The composition of first-year engineering curricula and its relationships to matriculation models and institutional characteristics

The preparation of technically excellent and innovative engineering graduates urges for a reform of the engineering curriculum to meet critical challenges in society (National Academy of Engineering, 2005). An examination of the current engineering curricula is needed to offer a baseline to further discuss if the curriculum reform meets the critical challenges. Meanwhile, concern about engineering retention prioritizes a review of the first-year engineering curricula. The existing literature does not include a nationwide examination of the first-year engineering curricula and introductory engineering courses. This study aspired to fill the gap by providing a detail description of the composition of first-year engineering curricula and introductory engineering courses of all ABET EAC-accredited programs. Furthermore, this study investigated the degree to which first-year engineering curricula and institutional characteristics varied by the matriculation policies of engineering programs. ^ To this end, this study analyzed the recommended first-year course sequences of 1,969 engineering programs and descriptions of 2,222 first-year engineering courses at all 408 U.S. institutions with ABET EAC-accredited programs. Keywords extracted from the engineering course descriptions were classified using a revised First-Year Engineering Course Classification Scheme (Reid, Reeping, & Spingola, 2013). In addition, institutional characteristics of 408 institutions grouped by matriculation models were examined. ^ There were five major findings. First, engineering courses took up 14-17% of total credit hours in the first year. Most first-year engineering courses were mandatory instead of elective or optional. Mathematics and science still formed the basis of the early engineering curriculum by accounting for more than half of the first-year credit hours. Second, the composition of first-year engineering curricula, the composition of first-year engineering courses, and the time when the first engineering course was required all varied by matriculation models. Third, topics related to engineering technologies and tools were listed most frequently in first-year engineering course descriptions, followed by topics related to design and the engineering profession. Topics related to global interest were seldom listed. Fourth, while first-year course composition varied by matriculation model, the most frequently listed topics were shared by programs with varied matriculation models, suggesting that content selection of first-year engineering courses was homogenous nationally. Lastly, institutions with different matriculation models had distinct characteristics, demonstrating the existence of relationships between institution-level and unit-level variables shown in the Model of Academic Plans in Context (Lattuca & Stark, 2009). ^ Findings of this study addressed fundamental questions of engineering education research, and had the potential to help program administrators and instructors with program and curriculum planning purposes

Analysis and Exploration of Large 3D Shape Databases

Exploring, examining, and manipulating 3D shapes is an increasingly important application area. In this work, we present new methods and techniques that address these tasks, as follows. For exploration, we use deep learning to create visual representations of large shape repositories. For examination and manipulation, we simplify the shapes to their essence, using so-called skeletons. Our work can serve both specialists and end users interested in navigating large collections of 3D shapes in a simple and intuitive way

Place Recognition under Occlusion and Changing Appearance via Disentangled Representations

Place recognition is a critical and challenging task for mobile robots, aiming to retrieve an image captured at the same place as a query image from a database. Existing methods tend to fail while robots move autonomously under occlusion (e.g., car, bus, truck) and changing appearance (e.g., illumination changes, seasonal variation). Because they encode the image into only one code, entangling place features with appearance and occlusion features. To overcome this limitation, we propose PROCA, an unsupervised approach to decompose the image representation into three codes: a place code used as a descriptor to retrieve images, an appearance code that captures appearance properties, and an occlusion code that encodes occlusion content. Extensive experiments show that our model outperforms the state-of-the-art methods. Our code and data are available at https://github.com/rover-xingyu/PROCA

A Sigmoid-based car-following model to improve acceleration stability in traffic oscillation and following failure in free flow

This paper proposes an improved Intelligent driving model (Sigmoid-IDM) to address the problems of excessive acceleration in traffic oscillation and following failure in free flow. The Sigmoid-IDM uses a Sigmoid function to enhance the start-following characteristics, improve the output strategy of the spacing term, and stabilize the steady-state velocity in free flow. Moreover, the model asymmetry is improved by means of introducing cautious following distance, driving caution factor, and segmentation function. The anti-interference ability of the Sigmoid-IDM is demonstrated by local stability and string stability analyses.Comment: 15 pages, 51 figures

Tripartite Entanglement and Quantum Correlation

We provide an analytical solution from the correlators of the generalized $R$-matrix in the 3-qubit pure states. It provides the upper bound to the maximum violation of Mermin's inequality. For a generic 2-qubit pure state, the concurrence characterizes the maximum violation of Bell's inequality from the $R$-matrix. Therefore, people expect that the maximum violation should be proper to quantify Quantum Entanglement. The $R$-matrix shows the maximum violation of Bell's operator. For a general 3-qubit state, we have five invariant entanglement quantities under local unitary transformations. We show that the five invariant quantities describe the correlation in the generalized $R$-matrix. The violation of Mermin's operator is not a proper diagnosis by observing the dependence for entanglement measures. We then classify 3-qubit quantum states. Each classification quantifies Quantum Entanglement by the total concurrence. In the end, we relate the experiment correlators to Quantum Entanglement.Comment: 14 pages, 4 figures, minor changes, reference change