Reviewerly/exHarmony huggingface dataset:
Foreign Aid and Dutch Disease: The Case of Vietnam

Abstract This study examines whether foreign aid from 1986 to 2019 caused the Dutch disease effect in Vietnam using a VAR model and Granger causality test. In this context, “Dutch disease” refers to the weakening of manufacturing processes as a consequence of the appreciation of a local currency due to capital inflow. Since foreign aid is considered a type of capital inflow, it is among the reasons for the appreciation of a local currency, which may offset the impact of foreign aid on economic growth. Although Vietnam experienced rapid economic growth, along with a large amount of foreign aid and appreciation in the real exchange rate, after Doi Moi (economic reform) in 1986, few studies have yet been conducted. The estimation results show that foreign aid does not cause an appreciation of the local currency in Vietnam. Based on this result, the Dutch disease did not occur due to foreign aid in Vietnam. JEL classification numbers: F35, O53. Keywords: Foreign Aid, Dutch Disease, Vietnam.
HISTORICAL AND SOCIAL PERSPECTIVES OF BLYTON’S THE FAMOUS FIVE

This article examines the historical and social perspectives in children literature of three series of Blyton’s The Famous Five. The objective of this study is, to explain the historical context and social perspectives of the three series novel of The Famous Five. This study used qualitative method to collect, select and analyze the data. The data of this study is three series of novel The Famous Five by Enid Blyton. This study used document analysis as the process of collecting data in this research. The writer collected the data using some notes and online news as the instrument to get the data. The theory used in this study is historical and social approaches in children literature by Jack Zipes. The study found some historical aspects and social elements in the novel. The result of this study showed that (1) there are twelve historical aspects dealing with place, event, and artifact. (2) there are four social elements dealing with economic condition, gender equality, tradition, and culture. The historical aspects and social elements of Blyton’s The Famous Five are depicted in the form of conversation and paragraphs. Based on the result of this study, the writer concludes that Blyton’s background influences the process of the historical aspects and social elements which are depicted in the three series of Blyton’s The Famous Five.
Effectiveness of Machine and Deep Learning for Blockchain Technology in Fraud Detection and Prevention

Blockchain was formerly originated to prevent fraud in digital currency exchanges. Blockchain refers to a decentralized collective ledger that is unaffected by tinkering; it provides the confirmed contributors access to store, view, and share the digital information in a situation that is rich in safety, which in turn supports the development of trust, liability, and transparent business associations. Identity theft and fraud safety is an endless challenge for everyone elaborate in buying and selling. With each novelty in security technology, hackers and fraudsters learn to outsmart the technology and breach these networks. The first section of the chapter describes the structure of the blockchain, its framework, the pros and cons of the combination of these technologies, and the role and importance of machine and deep learning algorithms in fraud detection and prevention in the blockchain. The next section focuses on the reported work, highlighting the work of different researchers for fraud detection and prevention using Blockchain technology. The final section of the chapter comprises comparative analysis based on various performance parameters such as accuracy, the area under the curve, confidence, true negative, false positive, and truly positive for a different type of fraud detection using blockchain technology.
Deep Learning in Computer Vision

The presence of several large-scale databases and advancements in hardware and software technologies have made the development of sophisticated deep learning algorithms a reality. Such deep learning algorithms have provided state-of-the-art performances in a variety of real-world tasks ranging from person identification to autonomous driving to game playing. In this chapter, we provide a comprehensive overview of two aspects of deep learning algorithms. The reason for studying deep learning is the breakthrough performances they yielded in several computer vision applications. The first aspect which we comprehensively reviewed is the progress of deep learning especially convolutional neural networks (CNN) in object recognition and face biometric recognition. A list of algorithms and popular databases are discussed to make the researchers aware of current trends and where to take the next steps to advance the field. In another aspect, the vulnerabilities of CNNs and face recognition algorithms are discussed in detail. While the advancement in the computer vision algorithm is needed, the protection of their integrity against threats is also critical to make a trustworthy decision. Toward both aspects challenges are provided which can act as a future research goal. Therefore, we believe the presence of such a chapter can significantly increase the understanding of the readers toward the deep learning in the computer and its vulnerabilities to make the progress further.
Big Data Analytics Process Implementation on a Educational Data Set Extracted from Online Testing System

The paper presents an application of the big data analytics process on a data extracted from the educational system for online testing. The procedure of data migration to a non-relational system was implemented. Big data analytics process was realized through query processing in MongoDB and analysis results visualization in Microsoft Power BI. The contribution of the research presented in this paper refers to the importance of applying the big data concept for analyze data set extracted from educational systems in order to discover information and knowledge important for improving the efficiency of the educational process.
One very long slow move - with benefits: Ireland's national geological collection.

This paper outlines the benefits of a protracted move, over many years, accompanied by a concurrent documentation project, for the geological collections of the National Museum of Ireland. Long neglected, and in storage for nearly 60 years, the collections have now been unpacked and moved to one site in the Collections Resource Centre, near Swords in County Dublin. An Inventory documentation project has collated basic data on the collection into an Adlib database, but all the physical storage and organisation has been improved in the process. The long, slow, careful move has made the collections fully accessible for the first time in around a century. It has opened up the potential to make further significant improvements in collections care, access, data records and use in exhibitions and research.
Intelligent Coin Dispensing Machine with Fake Note Detection

Although most transactions are now made digitally, some rural regions still use real currency for transactions. Coins are now more frequently used than cash at a variety of locations, including bus and train stations, malls, temples, and water systems that operate on a coin system. Obtaining coins is incredibly tough for regular people. A system is created to offer a solution to the difficulty indicated above. One mechanical device that has phoney note detection and an intelligent note to coin exchanger. In the proposed system, when the user inserts the note, it first uses UV rays to determine whether the note is real or fake. If the note is real, it is then taken inside for further processing and a camera takes a picture of it. By calculating the number of pixels and using image processing, it determines the value of the note, and then equivalent amounts of coins are dispensed in accordance with the value. This system will make it easier for regular people to go about their daily lives.
Handling Multicollinearity Problems in Indonesia's Economic Growth Regression Modeling Based on Endogenous Economic Growth Theory

One of the multiple linear regression applications in economics is Indonesia’s economic growth model based on the theory of endogenous economic growth. Endogenous economic theory is the development of classical theory which cannot explain how the economy grows in the long run. The regression model based on the theory of endogenous economic growth used many independent variables, which caused multicollinearity problems. In this study, the multiple linear regression model using the least-squares estimation method and some methods to handle the multicollinearity problem was implemented. Variable selection methods (backward, forward, and stepwise), principal component regression (PCR), partial least square (PLS), and regularization methods (Ridge, Lasso, and Elastic Net) were applied to solve the multicollinearity problem. Variable selection method with backward, forward, and stepwise has not been able to overcome the problem of multicollinearity. In contrast, Principal Component Regression, PLS regression, and regularization regression methods overcame the multicollinearity problem. We used "leave one out cross-validation" (LOOCV) to determine the best method for handling multicollinearity problems with the smallest mean square of error (MSE). Based on the MSE value, the best method to overcome the multicollinearity problem in the economic growth model based on endogenous economic growth theory was the Lasso regression method.
Study on Management System for Information Security

According to the relevance of the existing information's role in various companies, competent management is required to ensure the security of that information. The information security refers to protecting information and minimizing unauthorized access to it. Management system of the information security means the information security of a part of general and overall information security in an organization that is based on business risks’ approach and aims to establish, implement, operate, monitor, verify, maintain and improve information security. In this study, we have tried to introduce information security management system, types of threatening risks of information systems and also introduce and offer proper ways to maintain information security of each organization and then work on necessary requirements in order to design information security system and phases of implementing management system of information security.
Strategy Analysis in PBL-applied Classes in English and Arts: Case Study

The purpose of this study is to analyze the cases of PBL-applied classes and to explore the strategies used by the instructors. To this end, this study described the cases of the classes during the second semester of 2021 at S University in Chungnam and K University in Gangwon Province, and made the professors conduct self-reflection test on the teaching operation strategy for deriving strategies that are commonly used among them. As a result, the instructors who applied PBL generally used strategies related to classroom culture, facilitating, and various evaluation method among 12 strategies. However, this study has some limitations such as the amount of cases, so further studies are needed. Nevertheless, this study has its significance in suggesting useful strategies for instructors who run classes using PBL.
A Comparative Study on the Usage of Communicative Functions Used in Domestic and Abroad Elementary School Textbooks of English

This study examined the usage of communicative functions stipulated in the 2015 revised national curriculum of English in domestic and abroad elementary English textbooks. To this end, communication functions used in the domestic 5th and 6th-grade elementary school English textbooks were compared. Next, one domestic 6th grade textbook and one 6th grade textbook in the United States, China, and Singapore each were selected and analyzed to compare the usage of communication functions used in the four textbooks. The results show that in the comparison of the 5th and 6th-grade textbooks, more diverse categories of communicative functions were used as the grades went up, and even within the same communicative function category, the 6th-grade textbook contained more diverse communicative functions. Additionally, in the comparison of the domestic and abroad textbooks, it turned out that in Korea’s textbook, the proportion of ‘persuading, and advising,’ ‘socializing,’ and ‘constructing discourse’ was relatively high, and that of ‘expressing knowledge, memory, and belief,’ ‘expressing one’s will,’ and ‘expressing emotions' was relatively low. In addition, Korea’s textbook showed the lowest TTR value in terms of the communication function subcategory, which suggested that it is necessary to use more diverse expressions included in the communication function when developing English textbooks. In conclusion, some implications were also presented.
Research of readiness of teachers of rural secondary schools for innovations

The purpose is to establish the interdependence of key parameters and construct a factor structure of teachers’ readiness to reform and deploy innovative technologies in rural secondary schools. Research methods: ANOVA factor analysis with reduction of factor proportions, standard valid and reliable psychodiagnostics methods, statistical reliability coefficients. Results. The factor structure ensures the following main factors (73.92%). It has been found that the main are “MARI” (F1) (52.56%) and “CRI” (F2) (9.28%), which are interconnected with “SLRI” (F3) (p≤.01) and F4 “PRI” (F4) (p≤.01). Conclusions. It has been stated that the obtained scientific facts give an objective understanding of the subject of research and its determinants. The curriculum for the initiative to modernize education in rural areas is composed of established scientific facts and argumentation of the results obtained. It was noted that results will allow to operationalize the educational and professional training of future specialists in order to prepare them for modernization of training and teaching.
The Influence of the Teaching Behavior Types of the Orienteering Education Course in Chinese Universities on Learning Attitude and Learning Commitment

The purpose of this study is to empirically investigate the effect of teacher's behavioral patterns on the learning attitude and learning immersion of liberal arts orienteering class leaders.This in-person visit was conducted for random sampling.Among the randomly selected samples, a total 575 copies were evaluated, excluding the questionnaire with missing and invalid responses.To achieve the purpose of the study, frequency analysis, exploratory factor analysis, reliability verification, correlation analysis, and multiple regression analysis were performed using SPSS 26.0 program, and the study results were derived as follows.Results of the study revealed that the First, it was found that the teaching behavior type of orienteering liberal arts class had a significant effect on the learning attitude.It was found that the type of teaching behavior in orienteering liberal arts classes had a significant effect on learning immersion.In addition, through the limitations presented in this study, we propose the following for follow-up studies.First, since the respondents of the study of this study were students from the liberal arts orienteering class at Huizhou University, Guangdong, China, further research is needed by expanding the scope of the research subjects in the future, and overall research with different genders and projects is needed.Second, continuous research should be conducted by reflecting the opinions of the subjects through a qualitative research method like indepth interviews with players.
Performance of Graph-based Zero-knowledge Proofs

Zero-knowledge proofs (ZKP) are a widely used technology for privacy protection and data ownership that allows parties to verify the accuracy of a piece of information without sharing the data. In this study, we developed and performance tested two graph-based zero-knowledge proof methods, the Hamilton Cycle Based ZKP Algorithm (ZKPHC) and the Graph Isomorphism Based ZKP Algorithm (ZKPGI), using an open source library. As the graph sizes increased, we measured and compared the running times of these methods. We tested the completeness and robustness of the ZKPHC protocol for different modes. As the graph used grows, the ZKPHC method, which uses encryption at every stage, works much slower than ZKPGI.
An Efficient Image Retrieval Model with Convolutional Neural Network based Text/Image Identification for Copyright Violation Detection

One of the most important problems faced by broadcasters is the unauthorized use of their images by third parties or organizations in a large-scale database, which contains hundreds of thousands of images. For this reason, it is important to perform an efficient and effective image retrieval, whose objective is to find the most similar images to a given test image. In addition, test images often contain text, and the presence of the text together with the visual part complicates the search process. In this paper, we present an image retrieval framework based on a bag of visual words, which has been shown to be effective in the literature. A convolutional neural network model is used to parse the text in the images. Experiments demonstrate the efficacy of this model in a large database.
Risk Assessment of Waste Incineration Power Generation Project Based on BP Neural Network

The waste incineration power generation method can reduce the amount of waste and make it harmless, and can convert it into part of the electric energy. Due to the large amount of project investment and high professional and technical requirements, the cooperation model between the government and social capital is promoted, and social capital is encouraged to participate in infrastructure construction. There are still many risks in the investment, construction, operation stage and exit mechanism of waste incineration power generation projects. BP (Back Propagation) neural network is one of the most widely used training algorithms in artificial neural network algorithms, and has been widely used in prediction, recognition, diagnosis and other fields. We identify the potential risks of waste incineration power generation projects, deal with the risks that have appeared in the process of waste incineration power generation projects, reduce risk losses, and timely curb the expansion of risks are the main tasks of risk management of waste incineration power generation projects. This paper deeply studies the BP neural network algorithm, comprehensively analyzes various uncertain factors in the development of waste incineration power generation projects, builds a scientific and feasible risk assessment model for waste incineration power generation projects, selects relevant data for simulation analysis, and verifies the effectiveness of the training model.
Integrating Blockchain and IoT in Supply Chain Management

Internet of things(IoT) is the conception of interfacing the devices to the internet to make life more efficient. It comprises the large amount of data in its network where it fails to assure complete security in the network. Blockchain is a distributed ledger where it mainly focuses on the data security. Every block in the blockchain network is connected to its next block, which prevents threats like large data loss. In the area of agri-food supply chain, where IoT plays a very important role, there occurs data integrity issues or data tampering. This can lead to improper supply chain management, timely shortage of goods, food spoilage, etc. So the traceability of agri-food supply chain is necessary to ensure food safety and to increase the trust between all stakeholders and consumers. Many illegal activities can be prevented, and cold chain monitoring can be achieved by bringing in transparency and traceability.
Active learning algorithm through the lens of rejection arguments

Active learning is a paradigm of machine learning which aims at reducing the amount of labeled data needed to train a classifier. Its overall principle is to sequentially select the most informative data points, which amounts to determining the uncertainty of regions of the input space. The main challenge lies in building a procedure that is computationally efficient and that offers appealing theoretical properties; most of the current methods satisfy only one or the other. In this paper, we use the classification with rejection in a novel way to estimate the uncertain regions. We provide an active learning algorithm and prove its theoretical benefits under classical assumptions. In addition to the theoretical results, numerical experiments have been carried out on synthetic and non-synthetic datasets. These experiments provide empirical evidence that the use of rejection arguments in our active learning algorithm is beneficial and allows good performance in various statistical situations.
Hypertextuality of Oral Literature(s): Reading the Architectonics of Indian Folklores in Digital Archives

The paper attempts to examine the ways folklores are connected to one another to constitute an integrated whole of a popular literary genre. Folklores while retelling the underlying stories recontextualise the narratives to render significance to them. So, there is an inherent connection between the underlying narrative as hypotext and the retelling of the stories as hypertext. Secondly, it shows how the folktales are preserved in the digital archives and how effective they are in the context of modern literary studies and contemporary culture.
MODEL PEMBELAJARAN DISCOVERY LEARNING GAME GETS LUCKY CARD: STUDI ANALISIS PENINGKATAN PEMAHAMAN SISWA TERHADAP AL-QURAN

LEARNING MODEL DISCOVERY LEARNING GETS LUCKY CARD GAME: IMPROVEMENT ANALYSIS STUDY STUDENTS' UNDERSTANDING OF THE AL-QURANThis study aims to improve understanding of student learning outcomes with the Discovery Learning (DL) learning model through the Games Gets Lucky Card method. The current globalization that has occurred recently has a very significant impact on the transformation of the world of education, especially in Indonesia, to a negative direction. The fast involvement of technology media also adds to the challenges and problems that are quite formidable to be faced by teachers in finding effective, efficient learning formulations that are liked by students at this time. The research method used is quantitative methods based on classroom action research. This research was carried out in two stages, each of which was based on planning, action, observation and reflection. Data collection was carried out using observation-based field study techniques where the research subjects were students and teachers at the MI Negeri Bekasi school. This study shows that the application of the Discovery Learning model can increase understanding activities and student learning outcomes in BTQ subjects. The research percentage shows that in the first cycle, the achievement of student learning activities was 68.62% which then increased in the second cycle to 96.10%. The increase in learning outcomes includes aspects of knowledge where the value obtained reaches an average of 77.63 and then these results increase so sharply in the implementation of cycle II with an average value of 87.95.