based on the social networks. OSN services, such as Facebook and Twitter, threaten the established ones, such as Microsoft, Google and Apple. Twitter, a microblogging service, stands out from other OSN services in that its relations are directional and most user profiles and tweets are public. For three months from June 2009, we collected profiles of all Twitter users. Our analysis shows that Twitter has characteristics of not only a social network but also of media. The reciprocity typically over 80％ in social networks is low (less than 50％). Most tweets are of news nature. Retweets expand readership by 100 or more easily. ※Excellency and Expected effects No further explanation is necessary for the influential power of Twitter, as demonstrated in the recent Seoul mayor election. However, in 2009 when we started our research on Twitter, domestic awareness was low and nobody could have imagined the explosive power in the MENA (Middle East North Africa) situations this spring. Our paper, “What is Twitter, a Social Network or a News Media?” published in the World-Wide Web (WWW) conference on April 2010, investigates social phenomena via Twitter and provides statistical approaches on the complete data of Twitter. Our data crawling and analysis methodologies have become a de-facto standard in follow-up research. The Library of Congress in US has decided to archive the entire Twitter data, thus acknowledging the historic significance of massive-scale communication records among hundreds of million users for the first time in human history. Twitter provides an epoch-making data that allows people to collect information and observe its diffusion in an unprecedentedly massive scale and is changing the face of research methodologies in computer science, sociology, politics, business administration, cognitive science and more. Our paper, published in the WWW conference in 2010, is cited more than 2000 times (via Google Scholar) as of July 2014 and we expect the number to increase even more in the coming years. This work has been covered by domestic and foreign press such as ChosunIlbo, HankookIlbo, MIT Technology Review Blog, ReadWriteWeb, the Observer, PC World, Mashable Op-Ed. Computer science graduate courses at Georgia Institute of Technology, UC Santa Barbara and Cornell have included our paper in their lecture material. Non-computer science departments, such as MIT Business School, Bowdoin College sociology department, and the University of California at San Diego Visual Arts Department have also included our work. From 2009 I have given more than 10 invited talks on this paper, including Boston Univ., Northwestern Univ., UC Santa Barbara, Microsoft Research Bangalore, Microsoft Research Redmond, Duke Univ., North Carolina State Univ. This work provides data collection and analysis methodologies for new media studies and falls to the category of fundamental science. It is hard to file for a patent or apply immediate productization from this work but this work reveals basic characteristics of new media, of which knowledge is imperative to designing derivative products or services. Our investigation of human society via online service provides a new direction for interdisciplinary research between computer science, humanities, and social sciences. KAIST established the Web Science and Technology division under the World-Class University program sponsored by the Ministry of Education, Science and Technology, for this kind of interdisciplinary research. In Korea with its world-best high-speed Internet infrastructure and less-than-1％ illiteracy and highly educated work-force, interdisciplinary research could be the guiding light to take our IT industry to the next level. We hope our social network of interdisciplinary collaborators initiated by this Twitter research continues to expand and become a catalyst for explosive growth in our academic excellence. Reference Published papers 1. Haewoon Kwak, Changhyun Lee, Hyunwoo Chun, Sue Moon,“What is Twitter, a Social Network or a News Media?” Proceedings of the World-Wide Web, April 2010, Raleigh, North Carolina.(Acceptance rate: 14％ , Citation: 313) Funding Sources 1. Collect, Analyze and Share for Future Internet : High-Precision Measurement and Analysis Research, 2008.3.1.∼2013.2.28., MKE...Read more
Scalable Big Graph Mining
[Prof. U Kang] Scalable big graph mining using distributed systems opens new opportunities for the discovery of interesting patterns and anomalies on very large graphs which could not be analyzed before. Article: Graphs are ubiquitous: computer networks, social networks, mobile call networks, biological networks, citation networks, protein regulation networks, and the World Wide Web, to name a few. Spurred by the lower cost of disk storage, the success of social networking sites (e.g. Facebook, Twitter, and Google＋) and Web 2.0 applications, and the high availability of data sources, graph data are being generated at an unparalleled rate. They are now measured in terabytes and heading toward petabytes, with more than billions of nodes and edges. Mining such big graphs helps us find patterns and anomalies which lead to many interesting applications including fraud detection, cyber security, social network analysis, etc. The research team at Prof. U Kang in Department of Computer Science is working on scalable big graph mining which includes two components: scalable algorithms and discoveries on real world graphs. Scalable Algorithms. Traditional graph algorithms assume the input graph fits in the memory or disks of a single machine. However, the recent growth of the sizes in graphs violates this assumption. Since single machine algorithms are not tractable for handling big graphs, the research team at Prof. U Kang is working on designing and developing scalable algorithms and distributed platforms for mining and managing big graphs. Prof. U Kang is the main author of the award-winning Pegasus graph mining software which includes various large scale graph mining algorithms including PageRank, Random Walk with Restart (RWR), diameter estimation, connected components, eigensolver, and tensor analysis. Discoveries on Real World Graphs. The developed scalable algorithms lead to the analysis of large real world graphs, and interesting discoveries of patterns and anomalies which could not be found before. One of the most interesting discoveries is the seven-degrees of separation in one of the largest publicly available Web graphs with ∼7 billion edges. The discovery suggests that the so-called ＇small world' phenomenon exists in the Web, and the distance between any two Web pages is much smaller than people's expectations. Another interesting discovery is the existence of suspicious adult advertisers in the Twitter who-follows-whom social network at 2009 with 3 billion edges. In the scatter plot of degree vs. triangles of Twitter accounts, some famous U.S. politicians have mildly connected followers, while adult advertisers have tightly connected followers, creating many triangles. The reason is that adult accounts are often from the same provider, and the accounts follow each other to boost their rankings, thereby creating many cliques containing triangles. Image caption: Anomaly detection in graph: the degree vs. triangles in the Twitter who-follows-whom social network at 2009. Some famous U.S. politicians have mildly connected followers, while adult advertisers have tightly connected followers, creating many triangles. The reason is that adult accounts are often from the same provider, and the accounts follow each other to boost their rankings, thereby creating many cliques containing triangles. [U KANG AND CHRISTOS FALOUTSOS, BIG GRAPH MINING: ALGORITHMS AND DISCOVERIES, SIGKDD EXPLORATION VOLUME 14 ISSUE 2, DECEMBER 2012....Read more
Smartphone-based Interaction Sensing to Innovate O..
[Prof. Junehwa Song] Advancing our smartphones as conversational interaction sensing platforms to promote social health in everyday life Article: A team of researchers in Dept. of Computer Science, KAIST are leading new mobile initiatives to build social context platforms and create life-immersive social services. The key inspiration is to advance our commodity mobile devices such as smartphones towards a face-to-face social gateway – to acquire the real-time social contexts and create proactive services naturally overlaid on our everyday face-to-face social lives. Why social? Because it is an integral basis which constitutes many of our daily activities, such as family life, team-oriented works, hanging out with friends, and so on. They believe that stretching out for diverse social contexts around the user will realize the foundation of future mobile systems which achieve holistic understanding on the user’s need and useful life-immersive services. The quest begins with a question, “What would be the primitive context in our face-to-face social interaction?” As the initial and natural step, the research team focused on conversation, which would be the most prevalent tool to communicate with people just in front of us. A number of new technical challenges arises to recognize delicate conversational contexts with commodity mobile devices. In 2013, they reached the first milestone, SocioPhone, a mobile face-to-face interaction platform with highlights meta-linguistic contexts in conversations. SocioPhone is described in a paper published in ACM MobiSys 20131 (International Conference on Mobile Systems, Applications, and Services) by a team of a KAIST graduate Youngki Lee, who is now an assistant professor of Information Systems, Singapore Management University (SMU), and 8 others. SocioPhone abstracts on-going conversations as a sequence of turns and pauses. SocioPhone provides applications with a set of intuitive APIs to monitor rich meta-linguistic context on the fly, without requiring computation-intensive semantic inference on conversation contents. At its core, the SocioPhone runtime monitors conversational turn-centric contexts in a highly-efficient and precise manner based on a new socially-leveraged collaborative sensing scheme. In addition to the paper publication, a live demonstration of SocioPhone won the Best Demonstration Award in ACM HotMobile 20132 (International Workshop on Mobile Computing Systems and Applications), which was conducted by a KAIST graduate student Chulhong Min and 14 others. Continuing the efforts, the research team is now creating compelling applications which are indispensable for a new platform to find its unique values. Notably, they proposed TalkBetter, a prominent initiative for everyday clinical care applications. The paper describing TalkBetter has won the Best Paper Award in ACM CSCW 20143 (International Conference on Computer Supported Cooperative Work and Social Computing), which was authored by an interdisciplinary team of a KAIST graduate Inseok Hwang who is now a research assistant professor of Center for Mobile SW Platform in KAIST, Prof. Dongsun Yim in Dept. of Communication Disorders, Ewha Womans University, and 5 others. They introduced a mobile in-situ intervention service to expedite everyday family-driven care for children with speech impediments. With close collaboration with the speech-language pathologists and the patients regularly taking speech-language care, TalkBetter has been designed and developed as an integrated therapeutic service which facilitates the parents to acquire clinically desirable conversation habits throughout natural conversations, not only depending on simple a-priori prescription as it has been done thus far. Today, many people observe growing concerns about the anti-social effects of smartphones, attempting to suppress the smartphone use in face-to-face social situations. These researches advocate an antithesis of such technophobic skepticisms. They are pursuing the pro-social potential of pervasive mobile devices around us, and realizing the first-of-its-kind mobile systems to enhance our everyday social life experience. These researches were supported by National Research Foundation funded by Ministry of Science, ICT, and Future Planning (MSIP) and IT R&D Program of MSIP/KEIT of the Korean Government. 1. Lee, Y., Min, C., Hwang, C., Lee, J., Hwang, I., Ju, Y., Yoo, C., Moon, M., Lee, U., Song, J. SocioPhone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion. ACM MobiSys 2013, Taipei, Taiwan, June 2013. 2. Min, C., Hwang, I., Lee, J., Hwang, C., Yoo, C., Moon, M., Park, T., Lee, C., Lee, H., Kim, Y., Ju, Y., Lee, Y., Lee, U., Song, J. Demo: Bringing In-situ Awareness to Mobile Systems: Everyday Interaction Monitoring and Its Applications. ACM HotMobile 2013 (Demo), Jekyll Island, GA, USA, February 2013. 3. Hwang, I., Yoo, C., Hwang, C., Yim, D., Lee, Y., Min, C., Kim, J., Song, J. TalkBetter: Family-driven Mobile Intervention Care for Children with Language Delay. ACM CSCW 2014, Baltimore, MD, USA, February 2014. Image caption: Real-time meta-linguistic monitoring and feedback by the smartphone for the on-going conversation between the mother and her son. [PHOTO COURTESY OF THE RESEARCHERS] Image caption: Face-to-face conversation situations and socially-leveraged collaborative sensing scheme for conversational turn monitoring [PHOTO COURTESY OF THE RESEARCHERS]...Read more
Internet of things and system software
[Prof. Dae Young Kim] The term Internet of Things was firstly introduced in 1999 by Kevin Ashton at the Auto-ID Labs, MIT, which is the primary research partner of GS1. GS1 is a global organization which provides various types of codes such as bar code, RFID code, QR code for thing identification, and also standardizing system infrastructure for global business and application. Among seven Auto-ID Labs (MIT, Cambridge, ETH Zurich, Keio, Fudan, Adelaide, KAIST) over the world, Auto-ID Lab, KAIST have studied in IoT field since 2002, with the RFID and wireless sensor network technology. And since 2005, we started to develop various IoT technologies that are specialized to GS1 standard. We are currently working on following projects; Oliot (GS1 based IoT Infrastructure Platform), SNAIL (6LoWPAN based IoT Connectivity Platform), SeaHaven (Visual Sensor Network Cloud Platform), IoT-App Ecosystem (Ecosystem for Mobile Versatile Applications), GPGPU HPC Cloud (Cloud Computing for HPC with GPGPU). [Research Results] The IoT is the vision that aims to give every day object virtual personality. The rationale behind this is to let them have global identification, computation and communication capabilities. That is, our everyday things become intelligent and are able to provide us with any information about themselves. As a result, vast opportunities to create entirely new dimension of services appear. In this regard, we have developed the following five technologies to realize the IoT vision. (1) SNAIL: We enabled communication among things over Internet to achieve 6LoWPAN IoT network. SNAIL (Sensor Network for an All-IP World) is a solution for IoT network, which is a tiny IPv6-based sensor networking platform including a complete architecture of a lightweight TCP/IP stack supporting IPv6 adaptation, ad-hoc routing, header compression, and bootstrapping as well as four important technologies, mobility, web enablement, time synchronization, and security. (2) Oliot: Oliot is aiming an international standard based IoT Infrastructure Platform, by extending the code system of GS1 and their standard architecture to support various IoT connectivity and protocols such as bar code, RFID, ZigBee, 6LoWPAN, etc. Oliot also aims a complete implementation of GS1/EPCglobal standard. (3) IoT-App Ecosystem: IoT-App Ecosystem is a new ecosystem for mobile software, which enables easier interaction between mobile application and various smart things. This is currently being implemented for Android and supports current Android development environment. (4) SeaHaven: SeaHaven is a portable and secure multi-tenant visual sensor networks cloud platform which covers visual sensor node operating systems, visual sensor streaming service, visual big data processing service, and user applications. The major goal of this project is to make the machine understand the context of the scene by leveraging visual sensors all over the world which are very beyond human’ visual sensory. (5) GPGPU HPC Cloud: This project is about Cloud computing for HPC with general purpose graphical processing unit (GPGPU). Using GPGPU on Cloud will reduce cost and power usage than using only CPUs. We implemented platform with OpenStack, KVM, and API forwarding technique. [Excellency and Expected effects] (1) SNAIL: We make an effort to support secure, dynamic, global, and easy access to everyday objects using IPv6 address. Our IoT platform SNAIL is evaluated as a promising IoT platform and new version SNAIL 2.0 will come out soon. (2) Oliot: The entire source code was opened to public and is designated to be utilized on various project such as EU IoT6 Smart Building Project, KAIST Dr. M Project, c-ITRC Food Safety System, Stanford Civil Engineering Project, Korea University Hospital Project, and Smart Consumer Electronics. The roadmap and vision of Oliot project is described in oliot.org. (3) IoT-App Ecosystem: With this work, mobile application developers can more easily implement applications which interacts with pervasive smart things. Also, it aids the developers to publish their business logic to customers. (4) SeaHaven: To make the machine understand the context of an event is a quite challenging job to handle. Variety and sparse distribution of sensors must be the most helping key in resolving this issue. SeaHaven provides a universal interface for sensors to cover variety and heterogeneity of sensor devices and a very scalable service architecture to easily scale out the system over the cloud infrastructure. (5) GPGPU HPC Cloud: To use GPGPU on Cloud, previous approach only supports one to one mapping virtual machine and GPGPU. With API forwarding technique and Kepler architecture GPGPU, our platform supports scalable use of GPUs. And with efficient GPU resource scheduling algorithms, our platform can maximize resource utilization while providing SLA for HPC users....Read more
Investigating Reliable Computing Systems in Nano-s..
[Prof. Soontae Kim] With technology scaling, feature sizes, and supply and sub-threshold voltages are decreasing for high performance, high transistor density, and low power consumption. At the same time, microprocessors and memory systems are integrating more transistors to extract more performance. Unfortunately, these trends make computing systems more susceptible to various errors. Transient errors occur when energetic neutrons coming from deep space and alpha particles from packaging materials hit transistors, which change the state of memory bits or the output of combinational logic temporarily. In addition, permanent errors due to process variations and wear-out in interconnect and transistors increase over time, which in turn decrease yield and lifetime of the computing systems. Therefore, it is essential to provide reliable computing on top of unreliable systems for the continued success of computing. We investigate low-cost processor architectures, memory systems and software to combat against those various errors in nano-scale era. [Research Highlight] Access-time Variation Insensitive Level-1 Caches  Ever-scaling process technology increases variations in transistors. The process variations cause large fluctuations in the access times of SRAM cells. Caches made of those SRAM cells cannot be accessed within the target clock cycle time, which reduces yield of processors. To combat these access time failures in caches, many schemes have been proposed, which are, however, limited in their coverage and do not scale well at high failure rates. We proposed a new level-1 cache architecture (AVICA) employing asymmetric pipelining and pseudo multi-banking. Asymmetric pipelining eliminates all access time failures in L1 caches. Pseudo multi-banking minimizes the performance impact of asymmetric pipelining. For further performance improvement, architectural techniques were proposed. [Reference] 1. Seokin Hong and Soontae Kim. AVICA: An Access-time Variation Insensitive L1 Cache Architecture. Design Automation and Test in Europe Conference (DATE’13), March 18∼22, 2013, Grenoble, France (Best Paper Award)....Read more
OncoSearch： A web tool that searches biomedical li..
[Prof. Jong Cheol Park] OncoSearch (http://oncosearch.biopathway.org) is a web tool that allows the user to query into biomedical literature for information on cancer-related genes and shows the results for further insights into oncogenesis, with an aim to catalyze and accelerate the ongoing cancer research. [Article] Automatic identification of gene-cancer relations from a very large volume of biomedical text is an important task for cancer research since changes in genes are known to be the main cause of oncogenesis and a huge amount of information on such genes is archived in biomedical literature databases. To identify such relations, it is essential to understand, as much as possible, how a gene affects a cancer and to distinguish oncogenes (genes that cause cancers), tumor suppressor genes (genes that protect cells from cancers), and biomarkers (genes that indicate normal or cancerous states) since this will speed up the development of treatment and diagnosis methods for cancer. Although genes may sometimes be explicitly claimed as oncogenes or tumor suppressor genes in the biomedical text, it is more often the case that information on gene-cancer relations is conveyed only implicitly with detailed descriptions about gene and cancer properties. Consider the example of the sentence below. WWOX overexpression induced apoptosis and suppressed prostate cancer growth in vitro and in vivo [PMID:17704139]. While the gene WWOX is a well-known tumor suppressor, the sentence above does not contain an explicit reference to the gene as such. Instead, the sentence gives information that helps to classify the gene WWOX as a tumor suppressor of prostate cancer through the following inference: 1) WWOX expression level is increased, 2) prostate cancer regresses when WWOX expression increases, and 3) there is causality between the change in WWOX and the change in prostate cancer. By combining the three pieces of information above, one may classify the gene WWOX as a tumor suppressor gene. Although a single sentence with such implicit information may not provide enough evidence to confirm a particular gene's class, collecting a large amount of such information in the literature would certainly help to substantiate such a conclusion. Prof. Jong C. Park’s research team at KAIST developed OncoSearch, a web tool that allows the user to query into the biomedical literature for free-text information on cancer-related genes and provides the results for further insights into oncogenesis, or the process by which normal cells are transformed into cancer cells. In particular, OncoSearch can classify genes into either oncogenes, tumor suppressor genes, or biomarkers by taking into account implicit information as well as explicit information on their roles. The tool characterizes gene-cancer relations described in biomedical text with 1) how a gene changes, 2) how a cancer changes, and 3) the causality between the gene and the cancer, and the tool infers the respective roles of genes in cancers. Through this classification, the research team showed that the tool can correctly pick out oncogenes and tumor suppressor genes already registered as such in biology databases. The research team also showed that only small portions, or 6.87％ and 3.76％, respectively, of the oncogenes and tumor suppressor genes in one of the de facto standard gene databases, or UniProtKB, are registered in the list of oncogenes and tumor suppressor genes published by Vogelstein and colleagues (Science, 2013). This indicates either 1) that the process of identifying new oncogenes or tumor suppressor genes is still at an early stage or 2) that the exact definitions of oncogene and tumor suppressor gene are highly dependent upon each biology database. OncoSearch is, thus, expected to catalyze much further research in oncology since the tool can collect and infer information about novel oncogenes, tumor suppressor genes, and biomarkers from the rapidly growing body of the literature that does not necessarily contain explicit expressions such as oncogene and tumor suppressor gene....Read more
High-physicality touch interfaces
[Prof. Geehyuk Lee] Touch interfaces are now a de facto standard for information appliances. They enabled more direct and natural interaction than traditional computer interfaces, but are still in their early stage as the types of operations are quite limited compared with diverse surface operations that we perform in the real world. The limitations of the current touch interfaces stem mainly from their inability to discriminate touches of different degrees, for example, hover, light touch and heavy touch. We are interested in new possibilities that may be enabled when touch surfaces become more physically sensitive, for instance, when they can sense the approach or the pressure of the fingers as well as their touch. We are conducting a series of interaction design studies with high-fidelity prototyping, and are publishing some of early results in leading HCI conferences. Research Results Touch with Hover We developed a world-best class optical hover tracking touchpad technology and are exploring the potential of using it. Using this technology, we can provide a touch-screen-like interaction in the TV environment. For instance, the shadow of the user's fingers touches the screen, presses a button, and flicks a cover-flow-like list, while the fingers stay and move on a touchpad. In order to explore this concept, we developed a hover-tracking optical touchpad, and designed a TV application to demonstrate possible new interaction techniques. Through a prototyping study, we could correct some of our false expectations, and verify its potential as a viable option for a TV remote interface. (left) RemoteTouch concept and device, (right) Hover-tracking long touchpad Touch with Force The same finger movement on an object may be associated with different intentions depending on its normal and tangential forces. For instance, the same finger movement can be intended to turn a single page or to turn multiple pages, or to slide on a page, but a touch screen cannot differentiate these gestures. We solved this problem with a touch screen that can sense not only touch positions but also touch forces. We implemented a prototype device that can sense the normal and the tangential component of the forces on the screen, designed Force Gestures, which differ in terms of both touch movements and force patterns, and conducted an experiment to verify the feasibility of this approach. (left) example force gestures, (right) example multi-point tangential force interaction Excellency and Expected effects A complete report of our research on the RemoteTouch concept was presented at ACM CHI 2011 [C1]. The CHI paper soon attracted the attention of technology reporters and a news article about the paper appeared in DiscoveryNews [W1] and MSNBC.com [W2]. The optical hover-tracking technology was also implemented into form factors of a standard laptop touchpad and long shaped palm rest-length touchpad, and presented at ACM UIST 2011 [C2] and ACM CHI 2013 [C3], as a demo and a poster, respectively. The long touchpad was also introduced by American technology blogs, NewScientist Blog [W3] and Gizmodo [W4]. Regarding Force-sensing touch technology, a complete report is presented at ACM UIST 2011 [C4] and ACM CHI 2013 [C5], which is one of the most competitive venues for UI researchers. Published at ACM CHI and ACM UIST, the results of the current research were verified to be original and academically important. The research is also expected to have an impact on ICT industry since their main application targets are smart phones and smart TVs. After the introduction of iPhone, mobile phone manufacturers realized the importance of UI technologies and are experimenting with many new UI technologies to impress the market. High physicality touch screen or touchpad as demonstrated by our research results is certainly one of them. We were invited to present our research on touch interfaces by major companies such as LG and Samsung this year. We could also attract research funds from an industry source [F1] and a government source [F2] for the current research. The aforementioned news articles [W1, W2, W3] also reflect the public interests in the current research. References C1. Sangwon Choi, Jaehyun Han, Geehyuk Lee, Narae Lee, and Woohun Lee, RemoteTouch: Touch-Screen-like Interaction in the TV Viewing Environment, CHI 2011 (paper). C2. Sangwon Choi, Jaehyun Han, Sunjun Kim, Seongkook Heo, and Geehyuk Lee, ThickPad: A Hover-Tracking Touchpad for a Laptop, ACM UIST 2011 (demo). C3. Jiseong Gu, Seongkook Heo, Jaehyun Han, Sunjun Kim, and Geehyuk Lee, LongPad: a touchpad using the entire area below the keyboard of a laptop computer, ACM CHI 2013 (paper) C4. Seongkook Heo and Geehyuk Lee, Force gestures: augmenting touch screen gestures with normal and tangential forces, ACM UIST 2011 (paper). C5. Seongkook Heo and Geehyuk Lee, Indirect shear force estimation for multi-point shear force operations, ACM CHI 2013 (paper) W1. http://news.discovery.com/tech/shadow-remote- touchscreen-110519.html W2. http://www.msnbc.msn.com/id/43095028 W3. http://www.newscientist.com/blogs/onepercent/2013/01/trackpad-ignores-accidental-to.html?cmpid=RSS％7CNSNS％7C2012-GLOBAL％7Conline-news W4. http://gizmodo.com/5982160/intelligent-keyboard-wide-touchpad-is-smart-enough-to-ignore-your-palms Funding Sources 1. Implementation of USN Sensor Platform and Network Systems, Funded by National Research Laboratory (NRL) Program of NRF, 2007-current 2. u-Agriculture, Funded by ITRC (Information Technology Research Center) Program of MKE, 2007-current...Read more