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Rupture and repair in the therapeutic alliance: An attachment perspective
No full textResearch has consistently demonstrated that the quality of the relationship between a therapist and their client, often referred to as the therapeutic alliance, has been shown to be a reliable predictor of positive therapeutic outcome. Equally, weakened alliances have been found to be correlated with unilateral termination by clients. It is therefore important to understand the factors that contribute to the quality of the alliance, and the factors influencing alliance ruptures and repair processes when they occur. There is considerable evidence that clients with secure attachment styles are found to have stronger alliances with their therapists, while the alliances of those with insecure attachment styles are weaker. Recent developments in rupture repair research suggest that attachment style may play a role in a client’s ability to engage in rupture repair processes. This study aims to explore rupture and repair in the therapeutic alliance from an attachment perspective
Capturing art: exploring the role of the academic art librarian in the modern world
No full textArt Libraries and Art special Collections are a place of academic wonder, a space for
communication, connection and creation. The recent re-emergence of the ‘visual’ has in
terms of art education and academic art study, highlighted the necessity to determine the
value of art librarianship and explore the role of the Art Librarian in the modern world. In
this study, eight qualitative semi-structured interviews with Art Librarians, four in Art and
Design Schools and four in academic Special Collections, were conducted. The study shows
that the majority of Art Librarians define their role by aligning it with their main duties
including; ‘reviewing and sustaining the mission of the institution, collection development
and user needs assessment.’ All of the Art Librarians were of the opinion that the nature of
their role in art librarianship has evolved in the form of increased ‘outreach, learning and
education, advocacy and technological advances.’ An Art qualification is not essential
however a passion or interest in the study of Art is vital to enhancing the prosperity of Art in
the institution. Library Science qualifications are also deemed a necessity. The study shows
Art Librarians in Ireland do possess the skills required to assist artistic patrons’. The study
also shows, Art Librarianship depends on the practise and creation of art in order to stay
viable and visible in the canon of academic librarianship. Therefore, Art Librarians are of
upmost importance in the modern world, in order to sustain the continued growth and
development of the Arts. Ultimately, the value of the Art Librarian in academic circles today
is of high acclaim as they continue to recreate, reinvent, discover and lead the ‘Art World’
into the future
Face recognition using OpenCV
No full textFace recognition is one of the most useful contactless biometric identi cation tool, having
several applications in security, surveillance and human-computer interactions etc. The
concept of face recognition has been familiar in the Computer Vision community since
long, but little development have been achieved due to challenges in feature engineering
and achieving robustness (in terms of pose, illumination, occlusion etc.). However, with
the inception of deep learning, most of these problems have been mitigated. But with all
this improvents, deep learning models require a large amount of data and computational
power to provide an accuracte model.
In this work, we propose a face recognition pipeline based on deep learning architecture
which can be trained with minimum number of samples without hours of training and can
be implemented to run on videos in real time. Our method uses a pretrained deep learning
framework based on the Inception module for feature generation, i.e. this module provides
the feature vector for each face image. These features are used to train a Support Vector
Machine (SVM) for classi cation. This architecture is validated on two large datasets
(LFW and IMFDB).We have tested our model on videos, speci cally movie clips to access
the model accuracy and speed. The achieved accuracy is above 91% with approximately
4-5 frames per second which proves the superority of our model. We have also provided a
real life example of face recognition using our method with very few training images, and
the achieved results are very promising. Finally, we have analysed the factors a ecting
the end result and investigated some of our failure cases for better understanding
Implementation of clustering algorithm using graph embeddings and graph data science on Yelp restaurant dataset
Get PDFThis research uses the leading property graph DBMS, Neo4j to implement a Restaurant Knowledge Graph of the Yelp Dataset (Challenge 2020 – business; users; category; reviews). The application of CYPHER queries; graph algorithms for insight and graph embeddings for machine learning on the graph are presented. Recently released (April 2020) Version 1.3 of the Neo4j Graph Data Science library on Neo4j 4.1.0 is explored using the Python library Py2Neo. Use cases for the graph algorithms PageRank and Overlap Similarity are presented.
It is shown that using Py2neo library, data can be prepared for the application of machine learning algorithms in Python. A graph embedding algorithm (Node2vec) is applied for clustering using a traditional k-Means clustering algorithm using Tableau. The results are visualized in Tableau
Text sentiment analysis of Marathi language in English And Devanagari script
Get PDFMarathi is a language spoken by a very large number of people in India and about 10% of the Indian population uses ‘Marathi + English’ while texting one another. This study focuses on text sentiment analysis of the mixed language text of Marathi (written in English) first, and then compares the accuracy again after the same sentences (written in Devanagari script) have been translated using Google’s cloud translation services. Same machine learning techniques were applied on both in order to maintain equality. A new and accurate dataset which comprised of day to day sentences was compiled manually in order to reduce error. The outputs were later compared and the need to develop such researches further is highlighted. The results of the research show that the algorithms like Random Forest and SVM give us the highest accuracies of 65.41% and 64.16% respectively
Publishing to inspire the library profession
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
Strategic operations management: factors impacting job satisfaction and communication effectiveness
No full textThe alignment of strategic operations and objectives have always been high in demand due to failures of organisations not able to achieve their strategic goals. The lower level of employee’s engagement towards achieving the strategic objective has been a challenging job for the organisations and they have been seeking after the factors which affect strategic alignment. Therefore, it is essential to learn about the factors which can enhance the alignment between employees and the strategic objective of the organisation. It is also essential that an organisation need to take adequate steps to improve the factors which affect strategic alignment. The primary goal of this research is to define the effectiveness of motivation, job satisfaction, communication effectiveness and emotional intelligence in aligning employees with achieving organisation’s strategic objective and also to examine the level of strategic alignment of employees and organisation in Ireland mainly from retail, banking, and hospitality industry
Exploring the space of topic modelling and topic coherence on short and long text corpora
No full textTopic Modelling, a discipline of Natural Language Processing, is widely prevalent and its application on social network communications has become essential in identifying key themes impacting society. In this dissertation titled- “Exploring the space of Topic Modelling and Topic Coherence on short and long text corpora” a comparative study of topic modelling algorithms is presented including LDA (Latent Dirichlet Allocation), LSA(Latent Semantic Analysis), NMF(Non Negative Matrix Factorization) ,BTM(Biterm Topic Modelling). Algorithms are applied on Zomato and Ovarian Cancer Tweets extracted from Twitter and on Amazon Food Reviews. Six robust performance metrics are used for comparative purposes using the online Palmetto tool. The results obtained reveal that all models have strong potential for topic modelling. BTM performed the best in detecting more coherent topics on short texts measured across the six coherence metrics, whereas LDA outperformed on long texts. NMF outperforms other algorithms in terms of execution time
Investigating the effects of the implementation of open access publishing on the roles of academic librarians
No full textThis research study aimed to determine if academic librarians in Dublin have redefined their role after implementing open access publishing in their libraries. This was done through semi-structured qualitative interviews with 7 participants from 6 third level institutions based in Dublin. The study found that academic librarians had redefined their role due to the open access initiatives in their institutions and that this change in the role was due to the influence of the initiatives themselves, advancing technologies, the available resources, and external and internal influences. All participants in the study regarded this redefinition as a positive change and predicted that open access library publishing will become the predominant path for scholarly communication in the future
The student voice on a token economy system at whole-school level
No full textThis qualitative study set out to explore the student perspective on an implemented token economy system in a secondary school setting. Two focus group interviews were conducted, each with five participants, randomly sampled to include two students from each of the five year groups (first to fifth year) in the school. An inductive approach to thematic analysis was employed to analyze the data and four main themes were identified, including: 1) The Whole School Approach, 2) The Implementation of The System, 3) The Effect of The System on Student Motivation, and 4) The Reward Value. The results yielded some insights into the effectiveness of a token economy system in a secondary school setting and highlighted the importance of garnering the views of students in evaluating the impact that such a system can have on student motivation and behaviour. The results from this study would suggest that further investigation into the systematic implementation of a token economy system at whole school level would be beneficial. It also probes further exploration into how the inclusion of student voice, in the development of key elements of a token economy system, such as the type of reward and organization of the system, would impact the efficacy of a token economy system, in place, in a post-primary setting