Computer Information and Graphics Technology Works

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A Computationally Effective Pedestrian Detection using Constrained Fusion with Body Parts for Autonomous Driving
(IEEE, 2021) Islam, Muhammad Mobaidul; Newaz, Abdullah Al Redwan; Tian, Renran; Homaifar, Abdollah; Karimoddini, Ali; Computer Information and Graphics Technology, School of Engineering and Technology
This paper addresses the problem of detecting pedestrians using an enhanced object detection method. In particular, the paper considers the occluded pedestrian detection problem in autonomous driving scenarios where the balance of performance between accuracy and speed is crucial. Existing works focus on learning representations of unique persons independent of body parts semantics. To achieve a real-time performance along with robust detection, we introduce a body parts based pedestrian detection architecture where body parts are fused through a computationally effective constraint optimization technique. We demonstrate that our method significantly improves detection accuracy while adding negligible runtime overhead. We evaluate our method using a real-world dataset. Experimental results show that the proposed method outperforms existing pedestrian detection methods.
Incorporating Global Learning Perspectives in a Freshman Computing Curriculum
(IEEE, 2022-10-11) Mithun, Shamima; Goldfarb, Nancy; Computer Information and Graphics Technology, School of Engineering and Technology
This research-to-practice full paper describes our integration of global learning perspectives through a research-based group project in a First-Year Seminar course for new technology major students at our urban Midwestern university, IUPUI (Indiana University - Purdue University Indianapolis). Since 2003, the ACE (American Council on Education) has emphasized global competencies, which are defined as "the attitudes, skills, and knowledge to live and work in a multicultural and interconnected world". Despite the increasing recognition of the importance of developing these global competencies, opportunities for young people to do so suffer from issues of accessibility. Educational institutions are challenged with providing opportunities to prepare students for global citizenship in the twenty-first century and are working to expand global competency education. Our undergraduate institution is no exception.In accordance with this mission, we incorporated global learning perspectives through a group project in our First-Year-Seminar course to increase students’ interest in global learning experiences (such as studying abroad) and provide resources for students to develop global competencies. This is important both for personal development in the quest for a more equitable world and employability; employers repeatedly convey that awareness of global issues is a highly desirable characteristic in potential hires.In our implementation, students selected a global issue, chosen from the United Nations Sustainable Development Goals database, which had unique significance to them and their communities. This approach allowed space for students to take ownership and agency over the content of their learning experiences while ensuring they engaged with the following learning objectives: 1)Team collaboration, communication, and cohesion 2)Conducting independent research on a global problem and its solutions 3)Synthesis of information from multiple sources and perspectives to develop an informed stance 4)Developing a stance regarding a global problem and justification of this stance using data 5)Creating a well-organized deliverable with consideration for the audience (i.e., their peers) and contextWe point to course survey data and student reflections to evaluate our course. Students conveyed how the course structure enabled them to (a) consider global perspectives around issues that may or may not have been salient to them before the course, (b) experience empathy for people experiencing challenges related to the issues of interest and gratitude for their circumstances, and (c) consider their personal role in addressing global issues in their communities. Students also indicated an interest in further addressing such issues through self-education and advocacy on a community and political scale.To further expand efforts to make global competency education accessible, our next implementation will utilize Collaborative Online International Learning experiences in which students virtually collaborate with students outside of the United States through our local Office of International Affairs. Through these collaborations, students will be challenged to consider how such global issues manifest in different communities, cultures, and geographic regions and the implications of these differences for solution design.
Hands-Free Electronic Documentation in Emergency Care Work Through Smart Glasses
(Springer, 2022-02) Zhang, Zhan; Luo, Xiao; Harris, Richard; George, Susanna; Finkelstein, Jack; Computer Information and Graphics Technology, School of Engineering and Technology
As U.S. healthcare system moves towards digitization, Electronic Health Records (EHRs) are increasingly adopted by medical providers. However, EHR documentation is not only time-consuming but also difficult to complete in real-time, leading to delayed, missing, or erroneous data entry. This challenge is more evident in time-critical and hands-busy clinical domains, such as Emergency Medical Services (EMS). In recent years, smart glasses have gained momentum in supporting various aspects of clinical care. However, limited research has examined the potential of smart glasses in automating electronic documentation during fast-paced medical work. In this paper, we report the design, development, and preliminary evaluations of a novel system combining smart glasses and EHRs and leveraging natural language processing (NLP) techniques to enable hands-free, real-time documentation in the context of EMS care. Although optimization is needed, our system prototype represents a substantive departure from the status quo in the documentation technology for emergency care providers, and has a high potential to enable real-time documentation while accounting for care providers’ cognitive and physical constraints imposed by the time-critical medical environment.
Flipped Instructional Design Factors in an Introductory and an Advanced Data Science Course
(ASEE, 2022-06) Mithun, Shamima; Vickery, Morgan; Luo, Xiao; Computer Information and Graphics Technology, School of Engineering and Technology
In this full research paper, we evaluate the flipped instructional designs of two undergraduate data science courses at a Midwestern university: an introductory course on database fundamentals and an advanced database design course. This study is built upon our prior work in which we identified a set of eight instructional design factors for effective flipped classrooms in the literature and assessed their efficacy with senior students. Our analysis relies on students’ course evaluations, self-reported survey data, focus group responses, course performance data, and instructor observation data to answer the following research questions: 1. How do the eight instructional design factors for effective flipped classrooms serve novice versus advanced data science students? 2. How should instruction in flipped classrooms be varied for novice versus advanced data science students? Our analysis indicates that novice data science students have different instructional needs and challenges compared to their senior peers, particularly in relation to activities that require peer collaboration and were unmoderated by the instructor. We share the results of our quantitative analysis of self-reported survey data in which students ranked the aforementioned instructional design factors based on their effectiveness for their learning and qualitative analysis which takes student comments (from a free-response survey and focus group data) and instructor observation data to contextualize these rankings and inform our instructional design recommendations. These recommendations address students differing academic and interactional needs within the classroom and are to be implemented within the introductory course in its next iteration: (a) group norming and standardization around expectations for communication/collaboration, (b) transparent disclosure of the learning objectives for each activity, (c) offering guidelines to support students in providing actionable peer feedback, and (d) introducing low-stakes peer evaluations. We conclude with a discussion on the general affordances of the flipped classroom model for both introductory and advanced data science instruction compared to traditional lecture-based approaches.
Novice Versus Advanced Undergraduate Computing Students’ Engagement in Collaboration in an Online Flipped Classroom
(International Society of the Learning Sciences, 2022) Vickery, Morgan; Mithun, Shamima; Computer Information and Graphics Technology, School of Engineering and Technology
This paper explores students' engagement in collaborative learning activities within two data science courses (one introductory and one advanced) taught synchronously online during the 2020-2021 academic year. Here, we draw on a multidimensional perspective of student engagement to understand novice and advanced computing students' collaborative learning practices and propose instructional design elements informed by students’ unique needs and the limitations of the virtual format.
Electronic Co-design (ECO-design) Workshop for Increasing Clinician Participation in the Design of Health Services Interventions: Participatory Design Approach
(JMIR Publications, 2022-09-22) Savoy, April; Patel, Himalaya; Shahid, Umber; Offner, Alexis D.; Singh, Hardeep; Giardina, Traber D.; Meyer, Ashley N.D.
Background: Participation from clinician stakeholders can improve the design and implementation of health care interventions. Participatory design methods, especially co-design methods, comprise stakeholder-led design activities that are time-consuming. Competing work demands and increasing workloads make clinicians' commitments to typical participatory methods even harder. The COVID-19 pandemic further exacerbated barriers to clinician participation in such interventions. Objective: The aim of this study was to explore a web-based participatory design approach to conduct economical, electronic co-design (ECO-design) workshops with primary care clinicians. Methods: We adapted traditional in-person co-design workshops to web-based delivery and adapted co-design workshop series to fit within a single 1-hour session. We applied the ECO-design workshop approach to codevelop feedback interventions regarding abnormal test result follow-up in primary care. We conducted ECO-design workshops with primary care clinicians at a medical center in Southern Texas, using videoconferencing software. Each workshop focused on one of three types of feedback interventions: conversation guide, email template, and dashboard prototype. We paired electronic materials and software features to facilitate participant interactions, prototyping, and data collection. The workshop protocol included four main activities: problem identification, solution generation, prototyping, and debriefing. Two facilitators were assigned to each workshop and one researcher resolved technical problems. After the workshops, our research team met to debrief and evaluate workshops. Results: A total of 28 primary care clinicians participated in our ECO-design workshops. We completed 4 parallel workshops, each with 5-10 participants. We conducted traditional analyses and generated a clinician persona (ie, representative description) and user interface prototypes. We also formulated recommendations for future ECO-design workshop recruitment, technology, facilitation, and data collection. Overall, our adapted workshops successfully enabled primary care clinicians to participate without increasing their workload, even during a pandemic. Conclusions: ECO-design workshops are viable, economical alternatives to traditional approaches. This approach fills a need for efficient methods to involve busy clinicians in the design of health care interventions.
Electronic Health Records’ Support for Primary Care Physicians’ Situation Awareness: A Metanarrative Review
(Sage, 2023) Savoy, April; Patel, Himalaya; Murphy, Daniel R.; Meyer, Ashley N.D.; Herout, Jennifer; Singh, Hardeep
Objective: Situation awareness (SA) refers to people's perception and understanding of their dynamic environment. In primary care, reduced SA among physicians increases errors in clinical decision-making and, correspondingly, patients' risk of experiencing adverse outcomes. Our objective was to understand the extent to which electronic health records (EHRs) support primary care physicians (PCPs)' SA during clinical decision-making. Method: We conducted a metanarrative review of papers in selected academic databases, including CINAHL and MEDLINE. Eligible studies included original peer-reviewed research published between January 2012 and August 2020 on PCP-EHR interactions. We iteratively queried, screened, and summarized literature focused on EHRs supporting PCPs' clinical decision-making and care management for adults. Then, we mapped findings to an established SA framework to classify external factors (individual, task, and system) affecting PCPs' levels of SA (1-Perception, 2-Comprehension, and 3-Projection) and identified SA barriers. Results: From 1504 articles identified, we included and synthesized 19 studies. Study designs were largely noninterventional. Studies described EHR workflow misalignments, usability issues, and communication challenges. EHR information, including lab results and care plans, was characterized as incomplete, untimely, or irrelevant. Unmet information needs made it difficult for PCPs to obtain even basic SA, Level 1 SA. Prevalent barriers to PCPs developing SA with EHRs were errant mental models, attentional tunneling, and data overload. Conclusion: Based on our review, EHRs do not support the development of higher levels of SA among PCPs. Review findings suggest SA-oriented design processes for health information technology could improve PCPs' SA, satisfaction, and decision-making.
A Practical Approach to Learner Experience Design
(2022) Schnepp, Jerry; Rogers, Christian; Computer Information and Graphics Technology, School of Engineering and Technology
Educators face the challenge of continually adapting and evolving their pedagogy to meet the needs of diverse learners. Learner experience design (LX) is a human-centered approach to curriculum and assessment development that is easily learned, adaptable, and repeatable. It focuses on empathy for students and creative problem-solving. In this work, we present an overview of LX and identify its usefulness to faculty in higher education. We proceed to describe a practical set of steps that teachers can follow to gain empathy for their students, identify important insights, and ideate creative solutions that can be implemented quickly, evaluated, and iteratively refined.
X-Composer: Enabling Cross-Environments In-SituWorkflows between HPC and Cloud
(ACM, 2021-07) Li, Feng; Wang, Dali; Yan, Feng; Song, Fengguang; Computer Information and Graphics Technology, School of Engineering and Technology
As large-scale scientific simulations and big data analyses become more popular, it is increasingly more expensive to store huge amounts of raw simulation results to perform post-analysis. To minimize the expensive data I/O, "in-situ" analysis is a promising approach, where data analysis applications analyze the simulation generated data on the fly without storing it first. However, it is challenging to organize, transform, and transport data at scales between two semantically different ecosystems due to the distinct software and hardware difference. To tackle these challenges, we design and implement the X-Composer framework. X-Composer connects cross-ecosystem applications to form an "in-situ" scientific workflow, and provides a unified approach and recipe for supporting such hybrid in-situ workflows on distributed heterogeneous resources. X-Composer reorganizes simulation data as continuous data streams and feeds them seamlessly into the Cloud-based stream processing services to minimize I/O overheads. For evaluation, we use X-Composer to set up and execute a cross-ecosystem workflow, which consists of a parallel Computational Fluid Dynamics simulation running on HPC, and a distributed Dynamic Mode Decomposition analysis application running on Cloud. Our experimental results show that X-Composer can seamlessly couple HPC and Big Data jobs in their own native environments, achieve good scalability, and provide high-fidelity analytics for ongoing simulations in real-time.
Analyzing the symptoms in colorectal and breast cancer patients with or without type 2 diabetes using EHR data
(Sage, 2021) Luo, Xiao; Storey, Susan; Gandhi, Priyanka; Zhang, Zuoyi; Metzger, Megan; Huang, Kun; Computer Information and Graphics Technology, School of Engineering and Technology
This research extracted patient-reported symptoms from free-text EHR notes of colorectal and breast cancer patients and studied the correlation of the symptoms with comorbid type 2 diabetes, race, and smoking status. An NLP framework was developed first to use UMLS MetaMap to extract all symptom terms from the 366,398 EHR clinical notes of 1694 colorectal cancer (CRC) patients and 3458 breast cancer (BC) patients. Semantic analysis and clustering algorithms were then developed to categorize all the relevant symptoms into eight symptom clusters defined by seed terms. After all the relevant symptoms were extracted from the EHR clinical notes, the frequency of the symptoms reported from colorectal cancer (CRC) and breast cancer (BC) patients over three time-periods post-chemotherapy was calculated. Logistic regression (LR) was performed with each symptom cluster as the response variable while controlling for diabetes, race, and smoking status. The results show that the CRC and BC patients with Type 2 Diabetes (T2D) were more likely to report symptoms than CRC and BC without T2D over three time-periods in the cancer trajectory. We also found that current smokers were more likely to report anxiety (CRC, BC), neuropathic symptoms (CRC, BC), anxiety (BC), and depression (BC) than non-smokers.

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