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The impact of social media fitness pages on Irish women’s self-esteem, body-image and wellbeing
No full textThis study aimed to examine the impact of social media fitness pages on the self-esteem, body-image and wellbeing of adult Irish women. The research was a correlation design with a between groups aspect. Data was collected from N=80 participants using online questionnaires and analysed using Pearson’s R and Manova tests using SPSS. The results found there was no correlation between the following of social media fitness pages and women’s self-esteem, body-image and wellbeing. A correlation did exist between the number of fitness pages followed and the body esteem subscale of physical condition. The Manova identified that there was no difference between age groups and their reported levels of self-esteem, body-image and wellbeing, but there was a difference in levels of social media usage across the age groups. Further research using a larger number of participants would be beneficial to broaden this area of study in Ireland
Supervised binary image classification using machine learning and convolutional neural networks
No full textMachine Learning and Deep Learning Algorithms were investigated in terms of their ability to perform a supervised binary image classification task involving the Kaggle Dogs vs Cats dataset. Machine Learning algorithms struggled to achieve above 60% training accuracy. Though the CNNs tended to overfit, the inclusion of regularisation via dropouts reduced this effect and the optimal deep learning algorithm developed using Convolutional Neural Networks achieved a training accuracy of 96% and a validation accuracy using unlabelled images of 94%.
In a straight comparison the optimal CNN model had an AUC of 94% compared to 51% for kNN and 58% for Naive Bayes when tested using unseen data
Effectiveness and survival status of patients through robotic surgery in healthcare sector using machine learning algorithm
No full textMedicine has experienced greater scientific and technological advances in last few years than in the rest of human history. Ever since computer technology entered the operating room, surgery has gone through one of the greatest changes throughout medical life. The major potential of robotic surgery are precision and miniaturization. The exposure of Robotic surgery using machine learning techniques is used to predict survival status of patients with regards to classification of multiple feedback from people and effectiveness to people in surgeries can help to improve betterment of life in healthcare sector. This research includes data in the year of 2015 at the California Research development and health care service which has information about patients in terms of Robotic surgery. We used almost five machine algorithms mainly Random Forrest, MLP neural network, Naïve Bayes, KNN, SVM. Random Forrest and Naïve Bayes are best fit and ability to learn from data so accurately that gives better insights and results in terms of Usefulness of Robotic surgery in certain low dimension space. MLP neural network gives the better prediction and performance when survival status of patients is concerned. The overall execution of these 3 models are measured by confusion matrix and accuracy of each model. The accuracy given by these models conclude that MLP neural network (97%) , Naïve Bayes(95%) has best figures followed by Random Forrest(92%). Therefore, MLP Neural network with Random Forrest and Naïve Bayes are most suitable and optimised models for this specific study of prediction of Robotic surgery in respective cases
An exploration of the role of creativity in psychotherapy
No full textThis paper explores the role of creativity in psychotherapy with focus on the intrinsic and interpersonal application of creativity in this context. The objective is to understand if there is a need for creative training in psychotherapy training. It starts with an exploration of creativity in human behavior and how new ideas originate. Then it covers the interpersonal nature of creativity and the processes that underlie this with focus on the individuality as well as co-creation in the therapeutic space. Finally, it discussed the application of creativity in psychotherapy including the therapeutic alliance, leveraging intuition as well as its limitations
Network intrusion detection system using classification techniques in machine learning
No full textWorldwide, the Internet is connected across the country. There are threats of network
attacks in this Internet environment. The risk of integrity and con dentiality
has also increased with the density of information and global reach. Security breach
has become too easy. In these days the improvement of the network security is
therefore highlighted. Protection of the Network allow the unintended interference
to some form to network and avoid it. It consists of software for network intrusion
detection that track the network. NIDS is positioned in the network in a strategic
location to track tra c inside the network from source to destination apps.
The machine would optimally screen both inbound and outbound tra c, but that
would create a congestion that would hinder the system's overall pace. Finally,
these methods include machine learning algorithms that render the device
exible
and deliver reliable performance. Intrusion activities leave evidence in the auditing
data, so it is possible to learn and distinguish the pattern of ordinary and malicious
activities with machine learning algorithms.
Machine training techniques can learn normal, anomalous patterns from training
data, and create classi ers for computer system attacks. In the area of intrusion
detection for our research works, machine learning methods, such as logistic regression,
Naive Bayes, K-Nearest Neighbor and Decision Trees were used. The research
provides a predictive computational approach to optimize intrusion detection in the
Network Tra c Data along with implementing di erent methodologies for the evaluation
of the best accuracy from the Classi cation and Deep - Learning Algorithms.
A new intrusion intrusion detection system for smart networks has been developed
using a two-stage distinction (Anomaly-Misuse) and a deep methodology for learning.
As detection methods to identify tra c disruption that could be attacked,
the Decision Tree, logistic regression, KNN and Naive Bayes were used and Deeplearning
used an ANN method that would recognize the attacks as they exist. The
analysis has used the complete 42 dimensional features of the training data set. The
ndings indicate that the high accuracy values are 100% with 0.10 recall levels at
stage 1 of the appraisal, and 99.5% with 0.99 at stage 2 of the validation. Experimental
ndings indicate that the design of the decision tree contributes to high
precision in contrast with other algorithm
Exploring trends and factors in the world happiness report
No full textThe World Happiness report, first published in 2012, ranks countries on the basis of their self-reported happiness levels. The report is released each year on World Happiness Day March 20th. Its goal is to underpin the importance of happiness and well-being as an indicator of the effectiveness of the social and economic policies of each country.
This project will look at the happiest (and unhappiest) countries and regions in 2020, examine the factors that appear to weigh most on the determination of happiness, and view the changing trends in happiness over the last 5 years. What factors can be used to predict happiness? A regression will be run on 2020 data to find out
Sales promotion: a comparative between price-volume discount and its impact on online impulse buying behavior
No full textThis research investigates and explores the influences of sales promotion on online impulse buying behaviour of consumers by comparing between the two (2) most widely used forms of sales promotion, namely, price discounts and volume discount. The aim is to identify which from is mostly preferred by online consumers and have a higher influence on impulse buying behaviour. The participants were made up of 206 online shoppers between the age of 18-35 years in Ireland, who responded to shopping scenarios that described both type of promotion. The primary data were collect using a quantitative research method and analysed employing a graphical representation method. Furthermore, the research findings indicate that online shoppers prefer price promotion over volume discount, which in turn incites a greater level of impulse buying behaviour in consumers
Revealing the subject behind attention deficit hyperactivity disorder (ADHD) a psychotherapeutic exploration of the child in a culture of diagnosis
No full textThis dissertation looks initially at the treatment of Attention Deficit Hyperactivity Disorder
(ADHD) at a national level. It would seem that although a dual treatment of medication and
therapy is recommended for those diagnosed with ADHD by the Health Service Executive
(HSE), due to the lack of mental health services offering such therapy, many children and
adults are on long waiting lists and are not receiving their complete treatment (McDonagh,
2017). Thus, the author will explore the possible overdependence on medication for the
treatment of ADHD. The research will focus on the reasons for medicating the subject with
ADHD and in doing so explore the concept of “Medicalization”. This dissertation considers
the importance of psychotherapeutic treatment in the awareness and management of ADHD
for the person diagnosed. The author will therefore explore the subject experiencing the
symptoms of ADHD through examining the relationship between the diagnosis of ADHD and
the subjects’ neurobiology as well their educational, family and social environments, past
present and future
Entrepreneurial marketing as sustainable competitive advantage for SME's: An exploratory study within the Irish flower industry
No full textEntrepreneurial marketing is a combination of entrepreneurial skill and marketing skill, when
applied, it brings out the best possible outcome from the non-conventional way. The core
measuring dimensions - proactiveness, opportunity focus, risk taking, innovativeness, customer
intensity, resource leverage and value creation decides effectiveness of an enterprise with the
restricted of resources. Entrepreneurial marketing was developed for SMEs; however, it can
add sustainable competitive advantage to any size of enterprise. The objective of this research
is to find out the practicality of entrepreneurial dimension on Irish flower business which are,
mainly SMEs and to explore the advantages of using entrepreneurial dimension n by different
situation to achieve competitive advantage. Qualitative method of was adopted for the
research method by conducting semi- structured interview to 8 florists from various counties of
Ireland. The findings from the research was analyzed using thematic analysis process and by
using NVivo 12 pro software. The finding revels that the entrepreneurial marketing dimension
are practice within the Irish Flower SMEs and there is a number of advantages for implementing
these dimensions. These dimensions have an impact on sustainable competitive advantage
however it depends on the implementation process. Further study with larger sample is
suggested for the researches
Future of Irish retail banking: Embracing the open banking FinTech disruption
No full textThe world has witnessed dramatic changes in everyday lives due to technology advancement. We growing in technology and as customer demands are changing frequently, soon we will see wealth managers are expecting the customers to make their wealth decision on the basis of automation, artificial intelligence, less human work. This has sharpened the banking competition and immense potential for fintech has emerged. All Irish banks are preparing to get their bread and butter back from digital companies and preventing the collapse of traditional retail banks in Ireland.
This dissertation report assesses Irish retail banks current condition and path forward to combat the fintech disruption along with its future state of banking. At the beginning of report, researcher will analyse relevant books, news articles, journals and industry papers. This research is primarily sourced through qualitative study which involves five interviews from banking and fintech industry. The conclusion derived from all these interviews will answer our main research question.
Retail banks and FinTech companies aiming to drive innovation, transparency and competition for the benefit of consumers as new payment directive PSD2 requires all European banks to open their infrastructures to third-party providers. The new legislation will change the retail banking services landscape for established banks in Ireland. The strategic implications of this legislation in Irish retail banks and how they survive this challenge will be significant part for our report. Digitisation will drive the future of banking but making digital transformation a reality is not easy task. Mainstream Irish retail banks has taken this as a challenge and initiated embracing change. Banks are adopting variety of ways in staying ahead of competition and reshaping the retail banking era to whole new level