Digital Commons Network^™

Inéire: An Interpretable Nlp Pipeline Summarizing Inclusive Policy Making Concerning Migrants In Ireland, Arefeh Kazem, Arjumand Younus, Mingyeong Jeon, Muhammad Atif Qureshi, Simon Caton

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Reaching marginal and other migrant communities to elicit their political views and opinions is a well-known challenge. Social media has enabled a certain amount of online activism and participation, especially in societies with abundant multicultural identities. However, it can be quite challenging to isolate the voice of the migrant in English-speaking countries, especially with an abundance of content in English on social media. In this paper, we pursue a case study of Ireland’s Twitter landscape, specifically migrant and native activists. We present a methodology that can accurately ( >80% ) isolate the Irish migrant voice with as little as 25 …

Technical Report: A Framework For Confusion Mitigation In Task-Oriented Interactions, Na Li, Robert J. Ross

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Confusion is a mental state that can be triggered in task-oriented interactions and which can if left unattended lead to boredom, frustration, or disengagement from the task at hand. Since previous work has demonstrated that confusion can be detected in embodied situated interactions from visual and auditory cues, in this technique report, we propose appropriate interaction structures which should be used to mitigate confusion. We motivate and describe this dialogue mechanism through an information state-style policy with examples, and also outline the approach we are taking to integrate such a meta-conversational goal alongside core task-oriented considerations in modern data driven …

Current Topics In Technology-Enabled Stroke Rehabilitation And Reintegration: A Scoping Review And Content Analysis, Katryna Cisek

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Background. There is a worldwide health crisis stemming from the rising incidence of various debilitating chronic diseases, with stroke as a leading contributor. Chronic stroke management encompasses rehabilitation and reintegration, and can require decades of personalized medicine and care. Information technology (IT) tools have the potential to support individuals managing chronic stroke symptoms. Objectives. This scoping review identifies prevalent topics and concepts in research literature on IT technology for stroke rehabilitation and reintegration, utilizing content analysis, based on topic modelling techniques from natural language processing to identify gaps in this literature. Eligibility Criteria. Our methodological search initially identified over 14,000 …

Know An Emotion By The Company It Keeps: Word Embeddings From Reddit/Coronavirus, Alejandro García-Rudolph, David Sanchez-Pinsach, Dietmar Frey, Eloy Opisso, Katryna Cisek, John Kelleher

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Social media is a crucial communication tool (e.g., with 430 million monthly active users in online forums such as Reddit), being an objective of Natural Language Processing (NLP) techniques. One of them (word embeddings) is based on the quotation, “You shall know a word by the company it keeps,” highlighting the importance of context in NLP. Meanwhile, “Context is everything in Emotion Research.” Therefore, we aimed to train a model (W2V) for generating word associations (also known as embeddings) using a popular Coronavirus Reddit forum, validate them using public evidence and apply them to the discovery of context for specific …

How Online Discourse Networks Fields Of Practice: The Discursive Negotiation Of Autonomy On Art Organisation About Pages, Tommie Soro

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This article examines how the online discourse of art organisations forges relationships between the artworld and the fields of politics and economy. Combining elements of Pierre Bourdieu’s field analysis and Norman Fairclough’s critical discourse analysis, the article analyses an elite art magazine, e-flux, and an elite art museum, IMMA, and the activities of discourses, genres, and utterances on their about pages. Its results suggest that the about pages of these organisations forge links between the artworld and the fields of politics and economy by mobilising discourse in these fields and by incorporating discourse practices from these fields. The ideological tension …

Performance Improvement Of Hybrid System Based Dfig-Wind/Pv/Batteries Connected To Dc And Ac Grid By Applying Intelligent Control, Younes Sahri, Salah Tamalouzt, Sofia Lalouni Belaid, Mohit Bajaj, Sherif S.M. Ghoneim, Hossam Zawbaa, Salah Kamel

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One of the main causes of CO2 emissions is the production of electrical energy. Therefore, many researchers goal’s is to develop renewable power systems. This paper proposes a new intelligent control development of hybrid PV–Wind-Batteries. Neuro-Fuzzy Direct Power Control (NF-DPC) is invested in order to enhance system performance and generated currents quality. An improved MPPT algorithm based on Fuzzy Controller (FC) is invested for PV power optimization. In addition, a new Modified Fuzzy Direct Power Control (MF-DPC) is developed and applied to the grid side converter to control the active and reactive power by monitoring the involved active power flow …

Toward Inclusive Online Environments: Counterfactual-Inspired Xai For Detecting And Interpreting Hateful And Offensive Tweets, Muhammad Deedahwar Mazhar Qureshi, Muhammad Atif Qureshi, Wael Rashwan

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The prevalence of hate speech and offensive language on social media platforms such as Twitter has significant consequences, ranging from psychological harm to the polarization of societies. Consequently, social media companies have implemented content moderation measures to curb harmful or discriminatory language. However, a lack of consistency and transparency hinders their ability to achieve desired outcomes. This article evaluates various ML models, including an ensemble, Explainable Boosting Machine (EBM), and Linear Support Vector Classifier (SVC), on a public dataset of 24,792 tweets by T. Davidson, categorizing tweets into three classes: hate, offensive, and neither. The top-performing model achieves a weighted …

Persuasive Communication Systems: A Machine Learning Approach To Predict The Effect Of Linguistic Styles And Persuasion Techniques, Annye Braca, Pierpaolo Dondio

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Prediction is a critical task in targeted online advertising, where predictions better than random guessing can translate to real economic return. This study aims to use machine learning (ML) methods to identify individuals who respond well to certain linguistic styles/persuasion techniques based on Aristotle’s means of persuasion, rhetorical devices, cognitive theories and Cialdini’s principles, given their psychometric profile.

Discovering Child Sexual Abuse Material Creators’ Behaviors And Preferences On The Dark Web, Vuong Ngo, Rahul Gajula, Christina Thorpe, Susan Mckeever

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Background: Producing, distributing or discussing child sexual abuse materials (CSAM) is often committed through the dark web in order to remain hidden from search engines and regular users. Additionally, on the dark web, the CSAM creators employ various techniques to avoid detection and conceal their activities. The large volume of CSAM on the dark web presents a global social problem and poses a significant challenge for helplines, hotlines and law enforcement agencies.

Objective: Identifying CSAM discussions on the dark web and uncovering associated metadata insights into characteristics, behaviours and motivation of CSAM creators.

Participants and Setting: We have conducted an …

Evaluating Large Delay Estimation Techniques For Assisted Living Environments, Swarnadeep Bagchi, Ruairí De Fréin

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Abstract Phase wraparound due to large inter-sensor spacings in multi-channel demixing limits the range of relative delays that many time–frequency relative delay estimators can estimate. The performance of a large relative delay estimation method, called the elevatogram, is evaluated in the presence of significant phase wraparound. This paper compares the elevatogram with the popular relative delay estimator used in DUET and the brute-force approach in D-AdRess and analyses its computational efficiency. The elevatogram can accurately estimate relative delays of speech signals of up to 800 samples, whereas DUET and D-AdRess were limited to delays of 7 and 35 samples, given …

A Framework For Sexism Detection On Social Media Via Byt5 And Tabnet, Arjumand Younus, Muhammad Atif Qureshi

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Hateful and offensive content on social media platforms particularly content directed towards a specific gender is a great impediment towards equality, diversity and inclusion. Social media platforms are facing increasing pressure to work towards regulation of such content; and this has directed researchers in text mining to work towards hate speech identification algorithms. One such attempt is sexism detection for which mostly transformer-based text methods have been proposed. We propose a combination of byte-level model ByT5 with tabular modeling via TabNet that has at its core an ability to take into account platform and language aspects of the challenging task …

Investigating How Speech And Animation Realism Influence The Perceived Personality Of Virtual Characters And Agents, Sean A. Thomas, Ylva Ferstl, Rachel Mcdonnell, Cathy Ennis

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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 …

Human Mental Workload: A Survey And A Novel Inclusive Definition, Luca Longo, Christopher D. Wickens, Gabriella Hancock, P.A. Hancock

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Human mental workload is arguably the most invoked multidimensional construct in Human Factors and Ergonomics, getting momentum also in Neuroscience and Neuroergonomics. Uncertainties exist in its characterization, motivating the design and development of computational models, thus recently and actively receiving support from the discipline of Computer Science. However, its role in human performance prediction is assured. This work is aimed at providing a synthesis of the current state of the art in human mental workload assessment through considerations, definitions, measurement techniques as well as applications, Findings suggest that, despite an increasing number of associated research works, a single, reliable and …

Examining The Size Of The Latent Space Of Convolutional Variational Autoencoders Trained With Spectral Topographic Maps Of Eeg Frequency Bands, Taufique Ahmed, Luca Longo

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Electroencephalography (EEG) is a technique of recording brain electrical potentials using electrodes placed on the scalp [1]. It is well known that EEG signals contain essential information in the frequency, temporal and spatial domains. For example, some studies have converted EEG signals into topographic power head maps to preserve spatial information [2]. Others have produced spectral topographic head maps of different EEG bands to both preserve information in The associate editor coordinating the review of this manuscript and approving it for publication was Ludovico Minati . the spatial domain and take advantage of the information in the frequency domain [3]. …

Audio Representations For Deep Learning In Sound Synthesis: A Review, Anastasia Natsiou, Sean O'Leary

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The rise of deep learning algorithms has led many researchers to withdraw from using classic signal processing methods for sound generation. Deep learning models have achieved expressive voice synthesis, realistic sound textures, and musical notes from virtual instruments. However, the most suitable deep learning architecture is still under investigation. The choice of architecture is tightly coupled to the audio representations. A sound’s original waveform can be too dense and rich for deep learning models to deal with efficiently - and complexity increases training time and computational cost. Also, it does not represent sound in the manner in which it is …

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

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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 …

Examining The Modelling Capabilities Of Defeasible Argumentation And Non-Monotonic Fuzzy Reasoning, Luca Longo, Lucas Rizzo, Pierpaolo Dondio

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Knowledge-representation and reasoning methods have been extensively researched within Artificial Intelligence. Among these, argumentation has emerged as an ideal paradigm for inference under uncertainty with conflicting knowledge. Its value has been predominantly demonstrated via analyses of the topological structure of graphs of arguments and its formal properties. However, limited research exists on the examination and comparison of its inferential capacity in real-world modelling tasks and against other knowledge-representation and non-monotonic reasoning methods. This study is focused on a novel comparison between defeasible argumentation and non-monotonic fuzzy reasoning when applied to the representation of the ill-defined construct of human mental workload …

Parents' Experiences Of A Language-Focused Home Visiting Scheme In Ireland, Aisling Ni Dhiorbhain Dr, Maire Mhic Mhathuna, Padraig Ó Duibhir Dr

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This article reports parents’ experiences of the Tús Maith (Good Start) home visiting scheme in South-West Ireland. The goal of Tús Maith is to support parents who wish to speak Irish to their children at home in the Kerry Gaeltacht, an Irish-speaking heartland area. Home visitors spend an hour a week, over a period of six weeks, interacting with children and parents with varying levels of competency in Irish. Home visitors who are native speakers of Irish, offer individualised guidance on how to promote the use of Irish as a home language, while encouraging families to engage in activities …

Opinion-Mining On Marglish And Devanagari Comments Of Youtube Cookery Channels Using Parametric And Non-Parametric Learning Models, Sonali Shah, Abhishek Kaushik, Shubham Sharma, Janice Shah

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No abstract provided.

An Examination Of The Role Of Spatial Ability In The Process Of Problem Solving In Chemical Engineering, Sheryl Sorby, Gavin Duffy, Norman Loney

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Engineers often communicate with one another through drawings or sketches and understanding technical information through graphical representations is a skill necessary for engineering practice. Well-developed spatial skills are known to be important to understanding technical drawings and are therefore, important to success in engineering. Unfortunately, of all cognitive processes, spatial skills show robust gender differences, favouring males, which could contribute to the underrepresentation of women in engineering. In this research, we administered a test of spatial cognition to students enrolled in a common 3rd year course in chemical engineering . In a second session, students were given a set of …

Size Matters: The Impact Of Training Size In Taxonomically-Enriched Word Embeddings, Alfredo Maldonado, Filip Klubicka, John D. Kelleher

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Word embeddings trained on natural corpora (e.g., newspaper collections, Wikipedia or the Web) excel in capturing thematic similarity (“topical relatedness”) on word pairs such as ‘coffee’ and ‘cup’ or ’bus’ and ‘road’. However, they are less successful on pairs showing taxonomic similarity, like ‘cup’ and ‘mug’ (near synonyms) or ‘bus’ and ‘train’ (types of public transport). Moreover, purely taxonomy-based embeddings (e.g. those trained on a random-walk of WordNet’s structure) outperform natural-corpus embeddings in taxonomic similarity but underperform them in thematic similarity. Previous work suggests that performance gains in both types of similarity can be achieved by enriching natural-corpus embeddings with …

Large-Scale Green Supplier Selection Approach Under A Q-Rung Interval-Valued Orthopair Fuzzy Environment, Limei Liu, Wenzhi Cao, Biao Shi, Ming Tang

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As enterprises pay more and more attention to environmental issues, the green supply chain management (GSCM) mode has been extensively utilized to guarantee profit and sustainable development. Greensupplierselection(GSS),whichisakeysegmentofGSCM,hasbeeninvestigated to put forward plenty of GSS approaches.

Languages For Different Health Information Readers: Multitrait-Multimethod Content Analysis Of Cochrane Systematic Reviews Textual Summary Formats, Jasna Karačić, Pierpaolo Dondio, Ivan Buljan, Darko Hren, Ana Marušić

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Background: Although subjective expressions and linguistic fluency have been shown as important factors in processing and interpreting textual facts, analyses of these traits in textual health information for different audiences are lacking. We analyzed the readability and linguistic psychological and emotional characteristics of different textual summary formats of Cochrane systematic reviews. Methods: We performed a multitrait-multimethod cross-sectional study of Press releases available at Cochrane web site (n= 162) and corresponding Scientific abstracts (n= 158), Cochrane Clinical Answers (n= 35) and Plain language summaries in English (n= 156), French (n= 101), German (n= 41) and Croatian (n=156). We used SMOG index …

Persistence Pays Off: Paying Attention To What The Lstm Gating Mechanism Persists, John D. Kelleher, Giancarlo Salton

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Language Models (LMs) are important components in several Natural Language Processing systems. Recurrent Neural Network LMs composed of LSTM units, especially those augmented with an external memory, have achieved state-of-the-art results. However, these models still struggle to process long sequences which are more likely to contain long-distance dependencies because of information fading and a bias towards more recent information. In this paper we demonstrate an effective mechanism for retrieving information in a memory augmented LSTM LM based on attending to information in memory in proportion to the number of timesteps the LSTM gating mechanism persisted the information.

Quantitative Fine-Grained Human Evaluation Of Machine Translation Systems: A Case Study On English To Croatian, Filip Klubicka, Antonio Toral, Victor Manuel Sanchez-Cartagena

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This paper presents a quantitative fine-grained manual evaluation approach to comparing the performance of different machine translation (MT) systems. We build upon the well-established Multidimensional Quality Metrics (MQM) error taxonomy and implement a novel method that assesses whether the differences in performance for MQM error types between different MT systems are statistically significant. We conduct a case study for English-to- Croatian, a language direction that involves translating into a morphologically rich language, for which we compare three MT systems belonging to different paradigms: pure phrase-based, factored phrase-based and neural. First, we design an MQM-compliant error taxonomy tailored to the relevant …

Assessment Of Mental Workload: A Comparison Of Machine Learning Methods And Subjective Assessment Techniques, Karim Moustafa, Saturnino Luz, Luca Longo

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Mental workload (MWL) measurement is a complex multidisciplinary research field. In the last 50 years of research endeavour, MWL measurement has mainly produced theory-driven models. Some of the reasons for justifying this trend includes the omnipresent uncertainty about how to define the construct of MWL and the limited use of datadriven research methodologies. This work presents novel research focused on the investigation of the capability of a selection of supervised Machine Learning (ML) classification techniques to produce data-driven computational models of MWL for the prediction of objective performance. These are then compared to two state-of-the-art subjective techniques for the assessment …

Optimized Sliding Mode Control To Maximize Existence Region For Single-Phase Dynamic Voltage Restorers, Samet Biricik, Hasan Komurcugil

Articles

This paper presents an optimized sliding mode control (SMC) strategy to maximize existence region for single-phase dynamic voltage restorers. It is shown analytically that there exists an optimum sliding coefficient which enlarges the existence region of the sliding mode to its maximum. Also, it is pointed out that the optimum sliding coefficient improves the dynamic response. In addition, a double-band hysteresis control which ensures the switching of a transistor in the voltage source inverter during a half-cycle while it remains either on or off in the other half cycle is used to mitigate the switching frequency. The theoretical considerations and …

Robust Fuzzy-Sliding Mode Based Upfc Controller For Transient Stability Analysis In Autonomous Wind-Diesel-Pv Hybrid System, Asit Mohanty, Sandipan Patra, Prakash K. Ray

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This study presents a comparative study of transient stability and reactive power compensation issues in an autonomous wind–diesel-photovoltaic based hybrid system (HS) using robust fuzzy-sliding mode based unified power flow controller (UPFC). A linearised small-signal model of the different elements of the HS is considered for the transient stability analysis in the HS under varying loading conditions. An IEEE type 1 excitation system is considered for the synchronous generator in the HS, with negligible saturation characteristic, for detailed voltage stability analysis. It is noted from the simulation results that the performance of UPFC is superior to static VAR compensator and …

Phenomenology And Hermeneutic Phenomenology: The Philosophy, The Methodologies And Using Hermeneutic Phenomenology To Investigate Lecturers' Experiences Of Curriculum Design, Arthur Sloan, Brian Bowe

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This article investigates the philosophy of phenomenology, continuing to examine and describe it as a methodology. There are different methods of phenomenology, divided by their different perspectives of what phenomenology is: largely grouped into the two types of descriptive and interpretive phenomenology. The focal methodology is hermeneutic phenomenology – one type of phenomenological methodology among interpretive phenomenological methodologies. The context for phenomenology and the location of hermeneutic phenomenology is explained through its historic antecedents. When using phenomenology as a methodology there are criteria for data gathering and data analysis and examples of these are cited in this paper. Also in …

Perception Based Misunderstandings In Human-Computer Dialogues, Niels Schütte, John D. Kelleher, Brian Mac Namee

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In a situated dialogue, misunderstandings may arise if the participants perceive or interpret the environment in different ways. In human-computer dialogue this may be due the sensor errors. We present an experiment system and a series of experiments in which we investigate this problem.