Types Of Tokens Research Articles

Head-Tail 토큰화 기법을 이용한 한국어 품사 태깅

Korean part-of-speech taggers decompose a compound morpheme into unit morphemes and attach part-of-speech tags. So, here is a disadvantage that part-of-speech for morphemes are over-classified in detail and complex word types are generated depending on the purpose of the taggers. When using the part-of-speech tagger for keyword extraction in deep learning based language processing, it is not required to decompose compound particles and verb-endings. In this study, the part-of-speech tagging problem is simplified by using a Head-Tail tokenization technique that divides only two types of tokens, a lexical morpheme part and a grammatical morpheme part that the problem of excessively decomposed morpheme was solved. Part-of-speech tagging was attempted with a statistical technique and a deep learning model on the Head-Tail tokenized corpus, and the accuracy of each model was evaluated. Part-of-speech tagging was implemented by TnT tagger, a statistical-based part-of-speech tagger, and Bi-LSTM tagger, a deep learning-based part-of-speech tagger. TnT tagger and Bi-LSTM tagger were trained on the Head-Tail tokenized corpus to measure the part-of-speech tagging accuracy. As a result, it showed that the Bi-LSTM tagger performs part-of-speech tagging with a high accuracy of 99.52% compared to 97.00% for the TnT tagger.

Blockchain tools for socio-economic interactions in local communities

Abstract Blockchain technology is generating interest in novel applicative fields such as co-production of public services. Our CommonsHood project is a “wallet app” that uses the Blockchain as a tool to support sustainability of the local economy. Its tokenization mechanism allows everyone to create new types of cryptographic tokens on the Blockchain in order to digitalize assets, augment the availability of local liquidity, and incentivize cooperative socio-economic interactions. This article analyzes a concrete application of CommonsHood for innovating local development policies and service co-production in the tourism sector. We examine this application using Linders’s analytical framework for information and communications technology (ICT)-enabled co-production of services (2012). We show the advantages our project brings for local policies on tourism development, and we discuss the benefits and costs of using the Blockchain in that context. We argue that the observed case study covers different types of digitally enabled co-production of services, and that it can be defined as a case of Governance as a Platform. We also argue that well-established analytical frameworks for ICT-enabled co-production of services need to be expanded in order to account for the new affordances enabled by the Blockchain technology, namely the creation and transaction of digital values, which represent a paradigm change in how we understand the Internet and digital co-production.

Token Economy for Sustainable Education in the Future: A Scoping Review

This research aims to examine the use of a token economy for education sustainability. It presents a recent review and evaluation of the token economy used among young learners and learners with special needs for behavior management and learning engagement in teaching. Online articles from Google Scholar, ERIC, and UKMLibrary were used. The terms used for reviewing the articles were token economy, token systems, positive reinforcement, and rewards. The scoping review protocol was used for this study. A total of 60 relevant articles published from 2000 to 2020 were filtered and grouped into three major themes for review: behavior management, learning engagement, and types of tokens. Findings suggested that although previous research had examined the impact of a token economy on behavior management and learning engagement, there was limited research on the correlation between teaching methods and social fairness. Teachers as the main participants in assessing the effectiveness of a token economy, were also lacking. Additionally, the use of social and physical reinforcers was found to assist in obtaining the desired behaviors and learning engagement from participants, thereby enabling them to sustain learners’ interest in future lessons.

NFT tokens in the context of copyright on the works

The article attempts to consider legal issues arising in connection with the use of blockchain technologies in the field of intellectual property rights to works of art. The article explores the essence of NFT tokens associated with copyright objects, analyzes alternative options for attributing them to the institute of real rights or intellectual property rights. The legal regime of certain types of tokens and their legal regulation in foreign legislation is considered. The conclusion is formulated that the NFT token is a digital confirmation of copyright related to a digital work. The current copyright regulations provide protection to the original work associated with the token, to the extent that protection is granted to works that exist in the real world. It is proposed to consider the NFT token registered in the blockchain registry as proof of the legitimacy of the copyright holder's title, the authenticity of the copy of the work and its origin (provenance). It is proved that the illegal issue of a token associated with a work, without the consent of the copyright holder of this work, should be recognized as the manufacture of a counterfeit copy of the work, and the person who illegally issued such a token is liable for creating a counterfeit copy of the work if it is possible to identify the subject of responsibility and there is evidence of his bad faith.

Learning Implicit Class Knowledge for RGB-D Co-Salient Object Detection With Transformers.

RGB-D co-salient object detection aims to segment co-occurring salient objects when given a group of relevant images and depth maps. Previous methods often adopt separate pipeline and use hand-crafted features, being hard to capture the patterns of co-occurring salient objects and leading to unsatisfactory results. Using end-to-end CNN models is a straightforward idea, but they are less effective in exploiting global cues due to the intrinsic limitation. Thus, in this paper, we alternatively propose an end-to-end transformer-based model which uses class tokens to explicitly capture implicit class knowledge to perform RGB-D co-salient object detection, denoted as CTNet. Specifically, we first design adaptive class tokens for individual images to explore intra-saliency cues and then develop common class tokens for the whole group to explore inter-saliency cues. Besides, we also leverage the complementary cues between RGB images and depth maps to promote the learning of the above two types of class tokens. In addition, to promote model evaluation, we construct a challenging and large-scale benchmark dataset, named RGBD CoSal1k, which collects 106 groups containing 1000 pairs of RGB-D images with complex scenarios and diverse appearances. Experimental results on three benchmark datasets demonstrate the effectiveness of our proposed method.

Putting collation of text witnesses on a formal basis

Abstract This article presents an approach to the collation problem of text witnesses which is correct for all distance functions and is applicable to the alignment of any types of tokens, be it letters, words, sentences, or paragraphs. In contrast to the existing approaches, which all are heuristics in nature, we specify a formal model in the form of an integer linear program (ILP) that formally describes the optimization problem. For a special case that usually occurs in practice, we then transfer the ILP into an efficient algorithm that optimally solves the alignment problem. In the second part of the article, we apply our approach to the alignment of paragraphs of text witnesses—an alignment problem that has received little attention in the literature so far—and compare the results of our approach, which we have called TSaligner, with those of CollateX.

SwapCT: Swap Confidential Transactions for Privacy-Preserving Multi-Token Exchanges

Abstract Decentralized token exchanges allow for secure trading of tokens without a trusted third party. However, decentralization is mostly achieved at the expense of transaction privacy. For a fair exchange, transactions must remain private to hide the participants and volumes while maintaining the possibility for noninteractive execution of trades. In this paper we present a swap confidential transaction system (SwapCT) which is related to ring confidential transactions (e.g. used in Monero) but supports multiple token types to trade among and enables secure, partial transactions for noninteractive swaps. We prove that SwapCT is secure in a strict, formal model and present its efficient performance in a prototype implementation with logarithmic signature sizes for large anonymity sets. For our construction we design an aggregatable signature scheme which might be of independent interest. Our SwapCT system thereby enables a secure and private exchange for tokens without a trusted third party.

Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs

To apply neural sequence models such as the Transformers to music generation tasks, one has to represent a piece of music by a sequence of tokens drawn from a finite set of pre-defined vocabulary. Such a vocabulary usually involves tokens of various types. For example, to describe a musical note, one needs separate tokens to indicate the note’s pitch, duration, velocity (dynamics), and placement (onset time) along the time grid. While different types of tokens may possess different properties, existing models usually treat them equally, in the same way as modeling words in natural languages. In this paper, we present a conceptually different approach that explicitly takes into account the type of the tokens, such as note types and metric types. And, we propose a new Transformer decoder architecture that uses different feed-forward heads to model tokens of different types. With an expansion-compression trick, we convert a piece of music to a sequence of compound words by grouping neighboring tokens, greatly reducing the length of the token sequences. We show that the resulting model can be viewed as a learner over dynamic directed hypergraphs. And, we employ it to learn to compose expressive Pop piano music of full-song length (involving up to 10K individual tokens per song), both conditionally and unconditionally. Our experiment shows that, compared to state-of-the-art models, the proposed model converges 5 to 10 times faster at training (i.e., within a day on a single GPU with 11 GB memory), and with comparable quality in the generated music

Deep Learning Strategy to Recognize Kannada Named Entities

Entity representatives are useful in understanding the natural language tasks including the semantics of the Kannada sentences into various entities. In this paper, we have come up with new pertained tag based representative learning of words and entities based on the bidirectional parsing. The proposed research works on segmenting the sentences of Kannada words into various taken, where every token makes various contributions in understanding the semantics of Kannada Sentences which treats words and entities in a given text as independent tokens, and outputs tagged entities based on representative learning mechanism. The research also has focused its attention towards achieving the results of good classification accuracy while recognizing the entities are through the tagging mechanism that is an extension of the general self-tagging mechanism of the Supervised Machine Learning Technique, and considers the types of tokens (words or entities) when computing attention scores. The erected research work has given its significant contribution in terms of good results over a standard benchmark datasets. In particular, it obtains state-of-the-art results on five well-known datasets: Open Entity (entity typing), TACRED (relation classification), CoNLL-2003 (named entity recognition), ReCoRD (cloze-style question answering), and SQuAD 1.1 (extractive question answering) as well as Kannada Named Entity Recognition of Central Institute of Indian Languages.

Quantity-quality trade-off in the acquisition of token preference by capuchin monkeys (Sapajus spp.).

Money represents a cornerstone of human modern economies and how money emerged as a medium of exchange is a crucial question for social sciences. Although non-human primates have not developed monetary systems, they can estimate, combine and exchange tokens. Here, we evaluated quantity-quality trade-offs in token choices in tufted capuchin monkeys as a first step in the investigation of the generalizability of tokens as reinforcers, which is a potentially relevant factor underlying the emergence of money in humans. We measured capuchins' exchange preferences when they were repeatedly provided with 10 units of three token types yielding food combinations varying in quantity and quality. Overall, capuchins maximized their quantitative payoff, preferring tokens associated with a higher food amount, rather than showing violations of rationality. However, some individuals did not maximize their qualitative payoff, possibly because of conditional valuation effects or owing to the choice overload phenomenon, according to which too many options reduce the accuracy of choice. Our study supports the importance of comparative research to finely analyse the multiple components shaping the economic behaviours of other species, possibly to achieve a more comprehensive, evolutionary- and ecologically based understanding of human economic behaviour. This article is part of the theme issue 'Existence and prevalence of economic behaviours among non-human primates'.

Potential of Cryptocurrency as Global Money of the Sixth Technological Mode Based on the Global Financial System

The change in technological modes is accompanied by financial crises that lead to changes in the global financial system. For a long period, gold played the role of world money. However, the development of technology required the transition to more flexible forms of world money, the basis of which is the national currency of the most industrialized countries. Currently, the transition to the technologies of the Sixth technological mode is accompanied by a global financial crisis. The US dollar does not cope with the functions that the latest technologies present to monetary systems. They are being replaced by a new generation of cryptocurrency-based monetary systems. Cryptocurrencies and blockchain offer new forms of investing, calculating, storing, and saving money. Such financial instruments as various types of cryptocurrencies, tokens, smart contracts, and crypto exchanges offer new opportunities for effective investment in technologies of the Sixth technological mode.

Pengaruh Model Pembelajaran Kooperatif Tipe Time Token Terhadap Hasil Belajar Bahasa Indonesia Siswa SD

: This research to find out whether there is the influence of the cooperative to time token type learning model on the learning outcomes of Indonesian language speaking skills in fifth grade students of SD Negeri 1 Massepe. This research uses a quantitative approach to the type of experimental research and uses a Pre-Experimental design in the form of One Group Pre-test - Post-test Design. The sampling technique used in this study was purposive sampling technique with a sample of 15 students. The results of hypothesis testing using the One Sample T-Test test obtained a significance of 0.00 (0.00 <0.05) the average score of the pretest was smaller than the average score of the posttest or µ1 ˂ µ2 indicating that H0 was rejected and Ha was accepted which means there are differences in the average results of speaking skills of fifth-grade students of SDN 1 Massepe on Indonesian language subjects between before and after the use of cooperative learning models of time token types. Based on these results it can be concluded that there is the influence of the cooperative to time token type learning model on the learning outcomes of Indonesian speaking skills in fifth grade students of SD Negeri 1 Massepe.

Investigating the Investment Behaviors in Cryptocurrency

This article investigates the socio-demographic characteristics that individual cryptocurrency investors exhibit and the factors that go into their investment decisions in different Initial Coin Offerings (ICOs). We conducted a web-based revealed preference survey among Australian and Chinese blockchain and cryptocurrency followers, and applied a Multinomial Logit model to inferentially analyze the characteristics of cryptocurrency investors and the determinants of their choice of investment in “cryptocurrency coins” versus other types of ICO tokens. The results showed differences in the determinant of these two choices among Australian and Chinese cryptocurrency folks. The significant factors of these two choices included age, gender, education, occupation, and investment experience, and they aligned well with the behavioral literature. Furthermore, in addition to differences in how they ranked the attributes of ICOs, there was further variance between how Chinese and Australian investors ranked deterrence factors and investment strategies. TOPICS:Currency, emerging markets Key Findings • The significant factors of the choice of investment in cryptocurrency include age, gender, education, occupation, and previous investment experience. • Chinese and Australian investors rank the ICO attributes differently. • The deterrence factors and investment strategies vary between Chinese and Australians.

Treasury Consultation Paper on ICOs in Australia: The Technology, The Market, and The Regulation of ICOs

The Australian Treasury has identified a number of challenges in FinTech, especially around Initial Coin Offerings (ICOs). In this paper we examine four types of tokens within ICOs: pure utility tokens, security tokens, stored value tokens, and hybrid tokens. There is considerable confusion surrounding what each means and signifies, and how each should be treated by both consumers and regulators. We explore the differences, noting what promoters should do to avoid falling into regulatory traps, and the consequences for selecting particular types of token. Because of the confusion around ICO tokens, we suggest there should be a new asset class of token recognised in the Australian Corporations Act. It would have its own funding limits and regulatory framework. Finally, we outline a new code of conduct for ICOs.

Governing Blockchain-based Token in Indonesia: Legal and Technical Perspective

In the past decade, blockchain technology has caught the world's attention because of its disruptive nature in various industries. Along with blockchain adoption, blockchain-based or more popularly known as the token, are widely used as a representation of a certain asset. In its development, blockchain innovators continue to encourage the birth of new tokens with more diverse attribution. From the regulator's point of view, the above gave rise to problems in the formation of regulations relating to tokens, mainly on its legality whether token will be determined as currency, securites, or commodity. If regulations still cannot catch up with the gap of technological advancement, this will actually hinder the development of blockchain technology in Indonesia. The token regulatory framework has been designed in several countries which have provided clear distinguishing characteristics for each type of token. However, in Indonesia, the absence of a clear and distinct definition of the types of tokens creates legal uncertainty for stakeholders. Therefore, this paper aims to give clarity to the legality of Blockchain-based tokens in Indonesia.

CodeGRU: Context-aware deep learning with gated recurrent unit for source code modeling

Recently deep learning based Natural Language Processing (NLP) models have shown great potential in the modeling of source code. However, a major limitation of these approaches is that they take source code as simple tokens of text and ignore its contextual, syntactical and structural dependencies. In this work, we present CodeGRU, a gated recurrent unit based source code language model that is capable of capturing source code's contextual, syntactical and structural dependencies. We introduce a novel approach which can capture the source code context by leveraging the source code token types. Further, we adopt a novel approach which can learn variable size context by taking into account source code's syntax, and structural information. We evaluate CodeGRU with real-world data set and it shows that CodeGRU outperforms the state-of-the-art language models and help reduce the vocabulary size up to 24.93\%. Unlike previous works, we tested CodeGRU with an independent test set which suggests that our methodology does not requisite the source code comes from the same domain as training data while providing suggestions. We further evaluate CodeGRU with two software engineering applications: source code suggestion, and source code completion. Our experiment confirms that the source code's contextual information can be vital and can help improve the software language models. The extensive evaluation of CodeGRU shows that it outperforms the state-of-the-art models. The results further suggest that the proposed approach can help reduce the vocabulary size and is of practical use for software developers.

Legal regulation of crypto assets in Switzerland

The development of cryptocurrency markets make the investors to seek for most convenient jurisdictions from the perspective of legal regulation. The countries commonly associated with the developed financial legal systems are often fasten attention. One of such financial hubs is Switzerland, which just starts to form the approaches towards creation of legal regime for operations with virtual assets. The subject of this research is the Swiss legal acts in area of securities, licensing, taxes related to regulation of cryptocurrency, as well as reports of the supervisory authorities for Swiss financial market on the matter. The object of this research is the legal framework for regulation of mining activity. The authors examine the rules dedicated ti the questions of licensing of the activity related to operations with different types of tokens. Special attention is given to the question of taxation of the income received from operations with cryptocurrencies. The author’s special contribution consists in comprehensive analysis of foreign sources presented on the three European languages. Having analyzed the legislation of Switzerland, the conclusion is made that similar to many developed countries, Switzerland has not created a complex regulation of operations with cryptocurrencies. At the same time, the normative acts that regulate certain aspects of circulation of crypto assets, such as fund raising in terms of tokens distribution and taxation have been adopted. Regulation of crypto assets often depends on the qualification of different types of tokens, in other words, their regime is consigned to the operations with such assets that are most similar to the corresponding type. The increase of operations with crypto assets will soon inevitably result in creation of a more accurate legal regime

Cryptocurrency potential in the context of transition of global economy to the sixth technological paradigm

This article explores the potential of using cryptocurrency as universal currency in the conditions of transition of the global economic system towards sixth technological paradigm. The goal of this research consists in analysis of the patterns of co-evolution of the global financial system, technological system, and global economy. Based on the historical material, the author demonstrates how shift in technological paradigms is accompanied by financial crises, and result in the changes of the world financial system. Over the course of time, the gold served as the universal currency, but the advancement of technologies demanded the transition towards more flexible forms of world currency based on the national currencies of most industrialized countries. Currently, the transition to the technology of the sixth technological paradigm is followed by the global financial crisis. The U.S. dollar is not handling the functions imposed by the latest technologies upon monetary systems. The conclusion is made that finite currencies are being replaced by an innovative generation of monetary systems that are based on cryptocurrency. The authors systematize the innovation forms of investment, accounting, keeping and saving of funds, which are based on cryptocurrency and blockchain. It is demonstrated that innovation financial instruments, including different types of cryptocurrency, tokens, smart contracts, and cryptocurrency exchanges, open new opportunities for effective investment in the technologies of sixth technological paradigm. The results of research can be valuable for the government branches in establishment of the policy for usage of cryptocurrency and blockchain for entrepreneurs dealing with developments in the area of practical implementation of cryptocurrency as innovative currency.

Nursing handovers as unbounded and scalar events

Abstract In this paper we analyse data from nursing handover meetings in terms of the interplay of different voices that operate at different interactional and institutional scales. We suggest, firstly, that the handover is not a single bounded event, as suggested in previous literature, but rather a gradual moving in and out of focus of a particular discourse activity; and, secondly, that while different phases within the handover as an extended event are characterised by voices operating at a specific scale, there are continuous movements between scales in each phase. This leads us to suggest two categories of rescaling as an activity: translational rescalings, as the handover shifts between phases and from one scale to another, and digressive scales, in which the scale of interaction that typifies a specific phase is temporarily interrupted by another. We illustrate how both these categories serve important revoicing functions and, on the basis of this analysis, extend the use of scales theory in interactional linguistics through the addition of dynamic systems theory and a-curve distributions, in which 20% of token types predominate, while the remainder, or tail, perform essential complementary activities that over time can open up space for gradual shifts in the characteristics and overall function of the activity itself.

Your Bitcoin Is Mine: What Does Law and Economics Have to Say about Property Rights in Cryptocurrencies?

Can anyone really own virtual tokens such as Bitcoin and Ether? And if so, how should the law protect the rights of the owner? Legal rulings in federal courts have yielded inconsistent policies regarding the applicable remedy when rights in cryptocurrencies are infringed. Some adopt a property rule, granting injunctions and enforcement of property rights against third parties, whereas others restrict the remedy to damages. However, all rulings share one problematic feature: a lack of distinction between types of tokens, resulting in an implicit one-size-fits-all policy. The economic analysis of law suggests that the choice between a property rule and a liability rule should depend on transaction costs, but such costs typically differ across cryptotokens, because tokens are diverse and customizable. Thus, this Article proposes to exploit the common taxonomy of cryptotokens, which distinguishes between security, utility, and currency tokens, as a proxy for transaction costs.