Reviewerly/exHarmony huggingface dataset:
Performance Analysis of Various Image Feature Extractor Filters for Pothole Anomaly Classification

Authors:
raw_author_name: Habeeb Bello-Salau
raw_author_name: Adeiza James Onumanyi
raw_author_name: Bashir Olaniyi Sadiq
raw_author_name: Busayo Hadir Adebiyi
raw_author_name: Emmanuel Adewale Adedokun

Abstract: Machine learning (ML) classifiers have lately gained traction in the realm of intelligent transportation systems as a means of enhancing road navigation while also assisting and increasing automotive user safety and comfort. The feature extraction stage, which defines the performance accuracy of the ML classifier, is critical to the success of any ML classifiers used. Nonetheless, the efficacy of various ML feature extractor filters on image data of road surface conditions obtained in a variety of illumination settings is uncertain. Thus, an examination of eight different feature extractor filters, namely Auto colour, Binary filter, Edge Detection, Fuzzy Color Texture Histogram Filter (FCTH), J-PEG Color, Gabor filter, Pyramid of Gradients (PHOG), and Simple Color, for extracting pothole anomalies feature from road surface conditions image data acquired under three environmental scenarios, namely bright, hazy, and dim conditions, prior classification using J48, JRip, and Random Forest ML models. According to the results of the experiments, the auto colour image filter is better suitable for extracting features for categorizing road surface conditions image data in bright light circumstances, with an average classification accuracy of roughly 96%. However, with a classification accuracy of around 74%, the edge detection filter is best suited for extracting features for the classification of road surface conditions image data captured in hazy light circumstances. The autocolor filter, on the other hand, has an accuracy of roughly 87% when it comes to classifying potholes in low-light conditions. These findings are crucial in the selection of feature extraction filters for use by ML classifiers in the development of a robust autonomous pothole detection and classification system for improved navigation on anomalous roads and possible integration into self-driving cars.
Training iterated protocols for distillation of GHZ states with variational quantum algorithms

Authors:
raw_author_name: Áron Rozgonyi
raw_affiliation_string: ELTE Eötvös Loránd University, H-1117 Budapest, Hungary; HUN-REN Wigner Research Centre for Physics, H-1525 Budapest, Hungary
raw_author_name: Gábor Széchenyi
raw_affiliation_string: ELTE Eötvös Loránd University, H-1117 Budapest, Hungary; HUN-REN Wigner Research Centre for Physics, H-1525 Budapest, Hungary
raw_author_name: Orsolya Kálmán
raw_affiliation_string: HUN-REN Wigner Research Centre for Physics, H-1525 Budapest, Hungary
raw_author_name: Tamás Kiss
raw_affiliation_string: HUN-REN Wigner Research Centre for Physics, H-1525 Budapest, Hungary

Abstract: We present optimized distillation schemes for preparing Greenberger-Horne-Zeilinger (GHZ) states. Our approach relies on training variational quantum circuits with white noise affected GHZ states as inputs. Optimizing for a single iteration of the scheme, we find that it is possible to achieve an increased fidelity to the GHZ state, although further iterations decrease the fidelity. The same scheme, acting on coherently distorted pure-state inputs, is effective only in certain special cases. We show that radically different results can be achieved, however, when one optimizes for the output after two iterations of the protocol. In this case, the obtained schemes are more effective in distilling GHZ states from inputs affected by white noise. Moreover, they can also correct several types of coherent pure-state errors.
Predicting the impacts of anthropogenic drivers on management scenarios using Bayesian belief network in the Zeribar freshwater wetland, Iran

Authors:
raw_author_name: Amir Sadoddin
raw_affiliation_string: Department of Watershed Management, Faculty of Rangeland and Watershed Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan 49189-4-3464, Golestan, Iran

Abstract: The Zeribar wetland in Iran’s western city of Marivan provides a valuable foundation for maintaining various aspects of social and cultural life, from water supply to recreational values, as well as for natural habitats. However, its different services have been put under strong anthropogenic pressure and urbanization processes. The present study is a part of ongoing efforts to improve understanding of the anthropogenic factors potential impact on management status of this vulnerable freshwater ecosystem, aiming to provide integrated management strategies using a Bayesian belief network (BBN) approach. A conceptual framework supporting the BBN was designed according to the main determining factors of the wetland’s management including “human-induced factors”, “economic factors and human capital”, “policy context” and “social and cultural issues”. The BBN model was parameterized using different data sources comprising literature review, face-to-face interviews, filed observation, model simulations, and experts’ knowledge. Stakeholders’ feedback on model accuracy and management strategies application was assessed in different workshops with representatives from locals, executives, and scientific communities. The results showed that the two subsystems of “policy context” and “economic factors and human capital” are the most important key factors influencing the target node, wetland management status. Then, fourteen alternative management scenarios (S2- S15) were generated using the improvement in prior probabilities of influencing factors, followed by evaluation and statistical comparison with the output of the current condition as the base-case scenario (S1). Under the S1 scenario, the probability of occurrence of the “Strong” state, in which the wetland is properly protected from anthropogenic disturbances, for the target node of the network was 25.8 %, while the most significant improvement in the wetland management status (66.4%) was observed after an improvement in all influencing variables was adopted (S15), suggesting a significant potential for improvement in the wetland management. According to the stakeholders’ feedback, the constructed BBN model, and the components included in the management scenarios are useful to fill a critical gap in the current management framework. The results of this work can assist decision-makers in managing the wetland more effectively by considering all socio-economic and anthropogenic dynamics.
Changing the Landscape of the Digital Workforce and DEI: A Call to Action for Engineering Education

Authors:
raw_author_name: Janis Terpenny
raw_affiliation_string: National Science Foundation

Abstract: Abstract Digital transformation has been implemented across a wide range of industries. Advanced technologies (e.g., artificial intelligence, robotics, cloud, internet of things etc.) and data are used to digitally connect organizations, automate processes, and represent each aspect of complex systems, products, and services. While digital transformation has changed the landscape of the engineering workforce, engineering programs of today remain largely based on 20th-century needs. Due to the interdisciplinary nature and interconnectedness of digital transformation, the traditionally siloed engineering disciplines require innovation to keep pace with the workforce demands. This paper explores the digital transformation workforce demands and digital competencies that are needed now and for the future of the engineering workforce. These skills extend beyond the technical, but also encompass social, emotional, and higher cognitive skills. Further, digital transformation will have tremendous impact on diverse communities - with the opportunity to either create access or create further disparity due to access to engineering education and opportunities beyond. The paper also reports on the experiences and advice of participants in the invited panel that was held at the 2023 ASEE Southeastern Regional Conference where panelists addressed the need to modernize engineering education in the era of Digital Transformation and the strategies they envision or have implemented to address opportunities and risks for diversity, equity, and inclusion.
Creation of a Mobile Science and Engineering Road Show for Texas A&amp;M University at Qatar: Multicultural STEM Education and Entertainment (Resource Exchange)

Authors:
raw_author_name: G. Cieslinski
raw_affiliation_string: Texas A&M University at Qatar
raw_author_name: Tala Katbeh
raw_affiliation_string: Texas A&M University at Qatar

Abstract: Abstract While active learning environments within pre-college have become increasingly common, the impact and novelty of the science demonstration cannot be overlooked. For many students, the spectacle of a well-presented science demo, full of gratuitous sparkle and showmanship, is the catalyst that creates initial interest in chemistry, physics, and engineering. Demonstrations can never supplant active learning or cumulative lessons, but they can act as reinforcement in situations where hands-on learning is still in its infancy. The educational systems of Qatar have undergone radical changes in the past twenty years with a rapidly expanding population, influx of international school systems, and an increased focus on teacher training and modern pedagogical ideas. But many of Qatar's students, for a variety of reasons, had no exposure to classroom demonstrations or laboratory experiments to be able to witness scientific phenomena. Texas A&M University at Qatar created the Science and Engineering Road Show to mediate these issues. Based upon the successful Chemistry Road Show and the Physics Festival at Texas A&M University in College Station, USA, the Road Show has performed demonstrations since 2017, traveling across Qatar reaching out to over 25,000 students. A wide variety of topics related to chemistry, physics, and engineering are discovered using audience participation and eye-catching approaches. As part of the Road Show, comprehensive risk assessments, safety and language surveys, and infrastructure methods were created and instituted. Obstacles such as language barriers, gender separation, and cultural differences were resolved via discussions and planning with multiple stakeholders across schools, ministries, and corporate sponsors. The Road Show has become a national institution; invited to schools, public events, and festivals to educate and entertain Qatar children and families. Details regarding the preparation, planning, safety aspects, and organizational structure of such a mobile demonstration platform are included in this paper as a model for others to start their own local road show.
Shifting Identity Trajectories within a Scholarship Program: Local Community Practices that Shape Computing Careers

Authors:
raw_author_name: Sarah Hug
raw_affiliation_string: Colorado Evaluation & Research Consulting

Abstract: Abstract As computer science seeks to diversify, the act of becoming in computing will be an important avenue of investigation, and the connections students make to specific careers in the field may support identity development that moves beyond the role of student towards future professional identities. This study is part of a three-year multi-method study of a program serving students in a rural computer science department at a Hispanic Serving Institution. The situative learning theory was employed to understand whether and how students developed interest and agency in a cybersecurity career path as they participate in a federally funded scholarship program for high achieving low income students. Evidence from the case study suggest that structured, mandatory participation in competitions fueled interest in cybersecurity, as did regular opportunities to discuss contemporary events in the field with students across grade levels and professional interests. Access to a national conference with a hackathon as well as a career fair supported career pathways in the field—the iterative nature of the participation in competitions and conferences gave an opportunity to see growth over time in cybersecurity. The study of community practices and discursive language development may support other educators intending to develop career-focused co-curricular activities that emphasize mutual engagement with other students across grade levels and intent on a joint enterprise, or shared goal. With time and through engagement with more capable peers, students in the study developed shared repertoires of technical language and technical skill specific to a potential career. Focusing on cybersecurity as a subfield shifted the emphasis of identity from one of major choice to one of future possibilities and connection to career. This shift may support future identity work in other subfields of computing, as well as in other elements of computing education, such as graduate study.
Sense of Belonging in the Cybersecurity Field of Study

Authors:
raw_author_name: Katerina Goseva-Popstojanova
raw_affiliation_string: West Virginia University

Abstract: Abstract ABSTRACT Because cybersecurity professionals are crucial to increased and continuing national security, public safety, and economic prosperity, employment opportunities in cybersecurity continue to increase. To meet the public and private sectors' need for cybersecurity professionals, universities are adding academic programs in Cybersecurity. One large, mid-Atlantic, land-grant R1 University with a vibrant cybersecurity program that offers a B.S. degree, academic minor, and an Area of Emphasis in Cybersecurity has received an NSF S-STEM grant to increase the number and diversity of highly qualified cybersecurity graduates by offering scholarships to high-achieving and economically challenged undergraduate students. Past research has focused on grit and motivation of the NSF S-STEM scholars from this initiative, their retention and persistence through their educational program, and what elements of the S-STEM program they found most helpful in supporting their development as cybersecurity professionals [1]. This research explores evidence of cybersecurity students' feelings of inclusion or sense of belonging within their major. Because many of the benefits of the NSF S-STEM program are available to all cybersecurity professionals, we will consider the level of engagement of all cybersecurity students and the effect of that engagement on an indication of their sense of belonging. This research is important because sense of belonging is one characteristic that has been linked with increased retention [2] – and lack of sense of belonging has been linked with attrition – within many STEM majors, which struggle to serve a student body that is as diverse as the broader population of college-age people in the U.S. [3]. References [1] Paper presented at the2022 ASEE Annual Conference at the 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. [2] Sophia Krause-Levy, William G. Griswold, Leo Porter, and Christine Alvarado. 2021. The Relationship Between Sense of Belonging and Student Outcomes in CS1 and Beyond. In Proceedings of the 17th ACM Conference on International Computing Education Research (ICER 2021), August 16–19, 2021, Virtual Event, USA. ACM, New York, NY, USA 13 Pages. https://doi.org/10.1145/3446871.3469748 [3] The STEM Labor Force of Today: Scientists, Engineers, and Skilled Technical Workers. National Science Foundation and National Science Board, Science & Engineering Indicators. August 2021. https://ncses.nsf.gov/pubs/nsb20212/participation-of-demographic-groups-in-stem. Accessed 11.16..2022.
Application of Product Lifecycle Management in the University Classroom and Laboratory

Authors:
raw_author_name: John Wagner
raw_affiliation_string: Clemson University

Abstract: Abstract Despite widespread acknowledgement of PLM technologies' pivotal role in supporting modern industry, undergraduate STEM programs often struggle to include instruction on PLM topics due to the difficulty of covering the preponderance of discipline-specific concepts inherent in traditional curricula within the allocated credit hours. This paper discusses the establishment and operation of a new center at with directives to prepare collegiate students in utilizing PLM technologies through a variety of extracurricular activities and PLM resources. These include short-course lectures, guided software workshops, semester-length projects, support for research activities, and provision of PLM software in an open-access computer lab. To access the effectiveness of these educational efforts, the analysis of student surveys can help to tailor the activities to better meet learning needs. This model of supporting traditional curricula with extracurricular activities shows potential in preparing students for career roles driven by modern, digital processes.
A Literature Review to Explore a Relationship: Empathy and Empathy and Mindfulness in Design Education

Authors:
raw_author_name: Diana Bairaktarova
raw_affiliation_string: Virginia Tech

Abstract: Abstract Learning to design in undergraduate engineering is a higher-order mentality that entails creative, conceptual, and methodological capabilities. One of the core principles of design thinking is its focus on human values at every stage of the process, including empathy for the eventual recipients or users of the tangible outcomes of the designs. Learning to be empathetic has a wide range of benefits, such as supporting effective teamwork and communication; supporting ethical decision-making; and informing the design process. The existing literature provides not enough guidance on how to foster empathy in undergraduate engineering programs, despite the recognized benefits. However, a growing body of research on the benefits of mindfulness has begun to show its potential as an intervention strategy to improve empathy in design. In this theory/method paper, we present an extended review that explores the relationship between how empathy may be supported through mindfulness practice. Based on the content of the studies, we organized publications in terms of the research focus. While some reported on the relationship between empathy and mindfulness practice, other publications focused on specific effects on individuals. These specific effects clustered around three major groups important to design education: (1) transition between analytical and affective mindsets (2) subjective understanding of the profession by focusing the mind on how we conceptualize engineering expectations, and (3) increased behaviors to support sustainability mindsets. Through our extended literature review on these topics, we suggest that promoting mindfulness practice in engineering design courses, workplaces and elsewhere encourages whole-bodied processes in professional decision-making and empathetic designs. Keywords: empathy, mindfulness, engineering design
New Course Development for Internet of Things

Authors:
raw_author_name: Yanxiao Zhao
raw_affiliation_string: Virginia Commonwealth University
raw_author_name: Shaobo Huang
raw_affiliation_string: University of Saskatchewan
raw_author_name: Carl Elks
raw_affiliation_string: Virginia Commonwealth University
raw_author_name: Umit Ozgur
raw_affiliation_string: Virginia Commonwealth University
raw_author_name: Vitaliy Avrutin
raw_affiliation_string: Virginia Commonwealth University

Abstract: Abstract IoT is a fast growing technology sector that is estimated to be valued at 100's of billions in US dollars for 2023. The number of IoT connected devices is growing at an annual rate of 20%/year with billions of devices connected. Accordingly, there is much need for foundational IoT engineering courses in our educational institutions to prepare engineers for this technology sector. The challenge for course developers is that IoT technical foundations are exceedingly broad - ranging from smart sensors to low power computing to cloud infrastructure. Most universities focus on one or two aspects of IoT technical foundations, specifically those associated with the computing aspects of IoT. We have developed a novel approach for an IoT course by segmenting the course into three fundamental technology areas. These areas are respectively (1) foundations of sensing, (2) IoT communication and networking, and (3) IoT computing models and architectures. Each module is taught by a different professor with technical expertise in that module. This paper will focus on course objectives, design, and outcomes. We use the Module 2 IoT communication and networking as an example of the type of content. In this module, we cover fundamental knowledge of networking including layered-architecture, protocols, wireless communication and propagation. Then we introduce two common communication protocols, i.e., Hypertext Transfer Protocol (HTTP) and Message Queuing Telemetry Transport (MQTT), which are widely used for IoT systems. Further, Node.js programming is taught and students learned how to use node.js for HTTP and MQTT implementation. Hands-on experiments using Arduino WiFi1010 board and grove sensors are designed to help deepen students' understanding for developing a small-scale IoT system as well. The term project of building an IoT-enabled smart Heating, Ventilation, and Air Conditioning (HVAC) will be introduced. Instructor observations and anecdotal student feedback on the course design and delivery are presented as well. Lessons learned will be discussed and modifications are proposed for future improvement.