2821 research outputs found
Sort by
Effective house price prediction using machine learning
No full textIn recent times, there have been a surge in the housing business, such that prediction of houses is of utmost important both for the seller and the potential buyer. This has been influenced by several key indices. Many approaches have been used to tackle the issue of predicting house prices to help the house owners and real estate agents maximise their profit while the prospective buyers make better informed decision. This study focuses on building an effective model for the prediction of house prices. Since price is a continuous variable, it was expedient we used regression models. Some regression models like linear regression, Random Forest regressor (RF), Extreme Gradient Boosting Regressor (XGBoost), Support Vector Machine (SVM) regressor, K-Nearest Neighbor (KNN) and Linear regression were employed. The result showed that Random Forest Regressor showed a superior performance having an R2 score of 99.97% while SVM regressor performed poorly with an R2 score of −4.11%. The result proved that Random Forest regressor as an effective machine learning model to predicting house prices
The role of blockchain technology and student coin case in Saudi Arabia's higher education sector. The challenge of achieving 2030 vision
No full textAt present, researchers and practitioners are increasingly interested in blockchain technology. This is due to its unique characteristics, including safety, regionalisation, dependability, and data security. Even with the increased attention and engagement, few individuals are aware of the present state of knowledge and usage of Blockchain (BC) technology, more so in the context of higher education in the Kingdom of Saudi Arabis. This paper offers a comprehensive evaluation of prior research pertaining to blockchain-based educational applications. It focuses on three primary themes: (1) educational applications and its use created by using blockchain technology, (2) the advantages of blockchain technology in higher education and (3) the adoption area in higher education challenges and problems of blockchain technology. Detailed analysis of the results for each topic and an in-depth discussion was carried out based on the survey results. This study also sheds light on other crucial areas of education where blockchain technology might help
Predicting and curing depression using long short term memory and global vector
Full text linkIn today’s world, there are many people suffering from mental
health problems such as depression and anxiety. If these conditions are not
identified and treated early, they can get worse quickly and have far-reaching
negative effects. Unfortunately, many people suffering from these conditions,
especially depression and hypertension, are unaware of their existence until the
conditions become chronic. Thus, this paper proposes a novel approach using
Bi-directional Long Short-Term Memory (Bi-LSTM) algorithm and Global
Vector (GloVe) algorithm for the prediction and treatment of these conditions.
Smartwatches and fitness bands can be equipped with these algorithms which
can share data with a variety of IoT devices and smart systems to better
understand and analyze the user’s condition. We compared the accuracy and
loss of the training dataset and the validation dataset of the two models
namely, Bi-LSTM without a global vector layer and with a global vector layer.
It was observed that the model of Bi-LSTM without a global vector layer had
an accuracy of 83%, while Bi-LSTM with a global vector layer had an accuracy
of 86% with a precision of 86.4%, and an F1 score of 0.861. In addition to
providing basic therapies for the treatment of identified cases, our model also
helps prevent the deterioration of associated conditions, making our method
a real-world solution
The United Kingdom’s National Early Warning Score: should everyone use it? A narrative review
No full textThis review critiques the benefits and drawbacks of the United Kingdom’s National Early Warning Score (NEWS). Potential developments for the future are considered, as well as the role for NEWS in an emergency department (ED). The ability of NEWS to predict death within 24 h has been well validated in multiple clinical settings. It provides a common language for the assessment of clinical severity and can be used to trigger clinical interventions. However, it should not be used as the only metric for risk stratification as its ability to predict mortality beyond 24 h is not reliable and greatly influenced by other factors. The main drawbacks of NEWS are that measuring it requires trained professionals, it is time consuming and prone to calculation error. NEWS is recommended for use in acute UK hospitals, where it is linked to an escalation policy that reflects postgraduate experience; patients with lower NEWS are first assessed by a junior clinician and those with higher scores by more senior staff. This policy was based on expert opinion that did not consider workload implications. Nevertheless, its implementation has been shown to improve the efficient recording of vital signs. How and who should respond to different NEWS levels is uncertain and may vary according to the clinical setting and resources available. In the ED, simple triage scores which are quicker and easier to use may be more appropriate determinants of acuity. However, any alternative to NEWS should be easier and cheaper to use and provide evidence of outcome improvement
Digital transformations in medical applications using audio and virtual reality procedures
No full textNumerous members of society struggle with health care issues, and despite the use of sensing
technology, diseases in the body are still unable to be detected. The main cause of this
identification process failure is the absence of any recognized virtual technology on the market.
The majority of health care solicitations seek to create a specific application that simply delivers
data on sensing values and ignores the virtual representation of those values. So, in order to
detect the existence of viruses inside the body, this article offers an integration platform that
links sensing devices with Virtual/Audio Reality (VR/AR) approaches. Additionally, a specific
form of swarm intelligence algorithm known as Fruit Fly (FF) is used in the recognition process
with a modified fitness function. The FF technique offers a lot of low layer awareness, which
improves the output for efficient operation. The proposed AR/VR technique is used with
biological sensors to analyze the real-time situations, and five different case studies are divided.
It is logical to conclude from the experimental results that all validated case studies offer
excellent productivity and are adaptable to all environmental circumstances
Flourishing, psychological distress and internalized stigma among parents of an adult son or daughter with schizophrenia
Full text linkBackground:
Parents of adults diagnosed with schizophrenia, have been reported to have higher levels of psychological distress than the general population, and parents whose offspring have other mental or physical illnesses.
Aim:
This study examines the comparatively new construct of flourishing, and its relationship to internalized stigma and psychological distress.
Method:
A cross-sectional survey was conducted between July 2021 and March 2022, with an international sample of 200 parents of adult sons or daughters diagnosed with schizophrenia. Participants completed a demographic questionnaire and three standardized inventories. These were the PERMA Profiler, which measures flourishing, the CORE-10, which measures psychological distress, and a new parental Internalized Stigma Scale. Sample characteristics of individuals of schizophrenia and their parents were examined using descriptive statistics, and the contributing factors affecting stigma were assessed through regression analysis.
Results:
The initial hypothesis that parents scoring high on internalized stigma, would have significantly higher levels of psychological distress and lower levels of flourishing, than parents with low-level internalized stigma, was confirmed. Overall, the flourishing levels were lower and psychological distress higher in these parents, than those of the general population. Regression analysis identified psychological distress and hopefulness as the two major predictors of flourishing, though in different directions. Interestingly, stigma did not determine flourishing, in spite of their close relationship
Acute Medicine: How will we grow? - An analysis of organisational capabilities for quality improvement, research & education from SAMBA 2021"
No full textBackground: Education, research, and Quality Improvement (QI) are key enablers for high quality care. We aimed to map the capability of Acute Medical Units (AMUs) to facilitate excellence in these areas.
Methods: AMUs were surveyed in an organisational questionnaire within the Society for Acute Medicine Benchmarking Audit 2021.
Results: 143 units participated. 80 units had a QI lead, 24 had a research lead and 99 had a medical education lead. 15 units had all three leadership roles. Most QI work considered service structure rather than changes in processes or care outcomes.
Conclusion: The organisational capability of AMUs in the strategic areas considered is variable. Improving leadership and disseminating learning could help build a strategic foundation for acute medicine to grow
Competition anxiety in combat sports and the importance of mental toughness
Full text linkCombat sports require participants to engage in potentially dangerous forms of contact-based competition. Pressure to succeed, coupled with the risk of severe injury can induce significant
levels of anxiety, which if uncontrolled, can negatively impact performance and possibly promote
unsporting conduct. The present study examined competitive anxiety levels of combat sports athletes and determined whether self-reported scores were associated with mental toughness and
Sportspersonship attitudes. A cross-sectional survey design was used whereby participants (N = 194)
completed a battery of questionnaires measuring competitive combat sport experiences, demographic
details, Sportspersonship traits (compliance towards rules, respect for opponents, and game perspective), and competition anxiety (somatic, cognitive, and self-confidence; reported retrospectively).
Results suggest that mentally tough athletes experience lower levels of cognitive and somatic anxiety,
and higher self-confidence, prior to competitions. Findings also found that athletes endorsing more
altruistic and respectful attitudes in sport (Sportspersonship) reported higher levels of competition
anxiety. The findings demonstrate that mental toughness is allied to positive attributes and could
potentially be operationalized to improve both the retention and performance of combat sports
athletes. Thus, the authors advocate the use of mental toughness coaching interventions within
combat sport
ASPIRE to be different: enhancing skills with students: Briefing Note
Full text linkThis work forms the basis of a QAA funded project (Reference Number: 30427/001/2022). Drawing upon a heutagogical philosophy of learning, this briefing note proposes a learning model that enables students to develop social entrepreneurial skills and academic colleagues to develop pedagogic skills appropriate to their context and community. This model, A.SP.I.RE, provides an opportunity to develop a holistic perspective to enhancing entrepreneurial skills with students