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  1. The development of the CS content standards underscores the importance of curricula aligned with the standards, ensuring equitable coverage of CS concepts for all students. Because standards are broad, we emphasize the need for CS curricula to specify not only the standards they align with but also which aspects of the standards they align with and how. We map one common middle school CS curriculum to a few standards to demonstrate this need. 
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    Free, publicly-accessible full text available March 14, 2025
  2. Abstract

    The new wave of Industry 4.0 is transforming manufacturing factories into data-rich environments. This provides an unprecedented opportunity to feed large amounts of sensing data collected from the physical factory into the construction of digital twin (DT) in cyberspace. However, little has been done to fully utilize the DT technology to improve the smartness and autonomous levels of small and medium-sized manufacturing factories. Indeed, only a small fraction of small and medium-sized manufacturers (SMMs) has considered implementing DT technology. There is an urgent need to exploit the full potential of data analytics and simulation-enabled DTs for advanced manufacturing. Hence, this paper presents the design and development of DT models for simulation optimization of manufacturing process flows. First, we develop a multi-agent simulation model that describes nonlinear and stochastic dynamics among a network of interactive manufacturing things, including customers, machines, automated guided vehicles (AGVs), queues, and jobs. Second, we propose a statistical metamodeling approach to design sequential computer experiments to optimize the utilization of AGV under uncertainty. Third, we construct two new graph models—job flow graph and AGV traveling graph—to track and monitor the real-time performance of manufacturing jobshops. The proposed simulation-enabled DT approach is evaluated and validated with experimental studies for the representation of a real-world manufacturing factory. Experimental results show that the proposed methodology effectively transforms a manufacturing jobshop into a new generation of DT-enabled smart factories. The sequential design of experiments effectively reduces the computation overhead of expensive simulations while optimally scheduling the AGV to achieve production throughput cost-effectively. This research is strongly promised to help SMMs fully utilize big data and DT technology for gaining competitive advantages in the global marketplace.

     
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    Free, publicly-accessible full text available November 1, 2024
  3. Abstract

    Automated optical inspection (AOI) is increasingly advocated for in situ quality monitoring of additive manufacturing (AM) processes. The availability of layerwise imaging data improves the information visibility during fabrication processes and is thus conducive to performing online certification. However, few, if any, have investigated the high-speed contact image sensors (CIS) (i.e., originally developed for document scanners and multifunction printers) for AM quality monitoring. In addition, layerwise images show complex patterns and often contain hidden information that cannot be revealed in a single scale. A new and alternative approach will be to analyze these intrinsic patterns with multiscale lenses. Therefore, the objective of this article is to design and develop an AOI system with contact image sensors for multiresolution quality inspection of layerwise builds in additive manufacturing. First, we retrofit the AOI system with contact image sensors in industrially relevant 95 mm/s scanning speed to a laser-powder-bed-fusion (LPBF) machines. Then, we design the experiments to fabricate nine parts under a variety of factor levels (e.g., gas flow blockage, re-coater damage, laser power changes). In each layer, the AOI system collects imaging data of both recoating powder beds before the laser fusion and surface finishes after the laser fusion. Second, layerwise images are pre-preprocessed for alignment, registration, and identification of regions of interests (ROIs) of these nine parts. Then, we leverage the wavelet transformation to analyze ROI images in multiple scales and further extract salient features that are sensitive to process variations, instead of extraneous noises. Third, we perform the paired comparison analysis to investigate how different levels of factors influence the distribution of wavelet features. Finally, these features are shown to be effective in predicting the extent of defects in the computed tomography (CT) data of layerwise AM builds. The proposed framework of multiresolution quality inspection is evaluated and validated using real-world AM imaging data. Experimental results demonstrated the effectiveness of the proposed AOI system with contact image sensors for online quality inspection of layerwise builds in AM processes.

     
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    Free, publicly-accessible full text available October 1, 2024
  4. ‘Algorithms’ is a core CS concept included in the K-12 CS standards, yet student challenges with understanding different aspects of algorithms are still not well documented, especially for younger students. This paper describes an approach to decompose the broad middle-school ‘algorithms’ standard into finer grained learning targets, develop formative assessment tasks aligned with the learning targets, and use the tasks to explore student understanding of, and challenges with, the various aspects of the standard. We present a number of student challenges revealed by our analysis of student responses to a set of standards-aligned formative assessment tasks and discuss how teachers and researchers interpreted student responses differently, even when using the same rubrics. Our study underscores the importance of carefully designed standards-aligned formative assessment tasks for monitoring student progress and demonstrates the need for teacher content knowledge to effectively use formative assessments during CS instruction. 
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    Free, publicly-accessible full text available October 3, 2024
  5. This poster presents findings on middle school students’ understanding of core Computer Science (CS) concepts, such as variables and control structures, using cognitive think-aloud interviews with eight students. Each student worked on 16-22 formative assessment tasks designed to assess understanding on the ‘Algorithms and Programming’ middle school CS standards. Our study describes students’ interpretations of the CS concepts and discusses potential factors influencing student interpretations. Significance and next steps are described. 
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    Free, publicly-accessible full text available October 3, 2024
  6. Dilated cardiomyopathy (DCM) is the third most common cause of heart failure and the primary reason for heart transplantation; upward of 70% of DCM cases are considered idiopathic. Our in-vitro experiments showed that reduced hybrid/complex N-glycosylation in mouse cardiomyocytes is linked with DCM. Further, we observed direct effects of reduced N-glycosylation on K v gating. However, it is difficult to rigorously determine the effects of glycosylation on K v activity, because there are multiple K v isoforms in cardiomyocytes contributing to the cardiac excitation. Due to complex functions of K v isoforms, only the sum of K + currents (I Ksum ) can be recorded experimentally and decomposed later using exponential fitting to estimate component currents, such as I Kto , I Kslow , and I Kss . However, such estimation cannot adequately describe glycosylation effects and K v mechanisms. Here, we propose a framework of simulation modeling of K v kinetics in mouse ventricular myocytes and model calibration using the in-vitro data under normal and reduced glycosylation conditions through ablation of the Mgat1 gene (i.e., Mgat1KO). Calibrated models facilitate the prediction of K v characteristics at different voltages that are not directly observed in the in-vitro experiments. A model calibration procedure is developed based on the genetic algorithm. Experimental results show that, in the Mgat1KO group, both I Kto and I Kslow densities are shown to be significantly reduced and the rate of I Kslow inactivation is much slower. The proposed approach has strong potential to couple simulation models with experimental data for gaining a better understanding of glycosylation effects on K v kinetics. 
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  7. The rapid expansion of K-12 CS education has made it critical to support CS teachers, many of whom are new to teaching CS, with the necessary resources and training to strengthen their understanding of CS concepts and how to effectively teach CS. CS teachers are often tasked with teaching different curricula using different programming languages in different grades or during different school years, and tend to receive different professional development (PD) for each curriculum they are required to teach. This often leads to a lack of deep understanding of the underlying CS concepts and how different curricula address the same concepts in different ways. Empowering teachers to develop a deep understanding of CS standards, and use formative assessments to recognize common student challenges associated with the standards, will enable teachers to provide more effective CS instruction, irrespective of the curriculum and/or programming language they are tasked with using. This position paper advocates supporting CS teacher professional learning by supplementing existing curriculum-specific teacher PD with standards-aligned PD that focuses on teachers' conceptual understanding of CS standards and ability to adapt instruction based on student understanding of concepts underlying the CS standards. We share concrete examples of how to design standards-aligned educative resources and instructionally supportive tools that promote teachers' understanding of CS standards and common student challenges and develop teachers' formative assessment literacy, all essential components of CS pedagogical content knowledge. 
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