Reviewerly/exHarmony huggingface dataset:
Causality Relationship between Spot and Futures Bitcoin Prices in CME

To protect against risks arising from fluctuations in spot prices and better manage risk, investors might evaluate futures markets. The role of price discovery in the futures markets and the possibility of reducing certain risks increase the importance of researching the relationship between spot and futures prices. This study aims to determine whether there is a relationship between the Bitcoin spot prices and the Bitcoin futures prices. To this end, the relationship between the two markets is analyzed using Johansen Cointegration analysis and Vector Error Correction Model (VECM) using the daily data of the period 02.23.2017 – 08.31.2021. Unit root tests show that each series are not stationary at the level values and that the first differences of the series are stationary. The results of the cointegration analysis show that there is a long-term equilibrium relationship between the bitcoin spot market and the bitcoin futures market, and it is a single cointegration vector. The Granger causality test based on the vector error correction model was used to determine the causality relationship between the series. It has been determined that there is a unidirectional causality relationship from the Bitcoin spot market to the Bitcoin futures market. Bitcoin is a new financial tool that attracts the attention of investors. Investors make transactions on Bitcoin for speculative purposes. Therefore, unlike other investment instruments, spot prices in the bitcoin market affect futures prices.
Exploring Learning Management System of the Smartphone Application Based e-Learning in Covid-19 Era: Developing Innovation to Investigate the Metacognitive Approach for Students of AIK Lesson

Exploring Learning Management System of the Smartphone Application Based e-Learning for learners’ approach about metacognitive approaches contact on effectiveness, and the association between metacognitive approach and effectiveness on their developing Innovation to Investigate the metacogntive Approach for Students of Al-Islam and Kemuhammadiyahan (AIK) lesson. To examine the effects of approach instruction on students’ reading performance, a qualitative interview technique and quantitative research methods including a paired-sample t-test and Person Product Moment Correlation will use to estimate the relationship between metacognitive approaches and effectiveness on students’ reading accomplishment of Al-Islam and Kemuhammadiyahan (AIK) lesson. Significance showed that the most frequent use of metacognitive approachwas found to be the metacognitive approach, followed by the cognitive approach. Learning strategies and on language learning documents of Al-Islam and Kemuhammadiyahan (AIK) lesson that are self-directed at continuing recognition of the need to help language learners reflect and improve their beliefs and knowledge about learning metacognitive knowledge explicitly about the function of knowledge in language learning of Al-Islam and Kemuhammadiyahan (AIK) lesson. This article reviews the theoretical literature and research on metacognition to enhance the understanding of approaches to second language acquisition that establish active roles for students, and conclude with consideration of the practical implications for teaching foreign languages and second languages. In addition, there is a significant positive connection between metacognitive approachand effectiveness on their Smartphone application. Reading approach, on the other hand, was unrelated to reading achievement.
EFEKTIVITAS LAYANAN FOTOKOPI SEBAGAI PENGGANTI PEMINJAMAN KOLEKSI BAGI PEMUSTAKA LUAR UPT PERPUSTAKAAN UNTAN

Abstract The main problem in this final task is that there are still outside leaders who do not know not allowed to borrow collections but can only photocopy and read on the spot. The purpose of this study is to find out the effectiveness of photocopying services as a substitute for collectible lending for UPT Untan library. The type of research used is descriptive research with a quantitative approach. The respondents numbered 17 people from various students of Universities / Institutes / Higher Schools in Pontianak and some even came from universities outside West Kalimantan. The data was collected using a questionnaire in the form of a Google Document link distributed through WhatsApp. Based on the results of data analysis using SPSS version 18 showed that the results of the questionnaire validity test were declared valid because it exceeded the signification level r calculated greater than the r table and with reliability test results declared reliable because 0.905 &gt; 0.60. While the results of the calculation of the effectiveness of the service using the percentage of interpretation of the score based on intervals obtained the number 72.5% which means effective. Keywords : Effectiveness, Photocopying Services, Outside Library
Методична компетентність майбутнього учителя початкових класів: нормативно-правовий аспект

International scientific conference «Innovative projects and programs on psychology, pedagogy and education» : conference proceedings, December 10–11, 2021. Riga, Latvia : “Baltija Publishing”, 2021. 212 pages.
The Correlation Between Students’ Metacognitive Awareness and Reading Comprehension

&lt;p class="abstrak" align="center"&gt;&lt;strong&gt;&lt;em&gt;Abstrak &lt;/em&gt;&lt;/strong&gt;&lt;em&gt;&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;Penelitian&lt;/em&gt;&lt;em&gt; ini &lt;/em&gt;&lt;em&gt;ditujukan&lt;/em&gt;&lt;em&gt; untuk mengidentifikasi hubungan antara kesadaran metakognitif dan pemahaman membaca siswa kelas II SMK Negeri 2 Bukittinggi (SMK Negeri 2 Bukittinggi, Sumatera Barat, Indonesia). Desain penelitian ini adalah penelitian korelasional. Populasi penelitian ini adalah seluruh siswa kelas II SMK Negeri 2 Bukittinggi yang berjumlah 544 siswa dan sampel penelitian ini adalah 109 siswa yang dipilih secara acak dari 20% populasi. Hasil penelitian menemukan bahwa ada hubungan antara kesadaran metakognitif dan pemahaman membaca siswa kelas II SMK Negeri 2 Bukittinggi. Koefisien korelasi (rxy) sebesar 0,285 yang berarti korelasi rendah. Jika dibandingkan antara rxy dan rtabel didapatkan bahwa 0,285 &amp;gt; 0,05 yang berarti Ha diterima dan Ho ditolak. Disimpulkan bahwa kesadaran metakognitif memiliki korelasi positif terhadap pemahaman membaca siswa. Dengan demikian, jika siswa memiliki kesadaran metakognitif, pemahaman membaca mereka akan meningkat.&lt;/em&gt;&lt;em&gt;&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Kata Kunci:&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; Korelasi, Kesadaran Metakognitif, Pemahaman Membaca.&lt;/em&gt;&lt;/p&gt;&lt;p class="abstrak" align="center"&gt;&lt;strong&gt;Abstract&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;This research is aimed to identify correlation between students’ metacognitive awareness and reading comprehension of the second grade of SMK Negeri 2 Bukittinggi (State Vocational School 2 of Bukittinggi, West Sumatera, Indonesia). The design of this research was correlational research. The research population was all students at the second grade of SMK Negeri 2 Bukittinggi encompassing 544 students and the samples were 109 students who were selected randomly from 20% of the population. The research found that there was a correlation between students’ metacognitive awareness and reading comprehension at the second grade of SMK Negeri 2 Bukittinggi. The correlation coefficient (r&lt;sub&gt;xy&lt;/sub&gt;) is 0,285 which means as low correlation. If it is compared between r&lt;sub&gt;xy&lt;/sub&gt; and r&lt;sub&gt;table&lt;/sub&gt;, it was found that 0,285 &amp;gt; 0,05 which meant that Ha was accepted and Ho was rejected. It was concluded that metacognitive awareness had a positive correlation to students’ reading comprehension. Thus, if the students have metacognitive awareness, their reading comprehension will increase.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords:&lt;/strong&gt; Correlation, Metacognitve Awareness, Reading Comprehension&lt;/p&gt;
Abstract

Public science is critical to the economy and to society.However, much of the beneficial impact of scientific research only occurs when scientific knowledge is disseminated broadly and is used by others.This book examines the emerging policy, law and practice of facilitating open access to scientific research data.One particular focus is to examine the open data policies recently introduced by research funders and publishers, and the potential in these for driving the practice of open scientific data into the future.This study identifies five major stumbling blocks to sustainable open scientific data.Firstly, it is the prevailing mindset that facilitating open access to data is analogous to facilitating open access to publications and, therefore, research data can easily be shared, with research funders and librarians effectively leading the process.Secondly, it is the unclear meaning of the term data which causes confusion among stakeholders.Thirdly, it is the misunderstood incentives for data sharing and the additional inputs required from researchers.Fourthly, data privacy-an issue that only applies to selected research datasets, and yet appears to dominate the discussion about open research data.Finally, there is a copyright law, which poses challenges at different stages of data release and reuse.In this book, it is argued that the above problems can be addressed using a staged model for open scientific data.I draw specifically on the practice with open scientific data at CERN (the European Organization for Nuclear Research) and the practice of sharing clinical trial data to argue that open data can be shared at various stages of processing and diversification.This model is supplemented by recommendations proposing changes to existing open data mandates and the introduction of a text and data mining exemption into Australian copyright law.
Conceptual Framework for the Specialized Education System Implementation for Children in the Kaliningrad region

The article discusses the relevance of the introduction of innovative forms of specialized education for children; it is proposed to get acquainted with the experience of implementing such a project on the basis of the IKBFU.The tasks of the educational project "Star of the Future" are revealed -the integration of general and additional education and future employers in order to expand the possibilities of vocational guidance training for children studying in specialized classes, mastering specialized subjects in various educational forms (modular training, project and online training, work in university laboratories , professional tests at enterprises and organizations), creating conditions for the formation of a child's image of a future profession and its conscious choice.The cluster approach to project implementation is substantiated as a direction in science and practice associated with the search and implementation of new opportunities for the development of society, increasing its welfare and competitiveness through the creation and management of clusters.The features of the project are listed: integration of basic (school part) and additional (university part) education; formation of universal competences, Digital and soft-competencies (including critical thinking, teamwork, communication and others); entrepreneurship training, formation of understanding of the "image of the future and professions of the future"; Deferred contract and targeted training; support and training of teachers who, in partnership with university teachers, implement programs.The quantitative and qualitative results of the project are proposed, the analysis of the effectiveness of the training is carried out for the assessment of which Donald Kirkpatrick`s four-level model was used.A conclusion is made about the success of the project and further ways of its development are discussed.
Behavioural Study of Constrained Convolutional Neural Network on Image Splicing Classification of Various Datasets

The Internet nowadays is exploded with digital images. However, it also has more forged images floating around and threatening the digital asset trustworthy, especially spliced images. Although there are many computational ways of detecting image splicing, the image splicing technique is advancing over time, driving feature specific algorithms to obsolete. Thus, more researchers nowadays are focusing on data-driven feature extraction. Convolutional Neural Network (CNN) is a Deep Learning algorithm well known for object detection, but it is ill-suited for manipulation feature extraction. In this research, a constrained convolution algorithm is to be injected into a simple CNN to study its performance in image splicing detection in a wide range of datasets. A strategic parameter tweaking can fit a wide range of spliced image datasets, but it is always biased to its train dataset. A cross-database splicing classification shows that it is ill-suited for generalizing a wide range of dataset evaluation.
Quantum private broadcasting

In private broadcasting, a single plaintext is broadcast to multiple recipients in an encrypted form, such that each recipient can decrypt locally. When the message is classical, a straightforward solution is to encrypt the plaintext with a single key shared among all parties, and to send to each recipient a copy of the ciphertext. Surprisingly, the analogous method is insufficient in the case where the message is quantum [i.e., in quantum private broadcasting (QPB)]. In this work, we give three solutions to $t$-recipient quantum private broadcasting ($t$-QPB) and compare them in terms of key lengths. The first method is the independent encryption with the quantum one-time pad, which requires a key linear in the number of recipients, $t$. We show that the key length can be decreased to be logarithmic in $t$ by using unitary $t$-designs. Our main contribution is to show that this can be improved to a key length that is logarithmic in the dimension of the symmetric subspace, using a concept that we define of symmetric unitary $t$-designs, which may be of independent interest.
Structural and Functional Model Development of the Culture of Intellectual Work Among Future Specialists

The relevance of the problem under study is due to the need for monitoring diagnostics to determine the level of intellectual work culture of the future specialist and the need for a structural and functional model of its development as a fundamental basis of training.This article pursues a goal that is aimed at revealing the essence of this model and includes blocks that define its functions.The design of this model is based on the human-anthropological approach and its approbation.The leading method of studying this problem is modeling, which allows revealing the integral systemdeveloping components of the culture of intellectual work.The article presents a structural and functional model of the development of the culture of intellectual work of the future specialist, consisting of logically interrelated blocks aimed at transforming the culture of intellectual work of the future specialist.
Характеристика мовленнєвого розвитку дітей з сенсорною алалією

International scientific conference «Innovative projects and programs on psychology, pedagogy and education» : conference proceedings, December 10–11, 2021. Riga, Latvia : “Baltija Publishing”, 2021. 212 pages.
A Proposal for Detecting Fraud in Drinking Water Consumption through Artificial Neural Networks

Water is an essential resource in any society, and it has become scarce according to the seasons. Therefore, an efficient administration is increasingly necessary. Drinking water management companies often have consumption losses due to fraudulent consumption by a group of users. Currently these frauds are detected through physical inspections, however it is possible that a user can avoid this detection. On the other hand, multiple studies show that the data contains common patterns in fraud cases. This work proposes the use of a neural network model capable of recommending, based on historical data, drinking water consumption services with a greater possibility of committing fraud within the commune of Lautaro, Chile. Our proposal considers reducing the operating costs associated with on-site inspections, increasing the probability of finding an infraction at the time of execution. By reducing the work associated with fraud analysis, we plan to optimize the man- hours of the process analysts. The evaluation of the predictive model indicates that the proposed model achieves a reduction of more than 60% of cases in relation to previous recent periods considering similar levels of fraud detection, which implies a reduction in operating costs. As future work, the use of recurrent neural networks will be explored, as well as the use of more user variables, in addition to the consumption history.
Freedom of expression as self-restraint

In my recent book Freedom of Expression as Self-Restraint, I expound and defend the moral principle of freedom of expression. This article recounts a few of the main strands of the exposition in that book, and it touches upon the justification for the principle of freedom of expression. Supplementing the abstract ideas broached in the article are several illustrative examples that render the abstractions more accessible.
Collaborative Filtering with Attribution Alignment for Review-based  Non-overlapped Cross Domain Recommendation

Cross-Domain Recommendation (CDR) has been popularly studied to utilize different domain knowledge to solve the data sparsity and cold-start problem in recommender systems. In this paper, we focus on the Review-based Non-overlapped Recommendation (RNCDR) problem. The problem is commonly-existed and challenging due to two main aspects, i.e, there are only positive user-item ratings on the target domain and there is no overlapped user across different domains. Most previous CDR approaches cannot solve the RNCDR problem well, since (1) they cannot effectively combine review with other information (e.g., ID or ratings) to obtain expressive user or item embedding, (2) they cannot reduce the domain discrepancy on users and items. To fill this gap, we propose Collaborative Filtering with Attribution Alignment model (CFAA), a cross-domain recommendation framework for the RNCDR problem. CFAA includes two main modules, i.e., rating prediction module and embedding attribution alignment module. The former aims to jointly mine review, one-hot ID, and multi-hot historical ratings to generate expressive user and item embeddings. The later includes vertical attribution alignment and horizontal attribution alignment, tending to reduce the discrepancy based on multiple perspectives. Our empirical study on Douban and Amazon datasets demonstrates that CFAA significantly outperforms the state-of-the-art models under the RNCDR setting.
Optimization on Large Interconnected Graphs and Networks Using Adiabatic  Quantum Computation

In this paper, we demonstrate that it is possible to create an adiabatic quantum computing algorithm that solves the shortest path between any two vertices on an undirected graph with at most 3V qubits, where V is the number of vertices of the graph. We do so without relying on any classical algorithms, aside from creating a (V x V) adjacency matrix. The objective of this paper is to demonstrate the fact that it is possible to model large graphs on an adiabatic quantum computer using the maximum number of qubits available and random graph generators such as the Barabasi-Albert and the Erdos-Renyi methods which can scale based on a power law.
Virtual Consolidation of Resource Sharing in Green Cloud using an Efficient Meta Scheduling Algorithm

In modern researchers, cloud parallel data processing has emerging resource that to be one of the problematic application for Infrastructure-as-a-Service (IaaS)clouds. Major Cloud processing companies include starting incorporate frameworks using VM models for parallel data processing in their resource portfolio creation too easy for a client to access these services and to set out their programs. The growing computing requires from multiple requests on the main server has led to excessive power utilization. The waiting resource in the long-term sustainability of Cloud like infrastructures in provisions of energy cost but also from cloud environmental perspective. The trouble can be addressed to require with high energy consumption resource sharing infrastructures, but in the process of resources are dynamically switch to new infrastructure. Switching is not enough to cost efficient and also need time sharing green consuming. Cloud being consists of several virtual centers like VM's under the different administrative domain, make a problem more difficult. Thus, for the reduction in energy consumption, this propose address the challenge by effectively distributing compute-intensive parallel applications on the cloud. To propose a Meta-scheduling algorithm, this exploits the heterogeneous nature of Cloud to achieve the reduction in energy consumption as the green cloud. This intent addresses these challenges by proposing a virtual file system specifically optimized for virtual machine image storage. It is based on a lazy transfer scheme coupled with object versioning that handles snapshot transparently in a hypervisor independent fashion, ensuring high portability for different configurations.
DroneBox - A Fully Automated UAV System for Surveillance and Inspection Application

Abstract Recently, an unmanned aerial vehicle or UAV technology has become more robust and reliable to serve industrial applications including site patronage, monitoring and surveillance missions. However, the operational growth is retarded by the slow development of experienced UAV pilots and operators, which makes the routine UAV missions costly and not feasible. The "DroneBox" is a fully automated, completely independent drone solution, where it will serve as the drone storage and self-maintenance base, for a surveillance operation without any human assistant. With our technology, the drone will be able to take off, perform missions, land precisely and recharge automatically while using accumulated real-time information to operate with the safest configuration. Implementation of the DroneBox system offshore will reduce the risk, cost and time of surveillance operation compared to the conventional method used in the industry. The predetermined events can be identified ahead of time, risks can be assessed earlier, and hazards can be prevented. Normally, scheduled offshore surveillance is done by assigning inspectors to investigate anomalies on offshore plants via crew boat vessels. These costly procedures can be replaced by the proposed solution, the innovative "DroneBox". Based on the feasibility study on PTTEP maintenance cost related to offshores surveillance, "DroneBox" could save up to 1.82 million USD annually from transportation expenses calculated from the operation on 30 different platforms in Artit (ART) and Great Bongkot North (GBN) wellhead platforms. Our developed technology is the transition towards the new era of autonomous surveillance in oil and gas industry.
Securing the Next Generation

Weak authentication practices that rely on passwords for security have led to widespread data breaches and successful phishing attacks. Recent advances in the cost and usability of hardware security tokens have made the prospect of effectively augmenting password-based authentication or removing it altogether a possibility. To actualize this, a paradigm change in how people learn to authenticate accounts on-line must occur. Towards this end, we describe a curriculum to teach high-school students the perils of passwords and a program to distribute hardware security tokens to them as they are first setting up their on-line presence in order to improve the security of the next generation.