• Small female citation advantages for US journal articles in medicine

      Thelwall, Michael; Maflahi, Nabeil (SAGE, 2021-12-31)
      Female underrepresentation continues in senior roles within academic medicine, potentially influenced by a perception that female research has less citation impact. This article provides systematic evidence of (a) female participation rates from the perspective of published journal articles in 46 Scopus medical subject categories 1996-2018 and (b) gender differences in citation rates 1996-2014. The results show female proportion increases 1996-2018 in all fields and a female majority of first authored articles in two fifths of categories, but substantial differences between fields: A paper is 7.3 times more likely to have a female first author in Obstetrics and Gynecology than in Orthopedics and Sports Medicine. Only three fields had a female last author majority by 2018, a probable side effect of ongoing problems with appointing female leaders. Female first-authored research tended to be more cited than male first-authored research in most fields (59%), although with a maximum difference of only 5.1% (log-transformed normalised citations). In contrast, male last-authored research tends to be more cited than female last-authored research, perhaps due to cases where a senior male has attracted substantial funding for a project. These differences increase if team sizes are not accounted for in the calculations. Since female first-authored research is cited slightly more than male first-authored research, properly analysed bibliometric data considering career gaps should not disadvantage female candidates for senior roles.
    • A flow-based multi-agent data exfiltration detection architecture for ultra-low latency networks

      Marques, Rafael Salema; Epiphaniou, Gregory; Al-Khateeb, Haider; Maple, Carsten; Hammoudeh, Mohammad; De Castro, Paulo Andre Lima; Dehghantanha, Ali; Choo, Kim-Kwang Raymond (Association for Computing Machinery, 2021-12-31)
      Modern network infrastructures host converged applications that demand rapid elasticity of services, increased security and ultra-fast reaction times. The Tactile Internet promises to facilitate the delivery of these services while enabling new economies of scale for high-fdelity of machine-to-machine and human-to-machine interactions. Unavoidably, critical mission systems served by the Tactile Internet manifest high-demands not only for high speed and reliable communications but equally, the ability to rapidly identify and mitigate threats and vulnerabilities. This paper proposes a novel Multi-Agent Data Exfltration Detector Architecture (MADEX) inspired by the mechanisms and features present in the human immune system. MADEX seeks to identify data exfltration activities performed by evasive and stealthy malware that hides malicious trafc from an infected host in low-latency networks. Our approach uses cross-network trafc information collected by agents to efectively identify unknown illicit connections by an operating system subverted. MADEX does not require prior knowledge of the characteristics or behaviour of the malicious code or a dedicated access to a knowledge repository. We tested the performance of MADEX in terms of its capacity to handle real-time data and the sensitivity of our algorithm’s classifcation when exposed to malicious trafc. Experimental evaluation results show that MADEX achieved 99.97% sensitivity, 98.78% accuracy and an error rate of 1.21% when compared to its best rivals. We created a second version of MADEX, called MADEX level 2 that further improves its overall performance with a slight increase in computational complexity. We argue for the suitability of MADEX level 1 in non-critical environments, while MADEX level 2 can be used to avoid data exfltration in critical mission systems. To the best of our knowledge, this is the frst article in the literature that addresses the detection of rootkits real-time in an agnostic way using an artifcial immune system approach while it satisfes strict latency requirements.
    • COVID-19 and construction law: comparing the United Kingdom and Australian response

      Charlson, Jennifer; Dickson, Rebecca (Informa Business Intelligence, 2021-12-31)
    • This! Identifying new sentiment slang through orthographic pleonasm online: Yasss slay gorg queen ilysm

      Thelwall, Mike (Institute of Electrical and Electronics Engineers, 2021-12-31)
      Identifying neologisms is important for natural language processing of social web text when informal language is standard and youth slang is common. For example, failing to identify neologisms can reduce the accuracy of lexical sentiment analysis if opinions are frequently expressed in words that are too new to be in the sentiment dictionary. This article proposes a method based on orthographic pleonasm to identify emotion-related neologisms in the social web: finding words with the most different letter repetition spelling variations. For this method, non-dictionary words are extracted from a large social web corpus, spelling standardisation is applied, and then words are ranked in decreasing order of spelling variation frequency. Words with the most spelling variations are then KWIC-analysed for semantic context. Applied to a collection of comments on YouTube influencers, this method found neologisms like slay and early as positive terms, mixed with traditional sentiment words, exclamations, and nouns. Although orthographic pleonasm was originally used to express the speaker’s rhythm and one of voice, it is also used for initialisms in a way that is difficult to vocalise. The method is therefore a practical method to identify new sentiment slang, including both normal words and initialisms.
    • Modulation of Protein phosphatase 1 complexes: a promising approach in cancer treatment

      Matos, Barbara; Howl, John; Jeronimo, Carmen; Fardilha, Margarida (Elsevier, 2021-12-31)
      Cancer is the second leading cause of death worldwide. Despite the numerous therapeutic options available, tumor heterogeneity and chemoresistance have limited their success and the development of an effective anticancer therapy remains a major challenge in oncology research. The serine/threonine-protein phosphatase 1 (PP1) and its complexes have been recognized as potential drug targets. Although research on the modulation of PP1 complexes is currently at an early stage, there is an immense potential. Chemically diverse compounds have been developed to disrupt or stabilize different PP1 complexes in various cancer types with the objective to inhibit disease progression. Beneficial results obtained in vitro now require further pre-clinical and clinical validation. In conclusion, the modulation of PP1 complexes seems to be a promising, albeit challenging, therapeutic strategy for cancer.
    • Business model innovation (BMI) in small enterprises from developing countries during COVID-19 outbreak: Exploring drivers and BMI outcomes

      Martinez, Gabriel; Renukappa, Suresh; Suresh, Subashini (Inderscience Enterprises Ltd., 2021-12-31)
      The purpose of this paper is to provide understanding of driving forces for Business Model Innovation (BMI) during the pandemic for small businesses in developing countries, comparing them with identified BMI drivers before the outbreak and evaluating their response to the current crisis. A qualitative multiple case study is conducted as it allows the study of BMI within real life and contemporary context. Case study organisations that adopt innovative business models participated from technology, education, and social enterprises. Findings shows that small organisations are influenced by internal and external factors towards BMI during the pandemic. Case organisations showed resilience to the crisis by adjusting accordingly to allow uninterrupted operation during lockdown; developing new products, services and processes that would ensure sustained demand during COVID-19 pandemic. The study explores theoretical implications of the findings. Also, lessons from this research could be useful for practitioners from developed and developing countries. Policymakers from developing countries could benefit from focusing their activities on promoting firms to find novel ways of operating during times of pandemic preventing further economic damage and unemployment.
    • Time-dependent thixotropic behaviours of lead-free Sn-Ag-Cu (SAC) solder pastes and flux mediums used in electronic assemblies

      Mallik, S; Ekere, Nduka; Depiver, Joshua (David Publishing, 2021-12-31)
      Solder pastes are widely used as crucial joining material in microelectronic assemblies. This study investigates time-depended behaviours of paste materials (solder pastes and flux mediums) in relation to their transportation, storage, handling and applications. Two fluxes and four commercially available lead-free solder pastes prepared from those fluxes were evaluated. Two rheological test methods – ‘hysteresis loop test’ and ‘step shear test’ were adapted, taking account of actual shear profile of solder pastes and flux mediums. Within hysteresis loop tests, samples were sheared for both single and multiple cycles, with increasing and decreasing shear rates. These tests provided a quick and straightforward way of benchmarking time-depended structural breakdown and build-up of paste materials. The test results also provided an effective means of predicting how the pastes will behave during their use, such as at various stages of the stencil printing process. Step shear tests were performed by applying a sequence of stepwise increase in shear rates. The step-wise increase in shear rate has influenced the timedependent behaviours of solder paste samples and flux mediums. The result from the stepshear-test implies that the build-up of solder paste structure depends mainly on both the previous shear history and the intensity of structural break-down.
    • A novel hybrid automaton framework for multi-phase epidemic modelling

      Navarro Lopez, Eva; Cabukoglu, Nurdan (SCS (The Society of Modeling & Simulation International), 2021-12-31)
      A framework for the multi-phase epidemic modelling of SEIARD (Susceptible-Exposed-symptomatic Infectious-Asymptomatic infectious-Recovered by immunity or by vaccination-Dead due to the disease) subpopulations is produced with switching transmission rate, basic reproduction ratio and vaccination strategy. Thekey novel featureof our modelis that we reproduce the different phasesof theevolutionof the infectious diseasebyusingahybrid automatonwithdifferent discrete locations correspondingtoeachof the phases of the disease. This is a general modelling framework applicable to the spreading of infectious diseases.We showhow the proposed modelworks with the simulationof different scenarios.
    • Drivers to improve talent management in the age of COVID-19: the case of UK construction industry

      Stride, Mark; Renukappa, Suresh; Suresh, Subashini (British Academy of Management, 2021-12-31)
      The UK built environment is constantly challenged with talent management issues that comprises of a multitude of individual areas effecting the construction industry and burdening many job roles including skilled labour, Architects, Engineers and Project Managers to build a huge housing programme, High Speed rail 2 (HS2), smart cities and many other key national projects. However, without the skilled labour, there will be subsequent implications including delays, rising costs and now the Coronavirus pandemic and the UK recession will inflate these factors further. The object of this review is to understand the key drivers to improve the talent management in the construction industry and therefore a critical review of the construction industry has been completed to understand how improvements can be made. Scopus and UK Government publications have been peer-reviewed and reported the drivers to improve talent management in the construction industry. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were used to select eligible articles. After the full screening, 53 articles that met the criteria were analysed and used to identify 9 key drivers to improve talent management in the construction industry. The identified drivers to improve talent management are women in the workplace, intersectionality, young adults, disabled workers, employer responsibility management, aging workforce, retaining talent, industry 4.0 and construction sustainability. This identified that further research is required into each of these areas to allow the sector to improve the recruitment and retainment of employees.
    • New working practices: a scientometric review

      Oladinrin, Olugbenga; Jayantha, Wadu; Moses, Tochukwu (Universiti Teknologi Malaysia, 2021-12-31)
      Study on New Working Practices (NWPs), which is the subject of this review paper, has created a large body of literature. Studies in this research area are progressing quickly and it is important to stay abreast of new trends and essential factors in the growth of mutual awareness. This study aims at evaluating the global scientific output of New Working Practices (NWPs) research and exploring their hotspots and frontiers from 1980 to 2018 (pre-COVID-19), using bibliometric methods. 850 relevant articles were retrieved from the Web of Science Core Collection (WoSCC) and were used for the analysis. Scientometric method and Citespace VI were used to analyse the bibliometric data. Reference citation and co-citation networks were plotted, while keywords were used to analyse the research hotspots and trends. There is a significant increase in the number of annual publications with time. The United Kingdom (UK) ranked highest in the countries with most publications, and the leading author is Friedhelm Nachreiner based on publication counts. The most cited author/organization is the UK Department of Health. Performance, work, and flexible working are the research hotspots, while flexible working arrangement represents the prominent research domain. The study offers valuable references for researchers, industry practitioners and policymakers.
    • A Bayesian hurdle quantile regression model for citation analysis with mass points at lower values

      Shahmandi, Marzieh; Wilson, Paul; Thelwall, Michael (MIT Press, 2021-12-31)
      Quantile regression is a technique to analyse the effects of a set of independent variables on the entire distribution of a continuous response variable. Quantile regression presents a complete picture of the effects on the location, scale, and shape of the dependent variable at all points, not just at the mean. This research focuses on two challenges for the analysis of citation counts by quantile regression: discontinuity and substantial mass points at lower counts, such as zero, one, two, and three. A Bayesian two-part hurdle quantile regression model was proposed by King and Song (2019) as a suitable candidate for modeling count data with a substantial mass point at zero. Their model allows the zeros and non-zeros to be modeled independently but simultaneously. It uses quantile regression for modeling the nonzero data and logistic regression for modeling the probability of zeros versus nonzeros. Nevertheless, the current paper shows that substantial mass points also at one, two, and three for citation counts will nearly certainly affect the estimation of parameters in the quantile regression part of the model in a similar manner to the mass point at zero. We update the King and Song model by shifting the hurdle point from zero to three, past the main mass points. The new model delivers more accurate quantile regression for moderately to highly cited articles, especially at quantiles corresponding to values just beyond the mass points, and enables estimates of the extent to which factors influence the chances that an article will be low cited. To illustrate the advantage and potential of this method, it is applied separately to both simulated citation counts and also seven Scopus fields with collaboration, title length, and journal internationality as independent variables.
    • Effect of stoichiometry on AC and DC breakdown of siliconnitride/epoxy nanocomposites

      Alhabil, Fuad; Vaughan, Alun; Anani, Nader; Andritsch, Thomas (IEEE, 2021-12-31)
      This study investigates the electrical behavior of silicon nitride/epoxy nanocomposites. It is demonstrated that the presence of the nanofiller affects the resin/hardener stoichiometry, which results in the development of different network structures throughout the matrix polymer. However, detailed analysis shows that this stoichiometric effect cannot account, alone, for the observed changes in the electrical behavior of the nanocomposite samples. A comparison between the electrical behavior of filled and the unfilled samples, where appropriate stoichiometric compensation has been applied, indicates that there is an additional effect that is exclusively a function of the nanofiller loading and which is superimposed on any matrix chemistry effects. Potential explanations for this nanoparticle effect are discussed, including: nanoparticle agglomeration; water shells around the nanoparticles; the influence of nanoparticles on matrix dynamics, structure or the free volume content of polymer interphase.
    • Self attended stack pointer networks for learning long term dependencies

      Tuç, Salih; Can, Burcu (Association for Computational Linguistics, 2021-12-31)
      We propose a novel deep neural architecture for dependency parsing, which is built upon a Transformer Encoder (Vaswani et al., 2017) and a Stack Pointer Network (Ma et al., 2018). We first encode each sentence using a Transformer Network and then the dependency graph is generated by a Stack Pointer Network by selecting the head of each word in the sentence through a head selection process. We evaluate our model on Turkish and English treebanks. The results show that our transformer-based model learns long term dependencies efficiently compared to sequential models such as recurrent neural networks. Our self attended stack pointer network improves UAS score around 6% upon the LSTM based stack pointer (Ma et al., 2018) for Turkish sentences with a length of more than 20 words.
    • Social media users produce more affect that supports cultural values, but are more influenced by affect that violates cultural values

      Hsu, Tiffany W; Niiya, Yu; Thelwall, Michael; Ko, Michael; Knutson, Brian; Tsai, Jeanne L (American Psychological Association, 2021-12-31)
      Although social media plays an increasingly important role in communication around the world, social media research has primarily focused on Western users. Thus, little is known about how cultural values shape social media behavior. To examine how cultural affective values might influence social media use, we developed a new sentiment analysis tool that allowed us to compare the affective content of Twitter posts in the United States (55,867 tweets, 1888 users) and Japan (63,863 tweets, 1825 users). Consistent with their respective cultural affective values, U.S. users primarily produced positive (vs. negative) posts, while Japanese users primarily produced low (vs. high) arousal posts. Contrary to cultural affective values, however, U.S. users were more influenced by changes in others’ high arousal negative (e.g., angry) posts, whereas Japanese were more influenced by changes in others’ high arousal positive (e.g., excited) posts. These patterns held after controlling for differences in baseline exposure to affective content, and across different topics. Together, these results suggest that across cultures, while social media users primarily produce content that supports their affective values, they are more influenced by content that violates those values. These findings have implications for theories about which affective content spreads on social media, and for applications related to the optimal design and use of social media platforms around the world.
    • Managing COVID-19 related knowledge in the UK Infrastructure sector

      Jallow, Haddy; Renukappa, Suresh; Suresh, Subashini; Algahtani, Khaled (Academic Conferences International, 2021-12-31)
      COVID-19 has caused the most serious economic and health crisis globally that we have witnessed in decades. Millions of people across the world have lost jobs, while the healthcare systems are struggling to cope with the rapid increase in cases. Many sectors have been affected with this pandemic including the construction infrastructure sector which benefits from engineers and different staff members travelling to site and interacting/collaborating with peers. Infrastructure construction organisations have responded well during the pandemic in order to carry on works while minimising risks to their employees and their families, however management styles have had to be updated and the transferring/ storage and collection of knowledge has seen new processes and methods being adopted. The relationship between Knowledge and its management within the infrastructure sector during the COVID-19 Pandemic is a topic that has not been regularly researched. This paper aims to review both the impact that COVID-19 has had within the infrastructure sector and Knowledge Management during these times attempting to gain an output of how knowledge has been managed throughout the pandemic within the sector.
    • Sustainable transformation of Qatar oil and gas industry: An organisational cultural perspective

      Sarrakh, Redouane; Renukappa, Suresh; Suresh, Subashini (British Academy of Management, 2021-12-31)
      Sustainable development and sustainability are concepts that are gaining a lot of popularity recently, mainly due to the increasing concerns regarding business and the environment relationship. Following the footsteps of the world, Qatar commitment towards sustainability was confirmed with the introduction of the Qatar National Vision 2030 and different National Development Strategies, where the Qatar leadership had outlined its development goals for the next generations to incorporate the concept of sustainable development. Such decisions induce changes within the country’s local, regional and national industry sector and especially oil and gas. The pathway for a successful implementation of sustainability strategies within organisations in the sector depends heavily on the alignment of the organisational culture with such change. Therefore, this paper provides a in depth view of the cultural changes the Qatar oil and gas sector underwent to manage the adaption of sustainability initiatives. The paper adopted a qualitative approach for the data collection process, interviewing 24 professionals from eight different Qatar oil and gas organisations. A thematic analysis was carried out to analyse the results and findings shows that important cultural changes had been experienced within the sector since the organisations’ decision to implement sustainability. Four cultural changes identified to be adapted in the Qatar oil and gas sector and are: behavioural change, leadership attitude, shareholders’ attitude and inter-organisational collaboration. Sustainability is not a stand-alone issue, but a dimension of management culture. As such, sustainability-related skills will have to reach further than personal relations skills.
    • Managing knowledge in the context of smart cities: a systematic review

      Abdalla, Wala; Renukappa, Suresh; Suresh, Subashini; Al Nabt, Saeed (Academic Conferences International, 2021-12-31)
      The most recent view on smart city development has recognized that the level of technology adoption in urban contexts is no more able to reflect the real smartness of cities. Smart cities is seen as a centre of knowledge, education, and creativity. The development of smart cities is becoming more and more knowledge based. As a result, knowledge has been perceived as the core component that makes cities smart. Hence, to take advantage of the opportunities that knowledge-based economy and society can bring to the city, leaders and decision makers need to develop cities that take advantage of local knowledge and intellectual capital of the population. Therefore, they need to take initiative to adapt Knowledge Management (KM) in smart cities development. Smart cities KM offers the means to create valuable knowledge that brings consistent and sustainable added value that can therefore be useful in avoiding strategic risk, better-informed decision, and finding smart and effective business solutions. However, smart cities is a relatively new concept that still raises many questions related to its relevance in knowledge management studies. This often calls for the creation, use, capture and exploitation of new knowledge. Therefore, managing this knowledge is considered an important source of sustainable competitive advantage. However, only a few studies in the academic literature on smart city initiatives address issues related to managerial and knowledge management perspectives. This paper investigates the underlying dynamics behind KM and the need for successful implementation of KM strategies within the context of smart cities. The findings are in the main, based on thorough review of literature. It reviews the concept of smart cities and KM. The paper concludes that effectiveness of smart cities knowledge creation, exploitation and management significantly influences on effectiveness of smart city development. Therefore, smart cities governance must be able to exploit and manage knowledge that results from smart cities development.
    • Fuzzy-logic approach for traffic light control based on IoT technology

      Hewei, Guan; Sadiq, Ali Safaa; Tahir, Mohammed Adam (Springer, 2021-12-31)
      Traffic congestion is an extremely common phenomenal issue, it occurs in many cities around the world, especially in those cities with high car ownership. Traffic congestion not only causes air pollution and fuel wastage, but it also leads to an increased commuting time and reduces the work time availability. Due to these reasons, traffic congestion needs to be controlled and reduced. The traffic light is the most widely adopted method to control traffic, however, most traffic lights in use are designed based on the predefined interval, which cannot cope with traffic volume change very well. Therefore, Internet of Things (IoT) based traffic lights or adaptive traffic lights are developed in the recent years as a complement of the traditional traffic lights. The adaptive traffic light can be built based on monitoring current traffic situation or using Vehicle-to-Vehicle and Vehicle-to-Infrastructure communication. In this paper, a new design of adaptive traffic light is proposed, this traffic light system is based on fuzzy logic and it introduces volunteer IoT agent mechanism, which introduces more accurate results.
    • PlenoptiCam v1.0: A light-field imaging framework

      Hahne, Christopher; Aggoun, Amar (IEEE, 2021-12-31)
      Light-field cameras play a vital role for rich 3-D information retrieval in narrow range depth sensing applications. The key obstacle in composing light-fields from exposures taken by a plenoptic camera is to computationally calibrate, re-align and rearrange four-dimensional image data. Several attempts have been proposed to enhance the overall image quality by tailoring pipelines dedicated to particular plenoptic cameras and improving the color consistency across viewpoints at the expense of high computational loads. The framework presented herein advances prior outcomes thanks to its cost-effective color equalization from parallax-invariant probability distribution transfers and a novel micro image scale-space analysis for generic camera calibration independent of the lens specifications. Our framework compensates for artifacts from the sensor and micro lens grid in an innovative way to enable superior quality in sub-aperture image extraction, computational refocusing and Scheimpflug rendering with sub-sampling capabilities. Benchmark comparisons using established image metrics suggest that our proposed pipeline outperforms state-of-the-art tool chains in the majority of cases. The algorithms described in this paper are released under an open-source license, offer cross-platform compatibility with few dependencies and a graphical user interface. This makes the reproduction of results and experimentation with plenoptic camera technology convenient for peer researchers, developers, photographers, data scientists and others working in this field.
    • Enhancing learning opportunities in higher education: best practices that reflect on the themes of the National Student Survey, UK

      Gomis, Muhandiramge Kasun Samadhi; Saini, Mandeep; Pathirage, Chaminda; Arif, Mohammed (Emerald, 2021-12-31)
      Purpose: This study assessed 'Learning Opportunities' provided to the undergraduate students, from level three to six, in Higher Education (HE). A knowledge gap was identified within the current practice relating to learning opportunities for Built Environment (BE) students in HE. The study focused on the themes under section two of the National Student Survey (NSS): how students explore ideas or concepts in-depth, bring information and ideas together from different topics, and apply the learned content in a real-life context. The study aimed to provide recommendations for enhancing 'Learning Opportunities' to the BE students within HE. Methodology: Data collection focused on section two of NSS ‘Learning Opportunities’ and documentary analysis, and a qualitative survey was adopted for this study. A documental analysis of 334 Mid Module Reviews (MMR’s) was carried out. The qualitative data was collected from level three to level six students and academics from Architecture, Construction Management, Civil Engineering and Quantity Surveying disciplines representing BE context. A sample of 40 students and 15 academics, including a Head of school, a Principal lecturer, Subject leads and lecturers, participated in interviews as part of a qualitative survey. Twelve drivers were developed using the data obtained through literature, documental analysis, and interviews. These drivers were analysed using manual content analysis to identify their influence on the specified themes under NSS section two and circulated among academics to be ranked by identifying its’ influence to promote learning opportunities to BE students in HE. Findings: This study highlighted twelve drivers which promote learning opportunities in HE within BE curriculum. Findings established that topics should be explained with more real-life or industry-orientated concepts such as simplification integrated into module delivery. Contrary to the literature, the use of physical materials (i.e. handouts and whiteboard) in addition to Virtual Learning Environment (VLE) for detailed explanations were considered effective in exploring concepts. During the current COVID-19 pandemic, context-based learning needs to be promoted by integrating videos of practical implementation for better understanding. The study recognised that lab, fieldwork and tutorials were essential to apply what students have learned in BE curricula to a real-life context. Originality/Value: This study identified current learning approaches and provided recommendations to improve the BE students learning experience in HE. The identified twelve drivers would significantly help academics and academic institutions to understand how learning opportunities should be facilitated in the BE curriculum to enhance student performances in HE. Conclusion: Study identified twelve drivers that significantly contribute towards enhancing learning opportunities for BE students in the current HE context. It concludes that certain drivers should be prioritised in enhancing learning opportunities provided in BE curriculum. The study recommends that using traditional and VLE is essential to implement identified drivers and enhance the learning opportunities provided.