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关键词： culture   leadership   slavic nations  

摘要： This Special Issue is an installment of the series of studies carried out by the Centre for Cross Cultural Comparisons ([https://***/](https://***/)), an international voluntary association of researchers, students and practitioners interested in the global study of culture and leadership. This Consortium investigates the relationships among preferred leader behavior dimensions and societal cultural values of employed businesspeople across the globe, with the intent of improving managerial leadership practice in businesses.

关键词： Servers   Data centers   Scalability   Routing   Fault tolerant systems   Fault tolerance   Computer science   Data center network   server-centric   scalability   fault tolerance   routing algorithm  

摘要： Topology design is vital to the high performance data center networks. Due to the limited scalability, many traditional server-centric data center networks are confronting the updating and upgrading hurdles. To address the issue, this paper proposes a highly scalable DCell-based server-centric data center network topology, called HS-DCell, which can use inexpensive and typical switches and servers with only three network ports to achieve excellent network performance HS-DCell can accommodate a large number of servers, and its diameter increases linearly with the growth of network levels, which is better than that of most existing server-centric networks. Furthermore, a fault-free routing algorithm and a fault-tolerant routing algorithm are developed based on HS-DCell. Compared with other mainstream server-centric network topologies, the experimental results show that HS-DCell has obvious advantages in many key performance indicators including scalability, fault tolerance, and server port utilization.

关键词： Blockchains   Routing   Routing protocols   Receivers   Resource management   Relays   Computer science   Blockchain   payment channel network   security   TEE  

摘要： Payment channel networks (PCNs) have been designed and utilized to address the scalability challenge and throughput limitation of blockchains. It provides a high-throughput solution for blockchain-based payment systems. However, such "layer-2" blockchain solutions have their own problems: payment channels require a separate deposit for each channel of two users. Thus it significantly locks funds from users into particular channels without the flexibility of moving these funds across channels. In this paper, we proposed Aggregated Payment Channel Network (APCN), in which flexible funds are used as a per-user basis instead of a per-channel basis. To prevent users from misbehaving such as double-spending, APCN includes mechanisms that make use of hardware trusted execution environments (TEEs) to control funds, balances, and payments. The distributed routing protocol in APCN also addresses the congestion problem to further improve resource utilization. Our prototype implementation and simulation results show that APCN achieves significant improvements on transaction success ratio with low routing latency, compared to even the most advanced PCN routing.

关键词： Kernel   Computer science   Real-time systems   Network function virtualization   Monitoring   Instruments   Hash functions   Hardware-software coordination   latency profiling   programmable switches  

摘要： In modern data center networks (DCNs), network-stack processing denotes a large portion of the end-to-end latency of TCP flows. So profiling network-stack latency anomalies has been considered as a crucial part in DCN performance diagnosis and troubleshooting. In particular, such profiling requires full coverage (i.e., profiling every TCP packet) and low overhead (i.e., profiling should avoid high CPU consumption in end-hosts). However, existing solutions rely on system calls or tracepoints in end-hosts to implement network-stack latency profiling, leading to either low coverage or high overhead. We propose Torp, a framework that offers full-coverage and low-overhead profiling of network-stack latency. Our key idea is to offload as much of the profiling from costly system calls or tracepoints to the Torp agent built on eBPF modules, and further to include a Torp handler on the ToR switch to accelerate the remaining profiling operations. Torp efficiently coordinates the ToR switch and the Torp agent on end-hosts to jointly execute the entire latency profiling task. We have implemented Torp on $32\times 100$ Gbps Tofino switches. Testbed experiments indicate that Torp achieves full coverage and orders of magnitude lower host-side overhead compared to other solutions.

关键词： Atmospheric effects   Software development   Computer science   Site testing   Methods: numerical   Techniques: image processing  

摘要： To enhance operational efficiency and meet experimental demands, we have developed a graphical user interface (GUI) using MATLAB for Acquiring Single Star SCIDAR Data, leveraging the software's integrated GUI Development Environment (GUIDE) tool. This interface streamlines the preprocessing and numerical computation of the power spectrum of atmospheric speckles while providing real-time graphical representations of atmospheric parameters, including the vertical profile of the refractive index structure function C-n(2)(h). It also incorporates parameters related to adaptive optics and high angular resolution, such as seeing, enabling immediate and instantaneous visual assessment of observational conditions. Furthermore, the novelty of this GUI lies in the ease of acquiring and processing data from various atmospheric parameters. The Single Star SCIDAR (Scintillation Detection and Ranging) method relies on analyzing the scintillation of light from single stars to assess the turbulent characteristics of the atmosphere. This assessment is based on the description provided by C-n(2)(h) derived from minimizing an objective function determined using the power spectrum of atmospheric speckles from single stars. For this purpose, a minimization algorithm called active-set is used.

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： bivariate length-biased exponential distribution   farlie-gumbel-morgenstern copula   maximum likelihood estimation   bayesian estimation   progressive type-II censoring   loss function   computer science analysis   bootstrap confidence interval   asymptotic confidence interval  

摘要： In this paper, we address the analysis of bivariate lifetime data from a length-biased exponential distribution observed under Type II progressive censoring with random removals, where the number of units removed at each failure time follows a binomial distribution. We derive the likelihood function for the progressive Type II censoring scheme with random removals and apply it to the bivariate length-biased exponential distribution. The parameters of the proposed model are estimated using both likelihood and Bayesian methods for point and interval estimators, including asymptotic confidence intervals and bootstrap confidence intervals. We also employ different loss functions to construct Bayesian estimators. Additionally, a simulation study is conducted to compare the performance of censoring schemes. The effectiveness of the proposed methodology is demonstrated through the analysis of two real datasets from the industrial and computer science domains, providing valuable insights for illustrative purposes.