Development of Computer Science Disciplines - A Social Network Analysis Approach

In contrast to many other scientific disciplines, computer science considers conference publications. Conferences have the advantage of providing fast publication of papers and of bringing researchers together to present and discuss the paper with peers. Previous work on knowledge mapping focused on the map of all sciences or a particular domain based on ISI published JCR (Journal Citation Report). Although this data covers most of important journals, it lacks computer science conference and workshop proceedings. That results in an imprecise and incomplete analysis of the computer science knowledge. This paper presents an analysis on the computer science knowledge network constructed from all types of publications, aiming at providing a complete view of computer science research. Based on the combination of two important digital libraries (DBLP and CiteSeerX), we study the knowledge network created at journal/conference level using citation linkage, to identify the development of sub-disciplines. We investigate the collaborative and citation behavior of journals/conferences by analyzing the properties of their co-authorship and citation subgraphs. The paper draws several important conclusions. First, conferences constitute social structures that shape the computer science knowledge. Second, computer science is becoming more interdisciplinary. Third, experts are the key success factor for sustainability of journals/conferences

Стягивающиеся системы гиперонов и эволюция звезд

Рассматривается влияние предположения об отсутствии насыщения в системе гиперонов на эволюцию звезд. При этом предположении существует новый механизм для выделения энергии в звездах, связанный с превращением нуклонов в стянутые системы гиперонов. Этот механизм может предотвратить гравитационное самозамыкание звезд в результате гравитационного коллапса. Обсуждается возможность реализации указанного механизма генерации энергии в квазарах

Continuous monitoring methods to achieve resiliency for virtual machines

This dissertation describes monitoring methods to achieve both security and reliability in virtualized computer systems. Our key contribution is showing how we can perform continuous monitoring and leverage information across different layers of a virtualized computer system to detect malicious attacks and accidental failures. For monitoring software running inside a virtual ma- chine, we introduce HyperTap and Hprobes, which are out-of-VM monitoring frameworks that facilitate detection of security and reliability incidents oc- curring inside a VM. For monitoring the hypervisor, we introduce hShield, a Control-Flow Integrity (CFI) enforcement method to detect VM-escape at- tacks. HyperTap, Hprobes, and hShield create a complete chain-of-trust for the entire virtualization software stack

Entrepreneurial Finance: Insights from English Language Training Market in Vietnam

Entrepreneurship plays an indispensable role in the economic development and poverty reduction of emerging economies like Vietnam. The rapid development of technologies during the Fourth Industrial Revolution (Industry 4.0) has a significant impact on business in every field, especially in the innovation-focused area of entrepreneurship. However, the topic of entrepreneurial activities with technology applications in Vietnam is under-researched. In addition, the body of literature regarding entrepreneurial finance tends to focus on advanced economies, while mostly neglecting the contextual differences in developing nations. Therefore, this research contributes to these topics by investigating the main characteristics of a high potential market for entrepreneurs in Vietnam, which is the English language training market (ELTM). It also aims at indicating the impacts of technology on the entrepreneurial firms within this market, with an emphasis on financing sources. To answer the research questions, this study employs a qualitative analysis and conducts 12 in-depth, semi-structured interviews with entrepreneurs and researchers in the field. The key findings in our study highlight the main contributing factors to the growth of the market, both universally and context-specific for a developing nation like Vietnam. It also lists the leaders in each market segment and the industry’s potential profit margin. The results also show that most entrepreneurs in the ELTM utilized private sources of finance rather than external ones, such as bank loans. It again confirms the idea from previous works that even with the rapid development of the economic and technological landscape, entrepreneurial activities in general barely benefit from additional sources of funding. However, it also points out the distinct characteristics of the ELTM that may influence these financing issues; for example, English training services usually collect revenues from customers before delivering their classes. This is of advantage for entrepreneurs in this area and helps significantly reduce the financial barriers. These findings, which are among the first attempts to contribute to a better understanding of entrepreneurial opportunities in the Industry 4.0 in Vietnam, provide valuable insights for policymakers and entrepreneurs, as well as investors

Parametric Risk-Neutral Density Estimation via Finite Lognormal-Weibull Mixtures

This paper proposes a new parametric risk-neutral density (RND) estimator based on a finite lognormal-Weibull mixture (LWM) density. We establish the consistency and asymptotic normality of the LWM method in a general misspecified parametric framework. Based on the theoretical results, we propose a sequential test procedure to evaluate the goodness-of-fit of the LWM model, which leads to an adaptive choice for the number and type of mixture components. Our simulation results show that, in finite samples with various observation error specifications, the LWM method can approximate complex RNDs generated by state-of-the-art multi-factor stochastic volatility models with a few (typically less than 4) mixtures. Application of the LWM model on index options confirms its reliability in recovering empirical RNDs with a heavy left tail or bimodality, which can be incorrectly identified as bimodality or a heavy left tail by existing (semi)-nonparametric methods if the goodness-of-fit to the observed data is ignored

Federated Few-shot Learning for Cough Classification with Edge Devices

Automatically classifying cough sounds is one of the most critical tasks for the diagnosis and treatment of respiratory diseases. However, collecting a huge amount of labeled cough dataset is challenging mainly due to high laborious expenses, data scarcity, and privacy concerns. In this work, our aim is to develop a framework that can effectively perform cough classification even in situations when enormous cough data is not available, while also addressing privacy concerns. Specifically, we formulate a new problem to tackle these challenges and adopt few-shot learning and federated learning to design a novel framework, termed F2LCough, for solving the newly formulated problem. We illustrate the superiority of our method compared with other approaches on COVID-19 Thermal Face & Cough dataset, in which F2LCough achieves an average F1-Score of 86%. Our results show the feasibility of few-shot learning combined with federated learning to build a classification model of cough sounds. This new methodology is able to classify cough sounds in data-scarce situations and maintain privacy properties. The outcomes of this work can be a fundamental framework for building support systems for the detection and diagnosis of cough-related diseases.Comment: 21 pages, 5 figure

Speedup of Interval Type 2 Fuzzy Logic Systems Based on GPU for Robot Navigation

As the number of rules and sample rate for type 2 fuzzy logic systems (T2FLSs) increases, the speed of calculations becomes a problem. The T2FLS has a large membership value of inherent algorithmic parallelism that modern CPU architectures do not exploit. In the T2FLS, many rules and algorithms can be speedup on a graphics processing unit (GPU) as long as the majority of computation a various stages and components are not dependent on each other. This paper demonstrates how to install interval type 2 fuzzy logic systems (IT2-FLSs) on the GPU and experiments for obstacle avoidance behavior of robot navigation. GPU-based calculations are high-performance solution and free up the CPU. The experimental results show that the performance of the GPU is many times faster than CPU

STEM education and outcomes in Vietnam: Views from the social gap and gender issues

United Nations’ Sustainable Development Goals 4 Quality Education has highlighted major challenges for all nations to ensure inclusive and equitable quality access to education, facilities for children, and young adults. The SDG4 is even more important for developing nations as receiving proper education or vocational training, especially in science and technology, means a foundational step in improving other aspects of their citizens’ lives. However, the extant scientific literature about STEM education still lacks focus on developing countries, even more so in the rural area. Using a dataset of 4967 observations of junior high school students from a rural area in a transition economy, the article employs the Bayesian approach to identify the interaction between gender, socioeconomic status, and students’ STEM academic achievements. The results report gender has little association with STEM academic achievements; however, female students (αa_Sex[2] = 2.83) appear to have achieved better results than their male counterparts (αa_Sex[1] = 2.68). Families with better economic status, parents with a high level of education (βb(EduMot) = 0.07), or non-manual jobs (αa_SexPJ[4] = 3.25) are found to be correlated with better study results. On the contrary, students with zero (βb(OnlyChi) = -0.14) or more than two siblings (βb(NumberofChi) = -0.01) are correlated with lower study results compared to those with only one sibling. These results imply the importance of providing women with opportunities for better education. Policymakers should also consider maintaining family size so the parents can provide their resources to each child equally

Linking Ethical Leadership to Employee Creative Performace: The Role of Leader-Member Exchange and Work Engagement

Purpose: The purpose of this research is to investigate the mediating role of leader-member exchange (LMX) and work engagement in the relationship between ethical leadership and creative performance.   Theoretical framework: The study is based on the theoretical foundation that ethical leadership positively influences creative performance. It further posits that this relationship is mediated by both leader-member exchange (LMX) and work engagement.   Design/Methodology/Approach: Data for this study was collected from a Vietnamese service firm, with a sample comprising 78 leaders and 354 employees. The collected data was analyzed using structural equation modeling (SEM) to examine the proposed relationships.   Findings: The findings of the study indicate a significant and positive correlation between ethical leadership and creative performance. Additionally, the study reveals that ethical leadership exerts an influence on both leader-member exchange (LMX) and work engagement, which subsequently enhance employees' demonstration of creativity in their work.   Research, practical & social implications: This research sheds light on the mediating mechanisms through which ethical leadership impacts creative performance. The findings highlight the importance of fostering positive leader-member relationships and promoting work engagement in order to enhance employees' creative behaviors. Practically, the study suggests that organizations should prioritize the development of ethical leadership qualities to foster a creative work environment. Moreover, the research contributes to the broader social implications by emphasizing the significance of ethical leadership in promoting creativity and innovation within organizations.   Originality/Value: This research contributes to the existing literature by examining the mediating role of leader-member exchange and work engagement in the relationship between ethical leadership and creative performance. The study provides valuable insights into the mechanisms through which ethical leaders can enhance creativity in the workplace. The findings of this research contribute to the understanding of the importance of ethical leadership and its impact on organizational outcomes, thereby adding to the originality and value of the study

Speedup of Interval Type 2 Fuzzy Logic Systems Based on GPU for Robot Navigation

As the number of rules and sample rate for type 2 fuzzy logic systems (T2FLSs) increases, the speed of calculations becomes a problem. The T2FLS has a large membership value of inherent algorithmic parallelism that modern CPU architectures do not exploit. In the T2FLS, many rules and algorithms can be speedup on a graphics processing unit (GPU) as long as the majority of computation a various stages and components are not dependent on each other. This paper demonstrates how to install interval type 2 fuzzy logic systems (IT2-FLSs) on the GPU and experiments for obstacle avoidance behavior of robot navigation. GPUbased calculations are high-performance solution and free up the CPU. The experimental results show that the performance of the GPU is many times faster than CPU