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关键词： Adaptation models   Data models   Electronic mail   Vectors   Data visualization   Heuristic algorithms   Computer science   Training   Tensors   Periodic structures   Confident graph   graph learning   incomplete multiview clustering (IMVC)   MVC  

摘要： Exploring the structure information is crucial for data clustering task, particularly for the sceneries of incomplete multiview clustering (IMVC) when some views are missing. However, almost all of the existing graph-based IMVC methods either introduce the Laplacian constraint with fixed graphs or simply fuse the graphs of all views, which are vulnerable to the quality of the constructed graphs. To address this issue, we propose a new graph-based method, called confident local structure-aware incomplete multiview spectral clustering. Different from existing works, our method seeks to adaptively uncover the inherent similarity structure among the available instances in each view and learn the optimal consensus graph within a unified learning framework. Moreover, to mitigate the adverse effects of imbalance information across incomplete views and improve the quality of consensus graph, we further impose some adaptive weights on the consensus graph learning model w.r.t. each view and introduce some confident structure graphs to explore the most confident similarity information in the model. In contrast to existing works, our approach simultaneously takes into account the pairwise similarity information and neighbor group-based confident structure information. This dual consideration makes our method more effective in achieving the optimal consensus graph and delivering superior IMVC performance. Experimental results on several datasets demonstrate that our method effectively learns a high-quality and clustering-friendly graph from incomplete multiview data, and it outperforms many state-of-the-art IMVC methods in terms of clustering performance.

关键词： Frequency estimation   Accuracy   Source address validation   Routing protocols   Information processing   Filtering   Time-frequency analysis   Distributed databases   Computer science   Wide area networks   Data streams   global top- K   top- K -fairness   sketch  

摘要： Finding top-K frequent items has been a hot topic in data stream processing with wide-ranging applications. However, most existing sketch algorithms focus on finding local top-K in a single data stream. In this paper, we tackle finding global top-K across multiple data streams. We find that using prior sketch algorithms directly is often unfair in global scenarios, degrading global top-K accuracy. We define top-K-fairness and show its importance for finding global top-K. To achieve this, we propose the Double-Anonymous (DA) sketch, where double-anonymity ensures fairness. We also propose two techniques, hot-filtering and early-freezing, to improve accuracy further. We theoretically prove that the DA sketch achieves top-K-fairness while maintaining high accuracy. Extensive experiments verify top-K-fairness in disjoint data streams, showing that the DA sketch's error is up to 129 times (60 times on average) smaller than the state-of-the-art. To enhance the applicability and technical depth, we also investigate how to extend the DA sketch to general distributed data stream scenarios and how to provide a fairer and more accurate global ranking for top-K items. The experimental results show that the extended version of the DA sketch can indeed compute better rankings and still has significant advantages in general data streams.

关键词： Task analysis   Optimization   Knowledge transfer   Knowledge acquisition   Evolutionary computation   Computer science   Vehicle routing   Evolutionary computation (EC)   evolutionary many-task optimization (EMaTO)   evolutionary multitask optimization (EMTO)   knowledge transfer   structure-preserved knowledge   tree-based knowledge propagation (TKP)  

摘要： As a challenging research topic in evolutionary multitask optimization (EMTO), evolutionary many-task optimization (EMaTO) aims at solving more than three tasks simultaneously. The design of the EMaTO algorithm generally needs to consider two major open issues, which are how to obtain useful knowledge from similar source tasks and how to effectively transfer knowledge to the target task. In this article, we discover that knowledge structure plays a significant role in dealing with these two issues and propose a novel knowledge structure preserving-based evolutionary algorithm (KSP-EA) to efficiently solve many-task optimization problems. KSP-EA aims to achieve two goals, which are first to obtain useful structure-preserved knowledge from similar source tasks and second to effectively transfer both direct and indirect knowledge to the target task. To achieve the first goal, we propose a local-structure-preserved knowledge acquisition strategy that projects the knowledge of similar source tasks into a unified subspace without loss of the knowledge structure, thus enhancing the quality of the obtained knowledge. To achieve the second goal, we propose a tree-based knowledge propagation strategy that constructs a knowledge propagating tree to connect all the tasks and propagates knowledge along the edges of this tree. This way, the target task can obtain both direct and indirect knowledge, improving the effectiveness of knowledge transfer. We conduct extensive experiments on CEC19 and WCCI22 many-task optimization test suites and a real-world application scenario to evaluate the performance of KSP-EA. The experimental results show that our KSP-EA generally outperforms state-of-the-art algorithms.

关键词： expectation   practical programming tasks   probability courses  

摘要： The concept of expectation is fundamental in computer science education, especially for analyzing the time efficiency of algorithms. However, the gap between theoretical knowledge and practical application can make it challenging for students to appreciate the importance of expectation in real-world contexts. This paper seeks to bridge that gap by highlighting the relationship between expectation and the population mean. To accomplish this, two experiments are presented, with tasks specifically designed to engage students in hands-on learning experiences in practical problem-solving. The first experiment focuses on the number of successes of the careless clerk, while the second experiment involves searching for all occurrences of a value in a randomly selected array, addressing the key question of the algorithm's expected time complexity. By presenting tasks that demonstrate the practical application of expectation, we aim to equip students with the tools needed to make informed decisions when designing and optimizing algorithms.

摘要： Black Bamboo (Gigantochloa atroviolacea Widjadja) is one type of bamboos that grows in Indonesia and is widely used by the community for various purposes. Propagation of black bamboo seedlings is generally done through stem cuttings, but this method requires a lot of propagation material so it is not efficient. One of the bamboo seed propagation techniques that can produce a very large number of seeds, uniform in size and does not use a lot of plant material is tissue culture technique. The problem that is often found in tissue culture is the emergence of bacterial, fungi and browning contamination in the growing media which can interfere with the growth of the explants. Therefore, it is necessary to use suitable sterilization materials to control the occurrence of such contamination. This study aims to determine the effect of adding NaOCl (NaOCl), streptomycin and povidone iodine in suppressing bacterial, fungi and browning contamination in the growing media of black bamboo tissue culture. The treatment aimed to select the best sterilization material for use in the production of black bamboo tissue culture. The research design used was a factorial completely randomized design (CRD) with 2 factors, namely the immersion time of HgCl2 (10 and 12 minutes), and the addition of sterilant NaOCl (NaOCl) 20%, Streptomycin 0.1%, Povidone iodine 10%). The results showed that there was no effect of immersion time of HgCl2 on bacterial contamination, fungi contamination and browning. Meanwhile, the addition of NaOCl, streptomycin and betadine had an effect on bacterial and fungi contamination but had no effect on browning. The addition of 10% povidone iodine to 0.01% HgCl2 proved to be the most effective in suppressing fungi contamination by 57.4% and suppressing bacterial contamination by 89.4%.

关键词： Information management  

摘要： In the past few decades, the life sciences have experienced an unprecedented accumulation of data, ranging from genomic sequences and proteomic profiles to heavy-content imaging, clinical assays, and commercial biological products for research. Traditional static databases have been invaluable in providing standardized and structured information. However, they fall short when it comes to facilitating exploratory data interrogation, real-time query, multidimensional comparison and dynamic visualization. Interactive databases aiming at supporting user-driven data queries and visualization oLer promising new avenues for making the best use of the vast and heterogeneous data streams collected in biological research. This article discusses the potential of interactive databases, highlighting the importance of implementing this model in the life sciences, while going through the state-of-the-art in database design, technical choices behind modern data management systems, and emerging needs in multidisciplinary research. Special attention is given to data interrogation strategies, user interface design, and comparative analysis capabilities, along with challenges such as data standardization and scalability in data-heavy applications. Conceptual features for developing interactive databases along diverse life science domains are then presented in the user case of cell line selection for in vitro research to bridge the gap between research data generation, actionable biological insight, subsequent meaningful experimental design, and clinical relevance. © 2025, CC BY.

关键词： Computer circuits  

摘要： We review four areas of theoretical computer science which share technical or philosophical ideas with the work of Belnap on his useful four-valued logic. Perhaps surprisingly, the inspiration by Belnap–Dunn logic is acknowledged only in the study of d-frames. The connections of Belnap’s work and linear logic, Blame Calculus or the study of LVars are not openly admitted. The key to three of these connections with Belnap’s work go via the twist-product representation of bilattices. On the one hand, it allows us to view a large class of models of linear logic as based on Belnap–Dunn logic. On the other hand, d-frames admit two twist-product representation theorems and, also, the key theorem in Blame Calculus is essentially a twist-product representation theorem too, albeit with a strong proof-theoretic flavour. © 2025, CC BY-SA.

关键词： Contrastive Learning  

摘要： Developing competency in artificial intelligence is becoming increasingly crucial for computer science (CS) students at all levels of the CS curriculum. However, most previous research focuses on advanced CS courses, as traditional introductory courses provide limited opportunities to develop AI skills and knowledge. This paper introduces an introductory CS course where students learn computational thinking through computer vision, a sub-field of AI, as an application context. The course aims to achieve computational thinking outcomes alongside critical thinking outcomes that expose students to AI approaches and their societal implications. Through experiential activities such as individual projects and reading discussions, our course seeks to balance technical learning and critical thinking goals. Our evaluation, based on pre-and post-course surveys, shows an improved sense of belonging, self-efficacy, and AI ethics awareness among students. The results suggest that an AI-focused context can enhance participation and employability, student-selected projects support self-efficacy, and ethically grounded AI instruction can be effective for interdisciplinary audiences. Students’ discussions on reading assignments demonstrated deep engagement with the complex challenges in today’s AI landscape. Finally, we share insights on scaling such courses for larger cohorts and improving the learning experience for introductory CS students. © 2025, CC BY.