Reviewerly/exHarmony huggingface dataset:
Argumentation Mining from Textual Documents Combining Deep Learning and Reasoning

Argumentation Mining (AM) is a growing sub-field of Natural Language Processing (NLP) which aims at extracting argumentative structures from text. In this work, neural learning and symbolic reasoning are combined in a system named N-SAUR, that extracts the argumentative structures present in a collection of texts, and then assesses each argument’s strength. The extraction is based on Toulmin’s model and the result quality surpasses previous approaches over an existing benchmark. Complementary scores are also extracted and combined with a set of rules that produce the final calculation of argument strength. The performance of the system was evaluated through human assessments. Users can also interact with the system in various ways, allowing for the strength calculation to change through user-cooperative reasoning.
Interpreting What is Important: An Explainability Approach and Study on Feature Selection

Machine learning models are widely used in time series forecasting. One way to reduce its computational cost and increase its efficiency is to select only the relevant exogenous features to be fed into the model. With this intention, a study on the feature selection methods: Pearson correlation coefficient, Boruta, Boruta-Shap, IMV-LSTM, and LIME is performed. A new method focused on interpretability, SHAP-LSTM, is proposed, using a deep learning model training process as part of a feature selection algorithm. The methods were compared in 2 different datasets showing comparable results with lesser computational cost when compared with the use of all features. In all datasets, SHAP-LSTM showed competitive results, having comparatively better results on the data with a higher presence of scarce occurring categorical features.
Multi-robot Adaptive Sampling for Supervised Spatiotemporal Forecasting

Learning to forecast spatiotemporal (ST) environmental processes from a sparse set of samples collected autonomously is a difficult task from both a sampling perspective (collecting the best sparse samples) and from a learning perspective (predicting the next timestep). Recent work in spatiotemporal process learning focuses on using deep learning to forecast from dense samples. Moreover, collecting the best set of sparse samples is understudied within robotics. An example of this is robotic sampling for information gathering, such as using UAVs/UGVs for weather monitoring. In this work, we propose a methodology that leverages a neural methodology called Recurrent Neural Processes to learn spatiotemporal environmental dynamics for forecasting from selective samples gathered by a team of robots using a mixture of Gaussian Processes model in an online learning fashion. Thus, we combine two learning paradigms in that we use an active learning approach to adaptively gather informative samples and a supervised learning approach to capture and predict complex spatiotemporal environmental phenomena.
Geochemistry as the Core of Biogeochemistry

This chapter examines the science of geochemistry, as the core, background discipline of biogeochemistry. Biogeochemistry is based on geochemistry; in that, it is the framework for those aspects of biology that link to the chemical bases of earth materials, which are defined as within the study of geochemistry. Therefore, the justification for this chapter is that a fuller understanding of biogeochemistry requires a study of geochemistry and the possibilities for its linkage with the biological sciences. Geochemistry is the study of the interfaces of geology and chemistry, using the methodology of the chemical sciences to investigate the composition of earth materials and the occurrence and movements of chemical elements and compounds within the earth system. Geochemistry is consequently an extremely wide subject, as it examines all aspects of the chemistry of earth materials. However, few studies have explored the links between geochemistry and the biological sciences, as the basis for biogeochemical studies. This chapter examines the relevant topics of chemistry, the content of geochemistry, and the developments that have forged a closer link with biogeochemistry. The branches of chemistry, namely, analytical, inorganic, organic, physical chemistry, and biochemistry, are examined, as is their relationship with geochemistry. The branches of geochemistry include organic geochemistry, inorganic geochemistry, isotope geochemistry, aqueous geochemistry, cosmochemistry, trace-element geochemistry, igneous rock geochemistry, metamorphic rock geochemistry, photogeochemistry, and low-temperature or environmental geochemistry. The literary evidence indicates that developments in chemistry, biology, geology, and even archaeology and astronomy (the last two linked to isotope geochemistry and cosmochemistry) have benefited geochemistry as a discipline, and in combination, these have contributed to the advancement of biogeochemistry. Variable issues in biogeochemistry are principally the concern of some branches of geochemistry, such as carbon, inorganic and marine chemistry, and organic, inorganic, isotope, and aqueous geochemistry. This examination contributes to knowledge on the interfaces between the biological, chemical, and geological sciences.
Understanding DevOps Critical Success Factors: Insights from Professionals

This paper explores the factors that contribute to the success of software development undertaken with DevOps practices. DevOps is a set of practices that aims to increase software development process efficiency by reducing barriers between operation and development teams. Despite the wealth of information available on DevOps practices, adoption, and the respective challenges, there is a dearth of research focusing specifically on the DevOps critical success factors. This paper seeks to fill this gap by analyzing and discussing the key factors that are essential for success in software development with DevOps. To this end, we have conducted an open-ended survey among 72 DevOps professionals. By employing the Gioia method, we elaborate on the professionals’ perspectives on the DevOps success factors identified and connect them to the prior literature. These success factors encompass intra-organizational collaboration, organizational hierarchy, strategic planning, team dynamics, cultural shift, performance engineering, integration, build and test automation, infrastructure, and DevOps as a service. We propose five DevOps implementation advice that could benefit companies while implementing DevOps practices. Those include management support, investment in DevOps tools, sharing knowledge within teams, sharing responsibility in teams, being willing to explore and experiment with the practices, and being agile are crucial for DevOps performance and organizational success.
On the Assessment of Deep Learning Models for Named Entity Recognition of Brazilian Legal Documents

A large amount of legal and legislative documents are generated every year with highly specialized content and significant repercussions on society. Besides technical, the produced information is not semantically standardized or format structured. Automating the document analysis, categorization, search, and summarization is essential. The Named Entity Recognition (NER) task is one of the tools that have the potential to extract information from legal documents with efficiency. This paper evaluates the state-of-the-art NER models BiLSTM+CRF and BERT+Fine-Tunning trained on Portuguese corpora through finetuning in the legal and legislative domains. The obtained results (F1-scores of 83.17% and 88.27%) suggest that the BERT model is superior, achieving better average results.
A Survey of Green Smart City Network Infrastructure

Smart cities are offering world-class services with significant use of resources. Thus, we need a huge power supply. Green smart city is minimizing energy utilization and maximizes eco-friendly techniques. Therefore, we need green energy and limit power wastage. Recent studies recommended use of sensors, machine learning (ML), internet of things (IoT), and cloud computing for optimizing power utilization. In this paper, we provide a review of green smart city and key areas of services explained. Additionally, recent development and enhancement at the different levels of smart cities to save energy are explained. The finding shows an improvement in conventional services and the use of ML in smart city applications that it can help in reducing the power requirements. Finally, the key objectives are proposed for future studies.
Human+Non-human Creative Identities. Symbiotic Synthesis in Industrial Design Creative Processes

As digital technologies are increasingly used in creative professions, the evolution of the relationship between designers and machines is growing in interest. Such topic is part of a broad debate on how cognitive processes and human intelligence development co-evolve in parallel with technology advancements in a process of technogenesis. In a complex socio-economic system, Artificial Intelligence-based technologies are both providing new tools and challenging the idea of creativity itself. We discuss how the creative process in the field of industrial design is commonly intended and we argue that the adoption of AI-based technologies is part of an ongoing process of symbiotic co-evolution between human and machine embedded in the creative process itself and, therefore, designers ought to develop synergic strategies to foster future innovation.
Cloud Computing Security Problems and Solution Methods

Cloud computing is one of the advanced and developing topics in the world of Information Technologies today. The model of cloud computing is changing the increasing reliability, massive scalability, and decreasing costs of computing, attracting interest in this area. This variability gives additional opportunities to Information Technology. The use of the cloud in Information Technology has increased significantly recently. As individuals and companies place their essential data in the cloud, it becomes more difficult to ensure data security. Microsoft and many other successful companies in the software industry use cloud services to support its development [1]. Despite the many supporting service benefits written about the cloud, customers are reluctant to put data in the cloud to protect their business. Despite the many benefits that companies derive from cloud computing services, many companies are slow to adopt the cloud computing service model. One of the biggest challenges affecting the development of cloud computing is ensuring security. This also includes the challenges of protecting data privacy. Users should consider the risk of damage or complete corruption of the data they store in the cloud environment. Cloud computing services provided by information and communication technologies that provide services needed by a customer over the Internet based on a specific contract may increase or decrease service requirements or needs based on that customer's opinion. Cloud computing services are delivered to customers on demand by a third party - the person who builds the infrastructure. There is a risk that some information may be lost as a result of third parties handling confidential information. In addition, it is possible to ensure security with 2-step authentication. However, you need to log into one cloud account on two separate devices. The cloud computing model has many advantages, including efficiency, flexibility, and scalability. Cloud computing offers organizations an innovative business concept to provide IT-based services without paying upfront. This model provides on-demand access to a shared cloud network of IT computing resources such as networks, servers, storage, applications, and services. In this article, we will discuss the opportunities, security issues, and challenges of adopting and managing a cloud computing services model in an organization. The importance of applying facial recognition systems to some cloud providers (such as Google and Amazon) is emphasized, too.
Teaching virtual production: the challenges of developing a formal curriculum

In this article, we explore how the recent proliferation of the virtual production stage with its promise of real-time visual effects has not only changed the working environment of the film studio, but also introduced an urgent need for new training and teaching approaches – not only for current and future film students, but also for educators and practitioners. This case study examines a research project involving students from Ravensbourne University London, UK, in collaboration with industry partner Mo-Sys Engineering, a leading manufacturer of virtual production solutions. The complex demands of new, multidisciplinary job roles in virtual production have created a skills shortage in the UK film and television industry. We illustrate the challenges of training not only film students but also educators for a continually changing workplace dominated by disruptive technologies and shifting skill sets.
GAC-Text-to-Image Synthesis with Generative Models using Attention Mechanisms with Contrastive Learning

The generation of high-quality images from textual descriptions is a challenging task in computer vision and natural language processing. The goal of text-to-image synthesis, a current topic of research, is to produce excellent images from written descriptions. This study proposes a hybrid approach to evaluating a dataset consisting of various text-image pairs by efficiently combining conditional generative adversarial networks (C-GAN), attention mechanisms, and contrastive learning (C-GAN+ATT+CL). We suggest a two-step method to improve image quality that starts by utilizing generative adversarial networks (GANs) with attention mechanisms to create low-resolution images and then contrastive learning to improve. Contrastive learning modules train on a separate dataset of high-resolution pictures; GANs learn on datasets of low-resolution text and image pairs. The Conditional GAN with Attention Mechanism and Contrastive Learning Method provides state-of-the-art performance in terms of image quality, diversity, and visual realism, among the several methods. The results of this study demonstrate that the proposed approach works better than all other methods, achieving an Inception Score (IS) of 35.23, a Fréchet Inception Distance (FID) of 18.2, and an R-Precision of 89.14. Our findings demonstrate that our "C-GAN+ATT+CL" approach significantly improves image quality and diversity and offers exciting paths for further study.
Copyright Issues in Legal Research and Writing

Legal research involves written work, and with many similar research papers, the chance of being illegally copied increases. Thus, to protect a work from unauthorized copying, intellectual property law is protected by copyright law. To do this, it contains some important criteria that must be met. In general, the guidelines are very common in all countries. So in general, all research done is easily protected in all countries. But if someone does not follow this guideline, they will not be copyrighted instead of protected. Copyright protects the author by prohibiting others from copying the work without permission. As members of the legal fraternity, judges, lawyers, academics, researchers and students, constantly engaged in legal research and writing, legal scholars and writers play a dual role as both authors and users in their academic practice.
Multi-Agent Task Assignment in Vehicular Edge Computing: A Regret-Matching Learning-Based Approach

Vehicular edge computing has emerged as a solution for enabling computation-intensive applications within Intelligent Transportation Systems (ITS), encompassing domains like autonomous driving and augmented reality. Despite notable progress in this domain, the efficient allocation of constrained computational resources to a spectrum of time-critical ITS tasks remains a substantial challenge. We address this challenge by devising an innovative task assignment scheme tailored for vehicles navigating a highway. Given the high speed of vehicles and the limited communication radius of roadside units (RSUs), the dynamic migration of computation tasks among multiple servers becomes imperative. We present a novel approach that formulates the task assignment challenge as a binary nonlinear programming (BNLP) problem, managing the allocation of computation tasks from vehicles to RSUs and a macrocell base station. To tackle the potentially large dimensionality of this optimization problem, we develop a distributed multi-agent regret-matching learning algorithm. Incorporating the method of regret minimization, our proposed algorithm employs a forgetting mechanism that enables a continuous learning process, thereby accommodating the high mobility of vehicle networks. We prove that this algorithm converges towards correlated equilibrium solutions for our BNLP formulation. Extensive simulations, grounded in practical parameter settings, underscore the algorithm's ability to minimize total delay and task processing costs, while ensuring equitable utility distribution among agents.
Apostrophes That Indicate a Length of Time or an Amount

Abstract The movies people don’t talk about or remember after six months’ time don’t really matter.
Using Commas When Describing or Naming Somebody or Something You’ve Just Referred to

Abstract Elevator footage showed Beyoncé’s sister, Solange, attacking Jay Z after the 2014 Met Gala. Justin Timberlake and Jessica Biel released the first photo of their baby boy, Silas Randall, via Instagram Sunday.
Using Commas around Parenthetical Bits in the Midst of Sentences

Abstract Because these parenthetical elements aren’t essential to the sentence, you should offset them with punctuation, as you do with other nonessential elements.
Starting Sentences with <i>And</i> or <i>But</i>

Abstract Writers have opened sentences with and since the Old English period. Chaucer did it. So did Malory, Shakespeare, the translators of the King James Version of the Bible, and many others. And authors have been starting sentences with but since the Middle Ages. Chaucer did that a lot, and Shakespeare and Milton did it, too.1 Even the early grammarians who prescribed many of the weird usage rules in English had no problem with starting sentences with but. In the nineteenth century, though, some schoolteachers opposed starting sentences with and or but, possibly because young students did that too often. Then teachers went overboard, banning the practice altogether.2 Today, most language experts and stylists agree that it’s fine to open sentences that way. In fact, The Chicago Manual of Style points out that up to ten percent of the sentences in first-rate writing begin with conjunctions such as and, but, or so.3 Starting with but can be stylistically powerful. It packs a punch that the more formal-sounding word however doesn’t. Just don’t do it too often.
Commas and Fanboys

Abstract Now you’ve seen the lesson on using commas with and or but. Those two words aren’t the only ones that you can use to connect two main clauses, though. Others include for, nor, or, (and) yet, or so.
Periods

Abstract Men want to make women happy. We want to do it. We don’t know how to do it. Sometimes we do it and we don’t know how we did it. . . . We can’t do nothing. If you do nothing, she says, “I can’t believe you’re doing that.” We say, “I’m not doing anything.” She starts crying.
Question Marks

Abstract You might think it would be pretty hard to say anything interesting about question marks, but Roy Peter Clark makes this intriguing observation: the question mark may be the most profoundly human form of punctuation. That’s because it imagines the other person, the one the writer or speaker is talking to, in a way that no other punctuation mark does.1
When to Hyphenate

Abstract As Mr. Spock, the elf-eared, half-Vulcan science officer and first mate of the Starship Enterprise, he created a role that turned him from a journeyman into a star. . . . As it turned out, Spock was a lifelong project. The five-year mission stretched to nearly half a century.
However

Abstract I intend to assist in the effort to re-establish communication with Starfleet. However, if crew morale is better served by my roaming the halls weeping, I will gladly defer to your medical expertise.
Defining Some Really Basic Terms

Abstract If you’re like most of my students, you don’t love grammar jargon. I don’t either. When I teach, I use only the terms that my students really need to know in order to learn how to write well in formal contexts. I take the same approach in this book. The lessons don’t always define basic grammar terms, though, so let’s review some of them here.
Using Commas to Mark Omitted Text

Abstract In war, Resolution. In defeat, Defiance. In victory, Magnanimity. In peace, Goodwill.
Foreword

Extract In this short but insightful book, Dr. Gabriele Balbi tells the story of an idea that has captured the imagination as much as or more than any other since the middle of the last century. It is a tale that asserts, often forcefully, that we are in the midst of a computer revolution that constitutes a radical rupture from the past and which irrevocably changes the lives of those living through it and future generation as well. Specifically, the transition from an analog to a digital world is not just a shift in technology, it portends a fundamental change in time, space, and social relations. Having spent the past 50 years engaging with the story Dr. Balbi recounts, I am familiar with the range of ideas and emotions it conjures. In The Digital Sublime (Mosco, 2004), building on the work of writers like Leo Marx (1964), David Nye (1996), and Carolyn Marvin (1990), I made it the object of a book that describes the idea of a digital revolution as more than just a change in technology and even more than a new set of political economic arrangements. Just as importantly, it marks the latest iteration in the grand myths that provide fodder for our emotional comfort and ideological justification for a changing world. In a word, it offers transcendence to humanity as it seeks to cope with the consciousness of its own mortality just as, in the past, the natural world and religion provided pathways that might take us beyond the limits of our biology. This latest vision of the technological sublime, now embodied in myths about artificial intelligence and the metaverse anticipates, for its major storytellers and believers, nothing short of the end of history, the end of geography, and the end of politics.
Using Apostrophes to Mark Some Plurals

Abstract Quick, what’s the plural of the lowercase letter i? It’s got to be i’s, right? The spellings is and ts in a sentence like “Dot your is and cross your ts” would only confuse people. It’s much clearer as “Dot your i’s and cross your t’s.” That’s one context in which we need apostrophes to mark plurals.
Emerging Digital Economies

Abstract This chapter explores how digital economies emerge as the harbingers of more comprehensive changes to business practices and ecosystems in the Middle East. Three cases of trailblazing ventures are illustrative examples: the e-shopping platform Souq, the ride-hailing app Careem, and the music-streaming service Anghami. Despite these ventures’ success, the digital economy in the region remains subject to conflictual pulls. As some of the inherent contradictions associated with the introduction of the Internet of Things (IoT), artificial intelligence (AI), and cloud computing suggest, the nature of this emerging economy is intricate, and its supporting ecosystem is precarious. While the digital represents the next frontier in the region’s economy, its development is neither uniform nor analogous to more established digital economies associated with the network society, which calls into question discourses that elevate the region to be “the next Silicon Valley.”