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Articles 151 - 180 of 816
Full-Text Articles in Computer Sciences
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 …
The Dynamic Impact Of Biomass And Natural Resources On Ecological Footprint In Brics Economies: A Quantile Regression Evidence, Abraham Ayobamiji Awosusi, Tomiwa Sunday Adebayo, Mehmet Altuntaş, Ephraim Bonah Agyekum, Hossam Zawbaa, Salah Kamel
The Dynamic Impact Of Biomass And Natural Resources On Ecological Footprint In Brics Economies: A Quantile Regression Evidence, Abraham Ayobamiji Awosusi, Tomiwa Sunday Adebayo, Mehmet Altuntaş, Ephraim Bonah Agyekum, Hossam Zawbaa, Salah Kamel
Articles
Many emerging economies, including the BRICS economies, are having difficulty meeting the Sustainable Development Goals’ (SDGs) objectives. Consequently, this research discusses the creation of an SDG framework for the BRICS economies, which can be utilized as a model for other blocs. To achieve this purpose, this research probes into the effect of biomass energy usage on ecological footprint in the BRICS economies between 1992 and 2018, considering the roles of gross capital formation, natural resources, and globalization. The novel Methods of Moments-Quantile-Regression (MMQR) approach with fixed effects is used, the outcomes of which reveal that in all quantiles (10th to …
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 …
An Improved Wild Horse Optimization Algorithm For Reliability Based Optimal Dg Planning Of Radial Distribution Networks, Mohammed Hamouda Ali, Salah Kamel, Mohamed H. Hassan, Marcos Tostado-Véliz, Hossam Zawbaa
An Improved Wild Horse Optimization Algorithm For Reliability Based Optimal Dg Planning Of Radial Distribution Networks, Mohammed Hamouda Ali, Salah Kamel, Mohamed H. Hassan, Marcos Tostado-Véliz, Hossam Zawbaa
Articles
This paper introduces a novel technique for optimal distribution system (DS) planning with distributed generation (DG) systems. It is being done to see how active and reactive power injections affect the system’s voltage profile and energy losses. DG penetration in the power systems is one approach that has several advantages such as peak savings, loss lessening, voltage profile amelioration. It also intends to increase system reliability, stability, and security. The main goal of optimal distributed generation (ODG) is a guarantee to achieve the benefits mentioned previously to increase the overall system efficiency. For extremely vast and complicated systems, analytical approaches …
Adopting Scenario-Based Approach To Solve Optimal Reactive Power Dispatch Problem With Integration Of Wind And Solar Energy Using Improved Marine Predator Algorithm, Noor Habib Khan, Raheela Jamal, Mohamed Ebeed, Salah Kamel, Hamed Zeinoddini-Meymand, Hossam Zawbaa
Adopting Scenario-Based Approach To Solve Optimal Reactive Power Dispatch Problem With Integration Of Wind And Solar Energy Using Improved Marine Predator Algorithm, Noor Habib Khan, Raheela Jamal, Mohamed Ebeed, Salah Kamel, Hamed Zeinoddini-Meymand, Hossam Zawbaa
Articles
The penetration of renewable energy resources into electric power networks has been increased considerably to reduce the dependence of conventional energy resources, reducing the generation cost and greenhouse emissions. The wind and photovoltaic (PV) based systems are the most applied technologies in electrical systems compared to other technologies of renewable energy resources. However, there are some complications and challenges to incorporating these resources due to their stochastic nature, intermittency, and variability of output powers. Therefore, solving the optimal reactive power dispatch (ORPD) problem with considering the uncertainties of renewable energy resources is a challenging task. Application of the Marine Predators …
An Audio Processing Pipeline For Acquiring Diagnostic Quality Heart Sounds Via Mobile Phone, Davoud Shariat Panah, Andrew Hines, Joseph Mckeever, Susan Mckeever
An Audio Processing Pipeline For Acquiring Diagnostic Quality Heart Sounds Via Mobile Phone, Davoud Shariat Panah, Andrew Hines, Joseph Mckeever, Susan Mckeever
Articles
Recently, heart sound signals captured using mobile phones have been employed to develop data-driven heart disease detection systems. Such signals are generally captured in person by trained clinicians who can determine if the recorded heart sounds are of diagnosable quality. However, mobile phones have the potential to support heart health diagnostics, even where access to trained medical professionals is limited. To adopt mobile phones as self-diagnostic tools for the masses, we would need to have a mechanism to automatically establish that heart sounds recorded by non-expert users in uncontrolled conditions have the required quality for diagnostic purposes. This paper proposes …
Automated Extraction Of Genes Associated With Antibiotic Resistance From The Biomedical Literature, Andre Brincat, Markus Hofmann
Automated Extraction Of Genes Associated With Antibiotic Resistance From The Biomedical Literature, Andre Brincat, Markus Hofmann
Articles
The detection of bacterial antibiotic resistance phenotypes is important when carrying out clinical decisions for patient treatment. Conventional phenotypic testing involves culturing bacteria which requires a significant amount of time and work. Whole-genome sequencing is emerging as a fast alternative to resistance prediction, by considering the presence/absence of certain genes. A lot of research has focused on determining which bacterial genes cause antibiotic resistance and efforts are being made to consolidate these facts in knowledge bases (KBs). KBs are usually manually curated by domain experts to be of the highest quality. However, this limits the pace at which new facts …
Towards An Inclusive Co-Design Toolkit: Perceptions And Experiences Of Co-Design Stakeholders, Eamon Aswad, Emma Murphy, Claudia Fernandez-Rivera, Sarah Boland
Towards An Inclusive Co-Design Toolkit: Perceptions And Experiences Of Co-Design Stakeholders, Eamon Aswad, Emma Murphy, Claudia Fernandez-Rivera, Sarah Boland
Articles
Participatory design holds great potential for the creation of inclusive technology but existing toolkits and resources to support co-design are not always accessible to designers and co-designers with disabilities. In this paper we present two studies to assist in facilitating the creation of a sustainable, accessible, inclusive co-design toolkit for individuals with intellectual disabilities i) exploration of the perceptions and experiences of lecturers (n =5) and students (n= 5) involved in co-design activities via individual interviews and ii) a protocol and initial findings from focus groups with men and women with intellectual disabilities to inform on best co-design practices (n=15). …
Measuring Semantic Similarity Of Documents By Using Named Entity Recognition Methods, David Efraín Muñoz Morales
Measuring Semantic Similarity Of Documents By Using Named Entity Recognition Methods, David Efraín Muñoz Morales
Masters
The work presented in this thesis was born from the desire to map documents with similar semantic concepts between them. We decided to address this problem as a named entity recognition task, where we have identified key concepts in the texts we use, and we have categorized them. So, we can apply named entity recognition techniques and automatically recognize these key concepts inside other documents. However, we propose the use of a classification method based on the recognition of named entities or key phrases, where the method can detect similarities between key concepts of the texts to be analyzed, and …
Investigating How Speech And Animation Realism Influence The Perceived Personality Of Virtual Characters And Agents, Sean A. Thomas, Ylva Ferstl, Rachel Mcdonnell, Cathy Ennis
Investigating How Speech And Animation Realism Influence The Perceived Personality Of Virtual Characters And Agents, Sean A. Thomas, Ylva Ferstl, Rachel Mcdonnell, Cathy Ennis
Articles
The portrayed personality of virtual characters and agents is understood to influence how we perceive and engage with digital applications. Understanding how the features of speech and animation drive portrayed personality allows us to intentionally design characters to be more personalized and engaging. In this study, we use performance capture data of unscripted conversations from a variety of actors to explore the perceptual outcomes associated with the modalities of speech and motion. Specifically, we contrast full performance-driven characters to those portrayed by generated gestures and synthesized speech, analysing how the features of each influence portrayed personality according to the Big …
The 4c’S Of Pal – An Evidence-Based Model For Implementing Peer Assisted Learning For Mature Students, Nevan Bermingham, Frances Boylan, Barry J. Ryan
The 4c’S Of Pal – An Evidence-Based Model For Implementing Peer Assisted Learning For Mature Students, Nevan Bermingham, Frances Boylan, Barry J. Ryan
Articles
Peer Assisted Leaning (PAL) programmes have been shown to enhance learner confidence and have an overall positive effect on learner comprehension, particularly in subjects traditionally perceived as difficult. This research describes the findings of a three-cycle Action Research study into the perceived benefits of implementing such a programme for mature students enrolled on a computer science programming module on an Access Foundation Programme in an Irish University. The findings from this study suggest that peer learning programmes offer students a valued support structure that aids transition and acculturation into tertiary education whilst simultaneously improving their subject-matter comprehension and confidence. An …
"What's In A Name?”: The Use Of Instructional Design In Overcoming Terminology Barriers Associated With Dark Patterns, Andrea Curley, Damian Gordon, Dympna O'Sullivan
"What's In A Name?”: The Use Of Instructional Design In Overcoming Terminology Barriers Associated With Dark Patterns, Andrea Curley, Damian Gordon, Dympna O'Sullivan
Conference Papers
Many users experience a phenomena when they are shopping on-line where they feel they are being pressured to either spend more money than they had intended, or to share more personal data than they wanted. In academic circles we use the term “Dark Patterns” to describe these deceptive practices, and categorize them as being within the discipline of User Experience (Narayanan, 2020). As academics it is important to name phenomena, and to categorize them, so that we can discuss and analyze these issues. However, this particular topic is one that all users should be made aware of when interacting online, …
A Framework Of Web-Based Dark Patterns That Can Be Detected Manually Or Automatically, Ioannis Stavrakakis, Andrea Curley, Dympna O'Sullivan, Damian Gordon, Brendan Tierney
A Framework Of Web-Based Dark Patterns That Can Be Detected Manually Or Automatically, Ioannis Stavrakakis, Andrea Curley, Dympna O'Sullivan, Damian Gordon, Brendan Tierney
Articles
This research explores the design and development of a framework for the detection of Dark Patterns, which are a series of user interface tricks that manipulate users into actions that they do not intend to do, for example, share more data than they want to, or spend more money than they plan to. The interface does this using either deception or other psychological nudges. User Interface experts have categorized a number of these tricks that are commonly used and have called them Dark Patterns. They are typically varied in their form and what they do, and the goal of this …
Explaining Deep Learning Models For Tabular Data Using Layer-Wise Relevance Propagation, Ihsan Ullah, Andre Rios, Vaibhov Gala, Susan Mckeever
Explaining Deep Learning Models For Tabular Data Using Layer-Wise Relevance Propagation, Ihsan Ullah, Andre Rios, Vaibhov Gala, Susan Mckeever
Articles
Trust and credibility in machine learning models are bolstered by the ability of a model to explain its decisions. While explainability of deep learning models is a well-known challenge, a further challenge is clarity of the explanation itself for relevant stakeholders of the model. Layer-wise Relevance Propagation (LRP), an established explainability technique developed for deep models in computer vision, provides intuitive human-readable heat maps of input images. We present the novel application of LRP with tabular datasets containing mixed data (categorical and numerical) using a deep neural network (1D-CNN), for Credit Card Fraud detection and Telecom Customer Churn prediction use …
Notions Of Explainability And Evaluation Approaches For Explainable Artificial Intelligence, Giulia Vilone, Luca Longo
Notions Of Explainability And Evaluation Approaches For Explainable Artificial Intelligence, Giulia Vilone, Luca Longo
Articles
Explainable Artificial Intelligence (XAI) has experienced a significant growth over the last few years. This is due to the widespread application of machine learning, particularly deep learning, that has led to the development of highly accurate models that lack explainability and interpretability. A plethora of methods to tackle this problem have been proposed, developed and tested, coupled with several studies attempting to define the concept of explainability and its evaluation. This systematic review contributes to the body of knowledge by clustering all the scientific studies via a hierarchical system that classifies theories and notions related to the concept of explainability …
Extending R2rml-F To Support Dynamic Datatype And Language Tags, Aparna Nayak, Bojan Bozic, Luca Longo
Extending R2rml-F To Support Dynamic Datatype And Language Tags, Aparna Nayak, Bojan Bozic, Luca Longo
Conference papers
Linked data is often generated from raw data with the help of mapping languages. Complex data transformation is one of the essential parts while uplifting data which either can be implemented as custom solutions or separated from the mapping process. In this paper, we propose an approach of separating complex data transformations from the mapping process that can still be reusable across the systems. In the proposed method, complex data transformations include the entailment of (i) language tag and (ii) datatype present at the data source. The proposed method also includes inferring missing datatype information. We extended R2RML-F to handle …
A Novel Parabolic Model Of Instructional Efficiency Grounded On Ideal Mental Workload And Performance, Luca Longo, Murali Rajendran
A Novel Parabolic Model Of Instructional Efficiency Grounded On Ideal Mental Workload And Performance, Luca Longo, Murali Rajendran
Articles
Instructional efficiency within education is a measurable concept and models have been proposed to assess it. The main assumption behind these models is that efficiency is the capacity to achieve established goals at the minimal expense of resources. This article challenges this assumption by contributing to the body of Knowledge with a novel model that is grounded on ideal mental workload and performance, namely the parabolic model of instructional efficiency. A comparative empirical investigation has been constructed to demonstrate the potential of this model for instructional design evaluation. Evidence demonstrated that this model achieved a good concurrent validity with the …
Provenance: An Intermediary-Free Solution For Digital Content Verification, Bilal Yousuf, M. Atif Qureshi, Brendan Spillane, Gary Munnelly, Oisin Carroll, Matthew Runswick, Kirsty Park, Eileen Culloty, Owen Conlan, Jane Suiter
Provenance: An Intermediary-Free Solution For Digital Content Verification, Bilal Yousuf, M. Atif Qureshi, Brendan Spillane, Gary Munnelly, Oisin Carroll, Matthew Runswick, Kirsty Park, Eileen Culloty, Owen Conlan, Jane Suiter
Articles
The threat posed by misinformation and disinformation is one of the defining challenges of the 21st century. Provenance is designed to help combat this threat by warning users when the content they are looking at may be misinformation or disinformation. It is also designed to improve media literacy among its users and ultimately reduce susceptibility to the threat among vulnerable groups within society. The Provenance browser plugin checks the content that users see on the Internet and social media and provides warnings in their browser or social media feed. Unlike similar plugins, which require human experts to provide evaluations and …
Towards A Framework For Comparing Functionalities Of Multimorbidity Clinical Decision Support: A Literature-Based Feature Set And Benchmark Cases., Dympna O'Sullivan, William Van Woensel, Szymon Wilk, Samson Tu, Wojtek Michalowski, Samina Abidi, Marc Carrier, Ruth Edry, Irit Hochberg, Stephen Kingwell, Alexandra Kogan, Martin Michalowski, Hugh O'Sullivan, Mor Peleg
Towards A Framework For Comparing Functionalities Of Multimorbidity Clinical Decision Support: A Literature-Based Feature Set And Benchmark Cases., Dympna O'Sullivan, William Van Woensel, Szymon Wilk, Samson Tu, Wojtek Michalowski, Samina Abidi, Marc Carrier, Ruth Edry, Irit Hochberg, Stephen Kingwell, Alexandra Kogan, Martin Michalowski, Hugh O'Sullivan, Mor Peleg
Articles
Multimorbidity, the coexistence of two or more health conditions, has become more prevalent as mortality rates in many countries have declined and their populations have aged. Multimorbidity presents significant difficulties for Clinical Decision Support Systems (CDSS), particularly in cases where recommendations from relevant clinical guidelines offer conflicting advice. A number of research groups are developing computer-interpretable guideline (CIG) modeling formalisms that integrate recommendations from multiple Clinical Practice Guidelines (CPGs) for knowledge-based multimorbidity decision support. In this paper we describe work towards the development of a framework for comparing the different approaches to multimorbidity CIG-based clinical decision support (MGCDS). We present …
A Quantitative Evaluation Of Global, Rule-Based Explanations Of Post-Hoc, Model Agnostic Methods, Giulia Vilone, Luca Longo
A Quantitative Evaluation Of Global, Rule-Based Explanations Of Post-Hoc, Model Agnostic Methods, Giulia Vilone, Luca Longo
Articles
Understanding the inferences of data-driven, machine-learned models can be seen as a process that discloses the relationships between their input and output. These relationships consist and can be represented as a set of inference rules. However, the models usually do not explicit these rules to their end-users who, subsequently, perceive them as black-boxes and might not trust their predictions. Therefore, scholars have proposed several methods for extracting rules from data-driven machine-learned models to explain their logic. However, limited work exists on the evaluation and comparison of these methods. This study proposes a novel comparative approach to evaluate and compare the …
Check Your Tech - The Ethics Of Deepfakes In A Political Context, Dympna O'Sullivan, Damian Gordon, Ioannis Stavrakakis, Michael Collins
Check Your Tech - The Ethics Of Deepfakes In A Political Context, Dympna O'Sullivan, Damian Gordon, Ioannis Stavrakakis, Michael Collins
Conference papers
No abstract provided.
Check Your Tech - The Ethics Of Gamification In Education, Dympna O'Sullivan, Ioannis Stavrakakis, Damian Gordon, Anna Becevel
Check Your Tech - The Ethics Of Gamification In Education, Dympna O'Sullivan, Ioannis Stavrakakis, Damian Gordon, Anna Becevel
Conference papers
No abstract provided.
The Future Of Medicine Is Digital: Developing Educational Materials To Explore The Ethics Of Digital Pills., Dympna O'Sullivan, J. Paul Gibson, Yael Jacob, Ioannis Stavrakakis, Damian Gordon
The Future Of Medicine Is Digital: Developing Educational Materials To Explore The Ethics Of Digital Pills., Dympna O'Sullivan, J. Paul Gibson, Yael Jacob, Ioannis Stavrakakis, Damian Gordon
Conference papers
Digital Pills are a drug-device technology that permit to combine traditional medications with a monitoring system that automatically records data about medication adherence and patients’ physiological data. They are a promising innovation in digital medicine, however their use has raised a number of ethical concerns. In this paper, we outline some of the main Digital Pills technologies and explore key ethical challenges surrounding their use. In this paper, we introduce educational materials we have developed that provide an insight into the technologies and ethical aspects that underpin Digital Pills.
(Linked) Data Quality Assessment: An Ontological Approach, Aparna Nayak, Bojan Bozic, Luca Longo
(Linked) Data Quality Assessment: An Ontological Approach, Aparna Nayak, Bojan Bozic, Luca Longo
Conference papers
The effective functioning of data-intensive applications usually requires that the dataset should be of high quality. The quality depends on the task they will be used for. However, it is possible to identify task-independent data quality dimensions which are solely related to data themselves and can be extracted with the help of rule mining/pattern mining. In order to assess and improve data quality, we propose an ontological approach to report data quality violated triples. Our goal is to provide data stakeholders with a set of methods and techniques to guide them in assessing and improving data quality
Human Or Robot?: Investigating Voice, Appearance And Gesture Motion Realism Of Conversational Social Agents, Ylva Ferstl, Sean Thomas, Cédric Guiard, Cathy Ennis, Rachel Mcdonnell
Human Or Robot?: Investigating Voice, Appearance And Gesture Motion Realism Of Conversational Social Agents, Ylva Ferstl, Sean Thomas, Cédric Guiard, Cathy Ennis, Rachel Mcdonnell
Conference papers
Research on creation of virtual humans enables increasing automatization of their behavior, including synthesis of verbal and nonverbal behavior. As the achievable realism of different aspects of agent design evolves asynchronously, it is important to understand if and how divergence in realism between behavioral channels can elicit negative user responses. Specifically, in this work, we investigate the question of whether autonomous virtual agents relying on synthetic text-to-speech voices should portray a corresponding level of realism in the non-verbal channels of motion and visual appearance, or if, alternatively, the best available realism of each channel should be used. In two perceptual …
The Development Of Teaching Case Studies To Explore Ethical Issues Associated With Computer Programming, Michael Collins, Damian Gordon, Dympna O'Sullivan
The Development Of Teaching Case Studies To Explore Ethical Issues Associated With Computer Programming, Michael Collins, Damian Gordon, Dympna O'Sullivan
Conference papers
In the past decade software products have become pervasive in many aspects of people’s lives around the world. Unfortunately, the quality of the experience an individual has interacting with that software is dependent on the quality of the software itself, and it is becoming more and more evident that many large software products contain a range of issues and errors, and these issues are not known to the developers of these systems, and they are unaware of the deleterious impacts of those issues on the individuals who use these systems. The authors of this paper are developing a new digital …
Exploring The Personality Of Virtual Tutors In Conversational Foreign Language Practice, Johanna Dobbriner, Cathy Ennis, Robert J. Ross
Exploring The Personality Of Virtual Tutors In Conversational Foreign Language Practice, Johanna Dobbriner, Cathy Ennis, Robert J. Ross
Conference papers
Fluid interaction between virtual agents and humans requires the understanding of many issues of conversational pragmatics. One such issue is the interaction between communication strategy and personality. As a step towards developing models of personality driven pragmatics policies, in this paper, we present our initial experiment to explore differences in user interaction with two contrasting avatar personalities. Each user saw a single personality in a video-call setting and gave feedback on the interaction. Our expectations, that a more extroverted outgoing positive personality would be a more successful tutor, were only partially confirmed. While this personality did induce longer conversations in …
Sediqa: Sound Emitting Document Image Quality Assessment In A Reading Aid For The Visually Impaired, Jane Courtney
Sediqa: Sound Emitting Document Image Quality Assessment In A Reading Aid For The Visually Impaired, Jane Courtney
Articles
For visually impaired people (VIPs), the ability to convert text to sound can mean a new level of independence or the simple joy of a good book. With significant advances in optical character recognition (OCR) in recent years, a number of reading aids are appearing on the market. These reading aids convert images captured by a camera to text which can then be read aloud. However, all of these reading aids suffer from a key issue—the user must be able to visually target the text and capture an image of sufficient quality for the OCR algorithm to function—no small task …
Classification Of Explainable Artificial Intelligence Methods Through Their Output Formats, Giulia Vilone, Luca Longo
Classification Of Explainable Artificial Intelligence Methods Through Their Output Formats, Giulia Vilone, Luca Longo
Articles
Machine and deep learning have proven their utility to generate data-driven models with high accuracy and precision. However, their non-linear, complex structures are often difficult to interpret. Consequently, many scholars have developed a plethora of methods to explain their functioning and the logic of their inferences. This systematic review aimed to organise these methods into a hierarchical classification system that builds upon and extends existing taxonomies by adding a significant dimension—the output formats. The reviewed scientific papers were retrieved by conducting an initial search on Google Scholar with the keywords “explainable artificial intelligence”; “explainable machine learning”; and “interpretable machine learning”. …
Adaptable And Reusable Educational ‘Bricks’ For Teaching Computer Science Ethics, Andrea Curley, Damian Gordon, Ioannis Stavrakakis, Anna Becevel, J.P. Gibson, Dympna O'Sullivan
Adaptable And Reusable Educational ‘Bricks’ For Teaching Computer Science Ethics, Andrea Curley, Damian Gordon, Ioannis Stavrakakis, Anna Becevel, J.P. Gibson, Dympna O'Sullivan
Conference papers
No abstract provided.