E-Jurnal Universitas Tunas Husada Tasikmalaya
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22393 research outputs found
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“It’s being a part of a grand tradition, a grand counter-culture which involves communities”: A qualitative investigation of autistic community connectedness
No full textAutistic people report greater comfort socialising and easier communication with each other. Despite autism being stereotypically associated with lack of social motivation, an autistic community has been described briefly in the literature but is not well understood. Autistic community connectedness may play a role in promoting wellbeing for autistic people. This qualitative study involved interviewing autistic individuals (N = 20) in-person, via a video-based platform, a text-based platform, or over email to investigate autistic community connectedness. Critical grounded theory tools were used to collect and analyse the data. There were three elements of autistic community connectedness: Belongingness, social connectedness, and political connectedness. Belongingness referred to the sense of similarity that autistic people experienced with each other. Social connectedness referred to specific friendship participants formed with other autistic people. Political connectedness referred to a connectedness to the political or social equality goals of the autistic community. Participants described the benefits of autistic community connectedness as being increased self-esteem, a sense of direction, and a sense of community not experienced elsewhere. Lack of connectedness involved ambivalence with an autistic identity and/or feelings of internalised stigma. Experiences of autistic community connectedness may have implications for autistic people’s wellbeing, as well as how they cope with minority stress
Training needs assessment of veterinary practitioners in Ethiopia
No full textPastoral and agro-pastoral farming are extensively practised in Ethiopia, and the main livestock kept are cattle, goats, sheep, poultry, and camels. The livestock sector is faced with complex challenges including limited availability of well-trained and skilled animal health professionals. The objective of this study was to identify and prioritise areas for training with the goal of providing evidence to guide strategies to improve the skills, delivery, and governance of veterinary services across Ethiopia. A cross-sectional survey was developed and administered electronically to veterinary professionals in Ethiopia using the Qualtrics platform. Data were collected on select parameters including demographics, diseases of economic significance, diagnosis, disease prevention, biosecurity, disease control, treatment, epidemiology, One Health, disease reporting, and the participants’ opinions about training. The survey data was downloaded in Microsoft Excel and descriptive statistics performed. A total of 234 veterinary professionals completed the survey. Most participants were male (89.7%) and aged between 26 and 35 years (81.2%). Of the total respondents, 56.4% worked in government and 8.5% in private practice. Most participants perceived training on laboratory diagnostic testing, disease prevention, antimicrobial resistance, antibiotic sensitivity testing, basic epidemiology, and clinical procedures, as most beneficial. In addition, most respondents would like to receive training on diseases affecting cattle, poultry, and small ruminants. The findings from this study provide baseline information on priority training areas for veterinary professionals and could potentially contribute to national efforts to develop and implement a continuing professional development programme in the veterinary domain, in view of improving veterinary service delivery. © 2022, The Author(s)
A Holistically Designed Hyperspectral Imager For CubeSats
No full text"CubeSat-based Hyperspectral Imagers have become an attractive concept to Earth Observation scientists in recent years, due to the potential of providing cost-effective constellations of satellites with hyperspectral capability. This will be beneficial to applications such as precision agriculture and disaster relief, where increased temporal resolution measurements and rapid response to information request is more critical. However, the challenges of providing science-grade Earth Observation data from CubeSats are great and varied, not only because of the physical size of the instrument, but because of the operational constraints of the CubeSat, such as limited physical pointing stability/accuracy and restricted data downlink budgets.The objective of this research is to investigate the problem holistically; rather than focussing only on the physical size of the instrument, the operational constraints of the CubeSat platform have been considered since design inception, allowing for the investigation of ways to mitigate these issues within the optical design of the instrument itself. In addition, the cost of the instrument must also be kept within the resources of a typical university CubeSat budget.To this end, the compact hyperspectral imager prototype CHAFF (CubeSat Hyperspectral Application For Farming) has been designed, developed and constructed with commercial off-the-shelf optics at Surrey Space Centre, in collaboration with the National Physical Laboratory (NPL). As part of the holistic design methodology, CHAFF aims to mitigate the pointing instability of the CubeSat via optically-aided image co-registration, allowing for automatic co-registration and data cube construction on-board the satellite. This in turn will improve the performance of lossless, predictive image compression schemes operating on the data cube, thus mitigating the data downlink bottleneck.Laboratory and field trials have shown that CHAFF has achieved good optical quality, with a spectral resolution of 3.46 nm at 546 nm. In addition, the image processing chain, including the optically-aided image co-registration, has been observed to improve the motion-induced distortion, by approximately a factor of 12.
‘What is the matter with me?’ or a ‘badge of honour’: Nurses’ constructions of resilience during Covid-19.
No full textAbstract It has long been known that nursing work is challenging and has the potential for negative impacts. During the COVID-19 pandemic most nurses’ working landscapes altered dramatically and many faced unprecedented challenges. Resilience is a contested term that has been used with increasing prevalence in healthcare with health professionals encouraging a ‘tool-box’ of stress management techniques and resilience-building skills. Drawing on narrative interview data (n=27) from the Impact of Covid on Nurses (ICON) qualitative study we examine how nurses conceptualised resilience during COVID-19 and the impacts this had on their mental wellbeing. We argue here that it is paramount that nurses are not blamed for experiencing workplace stress when perceived not to be resilient ‘enough’, particularly when expressing what may be deemed to be normal and appropriate reactions given the extreme circumstances and context of the COVID-19 pandemic. </p
Optimal Strategies for Cyber Security Decision-Making
No full textOne of the major concerns of organisations is how to protect themselves from the growing volume and sophistication of cyber attacks. In this context, methodologies, models, and frameworks must be developed to support decision makers in managing cyber risk. This dissertation presents novel models based on game theory and combinatorial optimisation to support cyber security decisions. In particular, this dissertation is composed of four distinct contributions.The first contribution extends an existing model to study the optimal selection of cyber security controls. In particular, we use game theory and combinatorial optimisation to determine the best combination of subcontrols for the Critical Internet Security (CIS) Control 17, which deals with implementing security awareness and training programmes for employees. The developed framework has assumed a healthcare scenario to protect the information and communication technology (ICT), clinical, and administrative personnel from social engineering attacks. Numerical illustrations show that the Nash defending strategies are consistently better (or at least as good as) than other competing strategies for different attacker profiles. Finally, alternative investment strategies on different Nash equilibria and the optimal choices are presented and discussed using the framework.The second contribution considers how the uncertainty of time required to exploit a vulnerability in a multi-stage cyber attack influences the optimal cyber security investment decisions. We develop two approaches for optimal investment in cyber security controls subject to a budget. To compare these approaches, we design and develop a decision support tool and a case study using the 2020 Common Weakness Enumerations (CWE) top 25 most dangerous software weaknesses and the CIS Controls. The solution highlights the cyber security investment strategies that fit various objectives of decision makers. These strategies provide cost-efficient solutions to counteract the most common cyber attacks.The third contribution addresses the challenge of designing effective honeypots to deceive attackers and collect threat intelligence. We present two novel game theoretic models for the selection and configuration of honeypots. The interaction between the network administrator (defender) and the attacker is modelled as aBayesian game with players having limited information about their opponent’s action. The first model details the selection of the best type of honeypot to deploy in a Smart Grid. The second model extends the core idea of the first model by considering a multi-phase attack scenario. It presents a deception framework to assist with the cost-effective selection of a honeypot type to implement, and, in particular, to determine the optimal honeypot configuration for strategic deployment in an Internet of Vehicle network. Through the use cases, we demonstrate how these models can assist in determining the optimal honeypot configuration to satisfy various purposes of using honeypots.The final contribution considers how often should cyber insurers audit to deter policyholders from misrepresenting their security levels to gain premium discounts. Cyber insurers offer discounts to policyholders based on their security posture and often rely on self-reports that controls are in place. Interviewing underwriters and reviewing regulatory filings has revealed concerns about whether security policies were complied with within reality. The post-incident claims management process is modelled as a Bayesian game of incomplete information to assist insurers in determining an optimal audit strategy. This work is the first theoretical consideration of post-incident claims management in cyber security. Simulation results demonstrate that common-sense techniques are not as efficient at providing effective cyber insurance audit decisions as ones computed using game theory
An integrated analysis and comparison of serum, saliva and sebum for COVID-19 metabolomics
No full textAbstract The majority of metabolomics studies to date have utilised blood serum or plasma, biofluids that do not necessarily address the full range of patient pathologies. Here, correlations between serum metabolites, salivary metabolites and sebum lipids are studied for the first time. 83 COVID-19 positive and negative hospitalised participants provided blood serum alongside saliva and sebum samples for analysis by liquid chromatography mass spectrometry. Widespread alterations to serum-sebum lipid relationships were observed in COVID-19 positive participants versus negative controls. There was also a marked correlation between sebum lipids and the immunostimulatory hormone dehydroepiandrosterone sulphate in the COVID-19 positive cohort. The biofluids analysed herein were also compared in terms of their ability to differentiate COVID-19 positive participants from controls; serum performed best by multivariate analysis (sensitivity and specificity of 0.97), with the dominant changes in triglyceride and bile acid levels, concordant with other studies identifying dyslipidemia as a hallmark of COVID-19 infection. Sebum performed well (sensitivity 0.92; specificity 0.84), with saliva performing worst (sensitivity 0.78; specificity 0.83). These findings show that alterations to skin lipid profiles coincide with dyslipidaemia in serum. The work also signposts the potential for integrated biofluid analyses to provide insight into the whole-body atlas of pathophysiological conditions
Towards standardizing retinal optical coherencetomography angiography: a review
No full textThe visualization and assessment of retinal microvasculature are important in the study, diagnosis, monitoring, and guidance of treatment of ocular and systemic diseases. With the introduction of optical coherence tomography angiography (OCTA), it has become possible to visualize the retinal microvasculature volumetrically and without a contrast agent. Many lab-based and commercial clinical instruments, imaging protocols and data analysis methods and metrics, have been applied, often inconsistently, resulting in a confusing picture that represents a major barrier to progress in applying OCTA to reduce the burden of disease. Open data and software sharing, and cross-comparison and pooling of data from different studies are rare. These inabilities have impeded building the large databases of annotated OCTA images of healthy and diseased retinas that are necessary to study and define characteristics of specific conditions. This paper addresses the steps needed to standardize OCTA imaging of the human retina to address these limitations. Through review of the OCTA literature, we identify issues and inconsistencies and propose minimum standards for imaging protocols, data analysis methods, metrics, reporting of findings, and clinical practice and, where this is not possible, we identify areas that require further investigation. We hope that this paper will encourage the unification of imaging protocols in OCTA, promote transparency in the process of data collection, analysis, and reporting, and facilitate increasing the impact of OCTA on retinal healthcare delivery and life science investigations
Next Generation DES Simulation: A Research Agenda for Human Centric Manufacturing Systems
No full textIn this paper we introduce a research agenda to guide the development of the next generation of Discrete Event Simulation (DES) systems. Interfaces to digital twins are projected to go beyond physical representations to become blueprints for the actual “objects” and an active dashboard for their control. The role and importance of real-time interactive animations presented in an Extended Reality (XR) format will be explored. The need for using game engines, particularly their physics engines and AI within interactive simulated Extended Reality is expanded on. Importing and scanning real-world environments is assumed to become more efficient when using AR. Exporting to VR and AR is recommended to be a default feature. A technology framework for the next generation simulators is presented along with a proposed set of implementation guidelines. The need for more human centric technology approaches, nascent in Industry 4.0, are now central to the emerging Industry 5.0 paradigm; an agenda that is discussed in this research as part of a human in the loop future, supported by DES. The potential role of Explainable Artificial Intelligence is also explored along with an audit trail approach to provide a justification of complex and automated decision-making systems with relation to DES. A technology framework is proposed, which brings the above together and can serve as a guide for the next generation of holistic simulators for manufacturing