Exploring the characteristics of abusive behaviour in online social media settings

Online abusive behaviour can impact interaction amongst contributors and moderators. It may lead to physical harm or threats. Existing research has not addressed the perception of moderation activity, discussion and disagreement can cause contributors to react aggressively. This thesis investigates the factors that lead to abusive behaviour in conversations within online settings. In particular, empirical analyses were conducted to identify the factors that contribute to abuse in online settings and to distinguish between polite and abusive forms of disagreement. Three contributions were presented in this research to address each to social computing, computational social science and cyber abuse research domains. The analyses suggested that moderators on Reddit view themselves as members of their community and work hard to both guard against violations, but also with contributors to enhance the quality of their content. Moderators also reported the nuances that distinguish polite and abusive disagreement. Furthermore, the analyses revealed that the differences between in-person and online conversations can help identify abusive behaviour. Specifically, the setting of discussion fosters participant behaviours (less hedging, more extreme sentiment, greater willingness to express personal opinion and straying from topic) that are known to increase the likelihood of abusive behaviour. Additionally, the findings revealed how consensus-building factors can influence disagreement in different settings. Finally, we showed how disagreement can be identified and can affect votes based on linguistics contexts. It was shown that different forms of disagreement can be detected better when using specific abuse, politeness and sentiment textual features using models of multi label text classification. The above research findings conceptualised the development of moderation systems to combat online abusive behaviour, based on analysis of the type of disagreement a contribution embodies and other linguistic and behavioural characteristics

SELF-HANDOVER OPTIMIZATION IN LTEA MOBILE SYSTEM

In recent era, peoples are using to share information through mobile. Wireless communication with relay nodes allows broadband internet access through radio communication. Example of such communication is vehicular communications with backhaul links. However mobility management equipment of existing system does not allow the high mobility vehicles for instant communication. We suggested a user optimized handover mechanism with dual mobile relay devises for wireless communication, to allow high speed communication environment. Proposed work combines the individual cell handover parameters with hysteresis. Performance analysis indicates that our developed mechanism is removes communications number link failure & also reduces the service interruption during handover

MAC –QOS MULTIMEDIA CONGESTIONS IN LOAD BALANCING BASED MESH NETWORKS

Wireless mesh network (WMNs) is becoming   familiarly mostly due to their deployment flexible. Major overhead of this network is to provide QoS to their servers. Lot of research work has been done to improve the efficiency of the QoS but it put extra overhead on WMNs resources. One among the major considerable characteristics is to enhance QoS in WMNs is end to end delay. In the proposed work focus is made to decreases the delay, thereby it is possible to enhance the throughput and also increasing QoS. As delay multimedia congestion needs to transmit in a fixed time otherwise quality of multimedia congestion degrades. Thus our work aims to degrade the delay to send the real time traffic like multimedia. A hybrid simulation cum emulation- test-bed is built and used for addressing ViLBaS performance compared with analyzed A-TXOP is developed over Re_AP to further enhance the performance of video congestion. Re_AP with A-TXOP helps in decreasing the delay of real-time congestion by over 32% and further enhances the quality of real-time congestion compared with Re_AP without A-TXOP. Finally, we have TXOP-accessible, whose goal is to reduce the delay of real time congestion. It includes using the TXOP to send to multiple receivers, for further analyzing the TXOP interval totally. This also decreases the multiple of contentions to the medium and hence decreases the delay of real-time congestion by over 14%. A-TXOP is developed over Re_AP to uphold improvement

A new hybrid multilevel thyristor-based DC-DC converter

The rapid growth in HVDC grids is becoming inevitable for long-distance power transmission. Therefore, the idea of interconnection between the point-to-point links becomes essential. However, these point-to-point connections face several challenges such as the requirement of DC fault blocking capability, interfacing of different grounding schemes, offering multi-vendor interoperability, and difficulty to achieve high DC voltage stepping. DC-DC converters are considered the optimum solution to tackle these challenges in DC grids interconnection. In this paper, a new hybrid modular DC-DC converter is proposed that achieves a low number of semiconductors, low losses, and cost in comparison to other DC-DC converters due to the utilization of thyristors. The new DC-DC converter consists of two hybrid MMC bridges connected through an isolating transformer. Each MMC bridge is comprised of half bridge submodules and bidirectional thyristors. Detailed mathematical analysis, design, and control are illustrated. A comparison is carried out between different topologies in terms of semiconductor count, power loss, and cost. Also, both simulation model and experimental test rig are built to validate the proposed hybrid modular DC-DC converter under different scenarios. Finally, another variant of the hybrid-thyristor based converter (version two) is proposed for multiport DC-Hub application to achieve DC fault blocking without turning off all connected bridges

Intellectual Capital History and Trends: A Bibliometric Analysis Using Scopus Database

This article aims to provide a bibliometric analysis of intellectual capital research published in the Scopus database from 1956 to 2020 to trace the development of scientific activities that can pave the way for future studies by shedding light on the gaps in the field. The analysis focuses on 638 intellectual capital-related papers published in the Scopus database over 60 years, drawing upon a bibliometric analysis using VOSviewer. This paper highlights the mainstream of the current research in the intellectual capital field, based on the Scopus database, by presenting a detailed bibliometric analysis of the trend and development of intellectual capital research in the past six decades, including journals, authors, countries, institutes, co-occurrence, and author’s keywords. The findings imply that intellectual capital researchers do not use broad relevant theories and findings from studies beyond their clusters. Another result is that developing nations continue to be underexplored in terms of intellectual property research due to a lack of trust representation and a lack of appropriate investigators. Finally, the data analysis identifies a number of potential research issues to be investigated regarding intellectual capital development, which serve as raw material for future research. Once again, this study provides a framework for firms to build and implement intellectual capital development plans

Evolutionary Generator Maintenance Scheduling in Power Systems

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Global Coinfections with Bacteria, Fungi, and Respiratory Viruses in Children with SARS-CoV-2: A Systematic Review and Meta-Analysis

Background: Coinfection with bacteria, fungi, and respiratory viruses has been described as a factor associated with more severe clinical outcomes in children with COVID-19. Such coinfections in children with COVID-19 have been reported to increase morbidity and mortality. Objectives: To identify the type and proportion of coinfections with SARS-CoV-2 and bacteria, fungi, and/or respiratory viruses, and investigate the severity of COVID-19 in children. Methods: For this systematic review and meta-analysis, we searched ProQuest, Medline, Embase, PubMed, CINAHL, Wiley online library, Scopus, and Nature through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for studies on the incidence of COVID-19 in children with bacterial, fungal, and/or respiratory coinfections, published from 1 December 2019 to 1 October 2022, with English language restriction. Results: Of the 169 papers that were identified, 130 articles were included in the systematic review (57 cohort, 52 case report, and 21 case series studies) and 34 articles (23 cohort, eight case series, and three case report studies) were included in the meta-analysis. Of the 17,588 COVID-19 children who were tested for co-pathogens, bacterial, fungal, and/or respiratory viral coinfections were reported (n = 1633, 9.3%). The median patient age ranged from 1.4 months to 144 months across studies. There was an increased male predominance in pediatric COVID-19 patients diagnosed with bacterial, fungal, and/or viral coinfections in most of the studies (male gender: n = 204, 59.1% compared to female gender: n = 141, 40.9%). The majority of the cases belonged to White (Caucasian) (n = 441, 53.3%), Asian (n = 205, 24.8%), Indian (n = 71, 8.6%), and Black (n = 51, 6.2%) ethnicities. The overall pooled proportions of children with laboratory-confirmed COVID-19 who had bacterial, fungal, and respiratory viral coinfections were 4.73% (95% CI 3.86 to 5.60, n = 445, 34 studies, I2 85%, p < 0.01), 0.98% (95% CI 0.13 to 1.83, n = 17, six studies, I2 49%, p < 0.08), and 5.41% (95% CI 4.48 to 6.34, n = 441, 32 studies, I2 87%, p < 0.01), respectively. Children with COVID-19 in the ICU had higher coinfections compared to ICU and non-ICU patients, as follows: respiratory viral (6.61%, 95% CI 5.06–8.17, I2 = 0% versus 5.31%, 95% CI 4.31–6.30, I2 = 88%) and fungal (1.72%, 95% CI 0.45–2.99, I2 = 0% versus 0.62%, 95% CI 0.00–1.55, I2 = 54%); however, COVID-19 children admitted to the ICU had a lower bacterial coinfection compared to the COVID-19 children in the ICU and non-ICU group (3.02%, 95% CI 1.70–4.34, I2 = 0% versus 4.91%, 95% CI 3.97–5.84, I2 = 87%). The most common identified virus and bacterium in children with COVID-19 were RSV (n = 342, 31.4%) and Mycoplasma pneumonia (n = 120, 23.1%). Conclusion: Children with COVID-19 seem to have distinctly lower rates of bacterial, fungal, and/or respiratory viral coinfections than adults. RSV and Mycoplasma pneumonia were the most common identified virus and bacterium in children infected with SARS-CoV-2. Knowledge of bacterial, fungal, and/or respiratory viral confections has potential diagnostic and treatment implications in COVID-19 children