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关键词： Gated recurrent unit (GRU) network   generalized Wiener process   interactive hybrid model   remaining useful life (RUL)   uncertainty quantification  

摘要： Journal bearings are the key components of the nuclear circulating water pump (NCWP), and accurate remaining useful life (RUL) prediction is of great significance for improving the reliability, safety, and maintenance planning of NCWP. However, it is difficult to quantify the uncertainty of bearing RUL based on the current deep learning (DL) model, resulting in a lack of credibility and effective convincing for RUL predicted by the model. Meanwhile, all existing hybrid models are basically simple combinations, and they cannot solve the uncertainty quantification problem of RUL predicted by DL. Hence, the bearing RUL prediction method based on a dynamic interactive hybrid model is proposed. Firstly, a degradation model based on a nonlinear enhanced generalized Wiener process (EGWP) is proposed, which combines gated neural networks and time-varying drift coefficients to describe the nonlinear degradation process of bearing. Then, a corrective gated recurrent unit (CGRU) network is designed to learn and predict real-time degradation increments, and the parameters of the degradation model are dynamically updated through the history and prediction of degradation increments. Finally, the bearing RUL prediction is given by the CGRU network, and the probability density function (PDF) of RUL is given by the proposed hybrid model. The performance of the proposed method is evaluated using the PHM 2012 bearing dataset and the NCWP journal bearing dataset. The results show that our proposed method can effectively predict bearing RUL and its uncertainty.

关键词： Task analysis   Electronic commerce   Social networking (online)   Computer science   Toy manufacturing industry   Sun   Recommender systems   Graph neural networks   group buying (GB)   recommender systems   social e-commerce  

摘要： Recent years have witnessed the great success of group buying (GB) in social e-commerce, opening up a new way of online shopping. In this business model, a user can launch a GB as an initiator to share her interested product with social friends. The GB is clinched once enough friends join in as participants to copurchase the shared product. As such, a successful GB depends on not only whether the initiator can find her interested product but also whether the friends are willing to join in as participants. Most existing recommenders are incompetent in such complex scenario, as they merely seek to help users find their preferred products and cannot help identify potential participants to join in a GB. To this end, we propose a novel joint product-participant recommendation (J2PRec) framework, which recommends both candidate products and participants for maximizing the success rate of a GB. Specifically, J2PRec first designs a relational graph embedding module, which effectively encodes the various relations in GB for learning enhanced user and product embeddings. It then jointly learns the product and participant recommendation tasks under a probabilistic framework to maximize the GB likelihood, i.e., boost the success rate of a GB. Extensive experiments on three real-world datasets demonstrate the superiority of J2PRec for GB recommendation.

关键词： Anomaly detection   Detectors   Behavioral sciences   Feature extraction   Task analysis   Electronic mail   Computer science   Cross-modal anomaly detection   triple-adaptive network   bi-quintuple contrastive learning   shared residual block  

摘要： Cross-modal anomaly detection is a relatively new and challenging research topic in machine learning field, which aims at identifying the anomalies whose patterns are disparate across different modalities. As far as we know, this topic has yet to be well studied, and existing works often suffer from the incomplete anomalous data detection and low data utilization problems. To alleviate these limitations, this paper proposes an efficient deep cross-modal anomaly detection approach via Triple-adaptive Network and Bi-quintuple Contrastive Learning (TN-BCL), which lies among the earliest attempt to detect various cross-modal anomalies within the heterogeneous multi-modal data. To be specific, a triple-adaptive network is explicitly designed to identify various anomalies, whose patterns are disparate in both single-modal scenario and cross-modal scenario. On the one hand, the top branch network is utilized to adaptively detect the attribute anomalies and part of mixed anomalies in multi-modal data samples. On the other hand, the bottom two-branch network, with shared residual blocks, is leveraged to learn the discriminative cross-modal embeddings. At the same time, an efficient bi-quintuple contrastive learning method is designed to enhance the feature correlation between the same attribute data, while maximally enlarging the feature difference between different attribute data. Besides that, the bidirectional learning scheme is employed to significantly improve the data utilization. Through the joint exploitation of the above, different kinds of anomalous samples can be well detected across different modalities. Extensive experiments show that the proposed framework outperforms the state-of-the-art competing methods, with a large improvement margin.

关键词： Computer science   Co-authorship   Collaboration   Citation  

摘要： Co-authored publications can bring positive results for those who participate, such as gaining additional expertise, accessing more funding or increasing the publication impact. China, the European Union, and the United States have been collaborating between each other throughout the years in the field of Computer Science. These collaborations varied over time, as well as they impacted the regions in different ways. In this paper, we collected the publications from these territories across 31 years on the topic of Computer Science and studied them focusing on how the regions have approached co-authorship. In particular, we have analyzed the number of collaborations during that period, the impact of those papers measured as the number of citations, and the topics that have been researched. We conclude that China's focus on Computer Science fields has led it to be the most productive region in recent years;plus, it has benefited from the American and European reputation, by increasing its citation rates when collaborating with them. On the other hand, the EU and the US have benefited from Chinese interest in computer science, increasing the number of publications together.

关键词： Teaching  

摘要： Introductory courses on formal foundations of computer science are often attended by large numbers of students with diverse backgrounds. In this paper we outline how we address this challenge in our courses by supplementing traditional teaching with web -based, interactive exercises. The web -based exercises are provided by Iltis, a modern teaching support system covering the foundations of computer science logic, formal languages, and (parts of) complexity theory. We give a gentle introduction to Iltis, describe its technical integration into our courses, and outline research challenges and opportunities coming up when developing such a system.

关键词： Affect   capital punishment   death penalty   defense   humanization   mitigation  

摘要： This article has two goals. First, I demonstrate the challenges that "humanization" poses for the defense as an ideal of sentencing mitigation in U.S. capital trials. Capital case procedure largely neutralizes the sympathetic effects of humanization with jurors. In addition, potential mitigation witnesses inhabit affective environs that undermine any inclination to help the defense through sympathetic testimony. Second, I explain how defense advocacy responds to humanization's challenges. Practitioners adopt an investigative mindset that focuses on forging the conditions to cultivate relationships with mitigation witnesses. This intensive affective labor translates back into the realm of procedure through strategic maneuvers intended to avoid trial and the performance of humanization.

摘要： Considering the interconnection of computing and human languages.

摘要： The craft beer industry is dominated by images of bearded White men and represents what is considered a "White space". In the present research, we explore racism and discrimination in the marketplace by advancing an understanding of Black-owned business experiences within an industry culture dominated by Whiteness. This phenomenological inquiry utilized a storytelling framework (Bell, 2020) to study the ways in which Blackness is explained, minimized, or celebrated in the development of counter-narratives enacted to challenge the dominant narrative within the craft beer industry. Our findings, obtained from interviews with 27 Black brewers, explain how color-blind racism is encountered, history is reframed, and an inclusive future is envisioned through the explication of concealed, resistance, and emerging stories, respectively. Our study answers the call for marketing scholars to more critically engage with how race and racism impact marketplace in-teractions, particularly among minoritized business owners.

关键词： Academic support   case study   computer science   higher education   learning technology   technology applications   tutoring  

摘要： Artificial intelligence (AI) in programming teaching is something that still has to be explored, since in this area assessment tools that allow grading the students work are the most common ones, but there are not many tools aimed toward providing feedback to the students in the process of creating their program. In this work a small sized AI-based intelligent tutor that answers students programming questions and provides them with examples is presented. AI is becoming more and more popular as time passes, allowing to perform tasks automatically in a way that could not be done before. From predictions to customization, AI is being used in many areas, not being educational environments outside this situation. AI is being used in educational settings to customize contents or to provide personalized feedback to the students, among others. In this scenario, The tool has been tested by university students at the Universidad Rey Juan Carlos during the course Programming Fundamentals in the first course of their Biomedical Engineering degree to evaluate if it helps the students in the process of learning programming skills. One of the main goals was to provide guidance to the students without needing the instructor to be physically by their side. Even if the tool is still in its preliminary phase, it helped the students with their questions, providing accurate answers and examples. The students were able to use the intelligent tutor easily and they thought that it could be a useful tool to use in other courses.

关键词： Computer science   Machine learning   Sustainability