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关键词： Remaining useful life   Interactive learning   Rolling bearings   Convolution  

摘要： To address the issues of low accuracy, high time cost, and different failure modes in predicting the remaining useful life of rolling bearings, a remaining useful life prediction model based on an interactive learning convolution network with a feature attention mechanism (ILCANet) was proposed in this paper. The model divided time series data into an odd part and an even part, and the interactive learning strategy improved the ability of the model to extract features from long series. The binary tree structure was used to increase the number of network layers and to subdivide sequence features. In the model, residual connection was introduced to prevent the gradient from disappearing. In addition, in order to determine the degree of contribution of different features, a feature attention mechanism was embedded to assign weights to features. Experiments were conducted with PHM2012 and XJTU-SY datasets, and the results showed that the proposed method had better prediction accuracy in RUL prediction than other prediction methods.

关键词： Energy consumption   Data centers   Optimization   Heuristic algorithms   Energy efficiency   Renewable energy sources   Temperature sensors   Computational modeling   Clouds   Computer science   Cloud data center   energy optimization   reinforcement learning   renewable energy  

摘要： The widespread adoption of cloud data centers has led to a rise in energy consumption, with the associated carbon emissions posing a further threat to the environment. Cloud providers are increasingly moving towards sustainable data centers powered by renewable energy sources (RES). The existing approaches fail to efficiently coordinate IT and cooling resources in such data centers due to the intermittent nature of RES and the complexity of state and action spaces among different devices, resulting in poor holistic energy efficiency. In this paper, a reinforcement learning (RL) based framework is proposed to optimize the holistic energy consumption of sustainable cloud data centers. First, a joint prediction method MTL-LSTM is developed to accurately evaluate both energy consumption and thermal status of each physical machine (PM) under different optimization scenarios to improve the state space information of the RL algorithm. Then, this framework designs a novel energy-aware approach named BayesDDQN, which leverages Bayesian optimization to synchronize the adjustments of VM migration and cooling parameter within the hybrid action space of the Double Deep Q-Network (DDQN) for achieving the holistic energy optimization. Moverover, the pre-cooling technology is integrated to further alleviate hotspot by making full use of RES. Experimental results demonstrate that the proposed RL-based framework achieves an average reduction of 2.83% in holistic energy consumption and 4.74% in brown energy, which also reduces cooling energy consumption by 13.48% with minimal occurrences of hotspots. Furthermore, the proposed MTL-LSTM method reduces the root mean square error (RMSE) of energy consumption and inlet temperature predictions by nearly half compared to LSTM and XGBoost.

关键词： Interdisciplinary teaching   e-learning   Interest   Engagement   Diversity   Gender   Computer science education  

摘要： The field of computer science (CS) is facing a crucial challenge in broadening participation and embracing diversity, especially among underrepresented gender groups. The presented interdisciplinary educational program is an efficient response to this challenge, designed to catalyze diversity in CS through engagement with complex, interest-driven problems. This paper outlines the program's structure, elucidates the pedagogical underpinnings, and reflects on the emergent challenges and opportunities. We delve into how the fusion of CS with other academic disciplines can allure a more varied demographic, emphasizing the engagement of female high school students-a demographic pivotally positioned yet significantly untapped in CS. Through a systematic survey analysis, we measure the program's efficacy in increasing interest in CS and in cultivating an appreciation for its application in addressing real-world, cross-disciplinary challenges. Our findings affirm the program's success in bridging the engagement gap by leveraging students' intrinsic interests, thus charting alternative pathways into the CS field. These insights underscore the critical role of interdisciplinary approaches, establishing anew standard for transformative CS educational methods.

关键词： Capital punishment   Sentencing   Aggravating &   mitigating factors  

摘要： Murder trials in which the death penalty is sought involves the jury's consideration of aggravating factors (circumstances necessary for the crime to be death penalty eligible) and mitigating factors (considerations submitted by the defense intended to dissuade a death sentence). Using data from capital murder trials in North Carolina from 1990 to 2023, this study examines the relationship of accepted and the heretofore unexplored impact of rejected aggravating, statutory mitigating, and non-mitigating factors on jury sentencing decisions while controlling for a host of other relevant variables. As expected, accepted aggravating factors statistically increased the odds of a death sentence while accepted statutory mitigating factors decreased those odds. However, in a finding not considered in previous the literature, we also determined that aggravating factors submitted but not accepted by the jury decreased the odds of a death sentence while mitigating factors (both statutory and non-statutory) submitted but not accepted increased the odds. A complex analysis of individual aggravators and mitigators revealed considerable variation in these impacts. The implications for the processing of capital punishment cases are discussed.

关键词： Location awareness   Proposals   Circuits and systems   Annotations   Training   Noise   Computer science   Weakly-supervised learning   temporal action localization   progressive complementary learning  

摘要： Weakly-Supervised Temporal Action Localization (WSTAL) aims to localize and classify action instances in long untrimmed videos with only video-level category labels as supervision. A critical challenge of WSTAL is the large gap between video-level supervision and unavailable snippet-level supervision. Prevailing methods typically assign pseudo labels to snippets, but these methods suffer from significant noise caused by the pseudo snippet-level labels. In this work, we address the WSTAL from a novel category exclusion perspective, which gradually enhances the snippet-level supervision to bridge the gap. Our proposed Progressive Complementary Learning (ProCL) is inspired by the fact that, video-level labels precisely indicate the categories that all snippets surely do not belong to, which is ignored by previous works. Accordingly, we first exclude these surely non-existent categories by the deterministic complementary learning. And then, we introduce the entropy-based pseudo complementary learning that is able to exclude more categories for snippets of less ambiguity. Furthermore, for the remaining ambiguous snippets, we attempt to reduce the ambiguity by distinguishing foreground actions from the background. Extensive experimental results show that our method achieves new state-of-the-art performance on THUMOS14, ActivityNet1.3, and MultiTHUMOS benchmarks.

关键词： Multi-agent system (MAS)   Life cycle assessment (LCA)   Environmental impact   University campus   Time-dependent variations   Interaction  

摘要： Neighborhoods consume large amount of energy and generate substantial pollutant emissions worldwide, and assessment of the environmental impacts (EIs) has garnered particular attention. Nevertheless, the traditional life cycle assessment (LCA) method fails to account for the local variability in non-homogeneous systems due to spatiotemporal dynamics and interactions. Hence, this study integrated the multi-agent system (MAS) with the dynamic LCA (DLCA) model to develop an intelligent EIs assessment model at the neighborhood scale from an interactive and dynamic perspective. MAS was employed to simulate the interactions in neighborhoods and generate foreground elementary flow data considering dynamics. DLCA provides an impact assessment framework. The proposed model was applied to a university campus to demonstrate its operability, and the enhancement effectiveness of integrating MAS with DLCA can be observed. The interactions among the climate, people, and built environment agents on the campus were simulated.10 temporal dynamic factors and four kinds of case-specific dynamic parameters were considered. The effects of several optimization strategies were simulated, and valuable directions, like raising energy conservation awareness, regulating public devices, and improving the campus layout, were proposed. This study established a comprehensive integrated MAS-DLCA model at the neighborhood scale, providing a methodology and practical application process for future studies. It can be used to promote green neighborhood management and sustainable city practices.

关键词： adult learning   data science applications in education   human-computer interface   21st century abilities  

摘要： The study focuses on evaluating the performance of AI-based tools, specifically ChatGPT versions 3.5 and 4.0, in comparison to human students in the field of Theoretical Computer Science Education. The experiment aims to assess the capabilities of both AI and human subjects in solving learning tasks based on Bloom's Taxonomy. The primary objectives of the study are to determine the educational performance of AI and students, identify areas where students may outperform AI in learning tasks, and evaluate the normalized overall results of educational performance with equal assignment weights. The assessment included testing on various types of Bloom's Learning Task Taxonomy (LTT) based on specific Learning Objectives (LOs). Hypotheses were formulated for quantitative and qualitative analysis to compare the performance of AI and human subjects. Quantitative analysis revealed engaging results regarding the educational performance evaluation with AI-based tools. While some differences were observed in the performance of AI and students, the normalized overall results with equal assignment weights did not show statistically significant differences. The study highlighted the advantages and disadvantages of both humans and AI bots in solving learning tasks. The study concludes that there are areas where students may have an advantage over AI in tasks requiring understanding, evaluation, and creative thinking. Recommendations are provided for educators on utilizing AI-based tools in education, emphasizing the coexistence of AI possibilities with well-designed assignments. The findings suggest that AI has a valuable role in education, and a thorough analysis of teaching approaches and student evaluation is essential in leveraging artificial intelligence effectively.

关键词： IEEE Regions   Collaboration   Social networking (online)   Web sites   Open Access   Multimedia communication   Hands   Computer science   Bibliometrics   Reviews   editorial  

摘要： Editorial of inaugural edition of IEEE Latin America Transactions in 2025.

关键词： Gender inclusivity   Education   Persona   GenderMag   Computer science   Software engineering   Software usability  

摘要： Women are underrepresented in Computer Science (CS)/ Software Engineering (SE) and other technology related degrees. As undergraduates, they are also less likely to persist with CS/SE studies than men enrolled in those same courses. Gender correlated differences in personal characteristics, behaviour, and preferences mean that course design decisions may introduce unintended bias. To address this issue, we drew inspiration from the GenderMag method. GenderMag uses personas with evidence-based gender differences in problem-solving traits to detect usability issues in software. In this paper we investigate the personal qualities of CS and SE students, and how these influence their CS/SE learning journey. A series of persona development workshops were held to gather an extensive and unique qualitative dataset capturing the prior experiences, preferences, learning styles, motivations, goals, frustrations, and constraints of CS/SE students. Gender differences were used to construct preliminary male and female student personas. These personas were used in cognitive walkthroughs of software applications commonly used in education, and their performance compared to GenderMag's Tim and Abi. While the student personas were less effective and lacked specificity compared to Abi, they were able to identify issues not detectable with GenderMag. Furthermore, the findings show the utility of persona development workshops as a data collection method and introduce a comprehensive list of CS/SE student qualities that may inspire future investigations.

关键词： advanced technology   aquaculture   black tiger shrimp   current status   Penaeus monodon   shrimp farming  

摘要： The increasing high-end market demand for the black tiger shrimp Penaeus monodon has brought tremendous industry opportunities. Although the industry has tried its best to increase production, according to the report data from the Food and Agriculture Organization (FAO), annual global production has shown no significant upward trend over the past decade. Besides that, newly implemented policies such as seafood safety and food security negatively impacted the industry and reduced production. However, P. monodon cultivation is still promising due to its larger body size and higher market acceptance as a premium product. Over the years, numerous studies have been conducted to increase the production of P. monodon by optimizing its culture conditions, implementing new culture system, increasing disease resistance to disease such as WSSV, AHPND, WFD, implementation of pre- and probiotics in feed, and selective breeding programs to increase genetic diversity and population of P. monodon broodstock. This review provides an overview of the current advances in P. monodon broodstock cultivation, thereby providing an essential baseline for P. monodon aquaculture. Areas needing urgent research focus are also highlighted. Future research should take great strides and take into account the impact of future climate change scenario during P. monodon culture and optimization, and increase biosecurity measures to prevent its introduction as an alien species in wild settings.