2013 IEEE Systems and Information Engineering Design Symposium最新文献

{"title":"Quantitative characterization of human performance during hip reduction","authors":"I. Motivation, M. E. Baltrusaitis, A. M. Lora, L. M. Hickman, A. C. Rodrigue, M. E. Baltrusaitis, Lingtian Wan, A. M. Lora, A. C. Rodrigue, Irene Y Kwon, L. M. Hickman, Daniel Fischer, Mark R Sochor, Gregory J Gerling","doi":"10.1109/SIEDS.2013.6549522","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549522","url":null,"abstract":"Hip dislocations are rare events. As a consequence, medical residents have little opportunity to gain experience through repeated practice. In fact, little is known about the forces and displacements that experienced physicians employ during the procedure. This study seeks to quantify the strategic maneuvering and substantial force required to reposition the femoral head into the pelvis during a hip reduction, toward a long-term goal of building a high fidelity training simulator. In particular, the work herein describes the design, construction and evaluation of a custom-built, force and motion measurement system (FMMS). As a physician attempts to relocate the hip, the FMMS measures force about the patient's waist using a seatbelt and inline load cell (4448 N range) and displacement of the dislocated leg with four magnetic displacement sensors (each 6 DOF). Iterations of the system have been tested on cadavers and able-bodied participants, with the current system deployed for collection on hip reduction patients. The results preliminarily indicate that forces at the hip range from 56.8 to 110.8 N, the forces at the leg range from 254.5 to 496.6 N, and that maximum angular movements from the pelvis to the thigh, from the thigh to the knee, and from the knee to the ankle are 80.1, 31.5 and 20.7 degrees, respectively.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121400394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Environmental surveillance modeling: A predictive respiratory alert model for the Shenandoah Valley, Virginia","authors":"Anne E. Hovland, Amanda M. Wagner, Katherine M. Pierce, John E. Drahos, Donald E. Brown","doi":"10.1109/SIEDS.2013.6549513","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549513","url":null,"abstract":"Chronic Obstructive Pulmonary Disease (COPD) is a serious respiratory ailment that affects millions of Americans. Several studies have shown that weather conditions and pollution can increase the occurrence of respiratory distress. The goal of the work described in this paper was to determine if the relationships between environmental variables and admissions rates for COPD were strong enough to enable the development of a surveillance system that could alert the population of potentially hazardous conditions. To conduct this study we obtained data on COPD admissions in the Shenandoah Valley of Virginia, an area of approximately 33,705 km<;sup>2<;/sup>. The data were coded at the zip code level (approximately 250 km<;sup>2<;/sup>). We obtained data for weather variables from 6 monitoring stations and used Kriging to estimate their values at the zip code level. We controlled for the effects of influenza in admission rates, although this required smoothing methods to impute missing values. We also controlled for different types of land use. To predict COPD admissions we developed three types of models: generalized linear models (GLM), multivariate adaptive regression splines (MARS), and random forests. All models showed that temperature or season was a significant (p <; 0.05) predictor for COPD admissions. In terms of predictive accuracy the random forest model provided the best performance measured by the receiver operations characteristic (ROC) and can provide the basis for strategic planning rather than tactical alerting.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122318118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Start with the discovery: Improving capacity factors analysis with the appreciative inquiry approach","authors":"Siddhartha Pailla, C. Pruitt","doi":"10.1109/SIEDS.2013.6549518","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549518","url":null,"abstract":"Several decision-aid frameworks attempt to provide an optimal solution to the complex, challenging problem of delivering water supply and sanitation services to communities in need. However, a failure in proper needs assessment or handoff causes systemic failure of an installed system. Capacity factors analysis (CFA) is one such framework that focuses on personalized technology-specific alternative recommendations; and it faces similar challenges. While helpful in many ways, designers using CFA still make critical assumptions with regards to community's expressed needs and only passively include the community members in the design process. Appreciative inquiry (AI) is introduced as a means to bridge this gap and increase community empowerment. The AI approach is a four-phase process: discovery, dream, design, and destiny. The process starts with asking community members about their strengths and capabilities, follows with their vision of the community, creates a space for collaborative design, and ends with implementation. A service-learning experience in Tshapasha is provided to demonstrate AI's benefits. The results are compared to a CFA-focused study of Tshapasha from 2011.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125204571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personalized Electronic Health Record System for Monitoring Patients with Chronic Disease","authors":"I. A. Khan","doi":"10.1109/SIEDS.2013.6549505","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549505","url":null,"abstract":"The Personalized Electronic Health Record System for Monitoring Patients with Chronic Disease (PEHRS-MPCD) is designed to permit tracking and monitoring of the symptoms of patients with chronic disease and provide healthcare professionals with data on patients' lifestyle changes, medication (drug) changes, diet changes and symptom changes. The current method of assessing the symptoms of patients with chronic disease uses an episodic approach that includes phone calls to the patient, paper surveys of health status and on-site examinations. A preventative approach that can actively involve the patient, monitor multiple conditions and provide real time information about a patient's health condition is proven to be effective in chronic disease care. PEHRS-MPCD is designed to continually monitor patients. The goal of the application is to continuously gain and provide patients' information to themselves and healthcare professionals in-order to improve the efficiency of the diagnosis and timely intervention which would yield better quality of care and quality of life for the patient. This personalized electronic health record system (PEHRS-MPCD) will be objective in providing feedback about patient lifestyle changes and choices, and in channeling this information to healthcare providers. PEHRS-MPCD would (a) allow for relevant data to be entered by the patient, (b) make relevant data available to patient's care provider, at real-time and at doctor's visit, (c) generate reports and graphs for the data and (d) provide secure storage of the data. PEHRS-MPCD is a work in progress as a lot of its functionalities and user interface design are still being amended. This paper describes the purpose, need and design of the application.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121947069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Campus shuttle: Design of a college campus parking and transportation system","authors":"J. Elliott, H. Jayachandran, P. Kumar, K. Metzer","doi":"10.1109/SIEDS.2013.6549502","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549502","url":null,"abstract":"George Mason University is a commuter campus in Fairfax, VA. To meet forecast growth, parking lots are being removed to make space for classroom buildings. The loss of parking slots requires either additional parking garages or mass-transit shuttles to make up for the loss in parking spaces. There are also concerns about traffic congestion and emissions caused by the college's commuters. The Fairfax campus population is predominantly made up of commuters, with 77% of the population living off campus, a vast majority of which drive single occupant vehicles (SOV) to campus due to poor access to mass transit. At present, the GMU Fairfax campus has a parking utilization of 86%, leaving a surplus of approximately 900 parking spaces. Fairfax campus is predicted to start having a parking deficit sometime between 2014 and 2015. Projections out to 2020 show a deficit of 3,800 spaces. To counter that deficit, more than 10,600 current commuters would need to switch from SOV transportation to alternate forms of transit. A reduction of SOV commuters would also lead to lower CO2 emissions from the Fairfax campus. This paper describes the design of a system for addressing transportation and parking demand. This has 3 major parts: (1) identifying surrounding areas of significant Fairfax commuter populations; (2) the ability to predict ridership if a shuttle stop were to be placed in any of those areas by using a decision support tool (DST); and (3) a utility analysis (CO2, parking, and cost) of creating shuttle routes or garages to meet parking needs. In order for GMU to continue growing, both commuter shuttles and parking garages will be needed. If four additional routes are added, GMU can continue to grow through 2016 with a parking utilization of 96%. To continue growth beyond that point will require additional parking garages or bus routes.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":"65 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115654808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of a small-scale biodiesel production system","authors":"J. Anderson, J. Cáceres, A. Khazaei, J. Shirey","doi":"10.1109/SIEDS.2013.6549517","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549517","url":null,"abstract":"The city of Fredericksburg is located in central Virginia and is home to 592 farms covering 16% of the total land area. Farms in this region have experienced declining profits from an average of $555 per farm in 1997 to -$14,931 per farm in 2007. One of the ways to reduce operating costs and return to profitability is to significantly reduce diesel costs. An alternative to purchasing diesel is to produce biodiesel from vegetable oil extracted from crops grown on the farm and sell the excess biodiesel that is not used. The goal of this paper is to design the process and evaluate the financial feasibility of converting farm crops into biodiesel using a small-scale biodiesel production facility on a farm. Five crops were selected as design alternatives based on regional availability, productivity, and cost criteria: Canola, Corn, Peanut, Soybean, and Sunflower. These alternatives were evaluated using two Monte Carlo models: (1) a Biodiesel Production Model to simulate the amount of biodiesel and other byproducts produced and (2) a Business Model to simulate the net present value of each alternative after 15 years. The biodiesel production model inputs are: (i) expected crop yield, (ii) oil content percentage, and (iii) oil press efficiency percentage. The outputs of this model are: (i) biodiesel yield, (ii) meal yield, (iii) glycerin yield, and (iv) net energy ratio; each of the yield outputs is an input for the financial model. Other inputs for the financial model include meal revenue, equipment costs, chemical expenses, planting and harvesting costs, lost profit cost, and biodiesel sales. The output is the net present value of each crop alternative at the end of 15 years. Utility of each crop alternative from first to last is as follows: Peanut (1.0), Sunflower (0.68), Canola (0.55), Soybean (0.52), and Corn (0.45). Plotting utility against net present value shows that Canola is the most cost-effective alternative and the recommended crop type.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116414552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Redesigning clinic workflows for electronic medical record integration","authors":"M. Brindisi, R. Bui, J. Mazo, Z. Y. Ong, S. V. van Vleet, R. Bailey","doi":"10.1109/SIEDS.2013.6549507","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549507","url":null,"abstract":"Electronic medical records (EMR) play a critical role in modern healthcare infrastructure, serving as the fundamental source of patient medical data. These medical records can function variously as a comprehensive record of past visits, a tool to aid physicians' diagnoses, a system to manage operational details during a patient visit, and an effective and accurate billing mechanism for insurance plans. In 2010, the University of Virginia (U.Va.) Medical Center adopted EpicCare EMR across its hospital and one-hundred and seventy-two ambulatory clinics to deliver higher quality patient care. With a focus on three U.Va. Orthopedics division clinics, this project seeks to characterize the current workflows involving EpicCare, identify opportunities for improvement, and evaluate and recommend a strategy for improving clinic operations. The iterative approach encompassed observations in each target clinic, discussions with employees and administration, and visualizations of the workflows for each clinic. Observation results were synthesized into findings, and related back to defined core objectives. Workflow variance, both within and among clinics, was analyzed to ultimately determine the best method to complete tasks common to all clinics. These tasks were further examined to determine if variability could be changed, whether this change could be beneficial, and the root cause of the variability. Alternatives for mitigating variability and improving the employee workflow across all clinics within U.Va. Orthopedics were generated, addressing each task with specific, tailored solutions. These alternatives can be evaluated according to identified metrics, based on feasibility and projected benefit.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131818819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detecting and mitigating driver distraction with motion capture technology: Distracted driving warning system","authors":"S. L. Gallahan, G. F. Golzar, A. P. Jain, A. Samay, T. J. Trerotola, J. G. Weisskopf, N. Lau","doi":"10.1109/SIEDS.2013.6549497","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549497","url":null,"abstract":"Distracted driving contributes to a significant portion of vehicle accidents and deaths. To mitigate distracted driving, the University of Virginia Center to Promote Effective Youth Development sponsored the development of a noninvasive system to detect and warn drivers of their distraction. This distracted driving warning system is installed in the medium-fidelity driving simulator of the Virginia Driving Safety Laboratory (VDSL). The system is composed of (i) the Microsoft Kinect motion sensing hardware for tracking head and skeletal movements and (ii) a custom software application for identifying four distractions and outputting audio alerts. The system is able to identify (a) reaching for a moving object, (b) talking on a cell phone, (c) personal hygiene, and (d) looking at an external object. To recognize these distractions, the algorithms for (a), (b), and (c) use the relative distances between spatial locations of various skeletal joints, and the algorithm for (d) use the yaw, pitch and roll of the head. The system deems the driver distracted if any of these gestures are sustained for more than two seconds. When the driver is deemed distracted, the system produces audio signals that increase in frequency as the time of the distraction increases, alerting the drivers of their distraction. The distracted driving warning system is tested with three participants performing distracted behaviors while driving the VDSL simulator. The system correctly identifies (a) at 100%, (b) at 33%, (c) at 50%, and (d) at 66%. These success rates show the feasibility of employing the Kinect to identify driver distraction. However, the system can improve with refining motion capture and eye tracking technology for some complex distraction behaviors. The application of commercially available motion capture technology appears promising for studying and monitoring driver behavior related to distraction.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131701733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk modeling to detect weapon production in biological laboratories","authors":"D. Collier, D. Edwards, D. Granados, A. J. Noh, J. Lark","doi":"10.1109/SIEDS.2013.6549510","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549510","url":null,"abstract":"The 2001 United States anthrax attacks raise issues regarding U.S. national security. These attacks bring into question the risk of biological laboratory misuse. This capstone project developed a model that determines whether a given facility could be involved in the production of a biological weapon. The proposed model centers around five laboratory factors that comprehensively evaluate a laboratory and provide insight concerning potential resource exploitation. These factors include materials in the lab, equipment in the lab, electricity usage, abnormal contents in wastewater, and background of laboratory personnel. Each of these factors has an individual model that detects suspicious behavior. A final model combines the results of the individual models above to produce an overall evaluation of the laboratory's threat level.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130434043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of a distributable stereo hearing test package","authors":"B. D. Allen, T. Battu, S. Ganev, L. Gray, B. Harwell, B. Kesser, M. A. Kessler, B. Lancaster, R. Nagel, J. Smith","doi":"10.1109/SIEDS.2013.6549520","DOIUrl":"https://doi.org/10.1109/SIEDS.2013.6549520","url":null,"abstract":"The localization and identification of sounds in background noise are such important auditory processing skills that a significant amount of incompetency may lead to various confusions and learning delays. Through a partnership with James Madison University and the University of Virginia, a unique opportunity exists to test patients before and after a corrected maximal conductive hearing loss in one ear. Patients with congenital aural atresia come to the University of Virginia for surgery that will give them normal hearing. Insurance pays for a pure tone threshold hearing test one month after surgery, but due to cost restrictions, longitudinal follow-up testing is often not performed. However, longitudinal data from follow-up studies is essential for understanding the effectiveness of the surgery. This paper focuses on the design, construction, and testing of a prototype shippable hearing test system for client use and patient testing. The system tests two binaural hearing abilities-the ability to isolate a spatially separated signal from noise and the ability to localize the source of a sound. This work has been performed as a partnership between the Department of Engineering and the Department of Communication Sciences and Disorders at James Madison University. The student team consists of two juniors and four seniors working on their two-year engineering capstone project in the Department of Engineering at James Madison University, as well as a senior studying Audiology & Speech Pathology working on her Honors thesis. This project has followed an engineering design process beginning with collecting customer needs and understanding required specifications and ending with prototype testing and refinement. Validation testing of the prototype testing system was performed with listeners with both normal hearing and with unilateral hearing loss. In initial testing, the RMS localization errors were measured from 19 control listeners with normal hearing and four with complete unilateral hearing loss. There was a significant difference between those listeners with one good ear versus those with two good ears (p=.01, Cohen's D > 1 or `large' effect size). These results provide promise as to the effectiveness of the designed testing package.","PeriodicalId":145808,"journal":{"name":"2013 IEEE Systems and Information Engineering Design Symposium","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121147137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}