2021 Systems and Information Engineering Design Symposium (SIEDS)最新文献

{"title":"Effects of Access to Mental Health Services Following Release from Custody","authors":"Nathaniel Donkoh-Moore, Madeline McNult, G. Boland, Patrick Leonard, Colin Y. Cool, Neal Goodloe, L. P. Alonzi, K. P. White, Michael C. Smith","doi":"10.1109/SIEDS52267.2021.9483772","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483772","url":null,"abstract":"About a third of current inmates in the United States prisons and jails suffer from severe mental illness (Collier, 2014). For most of these inmates, their untreated mental health needs contribute to their return to custody within the criminal justice system. A 2011 study reported that approximately 68% of inmates with an untreated mental illness and substance abuse diagnoses return to custody at least once within 4 years of the initial release, compared to 60% of those who do not suffer from either mental illness or substance abuse diagnoses (Bronson et al., 2017). This project extends over a decade of prior research examining current mental health services available to those released from the Albemarle-Charlottesville Regional Jail (ACRJ). The primary objective of this project was to identify individuals within the ACRJ, which serves jurisdictions in Charlottesville, Albemarle, and Nelson County who were recommended for services following screening through the Brief Jail Mental Health Screener (BJMHS) to answer questions surrounding the return to custody rate of those linked vs not linked to services.To examine the demographics of inmates screened, types of charges, and length of stay in the criminal justice system, data sets were obtained from Region Ten Community Services Board (R10), ACRJ, Offender Aid and Restoration (OAR), and the Thomas Jefferson Area Coalition for the Homeless (TJACH) after each member of the team completed a training on protecting personally identifiable information (PII) and signing a nondisclosure agreement (NDA). The research team analyzed 60 months of data spanning from July 2015 through June 2020. The data include individuals booked into ACRJ and individuals who received mental health, substance abuse, and intake/access/emergency services from R10. The data from ACRJ, the BJMHS, and R10 were merged to form a single data set compiling relevant information for each individual in ACRJ, such as booking details, BJMHS screener scores, and services received from R10.According to the merged data, of the individuals who took the BJMHS when they were booked into ACRJ, 26% screened in, meaning their BJMHS results indicated they should be referred for further mental health evaluation. The team analyzed the cohort of individuals who screened-in and were available to receive services from R10 following their release from custody. The key findings and outcomes of the study included:•From the ACRJ dataset from 2015 to 2019, 913 individuals screened-in for referral to mental health services. This is 26% of the total inmates who were screened at ACRJ.•Individuals who received services from R10 were more likely to return to custody (19%) within 12 months than screened-in individuals who did not receive these services (11%).","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129049397","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 and Implementation of a Vehicular Cloud Real Time System (VCRTS) Using a Fault-Tolerant Approach","authors":"Luther Bell, Puya Ghazizadeh, Samy El-Tawab, Aida Ghazizadeh","doi":"10.1109/SIEDS52267.2021.9483722","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483722","url":null,"abstract":"Vehicular Clouds are inherited from the cloud computing concept. Vehicles standing in a parking lot can corporate computing, sensing, communication, and physical resources. Vehicular Clouds were motivated by the realization that present- day vehicles are equipped with powerful onboard computers, powerful transceivers, and an impressive array of sensing devices. As it turns out, most of the time, the computing, storage, and communication resources available in our vehicles are chronically under-utilized. We are putting these resources to work in a meaningful way to provide computation power, which plays an essential role for service providers, transportation systems, health care, and online education in our modern society. Vehicular Clouds provide computation power to users based on a resource- sharing model. In this model, vehicle owners rent out their onboard computation powers to receive incentives in the form of payments or free parking spots. To use this computation power, there should be a way to submit jobs to the system. In this work, we develop a framework for the vehicular cloud to manage the onboard computation resource of the vehicles and computation tasks that users submit. This framework will be available to users in a software system called Vehicular Cloud Real-Time System (VCRTS). Random arrival and departure of vehicles in vehicular clouds can impact the computation nodes’ availability and lead to an interruption in the computation process. We design and implement the VCRTS based on a fault-tolerant approach to prevent interruption in job execution. Our approach uses a redundancy mechanism to handle the random nature of arrival and departure of the vehicles that are used as computation nodes.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130590674","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":"A Systems Approach to Optimizing Patient Flow During the COVID-19 Pandemic","authors":"Elizabeth Korte, Courtney Laughlin, T. Peters, Lillian Stiles, Robert J. Riggs, Kimberly Dowdell, Karen Measells","doi":"10.1109/SIEDS52267.2021.9483742","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483742","url":null,"abstract":"In 2020, health systems have been affected by the novel coronavirus (COVID-19) pandemic, causing an influx of COVID-19 related visits and a sharp decline in non-emergency and elective visits. To mitigate the spread of COVID-19, healthcare systems – including the University of Virginia Health System – reduced ambulatory visits and implemented various social distancing measures, resulting in a drastic change in the patient admittance process. The focus of this work is to accurately characterize the effect of COVID-19 on one of the UVA Internal Medicine, Primary Care clinics, and where possible, to refine and optimize patient flow through the appointment process while accommodating public health restrictions. To achieve these goals, the team adopted a systems approach, which involves the iterative process of problem identification, analysis, and testing recommendations.The first phase of the project focused primarily on establishment of the current state and problem identification. The appointment process contains six major elements: scheduling, sign-in/remote registration, check-in, rooming, check-out, and telemedicine. Through extensive discussions with the clients, surveys of clinic staff, in-person observation, and data collection and analysis, the capstone team was able to understand the pandemic’s impact on the clinic’s patient flow and identify key problem areas at each stage in the appointment process. The team then used these insights to develop informed recommendations for these pain points. The second phase of the project consisted of formulating trials within UVA health restrictions and guidelines to test the impact of our recommendations. Through a pilot of a new remote registration process, on-time patients increased from 68% to 75%, nurse perceived workload decreased significantly, and the arrival process became more predictable. From this work, the team was able to develop a more generic framework for how health systems might assess and address patient flow issues under normal circumstances as well as during future pandemics.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126307835","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":"The Future of Livestreaming: Strategy and Predictive Analysis for Future Operations of Facebook Live","authors":"Nolan Alexander, David Brenman, John Eshirow, Josh Rosenblatt, Justin Wolter, W. Scherer, James Valeiras","doi":"10.1109/SIEDS52267.2021.9483785","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483785","url":null,"abstract":"Social Network Services (SNS) are systems that allow users to build social relations with one another, with one of the largest SNSs being Facebook, totaling 2.6 billion active monthly users in 2020. Their live streaming service, Facebook Live, is one of the fastest-growing branches of the company, allowing creators to synchronously broadcast original content to the public. However, in the rapidly growing world of technology, Facebook Live faces fierce competition from other live streaming platforms (Twitch, YouTube Live, etc.) and well as other video-on-demand providers (Netflix, Hulu, TikTok, etc.). To better understand current issues and future directions, our team focused on the Facebook Live platform, to develop a three to five-year strategic plan for the platform. We focus on Facebook Live’s growth opportunities from a multitude of perspectives, including the competitive landscape, interface modification, future projections based on historical trends, and competitive analysis. Our approach utilizes the systems analysis process, focusing top-down on objectives and metrics. To produce a comprehensive strategy for future operations, we employ analytical methods ranging from quantitative data analysis to qualitative exploration of industry trends. These quantitative methods include statistical analysis, time-series forecasting, and natural language processing. Qualitative methods include domain research into the history, current state, and possible future for live-streaming. Forthcoming, the results for the complete analysis will be synthesized into a multi-recommendation strategic report to provide Facebook with flexible guidance for continuing operations. We also present a comments summarization and visualization feature for viewers and creators, three to five-year market forecasts after COVID-19 lockdowns, and attractive emerging markets including education and morning shows.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126414964","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":"Developing a Criteria-Based Evaluation Tool for User Experience Design that Balances Standardization and Creativity","authors":"E. Hopkins, Jacqueline Mazzeo, Vinh Nguyen, Emma Peck, Kelcie Satterthwaite, Carlos Lidón, G. J. Gerling","doi":"10.1109/SIEDS52267.2021.9483752","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483752","url":null,"abstract":"Design systems are increasing in popularity, created to ensure a consistent aesthetic of graphics and interactions in websites and apps, and guide product development. They tend to include a set of standards, principles, and documentation. Due to their often-rigid requirements on structure and uniformity, traditional design systems can discourage creativity and customization. To forge a balance, the work develops a criteria-based evaluation tool, or ‘scorecard’ for assessing design components that incorporate principles of consistent, standardized practice, yet prioritize creative freedom. The evaluation scorecard allows inconsistencies to be managed in a collaborative and consensus-based manner. Users select parameters and metrics to evaluate the various elements of a design component. The tool calculates a score based on the number of parameters passed or failed. Scores below team-desired thresholds signal a need for further modification or redesign. Usability feedback using talk-aloud and surveys in a focus group format assess the ease of use and efficiency of the tool and identify gaps in functionality.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"244 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122911836","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":"An Analysis and Visualization of Best Practices for Police Data Transparency","authors":"Maria Clara Arango, Andrew P. Hogue, K. Williams","doi":"10.1109/SIEDS52267.2021.9483786","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483786","url":null,"abstract":"The ability to hold police accountable for the actions of officers is contingent upon independent review of data surrounding misconduct. This research identifies gaps in information and useful features to build a guide for policing data collection and analysis for public accountability, based on the practices of other cities around the US. Our primary concern is to obtain actionable and transparent data on police activities and identify recording practices to serve Charlottesville as examples to follow. Prominent challenges include sourcing usable data, judging whether the data were comprehensive, and inconsistencies across datasets that prevented joining, and in turn, limited meaningful data analysis. Our guide also advises Charlottesville of the ethical and methodological considerations when analyzing policing data. The final guide includes: recommendations for sharing data with the public through dashboard visualization, which was informed by a multi-city scrub of open policing data portals; recommendations for feature variables to collect for meaningful analysis; and a multi-city proof-of-concept data dashboard.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"865 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122545461","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":"Fast, Safe, and Proactive Runtime Planning and Control of Autonomous Ground Vehicles in Changing Environments","authors":"Grace Glaubit, Katie Kleeman, N. Law, Jeremiah Thomas, Shijie Gao, Rahul Peddi, Esen Yel, N. Bezzo","doi":"10.1109/SIEDS52267.2021.9483719","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483719","url":null,"abstract":"Autonomous ground vehicles (UGVs) traversing paths in complex environments may have to adapt to changing terrain characteristics, including different friction, inclines, and obstacle configurations. In order to maintain safety, vehicles must make adjustments guided by runtime predictions of future velocities. To this end, we present a neural network-based framework for the proactive planning and control of an autonomous mobile robot navigating through different terrains. Using our approach, the mobile robot continually monitors the environment and the planned path ahead to accurately adjust its speed for successful navigation toward a desired goal. The target speed is selected by optimizing two criteria: (1) minimizing the rate of change between predicted and current vehicle speed and (2) maximizing the speed while staying within a safe distance from the desired path. Additionally, we introduce random noise into the network to model sensor uncertainty and reduce the risk of predicting unsafe speeds. We extensively tested and validated our framework on realistic simulations in Gazebo/ROS with a UGV navigating cluttered environments with different terrain frictions and slopes.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126725258","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":"Context Matrix Methods for Property and Structure Ontology Completion in Wikidata","authors":"J. A. Gómez, Thomas Hartka, B. Liang, Gavin Wiehl","doi":"10.1109/SIEDS52267.2021.9483776","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483776","url":null,"abstract":"Wikidata is a crowd-sourced knowledge base built by the creators of Wikipedia that applies the principles of neutrality and verifiability to data. In its more than eight years of existence, it has grown enormously, although disproportionately. Some areas are well curated and maintained, while many parts of the knowledge base are incomplete or use inconsistent classifications. Therefore, tools are needed that can use the instantiated data to infer and report structural gaps and suggest ways to address these gaps. We propose a context matrix to automatically suggest potential values for properties. This method can be extended to evaluating the ontology represented by knowledge base. In particular, it could be used to propose types and classes, supporting the discovery of ontological relationships that lend conceptual identification to the content entities. To work with the large, unlabelled data set, we first employ a pipeline to shrink the data to a minimal representation without information loss. We then process the data to build a recommendation model using property frequencies. We explore the results of these models in the context of suggesting type classifications in Wikidata and discuss potential extended applications. As a result of this work, we demonstrate approaches to contextualizing recently-added content in the knowledge base as well as proposing new connections for existing content. Finally, these methods could be applied to other knowledge graphs to develop similar completions for the entities contained therein.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"169 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116528842","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":"The Design and Evaluation of User-Interface Prototypes for a Next-Generation Dishwasher Mobile Application","authors":"Soumya Chappidi, Laura Gustad, Alexander Hu, Khin Kyaw, S. L. Riggs","doi":"10.1109/SIEDS52267.2021.9483711","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483711","url":null,"abstract":"Dishwashers have become an integral part of most American households and with the advent of technology, there is an opportunity to integrate smart features such as Wi-Fi connectivity, new user interfaces, and autonomous operation. The focus of our work is to inform the design of a next generation dishwasher. Here we provide research on how the smart technologies may change the paradigm in which users interact with their dishwasher and present an initial mobile prototype based on our research to improve the dishwashing experience. This study included three phases. For phase 1, we gathered data to inform the design of a mobile application prototype that included data information gathering from 31 user interviews, seven user daily-use diary interviews, and 164 questionnaires. For phase 2, we developed a mobile application prototype. For phase 3, we evaluated the mobile application prototype with 10 users. Our results thus far have shown that users are frustrated with the lack of transparency and understanding of all the functions available with their dishwasher, but have positively responded to using a mobile application to improve their understanding of their dishwasher. Overall, we believe that smart technologies have a potential to revolutionize the dishwashing experience; however, we believe that an effective UI design is critical towards that goal.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132396002","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":"Trust and Security of Embedded Smart Devices in Advanced Logistics Systems","authors":"Christopher M. VanYe, Beatrice Li, Andrew T. Koch, Mai N. Luu, Rahman O. Adekunle, Neginsadat Moghadasi, Zachary A. Collier, Thomas L. Polmateer, David Barnes, David L. Slutzky, Mark C. Manasco, J. Lambert","doi":"10.1109/SIEDS52267.2021.9483779","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483779","url":null,"abstract":"This paper addresses security and risk management of hardware and embedded systems across several applications. There are three companies involved in the research. First is an energy technology company that aims to leverage electric- vehicle batteries through vehicle to grid (V2G) services in order to provide energy storage for electric grids. Second is a defense contracting company that provides acquisition support for the DOD's conventional prompt global strike program (CPGS). These systems need protections in their production and supply chains, as well as throughout their system life cycles. Third is a company that deals with trust and security in advanced logistics systems generally. The rise of interconnected devices has led to growth in systems security issues such as privacy, authentication, and secure storage of data. A risk analysis via scenario-based preferences is aided by a literature review and industry experts. The analysis is divided into various sections of Criteria, Initiatives, C-I Assessment, Emergent Conditions (EC), Criteria-Scenario (C-S) relevance and EC Grouping. System success criteria, research initiatives, and risks to the system are compiled. In the C-I Assessment, a rating is assigned to signify the degree to which criteria are addressed by initiatives, including research and development, government programs, industry resources, security countermeasures, education and training, etc. To understand risks of emergent conditions, a list of Potential Scenarios is developed across innovations, environments, missions, populations and workforce behaviors, obsolescence, adversaries, etc. The C-S Relevance rates how the scenarios affect the relevance of the success criteria, including cost, schedule, security, return on investment, and cascading effects. The Emergent Condition Grouping (ECG) collates the emergent conditions with the scenarios. The generated results focus on ranking Initiatives based on their ability to negate the effects of Emergent Conditions, as well as producing a disruption score to compare a Potential Scenario's impacts to the ranking of Initiatives. The results presented in this paper are applicable to the testing and evaluation of security and risk for a variety of embedded smart devices and should be of interest to developers, owners, and operators of critical infrastructure systems.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133581123","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}