Category: ICC

Weihua Zhou to Present Friday Seminar Talk

Weihua Zhou

The College of Computing (CC) will present a Friday Seminar Talk on November 15, at 3:00 p.m. in Rekhi 214. Featured this week is Weihua Zhou, assistant professor of Health Informatics and member of the ICC’s Center for Data Sciences. He will present his research titled: “Information retrieval and knowledge discovery from cardiovascular images to improve the treatment of heart failure.” Refreshments will be served.

Abstract: More than 5 million Americans live with heart failure, and the annual new incidence is about 670,000. Once diagnosed, around 50% of patients with heart failure will die within 5 years. Cardiac resynchronization therapy (CRT) is a standard treatment for heart failure. However, based on the current guidelines, 30-40% of patients who have CRT do not benefit from CRT. One of Zhou’s research projects is to improve CRT favorable response by information retrieval and knowledge discovery from clinical records and cardiovascular images. By applying statistical analysis, machine learning, and computer vision to his unique CRT patient database, Zhou has made a number of innovations to select appropriate patients and navigate the real-time surgery. His CRT software toolkit is being validated by 17 hospitals in a large prospective clinical trial.

Keith Vertanen Is PI on $225K NSF Grant, “Improving Mobile Device Input for Users Who are Blind or Low Vision”

Keith Virtanen
Keith Vertanen

Keith Vertanen (CS/ICC-HCC) is the principal investigator on a three-year project that has received a $225,663 research and development grant from the National Science Foundation. The project is entitled, “CHS: Small: Collaborative Research: Improving Mobile Device Input for Users Who are Blind or Low Vision.”

Abstract: Smartphones are an essential part of our everyday lives. But for people with visual impairments, basic tasks like composing text messages or browsing the web can be prohibitively slow and difficult. The goal of this project is to develop accessible text entry methods that will enable people with visual impairments to enter text at rates comparable to sighted people. This project will design new algorithms and feedback methods for today’s standard text entry approaches of tapping on individual keys, gesturing across keys, or dictating via speech. The project aims to:  1) help users avoid errors by enabling more accurate input via audio and tactile feedback, 2) help users find errors by providing audio and visual annotation of uncertain portions of the text, and 3) help users correct errors by combining the probabilistic information from the original input, the correction, and approximate information about an error’s location. Improving text entry methods for people who are blind or have low vision will enable them to use their mobile devices more effectively for work and leisure. Thus, this project represents an important step to achieving equity for people with visual impairments.

This project will contribute novel interface designs to the accessibility and human-computer interaction literature. It will advance the state-of-the-art in mobile device accessibility by: 1) studying text entry accessibility for low vision in addition to blind people, 2) studying and developing accessible gesture typing input methods, and 3) studying and developing accessible speech input methods.  This project will produce design guidelines, feedback methods, input techniques, recognition algorithms, user study results, and software prototypes that will guide improvements to research and commercial input systems for users who are blind or low-vision. Further, the project’s work on the error correction and revision process will improve the usability and performance of touchscreen and speech input methods for everyone.

Kuilin Zhang is PI on $567K Federal Railroad Administration Project

Khuilin Zhang

Kuilin Zhang (CEE/MTTI), a member of the ICC Center for Cyber-Physical Systems (CPS), is the primary investigator on a project that has received a $567,230 contract with the Federal Railroad Administration. This project is entitled, “Developing Safe and Efficient Driving and Routing Strategies at Railroad Grade Crossings Based on Highway-Railway Connectivity.” Pasi Lautala (CEE) is the Co-PI on this potential two-year project.

Alex Sergeyev Wins ASEE Best Paper Award

Alex Sergeyev

College of Computing Professor Alex Sergeyev (DataS) presented his research article, “University, Community College and Industry Partnership: Revamping Robotics Education to Meet 21st Century Workforce Needs – NSF Sponsored Project Final Report,” at the 2019 American Society of Engineering Education (ASEE) annual conference, receiving the Best Paper Award in the Engineering Technology Division.

The conference took place June 16-19 in Tampa, Florida.

Co-authors of the publication are S. Kuhl, N. Alaraje, M. Kinney, M. HIghum, and P. Mehandiratta. The paper will be published in the fall issue of the prestigious Journal of Engineering Technology (JET).

ACIA Networking Mixer is Tues., Sept. 24, 4-6 pm

The Alliance for Computing, Information, and Automation (ACIA) and Michigan Tech Career Services invite students to a casual networking mixer with industry employment recruiters on Tuesday, September 24, 2019, from 4:00 to 6:00 p.m., in the Rozsa Center lobby. The event is free and appetizers and refreshments will be served.
Students in the following majors are encouraged to attend: Computer Network and System Administration (CNSA), Computer Engineering, Computer Science, Cybersecurity, Data Sciences, Electrical Engineering, Electrical Engineering Technology (EET), and Software Engineering.
Recruiters interested in hiring Michigan Tech students and graduates in the above majors will be in attendance.

The Alliance for Computing, Information, and Automation (ACIA) at Michigan Technological University is a collaborative effort between the Department of Electrical and Computer Engineering and the College of Computing. The mission of the ACIA is to provide faculty and students the opportunity to work across organizational boundaries to create an environment that is a reflection of contemporary technological innovation. The research arm of the ACIA is the Institute of Computing and Cybersystems (ICC).

Download the event flyer

Recruiters interested in hiring Michigan Tech students and graduates in the above majors will be in attendance. Invited companies include the following:

3M
Amcor (fka Bemis)
ArcelorMittal
Black & Veatch
Caterpillar
CCI Iron Mountain
Continental
Cummins
Denso
Dow
DTE Energy
Fiat Chrysler Automobiles (FCA)
Ford Motor Company
Georgia-Pacific
Gerdau
Greenheck
Kimberly-Clark
Kohler
Leidos
Los Alamos National Lab (LANL)
Marathon Petroleum
Mercury Marine
Michigan Scientific Corporation
Milwaukee Tool
National Air and Space Intelligence Center
Nexteer Automotive
Nucor
Oshkosh Corporation
Palantir
Plexus
Schneider
Superior Technologies
Systems Control

Zhen Liu Co-author of Publication in Cold Regions Science and Technology

Zhen Liu, associate professor of civil and environmental engineering and member of the ICC’s Center for Cyber-Physical Systems (CPS), is co-author of the article, “A multivariate freezing-thawing depth prediction model for spring load restriction,” which was published August 6, 2019, in the journal Cold Regions Science and Technology, which is published by Elsevier. Co-authors of the article are Ting Bio and John Bland.

Abstract: Road damages induced by heavily loaded truck traffic during the spring thaw are a major road distress in cold regions. To minimize these damages, Spring Load Restriction (SLR) is widely applied in the U.S., Canada, and other countries during the early thawing season by controlling the movement of freight-carrying trucks and heavy equipment travel until the thawing ends. Most SLR policies rely on the Freezing Depth (FD) and Thawing Depth (TD), especially the latter one. Therefore, accurate predictions of FD and TD are important to prevent both the extensive damage to the pavement due to the late placement or early removal of SLR and the economic loss of road users due to an unnecessarily long SLR period. Here, we propose a new multivariate model for predicting FD and TD in support of SLR decision-making. The model gives a curving surface of FD and TD in a 3-dimensional space, instead of 2-dimensional in traditional methods, by considering both the freezing and thawing indices in the entire freeze-thaw cycle. For model evaluations, yearly field data measured at five typical sites from 104 sites in Michigan were adopted. The evaluation results showed that the proposed model is accurate in predicting FD and TD for most sites. Compared to the previous TD predictions in the existing study, the TD predictions with the proposed model have been significantly improved. In addition, this study provides field data that have not been reported earlier in the literature and that can be used for validating other prediction models. The reported work is ready for practice for roadways in cold regions to support SLR decision-making.

https://digitalcommons.mtu.edu/michigantech-p/406

Citation: Bao, T., Liu, Z., & Bland, J. (2019). A multivariate freezing-thawing depth prediction model for spring load restriction. Cold Regions Science and Technology, 167.http://dx.doi.org/10.1016/j.coldregions.2019.102856

Bo Chen Receives $250K NSF Award for Mobile PDE Systems Research

Bo Chen, CS

Bo Chen, assistant professor of computer science and member of the Institute of Computing and Cybersystems Center for  Cybersecurity, is the principal investigator on a project that has received a $249,918 research and development grant from the National Science Foundation. The project is entitled, “SaTC: CORE: Small: Collaborative: Hardware-Assisted Plausibly Deniable System for Mobile Devices.” This is a potential three-year project.

Abstract: Mobile computing devices typically use encryption to protect sensitive information. However, traditional encryption systems used in mobile devices cannot defend against an active attacker who can force the mobile device owner to disclose the key used for decrypting the sensitive information. This is particularly of concern to dissident users who are targets of nation states. An example of this would be a human rights worker collecting evidence of untoward activities in a region of oppression or conflict and storing the same in an encrypted form on the mobile device, and then being coerced to disclose the decryption key by an official. Plausibly Deniable Encryption (PDE) has been proposed to defend against such adversaries who can coerce users into revealing the encrypted sensitive content. However, existing techniques suffer from several problems when used in flash-memory-based mobile devices, such as weak deniability because of the way read/write/erase operations are handled at the operating systems level and at the flash translation layer, various types of side channel attacks, and computation and power limitations of mobile devices. This project investigates a unique opportunity to develop an efficient (low-overhead) and effective (high-deniability) hardware-assisted PDE scheme on mainstream mobile devices that is robust against a multi snapshot adversary. The project includes significant curriculum development activities and outreach activities to K-12 students.

This project fundamentally advances the mobile PDE systems by leveraging existing hardware features such as flash translation layer (FTL) firmware and TrustZone to achieve a high deniability with a low overhead. Specifically, this project develops a PDE system with capabilities to: 1) defend against snapshot attacks using raw flash memory on mobile devices; and 2) eliminate side-channel attacks that compromise deniability; 3) be scalable to deploy on mainstream mobile devices; and 4) efficiently provide usable functions like fast mode switching. This project also develops novel teaching material on PDE and cybersecurity for K-12 students and the Regional Cybersecurity Education Collaboration (RCEC), a new educational partnership on cybersecurity in Michigan.

Publications related to this research:

[DSN ’18] Bing Chang, Fengwei Zhang, Bo Chen, Yingjiu Li, Wen Tao Zhu, Yangguang Tian, Zhan Wang, and Albert Ching. MobiCeal: Towards Secure and Practical Plausibly Deniable Encryption on Mobile Devices. The 48th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN ’18), June 2018 (Acceptance rate: 28%)
[Cybersecurity ’18] Qionglu Zhang, Shijie Jia, Bing Chang, Bo Chen. Ensuring Data Confidentiality via Plausibly Deniable Encryption and Secure Deletion – A Survey. Cybersecurity (2018) 1: 1.
[ComSec ’18 ] Bing Chang, Yao Cheng, Bo Chen, Fengwei Zhang, Wen Tao Zhu, Yingjiu Li, and Zhan Wang. User-Friendly Deniable Storage for Mobile Devices. Elsevier Computers & Security, vol. 72, pp. 163-174, January 2018
[CCS ’17] Shijie Jia, Luning Xia, Bo Chen, and Peng Liu. DEFTL: Implementing Plausibly Deniable Encryption in Flash Translation Layer. 2017 ACM Conference on Computer and Communications Security (CCS ’17), Dallas, Texas, USA, Oct 30 – Nov 3, 2017 (Acceptance rate: 18%)
[ACSAC ’15] Bing Chang, Zhan Wang, Bo Chen, and Fengwei Zhang. MobiPluto: File System Friendly Deniable Storage for Mobile Devices. 2015 Annual Computer Security Applications Conference (ACSAC ’15), Los Angeles, California, USA, December 2015 (Acceptance rate: 24.4%)
[ISC ’14] Xingjie Yu, Bo Chen, Zhan Wang, Bing Chang, Wen Tao Zhu, and Jiwu Jing. MobiHydra: Pragmatic and Multi-Level Plausibly Deniable Encryption Storage for Mobile Devices. The 17th Information Security Conference (ISC ’14), Hong Kong, China, Oct. 2014

Link to more information about this project: https://snp.cs.mtu.edu/research/index.html#pde

Soner Onder Receives Year One Funding for $1.2M NSF SCALE Project

Soner Onder
Dave Whalley

Soner Onder, professor of computer science, was recently awarded $246,329 for the first year of a four-year NSF grant for his project, “SHF: Medium: Collaborative Research: Statically Controlled Asynchronous Lane Execution (SCALE).” The project is in collaboration with Prof. David Whalley of Florida State University. Michigan Tech is the lead institution in the project, it is expected to total $1.2 million, with Michigan Tech receiving $600,000.

Abstract: Enabling better performing systems benefits applications that span those running on mobile devices to large data applications running on data centers. The efficiency of most applications is still primarily affected by single thread performance. Instruction-level parallelism (ILP) speeds up programs by executing instructions of the program in parallel, with ‘superscalar’ processors achieving maximum performance. At the same time, energy efficiency is a key criteria to keep in mind as such speedup happens, with these two being conflicting criteria in system design. This project develops a Statically Controlled Asynchronous Lane Execution (SCALE) approach that has the potential to meet or exceed the performance of a traditional superscalar processor while approaching the energy efficiency of a very long instruction word (VLIW) processor. As implied by its name, the SCALE approach has the ability to scale to different types and levels of parallelism. The toolset and designs developed in this project will be available as open-source and will also have an impact on both education and research. The SCALE architectural and compiler techniques will be included in undergraduate and graduate curricula.

The SCALE approach supports separate asynchronous execution lanes where dependencies between instructions in different lanes are statically identified by the compiler to provide inter-lane synchronization. Providing distinct lanes of instructions allows the compiler to generate code for different modes of execution to adapt to the type of parallelism that is available at each point within an application. These execution modes include explicit packaging of parallel instructions, parallel and pipelined execution of loop iterations, single program multiple data (SPMD) execution, and independent multi-threading.

This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.

https://www.nsf.gov/awardsearch/showAward?AWD_ID=1901005&HistoricalAwards=false

Keith Vertanen and Scott Kuhl Awarded $500K NSF Grant

Scott Kuhl
Scott Kuhl
Keith Vertanen
Keith Vertanen

Keith Vertanen, assistant professor of computer science (HCC), and Scott Kuhl (HCC), associate professor of computer science, are principal investigators of a recently funded three-year National Science Foundation grant for their project, “CHS: Small: Rich Surface Interaction for Augmented Environments.” The expected funding over three years is $499,552.00.

Vertanen and Kuhl are members of Michigan Tech’s Institute of Computing and Cybersystems (ICC) Center for Human-Centered Computing. A 2018 ICC research seed grant funded by ECE Alumnus Paul Williams was used to produce some of the preliminary results in the successful proposal. More info about the Williams Seed Grant can be found here: https://blogs.mtu.edu/icc/2019/07/16/appropriating-everyday-surfaces-for-tap-interaction/.

A related video can be found here: https://youtu.be/sF7aeXMfsIQ.

Abstract: Virtual Reality (VR) and Augmented Reality (AR) head-mounted displays are increasingly being used in different computing related activities such as data visualization, education, and training. Currently, VR and AR devices lack efficient and ergonomic ways to perform common desktop interactions such as pointing-and-clicking and entering text. The goal of this project is to transform flat, everyday surfaces into a rich interactive surface. For example, a desk or a wall could be transformed into a virtual keyboard. Flat surfaces afford not only haptic feedback, but also provide ergonomic advantages by providing a place to rest your arms. This project will develop a system where microphones are placed on surfaces to enable the sensing of when and where a tap has occurred. Further, the system aims to differentiate different types of touch interactions such as tapping with a fingernail, tapping with a finger pad, or making short swipe gestures.

This project will investigate different machine learning algorithms for producing a continuous coordinate for taps on a surface along with associated error bars. Using the confidence of sensed taps, the project will investigate ways to intelligently inform aspects of the user interface, e.g. guiding the autocorrection algorithm of a virtual keyboard decoder. Initially, the project will investigate sensing via an array of surface-mounted microphones and design “surface algorithms” to determine and compare the location accuracy of the finger taps on the virtual keyboard. These algorithms will experiment with different models including existing time-of-flight model, a new model based on Gaussian Process Regression, and a baseline of classification using support vector machines. For all models, the project will investigate the impact of the amount of training data from other users, and varying the amount of adaptation data from the target user. The project will compare surface microphones with approaches utilizing cameras and wrist-based inertial sensors. The project will generate human-factors results on the accuracy, user preference, and ergonomics of interacting midair versus on a rigid surface. By examining different sensors, input surfaces, and interface designs, the project will map the design space for future AR and VR interactive systems. The project will disseminate software and data allowing others to outfit tables or walls with microphones to enable rich interactive experiences.

Dr. Theda Daniels-Race to Present Seminar September 9

Dr. Theda Daniels-Race, the Michael B. Voorheis Distinguished Professor in the Division of Electrical & Computer Engineering at Louisiana State University, will present her seminar, “Deposition, Characterization, and Developments in Hybrid Electronic Materials for Next-Generation Nanoelectronics,” on Monday, September 9, at 3:00 pm in Room 6452 of the Dow Environmental Sciences and Engineering Building.

This seminar is presented by the Institute of Computing and Cybersystems and the Michigan Tech Visiting Professor Program, which is funded by a grant to the Michigan Tech Provost Office from the State of Michigan’s King-Chavez-Parks Initiative.

Dr. Daniels-Race also has a  joint appointment to the Center for Computation and Technology at Louisiana State University.  She is the founder of the Applied Hybrid Electronic Materials & Structures Laboratory as well as Director of the ECE Division’s Electronic Materials & Devices Laboratory.  Her research has encompassed a range of studies upon electronic materials from the growth of compound semiconductors via molecular beam epitaxy (MBE), to investigations of electron transport in low-dimensional systems such as quantum wells, wires, and dots, to device design and fabrication.  Her current work is in the area of hybrid electronic materials (HEMs) and involves studies of sample morphologies, nanoscale electronic behavior, and the design of apparatus for HEM deposition.

Dr. Daniels-Race received her degrees in Electrical Engineering from Rice, Stanford, and Cornell universities, for the B.S., M.S., and Ph.D., respectively.  As an undergraduate, she received a GEM (Graduate Engineering Minorities) Fellowship for her future MS studies, and while working on her masters, she was selected to receive one of fewer than ten CRFP (Cooperative Research Fellowship Program) competitive fellowships awarded nationally that year by AT&T for her PhD. Throughout her academic training, Daniels-Race worked in industry with corporations such as Union Carbide, Exxon, General Electric, and AT&T Bell Laboratories.  She began her academic career with the ECE Department at Duke University, where she built that institution’s first MBE laboratory and, over the next thirteen years, established a program in experimental compound semiconductor materials research.  Daniels-Race was recruited to join the LSU faculty where she conducts research upon HEMs for use in next-generation nanoscale devices.  To the community she has been an active member of several professional societies including the IEEE, the American Physical Society, the Materials Research Society, and the National Society of Black Physicists.  She is an ELATES (Executive Leadership in Academic Technology, Engineering and Science) alumna and is a strong advocate for minorities and women in science and engineering.

Seminar Abstract: Ubiquitous dependence upon semiconductor-based technology has reached a critical turning point.  In effect “small has hit the wall” (Moore’s Law) as advancements, in everything from cell phones to satellites, struggle to keep pace with demands for smaller, faster, and ever more affordable devices. Thus, researchers operating under the broadly defined umbrella of nanoelectronics inherently challenge traditional solid-state electronic design paradigms and fabrication practices.  To this end, my research focuses upon that which I have dubbed HEMs or “hybrid electronic materials.”  In this talk, I will present an overview of work in progress, conducted by both my graduate and undergraduate students, as part of the Applied Hybrid Electronic Materials & Structures (AHEMS) Laboratory that I have established in the Division of Electrical and Computer Engineering at Louisiana State University. With an eye toward the next generation of electronics, new materials and nanoscale structures must be investigated in order to understand the unique physics and potential applications of electronic phenomena “beyond the transistor.”  Using hybrid (inorganic-organic) electronic materials, my group works to characterize the nanoscale formations and electronic behavior of HEMs, as well as to develop innovative yet low-cost apparatus and techniques through which these materials may be explored.

Theda Daniels-Race CV

Download the Seminar Flyer