Anderson, United States
Anderson, United States

Time filter

Source Type

PubMed | Psychiatry and Behavioral science, Industrial and Systems Engineering., University of Washington, University of California at Los Angeles and 5 more.
Type: Journal Article | Journal: Journal of neurosurgery. Pediatrics | Year: 2016

OBJECTIVE Posttraumatic seizure is a major complication following traumatic brain injury (TBI). The aim of this study was to determine the variation in seizure prophylaxis in select pediatric trauma centers. The authors hypothesized that there would be wide variation in seizure prophylaxis selection and use, within and between pediatric trauma centers. METHODS In this retrospective multicenter cohort study including 5 regional pediatric trauma centers affiliated with academic medical centers, the authors examined data from 236 children (age < 18 years) with severe TBI (admission Glasgow Coma Scale score 8, ICD-9 diagnosis codes of 800.0-801.9, 803.0-804.9, 850.0-854.1, 959.01, 950.1-950.3, 995.55, maximum head Abbreviated Injury Scale score 3) who received tracheal intubation for 48 hours in the ICU between 2007 and 2011. RESULTS Of 236 patients, 187 (79%) received seizure prophylaxis. In 2 of the 5 centers, 100% of the patients received seizure prophylaxis medication. Use of seizure prophylaxis was associated with younger patient age (p < 0.001), inflicted TBI (p < 0.001), subdural hematoma (p = 0.02), cerebral infarction (p < 0.001), and use of electroencephalography (p = 0.023), but not higher Injury Severity Score. In 63% cases in which seizure prophylaxis was used, the patients were given the first medication within 24 hours of injury, and 50% of the patients received the first dose in the prehospital or emergency department setting. Initial seizure prophylaxis was most commonly with fosphenytoin (47%), followed by phenytoin (40%). CONCLUSIONS While fosphenytoin was the most commonly used medication for seizure prophylaxis, there was large variation within and between trauma centers with respect to timing and choice of seizure prophylaxis in severe pediatric TBI. The heterogeneity in seizure prophylaxis use may explain the previously observed lack of relationship between seizure prophylaxis and outcomes.


News Article | March 2, 2017
Site: www.eurekalert.org

BINGHAMTON, NY-Government agencies cannot always use social media and telecommunication to uncover the intentions of terrorists as terrorists are now more careful in utilizing these technologies for planning and preparing for attacks. A new framework developed by researchers at Binghamton University, State University of New York is able to understand future terrorist behaviors by recognizing patterns in past attacks. Researchers at Binghamton have proposed a comprehensive new framework, the Networked Pattern Recognition (NEPAR) Framework, by defining the useful patterns of attacks to understand behaviors, to analyze patterns and connections in terrorist activity, to predict terrorists' future moves, and finally, to prevent and detect potential terrorist behaviors. Using data on more than 150,000 terrorist attacks between 1970 and 2015, Binghamton University PhD student Salih Tutun developed a framework that calculates the relationships among terrorist attacks (e.g. attack time, weapon type) and detects terrorist behaviors with these connections. Mohammad Khasawneh, professor and head of the Systems Science and Industrial Engineering (SSIE) department at Binghamton University, assisted and advised Tutun with his research. Jun Zhuang, an associate professor and director of undergraduate studies in the Department of Industrial and Systems Engineering at the University at Buffalo, also contributed to this research. In the framework, there are two main phases: (1) building networks by finding connections between events, and (2) using a unified detection approach that combines proposed network topology and pattern recognition approaches. Firstly, the framework identifies the characteristics of future terrorist attacks by analyzing the relationship between past attacks. Comparing the results with existing data shows that the proposed method was able to successfully predict most of the characteristics of attacks with more than 90% accuracy. Moreover, after building the network with connections, the researchers propose a unified detection approach that applies pattern classification techniques to network topology and features of incidents to detect terrorism attacks with high accuracy, and identify the extension of attacks (90 percent accuracy), multiple attacks (96 percent accuracy) and terrorist goals (92 percent accuracy). Hence, governments can control terrorist behaviors to reduce the risk of future events. The results could potentially allow law enforcement to propose reactive strategies, said Tutun. "Terrorists are learning, but they don't know they are learning. If we can't monitor them through social media or other technologies, we need to understand the patterns. Our framework works to define which metrics are important," said Tutun. "Based on this feature, we propose a new similarity (interaction) function. Then we use the similarity (interaction) function to understand the difference (how they interact with each other) between two attacks. For example, what is the relationship between the Paris and the 9/11 attacks? When we look at that, if there's a relationship, we're making a network. Maybe one attack in the past and another attack have a big relationship, but nobody knows. We tried to extract this information." Previous studies have focused on understanding the behavior of individual terrorists (as people) rather than studying the different attacks by modeling their relationship with each other. And terrorist activity detection focuses on either individual incidents, which does not take into account the dynamic interactions among them; or network analysis, which gives a general idea about networks but sets aside functional roles of individuals and their interactions. "Predicting terrorist events is a dream, but protecting some area by using patterns is a reality. If you know the patterns, you can reduce the risks. It's not about predicting, it's about understanding," said Tutun. Tutun believes that policymakers can use these approaches for time-sensitive understanding and detection of terrorist activity, which can enable precautions to avoid against future attacks. "When you solve the problem in Baghdad, you solve the problem in Iraq. When you solve the problem in Iraq, you solve the problem in the Middle East. When you solve the problem in the Middle East, you solve the problem in the world," said Tutun. "Because when we look at Iraq, these patterns are happening in the USA, too." The paper, "New framework that uses patterns and relations to understand terrorist behaviors," was published in Expert Systems with Applications.


News Article | September 16, 2016
Site: www.rdmag.com

Researchers at North Carolina State University have developed a new type of inverter device with greater efficiency in a smaller, lighter package – which should improve the fuel-efficiency and range of hybrid and electric vehicles. Electric and hybrid vehicles rely on inverters to ensure that enough electricity is conveyed from the battery to the motor during vehicle operation. Conventional inverters rely on components made of the semiconductor material silicon. Now researchers at the Future Renewable Electric Energy Distribution and Management (FREEDM) Systems Center at NC State have developed an inverter using off-the-shelf components made of the wide-bandgap semiconductor material silicon carbide (SiC) – with promising results. “Our silicon carbide prototype inverter can transfer 99 percent of energy to the motor, which is about two percent higher than the best silicon-based inverters under normal conditions,” says Iqbal Husain, ABB Distinguished Professor of Electrical and Computer Engineering at NC State and director of the FREEDM Center. “Equally important, the silicon carbide inverters can be smaller and lighter than their silicon counterparts, further improving the range of electric vehicles,” says Husain, who co-authored two papers related to the work. “And new advances we’ve made in inverter components should allow us to make the inverters even smaller still.” Range is an important issue because so-called “range anxiety” is a major factor limiting public acceptance of electric vehicles. People are afraid they won’t be able to travel very far or that they’ll get stuck on the side of the road. The new SiC-based inverter is able to convey 12.1 kilowatts of power per liter (kW/L) – close to the U.S. Department of Energy’s goal of developing inverters that can achieve 13.4 kW/L by 2020. By way of comparison, a 2010 electric vehicle could achieve only 4.1 kW/L. “Conventional, silicon-based inverters have likely improved since 2010, but they’re still nowhere near 12.1 kW/L,” Husain says. The power density of new SiC materials allows engineers to make the inverters – and their components, such as capacitors and inductors – smaller and lighter. “But, frankly, we are pretty sure that we can improve further on the energy density that we’ve shown with this prototype,” Husain says. That’s because the new inverter prototype was made using off-the-shelf SiC components – and FREEDM researchers have recently made new, ultra-high density SiC power components that they expect will allow them to get closer to DOE’s 13.4 kW/L target once it’s incorporated into next generation inverters. What’s more, the design of the new power component is more effective at dissipating heat than previous versions. This could allow the creation of air-cooled inverters, eliminating the need for bulky (and heavy) liquid cooling systems. “We predict that we’ll be able to make an air-cooled inverter up to 35 kW using the new module, for use in motorcycles, hybrid vehicles and scooters,” Husain says. “And it will boost energy density even when used with liquid cooling systems in more powerful vehicles.” The current SiC inverter prototype was designed to go up to 55 kW – the sort of power you’d see in a hybrid vehicle. The researchers are now in the process of scaling it up to 100 kW – akin to what you’d see in a fully electric vehicle – using off-the-shelf components. And they’re also in the process of developing inverters that make use of the new, ultra-high density SiC power component that they developed on-site. A paper on the new inverter, “Design Methodology for a Planarized High Power Density EV/HEV Traction Drive using SiC Power Modules,” will be presented at the IEEE Energy Conversion Congress and Exposition (ECCE), being held Sept. 18-22 in Milwaukee. Lead author of the paper is Dhrubo Rahman, a Ph.D. student at NC State. The paper was co-authored by Adam Morgan, Yang Xu and Rui Gao, who are Ph.D. students at NC State; Wensong Yu and Douglas Hopkins, research professors in NC State’s Department of Electrical and Computer Engineering; and Husain. A paper on the new, ultra-high density SiC power component, “Development of an Ultra-high Density Power Chip on Bus Module,” will also be presented at ECCE. Lead author of the paper is Yang Xu. The paper was co-authored by Yu, Husain and Hopkins, as well as by Harvey West, a research professor in NC State’s Edward P. Fitts Department of Industrial and Systems Engineering. The research was done with the support of the PowerAmerica Institute, a public-private research initiative housed at NC State and funded by DOE’s Office of Energy Efficiency and Renewable Energy under award number DE-EE0006521. FREEDM, a National Science Foundation Engineering Research Center, is aimed at facilitating the development and implementation of new renewable electric-energy technologies.


News Article | September 7, 2016
Site: phys.org

That's according to a new University at Buffalo study that explores security vulnerabilities of 3-D printing, also called additive manufacturing, which analysts say will become a multibillion-dollar industry employed to build everything from rocket engines to heart valves. "Many companies are betting on 3-D printing to revolutionize their businesses, but there are still security unknowns associated with these machines that leave intellectual property vulnerable," said Wenyao Xu, PhD, assistant professor in UB's Department of Computer Science and Engineering, and the study's lead author. Xu and collaborators will present the research, "My Smartphone Knows What You Print: Exploring Smartphone-based Side-channel Attacks Against 3D Printers," at the Association for Computing Machinery's 23rd annual Conference on Computer and Communications Security in October in Austria. Unlike most security hacks, the researchers did not simulate a cyberattack. Many 3-D printers have features, such as encryption and watermarks, designed to foil such incursions. Instead, the researchers programmed a common smartphone's built-in sensors to measure electromagnetic energy and acoustic waves that emanate from 3-D printers. These sensors can infer the location of the print nozzle as it moves to create the three-dimensional object being printed. The smartphone, at 20 centimeters away from the printer, gathered enough data to enable the researchers to replicate printing a simple object, such as a door stop, with a 94 percent accuracy rate. For complex objects, such as an automotive part or medical device, the accuracy rate was lower but still above 90 percent. "The tests show that smartphones are quite capable of retrieving enough data to put sensitive information at risk," says Kui Ren, PhD, professor in UB's Department of Computer Science and Engineering, a co-author of the study. The richest source of information came from electromagnetic waves, which accounted for about 80 percent of the useful data. The remaining data came from acoustic waves. Ultimately, the results are eye-opening because they show how anyone with a smartphone—from a disgruntled employee to an industrial spy—might steal intellectual property from an unsuspecting business, especially "mission critical" industries where one breakdown of a system can have a serious impact on the entire organization. "Smartphones are so common that industries may let their guard down, thus creating a situation where intellectual property is ripe for theft," says Chi Zhou, PhD, assistant professor in UB's Department of Industrial and Systems Engineering, another study co-author. The researchers suggests several ways to make 3-D printing more secure. Perhaps the simplest deterrent from such an attack is distance. The ability to obtain accurate data for simple objects diminished to 87 percent at 30 centimeters, and 66 percent at 40 centimeters, according to the study. Another option is to increase the print speed. The researchers said that emerging materials may allow 3-D printers to work faster, thus making it more difficult for smartphone sensors to determine the print nozzle's movement. Other ideas include software-based solutions, such as programming the printer to operate at different speeds, and hardware-based ideas, such as acoustic and electromagnetic shields. Explore further: HP injecting Internet technology into new printers


Navarro E.N.,Industrial and Systems Engineering | Bourguet R.E.,Industrial and Systems Engineering | Aceves N.,Industrial and Systems Engineering | Garza J.,Cemex
61st Annual IIE Conference and Expo Proceedings | Year: 2011

This paper shows the design and development of a knowledge transfer tool. Specifically, to transfer design concepts on how to build simulation-based decision support systems for operational planning in a concrete order fulfillment process. The tool is based on self-directed learning methodology, interactive design principles, and supported by the computational package iThink. Design concepts to be transferred correspond to logical-discrete structures of a simulation model of more than 4000 variables. The simulator represents logistics knowledge at the execution level, and thus it supports minute-hourly basis decisions. The tool responds to a demand for disseminating best practices in a global organization. It is a result of a joined university-industry research effort to reinforce knowledge management capabilities in both entities. Foundations, design criteria, and detail of main results on the design and development process for the knowledge transfer tool are described. Finally, conclusions and future works are included.


Cogswell J.T.,Industrial and Systems Engineering | Li P.,Industrial and Systems Engineering | Faghri M.,Industrial and Systems Engineering
2010 14th International Heat Transfer Conference, IHTC 14 | Year: 2010

Rapid mixing of two fluids in microchannels has posed an important challenge to the development of many integrated lab-on-a-chip systems. In this paper, we present a planar labyrinth micromixer (PLM) to achieve rapid and passive mixing by taking advantage of a synergistic combination of the Dean vortices in curved channels, a series of perturbation to the fluids from the sharp turns, and an expansion and contraction of the flow field via a circular chamber. The PLM is constructed in a single soft lithography step and the labyrinth has a footprint of 7.32 mm x 7.32 mm. Experiments using fluorescein isothiocyanate solutions and deionized water demonstrate that the design achieves fast and uniform mixing within 9.8 s to 32 ms for Reynolds numbers between 2.5 and 30. Compared to the mixing in the prevalent serpentine design, our design results in 38% and 79% improvements on the mixing efficiency at Re=5 and Re=30 respectively. An inverse relationship between mixing length and mass transfer Péclet number (Pe) is observed, which is superior to the logarithmic dependence of mixing length on Pe in chaotic mixers. Having a simple planar structure, the PLM can be easily integrated into lab-on-a-chip devices where passive mixing is needed. © 2010 by ASME.


Lockhart T.E.,Industrial and Systems Engineering | Lockhart T.E.,Wake forest University | Soangra R.,Industrial and Systems Engineering | Soangra R.,Wake forest University | And 2 more authors.
50th Annual Rocky Mountain Bioengineering Symposium and 50th International ISA Biomedical Sciences Instrumentation Symposium 2013 | Year: 2013

Mobility characteristics associated with activity of daily living such as sitting down, lying down, rising up, and walking are considered to be important in maintaining functional independence and healthy life style especially for the growing elderly population. Characteristics of postural transitions such as sit-to-stand are widely used by clinicians as a physical indicator of health, and walking is used as an important mobility assessment tool. Many tools have been developed to assist in the assessment of functional levels and to detect a person's activities during daily life. These include questionnaires, observation, diaries, kinetic and kinematic systems, and validated functional tests. These measures are costly and time consuming, rely on subjective patient recall and may not accurately reflect functional ability in the patient's home. In order to provide a low-cost, objective assessment of functional ability, inertial measurement unit (IMU) using MEMS technology has been employed to ascertain ADLs. These measures facilitate long-term monitoring of activity of daily living using wearable sensors. IMU system are desirable in monitoring human postures since they respond to both frequency and the intensity of movements and measure both dc (gravitational acceleration vector) and ac (acceleration due to body movement) components at a low cost. This has enabled the development of a small, lightweight, portable system that can be worn by a free-living subject without motion impediment - TEMPO (Technology Enabled Medical Precision Observation). Using this IMU system, we acquired indirect measures of biomechanical variables that can be used as an assessment of individual mobility characteristics with accuracy and recognition rates that are comparable to the modern motion capture systems. In this study, five subjects performed various ADLs and mobility measures such as posture transitions and gait characteristics were obtained. We developed postural event detection and classification algorithm using denoised signals from single wireless IMU placed at sternum. The algorithm was further validated and verified with motion capture system in laboratory environment. Wavelet denoising highlighted postural events and transition durations that further provided clinical information on postural control and motor coordination. The presented method can be applied in real life ambulatory monitoring approaches for assessing condition of elderly. © 2013 by ISA - instrumentation Systems & Automation Society.


Medal H.R.,Industrial and Systems Engineering | Pohl E.A.,University of Arkansas | Rossetti M.D.,University of Arkansas
IIE Transactions (Institute of Industrial Engineers) | Year: 2016

We study a new facility protection problem in which one must allocate scarce protection resources to a set of facilities given that allocating resources to a facility only has a probabilistic effect on the facilitys post-disruption capacity. This study seeks to test three common assumptions made in the literature on modeling infrastructure systems subject to disruptions: 1) perfect protection, e.g., protecting an element makes it fail-proof, 2) binary protection, i.e., an element is either fully protected or unprotected, and 3) binary state, i.e., disrupted elements are fully operational or non-operational. We model this facility protection problem as a two-stage stochastic program with endogenous uncertainty. Because this stochastic program is non-convex we present a greedy algorithm and show that it has a worst-case performance of 0.63. However, empirical results indicate that the average performance is much better. In addition, experimental results indicate that the mean-value version of this model, in which parameters are set to their mean values, performs close to optimal. Results also indicate that the perfect and binary protection assumptions together significantly affect the performance of a model. On the other hand, the binary state assumption was found to have a smaller effect. © 2015 "IIE".


Mandal S.,Industrial and Systems Engineering | Singh K.,Industrial and Systems Engineering | Behera R.K.,ITR Chandipur | Sahu S.K.,ITR Chandipur | And 2 more authors.
Expert Systems with Applications | Year: 2015

Human error identification and subsequent prioritization are the foremost tasks involved in HRA. In this study a methodology is developed for performing these tasks with an application to overhead crane operations. The application of the present methodology will help to understand how the risk associated with the human errors propagates through different hierarchy levels. The methodology provides a framework for quantifying the risk of different human errors using the experts' subjective opinions only. The incorporation of fuzzy VIKOR technique enables us develop a ranking mechanism for the failure modes where the individual constituent components are non-commensurable in nature. The developed ranking mechanism helps the decision makers in optimal allocation of safety critical resources, used for risk mitigation purposes. © 2015 Elsevier Ltd. All rights reserved.


News Article | September 19, 2016
Site: phys.org

Preparing for the take off of faster production, Lockheed Martin and the Department of Industrial and Systems Engineering at Texas A&M University are investigating the use of advanced industrial engineering tools and procedures to study F-35 rate production.

Loading Industrial and Systems Engineering collaborators
Loading Industrial and Systems Engineering collaborators