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What we do in the silence: an exploration of the challenges and opportunities presented by silences in therapy
No full textThe silence of patients in therapy provides many challenges to the therapist. It is vague, undefinable and is difficult to challenge. It can signify resistance and negative transferences but can also be a space for the patient to communicate something that cannot be expressed in words. As a result of its ambiguous nature it can challenge the therapist’s confidence in their own abilities and create anxiety or tension in the therapeutic relationship. This paper aims to explore some of the developments in the understanding of patients’ silences in therapy, as well as some of the ways an therapist can work with silent patients. It is hoped that the paper will help therapists to understand more about what a patient’s silence can mean and also provide guidance on how best to work with silence in therapy
Investment advice based on market trends and financial distress of the company
No full textIn this day and age “Investment” has become a necessity and an important factor for companies and individuals. Investment is something which is called a monetary asset purchased with the idea that the investment will provide a profit in the future. Before investing people study Financial performance, Background and experience in the industry, Company uniqueness, Effective business model, Large market size of a particular company, but they do not focus on minute fingerprints of financial distress. The main of this research is to draw down the factors of investment under a single umbrella and generate and investment advice.
This study will mainly focus on developing two models to refine the investment process. The first model we have proposed is a stock market prediction based on deep learning techniques. Here we have used a Realtime dataset from Yahoo finance for a particular company where clients want to invest. Here we have used different deep learning techniques. But for this research sequential LSTM has outperformed all the models with minimum rmse (root mean squared error) score. With the help of this are able to predict the stock closing price of the company for up to one month. The second model will be of Financial Distress Predication based on various Bagging and Boosting techniques with the integration of various SMOTE techniques were used. But for this research Balanced Bagging Method with ADASYN has outperformed from all the models with an accuracy of 93%. ADASYN Adaptive Synthetic Sampling Method is a modified version of SMOTE which performed best with our bagging and boosting model, we have used ADASYN to deal with the class imbalance problem. This empirical research is carried out based on real world financial data of 3476 Chinees company with over 84 financial and non-financial features.
Keywords: Investment, Financial Distress Prediction, Stock Market Prediction, Deep learning, SMOTE, ADASYN, Bagging and Boosting, Ensemble Methods, Adaboost-SVM, LSTM
A context-aware personalized recommender system for automation in IoT based smart home environment
No full textAn IoT enabled smart-home fulfils many needs of the inhabitants such as providing conveniences through personalised home automation, saving energy through optimizations, etc., based mostly on the user’s behaviour and interaction with these devices. This research proposes a methodology to build a system that learns user’s habits/preferences in a given situation, merges them with contextual information and finally recommends relevant automation services, which the user would like to perform at that instance. The user preferences are learned using unsupervised algorithm such as association analysis, trained upon inhabitant’s prior interactions captured passively through the IoT enabled sensors while they live their daily lives. The contextual information, such as location, time, etc. are extracted from the given data. The preferences and the contextual information are fed to supervised learning algorithms to predict desired user action on the basis of current sensor outputs and the contextual setting at that moment
Exploring the role of Influencer Marketing to drive participation of Gen Z in Gaelic sport
No full textIn recent years, some famous players of Gaelic Games or better known as GAA have positioned themselves on Instagram, posting content, and promoting brands. Definitions name them as Influencer Marketing, social media marketing strategy to create brand communication. The purpose of the research is to explore the role of these Influencers Marketing in the GAA to drive participation of Generation Z in the sport. The use of a qualitative research design is adopted with interpretivism philosophy and inductive approach. The data have been collected with semi-structured interviews to investigate the experience of people belonging to the GAA and Instagram with Influencers. The results show that Influencers Marketing could increase the visibility of the GAA, promoting products related to the sport, and showing content to improve skills in the game. Furthermore, there is an association with other brands non-related to the field. Participants have stated to interact on Instagram with influencers, however they admitted that this could be more suitable for kids and adolescents. The results are analyzed with the literature review in the discussion chapter. Moreover, conclusions and recommendations are derived, and the futures of the research are presented
Yilmaz Akkilic City Research Awards and Publications: A Library Publishing Example from Turkey
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
Prediction of patient's health risk in critical care using a deep neural network
No full textThe Intensive care units (ICU’s) of a hospital comprise a large share of the health care budget as today’s lifestyle habits and environmental conditions contribute to the onset of chronic diseases. High risk patients in ICU require extensive monitoring and direct attention from healthcare providers. Improving the quality, efficiency, and effectiveness of healthcare provision is an issue of huge importance. Recent technological advances in machine learning have resulted in innovative solutions for the healthcare industry. This research evaluates state of the art deep learning against traditional machine learning algorithms for predicting patients most at risk in critical care. The proposed deep neural network classifier outperforms the traditional methods such as Logistic Regression, GLM, Naïve Bayes, Random Forest and Decision Tree in terms of accuracy, precision, recall, specificity, AUC, and training time. The best performing state of the art deep learning model has an accuracy of 97%
Game bot detection using behavioral analysis
No full textOnline games and especially MMORPGs have become very popular and people are investing and spending thousands of dollars on such games. Enhancing the user-experience has become a challenge for companies as gaming bots have begun to populate most of the games. In this paper, we battle this problem by using behavioural analysis of players to detect and differentiate between bots and human players. Feature selection was a key factor in this process as choosing the right features enabled to get higher accuracy rates. Feature selection techniques such as Rank importance were used to select the most important features to train the data. The data was then fit using classification algorithms such as Naïve Bayes, Random Forest, Generalized Linear Model and Ensemble technique. The results indicate that the Random Forest algorithm performs the best with an accuracy of 96
Quality of financial reporting as a measure of internal audit effectiveness a study of Irish non-financial PLCs
No full textAbility to demonstrate Internal Audit’s capability to fulfil its role in the organisation is crucial in defining its future role and significance. This study investigates the relationship between the Internal Audit Function and Quality of Financial Reporting. Using a pioneering research design it shows that a positive relationship between the presence of Internal Audit Function and Accruals Quality (a proxy for Quality of Financial Reporting) exists. Results indicate that outsourcing negatively affects Accruals Quality however the company size is an important factor in both cases. The study also explores the state of Internal Audit among non-financial PLCs in Ireland and reveals that adoption of the Internal Audit Function is not universal and its presence strongly related to company size. Internal Audit departments concentrate on the assurance function, widely implement Internal Audit charter and functional reporting to the Audit Committee. Internal Audit outsourcing is more common in mid-size companies and possibly a transition stage before introducing an in-house department
“The necessary evil”- an exploration into the provision of sign language interpreters in therapy and its effect on the therapeutic relationship
No full textThe author of this dissertation is a sign language interpreter who works closely with the Deaf
community and has become interested in exploring the implications of interpretation in therapy. The
aim of the study is to understand the use of the sign language interpreter, while also examining the
impact of their presence on the therapeutic relationship. Due to newly established accessibility laws in
Ireland, it was necessary to carry out research in order to provide an overview of the current literature
surrounding the process that takes place when a Deaf person avails of interpreted mental health
services. Language was identified as an essential element in the success of therapy, with the use of a
sign language interpreter emerging as the most realistic option when working with a Deaf client. It
was established that although a necessary addition for communication purposes, the interpreter brings
with them much more than linguistic translation. For this reason, they are identified as the necessary
evil. Issues such as translation inaccuracies and triadic relationship problems were found to have a
profound impact on the therapeutic alliance, reducing the effectiveness of the therapy. In order to
combat these negative effects, techniques such as professional collaboration and implementation of
boundaries were discussed, leading to an improved sense of effectiveness. The research concluded
with an observation of potential successes when using an interpreter in therapy. However, due to the
lack of literature in many key areas, it notes that there is a substantial need for further exploration into
this topic
An exploration of nature therapy and the application of ecopsychological ideas in theraputic practice
No full textAccording to Jung and others, a changing relationship to the natural world has brought about a loss of connection. The outer disconnection between man and nature is also reflected in man’s disconnection from his own inner self. In his work Jung explores the innate connection the human psyche has to nature through the collective unconscious. The aim of this research paper is to explore Jungian theory and Nature Therapy as a therapeutic tool in which ecopsychological ideas are introduced into a therapeutic practice.
The benefits of nature to stimulate restorative and healing effects on the human psyche are recognised, these effects support positive change at both psychological and physiological levels of our being. Jung’s ideas have also informed the theoretical foundation of ecopsychology, which explores the relationship between the natural world and human beings through ecological and psychological principles. According to the biophilia theory, nature is rooted in our genetic biology and it argues that it is this biological programming which connects us to the natural world. It maintains the perception that humans and the natural environment are not separate from one another but are connected through the genetic hard wiring of the human psyche.
According to Jung the purpose of returning to nature is to invite and allow nature to heal us (Carl Gustav Jung, 2002, p. 19) This dissertation concludes that nature therapy or the ‘return to nature, to heal’, encompasses the application of ecopsychological ideas into a therapeutic practice. Nature therapy is a form of therapy which relies on the natural environment to achieve therapeutic goals. Not only is nature the venue but also an active part in the therapeutic process used to address the underlying disconnection between humans and their ecological home