Reviewerly/exHarmony huggingface dataset:
Science Together: Co-Creating Meaningful Informal Science Education Experiences Between a Science Center and a Temporary Homeless Shelter – A Case Study

Homeless families are a vulnerable population not often engaged with directly by science centers. In 2019, the Museum of Life and Science formalized and strengthened a partnership with Families Moving Forward, the largest temporary homeless shelter serving families in Durham County, North Carolina. This partnership aimed to engage families in a co-creation process of understanding needs, co-developing projects, and delivering based on mutual interests between stakeholders. Along the way, lessons learned included designing equitable active listening opportunities, honest and transparent assessments of needs and assets, learning how to meet a new audience where they were, and learning how to be inclusive and accessible to an audience who is rarely designed with or for in museum settings.
RETRACTED ARTICLE: An Edge Computing Unloading Algorithm for IIoT-based Mobile and Internet of Vehicles (IoV) Applications

The Internet of vehicles (IoV) is a system of vehicles equipped with software, sensors, and IT and Communication technologies. The IoV is certainly used in defense and military services for exchanging data over the Internet for handling diverse defense-oriented operations. The IoV’ main goal is to make driving safer by allowing drivers and vehicles to communicate with each other (V2V) and with public infrastructure (V2I). Current systems face a number of operational challenges, including terminal losses, message processing delays, and high overhead costs. The aim of the paper is to deal with these issues, using a Markov decision-based edge computing offloading mechanism. The proposed study effort employs an analytical hierarchy technique to establish the task’s priority by determining the preferences of the tasks. Security signals are prioritized to avoid delays in getting essential information to the right people. Markov decision is used to find the best task offloading model in terms of latency and energy loss. Using the Lagrange relaxation method to convert a non-convex problem into a convex problem, a relationship model that incorporates both time delay and energy loss is constructed. Finally, to arrive at the best answer for our unloading model, the artificial fish swarm approach is used with modification in the original algorithm to make it compatible for our problem statement. The suggested technique reduces terminal loss, offload cost, and message processing latency effectively.
Electrofacies Classification in a Core of the Presalt, Santos Basin, on the Basis of a High-Resolution Rock-Log Correlation

Rock-log correlation to establish electrofacies is a challenging task caused by the complex carbonate reservoirs of the Brazilian presalt interval.The main problem is a similar response of the majority of carbonates to basic welllogs turning difficult the differentiation between rocks.On the other hand, diagenetic processes can disturb dramatically the rocks response to the well-logs.The main objective of this work is to present an alternative way to perform a rock-log correlation to recognize electrofacies in a core from the Presalt of the Santos Basin.The depth adjustment core-log, a fundamental step, is generally provide using a coregamma, unavailable for our study.Because of this lack of information, we adjust values of petrophysical porosity measured in laboratory from coreplugs to the effective porosity from the magnetic resonance log.The best adjustment of these porosities occurred with the core shifting of 3.5m down.Before the shifting, the relative error was 51% and after this shifting, the adjustment reduces the error to it is 24%.We calibrated the geophysical well logs -Gamma Ray (GR), Spectral Gamma Ray (SGR), Spectroscopy Logging Tool (SLT), Density (RHOB), Photoelectric Factor (PE), Sonic (DT) and Nuclear Magnetic Resonance (NMR) -with rock data derived from core, plugs and thin sections, such as lithology, cement, granulometry and sorting to determinate the classification of four electrofacies: BV-1 and BV-2 (Barra Velha Formation); ITP-1 and ITP-2 (Itapema Formation).BV-1 is predominantly composed by reworked sediments, mainly grainstones.The cement is basically composed of calcite and/or dolomite, medium to coarse grain size and well sorting.This electrofacies is characterized by relatively low values of GR and SGR (thorium and uranium), low silica content, high calcium quantity, low densities and slowless and high values of PE and porosity.BV-2 is essentially composed by laminites, spherulites and shrubs.It generally presents dolomite cement, clay matrix and varied sorting.This electrofacies is characterized by relatively high values of GR and SGR (thorium and uranium), medium to high values of silica content, medium to low calcium quantity, high densities and low values of PE and porosity.The ITP-1 and ITP-2 electrofacies are formed by coquinas.ITP-1 is mainly composed by rudstones and floatstones with calcite cement, coarse granulometry and normal to bad sorting.This electrofacies is characterized by relatively low values of GR and SGR (thorium and uranium), high calcium content, low silica quantity, medium density, low slowness and high values of PE and porosity.The ITP-2 is like the ITP-1.However, the ITP-2 presents higher silica content and, consequently, lower slowness and porosity and higher density and quartz cement quantity than ITP-1.These electrofacies provide an understanding of both depositional and diagenetic responses to well logs for the identification of key-surfaces to correlate wells of the presalt interval.
Contextualized Embeddings

This chapter provides an introduction to contextualized word embeddings which can be considered the new generation of word (and sense) embeddings. The distinguishing factor here is the sensitivity of a word’s representation to the context: a target word’s embedding can change depending on the context in which it appears. These dynamic embeddings alleviate many of the issues associated with static word embeddings and provide reliable means for capturing semantic and syntactic properties of word usage in context. Despite their young age, contextualized word embeddings have provided significant gains in almost any downstream NLP task to which they have been applied.
Graph Embeddings

Graphs are ubiquitous data structures. They are often the preferred choice for representing various type of data, including social networks, word co-occurrence and semantic networks, citation networks, telecommunication networks, molecular graph structures, and biological networks. Therefore, analyzing them can play a central role in various real-world scenarios, such as drug design, friendship recommendation in social networks, semantic modeling in language, and communication pattern extraction.
Word Embeddings

Section 1.2 briefly discussed the Vector Space Model (VSM). We saw in that section how objects can be represented using continuous vectors in a multidimensional space and how distances in this space can denote the similarities between objects. However, we did not discuss how these spaces are constructed. In other words, the following question remained unanswered: how can we place hundreds of thousands of words in a space such that their positioning corresponds to their semantic properties? In this chapter, we will talk about the foundations behind constructing semantic spaces, particularly for words.
Sentence and Document Embeddings

In the first part of the book, we focused on some of the smallest units in language, mostly those at the word-level. However, in most applications dealing with natural language, understanding longer units of meaning such as sentences1 and documents is crucial. While this chapter is not covered as exhaustively as the other chapters, we still provide a basic overview and pointers so the reader can delve into these topics on their own.
Sense Embeddings

In this chapter, we introduce a type representation aimed at modeling unambiguous lexical items.1 These representations emerged in order to address one of the main limitations of word-level representation techniques, meaning conflation.
Blockchain Technology and Intellectual Property Protection: A Systematic Literature Review

Many products and services require intellectual property protection (IPP). The current IPP schemes suffer from unclear ownership and potential risks of data tampering, among other drawbacks. Recent research has documented a significant need to address these issues. Blockchain presents an opportunity for IPP to help solve existing problems. This study attempts to conduct a systematic review of research on the applications of blockchain to IPP. To summarise existing research findings and provide a theoretical basis for scholars and practitioners, the authors' team used online databases (WOS, CNKI and CSSCI) to identify a total of 172 papers related to 'blockchain applications in IPP', then selected 82 papers for further analysis based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA). As a result, the paper analyses existing research topics and identifies directions that can be further investigated. The authors conclude that the urgent research directions to be explored in the future include blockchain technology architecture, IP laws and regulations, and IP management applications and operations.
Me, Myself &amp; Data - Principles for the Design of Self-Tracking Services

In this paper, we will explore how applying principles of design research to the design of self-tracking services can lead to a more human and delightful user experience, and thus more desirable services. Design research has always aimed at helping design human-centered products and services. To do so, researchers follow various guidelines to ensure that the conducted research is relevant, ethical and inspiring. The rise of new technologies for the self-tracking of personal data has blurred the distinction between users and researchers as devices for self-tracking have become more mobile, wearable, and affordable for the mainstream, allowing users to become researchers of their own lives. Yet, having access to more data does not automatically mean people will understand this information, or know how to apply it. The main challenge, therefore, lies in interpreting the data and acting upon the information gained. We have conducted a series of interviews and analyzed concrete examples of self-tracking services, and based on our observations have defined five principles of design research. We believe that when applied to the design process, these principles will ultimately result in self-tracking data that brings more value to users.
Semantic graph attention networks and tensor decompositions for computer vision and computer graphics

This thesis proposes new architectures for deep neural networks with attention enhancement and multilinear algebra methods to increase their performance. We also explore graph convolutions and their particularities. We focus here on the problems related to real-time human pose estimation. We explore different architectures to reduce computational complexity, and, as a result, we propose two novel neural network models for 2D and 3D pose estimation. We also introduce a new architecture for Graph attention networks called Semantic Graph Attention.
Robust Device Authentication Using Non-Standard Classification Features

This paper investigates the use of novel hardware features derived from the physical and behavioral characteristics of electronic devices to identify such devices uniquely. Importantly, the features examined exhibit non-standard and multimodal distributions which present a significant challenge to model and characterize. Specifically, the potency of four data classification methods is compared whilst employing such […]
Rethinking law, rethinking regulation, and rethinking technology

This chapter starts by asking how we might 'rethink' Law, Regulation and Technology. It proposes a method for 'rethinking' that starts with a 'baseline' view (the view or understanding that is to be rethought) and then can relate, more particularly, to the 'field' of our interest or inquiry; or, to the way that we 'frame' our thinking within that field; or, to the particular 'focus' of our reflections. Following this approach, the chapter discusses how we might rethink, respectively, Law, Regulation, and Technology, before turning to the question of how we might rethink the relationship between Law, Regulation, and Technology.
The Evolution of Software Development

The process of creating software has gone through several significant incarnations that are important to understand if you want to advise clients on the best way to develop software. The activity of writing software for computers began in the middle of the 20th century using tools and techniques that would be unfamiliar to most people today. Automation led to digital modernization strategies with priorities from companies to make changes to software more and more often. Newer project management methodologies such as Agile and Scrum incorporated the concept of continuous feedback to accommodate the pace of change. The software development lifecycle emerged as the need to create efficiency around the process of creating software intensified. At first, project management methodologies such as Waterfall were sufficient, but gradually other methodologies emerged to keep up with the accelerating need for software changes.
Semantic Repository for Automatic Deep Learning Generation

The automation of DL model has focused on model optimization, wholistic DL generation is an unexplored field. To address the issues, we propose a novel framework and method that enables DL architectures and data, developed by artificial-intelligence experts, to be shared by business developers who are not such specialized experts. In this paper, we focus on two issues: the generation of data for DL and DL architecture generation. The overall framework considers adaptability towards frequent updates and new architectural approaches by separating the system knowledge from the generation procedure for the DL architecture. The design strategy involves the creation of an ontology for the DL generation process and the construction of a rule for generating the DL architecture and its data. We demonstrate the entire DL generation workflow using an example scenario, with a user request forming the requirement. A prototype implementation to show working of inference on the ontology for DL generation is illustrated, and an evaluation of our repository comparing with the existing system is provided.
Will Robots Judge Me? Examining Consumer-Service Robots Interactions in Embarrassing Service Encounters: An Abstract

Service robots are gradually replacing humans service providers in numerous industries and their development is profoundly impacting the way in which service is delivered (Bornet et al. 2021; Wirtz et al. 2018). Accordingly, service robots encounters represent a primary research area in service. To date, researcher and practitioners have applied service robot across various contexts such as medical (Yoon and Lee 2019), hospitality (Tung and Au 2018) and tourism (Murphy et al. 2019), and have focused on the general application and acceptance of the technology (Huang and Rust 2017; van Doorn et al. 2016; Wirtz et al. 2018) and on services that may be executed by or improved by such technologies (Paluch and Blut 2013; Jörling, Bohm, and Paluch 2019). In addition, few studies have analysed service robot interactions in the service and consumer behaviour fields (Longoni et al. 2019), mainly focusing on the consumers’ reactions to specific service robot characteristics such as the level of human-likeness (Castelo et al. 2019; Kim et al. 2019; Mende et al. 2019). These approaches usually try to determine general principles of the service robot delivery, yet not much attention has been given to the particular boundary condition of the service delivery context under which human-robots encounters might be more beneficial than traditional human-to-human encounters. A typical consumption setting where the presence of other individuals can damage the general consumers’ experience is embarrassing service encounters. Consumer embarrassment is a widespread social emotion induced when a transgression is witnessed or perceived to be witnessed by others ( Krishna et al. 2019). For embarrassment to be elicited, individuals have to be concerned for what others are perceiving or thinking about them (Dahl et al. 2001), thus embarrassment is dependent on the presence of others. In this study, we suggest that interactions with a service robots in the context of a potentially embarrassing service encounter may reduce consumer embarrassment. We posit that this occurs because of the global attribution of mind to the robots such that consumers do not ascribe intentionality, cognition, and emotion to a service robot, thus ability to socially evaluate one’s purchase or behaviour (Gray et al. 2007). Moreover, we propose to investigate the impact of service robot human-likeness on consumer embarrassment (Mende et al. 2019). The study employs a mixed-method approach. Preliminary findings from the qualitative analysis identifies perceptions of mind and human-likeness appearance as potential factors influencing feelings of embarrassment. Further, findings from a first experimental study show that, in embarrassment service encounters, interaction with service robots decrease feelings of individuals’ consumer embarrassment. Theoretical and managerial contributions are discussed.
Using modified background subtraction for detecting vehicles in videos

In this paper, a comparison study has been introduced between the traditional foreground detector (background subtraction technique) and a modified background subtraction-based detector (empty frame subtraction technique). A case study for such analysis has been introduced for estimating the average vehicular speed and the level of crowdedness in three test traffic videos with five different indices; frame rate, resolution, number of frames, duration, and extension). The proposed modification in the background subtraction detector strategy aims to reduce vehicle detection processing time which increase vehicle tracking efficacy. In addition, video degradations (salt and pepper noise, Gaussian noise, and speckle noise) have been applied in both traditional and modified background subtraction. Results have reflected an obvious decrease in the processing time by almost 40% than the traditional background detector.
The Impact of Digitalisation of Higher Education: The Case of Latvia and Nordic-Baltic Region

Abstract For the next seven years, the digitalisation of higher education is one of the priority tasks of Latvia. An extensive review of information sources was performed, and an online survey with the technical staff of higher education institutions was conducted to evaluate the progress made towards education digitalisation in Latvia and compare these results with the countries of the Nordic-Baltic region. The paper presents the study results and identifies issues hindering the digitalisation progress, e.g., issues with the legislation, basic digital skills, and required competences for academic staff.
Towards a Broadcast Time-Lock Based Token Exchange Protocol

Many proposals for token exchange mechanisms between multiple parties have centralization points. This prevents a completely trustless and secure exchange between those parties. The main issue lies in the fact that communications in projects using a blockchain are asynchronous: classical result asserts that in an asynchronous system a secure exchange of secrets is impossible, unless there is a trusted third party. In this paper, we propose our preliminary results in the creation of our Broadcast Time-Lock Exchange (BTLE) protocol. The core of BTLE is the introduction of synchronicity in communications through the use of time-lock puzzles. This makes it possible to exchange secrets between two parties while eliminating the need for a trusted third party.
A Fuzzy Survival Tree (FST)

A fuzzy survival tree (FST) is introduced as an alternative proposal for survival tree learning. Fuzzy logic theory and Harrell’s index (c-index) are combined as a new rule in node splitting. The introduction of fuzzy sets in tree learning improves FST performance and provides robustness to the algorithm when data are missing. FST performance improves significantly over other tree-based machine learning algorithms as demonstrated in public clinical datasets.
Global and local feature fusion via long and short-term memory mechanism for dance emotion recognition in robot

In recent years, there are more and more intelligent machines in people's life, such as intelligent wristbands, sweeping robots, intelligent learning machines and so on, which can simply complete a single execution task. We want robots to be as emotional as humans. In this way, human-computer interaction can be more natural, smooth and intelligent. Therefore, emotion research has become a hot topic that researchers pay close attention to. In this paper, we propose a new dance emotion recognition based on global and local feature fusion method. If the single feature of audio is extracted, the global information of dance cannot be reflected. And the dimension of data features is very high. In this paper, an improved long and short-term memory (LSTM) method is used to extract global dance information. Linear prediction coefficient is used to extract local information. Considering the complementarity of different features, a global and local feature fusion method based on discriminant multi-canonical correlation analysis is proposed in this paper. Experimental results on public data sets show that the proposed method can effectively identify dance emotion compared with other state-of-the-art emotion recognition methods.
DEIXIS IN DISNEY MOVIE: CINDERELLA

When we communicate, especially through coversation or any means of communication, often we use phrases or words that describe time, place, or a person in a specific way within a specific context. Expressions of time and place usually called deictic expressions that included in Deixis. There is 5 Deixis which is people deixis, place deixis, article deixis, and social deixis. This research has a main focus to analyze the use of deictic espressions used in the 2015 Disney movie titled “Cinderella”. In this paper, researchers will be gathering data from the script of 2015 Disney Movie "Cinderella" in order to carry out the Pragmatic Deixis Theory. The method of research this article will be use is a qualitatively research with descriptive approach about what deixis is in "Cinderella" movie. This research had a purpose to identify and classify what kind of deixis and also meaning of each deixis that were used on the 2015 Disney movie "Cinderella". Based on collected data this research have gathered, it is concluded to understand source of Deixis from "Cinderella" by Disney movie on 2015, researcher have a better understanding to interpret it's deixis with it's appropriate word, research and reader's comprehension about what deixis meaning is slightly improve.