Reviewerly/exHarmony huggingface dataset:
Gelation

Gelation describes the transformation from a liquid or fluid state to a somewhat solid state, well known from daily experience, making, for instance, a jelly pudding. Gels and gelation are studied quite extensively in chemistry and physics, and especially over the past three decades theoreticians have discussed the formation of gels and the relation between structure and properties quite extensively (percolation theory, fractals). In this chapter, we will first discuss the viscosity of solutions and how it changes during gelation. For an understanding of modern equipment, to analyse gelation, it is important to briefly discuss viscoelasticity and simple models for a viscous fluids. We then describe how gelation is measured, from very simple methods to more elaborate ones. The chapter closes with a survey of theoretical models for gelation such as percolation, diffusion-limited cluster aggregation, mean field theory using the Smoluchowski equation, scaling analysis and polymerisation-induced phase transformation (PIPS). For all these models, predictions of gel time can be made, showing how the composition of the solution, the viscosity and the temperature affect it.
Experimenting with Evolutionary Algorithms to Reduce Feature Model Configuration Steps

In the software engineering world, software product lines constitute an approach for building reliable software systems. These use feature models to capture, develop, and document shared software for a base system. One of the main challenges when using feature models to derive new products configuration is a way of selecting a configuration that takes under consideration the minimum number of steps and minimum decision-making cost, taking into account resource constraints. To satisfy the challenges of optimizing the configuration selection technique, in this paper, we present an assessment approach that makes use of genetic algorithms to generate then evaluate the best product configurations from feature models. Our empirical outcomes reveal the effectiveness of using the genetic algorithm in obtaining the product configurations that meet the best level of trading-off between steps and decisions at a reasonable production time, consequently, assisting stakeholders in selecting the product configuration that fits their requirements.
Quick Start

This chapter is an overview of Roassal. This chapter acts as a teaser for Roassal by providing a few compelling examples. The chapter does not go into detail since that is the job of the forthcoming chapters. Many short code snippets are provided and briefly described. You can copy and paste these snippets directly into Pharo and each one illustrates a particular aspect of the Roassal platform.
Virtual Reality

Virtual reality, also known as computer-based reality, is an advanced technology that has the capability to upsurge destination accessibility and to increase the popularity of lesser-known destinations. The objective of the current study is to understand the latest trends in virtual reality and to discover the future scope of implementation of virtual reality in the tourism industry across the world. The potential and the employment of virtual reality is not entirely understood and comprehended by many destinations. The present study identifies that there is a continuous development in popularity of virtual reality, and it is the need of the hour today. This disruptive technology has led to the phenomenon of virtual tourism, which gives people a preview and understanding of what they will experience if they visit a place physically. Virtual reality is becoming an outstanding way to showcase information and to gain relevant response from the tourists to enhance the services and overall tourist experience in the tourism destination.
The use of context in multiword-term translation

The quality of a specialized translation depends to a great extent on the treatment of multiword terms (MWTs). Since MWTs are not always adequately described or even included in most terminological resources, translators and terminologists must find other ways to deal with them. One method involves the analysis of parallel texts. Traditionally, parallel texts have been a valuable resource for terminology extraction and knowledge acquisition. They can be compiled as comparable corpora (i.e. collections of texts originally written in the source and target languages). Nevertheless, even though comparable corpora can facilitate translation, many translators are often unfamiliar with corpus query techniques. This paper describes a method that identifies Spanish equivalents of English MWTs in corpora, and also provides translators and terminologists with a set of manual corpus query techniques that help to effectively translate MWTs. The comparable corpus compiled was composed of original English and Spanish texts on wind energy generation. The method proposed is based on distributional semantics and was used to identify and compare contextual elements of the concepts in both languages. The results of our study showed that this procedure simplifies and contributes to the accurate identification of MWT translation equivalents in corpora.
BLOCKLY 4SOS

BLOCKLY is a library that allows you to make block programming apps. Even if users do not really know a programming language, block programming allows them to construct scripts and programs using graphic blocks. In a drag-and-drop editor, BLOCKLY includes all you need to define and render blocks. Each block represents a single line of code that may be stacked and converted into code with ease. It can be used to let users personalize elements of the app and add actions to them.
Arrays

In this chapter, you will learn: how to work with arrays in Java and ArrayList, which is a collection of variable-length.
A Pointer-Generator Based Abstractive Summarization Model with Knowledge Distillation

The use of large-scale pre-trained models for text summarization has attracted increasing attention in the computer science community. However, pre-training models with millions of parameters and long training time cause difficulty to deployment. Furthermore, pre-training models focus on understanding language but ignore reproduction of factual details when generating text. In this paper, we propose a method for text summarization that applies knowledge distillation to a pre-trained model called the teacher model. We build a novel sequence-to-sequence model as the student model to learn from the teacher model’s knowledge for imitation. Specifically, we propose a variant of the pointer-generator network, which integrates multi-head attention mechanism, coverage mechanism and copy mechanism. We apply the variant to our student model to solve the word repetition and out-of-vocabulary words problem, so that improving the quality of generation. With experiments on Gigaword and Weibo datasets, our model achieves better performance and costs less time beyond the baseline models.
Reclaiming the People: Counter-Populist Algorithmic Activism on Israeli Facebook

This article examines a new form of resistance to right-wing populist discourse on social media which I define as counter-populist algorithmic activism. Practitioners of this type of activism exploit platforms’ automated ranking mechanisms and interface design to bolster the online visibility of counter-populist voices. By so doing, activists seek to stymie the digitally mediated spread of right-wing populist rhetoric and advance an alternative, non-exclusionary vision of “the people.” To explore this nascent form of resistance, this study draws on a year-long online ethnography of a Facebook group of Israeli activists called Strengthening the Left Online. Through an observation of the group’s activities during 2017, as well as interviews with its main administrator and other left-wing Facebook users, I elucidate the distinctive nature of the motivations, strategies, and goals that guide counter-populist algorithmic activists.
AdverseGen: A Practical Tool for Generating Adversarial Examples to Deep Neural Networks Using Black-Box Approaches

Deep neural networks are fragile as they are easily fooled by inputs with deliberate perturbations, which are key concerns in image security issues. Given a trained neural network, we are always curious about whether the neural network has learned the concept that we’d like it to learn. We want to know whether there might be some vulnerabilities of the neural network that could be exploited by hackers. It could be useful if there is a tool that can be used by non-experts to test a trained neural network and try to find its vulnerabilities. In this paper, we introduce a tool named AdverseGen for generating adversarial examples to a trained deep neural network using the black-box approach, i.e., without using any information about the neural network architecture and its gradient information. Our tool provides customized adversarial attacks for both non-professional users and developers. It can be invoked by a graphical user interface or command line mode to launch adversarial attacks. Moreover, this tool supports different attack goals (targeted, non-targeted) and different distance metrics.
4차산업혁명과 보안관리의 시사점 : 한국 사례 연구

This paper explores the implications of the Fourth Industrial Revolution (4IR) for security management using a case study of South Korea. The paper examines what the 4IR is and explores some of the technological innovations in security, before speculating on where these could lead using both positive and negative examples. The paper then explores what the implications of 4IR will be for security management using a case study of South Korea based upon a survey of security managers in a specific industrial zone. The paper argues the 4IR will accelerate further trends in the ‘convergence’ of security and related functions such as safety.
Don't Be Antisocial

This chapter asks one main question - what exactly is ‘social’ in social media? By focusing on the deviant side of social media – The Antisocial – the chapter amplifies the things we take for granted in these platforms, and how they are constructed rather than ‘naturally’ existing. The chapter focuses on two avenues: antisocial behaviors and antisocial design. With antisocial behaviors the chapter examines two types of behaviors, one, people or bots who act in what is considered to be malicious to others such as trolling, spamming, and spreading misinformation. The second group of antisocial behaviors is about people who go against the connectivity ideal of social media and practice various types of disconnectivity such as unfriending, unliking or disconnecting, temporarily or permanently. In the second avenue, the chapter focuses on antisocial designs that can broadly be called dark patterns because these are intentional interventions in social media’s interface to create a specific social behavior. These dark patterns come in the shape of showing specific metrics, algorithmic ordering that is presented as ‘organic’, and terms of use. What these two avenues show is that nothing is inherently ‘social’ in social media and highlights the importance in examining how different mechanisms make it seem naturally produced.
A Scheme for Efficient Question Answering with Low Dimension Reconstructed Embeddings

Question answering (QA) is a fundamental task whose aim is to answer natural language questions. Several embedding based methods that capture semantic similarity between the natural language question and the given answer have been proposed. While these methods achieve good results on the QA task, the high dimensional representations of embeddings comes at a high memory and computational cost. In this work, we propose a scheme where embedding dimensions are reconstructed with a low dimension for solving the question answering task. To be specific, we apply an autoencoder that learns the low dimension properties of the input embedding representations which we then use for measuring similarity between the natural language question and the given answer. We demonstrate through our analysis that with dimensionality reduction, computation time, and memory requirements can be reduced all the while achieving a reasonable performance. Experiments and analysis on insuaranceQA benchmark, show that our proposed method can obtain performance comparable to standard baselines while remaining cost efficient on both time and memory.
WYK: Mobile Device Authentication Using the User’s Address Book

Authenticating a user the correct way is paramount to IT systems, where the risk is growing more and more in number and complexity. This is specially important in mobile phones, where a number of applications require continuous device authentication following the Point-of-Entry user authentication. Existing common approach in systems that require strict security rules and regulations is to use a One-Time-Password (OTP). Usually the OTP is generated using a special hardware device or another application that is synchronised with the back-end system. Another approach is to use SMS based activation/approval codes such as used by Telegram, Facebook, Twitter and other social media platforms. However, this approach has three major drawbacks: (1) it requires active user participation/interaction which could be annoying if repeated continuously, (2) SMS messages can be accessed by service provider’s employees, and (3) it does not consider the authenticity of the device from which the services are being accessed. The later is particularly serious as access sessions can be hijacked by malicious entities. In this paper, we investigate the possibility of using the user’s address book (contacts list) to continuously authenticate the device to ensure the services are only accessed from the mobile phone that belongs to the legitimate user. We call this authentication the Who-You-Know (WYK) scheme. For our research, we developed three components, the WYK-Mobile-Service, WYK-API-Server and a Mobile-Demo-Application. The WYK-API-Server exposes a set of authentication server APIs and the WYK-Mobile-Service consumes these APIs to authenticate the device every time the mobile applications are launched and make a request to the API server. Finally, the Mobile-Demo-Application will extract user’s data from the server if the device is successfully authenticated.
Determining Bring Your Own Device (Byod) Security Policy Compliance Among Malaysian Teleworkers: Perceived Cybersecurity Governance as Moderator

Literature evidently shows that many organizations have enabled Bring Your Own Device (BYOD) for their employees as an immediate strategy to cushion the risks of disruption to their business operations. Though these types of environments were typically not designed to support an organization&#x2019;s entire workforce, it certainly made the transition easier as BYOD policy offers organizational flexibility, efficiency, and collaboration in remote work-from-home cases. Although BYOD brings many benefits to organizations and employees, cybersecurity on one endpoint is a critical concern for organizations. Cyber intruders will capitalize on any cybersecurity vulnerabilities to steal valuable data. While organizations have established BYOD security policy as a basis, the issue is whether the teleworkers comply with it. Protection Motivation Theory is used to explain the action taken by teleworkers to protect themselves when under attack and how accounting teleworker&#x2019;s behavior to avoid cyber threat. Intention compliance has been studied by many researchers and recently, there was a call from a researcher to study the actual compliance in ISSPs due to a gap between intention and actual compliance. Hence, ensuring BYOD security policy compliance is crucial among the teleworkers. This paper, supported by Protection Motivation Theory (PMT) in addressing gaps in the literature, presents a conceptual model that examines determinants of BYOD security policy compliance among Malaysian teleworkers. The role of the perceived cybersecurity governance is also incorporated to investigate its interplay with the determinants.
Artificial Intelligence Path Search Technology Based on Marine Safety Big Data of Ships

Under the background of the gradual implementation of the national big data strategy and the smooth development of data science, data is gradually changing from a simple processing object to a basic strategic resource, and data-driven analysis and research methods are also profoundly changing the way of traditional scientific research. With the advantages of low cost, high safety and large volume, maritime shipping has become the most important way of commodity exchange and trade in the modern world. The purpose of this paper is to provide technical suggestions for safe navigation at sea by studying artificial intelligence path search technology based on big data of maritime safety of ships. In order to further improve the efficiency and safety of maritime shipping, this paper makes an in-depth study on the route and path search technology of ship AIS system. The ship AIS system is an automatic identification system of ship, which plays an important role in ship management, route scheduling and other fields. This paper first introduces the adaptive neural network algorithm, and then based on the intelligent algorithm developed a ship AIS intelligent path search technology, and introduces the principle and working process of the technology, results show that the error of the AIS path search based on neural network algorithm with growth and reduce the time, eventually can realize error is 0.
Automatic Telephone Interview Survey System

Nowadays, governments or enterprises often use questionnaires to investigate people’s views on issues or products, and telephone interviews are one of the most commonly used methods for questionnaire surveys. The proposed system is mainly divided into four parts. The first part is pre-processing, according to the questionnaire to be interviewed to generate the data needed in the follow-up dialogue in advance. The second part is to build a VoIP soft phone, the purpose is to realize the function of making calls on the software side with multiple SIP lines at the same time through the SIP architecture. In addition, the system also connects the front-end softphone module with the back-end dialogue module through a dialogue interface to automatically conduct the telephone interview. The third part is multi-turn question answering dialogue. If the call is answered, the dialogue module will actively ask the respondent according to the questions in the questionnaire, and then through hybrid answer matching to determine the option matched by the respondent’s answer. Finally, the dialogue module decides the question to be asked in the next turn to achieve the effect of multi-turn dialogue. The fourth part is call detail record and table generation, which is responsible for recording the call status and answering situation during the telephone interview. In addition, the system performs post-processing according to the telephone interview results of all lines after the execution, so that we can quickly understand the situation of the telephone interview survey.
Towards Using Heterogeneous Relation Graphs for End-to-End TTS

Neural models for end-to-end text-to-speech (TTS) synthe-sis are increasingly outperforming traditional approaches in statistical parametric speech synthesis. Speech generation in these neural models predominantly relies on using free-form text as the input modality. However, the earlier statistical parametric models were built on encoded phonetic and syn-tactic features. In this work, we explore the possibility of explicitly feeding deterministic linguistic structure to a neural TTS system in the form of Heterogeneous Relational Graphs (HRGs), an expressive formalism capable of representing pho-netic and syntactic information. Specifically, we use Graph Convolutional Networks to learn structurally informed contin-uous representations of the HRGs, which can be seamlessly passed to the encoders of popular neural TTS models like TransformerTTS or Tacotron. Furthermore, our simple HRG based text-to-speech synthesis leverages the syntactic bias in HRGs as demonstrated by improvements in automated met-rics and human evaluation on i) the single speaker dataset LJSpeech; ii) the multi-speaker dataset Arctic; and iii) out-of-domain test sets from the Blizzard challenge. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> The code, trained models, and our dataset of HRGs will be released at https://github.com/ars22/GraphNeuralTTS/.
선교초기부터 삼일운동 시기까지 한국기독교의 복음주의의 성격 : 한국 주류 개신교의 형성에 대한 역사적 연구

This paper will investigate historically in what ways evangelicalism constructed Korean Protestantism and in turn, how evangelicalism has been influenced by the Korean contexts, focusing on the period from 1884 to 1919. An interaction between the two informed the nature and character of Korean Protestantism cooperating and conflicting with each other. Nationalism paved the way for receiving, establishing, and developing evangelical Protestantism in the Korean context while evangelicalism reinforced and preserved nationalism before and during the colonial period. Nevertheless, as shown in the Great Revival of 1907, the interrelatedness came to fracture when evangelical missionaries and leaders emphasized the separation between religion and politics keeping the church away from the nationalist activism against Japanese imperialism. Despite the separation between religion and politics, displayed in the March First Independence Movement in 1919, evangelical Protestantism continued to function as a center for the cultural and religious nationalism in the colonial period. Bogǔmjuǔi (evangelicalism) and minjokjuǔi (nationalism) formed the nature and character of the mainstream Korean Protestantism into bogǔmjuǔi minjok kidokkyo (evangelical Nationalist Christianity).
Bitcoins

The Encyclopedia of Tourism Management and Marketing is, quite simply, the definitive reference work in the field. Carefully curated by leading tourism scholar Dimitrios Buhalis, this is the largest tourism management and marketing ontology that has ever been put together and offers a holistic examination of this interdisciplinary field This is a 4-volume set. Volume 1 contains entries A–D, Volume 2 contains entries E–I, Volume 3 contains entries J–R and Volume 4 contains entries S–Z. Page numbers start from 1 in each volume.
A Study of Gyorinsuji(交隣須知) Volume 4

The most well-known Korean textbook of Japanese during the Edo and Meiji eras, is known as the Gyorinsuji(交隣須知). There are currently four publications and more than ten manuscripts of the Gyorinsuji in existence. This paper analyzes the headwords and Korean sentences in 9 of the versions of Gyorinsuji, focusing on 4 publications and 5 manuscripts. This will be done to clarify the influence of the Korean sentences in each manuscript of the 1881 publication of Gyorinsuji. Additionally, it will show the differences in the composition of the headwords in all of the versions. This study shows that the influence of the Korean sentences in each manuscript of the 1881 publication is different for each section. The sections of JEONGJI(靜止), SUUN(手運), JOKSA(足使), SIMDONG(心動), EON􋹲EO (言語), SIMSA(心使), SADAN(四端), SOYO(逍遙) are all influenced by the manuscripts of the Seoul University version, the Aston version and the Oda version. The sections of EOSA(語 辭), DAEDA(大多), BEOMWI(範圍), JAP􋹲EO(雜語) are influenced by the manuscripts of the Nagasaki version and the Kyoto University version.