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Articles 1 - 30 of 49
Full-Text Articles in Physical Sciences and Mathematics
The Interaction Of Normalisation And Clustering In Sub-Domain Definition For Multi-Source Transfer Learning Based Time Series Anomaly Detection, Matthew Nicholson, Rahul Agrahari, Clare Conran, Haythem Assem, John D. Kelleher
The Interaction Of Normalisation And Clustering In Sub-Domain Definition For Multi-Source Transfer Learning Based Time Series Anomaly Detection, Matthew Nicholson, Rahul Agrahari, Clare Conran, Haythem Assem, John D. Kelleher
Articles
This paper examines how data normalisation and clustering interact in the definition of sub-domains within multi-source transfer learning systems for time series anomaly detection. The paper introduces a distinction between (i) clustering as a primary/direct method for anomaly detection, and (ii) clustering as a method for identifying sub-domains within the source or target datasets. Reporting the results of three sets of experiments, we find that normalisation after feature extraction and before clustering results in the best performance for anomaly detection. Interestingly, we find that in the multi-source transfer learning scenario clustering on the target dataset and identifying subdomains in the …
A Review Of Risk Concepts And Models For Predicting The Risk Of Primary Stroke, Elizabeth Hunter, John D. Kelleher
A Review Of Risk Concepts And Models For Predicting The Risk Of Primary Stroke, Elizabeth Hunter, John D. Kelleher
Articles
Predicting an individual's risk of primary stroke is an important tool that can help to lower the burden of stroke for both the individual and society. There are a number of risk models and risk scores in existence but no review or classification designed to help the reader better understand how models differ and the reasoning behind these differences. In this paper we review the existing literature on primary stroke risk prediction models. From our literature review we identify key similarities and differences in the existing models. We find that models can differ in a number of ways, including the …
The Smart Dementia Care Project, Dympna O'Sullivan, Jonathan Turner, Ciaran Nugent, Damon Berry, Michael Wilson, Julie Doyle
The Smart Dementia Care Project, Dympna O'Sullivan, Jonathan Turner, Ciaran Nugent, Damon Berry, Michael Wilson, Julie Doyle
Articles
No abstract provided.
Open-Source Clinical Machine Learning Models: Critical Appraisal Of Feasibility, Advantages, And Challenges, Keerthi B. Harish, W. Nicholson Price Ii, Yindalon Aphinyanaphongs
Open-Source Clinical Machine Learning Models: Critical Appraisal Of Feasibility, Advantages, And Challenges, Keerthi B. Harish, W. Nicholson Price Ii, Yindalon Aphinyanaphongs
Articles
Machine learning applications promise to augment clinical capabilities and at least 64 models have already been approved by the US Food and Drug Administration. These tools are developed, shared, and used in an environment in which regulations and market forces remain immature. An important consideration when evaluating this environment is the introduction of open-source solutions in which innovations are freely shared; such solutions have long been a facet of digital culture. We discuss the feasibility and implications of open-source machine learning in a health care infrastructure built upon proprietary information. The decreased cost of development as compared to drugs and …
Monitoring Activities Of Daily Living For Maintaining Independent Living In Dementia, Jonathan Turner, Ciaran Nugent, Damon Berry, Dympna O'Sullivan, Michael Wilson, Julie Doyle
Monitoring Activities Of Daily Living For Maintaining Independent Living In Dementia, Jonathan Turner, Ciaran Nugent, Damon Berry, Dympna O'Sullivan, Michael Wilson, Julie Doyle
Articles
Our ability to live independent meaningful lives depends on our ability to perform various activities and to maintain our cognitive functions. Maintaining independent living is important for persons with dementia, it increases selfworth and allows to remain independent and in their own homes for longer. We describe the activities established as being important for the maintenance of independent living, and methods for monitoring these activities using technology.
Minding The Gap: Computing Ethics And The Political Economy Of Big Tech, Ioannis Stavrakakis, Damian Gordon, Paul John Gibson, Dympna O'Sullivan, Anna Becevel
Minding The Gap: Computing Ethics And The Political Economy Of Big Tech, Ioannis Stavrakakis, Damian Gordon, Paul John Gibson, Dympna O'Sullivan, Anna Becevel
Articles
In 1988 Michael Mahoney wrote that “[w]hat is truly revolutionary about the computer will become clear only when computing acquires a proper history, one that ties it to other technologies and thus uncovers the precedents that make its innovations significant” (Mahoney, 1988). Today, over thirty years after this quote was written, we are living right in the middle of the information age and computing technology is constantly transforming modern living in revolutionary ways and in such a high degree that is giving rise to many ethical considerations, dilemmas, and social disruption. To explore the myriad of issues associated with the …
“Be A Pattern For The World”: The Development Of A Dark Patterns Detection Tool To Prevent Online User Loss, Jordan Donnelly, Alan Downley, Yunpeng Liu, Yufei Su, Quanwei Sun, Lan Zeng, Andrea Curley, Damian Gordon, Paul Kelly, Dympna O'Sullivan, Anna Becevel
“Be A Pattern For The World”: The Development Of A Dark Patterns Detection Tool To Prevent Online User Loss, Jordan Donnelly, Alan Downley, Yunpeng Liu, Yufei Su, Quanwei Sun, Lan Zeng, Andrea Curley, Damian Gordon, Paul Kelly, Dympna O'Sullivan, Anna Becevel
Articles
Dark Patterns are designed to trick users into sharing more information or spending more money than they had intended to do, by configuring online interactions to confuse or add pressure to the users. They are highly varied in their form, and are therefore difficult to classify and detect. Therefore, this research is designed to develop a framework for the automated detection of potential instances of web-based dark patterns, and from there to develop a software tool that will provide a highly useful defensive tool that helps detect and highlight these patterns.
Self-Supervised Learning For Invariant Representations From Multi-Spectral And Sar Images, Pallavi Jain, Bianca Schoen Phelan, Robert J. Ross
Self-Supervised Learning For Invariant Representations From Multi-Spectral And Sar Images, Pallavi Jain, Bianca Schoen Phelan, Robert J. Ross
Articles
Self-Supervised learning (SSL) has become the new state of the art in several domain classification and segmentation tasks. One popular category of SSL are distillation networks such as Bootstrap Your Own Latent (BYOL). This work proposes RS-BYOL, which builds on BYOL in the remote sensing (RS) domain where data are non-trivially different from natural RGB images. Since multi-spectral (MS) and synthetic aperture radar (SAR) sensors provide varied spectral and spatial resolution information, we utilise them as an implicit augmentation to learn invariant feature embeddings. In order to learn RS based invariant features with SSL, we trained RS-BYOL in two ways, …
Understanding The Assumptions Of An Seir Compartmental Model Using Agentization And A Complexity Hierarchy, Elizabeth Hunter, John D. Kelleher
Understanding The Assumptions Of An Seir Compartmental Model Using Agentization And A Complexity Hierarchy, Elizabeth Hunter, John D. Kelleher
Articles
Equation-based and agent-based models are popular methods in understanding disease dynamics. Although there are many types of equation-based models, the most common is the SIR compartmental model that assumes homogeneous mixing and populations. One way to understand the effects of these assumptions is by agentization. Equation-based models can be agentized by creating a simple agent-based model that replicates the results of the equationbased model, then by adding complexity to these agentized models it is possible to break the assumptions of homogeneous mixing and populations and test how breaking these assumptions results in different outputs. We report a set of experiments …
Accessdesign: An Inclusive Co-Design Toolkit For The Creation Of Accessible Digital Tools., Claudia Fernandez-Rivera, Sarah Boland, Eamon Aswad, John Gilligan, Dympna O'Sullivan, Emma Murphy
Accessdesign: An Inclusive Co-Design Toolkit For The Creation Of Accessible Digital Tools., Claudia Fernandez-Rivera, Sarah Boland, Eamon Aswad, John Gilligan, Dympna O'Sullivan, Emma Murphy
Articles
Existing toolkits and resources to support co-design are not always accessible to designers and co-designers with disabilities. In this paper we present a study based on an innovative co-design programme, in collaboration with St John of God Community Services, where 3rd year computer science students work with service users with intellectual disabilities to create digital applications together. We conducted a series of co-design focus group sessions involving the service users who were previously involved in the co-design collaboration with SJOG Services and TU Dublin. The data collected during these design sessions has been integrated to form an accessible design toolkit …
Addressing Ethical Issues In The Design Of Smart Home Technology For Older Adults And People With Disabilities., Jonathan Turner, Dympna O'Sullivan, Damian Gordon, Yannis Stavrakakis, Brian Keegan, Emma Murphy
Addressing Ethical Issues In The Design Of Smart Home Technology For Older Adults And People With Disabilities., Jonathan Turner, Dympna O'Sullivan, Damian Gordon, Yannis Stavrakakis, Brian Keegan, Emma Murphy
Articles
Unique ethical, privacy and safety implications arise for people who are reliant on home-based smart technology due to health conditions or disabilities. In this paper we highlight a need for a reflective, inclusive ethical framework that encompasses the life cycle of smart home technology. We present key ethical considerations for smart home technology for older adults and people with disabilities and argue for ethical frameworks which combine these key considerations with existing models of design and development.
Co-Design To Support Engagement In Activities Of Daily Living And Meaningful Activities For People Living With Dementia, Michael Wilson, Julie Doyle, Ann Marron, Jonathan Turner, Ciaran Nugent, Dympna O'Sullivan
Co-Design To Support Engagement In Activities Of Daily Living And Meaningful Activities For People Living With Dementia, Michael Wilson, Julie Doyle, Ann Marron, Jonathan Turner, Ciaran Nugent, Dympna O'Sullivan
Articles
Dementia is a chronic and progressive neurodegenerative illness, which can lead to significant difficulties in a person’s capacity to perform activities of daily living and engage in meaningful activities. The Smart Dementia Care project aims to establish an understanding of how best to design digital tools that persons with dementia and their carers will find useful and usable for care planning and goal setting. This paper discusses the first phase of this project and describes how co-design is being used to support engagement in activities of daily living and meaningful activities for people living with the early stages of dementia, …
Osm-Gan: Using Generative Adversarial Networks For Detecting Change In High-Resolution Spatial Images, Lasith Niroshan, James Carswell
Osm-Gan: Using Generative Adversarial Networks For Detecting Change In High-Resolution Spatial Images, Lasith Niroshan, James Carswell
Articles
Detecting changes to built environment objects such as buildings/roads/etc. in aerial/satellite (spatial) imagery is necessary to keep online maps and various value-added LBS applications up-to-date. However, recognising such changes automatically is not a trivial task, and there are many different approaches to this problem in the literature. This paper proposes an automated end-to-end workflow to address this problem by combining OpenStreetMap (OSM) vectors of building footprints with a machine learning Generative Adversarial Network (GAN) model - where two neural networks compete to become more accurate at predicting changes to building objects in spatial imagery. Notably, our proposed OSM-GAN architecture achieved …
Meaningful Activity Replacement Recommendations In Dementia, Jonathan Turner, Michael Wilson, Ciaran Nugent, Damon Berry, Julie Doyle, Dympna O'Sullivan
Meaningful Activity Replacement Recommendations In Dementia, Jonathan Turner, Michael Wilson, Ciaran Nugent, Damon Berry, Julie Doyle, Dympna O'Sullivan
Articles
Exercise of meaningful activities is important for people living with dementia, both for quality of life and to maintain the necessary basic activities of daily living. A method is proposed for recommendation of replacements for lost meaningful activities that accounts for the need to maintain activities of daily living.
An Exploratory Study On Refactoring Documentation In Issues Handling, Eman Abdullah Alomar, Anthony Peruma, Mohamed Wiem Mkaouer, Christian D. Newman, Ali Ouni
An Exploratory Study On Refactoring Documentation In Issues Handling, Eman Abdullah Alomar, Anthony Peruma, Mohamed Wiem Mkaouer, Christian D. Newman, Ali Ouni
Articles
Understanding the practice of refactoring documentation is of paramount importance in academia and industry. Issue tracking systems are used by most software projects enabling developers, quality assurance, managers, and users to submit feature requests and other tasks such as bug fixing and code review. Although recent studies explored how to document refactoring in commit messages, little is known about how developers describe their refactoring needs in issues. In this study, we aim at exploring developer-reported refactoring changes in issues to better understand what developers consider to be problematic in their code and how they handle it. Our approach relies on …
Code Review Practices For Refactoring Changes: An Empirical Study On Openstack, Mohamed Wiem Mkaouer, Eman Abdullah Alomar, Moatz Chouchen, Ali Ouni
Code Review Practices For Refactoring Changes: An Empirical Study On Openstack, Mohamed Wiem Mkaouer, Eman Abdullah Alomar, Moatz Chouchen, Ali Ouni
Articles
Modern code review is a widely used technique employed in both industrial and open-source projects to improve software quality, share knowledge, and ensure adherence to coding standards and guidelines. During code review, developers may discuss refactoring activities before merging code changes in the code base. To date, code review has been extensively studied to explore its general challenges, best practices and outcomes, and socio-technical aspects. However, little is known about how refactoring is being reviewed and what developers care about when they review refactored code. Hence, in this work, we present a quantitative and qualitative study to understand what are …
The World Is Our Classroom: Developing A Model For International Virtual Internships - The Global Innovations Project, Paul Doyle, Brian Keegan, Damian Gordon, Anna Becevel, Paul J. Gibson, Zhiying Jiang Phd, Dympna O'Sullivan
The World Is Our Classroom: Developing A Model For International Virtual Internships - The Global Innovations Project, Paul Doyle, Brian Keegan, Damian Gordon, Anna Becevel, Paul J. Gibson, Zhiying Jiang Phd, Dympna O'Sullivan
Articles
In the aftermath of COVID-19, remote working has become the norm, and graduates now need an even wider range of skills, which traditional classrooms and internships do not always provide. Working in multiple time zones, within global multi-cultural teams, and only ever meeting colleagues through online technology are just some of the challenges, which require a new type of global graduate. Transversal skills including leadership, collaboration, innovation, digital, green, organization and communication skills are critical. The disruption from COVID-19 also presents unprecedented opportunities to develop more inclusive approaches to internships and international experiences, to level the playing field for students …
Ai Insurance: How Liability Insurance Can Drive The Responsible Adoption Of Artificial Intelligence In Health Care, Ariel Dora Stern, Avi Goldfarb, Timo Minssen, W. Nicholson Price Ii
Ai Insurance: How Liability Insurance Can Drive The Responsible Adoption Of Artificial Intelligence In Health Care, Ariel Dora Stern, Avi Goldfarb, Timo Minssen, W. Nicholson Price Ii
Articles
Despite enthusiasm about the potential to apply artificial intelligence (AI) to medicine and health care delivery, adoption remains tepid, even for the most compelling technologies. In this article, the authors focus on one set of challenges to AI adoption: those related to liability. Well-designed AI liability insurance can mitigate predictable liability risks and uncertainties in a way that is aligned with the interests of health care’s main stakeholders, including patients, physicians, and health care organization leadership. A market for AI insurance will encourage the use of high-quality AI, because insurers will be most keen to underwrite those products that are …
Advancing Ubiquitous Collaboration For Telehealth - A Framework To Evaluate Technology-Mediated Collaborative Workflow For Telehealth, Hypertension Exam Workflow Study, Christopher Bondy Ph.D., Linlin Chen Ph.D, Pamela Grover Md, Pengcheng Shi Ph.D
Advancing Ubiquitous Collaboration For Telehealth - A Framework To Evaluate Technology-Mediated Collaborative Workflow For Telehealth, Hypertension Exam Workflow Study, Christopher Bondy Ph.D., Linlin Chen Ph.D, Pamela Grover Md, Pengcheng Shi Ph.D
Articles
Healthcare systems are under siege globally regarding technology adoption; the recent pandemic has only magnified the issues. Providers and patients alike look to new enabling technologies to establish real-time connectivity and capability for a growing range of remote telehealth solutions. The migration to new technology is not as seamless as clinicians and patients would like since the new workflows pose new responsibilities and barriers to adoption across the telehealth ecosystem. Technology-mediated workflows (integrated software and personal medical devices) are increasingly important in patient-centered healthcare; software-intense systems will become integral in prescribed treatment plans [1]. My research explored the path to …
Towards An Ethical Framework For The Design And Development Of Inclusive Home-Based Smart Technology For Smart Spaces For Older Adults And People With Disabilities, Emma Murphy, Julie Doyle, Ioannis Stavrakakis, Damian Gordon, Brian Keegan, Dympna O'Sullivan
Towards An Ethical Framework For The Design And Development Of Inclusive Home-Based Smart Technology For Smart Spaces For Older Adults And People With Disabilities, Emma Murphy, Julie Doyle, Ioannis Stavrakakis, Damian Gordon, Brian Keegan, Dympna O'Sullivan
Articles
Unique ethical, privacy and safety implications arise for people who are reliant on home-based smart technology due to health conditions or disabilities. As a result we need to carefully reflect on our approaches to ethical issues over the life cycle of smart home technology design and the wider living context for end users and relevant stakeholders. In this position paper we highlight a need for a reflective, inclusive ethical framework for the design of inclusive smart spaces. We present key ethical considerations in the design, development and deployment of smart home-based technology for older adults and people with disabilities. We …
Detecting Patches On Road Pavement Images Acquired With 3d Laser Sensors Using Object Detection And Deep Learning, Syed Ibrahim Hassan, Dympna O'Sullivan, Susan Mckeever, Kieran Feighan, David Power, Ray Mcgowan
Detecting Patches On Road Pavement Images Acquired With 3d Laser Sensors Using Object Detection And Deep Learning, Syed Ibrahim Hassan, Dympna O'Sullivan, Susan Mckeever, Kieran Feighan, David Power, Ray Mcgowan
Articles
Regular pavement inspections are key to good road maintenance and road defect corrections. Advanced pavement inspection systems such as LCMS (Laser Crack Measurement System) can automatically detect the presence of different defects using 3D lasers. However, such systems still require manual involvement to complete the detection of pavement defects. This paper proposes an automatic patch detection system using object detection technique. To our knowledge, this is the first time state-of-the-art object detection models Faster RCNN, and SSD MobileNet-V2 have been used to detect patches inside images acquired by LCMS. Results show that the object detection model can successfully detect patches …
Assessing Feature Representations For Instance-Based Cross-Domain Anomaly Detection In Cloud Services Univariate Time Series Data, Rahul Agrahari, Matthew Nicholson, Clare Conran, Haythem Assem, John D. Kelleher
Assessing Feature Representations For Instance-Based Cross-Domain Anomaly Detection In Cloud Services Univariate Time Series Data, Rahul Agrahari, Matthew Nicholson, Clare Conran, Haythem Assem, John D. Kelleher
Articles
In this paper, we compare and assess the efficacy of a number of time-series instance feature representations for anomaly detection. To assess whether there are statistically significant differences between different feature representations for anomaly detection in a time series, we calculate and compare confidence intervals on the average performance of different feature sets across a number of different model types and cross-domain time-series datasets. Our results indicate that the catch22 time-series feature set augmented with features based on rolling mean and variance performs best on average, and that the difference in performance between this feature set and the next best …
Assessing Feature Representations For Instance-Based Cross-Domain Anomaly Detection In Cloud Services Univariate Time Series Data, Rahul Agrahari, Matthew Nicholson, Clare Conran, Haytham Assem, John D. Kelleher
Assessing Feature Representations For Instance-Based Cross-Domain Anomaly Detection In Cloud Services Univariate Time Series Data, Rahul Agrahari, Matthew Nicholson, Clare Conran, Haytham Assem, John D. Kelleher
Articles
In this paper, we compare and assess the efficacy of a number of time-series instance feature representations for anomaly detection. To assess whether there are statistically significant differences between different feature representations for anomaly detection in a time series, we calculate and compare confidence intervals on the average performance of different feature sets across a number of different model types and cross-domain time-series datasets. Our results indicate that the catch22 time-series feature set augmented with features based on rolling mean and variance performs best on average, and that the difference in performance between this feature set and the next best …
All Things Merge Into One, And A River Runs Through It: Exploring The Dimensions Of Blended Learning By Developing A Case Study Template For Blended Activities, Damian Gordon, Paul Doyle, Anna Becevel, Tina Baloh
All Things Merge Into One, And A River Runs Through It: Exploring The Dimensions Of Blended Learning By Developing A Case Study Template For Blended Activities, Damian Gordon, Paul Doyle, Anna Becevel, Tina Baloh
Articles
The BLITT (Blended Learning International Train the Trainer) Project is focused on developing a training programme to equip teachers to become proficient in championing the use of Blended Learning in the classroom. The training programme will be developed in two phases, in the first phase involves the development of a series of case studies relevant to Blended Learning, followed by a second phase where the BLITT training programme will be designed and developed, using input from these cases. In developing the blended learning case studies, two key documents were identified as being essential, first, a case study tracking template to …
Satdbailiff- Mining And Tracking Self-Admitted Technical Debt, Mohamed Wiem Mkaouer, Eman Abdullah Alomar, Ben Christians, Mihal Busho, Ahmed Hamad Alkhalid, Christian D. Newman
Satdbailiff- Mining And Tracking Self-Admitted Technical Debt, Mohamed Wiem Mkaouer, Eman Abdullah Alomar, Ben Christians, Mihal Busho, Ahmed Hamad Alkhalid, Christian D. Newman
Articles
Self-Admitted Technical Debt (SATD) is a metaphorical concept to describe the self-documented addition of technical debt to a software project in the form of source code comments. SATD can linger in projects and degrade source-code quality, but it can also be more visible than unintentionally added or undocumented technical debt. Understanding the implications of adding SATD to a software project is important because developers can benefit from a better understanding of the quality trade-offs they are making. However, empirical studies, analyzing the survivability and removal of SATD comments, are challenged by potential code changes or SATD comment updates that may …
Residential Demand Side Management Model, Optimization And Future Perspective: A Review, Subhasis Panda, Sarthak Mohanty, Pravat Kumar Rout, Binod Kumar Sahu, Mohit Bajaj, Dr Hossam Zawbaa, Salah Kamel
Residential Demand Side Management Model, Optimization And Future Perspective: A Review, Subhasis Panda, Sarthak Mohanty, Pravat Kumar Rout, Binod Kumar Sahu, Mohit Bajaj, Dr Hossam Zawbaa, Salah Kamel
Articles
The residential load sector plays a vital role in terms of its impact on overall power balance, stability, and efficient power management. However, the load dynamics of the energy demand of residential users are always nonlinear, uncontrollable, and inelastic concerning power grid regulation and management. The integration of distributed generations (DGs) and advancement of information and communication technology (ICT) even though handles the related issues and challenges up to some extent, till the flexibility, energy management and scheduling with better planning are necessary for the residential sector to achieve better grid stability and efficiency. To address these issues, it is …
Image-Based Malware Classification Hybrid Framework Based On Space-Filling Curves, Stephen O Shaughnessy, Stephen Sheridan
Image-Based Malware Classification Hybrid Framework Based On Space-Filling Curves, Stephen O Shaughnessy, Stephen Sheridan
Articles
There exists a never-ending “arms race” between malware analysts and adversarial malicious code developers as malevolent programs evolve and countermeasures are developed to detect and eradicate them. Malware has become more complex in its intent and capabilities over time, which has prompted the need for constant improvement in detection and defence methods. Of particular concern are the anti-analysis obfuscation techniques, such as packing and encryption, that are employed by malware developers to evade detection and thwart the analysis process. In such cases, malware is generally impervious to basic analysis methods and so analysts must use more invasive techniques to extract …
Effect Of Cryogenic Treatment On Drill Tool For Enhancing Metal Cutting Operation Of Aluminium Alloy Is737.Gr19000, G. Navaneethakrishnan, B. Sureshkumar, R. Palanisamy, Mohit Bajaj, Hossam Zawbaa, Salah Kamel
Effect Of Cryogenic Treatment On Drill Tool For Enhancing Metal Cutting Operation Of Aluminium Alloy Is737.Gr19000, G. Navaneethakrishnan, B. Sureshkumar, R. Palanisamy, Mohit Bajaj, Hossam Zawbaa, Salah Kamel
Articles
Drilling is the hole making process on the component face with the aid of a twisted drillbit. Normal drill bits easily wear out through penetration of drill bit into the workpiece material due to force generated in the drilling operation. So this work tries to investigate the machining parameters with cryogenically treated drill bits on various responses. Cryogenic treatment is one of the thermal engineering processes, which is used to cool the material from the temperature of −150 °C to −273 °C. This research work utilizes cryogenically treated drill tools for investigating the drilling performance on aluminium alloy (IS737.Gr19000) workpiece …
Using Feature Selection With Machine Learning For Generation Of Insurance Insights, Ayman Taha, Bernard Cosgrave, Susan Mckeever
Using Feature Selection With Machine Learning For Generation Of Insurance Insights, Ayman Taha, Bernard Cosgrave, Susan Mckeever
Articles
Insurance is a data-rich sector, hosting large volumes of customer data that is analysed to evaluate risk. Machine learning techniques are increasingly used in the effective management of insurance risk. Insurance datasets by their nature, however, are often of poor quality with noisy subsets of data (or features). Choosing the right features of data is a significant pre-processing step in the creation of machine learning models. The inclusion of irrelevant and redundant features has been demonstrated to affect the performance of learning models. In this article, we propose a framework for improving predictive machine learning techniques in the insurance sector …
Drivers Of Environmental Degradation In Turkey: Designing An Sdg Framework Through Advanced Quantile Approaches, Tomiwa Sunday Adebayo, Ephraim Bonah Agyekum, Salah Kamel, Hossam Zawbaa, Mehmet Altuntaş
Drivers Of Environmental Degradation In Turkey: Designing An Sdg Framework Through Advanced Quantile Approaches, Tomiwa Sunday Adebayo, Ephraim Bonah Agyekum, Salah Kamel, Hossam Zawbaa, Mehmet Altuntaş
Articles
Turkey is a laggard in terms of the achievement of its Sustainable Development Goals (SDGs), and one of the primary issues it faces is environmental deterioration. Therefore, a policy-level reorientation may be needed to address this relevant issue. From this standpoint, this research assesses the impact of renewable energy (RE) use and financial development on the emissions of CO2 as well as the role of urbanization and agriculture, utilizing a dataset stretching between 1985 and 2019. By applying the innovative quantile-on-quantile regression (QQR) and non-parametric Granger causality in quantiles techniques, the study assesses the ways in which the quantiles of …