Reviewerly/exHarmony huggingface dataset:
4-D Model : Teaching Materials To Reading Comprehension With DRTA Strategy For Elementary School Students

Reading is a skill that must be mastered by elementary school students because it can increase a person's reasoning for that a teacher must be a bridge in transferring knowledge by using teaching materials with DRTA strategies. Research method 4-D development with 4 stages define, design, develop, and disseminate. Teaching materials that have been validated by experts and practitioners with validation results of content eligibility with an average of 88.3 are very valid, linguistic aspects with an average of 91.6 are very valid, presentation aspects with an average of 90 are very valid, and aspe graphic of 87.5 is very valid.. After the validated teaching materials were tested in the class using a quasi-experimental method to obtain an increase in experimental class reading comprehension 18.75% higher than the increase in the control class with a 12.5% increase in class. To test whether there is a significant difference in the gain value tested by using normality and homogeneity tests, after the results are obtained, it is re-tested using the average difference test with the results of t_counts = 0.26 and t_table= 2.00 so that it can be concluded that the ability to read comprehension does not exist significant difference.
Research Questions on Silica Melting Based on Image Analysis

This paper makes a perfect and reasonable explanation and solution to the highly researchable problems under the melting of silica, and uses the methods of image matching, moving state target tracking, gray and binary methods to construct multiple linear regression. Equations, feature image matching models, background difference models, etc., are comprehensively solved using software such as MATLAB, and it is found that the silica particle coordinates and particle motion trajectories, generalized radius and area can represent changes in the silica melting process the conclusion of the melting rate of silicon oxide is finally combined with the model to verify the reliability of the conclusion.
A Serverless Cloud-Fog Platform for DNN-Based Video Analytics with Incremental Learning

DNN-based video analytics have empowered many new applications (e.g., automated retail). Meanwhile, the proliferation of fog devices provides developers with more design options to improve performance and save cost. To the best of our knowledge, this paper presents the first serverless system that takes full advantage of the client-fog-cloud synergy to better serve the DNN-based video analytics. Specifically, the system aims to achieve two goals: 1) Provide the optimal analytics results under the constraints of lower bandwidth usage and shorter round-trip time (RTT) by judiciously managing the computational and bandwidth resources deployed in the client, fog, and cloud environment. 2) Free developers from tedious administration and operation tasks, including DNN deployment, cloud and fog's resource management. To this end, we implement a holistic cloud-fog system referred to as VPaaS (Video-Platform-as-a-Service). VPaaS adopts serverless computing to enable developers to build a video analytics pipeline by simply programming a set of functions (e.g., model inference), which are then orchestrated to process videos through carefully designed modules. To save bandwidth and reduce RTT, VPaaS provides a new video streaming protocol that only sends low-quality video to the cloud. The state-of-the-art (SOTA) DNNs deployed at the cloud can identify regions of video frames that need further processing at the fog ends. At the fog ends, misidentified labels in these regions can be corrected using a light-weight DNN model. To address the data drift issues, we incorporate limited human feedback into the system to verify the results and adopt incremental learning to improve our system continuously. The evaluation demonstrates that VPaaS is superior to several SOTA systems: it maintains high accuracy while reducing bandwidth usage by up to 21%, RTT by up to 62.5%, and cloud monetary cost by up to 50%.
Dark energy as the information field of the universe

Abstract Using modern theories of the origin and expansion of the Universe, recent discoveries in astronomy and quantum physics, the article proposes the hypothesis to add to attributes of the nascent universe such as “space” and “time” of the attribute “information,” which finds its embodiment from a physical point of view in the form dark energy. With the development of the Universe, the volume of information grows and, accordingly, the mass of dark energy increases, turning into an information field or noosphere, which provides for the expansion of the Universe. An analogy is made between the Big Bang and the expansion of the Universe in the process of its evolution, due to the increase in the amount of dark energy and between the birth of Man from singularity (egg) and the growth of his information and knowledge in the process of his life.
Central bank digital currencies: experience of pilot projects and conclusions for the NBU

An overview of the definitions of central bank digital currency (CBDC), formulated by researchers of the International Monetary Fund (IMF), the Bank for International Settlements (BIS), the Bank of England, is presented, and the essence of the CBDC is revealed. It is stated that the existing electronic money is a digital form of obligations of financial intermediaries, and CBDC is a form of emission and obligations of central banks. The types and forms of CBDC are generalized, namely: retail or wholesale, account-based or token-based ones. The structure and functionality of the register, payment authentication, access to infrastructure, and governance are defined as factors taken into account during CBDC designing. Similar models of launching national CBDC by the Bank of England (economy-wide access or financial institutions access, and financial institutions plus CBDC backed narrow bank access) and BIS (direct, indirect, hybrid) are under consideration. The synthetic CBDCs are marked as a theoretical concept of CBDC. The overview of projects of the People's Bank of China – "e-renminbi", the Central Bank of the Uruguay – "e-peso", the Central Bank of the Bahamas – "sand dollar" and the Eastern Caribbean Central Bank affirm the interest of developing countries in launching national retail CBDCs. It was found that apart from the Riksbank with the successful "e-krona" project, most of the monetary authorities of developed countries (BIS, Bank of Japan, Bank of Canada, Deutsche Bank, FRS) are just planning or starting to experiment with the issuance of digital securities, which demonstrates their concern about the restructuring of the banking system and the changes of global role of traditional currencies. Among the positive consequences of the introduction of CBDC for the domestic banking system are the emergence of an alternative payment instrument, the implementation of effective monetary policy through increased influence on interest rates, and regulation of the legal regime of crypto currencies. At the same time, the introduction of CBDC involves certain changes in financial intermediation (replacement of the deposits of commercial banks with the CBDC, the performance of functions inherent to commercial banks by the central bank or fintech companies), and will require powerful technical capabilities, including those related to protection from cyber risks. The results of the study point to the need for a cautious approach to the implementation of the Ukrainian CBDC only after the NBU assesses the public demand for new forms of money and the impact of the launch of CBDC models on price and financial stability, and compares available payment technologies that can achieve the same goals as the CBDC.
Future of the OPAC: Integrating the OPAC with Emerging Discovery Tools

This presentation will explore how the library catalogue, a tool with a long and distinguished history, is changing with the advent of the Internet. We, as library practitioners, know the power of the catalog to find information sources in library collections. But our users, who have become used to having some results regardless of what search terms they enter into Web search engines, are becoming increasingly frustrated with the current OPAC technologies. What are some of limitations of online library catalogues and in what ways are members of the information community and library automation vendors discovering ways of making local resources more available to our users? Information will be presented about recent studies of user behaviour as well as some commercial solutions to the problem of user/catalog interface.
Research on the Collaborative Diagnosis of Automobile Maintenance and Repair based on an Improved SimHash Algorithm

This paper proposes an improved SimHash algorithm for automobile maintenance and repair diagnosis for overcoming the challenges of collaborative automobile diagnosis, i.e. lack of characteristic information, highly synonymous, low-matching accuracy, etc. First, the merging of synonymous terms in short texts was applied in order to solve the low-matching accuracy problem of highly-related cases using a traditional matching method due to a lack of information about a sentence and ignoring the synonyms. Second, consideration of the relative position between terms was made, while it was ignored in traditional TF-IDF algorithm which only takes word frequency into consideration. Finally, the synonymous terms and the relative positions between terms were implemented in the SimHash algorithm, and query results were sorted via the BM25 algorithm. The proposed method's effectiveness was verified via comparison with the traditional algorithm based on vehicle maintenance case studies. Results show that the improved algorithm has significantly higher accuracy than the traditional algorithm.
Digital Audio Workstation in Music Self-Learning

The rapid development of information and communication technology has had a strong impact on the process of learning music.One impact that can be seen is that the teacher is no longer seen as the only source of information, but he is a guide for his students to access and manage their learning process.This article discusses how students of the Department of Music Education, Universitas Pendidikan Indonesia undertook the process of developing creativity and musical skills.Creativity and skills are two lovebirds that cannot be separated in musical activities.Through an approach to the activity of making music rearrangements, it can be seen that digital audio workstations (DAW), as artificial intelligence and machine learning, have motivated students and teachers in building the stages of music self-learning.By using a research-based design method, these stages consist of the problem analysis stage, the development of a problem-solving design based on relevant theories, the product evaluation and trial phase, and the reflection and documentation stage.The work steps in each stage are carried out collaboratively between researchers and students as practitioners which are based on objectives, optimization, and process efficiency.The data obtained from observations, interviews, and literature review which is then described qualitatively.
Causal Collaborative Filtering

Many of the traditional recommendation algorithms are designed based on the fundamental idea of mining or learning correlative patterns from data to estimate the user-item correlative preference. However, pure correlative learning may lead to Simpson's paradox in predictions, and thus results in sacrificed recommendation performance. Simpson's paradox is a well-known statistical phenomenon, which causes confusions in statistical conclusions and ignoring the paradox may result in inaccurate decisions. Fortunately, causal and counterfactual modeling can help us to think outside of the observational data for user modeling and personalization so as to tackle such issues. In this paper, we propose Causal Collaborative Filtering (CCF) --- a general framework for modeling causality in collaborative filtering and recommendation. We provide a unified causal view of CF and mathematically show that many of the traditional CF algorithms are actually special cases of CCF under simplified causal graphs. We then propose a conditional intervention approach for do-operations so that we can estimate the user-item causal preference based on the observational data. Finally, we further propose a general counterfactual constrained learning framework for estimating the user-item preferences. Experiments are conducted on two types of real-world datasets---traditional and randomized trial data---and results show that our framework can improve the recommendation performance and reduce the Simpson's paradox problem of many CF algorithms.
Face recognition system with feature normalization

ABSTRACTThis study proposed an identity verification system that uses face recognition. The system features face detection as well as facial feature extraction and comparison methods. Early methods of face detection involved using specific approaches coupled with a classifier to extract features and detect faces. Although these methods can detect faces quickly, they generate a high false positive rate. Recent face detection methods based on a deep learning structure are extremely accurate but time-consuming. This study realized a face detection method based on the histogram of oriented gradient. The proposed method is not as accurate as deep learning; however, it is fast and can complete instant computing. Early methods of face recognition also involved using feature extraction methods coupled with a classifier to complete face recognition; however, these methods were not extremely accurate. The emergence of deep learning has facilitated greatly increasing the accuracy of face recognition. A deep learning-based method requires the entire deep learning structure to be retrained when a system needs to add a new user. This requirement is not feasible in actual applications. A researcher has therefore proposed the FaceNet method, which uses deep learning structure to extract eigenvectors and calculates the distance between eigenvectors as a measure of face similarity. Thus, the entire deep learning structure does not need to be retrained when a new user is added to the system. In this paper, FaceNet was used to extract the eigenvector of a face. However, the experiments of this study showed that facial features extracted using FaceNet are unevenly distributed in different dimensions, and using the calculated distance of the eigenvector as a measure of face similarity will yield inaccurate results. Therefore, this study proposed a facial feature normalization comparison method. The experimental results verified that the proposed method can achieve more than 98% accuracy and can be applied in practice.
Penerapan Aplikasi Berbasis Android Untuk Ternak Ayam Petelur Sebagai Wadah Untuk Menghubungkan Pemilik Modal Dengan Calon Peternak

Laying hens are one of the producers of animal protein through the production of eggs, eggs that contain many nutrients needed by the body. The need for chicken eggs in NTB in 2019 reaches 1.3 million eggs, but regional layer hen breeders are only able to produce as many as 6000 eggs so that to meet the need for eggs, the government needs to bring eggs from other regions. The government also encourages people to raise laying hens through the poultry village program, which is one of the industrialization programs in the livestock sector to make NTB egg independent. However, to start raising livestock there are several problems that become sellers, namely the problem of capital and land. People who have capital do not have the choice of where to invest their money in the end only save their money in a bank whereas on the other hand farmers who own land need capital to start a livestock business. Therefore, the authors provide a solution by creating a well-known application as a place to connect investors with prospective breeders through an Android-based application so that investors can easily find potential breeders and breeders find it easier to get capital to start raising laying hens
Impact of Financial and Trade Openness on Financial Development in Oil and Non-Oil Developing Countries using the Panel ARDL Approach (With Emphasis on Institutional Components)

Impact of Financial and Trade Openness on Financial Development in Oil and Non-Oil Developing Countries using the Panel ARDL Approach (With Emphasis on Institutional Components)
Atomtronic protocol designs for NOON states

The ability to reliably prepare non-classical states will play a major role in the realization of quantum technology. NOON states, belonging to the class of Schroedinger cat states, have emerged as a leading candidate for several applications. Starting from a model of dipolar bosons confined to a closed circuit of four sites, we show how to generate NOON states. This is achieved by designing protocols to transform initial Fock states to NOON states through use of time evolution, application of an external field, and local projective measurements. By variation of the external field strength, we demonstrate how the system can be controlled to encode a phase into a NOON state. We also discuss the physical feasibility, via an optical lattice setup. Our proposal illuminates the benefits of quantum integrable systems in the design of atomtronic protocols.
Cyborgian Approach of Eco-interaction Design Based on Machine Intelligence and Embodied Experience

Abstract The proliferation of digital technology has swelled the amount of time people spent in cyberspace and weakened our sensibility of the physical world. Human beings in this digital era are already cyborgs as the smart devices have become an integral part of our life. Imagining a future where human totally give up mobile phones and embrace nature is neither realistic nor reasonable. What we should aim to explore is the opportunities and capabilities of digital technology in terms of fighting against its own negative effect - cyber addiction, and working as a catalyst that re-embeds human into outdoor world. Cyborgian systems behave through embedded intelligence in the environment and discrete wearable devices for human. In this way, cyborgian approach enables designers to take advantages of digital technologies to achieve two objectives: one is to improve the quality of environment by enhancing our understanding of non-human creatures; the other is to encourage a proper level of human participation without disturbing eco-balance. Finally, this paper proposed a cyborgian eco-interaction design model which combines top-down and bottom-up logics and is organized by the Internet of Things, so as to provide a possible solution to the concern that technologies are isolating human and nature.
Topological semantics of conservativity and interpretability logics

Abstract We introduce and develop a topological semantics of conservativity logics and interpretability logics. We prove the topological compactness theorem of consistent normal extensions of the conservativity logic $\textbf {CL}$ by extending Shehtman’s ultrabouquet construction method to our framework. As a consequence, we prove that several extensions of $\textbf {CL}$ such as $\textbf {IL}$, $\textbf {ILM}$, $\textbf {ILP}$ and $\textbf {ILW}$ are strongly complete with respect to our topological semantics.
Blockchain as a tool for transparency and governance in the delivery of development aid

There are global discussions recognising the need for more development aid with jurisdictions such as the EU unveiling increased foreign aid budget for 2021–27 to deliver large increase in aid spending and eliminating the bureaucratic barriers. However, this increased flexibility gives rise to growing concerns on where aid is sent and that whole chain of custody in terms of tracking, traceability, and reporting. The fear is monies are raised, approved, and sent, but there is uncertainly where and if those monies have reached the persons most in need of development aid. Also, for those that willingly contribute to aid development who want to have clear knowledge that funds were securely used for the correct purposes. Therefore more desire for openness, transparency, and method of governance for accurate monitoring and use of evaluation tools in development aid will help secure the chain of custody and for all to realise project outcomes. Recent studies have shown that the utilisation of technology presents opportunities for advancement and particularly the use of blockchain and its attributes of immutability, transparency, audit control through smart contracts, and security. However, the contribution of blockchain to increase transparency in development aid deliverables has received less attention within scholarly research. The aim of this chapter is to examine the viability of blockchain technology in delivering development aid in explaining these attributes of blockchain, some use cases, and applications and analysing data points that can support taking forwards as viable blockchain models.