Reviewerly/exHarmony huggingface dataset:
Plasma Go: A Scalable Sidechain Protocol for Flexible Payment Mechanisms in Blockchain-based Marketplaces.

Decentralized marketplace applications demand fast, cheap and easy-to-use cryptocurrency payment mechanisms to facilitate high transaction volumes. The standard solution for off-chain payments, state channels, are optimized for frequent transactions between two entities and impose prohibitive liquidity and capital requirements on payment senders for marketplace transactions. We propose PayPlace, a scalable off-chain protocol for payments between consumers and sellers. Using PayPlace, consumers establish a virtual unidirectional payment channel with an intermediary operator to pay for their transactions. Unlike state channels, however, the PayPlace operator can reference the custodial funds accrued off-chain in these channels to in-turn make tamper-proof off-chain payments to merchants, without locking up corresponding capital in channels with merchants. Our design ensures that new payments made to merchants are guaranteed to be safe once notarized and provably mitigates well-known drawbacks in previous constructions like the data availability attack and ensures that neither consumers nor merchants need to be online to ensure continued safety of their notarized funds. We show that the on-chain monetary and computational costs for PayPlace is O(1) in the number of payment transactions processed, and is near-constant in other parameters in most scenarios. PayPlace can hence scale the payment throughput for large-scale marketplaces at no marginal cost and is orders of magnitude cheaper than the state-of-art solution for non-pairwise off-chain payments, Zero Knowledge Rollups.
Do Payment Channel Networks Need a Blockchain? - Rethinking Blockchain Layers

One of the fundamental problems in designing digital currencies is the prevention of double-spends. The breakthrough of Bitcoin lies in its seminal idea to use a global blockchain to verify whether a coin has already been spent. Bitcoin’s approach to prevent double-spends, however, has the drawback that it does not scale in the number of transactions issued per second. To address this problem, current research explores building second layer architectures on top of the blockchain, such as payment channel networks. Although these architectures use a blockchain as their underlying layer, they need to solve the problem of preventing double-spends again. As it seems inefficient to solve the same problem multiple times, we explore whether payment channel networks with their way of preventing double-spends can be used to create an architecture for digital payments that is to some extent decentralized but does not require a blockchain as its underlying layer.A payment channel requires from its underlying layer a way to lock a channel’s funds during the lifetime of the channel. Instead of locking funds on a blockchain, this can be implemented by depositing funds at a trusted third party who is trusted to make the funds available again upon channel closure. In our current financial system, users deposit money into their bank accounts and trust their bank to make these funds available upon request. Making use of this trust, we build on the ideas of Tremback et al. and propose an architecture for a payment channel network where banks, or similar entities, perform the role of the underlying blockchain. In this architecture, a bank provides each channel with a unique identifier and locks a channel’s funds. When one party closes the channel, the bank informs the other party. In case of dispute about the channel’s closing state, the bank has to decide which state is most current and close the channel accordingly. By connecting multiple payment channels, a payment channel network can be created, which allows for decentralized payments using traditional currencies. Similar to cash, single payments cannot be tracked by banks in this architecture. To prevent the architecture from attracting illegal activities, the capacity of payment channels could be limited to a maximum value. Compared to exchanging traditional currencies for cryptocurrencies to use a payment channel network, this architecture removes the cost of currency exchanges and the risk introduced by exchange rate fluctuations.
CASE STUDIES ON MODELING SECURITY IMPLICATIONS ON SAFETY

Security is widely recognized as an important property that is tightly interdependentwith safety in safety-critical systems. The goal of this thesis is to conduct case studies on the implications t ...
LibGuides: Effective Notetaking: e-learning and eBooks (30 mins+)

Our top tips and advice on getting the most from your reading, taking effective notes from journal article and identifying links between sources.
Efficient Rule Learning with Template Saturation for Knowledge Graph Completion.

Efficiently inducing high-level interpretable regularities from knowledge graphs (KGs) is an essential yet challenging task that benefits many downstream applications. In this work, we present GPFL, a probabilistic rule learner optimized to mine instantiated first-order logic rules from KGs. Instantiated rules contain constants extracted from KGs. Compared to abstract rules that contain no constants, instantiated rules are capable of explaining and expressing concepts in more details. GPFL utilizes a novel two-stage rule generation mechanism that first generalizes extracted paths into templates that are acyclic abstract rules until a certain degree of template saturation is achieved, then specializes the generated templates into instantiated rules. Unlike existing works that ground every mined instantiated rule for evaluation, GPFL shares groundings between structurally similar rules for collective evaluation. Moreover, we reveal the presence of overfitting rules, their impact on the predictive performance, and the effectiveness of a simple validation method filtering out overfitting rules. Through extensive experiments on public benchmark datasets, we show that GPFL 1.) significantly reduces the runtime on evaluating instantiated rules; 2.) discovers much more quality instantiated rules than existing works; 3.) improves the predictive performance of learned rules by removing overfitting rules via validation; 4.) is competitive on knowledge graph completion task compared to state-of-the-art baselines.
A New Implementation of Manacher's Algorithm

Manacher's algorithm has been shown to be optimal to the longest palindromic substring problem. Many of the existing implementations of this algorithm, however, unanimously required in-memory construction of an augmented string that is twice as long as the original string. Although it has found widespread use, we found that this preprocessing is neither economic nor necessary. We present a more efficient implementation of Manacher's algorithm based on index mapping that makes the string augmentation process obsolete.
Exploring Key Factors for Customer Satisfaction in Online Shopping: A Systematic Literature Review

In the context of online shopping, customer satisfaction is considered as a important matter to be focused by marketers and organizations. Consequently, identification of what really affects customer satisfaction in online context is useful from many aspects. Previous researchers have attempted to address this important concept mostly through their empirical studies, utilizing limited number of factors. A closer examination reveals that those studies have utilized different sets of factors and been performed in different contexts. Overall, prior studies remain broad and appear relatively fragmented. At present, there is a lack of research which have used a systematic literature review process to examine the factors affecting online customer satisfaction. Therefore, the purpose of this research is to perform a comprehensive study on literature related to online customer satisfaction and analyze the factors identified by previous scholars under different criteria. Accordingly, the researchers gathered all possible studies related to online customer satisfaction between the period 2000 and January 2019. The study identified forty-one previous studies done by different researchers which revealed fifty-one different factors affecting online customer satisfaction. The researchers performed a rigorous analysis of those fifty-one factors under different criteria and results are presented in this paper. Keywords Online customer satisfaction; Online shopping; Systematic literature review
Pengukuran Kuat Hempasan Ombak Dan Kecepatan Angin Laut Berbasis Mikrokontroller Arduino Uno

The sea is a large body of salt water that is surrounded in whole or in part by land. In oceanography that examines various physical conditions of the sea, one of which is sea waves. In everyday life sea waves affect the activities of marine vessels and fishing vessels to sail. In this research, a device that is capable of monitoring the strength of ocean waves is made. The tool is designed using load cell sensors, wind speed sensors, Arduino Uno and Xbee-pro modules. From the tests carried out, the highest value of the wave's strong blow is 9.31 N/m2 and the wind speed is 3.62 m/s, while the lowest wave's blow value is 1.78 with wind speed of 0.76 m / s. so that this tool is expected to be able to monitor the condition of waves and sea waves so that the community and fishermen can be used as information media.
Distance Interactive Collaborative Training for Future Teachers

The paper discusses the questions connected with managing distance teaching and learning at the humanitarian pedagogical university. The article identifies the opportunities for interactive collaborative distant training for students – future teachers – and developing their practical skills and competences in solving usual and non-standard problems, shaping personal characteristics. The study shows the importance of providing supportive environment for learners. The paper demonstrates the main tool for the pilot study – multiple variable repetition of transitions between ‘theory-practice’, ‘practice-theory’ which was based on different forms of cognitive and pedagogical activity that provided step-by-step development of pedagogical competence of future teachers. The main focus is on the interactive forms of collaborative learning, using information-communication technologies both during intersession periods (online) and in the classroom together with the teacher (offline). The article describes the main output of the research which is resulted in the development of students’ communicative competence as well as readiness and ability for professional-research pedagogical performance, continuous professional development, development of individual teaching style, development of pedagogical thinking and mindset, self-analysis of own professional performance, information and media literacy.
Library Guides: Open Science Framework (OSF): Examples

OSF is an open source cloud-based project management platform that helps teams collaborate in one centralized location and provides file hosting, version control, persistent URLs, and DOI registration.
Clustering Technique On Students' Vocabulary Mastery

Abstract Clustering is making a visual map the students to think creativity. This research aims to determine whetherclustering technique affect students’ vocabulary mastery or not.The design used in this research was QuasiExperimental. The population in this research were all class VII Mts Al-Washliyah Tanjung Haloban 2018/2019 academic year consisting of 84 people. The research sample was taken using a saturated sample technique with the experimental method. Test was used as the instrument in this research. The test were pre-test and post-test.The mean of student learning outcomes using clustering technique is 78.36 with a standard deviation of 7.18 while those that do not use is 59.52 with a standard deviation of 14.86. from the difference of mean values from real level a is 0.05 indicates that students who get treatment clustering technique is better than those who don't get it. so that it can be seen that the use of clustering technique affect students' vocabulary mastery at Mts Al-Washliyah Tanjung Haloban Academic Year 2018/2019. Keyword :Vocabulary and Clustering technique
A SINGLE COMPOSITE METRIC TO QUANTIFY THE DATA-RICH ZONE FOR PRIMARY PREVENTION ICDS

Extrapolation of clinical trial results to individual patients is challenging because trial participants have heterogeneous baseline characteristics poorly captured by inclusion criteria alone. We previously established a Trial Score (TS) method to transform trial participants’ baseline
Subject Guides & Tutorials: ‘Free for Now’ Resources for Online Learning: Virtual Book Festival

During this crisis, vendors are stepping up to ensure that you and your kids can keep learning while at home. Explore this “Free for Now” resource list. Wyoming residents can also check out GoWYLD.net and log in with a library card.
Classification of Clothing Attributes Across Domains

Classifying clothing attributes in surveillance images can be useful in the forensic field, making it easier to, for example, find suspects based on eyewitness accounts. Deep Neural Networks are of ...
Analysis of Face Recognition Security Features and Customer Friendly Interface in Internet Banking System

The main objective of face recognition security approach is to provide the customers with a simple and friendly interface to perform the transactions by customer easily. The interface options and modules of this application will be available for the customer in their respective languages such that even a uneducated customer can login to his/her account and perform transactions and the other main feature of the project is to focus on the security issues , login credentials , hacking of the account and cracking the passwords. The main feature of this approach is reducing the security attacks on the online banking users. They can install a face recognition feature to the online banking system to avoid unauthorized persons. This reduces the issue of hacking of the accounts of customers and keeps the amount of customers safe.
Project Publizebra.se : Development of a user-centered special digital library service for self-publishing authors in Sweden

The goal of this thesis is the development of Publizebra.se, a user-centered special digital library prototype for self-publishing authors. The service is aimed to provide valuable information, fea ...
Universal Function Approximation on Graphs using Multivalued Functions.

In this work we produce a framework for constructing universal function approximators on graph isomorphism classes. Additionally, we prove how this framework comes with a collection of theoretically desirable properties and enables novel analysis. We show how this allows us to outperform state of the art on four different well known datasets in graph classification and how our method can separate classes of graphs that other graph-learning methods cannot. Our approach is inspired by persistence homology, dependency parsing for Natural Language Processing, and multivalued functions. The complexity of the underlying algorithm is O(mn) and code is publicly available.
The Impact of Supply Chain Management for The Innovation Activity Development in Russia: Relevant Issues

Abstract - Innovation activity plays a crucial role in the supply chain and socio-economic development of society, both globally and at the level of individual economic entities. Competent and, as a result, effective management of innovation activities contributes to the satisfaction of the material and intellectual needs of society, provides vital functions of society with fundamentally new benefits and leads to a positive economic effect for the economic entities at the micro, meso, and macro levels. An exploratory case study approach to answer the research questions has been conducted in order to develop a model for innovation management within a supply chain of large manufacturing firm. To study the features of the formation of the innovation activity practice and the current state of innovation activity in the Russia; to identify the causes of technological backwardness of Russia and assess the potential for the development of innovation activity to strengthen the position of the state at the global level.
SECURITY INCURSION AND CRYPTOGRAPHY QUICK FIX FOR DATA ACCUMULATED IN CLOUD STORAGE

Cloud computing dictate the IT business in Modern years. It furnishes many favors to the people who are not having adequate gauge footing for computing trade. Computational capabilities are contributed in virtualized aspects. Numerous datacenters are allotted for organizing and preserving the end users’ data. Various Data centers are established in distant terrestrial point in the world. Cloud service provider is composed and manages the data center of the cloud where users’ data are stored. Some specimens of cloud service providers are IBM, Amazon, Google applications etc. User doesn’t have any authority or immunity on their data occupied in the cloud not even knows the region of the data in the cloud. This outlook of the cloud brings many security affiliated issues on the data depot in the cloud. The huge dispute in the cloud is Security. Cloud data are outbreak by abettor or stranger in distinctive methods. This paper characterized the various descriptions of attacks on cloud data. It also states cryptography quick fix method to assure the data from different incursion. Security is approached by various criterions like validation, authorization, confidentiality and integrity.
H-BwoaSvm: A Hybrid Model for Classification and Feature Selection of Mammography Screening Behavior Data

Breast cancer is one of the most common cancer in the world. Early detection of cancers cause significantly reduce in morbidity rate and treatment costs. Mammography is a known effective diagnosis method of breast cancer. A way for mammography screening behavior identification is women's awareness evaluation for participating in mammography screening programs. Todays, intelligence systems could identify main factors on specific incident. These could help to the experts in the wide range of areas specially health scopes such as prevention, diagnosis and treatment. In this paper we use a hybrid model called H-BwoaSvm which BWOA is used for detecting effective factors on mammography screening behavior and SVM for classification. Our model is applied on a data set which collected from a segmental analytical descriptive study on 2256 women. Proposed model is operated on data set with 82.27 and 98.89 percent accuracy and select effective features on mammography screening behavior.
Wh-Less Wh-Questions in Korean and Their Implications for the Position(s) of WHY

This paper deals with the syntax of WHY in Korean. Especially, it presents novel interrogative data in Korean that have not attracted researchers??..
.AN EFFECTIVE COLLABORATIVE FILTERING FOR UNPREFERED ITEMS BY USING L- INJECTION

In recent years there has been a dramatic increase in the amount of online content. Recommender systems form a specific type of Information Filtering (IF) technique. To date a number of recommendation algorithms have been proposed, where collaborative filtering is one of the most famous and adopted recommendation technique. Collaborative filtering recommender systems recommend items by identifying other users with similar taste and use their opinions for recommendation. In the last decade, the amount of customers and online information has grown rapidly, yielding the big data analysis problem for recommender systems. Consequently, traditional recommender systems often suffer from scalability and inefficiency problems when processing or analysing such large-scale data. Due to this, the implementation of these algorithms on single node machine is time consuming and fail to meet the computing requirement of large data sets. Distributed processing of big data across multiple clusters of nodes can help to improve the performance in such cases. In this paper, the former collaborative filtering recommendation algorithm is designed to parallel on MapReduce framework and uses Pearson correlation as similarity metric. Apache Hadoop is parallel distributed framework. Hadoop distributed file system(HDFS) allows distributed processing of big data across multiple clusters of nodes.
Selfevaluation tool for learning by children in a maker space

Maker spaces are generally regarded as a valuable innovation in comparison to traditional education, although it is largely unclear what is exactly learned. This deficiency hampers the deployment of maker spaces, particularly their embedding and integration in the existing practice in formal education. In the work presented here, we explore the possibility of having learners self-report on their learning experience. For this purpose, we developed an easy-to-use visual tool for assessing learning of 21st Century Skills in children’s maker space activities, the Self-Evaluation Tool (SET). Particularly, we investigated the validation of the SET for the self-evaluation of learning activities in the maker space and how children evaluate their own performance in the various domains. The results show higher scores on learning goals in subjectification and lower scores for socialization. Future research will focus on a comparison of the different types of maker programs.
LibGuides: Access to Online Services and Collections: Resources for COVID 19: Home

This guide contains information about the University Libraries' online resources, including library services and various types of informational content the WSU community can access remotely.
Hardening Containers for Cross-Domain Applications

Cross-domain platforms control the sharing of information at multiple classification levels. For example, some cross-domain systems allow a single user to view multiple screens, at different security classification levels, on a single monitor. The core security guarantees rest on a base-of-trust in hardware established primarily through hypervisor technology. Unfortunately, over the years, hypervisors and their associated management interfaces have steadily grown in complexity, to the point where they now exceed the size of the operating system kernels they seek to protect. This has made it increasingly difficult to verify security properties in the face of kernel-level zero-day exploits and advanced persistent threats. At the same time, there has been a radical shift in computing methodology motivated by the realization that reliable deployment at scale requires an application to be associated with a specific operating system version with carefully designated libraries. This realization has resulted in an alternative computing paradigm ― containers - that wrap application attributes and execute through a shared kernel. This paper describes a novel embedded systems technology, the nano-marshal: a light-weight container system, compliant with the Open Containers Initiative (OCI), that supports cross-domain applications. The system permits container security to be hardened through innovative hardware mechanisms, hidden within Field Programmable Gate Arrays (FPGA's).
Subject guides: MicroMasters® at the University of Edinburgh: Evaluating information

An introduction to the resources available to support your learning Some guidance around how to evaluate different kinds of resources including academic or scholarly literature and information you find on the web.