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摘要： We report on the technology transfer project "Do it yourself, but not alone: Companion-Technology for Home Improvement" that was carried out by Ulm University in cooperation with Robert Bosch GmbH. We developed a prototypical assistance system that assists a Do It Yourself (DIY) handyman in carrying out DIY projects. The assistant, based on various AI and dialog management capabilities, generates a sequence of detailed instructions that users may just follow or adapt according to their individual preferences. It features explanation capabilities as well as pro-active support based on communication with the user as well as with the involved tools. We report on the project's main achievements, including the findings of various empirical studies conducted in various development stages of the prototype.

关键词： Computer science   Bibliometrics   Term life cycles   MACD   Logistic model   Gompertz model  

摘要： Scientific topics vary in popularity over time. In this paper, we model the life cycles of 200 trending topics by fitting the Logistic and Gompertz models to their frequency over time in published abstracts. Unlike other work, the topics we use are algorithmically extracted from large datasets of abstracts covering computer science, particle physics, cancer research, and mental health. We find that the Gompertz model produces lower median error, leading us to conclude that it is the more appropriate model. Since the Gompertz model is asymmetric, with a steep rise followed a long tail, this implies that scientific topics follow a similar trajectory. We also explore the case of double-peaking curves and find that in some cases, topics will peak multiple times as interest resurges. Finally, when looking at the different scientific disciplines, we find that the lifespan of topics is longer in some disciplines (e.g. cancer research and mental health) than it is others, which may indicate differences in research process and culture between these disciplines.

关键词： Privacy   Computer science education   Computer science education   Computer security   Artificial intelligence   Convergence  

摘要： We summarize integrating cybersecurity and artificial intelligence (AI) research in cybersecurity education and implementing a module in an existing noncybersecurity undergraduate engineering course. This initiative will drive the broader community to focus on the convergence of cybersecurity and AI education.

关键词： ESL   Word list   Computer science   Academic vocabulary   Language education  

摘要： This article presents the Computer Science Academic Vocabulary List (CSAVL), a pedagogical tool intended for use by English-for-specific-purpose educators and material developers. A 3.5-millionword corpus of academic computer science texts was developed in order to produce the CSAVL. The CSAVL draws from the improved methodologies used in the creation of recent lemma-based word lists such as the Academic Vocabulary List (AVL) (Gardner & Davies, 2014) and the Medical Academic Vocabulary List (MAVL) (Lei & Liu, 2016), which take into account the disciplinespecific meanings of academic vocabulary. The CSAVL provides specific information for each entry, including part of speech and CS-specific meanings in order to provide users with clues as to how each item is used within the context of academic CS. Based on the analyses performed in this study, the CSAVL was found to be a more efficient tool for reaching an minimal level of academic CS reading comprehension than the Academic Word List (AWL) (Coxhead, 2000), or the combination of the AWL with the Computer Science Word List (CSWL) (Minshall, 2013).

关键词： Signal processing algorithms   Adaptation models   Gallium nitride   Computer science   Machine learning algorithms   Numerical models   Convergence   Online learning   recursive identification   separable nonlinear models (SNLMs)   variable projection (VP)  

摘要： In this article, we study the recursive algorithms for a class of separable nonlinear models (SNLMs) in which the parameters can be partitioned into a linear part and a nonlinear part. Such models are very common in machine learning, system identification, and signal processing. Utilizing the special structure of the SNLMs, we propose a recursive variable projection (RVP) algorithm, in which at each recursion, the linear parameters of the model are eliminated, and the nonlinear parameters are updated by the recursive Levenberg-Marquart algorithm. Then, based on the updated nonlinear parameters, the linear parameters are updated by the recursive least-squares algorithm. According to a convergence analysis of the RVP algorithm, the parameter estimation error is mean-square bounded. Numerical examples confirm the satisfactory performance of the proposed algorithm.

关键词： Computer science   Education   History  

摘要： Nature’s pages feature a textbook that takes a new approach for covering science, and an obituary of Charles Babbage.

关键词： Testing   Software development management   Software engineering   Tools   Programming   Games   Data structures   Computer science (CS)   gamification   leaderboards   learning management systems (LMSs)   motivation   study behaviors   unit testing   version control  

摘要： Contribution: Research has shown that computer science (CS) students who start programming assignments (PAs) early generally receive higher grades. This article presents and evaluates a gamification approach that utilizes software engineering tools to motivate CS students to start and finish PAs earlier. Background: CS can be difficult to learn because students often struggle with errors and how to properly test their code. For these reasons, it is essential that students start their PAs early. Furthermore, software engineering tools, such as version control and unit testing, are increasingly important for students to learn early in their career. Intended Outcomes: This gamification approach aims to motivate CS students to start and complete PAs earlier, as well as instill software engineering best practices. Application Design: To motivate students to start and finish assignments early, an open-source gamification system called the Leaderboard was developed. Using gamified points, the Leaderboard rewards students who pass PA unit tests well before the assignment is due. The system is fully automated using Github Classroom, a build server, and the Moodle learning management system. Findings: Results indicate students who used the Leaderboard did not start assignments significantly earlier;however, they finished assignments earlier, committed code more frequently, and passed more unit tests. The students found the Leaderboard to be motivating and passing unit tests was exciting for them.

关键词： Computer science   Scientific data   Climate sciences   Information technology  

摘要： Hundreds of petabytes are produced annually at weather and climate forecast centers worldwide. Compression is essential to reduce storage and to facilitate data sharing. Current techniques do not distinguish the real from the false information in data, leaving the level of meaningful precision unassessed. Here we define the bitwise real information content from information theory for the Copernicus Atmospheric Monitoring Service (CAMS). Most variables contain fewer than 7 bits of real information per value and are highly compressible due to spatio-temporal correlation. Rounding bits without real information to zero facilitates lossless compression algorithms and encodes the uncertainty within the data itself. All CAMS data are 17x compressed relative to 64-bit floats, while preserving 99% of real information. Combined with four-dimensional compression, factors beyond 60x are achieved. A data compression Turing test is proposed to optimize compressibility while minimizing information loss for the end use of weather and climate forecast data.

关键词： Deep learning   Communications technology   Correlation   Urban areas   Computer science   Predictive models   Intelligent transportation systems   Traffic passenger flows prediction   bus transit systems   multitask learning   deep learning  

摘要： Bus services play a crucial role in urban transit. It is significant to achieve the fine-grained service-level passenger flow prediction (SPFP), namely to predict the total number of passengers for each service of each bus line passing through each station during the next short-term interval. However, it faces great challenges due to complex factors including inter-station and inter-line spatial dependencies, intra-station and inter-service temporal dependencies, and internal/external influences. To address these challenges, we propose a multitask deep-learning (MDL) approach, called MDL-SPFP, to jointly predict the arriving bus service flow, line-level on-board passenger flow and line-level boarding/alighting passenger flow by leveraging well-designed deep neural networks called ARM. The MDL framework can mutually reinforce the prediction of each type of flow, and finally integrate the outputs to achieve the fine-grained service-level prediction. The ARM network combines three modules, Attention mechanism, Residual block and Multi-scale convolution, to well capture various complex non-linear spatio-temporal dependencies and influence factors. Extensive experiments based on a large-scale realistic bus operation dataset are conducted to confirm that our MDL-SPFP approach outperforms 10 state-of-the-art baselines, and improves 22.39% accuracy than the best baseline.