3830 research outputs found
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Formal volunteering in child listening services: the motivating factors and relative impact on volunteers
No full textThe aim of this research was to understand the motivating factors by which individuals engage in child-based listening services, their expectations prior to commencing their role, had their expectations been met and the reasoning behind why their remain in their role to date. Four semi-structured interviews were conducted which examined the experiences of each participant. Thematic Analysis was used to identify the themes which were found in each of the interviews. Interviews were transcribed and coded to understand these subthemes which led to the creation of five main themes which included volunteer supports, motivators, frustration, benefits and difficulties in volunteering. The results found that the volunteers all had a shared interest in working with children either in a professional or volunteering setting. Participants experienced a great amount of difficulties and frustration in their roles, however, the benefits which they described seemed to outweigh the negative aspects which was the motivating factor for them to remain in the role. The participants also described a large amount of support available to them through the organisation in the form of supervisors, counselling services and friendships
The role of general practitioner (GP) gender on women’s sense of health autonomy and wellbeing
No full textThe study aims to explore the differences in women’s sense of health autonomy and wellbeing based on their GP’s gender, it also looks at the association of health autonomy and wellbeing. Design is quantitative survey-based using non-probability snowball sampling methods of Irish females of 18+ years (N=174). The measures used were the Health Care Climate Questionnaire (Williams et al., 1996), Positive Affect Negative Affect Schedule (Watson, Clark, & Teilegen, 1988), 5-Item Well-Being 5 Item (WHO, 1998) and General Self-Efficacy scale (Schwarzer & Jerusalem, 1995). Results found that there was not a significant difference in health autonomy between GP gender groups, however, there was a significant difference in wellbeing between the groups. Wellbeing was shown to predict health autonomy. Additionally, the 51 – 65 age group showed significantly higher levels of mental health wellbeing. The findings support building medical practitioners’ health autonomy skills and for further research on GP-patient gender concordance
Rebuilding old WordPress page into modern web application
No full textThe main goal of this project was an educational goal, to develop, deploy, and monitor a
full-stack application that can be used later as a showcase and help me to progress in my
career. The used stack is in demand and there are a lot of opportunities and different projects
where these technologies like React and Node.js can be used. The second goal was to create
an application that will be used for a real business and help improve the current user experience
and the overall performance
Homeless truths: A qualitative exploration into the impact homelessness has on mental health
No full textThe aim of the study was to explore the lived experiences of formerly homeless adults now in secure housing, main research interests focused on how being homeless impacted their mental health. This was a qualitative study included three participants, one female and two male and conducted semi structured interviews to gain detailed insight into the phenomenon of homelessness. Interpretative phenomenological analysis was used with raw data interpreted by the researcher to create themes. The five superordinate themes which emerged were, Mental Health Issues, Feelings of Homelessness, Support Networks, Survival Strategies and Impact of Homelessness. Findings identified common themes of mental health issues occurring throughout homelessness and in the aftermath even years later…. harrowing lived experiences of fear, shame and isolation with many participants let down by close networks and services although shared an exhilarating indomitability to survive homelessness. Future research is needed within Ireland and on a wider scale
An exploration of transference and countertransference in working therapeutically with clients experiencing IPV within private practice
No full textThis paper will examine the transference and countertransference that can occur while working therapeutically with clients experiencing Intimate Partner Violence (IPV). The psychodynamics of Intimate Partner Violence will be explored, highlighting the complexity of the dynamics that occur in violent relationships such as projection and splitting. The findings from existing literature stresses the importance of the psychotherapist's continuous work on self-awareness, training, risk assessment and supervision when working therapeutically with perpetrators of IPV. Some findings of this theoretical work would suggest that more collaborative psychotherapy research and training for psychotherapists is required to focus on creating best practices around violence prevention measures and interventions
Job recommendation system using machine learning and natural language processing
No full textThe rise of digital communication and the spread of the internet has made an
enormous impact in every industry. One such domain is the Hiring process, where
a job seeker applies to a job by creating a profile on a job portal by providing all
his/her work preferences. These work preferences of each user can be collected
from each user and provide job recommendations based on their preference. There
had been work done in this field, where researchers have implemented Recsys using
the Hybrid filtering method as user data had previous interaction with item (Rafter
et al., 2000).In this dissertation, we have approached the problem with the three-tier
approach design. Data acquired for our study has no previous interaction between
the user data and Job listing data. With such a dataset, we have addressed the issue
of cold start from both User and Job perspective. Also, recommend the top-n job
to the user by analyzing and measuring similarity between the user preference and
explicit features of job listing using Content-based filtering, which is devised in
support of natural language processing and cosine similarity. The Recommender
System is then evaluated using precision, recall, and F1 score(Barrón-Cedeno et al.,
2009). The top-n recommendation made to the user is presented in the third tier of
the design, a web app deployed in the local server. The presentation layer web-app
is developed using Plotly’s dash web framework
Understanding HR practices in the Peruvian insurance context and their effect on employee satisfaction
No full textThe relationship between human resource practices to performance and organization’s achievements has been widely studied. But today, human capital has become the most valuable assets in organizations, this research study focuses on the impact of human resource practices on employee job satisfaction rather than only on organizational performance. Primary qualitative data was collected through in depth semi-structured interviews with line managers in a multinational insurance company operating in Peru. It was found that the company has an employee-oriented approach and practices with positive relation between employee satisfaction and both individual and organizational performance. Moreover, communication, training, and non-monetary rewards as main practices implemented, involvement of line managers as a key factor in this successful implementation. The main contributions of this study are the empirical findings and a conceptual framework, which gives priority to practices to enhance employee satisfaction improving individual and organization performance
Collaboration and Commitment: Publishing Diverse Academic Scholarship for the Public Good
No full textThe IFLA Special Interest Group on Library Publishing held the Virtual Open Programme on October 15th 2020. The event had been scheduled as part of WLIC 2020 in Dublin which was postponed due to the pandemic. The theme was "Library Publishing: A catalyst for change" and it featured seven 8-minute lightening talks by library publishers from across the world. The event was broken into two parts: Case Studies and Collaborations in Library Publishing
Study of deep learning models on educational channel video from YouTube for classification of Hinglish text
No full textThe applications of data mining process are widespread. Within the framework of CRISP-DM a data mining project, this research exposes key areas like data preparation, feature engineering, model training and evaluation techniques.
Sentiment analysis / opinion mining is the technique for categorizing and defining computationally the opinions or feelings expressed in a piece of text to decide whether the attitude of individuals towards any topic, interest or product is a polarity of positive, negative or neutral. In numerous natural language processing assignments, deep learning is one of the most widely recognized methodologies. Deep learning models on normal language processing undertakings likewise beat regular AI models.
It is a common practice these days for public to use social media to share their opinions and ideas about most of the things and topics related to education is one of the most common searches among many social media posts or videos. Everyday lot of educational videos are uploaded to YouTube platform and most people share their opinions about the channel or video in the comment section. The research focuses on how well deep learning techniques work in extracting student/viewer tendency of YouTubers from the Hinglish dataset.
This research shall serve as a basis to provide useful information to teachers and online tutors by understanding and acting on the emotions of the students during the process of learning from their uploaded video and help them improve more on their methods of teaching
Topic modelling and theme discovery on Aylien News articles during COVID-19
No full textTopic modelling is increasingly important for the analysis of large volumes of unlabelled data necessitating scanning a collection of documents and identifying keywords and language usage patterns. It is a technique of unsupervised machine learning that enables clustering of similar word groups and expressions under topics as well as analyse individual topic content. The negative impacts of the pandemic have been reflected in the news media. This research applies topic modelling to the COVID-19 news articles from AYLIEN to identify key themes in the large volume of COVID-19 news articles. Topic modelling algorithms applied and compared include LDA, NMF, LSI and HDP. LDA showed interpretable topics with better topic coherence and identification of underlying themes including worldwide spread; workplace activity impact; lockdown implications; medical supply shortages; social and sport knock-on effects; and disease statistics. Results of applying the different algorithms are presented