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关键词： Clustering methods   Computer science   Fuzzy systems   Data mining   Uncertainty   Representation learning   Learning systems   Fuses   Entropy   Data models   Common information   dual anchor graph learning   fuzzy clustering   multiview data   specific information  

摘要： Multiview anchor graph clustering has been a prominent research area in recent years, leading to the development of several effective and efficient methods. However, three challenges are faced by current multiview anchor graph clustering methods. First, real-world data often exhibit uncertainty and poor discriminability, leading to suboptimal anchor graphs when directly extracted from the original data. Second, most existing methods assume the presence of common information between views and primarily explore it for clustering, thus neglecting view-specific information. Third, further exploration and exploitation of the learned anchor graph to enhance clustering performance remains an open research question. To address these issues, a novel dual anchor graph fuzzy clustering method is proposed in this article. First, a novel matrix factorization-based dual anchor graph learning method is proposed to address the first two issues by extracting highly discriminative hidden representations for each view and subsequently deriving both common and specific anchor graphs from these hidden representations. Then, to address the third issue, a novel anchor graph fuzzy clustering method is developed with cooperative learning to exploit and utilize the common and specific anchor graphs fully. Meanwhile, a fuzzy membership structure preservation mechanism with dual anchor graphs is constructed to enhance clustering performance. Finally, negative Shannon entropy is further introduced to adaptively adjust the view weighing. Extensive experiments on several datasets demonstrate the effectiveness of the proposed method.

关键词： Data visualization   Bars   Computer science   Strain   Sensitivity   Encoding   Visualization   Magnitude   axis manipulation   cognition   bias   framing effects  

摘要： When visualising data, chart designers have the freedom to choose the upper and lower limits of numerical axes. Axis limits can determine the physical characteristics of plotted values, such as the physical position of data points in dot plots. In two experiments (total N=300), we demonstrate that axis limits affect viewers' interpretations of the magnitudes of plotted values. Participants did not simply associate values presented at higher vertical positions with greater magnitudes. Instead, participants considered the relative positions of data points within the axis limits. Data points were considered to represent larger values when they were closer to the end of the axis associated with greater values, even when they were presented at the bottom of a chart. This provides further evidence of framing effects in the display of data, and offers insight into the cognitive mechanisms involved in assessing magnitude in data visualisations.

关键词： HI   IT-BiLSTM   rotating machinery   RUL  

摘要： Rotating machinery, as a key component of mechanical equipment, plays a crucial role in ensuring the reliability and safety of the equipment. This article proposes a RUL prediction framework based on interactive bidirectional long short-term memory (IT-BiLSTM) and function fitting, aiming to improve the accuracy of RUL prediction in rotating machinery. Firstly, to unify the failure threshold under different working conditions, a data interception method based on root mean square is proposed, and empirical mode decomposition is used to reconstruct the intercepted signals;then, 16 features are extracted, and health indicator (HI) is constructed through IT-BiLSTM, which is mapped to the [0,1] interval;finally, the time when HI is 0 is found through function fitting, which is the current RUL. The accuracy of the proposed method is verified using two datasets. The results show that the proposed IT-BiLSTM can more accurately predict the RUL of rotating machinery.

关键词： Computer science   Machine learning   Technology  

摘要： Developers are racing to find new ways to train large language models, after sucking the Internet dry of usable information.

摘要： Computer science (CS) is increasingly becoming part of the curricula of K-12 education in different countries. However, there are few K-12 CS teachers, and tools to offer K-12 CS education are often limited. Massive Open Online Courses (MOOCs) might help to temporarily address these challenges, and enable more schools to offer CS education. The goal of this systematic review is to give an overview of how CS MOOCs have been used in K-12 education. Nineteen papers from 2014 to May 2024 were included, describing thirteen different MOOCs. This review summarizes the research performed with these MOOCs and discusses directions for future research. Our findings show that most CS MOOCs target only part of the CS curriculum. When using a MOOC, a classroom teacher has an important role in supporting and managing students as they work in the MOOC. Research evaluating MOOCs is diverse, both in aims and in methods. In conclusion, MOOCs can play a valuable role in K-12 CS education, although additional teacher training to support students might be required. Moreover, additional learning material is needed to cover the full curriculum, as most MOOCs focus on programming and computational thinking. © 2025, CC BY-SA.

关键词： Machine learning   Computer science   Authorship   Databases  

摘要： In a year that will see many AI achievements and battles, let’s not forget that not all AI research makes the front pages.

关键词： Blaberidae   computer science   machine learning   animal tracking  

摘要： Radio frequency identification (RFID) technology and marker recognition algorithms can offer an efficient and non-intrusive means of tracking animal positions. As such, they have become important tools for invertebrate behavioral research. Both approaches require fixing a tag or marker to the study organism, and so it is useful to quantify the effects such procedures have on behavior before proceeding with further research. However, frequently studies do not report doing such tests. Here, we demonstrate a time-efficient and accessible method for quantifying the impact of tagging on individual movement using open-source automated video tracking software. We tested the effect of RFID tags and tags suitable for marker recognition algorithms on the movement of Argentinian wood roaches (Blapicta dubia, Blattodea: Blaberidae) by filming tagged and untagged roaches in laboratory conditions. We employed DeepLabCut on the resultant videos to track cockroach movement and extract measures of behavioral traits. We found no statistically significant differences between RFID tagged and untagged groups in average speed over the trial period, the number of unique zones explored, and the number of discrete walks. However, groups that were tagged with labels for marker recognition had significantly higher values for all 3 metrics. We therefore support the use of RFID tags to monitor the behavior of B. dubia but note that the effect of using labels suitable for label recognition to identify individuals should be taken into consideration when measuring *** behavior. We hope that this study can provide an accessible and viable roadmap for further work investigating the effects of tagging on insect behavior.

关键词： Technology   Computer science   Sustainability   Machine learning   Immunology  

摘要： Sustainability and artificial intelligence dominate our seventh annual round-up of exciting innovations.

关键词： Machine learning   Computer science   Technology  

摘要： Developers have tricks to stop artificial intelligence from making things up, but large language models are still struggling to tell the truth, the whole truth and nothing but the truth.