scholarly journals Shoreline: Data-Driven Threshold Estimation of Online Reserves of Cryptocurrency Trading Platforms

2020 ◽  
Vol 34 (01) ◽  
pp. 1194-1201
Author(s):  
Xitong Zhang ◽  
He Zhu ◽  
Jiayu Zhou
Keyword(s):  
Empirical Studies ◽  
Gain Control ◽  
Data Driven ◽  
Optimal Threshold ◽  
Threshold Estimation ◽  
Trading Systems ◽  
Different Types ◽  
Dynamic Trading ◽  
Trading Networks ◽  
Digital Assets

With the proliferation of blockchain projects and applications, cryptocurrency exchanges, which provides exchange services among different types of cryptocurrencies, become pivotal platforms that allow customers to trade digital assets on different blockchains. Because of the anonymity and trustlessness nature of cryptocurrency, one major challenge of crypto-exchanges is asset safety, and all-time amount hacked from crypto-exchanges until 2018 is over $1.5 billion even with carefully maintained secure trading systems. The most critical vulnerability of crypto-exchanges is from the so-called hot wallet, which is used to store a certain portion of the total asset of an exchange and programmatically sign transactions when a withdraw happens. Whenever hackers managed to gain control over the computing infrastructure of the exchange, they usually immediately obtain all the assets in the hot wallet. It is important to develop network security mechanisms. However, the fact is that there is no guarantee that the system can defend all attacks. Thus, accurately controlling the available assets in the hot wallets becomes the key to minimize the risk of running an exchange. However, determining such optimal threshold remains a challenging task because of the complicated dynamics inside exchanges. In this paper, we propose Shoreline, a deep learning-based threshold estimation framework that estimates the optimal threshold of hot wallets from historical wallet activities and dynamic trading networks. We conduct extensive empirical studies on the real trading data from a trading platform and demonstrate the effectiveness of the proposed approach.

scholarly journals Shoreline: Data-Driven Threshold Estimation of Online Reserves of Cryptocurrency Trading Platforms (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13985-13986
Author(s):  
Xitong Zhang ◽  
He Zhu ◽  
Jiayu Zhou
Keyword(s):  
Deep Learning ◽  
Network Security ◽  
Data Driven ◽  
Total Asset ◽  
Threshold Estimation ◽  
Trading Systems ◽  
Different Types ◽  
Dynamic Trading ◽  
Trading Networks ◽  
Digital Assets

With the proliferation of blockchain projects and applications, cryptocurrency exchanges, which provides exchange services among different types of cryptocurrencies, become pivotal platforms that allow customers to trade digital assets on different blockchains. Because of the anonymity and trustlessness nature of cryptocurrency, one major challenge of crypto-exchanges is asset safety, and all-time amount hacked from crypto-exchanges until 2018 is over $1.5 billion even with carefully maintained secure trading systems. The most critical vulnerability of crypto-exchanges is from the so-called hot wallet, which is used to store a certain portion of the total asset online of an exchange and programmatically sign transactions when a withdraw happens. It is important to develop network security mechanisms. However, the fact is that there is no guarantee that the system can defend all attacks. Thus, accurately controlling the available assets in the hot wallets becomes the key to minimize the risk of running an exchange. In this paper, we propose Shoreline, a deep learning-based threshold estimation framework that estimates the optimal threshold of hot wallets from historical wallet activities and dynamic trading networks.

scholarly journals Optimal Threshold Estimation using Grey Wolf Optimization for EMD-DTCWT Based ECG Denoising

2020 ◽  
Vol 8 (6) ◽  
pp. 2589-2596
Keyword(s):  
Adaptive Filtering ◽  
Data Driven ◽  
Optimal Threshold ◽  
Signal Denoising ◽  
Grey Wolf ◽  
Threshold Estimation ◽  
Complex Wavelet Transform ◽  
Grey Wolf Optimization ◽  
Mode Decomposition ◽  
Ecg Denoising

The noise reduction in the ECG has been focused for research in recent years, since desired reduction allows a better signal pre-processing, and allows to extract from it the maximum amount of efficient and meaningful information. This paper proposes an adaptive threshold technique using Empirical Mode Decomposition (EMD) and Dual-Tree Complex Wavelet Transform (DTCWT) for ECG signal denoising. Initially the data driven EMD technique is applied to get the IMFS and these IMFS further passed though DTCWT for filtration. To accomplish the better adaptive filtering process the optimal threshold is further calculated based on Grey Wolf Optimization (GWO). The performance evaluation is achieved on MIT-BIH database.

Reliability Estimates for IRT-Based Forced-Choice Assessment Scores

2021 ◽  
pp. 109442812199908
Author(s):  
Yin Lin
Keyword(s):  
Impression Management ◽  
Empirical Studies ◽  
Forced Choice ◽  
Reliability Estimation ◽  
Estimation Methods ◽  
High Stakes ◽  
Personnel Decisions ◽  
Assessment Scores ◽  
Reliability Estimates ◽  
Different Types

Forced-choice (FC) assessments of noncognitive psychological constructs (e.g., personality, behavioral tendencies) are popular in high-stakes organizational testing scenarios (e.g., informing hiring decisions) due to their enhanced resistance against response distortions (e.g., faking good, impression management). The measurement precisions of FC assessment scores used to inform personnel decisions are of paramount importance in practice. Different types of reliability estimates are reported for FC assessment scores in current publications, while consensus on best practices appears to be lacking. In order to provide understanding and structure around the reporting of FC reliability, this study systematically examined different types of reliability estimation methods for Thurstonian IRT-based FC assessment scores: their theoretical differences were discussed, and their numerical differences were illustrated through a series of simulations and empirical studies. In doing so, this study provides a practical guide for appraising different reliability estimation methods for IRT-based FC assessment scores.

scholarly journals Adaptive data-driven age and patch mixing in contact networks with recurrent mobility

2021 ◽  
Author(s):  
Jesse Knight ◽  
Huiting Ma ◽  
Amir Ghasemi ◽  
Mackenzie Hamilton ◽  
Kevin Brown ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Age Distribution ◽  
Age Groups ◽  
Data Driven ◽  
Infectious Disease Transmission ◽  
Mobility Data ◽  
Contact Patterns ◽  
Different Types ◽  
Mixing Patterns ◽  
Transmission Models

AbstractInfectious disease transmission models often stratify populations by age and geographic patches. Contact patterns between age groups and patches are key parameters in such models. Arenas et al. (2020) develop an approach to simulate contact patterns associated with recurrent mobility between patches, such as due to work, school, and other regular travel. Using their approach, mixing between patches is greater than mobility data alone would suggest, because individuals from patches A and B can form a contact if they meet in patch C. We build upon their approach to address three potential gaps that remain. First, our approach includes a distribution of contacts by age that is responsive to underlying age distribution of the mixing pool. Second, different age distributions by contact type are also maintained in our approach, such that changes to the numbers of different types of contacts are appropriately reflected in changes to the overall age mixing patterns. Finally, we introduce and distinguish between two mixing pools associated with each patch, with possible implications for the overall connectivity of the population: the home pool, in which contacts can only be formed with other individuals residing in the same patch; and the travel pool, in which contacts can be formed with some residents of, and any other visitors to the patch. We describe in detail the steps required to implement our approach, and present results of an example application.Graphical Abstract

scholarly journals Corpus linguistics and its aplications in higher education

2010 ◽  
pp. 51 ◽  
Author(s):  
Miguel Fuster Márquez ◽  
Begoña Clavel Arroitia
Keyword(s):  
Higher Education ◽  
Corpus Linguistics ◽  
Teaching Practices ◽  
Language Teaching ◽  
Applied Linguistics ◽  
Data Driven ◽  
Future Success ◽  
Different Types ◽  
Theoretical Linguistics ◽  
Relevant Factors

The aim of this paper is to review and analyse relevant factors related to the implementation of corpus linguistics (CL) in higher education. First we set out to describe underlying principles of CL and its developments in relation to theoretical linguistics and its applications in modern teaching practices. Then we attempt to establish how different types of corpora have contributed to the development of direct and indirect approaches in language teaching. We single out Data Driven Learning (DDL) due to its relevance in applied linguistics literature, and examine in detail advantages and drawbacks. Finally, we outline problems concerning the implementation of CL in the classroom since awareness of the limitations of CL is vital for its future success.

scholarly journals Reputation, concessions, and territorial civil war

2018 ◽  
Vol 55 (5) ◽  
pp. 671-686 ◽  
Author(s):  
Nils-Christian Bormann ◽  
Burcu Savun
Keyword(s):  
Ethnic Groups ◽  
Armed Conflict ◽  
Empirical Studies ◽  
Power Sharing ◽  
Self Determination ◽  
Territorial Disputes ◽  
Territorial Conflicts ◽  
Different Types ◽  
Future Demands ◽  
Reputation Building

Barbara Walter’s application of reputation theory to self-determination movements has advanced our understanding of why many separatist movements result in armed conflict. Walter has shown that governments of multi-ethnic societies often respond to territorial disputes with violence to deter similar future demands by other ethnic groups. When governments grant territorial accommodation to one ethnic group, they encourage other ethnic groups to seek similar concessions. However, a number of recent empirical studies casts doubt on the validity of Walter’s argument. We address recent challenges to the efficacy of reputation building in the context of territorial conflicts by delineating the precise scope conditions of reputation theory. First, we argue that only concessions granted after fighting should trigger additional conflict onsets. Second, the demonstration effects should particularly apply to groups with grievances against the state. We then test the observable implications of our conditional argument for political power-sharing concessions. Using a global sample of ethnic groups in 120 states between 1946 and 2013, we find support for our arguments. Our theoretical framework enables us to identify the conditions under which different types of governmental concessions are likely to trigger future conflicts, and thus has important implications for conflict resolution.

scholarly journals Data-driven Learning in Second Language Writing Class: A Survey of Empirical Studies

2017 ◽  
Vol 12 (03) ◽  
pp. 182 ◽  
Author(s):  
Qinqin Luo ◽  
Jie Zhou
Keyword(s):  
Second Language ◽  
Empirical Studies ◽  
Ordinary Language ◽  
L2 Writing ◽  
Language Teachers ◽  
Data Driven ◽  
Free Access ◽  
Foreign Language Learners ◽  
Writing Class ◽  
Reference Tools

Corpus technology is commonly used by researchers and professionals for language description; however it can also be employed by second or foreign language learners in what has come to be known as data-driven learning (DDL). DDL has been suggested as an effective approach to improve second language (L2) learners’ writing competence. To popularize DDL approach among ordinary language teachers and learners, this paper offers an overview of empirical DDL research in writing published from 2010 to 2016, which can provide insights into how DDL approach is integrated into an actual writing classrooms and how much it can contribute to the development of L2 writing skill. The analysis of the surveyed studies reveals the great potentials of DDL activities in L2 writing class from different perspectives but it’s also found that corpora are not superior to other traditional reference tools for some consultation purposes. It is thus necessary to develop online platforms which could provide easy and free access to the user-friendly corpora along with other types of reference tools. Then suggestions about further studies are also offered in the end.

Modes of engagement with the future in everyday life

2019 ◽  
Vol 29 (3) ◽  
pp. 681-703
Author(s):  
Giuliana Mandich
Keyword(s):  
Everyday Life ◽  
Empirical Analysis ◽  
Daily Life ◽  
Empirical Studies ◽  
Public Domain ◽  
The Public ◽  
Starting Point ◽  
Different Types ◽  
The Future ◽  
Modes Of Engagement

This paper is aimed at understanding how we engage with the future in different ways in everyday life. Many empirical studies have emphasised that what we usually call ‘imagination’ of the future takes diverse forms and meanings. Varied narratives of the future that are possible coexist in daily life in a bumpy, semi-conscious and occasionally tense dialogue with one another. To understand this variation of narratives, a thorough exploration of the different modes of engaging with the future that various forms of agency bring into play is required, together with a sensitive empirical analysis. I use Thévenot’s theory of regimes of engagement as a starting point to at least partially explain this variety. Thévenot’s idea that different types of individual involvement in relation to different definitions of the relevant reality (e.g. familiarity, plans and the public domain of justification and exploration) contain interesting implications for the analysis of what I define as modes of engagement with the future. As involved as we are with social reality through specific formats, so are we with the future. As the ‘relevant reality’ is different according to the regime of engagement that we are involved in, the nature of anticipation also varies. The future is ‘made and measured’ within the logic of probability in the regime of plans; of possibility in the regime of justification; of practical anticipation in the regime of familiarity; and of discovery in the regime of exploration. This perspective helps to avoid a reification of the future as something that is ‘there’ and that we simply discover and avoids easy dichotomisation of forms of anticipation of the future as realistic or unrealistic.

scholarly journals Multi-brand loyalty in consumer markets: a qualitatively-driven mixed methods approach

2019 ◽  
Vol 53 (11) ◽  
pp. 2419-2450 ◽  
Author(s):  
Ghizlane Arifine ◽  
Reto Felix ◽  
Olivier Furrer
Keyword(s):  
Brand Loyalty ◽  
Cultural Context ◽  
Market Competition ◽  
Empirical Studies ◽  
Content Type ◽  
Family Factor ◽  
Consumer Markets ◽  
Different Types ◽  
Congruence Identity ◽  
Conceptual Foundations

Purpose Although multi-brand loyalty (MBL) in consumer markets has been identified in previous brand loyalty research, empirical studies have not yet explored the facets of its different types. This paper aims to have a deeper understanding of MBL by investigating its different types and facets. Design/methodology/approach This study uses a sequential, qualitatively driven mixed-method design consisting of in-depth interviews and supplementary survey research. Findings The findings of this study suggest that mood congruence, identity enhancement, unavailability risk reduction and market competition are the most important facets that explains the two types of MBL (complementary-based and product substitutes). Furthermore, the findings show that the family factor can motivate consumers to be multi-brand loyal by adding brands to an initially family-endorsed brand. Research limitations/implications This study advances the conceptual foundations of MBL and extends previous research on brand loyalty. Some of the findings may be limited to the economic and cultural context of relatively affluent countries with an abundance of market offers. Practical implications Marketing managers gain insights into how to manage brand loyalty and how to transition from MBL to single-brand loyalty. Originality/value The study generates novel insights into the facets of different types of MBL.

scholarly journals Assessing Community Resilience to Urban Flooding in Multiple Types of the Transient Population in China

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2784 ◽  
Author(s):  
Wenping Xu ◽  
Lingli Xiang ◽  
David Proverbs
Keyword(s):  
Climate Change ◽  
Empirical Studies ◽  
Back Propagation ◽  
Community Resilience ◽  
Back Propagation Neural Network ◽  
Disaster Resilience ◽  
Urban Flooding ◽  
Adaptation To Climate Change ◽  
Mitigation And Adaptation ◽  
Different Types

While various measures of mitigation and adaptation to climate change have been taken in recent years, many have gradually reached a consensus that building community resilience is of great significance when responding to climate change, especially urban flooding. There has been a dearth of research on community resilience to urban floods, especially among transient communities, and therefore there is a need to conduct further empirical studies to improve our understanding, and to identify appropriate interventions. Thus, this work combines two existing resilience assessment frameworks to address these issues in three different types of transient community, namely an urban village, commercial housing, and apartments, all located in Wuhan, China. An analytic hierarchy process–back propagation neural network (AHP-BP) model was developed to estimate the community resilience within these three transient communities. The effects of changes in the prioritization of key resilience indicators under different environmental, economic, and social factors was analyzed across the three communities. The results demonstrate that the ranking of the indicators reflects the connection between disaster resilience and the evaluation units of diverse transient communities. These aspects show the differences in the disaster resilience of different types of transient communities. The proposed method can help decision makers in identifying the areas that are lagging behind, and those that need to be prioritized when allocating limited and/or stretched resources.

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