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关键词： Quantum computing   Computers   Bibliometrics   Computer science   Qubit   Network analyzers   Databases   CiteSpace   quantum algorithms (QAs)   quantum computing (QC)   quantum machine learning (QML)   scientometrics  

摘要： Quantum computing is a revolutionary field of research in science and technology, which provides sophisticated processing capacity and computation in a finite time frame based on quantum mechanics. It has the great potential to offer more effective and faster solutions to overcome current processing constraints. Therefore, to address the global significance, relevance, and exponential growth, it is imperative to conduct a thorough investigation and promote advancements through rigorous scientometric analysis. The current article presents the knowledge mapping of rapidly expanding quantum computing research using the CiteSpace visualization tool. The foundation of research is the scientific literature on quantum computing extracted from the Scopus database, covering the period of 2008-2022. It provides publication patterns, citation structure, and in-depth keyword co-occurrence network analysis insights to extract emerging research areas. It illustrates a variety of empirical approaches to discover the status quo and evolution. The findings reveal that quantum algorithms serve as the fundamental basis for all research fields, and quantum machine learning is the most active research area nowadays.

关键词： computer science   engineering   mentorship   mentorship competency assessment   postdoctoral  

摘要： BackgroundPostdoctoral training holds an increasingly important place in preparation for leading academic and research positions. While little empirical research has described postdoctoral training beyond the sciences, across all fields, "misaligned expectations" are often touted as a key source of postdoctoral ***/HypothesisThis article describes mentorship competency beliefs within engineering and computer science fields, which increasingly engage in postdoctoral ***/MethodAn embedded mixed-methods design was used to quantitatively identify mentorship profiles from survey data using latent profile analysis (LPA) from a sample of n = 118 postdoctoral scholars and n = 165 postdoctoral supervisors. Qualitative thematic analysis of interviews with n = 29 postdoctoral scholars and n = 20 postdoctoral supervisors was used to identify meaning in the differences between quantitative profiles. The combination of LPA with thematic analysis enabled the triangulation of distinct postdoctoral mentorship profile *** identified six postdoctoral fellow profiles and four supervisor profiles, which became clearly definable through thematic analysis. Postdoc profiles included Technical Manager, Autonomy Focused Advisor, Stretched Mentor, Well-Rounded Mentor, Exemplar Mentor, and Leader-Mentor, while supervisor profiles included Autonomous Mentor, Reflective Mentor, Research Lab Mentor, and Confident Leader-Mentor. Some of these are aligned, but several are not, giving insight into the phenomenon of "misaligned expectations" in postdoctoral *** mentorship profiles illustrate the misalignment in expectations, which leads to negative mentorship experiences for many postdoctoral scholars.

关键词： Training   Ensemble learning   Costs   Computer science   Linear programming   Learning systems   Classification algorithms   Multi-class imbalance classification   ensembles   AdaBoost   adaptive weight   data density  

摘要： AdaBoost approaches have been used for multi-class imbalance classification with an imbalance ratio measured on class sizes. However, such ratio would assign each training sample of the same class with the same weight, thus failing to reflect the data distribution within a class. We propose to incorporate the density information of training samples into the class imbalance ratio so that samples of the same class could have different weights. As one could use the entire training set to calculate the imbalance and density factors, the weight of a training sample resulting from the two factors remains static throughout the training epochs. However, static weights could not reflect the up-to-date training status of base learners. To deal with this, we propose to design an adaptive weighting mechanism by making use of up-to-date training status to further alleviate the multi-class imbalance issue. Ultimately, we incorporate the class imbalance ratio, the density-based factor, and the adaptive weighting mechanism into a single variable, based on which the adaptive weights of all training samples are computed. Experimental studies are carried out to investigate the effectiveness of the proposed approach and each of the three components in dealing with multi-class imbalance classification problem.

关键词： Adaptation models   Computer crime   Servers   Electronic mail   Computer science   Training   Proposals   Intrusion detection system   fine-grained unknown class detection   isolation forest  

摘要： Anomaly-based network intrusion detection systems (NIDSs) are essential for ensuring cybersecurity. However, the security communities realize some limitations when they put most existing proposals into practice. The challenges are mainly concerned with fine-grained unknown attack detection and ever-changing legitimate traffic adaptation. To tackle these problem, we present three key design norms. The core idea is to construct a model to split the data distribution hyperplane and leverage the concept of isolation, as well as advance the incremental model update. We utilize the isolation tree as the backbone to design our model, named, to echo back three norms. By analyzing the popular dataset of network intrusion traces, we show that significantly outperforms the state-of-the-art methods. Further, we perform an initial deployment of by working with the Internet Service Provider (ISP) to detect distributed denial of service (DDoS) attacks. With real-world tests and manual analysis, we demonstrate the effectiveness of to identify previously-unseen attacks in a fine-grained manner.

关键词： Students  

摘要： This study examines the effectiveness of the Students Industrial Work Experience Scheme (SIWES) for Computer Science students at Moshood Abiola Polytechnic, Abeokuta. Through correlational analysis of various assessment components, including employer evaluations, student logbooks, and technical reports, the research aims to identify key factors contributing to student performance and skill development. The findings reveal strong correlations between employer evaluations, logbook quality, and overall performance, highlighting the importance of practical experience and documentation in the SIWES program. This research contributes to the ongoing discourse on the role of industrial training in higher education and provides recommendations for enhancing the SIWES experience for computer science students. © 2024, CC BY.

关键词： Computer simulation languages  

摘要： Large Language Models (LLMs) have ushered in a transformative era in Natural Language Processing (NLP), reshaping research and extending NLP's influence to other fields of study. However, there is little to no work examining the degree to which LLMs influence other research fields. This work empirically and systematically examines the influence and use of LLMs in fields beyond NLP. We curate 106 LLMs and analyze ∼148k papers citing LLMs to quantify their influence and reveal trends in their usage patterns. Our analysis reveals not only the increasing prevalence of LLMs in non-CS fields but also the disparities in their usage, with some fields utilizing them more frequently than others since 2018, notably Linguistics and Engineering together accounting for ∼45% of LLM citations. Our findings further indicate that most of these fields predominantly employ task-agnostic LLMs, proficient in zero or few-shot learning without requiring further fine-tuning, to address their domain-specific problems. This study sheds light on the cross-disciplinary impact of NLP through LLMs, providing a better understanding of the opportunities and challenges. © 2024, CC BY-NC-SA.

关键词： Agriculture   Management strategies   Environmentally friendly innovations   Green innovation   Environmental destruction   Digital agriculture   Agricultural development infrastructures  

摘要： This research focuses on the importance of management strategies, green innovation, and sustainable practices in the agricultural sector. These factors are crucial for job creation, food security, and environmental conservation. Particularly in water-scarce regions, effective management is necessary to overcome natural resource constraints and encourage a shift towards digital agriculture (AGRI). The study aims to identify and analyze the challenges and issues related to agricultural research and technology in Asian countries. The collected data were analyzed using exploratory factor analysis in the SPSS software. The analysis revealed a range of issues and challenges for agricultural development, including those related to the structure and policy framework, the availability and quality of resources and infrastructures, and the provision of effective support services, all of which encompassed factors such as research and technology investment, research management, productivity, research culture, networking, and the integration of higher education and agricultural research. To estimate the efficiency of technology development, agricultural development, and support services for AGRI, an artificial neural network (ANN) was utilized. The ANN was trained by incorporating changes in management strategies, green innovation, and sustainability across a broader range of experimental scenarios. The evaluation of the ANN's predictions showed that improvements in management strategies and the adoption of green innovation and sustainability significantly impacted the productivity of technology development, agricultural development, and support services for AGRI. The accuracy of the ANN's predictions was further assessed using linear regression. The results indicated an acceptable level of error when compared to the target results obtained from experimental tests. Overall, this study emphasizes the importance of effective management, green innovation, and sustainable practices i

关键词： Climate sciences   Computer science   Engineering   Technology  

摘要： Frontier, the first machine to break supercomputing’s exascale speed barrier, is giving researchers unprecedented insights into everything from atoms to galaxies.

关键词： Computer science   Sustainability   Policy  

摘要： Online safety is crucial, but so are privacy and decentralization. Computer scientists who set the Internet's technical standards should be included in governance talks. Online safety is crucial, but so are privacy and decentralization. Computer scientists who set the Internet's technical standards should be included in governance talks.