Digital Commons Network^™

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 …

On The Documentation Of Refactoring Types, Eman Abdullah Alomar, Jiaqian Liu, Kenneth Addo, Mohamed Wiem Mkaouer, Christian D. Newman, Ali Ouni, Zhe Yu

Articles

Commit messages are the atomic level of software documentation. They provide a natural language description of the code change and its purpose. Messages are critical for software maintenance and program comprehension. Unlike documenting feature updates and bug fixes, little is known about how developers document their refactoring activities. Specifically, developers can perform multiple refactoring operations, including moving methods, extracting classes, renaming attributes, for various reasons, such as improving software quality, managing technical debt, and removing defects. Yet, there is no systematic study that analyzes the extent to which the documentation of refactoring accurately describes the refactoring operations performed at the …

The Circle Of Life: The Mathematics Of Predator-Prey Dynamics, John Butler, Rebecca Brady

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Some animals hunt other animals to feed themselves; these animals are called predators. Animals who are hunted and eaten are known as prey. What do you think would happen if a predator were introduced to an ecosystem where the prey previously lived without fear of being hunted? Would the new predator eat all the prey animals until they go extinct? Actually, the relationship between predator and prey is far more interesting than this. In this article, we show what the predator-prey relationship looks like over time and explain how scientists can make predictions about future population levels, all using basic …

A Nanoscale Shape-Discovery Framework Supporting Systematic Investigations Of Shape-Dependent Biological Effects And Immunomodulation, Wei Zhang, Hender Lopez, Luca Boselli, Paolo Bigini, André Perez-Potti, Zengchun Xie, Valentina Castagnola, Qi Cai, Camila P. Silveira, Joao M. De Araujo, Laura Talamini, Nicolò Panini, Giuseppe Ristagno, Martina B. Violatto, Stéphanie Devineau, Marco P. Monopoli, Mario Salmona, Valeria A. Giannone, Sandra Lara, Kenneth A. Dawson, Yan Yan

Articles

Since it is now possible to make, in a controlled fashion, an almost unlimited variety of nanostructure shapes, it is of increasing interest to understand the forms of biological control that nanoscale shape allows. However, a priori rational investigation of such a vast universe of shapes appears to present intractable fundamental and practical challenges. This has limited the useful systematic investigation of their biological interactions and the development of innovative nanoscale shape-dependent therapies. Here, we introduce a concept of biologically relevant inductive nanoscale shape discovery and evaluation that is ideally suited to, and will ultimately become, a vehicle for machine …

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 …

Newgrange Skyscape In Stellarium, Frank Prendergast

Articles

Newgrange Skyscape in Stellarium is a new customised landscape planetarium model giving the user the unique ability to interrogate the dynamic sky above the Boyne Valley on any date of interest during the hours of daylight or darkness. Archaeological, astronomical and topographical points of interest are labelled in the model and visible even during the hours of darkness. These are summarily described in a short gazetteer appended at the end of the instruction document to encourage further exploration of the wonderful heritage found in the Boyne Valley and beyond.

Watch on Youtube: https://www.youtube.com/watch?app=desktop&v=aGPsVGBXkY4

Watch on Vimeo: https://vimeo.com/493351576

Artificial Intelligence-Based Power System Stabilizers For Frequency Stability Enhancement In Multi-Machine Power Systems, Aliyu Sabo, Noor Izzri Abdul Wahab, Mohammad Lutfi Othman, Mai Zurwatul Ahlam Mohd Jaffar, Hakan Acikgoz, Hamed Nafisi, Hossein Shahinzadeh

Articles

Low frequency oscillations (LFOs) occur in a system of interconnected generators connected by weak interconnection. A power system stabilizer (PSS) is commonly used to improve the capacity of the power system dampening. Under a variety of operating conditions, traditional PSSs fail to deliver superior damping. To address this issue, a Farmland Fertility Algorithm (FFA-PSSs controller) was used to solve an optimization problem for optimal design of PSSs system parameters, and its performance efficiency was compared to GA and PSO-based PSSs controllers. In addition to PSS, flexible current transmission (FACTS) devices are widely used. PSSs controllers and FACTS devices are frequently …

Knowtext: Auto-Generated Knowledge Graphs For Custom Domain Applications, Bojan Bozic, Jayadeep Kumar Sasikumar, Tamara Matthews

Articles

While industrial Knowledge Graphs enable information extraction from massive data volumes creating the backbone of the Semantic Web, the specialised, custom designed knowledge graphs focused on enterprise specific information are an emerging trend. We present “KnowText”, an application that performs automatic generation of custom Knowledge Graphs from unstructured text and enables fast information extraction based on graph visualisation and free text query methods designed for non-specialist users. An OWL ontology automatically extracted from text is linked to the knowledge graph and used as a knowledge base. A basic ontological schema is provided including 16 Classes and Data type Properties. The …

On Preserving The Behavior In Software Refactoring: A Systematic Mapping Study, Eman Abdullah Alomar, Mohamed Wiem Mkaouer, Christian D. Newman, Ali Ouni

Articles

Context: Refactoring is the art of modifying the design of a system without altering its behavior. The idea is to reorganize variables, classes and methods to facilitate their future adaptations and comprehension. As the concept of behavior preservation is fundamental for refactoring, several studies, using formal verification, language transformation and dynamic analysis, have been proposed to monitor the execution of refactoring operations and their impact on the program semantics. However, there is no existing study that examines the available behavior preservation strategies for each refactoring operation.

Objective: This paper identifies behavior preservation approaches in the research literature. Method: We conduct, …

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 …

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

Articles

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 …

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 …

A Survey Of Machine Learning Techniques For Video Quality Prediction From Quality Of Delivery Metrics, Obinna Izima, Ruairí De Fréin, Ali Malik

Articles

A growing number of video streaming networks are incorporating machine learning (ML) applications. The growth of video streaming services places enormous pressure on network and video content providers who need to proactively maintain high levels of video quality. ML has been applied to predict the quality of video streams. Quality of delivery (QoD) measurements, which capture the end-to-end performances of network services, have been leveraged in video quality prediction. The drive for end-to-end encryption, for privacy and digital rights management, has brought about a lack of visibility for operators who desire insights from video quality metrics. In response, numerous solutions …

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

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

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 …

Behind The Scenes: On The Relationship Between Developer Experience And Refactoring, Eman Abdullah Alomar, Mohamed Wiem Mkaouer, Anthony Peruma, Christian D. Newman, Ali Ouni

Articles

Refactoring is widely recognized as one of the efficient techniques to manage technical debt and maintain a healthy software project through enforcing best design practices, or coping with design defects. Previous refactoring surveys have shown that code refactoring activities are mainly executed by developers who have sufficient knowledge of the system’s design, and disposing of leadership roles in their development teams. However, these surveys were mainly limited to specific projects and companies. In this paper, we explore the generalizability of the previous results by analyzing 800 open-source projects. We mine their refactoring activities, and we identify their corresponding contributors. Then, …

Synergistic Anticancer Response Of Curcumin And Piperine Loaded Lignin-G-P (Nipam-Co-Dmaema) Gold Nanogels Against Glioblastoma Multiforme, Xinyi Zhao, Bilal Javad, Daxing Cui, James Curtin, Furong Tian

Articles

Glioblastoma multiforme (GBM) is the most aggressive and commonly diag- 11 nosed brain cancer and presents a strong resistance to routine chemotherapeutic drugs. 12 The present study involves the synthesis of Lignin-g- p (NIPAM-co-DMAEMA) gold 13 nanogel, loaded with curcumin and piperine to treat GBM. The application has three 14 functions: (1) overcome the limitations of biodistribution, (2) enhance the toxicity of an- 15 ticancer drugs against GBM, (3) identify the uptake pathway. Atom transfer radical 16 polymerization was used to synthesize the Lignin-g-PNIPAM network, crosslinked with 17 the gold nanoparticles (GNPs) to self-assemble into nanogels. The size distribution and …

Towards An Integrated Case Method In Management Education - Developing An Ecosystem-Based Research And Learning Journey For Flipped Classrooms, Jan-Philipp Buechler Prof Dr, Gregor Brüggelambert Prof Dr, Jan-Phillip Büchler Prfo Dr, Helen De.Haan-Cao Dr, Asta Savaneviciene Prof

Articles

In the field of management science and business administration, the case method is gaining ground in research as well as in teaching. Case studies support on the one hand exploratory re-search and on the other hand problem-based teaching. However, we find that case research and case teaching remain unchained in management study programs and propose to close this gap. We identify an untapped potential of boosting the case method by integrating case-based re-search and teaching into a discovery and learning journey of applied science. We suggest em-bedding the ‘Integrated Case Method’ (ICM) in the ecosystem of universities to the end …

Teaching Meiosis With The Dna Triangle Framework: A Classroom Activity That Changes How Students Think About Chromosomes, Leslie Kate Wright, Paulina Cortez, Margaret A. Franzen, Dina L. Newman

Articles

Many biology students struggle to learn about the process of meiosis and have particular difficulty understanding the molecular basis of crossing over and the importance of homologous pairing for proper segregation. To help students overcome these challenges, we designed an activity that uses a newly developed Chromosome Connections Kit® from 3-D Molecular Designs to allow learners to explore meiosis at the molecular level. We took a backwards design approach in constructing an effective classroom activity. We developed evidence-based learning objectives and designed a crossing over activity that targets students' misconceptions and key concepts about meiosis. Assessment questions were designed based …

Why Are You Here? Modeling Illicit Massage Business Location Characteristics With Machine Learning, Anna White, Seth Guikema, Bridgette Carr

Articles

Illicit massage businesses are a venue for sex and labor trafficking in the United States. Though many of their locations are made publicly available through online advertising, little is known about why they choose to locate where they do. In this work, we use inferential modeling to better understand the spatial distribution of illicit massage businesses within the U.S. Based on addresses web-scraped weekly from online advertisements over 6 months, we modeled illicit massage business prevalence at the census tract and county levels. We used publicly available data to characterize census tracts and counties, finding that the state in which …

Punnett Square Or Protein Production? The Expert-Novice Divide For Conceptions Of Genes And Gene Expression, Dina L. Newman, Aeowynn Coakley, Aidan Link, Korinne Mills, Leslie Kate Wright

Articles

Concepts of molecular biology and genetics are difficult for many biology undergraduate students to master yet are crucial for deep understanding of how life works. By asking students to draw their ideas, we attempted to uncover the mental models about genes and gene expression held by biology students (n = 23) and experts (n = 18) using semistructured interviews. A large divide was identified between novice and expert conceptions. While experts typically drew box-and-line representations and thought about genes as regions of DNA that were used to encode products, students typically drew whole chromosomes rather than focusing on gene structure …

Cavity Optomechanical Sensing And Manipulation Of An Atomic Persistent Current, Pardeep Kumar, Tushar Biswas, Kristian Feliz, Rina Kanamoto, M-S Chang, Anand K. Jha, Mishkat Bhattacharya

Articles

This theoretical work initiates contact between two frontier disciplines of physics, namely, atomic superfluid rotation and cavity optomechanics. It considers an annular Bose-Einstein condensate, which exhibits dissipationless flow and is a paradigm of rotational quantum physics, inside a cavity excited by optical fields carrying orbital angular momentum. It provides the first platform that can sense ring Bose-Einstein condensate rotation with minimal destruction, in situ and in real time, unlike demonstrated techniques, all of which involve fully destructive measurement. It also shows how light can actively manipulate rotating matter waves by optomechanically entangling persistent currents. Our work opens up a novel …

Dynamic Stochastic Joint Expansion Planning Of Power Systems, Natural Gas Networks, And Electrical And Natural Gas Storage, Arash Gholami, Hamed Nafisi, H. Askarian A., Ali Jahanbani Ardakani

Articles

Over the last decades, electricity generation from natural gas has substantially increased, mostly driven by low natural gas prices due to fracturing and lower extraction costs. The geographic distance between natural gas resources and load centers calls for a holistic tool for joint expansion of power systems and natural gas networks. In this paper, a Dynamic Stochastic Joint Expansion Planning (DSJEP) of power systems and natural gas networks is proposed to minimize the investment and operational costs of power and natural gas systems. Electrical and natural gas storage (ENGS) are considered as an option for decision-makers in the DSJEP problem. …

The Promise And Limits Of Lawfulness: Inequality, Law, And The Techlash, Salomé Viljoen

Articles

In response to widespread skepticism about the recent rise of “tech ethics”, many critics have called for legal reform instead. In contrast with the “ethics response”, critics consider the “lawfulness response” more capable of disciplining the excesses of the technology industry. In fact, both are simultaneously vulnerable to industry capture and capable of advancing a more democratic egalitarian agenda for the information economy. Both ethics and law offer a terrain of contestation, rather than a predetermined set of commitments by which to achieve more democratic and egalitarian technological production. In advancing this argument, the essay focuses on two misunderstandings common …

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 …

Profiling Mathematical Procedural And Problem-Solving Skills Of Undergraduate Students Following A New Mathematics Curriculum, Fiona Faulkner, Mark Prendergast, Cormac Breen, Michael Carr

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In 2010 a mathematics curriculum was introduced in Irish second level schools entitled ‘Project Maths’ (PM). It aimed to refocus second level mathematics teaching and learning away from an over emphasis on procedural mathematics towards problem solving and real understanding [Department of Education and Skills (DES). (2010). Report of the Project Maths implementation support group. https://www.education.ie/en/Publications/Policy-Reports/Report-of-the-Project-Maths-Implementation-Group.pdf]. This paper aims to examine the performance of 1st year undergraduate students’ procedural and problem solving skills after the introduction of PM. A diagnostic test was developed to determine students’ skills in each area and findings demonstrated that students perform statistically significantly …

Immobilized-Enzyme Reactors Integrated Into Analytical Platforms: Recent Advances And Challenges, Bert Wouters Dr, Sinead Currivan, Noor Abdulhussain, T. Hankemeier, Peter J. Schoenmakers

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Immobilized-enzyme reactors (IMERs) are flow-through devices containing enzymes that are physically confined or localized with retention of their catalytic activities. IMERs can be used repeatedly and continuously and have been applied for (bio)polymer degradation, proteomics, biomarker discovery, inhibitor screening, and detection. Online integration of IMERs with analytical instrumentation, such as high-performance liquid chromatography (HPLC) systems, reduces the time needed for multi-step workflows, reduces the need for sample handling, and enables automation. However, online integration can also be challenging, as reaching its full potential requires complex instrumental setups and experienced users. This review aims to provide an assessment of recent advances …

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”. …

Pandemic Transformation Of Teaching And Learning: Designing Pedagogy Using The Contents Of Instructors’ “Pedagogical Pantry,” Rather Than “Established Recipes.”, Sara Schley, Carol E. Marchetti

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How can faculty successfully shift from a physical classroom environment to creating meaningful online learning experiences in the midst of a pandemic? Using a “kitchen pantry” metaphor, this essay suggests faculty use a “what’s in my pantry?” approach, rather than trying to replicate the in-class experience and following a previously identified “recipe.” Some faculty embrace new technology options with great gusto. Others are resistant; and still others wait until they’ve seen others use it first to consider incorporating it. This model allows for different entry points of interaction, and for different levels of experimentation, reflecting individual faculty’s strengths and capabilities. …