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Comparison of Artificial Intelligence Based Maximum Power Point Techniques for Photovoltaic systems
No full textMaximum Power Point Tracking technologies are being used in traditional PV system charge controllers to enhance the power conversion efficiency. An MPPT controller will ensure power extracted from the PV panels during varying climatic conditions is always maximum. This will ensure that maximum power is flowing between the panel and load. As both Temperature and Irradiation levels vary during the day, maximum power point trackers are an inevitable component in a PV system. As solar energy holds a major share in renewable energy in the world market, an improvement in MPPT technique makes the efficiency of the PV system increase and in turn cost reduction possible. However, the efficiency of conventional MPPT Techniques suffers from failing in tracking MPPT at fast varying climatic conditions and falling in local maxima of maximum power point than global maxima. The issues of stability, tracking speed, and accuracy can be solved using intelligent MPPT techniques methods based on soft computing tools: Therefore, this paper aims to study and provide a comparative analysis of two AI-based MPPT techniques such as ANN and ANFIS. The MPPT techniques considered in this study are ANN and ANFIS. Performance evaluation is carried out using MATLAB Simulation. Experimental results indicate that the two methods ANN and ANFIS are more efficient than conventional MPPT techniques due to its capability to avoid local MPP and partially shaded conditions.Maximum Power Point Tracking technologies are being used in traditional PV system charge controllers to enhance the power conversion efficiency. An MPPT controller will ensure power extracted from the PV panels during varying climatic conditions is always maximum. This will ensure that maximum power is flowing between the panel and load. As both Temperature and Irradiation levels vary during the day, maximum power point trackers are an inevitable component in a PV system. The renewable energy source has a vital role in supplying sustainable power to meet the rising electricity demands. However, the PV system performance heavily depends on environmental conditions. This, in turn, causes efficiency to be less and in turn higher cost. For maximum power to be transferred from the PV panels under varying climatic conditions PV systems should operate at Maximum Power Point
An autoethnographic study of a research and teaching for transformative Education Journey in Foundation law teaching – preparing diverse students for law school
No full textThis article presents the findings of an auto ethnographic study of adopted changes in teaching practice within a preparatory foundation module in law at a small to medium sized university in England and Wales. The emphasis of this study is placed on the development or redevelopment of effective learning environments and effective and inclusive teaching, learning, assessment and feedback practices. In particular, the focus on inclusion has formed the main theme in the objective of solving the disparities in terms of literacy and learning skills amongst a cohort of learners with diverse skills bases to build upon. This study has found that most notably, linguistic ability presents a divide within the experienced classroom. The study has revealed best practice in relation to closing the linguistic gaps for EU and International students. This category of student has benefitted most the adopted approaches and methods, Nevertheless, the approaches taken do not compromise the quality or the content of lectures, whereby the initial learning plan based on the SOLO taxonomy is still able to render the desired learning outcomes. This contributes to enhancing inclusivity within the curriculum. The study also finds that motivation is a vital factor in the successful implementation of inclusive learning environments from which all students, regardless of their ethnic and linguistic backgrounds can benefit equally
Die echte „Gretchen-Tragödie“
No full textThe real "Gretchen tragedy": An examination of child murder in the early modern era using the example of Susanna Margaretha Brand / Alicia Danielsso
The feeling's mutual
No full textThe impact of COVID-19 has shown that mutual aid groups like AA may be even more beneficial than we realised, say Lisa Ogilvie and Jerome Carson
Work-family conflict and the role of socio-cultural factors : the case of the Nigerian migrant women in the Irish healthcare sector
No full textSystemic review of studies on work-family conflict (WFC) demonstrate that high levels of stress and mental health problems are some of the consequences of WFC and also two well known risk factors for suicide amongst health care workers. Studies have also evidenced that female healthcare workers have a higher suicide rate than the national average as result of intensified WFC. The office for National statistics has noted a 20% increase in mental health problems and suicide rate in the industry since the start of the Covid19 pandemic. There is no doubt that WFC has been an enduring preoccupation of researchers considering its ominous consequences. However, majority of the studies and findings continue to assume that individuals live and function within a single culture and overlook the fact that globalisation has resulted in an ethnic diverse and multi-cultural workforce especially in the Western world. For instance, ethnic black/African-American women are reported to suffer depression or decreases in psychological well-being at disparate rates when compared with white women implying a higher susceptibility to WFC. Despite these emerging facts and globalisation with its attendant growing migrant population, very little is known about the work-family conflict (WFC) experiences of ethnic migrant sub-groups across diverse cultural contexts such as the migrant Nigerians in the Irish healthcare sector. This has left a void in the knowledge of WFC for this group despite their preponderance in the healthcare sector. This study therefore, sought to help fill a critical gap in work-family conflict research by exploring the experiences of WFC amongst this group
Blockchain-based security mechanism for the medical data at fog computing architecture of internet of things
No full textThe recent developments in fog computing architecture and cloud of things (CoT) technology includes data mining management and artificial intelligence operations. However, one of the major challenges of this model is vulnerability to security threats and cyber-attacks against the fog computing layers. In such a scenario, each of the layers are susceptible to different intimidations, including the sensed data (edge layer), computing and processing of data (fog (layer), and storage and management for public users (cloud). The conventional data storage and security mechanisms that are currently in use appear to not be suitable for such a huge amount of generated data in the fog computing architecture. Thus, the major focus of this research is to provide security countermeasures against medical data mining threats, which are generated from the sensing layer (a human wearable device) and storage of data in the cloud database of internet of things (IoT). Therefore, we propose a public-permissioned blockchain security mechanism using elliptic curve crypto (ECC) digital signature that that supports a distributed ledger database (server) to provide an immutable security solution, transaction transparency and prevent the patient records tampering at the IoTs fog layer.The blockchain technology approach also helps to mitigate these issues of latency, centralization, and scalability in the fog model
Risk assessment models for venous thromboembolism in hospitalised adult patients: a systematic review
No full textIntroduction Hospital-acquired thrombosis accounts for a large proportion of all venous thromboembolism (VTE), with significant morbidity and mortality. This subset of VTE can be reduced through accurate risk assessment and tailored pharmacological thromboprophylaxis. This systematic review aimed to determine the comparative accuracy of risk assessment models (RAMs) for predicting VTE in patients admitted to hospital.Methods A systematic search was performed across five electronic databases (including MEDLINE, EMBASE and the Cochrane Library) from inception to February 2021. All primary validation studies were eligible if they examined the accuracy of a multivariable RAM (or scoring system) for predicting the risk of developing VTE in hospitalised inpatients. Two or more reviewers independently undertook study selection, data extraction and risk of bias assessments using the PROBAST (Prediction model Risk Of Bias ASsessment Tool) tool. We used narrative synthesis to summarise the findings.Results Among 6355 records, we included 51 studies, comprising 24 unique validated RAMs. The majority of studies included hospital inpatients who required medical care (21 studies), were undergoing surgery (15 studies) or receiving care for trauma (4 studies). The most widely evaluated RAMs were the Caprini RAM (22 studies), Padua prediction score (16 studies), IMPROVE models (8 studies), the Geneva risk score (4 studies) and the Kucher score (4 studies). C-statistics varied markedly between studies and between models, with no one RAM performing obviously better than other models. Across all models, C-statistics were often weak (0.8). Similarly, estimates for sensitivity and specificity were highly variable. Sensitivity estimates ranged from 12.0% to 100% and specificity estimates ranged from 7.2% to 100%.Conclusion Available data suggest that RAMs have generally weak predictive accuracy for VTE. There is insufficient evidence and too much heterogeneity to recommend the use of any particular RAM
COVID-19 impact on air quality and associated elements: knowledge data of the Emirate of Ajman − UAE
No full textAir pollution is one of the core issues at the local and global levels and maybe “one of the most important contributors” to deaths. According to the United Nations, air pollution is one of the extreme environmental threats to health globally. Air pollution problems increased worldwide due to the massive emission volumes generated every day from the increased lifestyle associated technology. The air pollutants are not only dangerous to the health and wellbeing of plants, animals, and people, but they are also harmful to the environment as a significant contributor to recent climate change. The reduction in the volume of pollutants produced is a crucial and challenging step in managing our adverse effects on the environment and climate. The primary outdoor pollution sources include vehicles, Industry, power generation, building heating/cooling systems, and agriculture/waste incineration. The regulation, policies, clean production, investments supporting cleaner transport, energy-efficient housing, power generation, Industry, and better municipal waste management can effectively reduce critical sources of ambient air pollution. When many countries of the world are fighting the Coronavirus, as a challenge to limit its spread, because of its negative repercussions on the economy, health, and political stability as well, several reports have emerged confirming that the spread of the virus has positive effects on the climate change crisis through its impact on the demand for energy and greenhouse gas emissions in endemic countries. Ajman is an emirate that has experienced considerable change in the level of air-associated pollution. Therefore, this article aims to assess air quality impacts in the Ajman Emirates during the lockdown when social distancing was implemented, and human activities were significantly eliminated. Moreover, it seeks to identify the percentages of the improved outdoor pollutants concentrations and the general air quality index. This paper shows evidence from live measurements that the Emirate has recorded over four months since the lockdown was imposed at this Emirate and compared with similar months of the previous year. Moreover, it indicates that having climate improvement exists for specific periods could well support the fight against the COVID-19. The article clearly shows results with a significant reduction of more than 40% of each air-associated pollution element during the pandemic compared with similar periods in 2018 and 2019
Acoustics Based Monitoring and Diagnostics for the Progressive Deterioration of Helical Gearboxes
No full textGearbox condition monitoring (CM) plays a significant role in ensuring the operational reliability and efficiency of a wide range of critical industrial systems such as wind turbines and helicopters. Accurate and timely diagnosis of gear faults will improve the maintenance of gearboxes operating under sub-optimal conditions, avoid excessive energy consumption and prevent avoidable damages to systems. This study focuses on developing CM for a multi-stage helical gearbox using airborne sound. Based on signal phase alignments, Modulation Signal Bispectrum (MSB) analysis allows random noise and interrupting events in sound signals to be suppressed greatly and obtains nonlinear modulation features in association with gear dynamics. MSB coherence is evaluated for selecting the reliable bi-spectral peaks for indication of gear deterioration. A run-to-failure test of two industrial gearboxes was tested under various loading conditions. Two omnidirectional microphones were fixed near the gearboxes to sense acoustic information during operation. It has been shown that compared against vibration based CM, acoustics can perceive the responses of vibration in a larger areas and contains more comprehensive and stable information related to gear dynamics variation due to wear. Also, the MSB magnitude peaks at the first three harmonic components of gear mesh and rotation components are demonstrated to be sufficient in characterizing the gradual deterioration of gear transmission. Consequently, the combining of MSB peaks with baseline normalization yields more accurate monitoring trends and diagnostics, allowing the gradual deterioration process and gear wear location to be represented more consistently
The stress state of the fraenal notch region in complete upper dentures
No full textThe present study determines the stress field in the region of the labial flange of the complete upper denture (CUD).Using commercial edentulous molds and standardized procedures eight identical CUDs were fabricated with an initial fraenal notch of 5 mm. Three addition notch conditions were produced by deepening the notch two times giving a total depth of the notch of 7 and 9 mm respectively. Finally an incisal diastema of 7 mm was created in every CUD.Three elements rosette strain gauge was cemented onto the midline of each denture specimen near the fraenal notch, for calculating the two principal stresses and the maximum shear stress.It is less possible that a failure crack in a CUD will be initiated from the region of the fraenal notch, due to the compressive nature of the principal stresses (they are varied significantly among the four notch conditions with P = 0.035 for σ1 and P = 0.007 for σ2) and the low value of the maximum shear stress. The creation of an incisal diastema significantly decreased the values of the principal stresses σ1 (P = 0.012) and σ2 (P = 0.025). Further investigation is needed to detect the region of the CUD where a failure crack may be initiated