Illinois Institute of Technology, commonly called Illinois Tech or IIT, is a private Ph.D.-granting research university located in Chicago, in the U.S. state of Illinois, with programs in engineering, science, psychology, architecture, business, communications, industrial technology, information technology, design and law. Wikipedia.
University of Chicago and Illinois Institute of Technology | Date: 2015-08-05
The disclosure provides methods of preventing or treating metabolic syndrome in a subject by administering an effective amount of an inhibitor of laminin 4 expression, laminin 4 activity, or both.
Illinois Institute of Technology | Date: 2016-07-22
A region of interest (ROI) generation method for stereo-based pedestrian detection systems. A vertical gradient of a clustered depth map is used to find ground plane and variable-sized bounding boxes are extracted on a boundary of the ground plane as ROIs. The ROIs are then classified into pedestrian and non-pedestrian classes. Simulation results show the algorithm outperforms the existing monocular and stereo-based methods.
The Regents Of The University Of California and Illinois Institute of Technology | Date: 2017-02-01
Method for modulating oxidative stress, inflammation, and impaired insulin sensitivity in a subject by using a grape seed extract, the method being useful in modulating post-prandial oxidative stress, inflammation, and impaired insulin sensitivity in patients suffering from Metabolic Syndrome (MetS). The method comprising administering a therapeutically effective amount of a grape seed extract and a pharmaceutically acceptable excipient. The grape seed extract is a polyphenolic extract comprising proanthocyanidins and anthocyanidins.
Hildt E.,Illinois Institute of Technology
Frontiers in Systems Neuroscience | Year: 2015
Recent brain-to-brain interfacing studies provide proof of principle for the feasibility of various forms of direct information transfer between two brains, and may lead to the development of new approaches involving memory, emotions, or senses. What makes brain-to-brain interfaces unique is the transfer of information representing specific messages directly from one brain to another, without involving any activity of the peripheral nervous system or senses. The article discusses ethical issues that arise in neural interfacing. The focus is on the implications that brain-to-brain interfaces may have on the individual at the recipient side. © 2015 Hildt.
Arges C.G.,Illinois Institute of Technology |
Ramani V.,Illinois Institute of Technology
Proceedings of the National Academy of Sciences of the United States of America | Year: 2013
Anion exchange membranes (AEMs) find widespread applications as an electrolyte and/or electrode binder in fuel cells, electrodialysis stacks, flow and metal-air batteries, and electrolyzers. AEMs exhibit poor stability in alkaline media; their degradation is induced by the hydroxide ion, a potent nucleophile. We have used 2D NMR techniques to investigate polymer backbone stability (as opposed to cation stability) of the AEM in alkaline media. We report the mechanism behind a peculiar, often-observed phenomenon, wherein a demonstrably stable polysulfone backbone degrades rapidly in alkaline solutions upon derivatization with alkaline stable fixed cation groups. Using COSY and heteronuclear multiple quantum correlation spectroscopy (2D NMR), we unequivocally demonstrate that the added cation group triggers degradation of the polymer backbone in alkaline via quaternary carbon hydrolysis and ether hydrolysis, leading to rapid failure. This finding challenges the existing perception that having a stable cation moiety is sufficient to yield a stable AEM and emphasizes the importance of the often ignored issue of backbone stability.
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 500.00K | Year: 2016
Wireless communications powered by renewable energy sources have been emerging as a promising solution to mitigate the carbon footprints to achieve a green radio network. However, renewable energy sources, such as solar and wind, are by nature unstable in their availability and capacity, which poses new challenges in the design and deployment of a sustainable communication network. The project will develop theoretical tools, propose new protocols and cross-layer optimization methods to enable an energy sustainable communication network. The multidisciplinary project will also foster the integration of research and education and provide both undergraduate and graduate students, particularly women and minority students, with an opportunity to participate in various training projects, which further inspire students to pursue high quality research with critical thinking.
In a renewable energy powered communication network, the fundamental design criterion and main performance metric have shifted from energy efficiency to energy sustainability, i.e., to ensure the harvested energy can sustain the user demands with satisfactory quality of service provisioning. In this project, a novel performance metric, the energy sustainability, is first formulated, based on which the energy sustainable performance of a communication system will be systematically analyzed, characterizing the dynamic energy charging and discharging processes. The analysis will be leveraged to investigate a series of fundamental research issues on sustainable communication and networking, including energy management, network deployment, admission control, adaptive resource allocation, and medium access control. Analytical tools in queueing theory, game theory, stochastic optimization, probability theory, and random processes will be used in the design, analysis, and optimization of the proposed algorithms and protocols to ensure energy sustainable operation of a wireless communication network. The research outcomes of the project have potential to be implemented in the next generation wireless communication network powered by renewable energy.
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 500.00K | Year: 2016
Traffic congestion jeopardizes the function of urban transportation systems and has a growing negative effect on the health of urban economies. It also increases air pollution with numerous negative health impacts on our citizenry. A promising solution to alleviating traffic congestion is to establish coordinated driving mechanisms. This is enabled by recent connected or even autonomous vehicle technologies and advanced onboard computing facilities. However, engineers who design such mechanisms are still lacking scientific knowledge and effective tools that can be proven as efficient and reliable for use by the general public. The goal of this Faculty Early Career Development (CAREER) program award is to develop innovative approaches to the coordination of connected vehicle drivers- online route choices. This will be done by exploiting emerging information and computing technologies equipped in connected transportation infrastructure. This approache will improve transportation system mobility, safety, and environmental sustainability without sacrificing the interests of the individual vehicles. This research will deepen our understanding of the competition among vehicles on limited traffic resources. It should also reveal the impacts of the decisions of individual vehicles on traffic congestion, and offer a new paradigm of real-time traffic control.
The specific research objectives of this CAREER project are: (a) developing coordinated mechanisms for drivers - route choices to mitigate over-competition; (b) engineering collective effects of drivers - decisions to improve system-level performance; and (c) implementing the coordinated routing mechanisms and decentralized traffic control in an online environment. If successful, this project will lead to: (1) game-theory based modeling, analysis, and design techniques for coordinated routing mechanisms; (2) innovative methods for integrating decentralized control into individual routing decisions via intentional information perturbation techniques; and (3) better understanding of convergence, efficiency and robustness of distributed algorithms for decentralized congestion control. The reseach approaches include: (a) using game theory, optimization, and traffic dynamics to design and analyze coordination mechanisms; (b) using equilibrium analysis, price of anarchy, bounded rationality, and decentralized control for the study of collective effects; and (c) developing distributed algorithms for implementation and carrying out a theoretical analysis of these algorithms. This project will involve underrepresented K-12 students, undergraduate and graduate college students in numerous research tasks, and disseminate research findings through multiple channels, such as national/international workshops and conferences, as well as journal publications.
Agency: NSF | Branch: Standard Grant | Program: | Phase: Campus Cyberinfrastrc (CC-NIE) | Award Amount: 342.80K | Year: 2017
To drive innovation, improve research capabilities and productivity, enhance faculty competiveness, and foster remote collaborations of resources and people, the Illinois Institute of Technology (IIT or Illinois Tech) is building a Science DMZ (Demilitarized Zone) ecosystem to provide access to a secured, high-throughput infrastructure for the IIT research community. The proposed Science DMZ bridges the needs of many diverse data-intensive research projects and address common issues and limitations with real-time data analysis that results from the current campus network. The overall goal for the Science DMZ is to deploy a scalable research network infrastructure with a minimum bandwidth of 10Gbps that can isolate and secure research network traffic from other segments of the campus network without impacting performance. This goal is buttressed by several broad objectives including increasing the bandwidth between the research data center and Internet2 exchange node; and connecting with other world-class universities and research center at throughput speeds sufficient for practical end-to-end research collaborations.
The deployment of the Science DMZ has far-reaching broader impacts. For example, the Science DMZ makes it feasible for IIT researchers analyzing urban metropolitan transportation congestion relief, safety and capital investment to improve the efficiency of intersection utilization across the United States. The Institute of Food Safety and Health (IFSH) is working on a whole genome sequencing project that aims to create a global catalogue of bacteria-causing food poisoning. This advanced high performance infrastructure provides greater collaboration opportunities with Tier-1 research universities and by default, introduces greater opportunities for IIT students to get hands-on experience working with faculty on various research projects, thereby improving the quality of their STEM education. Collaborative activities are also planned with several of IITs K-12 outreach initiatives including the Global Leaders Program, which seeks to increase access to STEM fields.
Agency: NSF | Branch: Standard Grant | Program: | Phase: BIOPHOTONICS, IMAGING &SENSING | Award Amount: 500.00K | Year: 2017
ABSTRACT: Tichauer; 1653627
Approximately 1 in 8 women in the US will develop breast cancer in their lifetime. Over 40,000 women are projected to die from the disease in 2016. Surgical resection and pathology of tumor-draining lymph nodes is the current standard for detecting whether cancer has spread. However, because of the time-consuming nature of pathological assessment, less than 1% of a typical excised node is surveyed and microscopic levels of cancer are liable to be missed. The objective of this work is to rapidly map cancer distribution in surgically excised tumor-draining or sentinel lymph nodes using a novel optical imaging technology that could guide sectioning of lymph nodes in pathology so that even microscopic levels of cancer are not missed.
The approach, named ADEPT (Agent Dependent Early Photon Tomography), combines two methods that serve to provide high sensitivity and selectivity for cancer cells within highly scattering media. First, an infrared-emitting dye perfuse the node, with one dye selectively targeted to cancer cells, while the other is nonspecific, enabling compensation for local variability in dye concentration. Second, pulse excitation combined with snapshot detection of the earliest photons-to-arrive-at-the detector are counted. To obtain 3-D reconstructions of the internal lymph node volume, the image plane is scanned through the volume. With the appropriate selection of dyes, the approach can be applied to thick tissue (up to 1 cm), with a goal of 100 um image resolution.
Agency: NSF | Branch: Standard Grant | Program: | Phase: National Robotics Initiative | Award Amount: 899.93K | Year: 2016
The objective of this research is to ensure the integrity of vehicle position, heading, and velocity estimates that are used by self-driving cars as the basis for life-critical decisions such as the initiation and execution of hazard-avoidance maneuvers. Integrity, which is a measure of trust in a sensors information, has been successfully implemented in commercial aircraft to guarantee the safety of maneuvers such as landing. This project addresses several obstacles in translating integrity from aviation applications to self-driving cars, including integrating the disparate sensor types used by ground vehicles; meeting the stringent demands of routine autonomous driving; accounting for the number, proximity, and high relative velocity of other vehicles on the road; and evaluating multiple, distinct, and mutually exclusive courses of action in a timely manner. Project subtasks include characterization of integrity for representative sensors, construction of appropriate models for uncertainty propagation, and experimental validation of the resulting integrity framework. The project will advance the larger research effort to realize the potential of self-driving cars for relieving congestion, reducing emissions, and saving lives. The work includes public outreach efforts on autonomous navigation for self-driving cars, which will build upon an ongoing relationship with Chicagos Museum of Science and Industry, including a hands-on demonstration during National Robotics Week to illustrate how safety can be ensured despite uncertainties related to sensor readings, vehicle dynamics, and the driving environment.
Specifically, this research will provide new experimental and analytical methods to quantify and prove self-driving car safety. The results of this work will create a high-level, sensor-independent, quantifiable metric that can be used to compare, evaluate, and certify safety across self-driving car manufacturers. Knowledge will be advanced in several previously-unexplored areas, including first-ever demonstrations of: 1) high-integrity sensor measurement error and fault models for non-GPS sensors, 2) analytical methods to quantify the safety risk of feature extraction and data association algorithms required in lidar, radar, and camera-based localization, 3) multi-sensor pose estimators and integrity monitors designed to evaluate the impact of undetected sensor faults on safety risk, and 4) rigorously derived and experimentally validated integrity risk prediction methods in dynamic environments.