Reviewerly/exHarmony huggingface dataset:
Stablecoins: risks, potential and regulation

The technologies underlying money and payment systems are evolving rapidly. Both the emergence of distributed ledger technology (DLT) and rapid advances in traditional centralised systems are moving the technological horizon of money and payments. These trends are embodied in private “stablecoins”: cryptocurrencies with values tied to fiat currencies or other assets. Stablecoins – in particular potential “global stablecoins” such as Facebook’s Libra proposal – pose a range of challenges from the standpoint of financial authorities around the world. At the same time, regulatory responses to global stablecoins should take into account the potential of other stablecoin uses, such as embedding a robust monetary instrument into digital environments, especially in the context of decentralised systems. Looking forward, in such cases, one possible option from a regulatory standpoint is to embed supervisory requirements into stablecoin systems themselves, allowing for “embedded supervision”. Yet it is an open question whether central bank digital currencies (CBDCs) and other initiatives could in fact provide more effective solutions to fulfil the functions that stablecoins are meant to address.
Ανάλυση και παρουσίαση των βασικών τεχνικών τεχνικών εξόρυξης πληροφορίας από επιχειρησιακές βάσεις δεδομένων

To be able to generate data is a need tothe collection of data is massively carried out. The data can beit's just figures and text documents in morecomplex information such as spatial data, multimedia data as welland hypertext documents. To make full use ofdata recovery is not enough, a data recovery is requiredtool for Automatic Data Summary, knowledge extraction, the essence of the stored information and the discovery of patternsin the primary data. Large data volume sizes are storedin files, databases and other repositories,. It is indeed, becomingmost important to develop a powerful tool for analysis,interpretation of these data and to extract interesting knowledgethat could help make the decisions. Uniqueanswer to all of the above is data mining.
Forming a conceptual understanding of mathematics at students of technical universities

The global challenges that humanity is facing today pose the task of higher education to prepare a specialist with fundamental training and the ability to learn throughout life. Fundamentalization of education is not possible without the formation of students' conceptual understanding of the material studied. This problem is quite relevant in the study of mathematics due to the specific nature of this science. The researchers' lack of a unified point of view in determining the essence of the conceptual understanding of mathematics does not allow practitioners to develop tools for assessing the level of conceptual understanding among university students. The purpose the article is to identify and formulate the essential characteristics and pedagogical conditions for the formation of a conceptual understanding of mathematics, as well as to explore the possibilities and effectiveness of the integration of computer modeling as an instrument of forming a conceptual understanding in the process of teaching probability theory to students of technical universities. The study showed that a computer workshop, developed based on identified pedagogical conditions and taking into account the didactic capabilities of ICT in the educational process, is an effective means of developing conceptual understanding when studying a course in probability theory. Students whose curriculum included a workshop with elements of computer modeling have a more excellent knowledge of methodologically significant knowledge and the ability to relate previously learned material to new problems.
THE SIMULATION STRUCTURE OF THE HISTORICAL AND MYTHOLOGICAL TYPES IN FANTASY MMORPG

The article deals with the reception of historical and mythological heritage in the video games of fantasy genre. The paradigms of object-oriented programming and MMORPG algorithm logic determine the structure of the content simulation. Сreating thousands of similar objects provides for top priority the provision of a single interface to entities of different types. Mythological content class upon another class, retaining similar implementation combines the principles of historical reception and programming inheritance.
MCCC Library Guides: OER's at MCCC: Resources for Faculty

Monroe County Community College Faculty Professional Development Day January 7, 2020 Contains additional materials and websites on OER.
â€œW- COMVISâ€ : Water Meter Reader Application With Image Recognition For Billing Management

AbstractWater is the basic need for living things in this world, including human being. It is the dailyneed that must be available every day, not only for the consumption but also for the otheractivity as like washing. There are so many ways to fulfill their daily need including the cleanwater such as using the water mater to get the water. By using water meter, people are ableto know the fee based on the water usage. However, practically, the water volume calculationis still using manual method. The usage water of each person is recorded in a book andreported to country treasurer. This affects the calculation into a problem for example whenthere is a damage on the book of recorded water usage. As the developing technology,therefore it is created an application to read the water meter by image recognition. The wholesystem that is made is about the scanning of number water meter based on android. However,this project will not discuss when the taken image is blur. This application is expected toimprove service optimally so that people will get easy access to their needs.
Deploying Custom Fiori Applications

Welcome to the final chapter of Custom Fiori Applications. This is an exciting chapter because everything that has been presented thus far is now going to be promoted to a different environment so that it can be used by people other than developers. Deploying an application involves more than copying files or clicking buttons to make our software move from a local workspace or development environment into a quality environment or, even better, eventually into a production environment. There is probably a set of items that need to be verified before software is deployed to upstream environments. Depending on the company’s policies, certain steps may be followed during the software development life cycle, including related steps to approve and release software. There may be certain nontechnical requirements that need to be met prior to the release of this or other web applications.
Research Guides: Welcome to Using Primo: Safari (O'Reilly) eBooks

A resource guide for students and faculty about the transition to the Primo VE discovery service.
Implementation of Pierce Similarity Distance Algorithm to Detect Harfu Jar In the Quran As a Basic Learning media Of Arabic Language Science

Arabic is a language that is rich in rules and rules in composing sentences and understanding speech. As we know, a collection of Arabic languages ​​is found in the Holy Qur'an of the Islamic Ummah. In the Al-Quran there are many jar letters that have special meanings in each letter. In Arabic language rules, In the Letters jar is a letter whose job is to give a hard line in the sentence in front of it. The purpose of this study is to build a basic Arabic learning media in detecting JAR letters using the pierce similarity method. In building the system, an image processing theory approach is carried out. The stages of the detection system process begin with the file.bmp extension process of the original image, then resizing, namely the process of placing the image to the specified coordinate points, Grayscale, convolution or edge detection and distance calculation with Pierce similarity where this algorithm will store the value of bits in the pattern of letters that are trained and then will match the values ​​in the image to be tested. Input image is the result of drawing the verses of the Quran.
Integrated approach of Random Projections and Sparse Grids for Density estimation

Sparse Grid Density Estimation faces two challenges when it is applied to extremelyhigh-dimensional and clustered data. The first is the Curse of dimensionalty which makesthe required computing power increase exponentially with the number of dimensions.Despite that Sparse Grids moderate the effect of the dimensionality it can reach a pointin which a computation is unfeasible. The second challenge is the location of some gridpoints; at the beginning of the computation the grid spreads all over the domain, includ-ing places where there is no data at all. When clustered data is used all samples are lo-cated around cluster centroids and not scattered all over the domain, this makes the phe-nomenon of placing grid points where they are not really necessary, to accentuate. Thisunwanted product adds computational cost but does not improve accuracy. Despite thatAdaptive Refinement have shown very good results, the computation will carry all theway those inefficient grid points added at the beginning.To reduce the undesired aforementioned effects a pipeline is implemented. This pipelineis divided in two parts: The first one is a Locality Sensitive Hashing algorithm that usesRandom Projections to divide the data in subsets that correspond to clusters. The secondpart applies dimensionality reduction to embed the whole data set and each cluster to asignificantly lower dimensional space and then compute density estimations using SparseGrids. For both parts two different sets of metrics are introduced to measure the efficacyof this implementation. Finally, the Conventional Approach using the whole data set is com-pared to two different methodologies to treat each individual cluster in parallel(ClusterAnalysis and Clusters Extraction).Results for a real-world data set and Synthetic one show that the Conventional Ap-proach presents better results than Cluster Analysis in most of the scenarios. However,Cluster Extraction exhibit very good results compare to those two methodologies in 60%to 80% of the proposed numerical experiments. This promising results are consistent evenin scenarios when the numerical experiments have very similar computational cost.
FAST DIFFERENTIALLY PRIVATE-SGD VIA JL PROJECTIONS

Differentially Private-SGD (DP-SGD) of Abadi et al. (2016) and its variations are the only known algorithms for private training of large scale neural networks. This algorithm requires computation of per-sample gradients norms which is extremely slow and memory intensive in practice. In this paper, we present a new framework to design differentially private optimizers called DP-SGD-JL and DP-Adam-JL. Our approach uses Johnson–Lindenstrauss (JL) projections to quickly approximate the per-sample gradient norms without exactly computing them, thus making the training time and memory requirements of our optimizers closer to that of their non-DP versions. Our algorithms achieve state-of-the-art privacy-vs-accuracy tradeoffs on MNIST and CIFAR10 datasets while being significantly faster. Unlike previous attempts to make DP-SGD faster which work only on fully-connected or convolutional layers, our algorithms work for any network in a black-box manner which is the main contribution of this paper. To illustrate this, on IMDb dataset, we train a Recurrent Neural Network (RNN) to achieve good privacy-vs-accuracy tradeoff, whereas existing DP optimizers are either inefficient or inapplicable. On RNNs, our algorithms are orders of magnitude faster than DP-SGD for large batch sizes. The privacy analysis of our algorithms is more involved than DP-SGD, we use the recently proposed f-DP framework of Dong et al. (2019). In summary, we design new differentially private training algorithms which are fast, achieve state-of-the-art privacy-vs-accuracy tradeoffs and generalize to all network architectures.
Log Anomaly Mining System based on Machine Learning

With the development of information technology, a large amount of log data is generated in the background of various information systems and equipment. There are different types of abnormal and fault information. The traditional detection methods usually rely on manual statistical discovery, or match by regular expression. An abnormal anomaly system based on artificial intelligence is constructed here, through the extraction of log templates, log clustering and log classification technology, to find abnormal events and fault information in the information system in time to avoid abnormal development and deterioration, reduce troubleshooting time and business interruption time to ensure the healthy operation of the system. The system has been actually tested and compared with the traditional log anomaly detection system. The results show that the depth of log analysis, the accuracy of event recognition, and the efficiency have been improved.
Deep Reinforcement Learning with Temporal-Awareness Network

Advances in deep reinforcement learning have allowed autonomous agents to perform well on video games, often outperforming humans, using only raw pixels to make their decisions. However, timely context awareness is not fully integrated. In this paper, we extend Deep Q-network (DQN) with spatio-temporal architecture - a novel framework that handles the temporal limitation problem. To incorporate spatio-temporal information, we construct variants of architectures by feeding spatial and temporal representations into Deep Q-networks in different ways, which are DQN with convolutional neural network (DQN-Conv), DQN with LSTM recurrent neural network (DQN-LSTM), DQN with 3D convolutional neural network (DQN-3DConv), and DQN with spatial and temporal fusion (DQN-Fusion), to explore the mutual but also fuzzy relationship between them. Extensive experiments are conducted on popular mobile game Flappy Bird and our framework achieves superior results when compared to baseline models.
Research Guides: Contactless Curbside Pickup @ the Van Houten Library: Curbside Pickup

The Van Houten Library will provide curbside pickup of books or media materials for current students, faculty, and staff.
Analisis Kemampuan Berbahasa Siswa Segugus Lebakharjo Kecamatan Ampelgading

The function of language is to communicate. To be able to communicate well, there are four language skills that must be mastered, namely the ability to listen, speak, read and write. The fourth ability is a unit that supports each other in communication. In order for a student to communicate smoothly, the four language skills must be trained to students. This study aims to find out how the language ability of students in the Lebakharjo cluster of Ampelgading District and what factors affect the students 'language abilities, so that schools and parents can work together to improve students' language abilities. This research uses qualitative research with descriptive research type. The subjects of this study were the fifth grade teachers and fifth grade students of SDN in the Lebakharjo cluster. The instruments used to collect data were observation sheets, interview guidelines, and documentation. The data analysis technique used was qualitative data analysis which was tested by triangulation. The results of this study indicate that the highest language ability is SDN 02 Lebakharjo with an average of 78% the Good category (B) and the lowest language ability is SDN 05 Lebakharjo with an average of 67% the Fair category (C). The main factor influencing students' language skills is the environmental factors in which students live.
Dynamic multi-agent path finding based on conflict resolution using answer set programming

We study a dynamic version of multi-agent path finding problem (called D-MAPF) where existing agents may leave and new agents may join the team at different times. We introduce a new method to solve D-MAPF based on conflict-resolution. The idea is, when a set of new agents joins the team and there are conflicts, instead of replanning for the whole team, to replan only for a minimal subset of agents whose plans conflict with each other. We utilize answer set programming as part of our method for planning, replanning and identifying minimal set of conflicts.
Handling Imbalanced Data Classification With Variational Autoencoding And Random Under-Sampling Boosting

In this thesis, a comparison of three different pre-processing methods for imbalanced classification data, is conducted. Variational Autoencoder, Random Under-Sampling Boosting and a hybrid approac ...
Damaging Similarities in Highly Skilled Signature Simulations - Their Detection and Authorship

Questioned document examination is a highly specialized and challenging field of study, because of the variety and complexity of problems that are referred to document examiners. Detection and identification of practiced simulated forgeries is an area of forensic science which requires the professional skill, capability and acumen of an examiner, every time he (or she) is called upon to examine and report a case of this nature. This is because firstly, the practiced simulations bear a striking semblance to the copied model and usually contains the handwriting features of the writers, the real person as well as the forger, though in varying degrees.Secondly, the skilled forger rarely leaves his own imprint in the forgery he committed. Most authorities on the subject have advised that the identification of authorship, in such cases, may be considered as an exception rather than the rule. Besides discussing and reviewing the work done in this regard, the authors have also presented and illustrated an intricate case study where the authorship of simulated signatures could be associated with the known handwriting of the suspected forger
WebGIS sebagai media diseminasi kemas ulang informasi

Introduction. Not all scientific work can be easily utilized directly by the public (society). Pusat Data dan Dokumentasi Informasi Ilmiah (PDDI) has not optimally disseminated knowledge products. The knowledge products should be assembled, visualized and informed - through digital media. This paper aims to examine whether WebGIS can be used as a medium for disseminating information.&#x0D; Data Collection Method. The method used was descriptive qualitative. Data collection was conducted by means of a survey.&#x0D; Data Analysis. This research use descriptive analysis. The results of the survey analysis were reviewed with the results of literature studies so that conclusions could be drawn to answer the research questions.&#x0D; Results and Discussions. The survey shows that the Banyuwangi community expect that an interactive industrial tree to be attached in the WebGIS (BAGEOS) of the Banyuwangi Regency Government. The survey shows that installing industrial trees on BAGEOS is not only beneficial for BAGEOS, but also for the community.&#x0D; Conclusions. Combination between industrial trees with WebGIS or digital maps is a good combination. All respondents agreed to pair industrial trees on digital maps. GIS is capable as a medium for disseminating information packaging.
ECOSISTEMA TECNOLÓGICO: COMO HERRAMIENTA TRANSFORMADORA PARA EL PROCESO DE APRENDIZAJE

The technological ecosystem that currently impacts society leaves a great vestige in the educational field, and therefore generates an enigma for the need for teachers to integrate the use of technology in the pedagogical process to support the traditional educational model. To address this phenomenon, a mixed methodology research (quantitative - survey - qualitative - interview -) will be structured, applied to students and teachers of the Teaching 2.0 technology-educational platform, from which an experimental exercise of communicative action was approached, on the use of technology in the classroom, as well as the interpretation of this use by the actors involved in the training process. The corpus of analysis admits to evidence that in the traditional educational model the technological becomes a sustenance, tool, educational complement, in order to achieve, the significant teaching-learning process. The e-learning and blended educational model is approached as a model of technological pedagogy
Research on Indexing Mechanism for Massive Distributed Data Fragment Storage

Currently, massive distributed storage systems store a large number of interrelated heterogeneous data, but lack of a perfect indexing mechanism to solve the query problem of massive heterogeneous data. Therefore, this paper proposes an index model based on the combination of associative index and auxiliary index. The model uses the description of the common entity between structured data and unstructured data to establish a relationship, and creates an index as a keyword to establish an associated index layer. At the same time, a secondary index layer is established at each node to create an R tree index for the structured data, and an entity-based inverted index is created for the unstructured free document, thereby improving the query efficiency and accuracy. Experimental results show that the indexing system can not only effectively support mixed queries of heterogeneous data, but also improve the accuracy of query results.
Smart technology for ageing in place: Machine learning for continuous sensor monitoring of the functional health of independently living older adults

This thesis describes research on the use of sensor monitoring to detect changes in the functional health of older adults living alone. Functional health refers to the capability to perform activities that a person needs and wants to do without being limited by pain or injury. The ability to perform these activities is crucial for older adults living independently, because the process of ageing involves many unavoidable changes (usually a decline) related to mental and physical health. Early detection of a decline of functional health status allows for timely intervention, which may contribute to healthy and active ageing in the home environment.
Bitcoin Trading in Australian and Canadian Dollars, the Pound and Euro: Pre- and Post-COVID-19

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL Copy DOI
Relationship Recognition and Processing of Descriptive Complex Sentences in Chinese English Machine Translation

As a higher level of language unit, complex sentence plays an important role in the practical application of language, and its frequency is always high. However, compared with single sentences, complex sentences are more complex in structure and logic semantics, so students often make a variety of grammatical errors when learning complex sentences. Especially when Chinese students are learning English and foreign students are learning Chinese, it is inevitable that they will make grammatical mistakes at the level of complex sentences. This paper takes the comparative study of Chinese and English complex sentence Association markers as the breakthrough point, and makes a systematic and detailed contrastive analysis of the similarities and differences of the types and patterns of the association markers in Chinese and English complex sentences, and concludes the similarities and differences in the level of complex sentences between Chinese and English. The experimental results show that this method can improve the efficiency and accuracy of the relationship recognition and processing of complex sentences. This method has a certain reference value for the relationship recognition and processing of descriptive complex sentences in Chinese-English machine translation.
State investigates possible $5.97M in erroneous unemployment payments

The Department of Workforce Development (DWD) has identified 7,843 unemployment insurance claims it suspects were filed fraudulently due to identity theft.
Deploy Containers with Cloud Run

In this chapter, we will learn how to deploy containerized applications to Google Cloud using Cloud Run. We will also take a deep dive into the following topics: