Reviewerly/exHarmony huggingface dataset:
The implementation of animated-narrative-video to improve students’ vocabulary mastery in an orphanage

Mastering adequate vocabulary is necessary for English as a Foreign Language learners to perform their skills in English better. In fact, some EFL learners still have a relatively low vocabulary mastery and difficulty in acquiring English vocabulary. This study was conducted to find out whether there is a significant difference in students’ vocabulary mastery before and after being taught through animated narrative videos. The subject of this study was seventeen students at Al-Husna Orphanage, Bandar Lampung. This study applied a one-group pre-test and post-test design. The instrument used in collecting the data was vocabulary test, fifty multiple-choice items. The data were gathered through a quantitative approach, then analyzed using Repeated Measure T-Test. The result shows that there is a significant difference in students’ vocabulary mastery after being taught through animated narrative videos. It could be seen from the calculation that the t-value is 9.263, higher than the t-table in 2.120 and the significant value is lower than alpha (p=0.000&lt;0.05). It could be said that animated-narrative-video is effective in teaching vocabulary to EFL learners.
Machine Learning Detection for Financial Statement Fraud

This study intends to develop a methodology of fraudulent transaction detection model. The algorithm of XGBoost integrating the techniques of SMOTE sampling method and Bayesian Hyperparameter Optimization, is proposed to separate fraud transactions from non-fraud transactions. The experimental results based on the public data set of financial statement fraud from Kaggle website show the proposed model is better than the commonly used binary-classification methods, such as Logistic Regression, SVM, KNN, Random Forest, XGBoost without Hyperparameter Tuning and Multilayer Perceptron. The method of establishing fraud detection models assists people who lack the machine learning domain expertise for the modeling and tuning parameter techniques. It can help to detect abnormal transactions as early as possible and carry out risk management for banking industry.
Prototype of laundry status tracking information system using codeigniter framework

Laundry is a business in the service sector that offers clothes washing services.The tracking system at laundry outlets currently still uses a manual tracking system.The laundry status tracking information system is a system that can make it easier for laundry service users and computerized laundry service business owners.This system can facilitate the process of laundry activities in providing information on the status of laundry to customers.This laundry status tracking information system is built with a codeigniter framework as a framework and uses the SDLC (Software Development Life Cycle) method.Codeigniter is a framework for developing a web-based application with the PHP programming language which aims to speed up the process of making web-based applications by utilizing the provided libraries.The results of the laundry status tracking application prototype have a feature to send messages directly to WhatsApp when the laundry status changes.Order data will be inputted first into the application.The expected result of this application is that the laundry service business transaction process can run more practically and quickly so that it can make it easier for customers to track the laundry process and make it easier to manage data and laundry services.
Distributed State Estimation for Topology Random Switching in Sensor Networks

This paper proposes a distributed robust filter design method for sensor networks with sensor saturation nonlinearity and random switching of communication topology. In the sensor network, a large number of sensor nodes are deployed to realize the sensing and measurement of the target system, and transmit it to the remote filter through the network. In filter networks, local estimators not only receive the measurement information of sensor nodes, but also receive and fuse the estimation information of neighboring nodes through random time-varying communication topology to achieve state estimation and trajectory tracking of target objects. The saturation nonlinearity of sensor network is described by Bernoulli binary distribution, the random switching of topology is described by inhomogeneous Markov chain, and the sufficient conditions for the existence of distributed filter are given in the form of linear matrix inequality. Finally, a numerical example is given to illustrate the effectiveness of the proposed design method.
The Progressive Development Model of Virtual YouTubers in the Perspective of Dramaturgical Theory - An Analysis from the Perspective of Audience

The current development of AI technology, coupled with the outbreak of the COVID-19, has forced people to communicate online, accelerating the migration of the public to the virtual world, and virtual YouTubers have received widespread attention.Looking at the pre-development path of virtual YouTubers, we can see many problems such as slow development process, outdated technical means and unclear character setting.It is more like an attempt for creators to employ new technology and express themselves.However, the essence of virtual YouTuber is a commodity, and it ought to do service to people after all.Therefore, this paper analyzes the audience's demand for virtual YouTubers from the perspective of audience, and further explores the influence of audience demand on the progressive development mode of virtual YouTubers.
The first period is over: what are the perspectives for us in the museum’s world?

Book review: World trends and museum practice in Russia: Proc. of the Intern. Sci. Conf., Moscow, Oct. 30–31, 2018 / ed. A. A. Sundieva. – Moscow: Russ. State Humanitarian Univ., 2019. – 462 p. – ISBN 978-5-7281-2323-1
DEVELOPMENT OF NEW CRITERIA FOR MONITORING OF SCIENTIFIC ACTIVITY ON THE EXAMPLE OF INSTITUTIONS OF THE EMERCOM OF RUSSIA

New approaches and criteria for evaluating scientific activity are proposed based on existing methods - bibliometric and peer review. The provision is derived that the unified criteria for evaluating scientific activity do not work for many scientific institutions that conduct specialized activities. An objective assessment of the effectiveness of their work will allow the combination of evaluation criteria and their distribution by “weights”. An indicator is proposed - a criterion for the significance of scientific activity for comparing the activities of similar organizations.
The Description of Innovative Work Behavior in Entrepreneurs

Innovative Work Behavior (IWB) in entrepreneurs is individual work behavior that aims to achieve intentional initiation and recognition.The purpose of this study was to determine the description of Innovative Work Behavior (IWB) in entrepreneurs.The hypothesis proposed in this study is that there are high idea exploration, idea generation, idea championing, and idea implementation of the Innovative Work Behavior (IWB) dimensions in entrepreneurs.The subjects in this study were 100 entrepreneurs who worked in all types of business fields.The sampling technique used in this research is purposive sampling.The research method used is descriptive quantitative research.The scale used is the innovative work behavior measurement scale.The results showed that the mean value of the idea exploration dimension was 8.15, the idea generation dimension was 20.94, the idea championing dimension was 16.28, and the idea implementation dimension was 16.3.From innovative work behavior, entrepreneurs are included in the high category.
Use chains to block DNS attacks: A trusty blockchain-based domain name system

Stratification: A hierarchical architecture.From top to bottom, DNS
STEAM and Educational Applications with 3D Printing

The STEAM methodology is based on the integrated learning of science, technology, engineering, arts and mathematics disciplines in an interdisciplinary framework. Education seeks to promote the transversality of knowledge in children and young people to guarantee meaningful learning, which also involves the development of skills and types of thinking such as scientific, quantitative, visuospatial processing, among others. Its fundamental principle is experience-based learning, combined with project-based learning with an innovative approach to teaching. It involves the integration of learning with TICs, the appropriation of knowledge in scientific areas, it promotes creative capacity and imagination.In this sense, the learning spaces generated are collaborative spaces, which provide the conditions to develop mathematical thinking, computational thinking, emotional management skills in young people and enhance communication skills with their peers.Under this framework, 3D printing technology now more accessible and within the reach of children in educational institutions, allows venturing into rapid prototyping for the generation of physical models and the practical consolidation of ideas, achieving more interesting classes for students. Thus, three-dimensional printing technology is being used more and more in education at all levels. This paper discusses the different applications that can be given to rapid prototyping through 3D printing in education and how it can influence the STEAM skills acquired by students.
RF Fingerprinting of Software Defined Radios Using Ensemble Learning Models

Machine Learning (ML) is becoming a transformative technology in wireless communication. The deployment of large scale RF devices particularly in IoT applications escalates security threats and also setting up of secure networks using wireless devices is becoming a big challenge. Along with ensuring security, identifying each RF device in an autonomous network is essential and the RFML (Radio Frequency Machine Learning) can play a crucial role here. This paper focuses on the RF characterization of a set of Software Defined Radios (SDR) using advanced machine learning models. This helps to identify each SDR module in the deployed network which runs only a specific protocol in a particular network. The SDRs will be configured for a particular specification and the test will be conducted. The transmitted data from multiple radio nodes were collected using a reconfigurable radio’s receive chain in IQ-format, in the laboratory environment. The RF features like IQ-imbalance, DC-offset and the image leakages in the multicarrier modes were used to set fingerprints for identifying the reconfigurable radios. Two ensemble learning models Random Forest and AdaBoost were used to train and develop predictive models to identify the radio. At a SNR of 30dB Random Forest achieved an accuracy of 85% and AdaBoost achieved an accuracy of 78% with 32K multicarrier data. A maximum recognition rate of 92% is achieved with RF and 83% with AdaBoost.
Implementation of point-counting algorithms on genus 2 hyperelliptic curves based on the birthday paradox

Our main contribution is an efficient implementation of the Gaudry - Schost and Galbraith - Ruprai point-counting algorithms on Jacobians of hyperelliptic curves. Both of them are low memory variants of Matsuo - Chao - Tsujii (MCT) Baby-Step Giant-Step-like algorithm. We present an optimal memory restriction (a time-memory tradeoff) that minimizes the runtime of the algorithms. This tradeoff allows us to get closer in practical computations to theoretical bounds of expected runtime at 2.45√N and 2.38a√N for the Gaudry - Schost and Galbraith - Ruprai algorithms, respectively. Here N is the size of the 2-dimensional searching space, which is as large as the Jacobian group order, divided by small modulus m, precomputed by using other techniques. Our implementation profits from the multithreaded regime and we provide some performance statistics of operation on different size inputs. This is the first open-source parallel implementation of 2-dimensional Galbraith - Ruprai algorithm.
Combine to Describe: Evaluating Compositional Generalization in Image Captioning

Compositionality -the ability to combine simpler concepts to understand & generate arbitrarily more complex conceptual structureshas long been thought to be the cornerstone of human language capacity.With the recent, notable success of neural models in various NLP tasks, attention has now naturally turned to the compositional capacity of these models.In this paper, we study the compositional generalization properties of image captioning models.We perform a set of experiments under controlled conditions using model and data ablations, each designed to benchmark a particular facet of compositional generalization: systematicity is the ability of a model to create novel combinations of concepts out of those observed during training, productivity is here operationalised as the capacity of a model to extend its predictions beyond the length distribution it has observed during training, and substitutivity is concerned with the robustness of the model against synonym substitutions.While previous work has focused primarily on systematicity, here we provide a more in-depth analysis of the strengths and weaknesses of state of the art captioning models.Our findings demonstrate that the models we study here do not compositionally generalize in terms of systematicity and productivity, however, they are robust to some degree to synonym substitutions 1 .
A Latency Reduction Method for Cloud-fog Gaming based on Reinforcement Learning

Unlike traditional gaming where a game run locally on a user's device, in cloud gaming, an online video game runs on remote servers and streams directly to a user's device. This caused players to become independent of having high hardware resources in their local computers. Since video games are a kind of latency-sensitive application, cloud servers far from users are not suitable. In fog computing, fog nodes are in the vicinity of users and can reduce the latency. In this paper, a latency reduction method based on reinforcement learning is proposed to determine which computing fog node can run the video games with the lowest latency. In the proposed method, a Principal Component Analysis (PCA) based approach is used to extract the most important features of each video game as the input of the learning process. The proposed method was implemented using Python. Experimental results show that the proposed method compared to some existing methods can reduce the frame latency and increase the frame rate of video games.
Machine Translation for Livonian: Catering to 20 Speakers

Livonian is one of the most endangered languages in Europe with just a tiny handful of speakers and virtually no publicly available corpora.In this paper we tackle the task of developing neural machine translation (NMT) between Livonian and English, with a two-fold aim: on one hand, preserving the language and on the other -enabling access to Livonian folklore, lifestories and other textual intangible heritage as well as making it easier to create further parallel corpora.We rely on Livonian's linguistic similarity to Estonian and Latvian and collect parallel and monolingual data for the four languages for translation experiments.We combine different low-resource NMT techniques like zero-shot translation, cross-lingual transfer and synthetic data creation to reach the highest possible translation quality as well as to find which base languages are empirically more helpful for transfer to Livonian.The resulting NMT systems and the collected monolingual and parallel data, including a manually translated and verified translation benchmark, are publicly released via the OPUS corpora collection and Huggingface model repository.
Experimental generation of multimode quantum correlations between a conical probe and a conical conjugate based on a four-wave mixing process

Multimode quantum correlations and entanglements has drawn much attention recently due to its importance for both fundamental science and the future development of quantum information processing and quantum communication. Here, by using a four-wave mixing process with a conical pump beam and a conical probe beam, we experimentally generate the multimode quantum correlations between a conical probe beam and a conical conjugate beam, and we also observe about –2.6-dB intensity-difference squeezing between these two conical beams. In addition, we find the optimal value of each parameter in this scheme for further applications. Besides, the multi-spatial-mode nature of the generated quantum correlated beams is shown by comparing the variation tendencies of the intensity-difference noise of the probe and conjugate beams under global attenuation and local cutting attenuation. Our scheme may find potential applications in quantum information processing and quantum communication.
ON THE QUESTION OF THE “NOVEL-MYTH” MODEL (J.D. SALINGER’S NOVEL “THE CATCHER IN THE RYE”)

Mythology is a science that studies fantastic ideas and myths which belonged to ancient man about the world.The earth, the sky, the plant and animal world are represented by universal communities, and in this universal community all objects were understood not only as living beings, but also as beings consciously and definitely related to each other.These ideas have been generalized in mythology."The Catcher in the Rye" is a novel written in 1951 by American writer Jerome Salinger.The work very vividly tells about the acute understanding of American realities by a sixteen-year-old young man named Holden and his rejection of the general rules and morals of modern society.The novel gained great popularity, mainly among young people, and had a significant impact on the world culture of the second half of the twentieth century.The work openly presents a sharp criticism of the American realities of the mid-20th century, the hypocrisy of people, unnecessary steoreotypes of religion.It is also interesting that the author can perfectly express all this in the language of a 16-year-old teenager.The article is about the novel "The Catcher in the Rye" and its relation to the mythology.In the novel "The Catcher in the Rye" by J.D. Salinger, many well-known archetypes are demonstrated such as "The Mentor", "The Outcast", and "The Initiation".We can also come across with one of the well-known archetypes, such as "The Quest" and immediately we ask: is "The Catcher in the Rye" an example of it?Clearly, the answer is yes.The "Quest" archetype is defined as "the search for someone or something", oftentimes an object that will "restore fertility to a wasted land".Though Holden does not go on a search for a physical object or a person, he does go on a quest for something else: his own identity.In this case, the "wasted land" is Holden's mind, and the restoration of fertility is the restoration of hope and positivity in his mind.Holden is in the middle of his transition between childhood and adulthood, causing confusion over who he is as he is not on either side of the line separating these two stages of life.He shows that he does want to be accepted as an adult but at the same time he does not behave as a child.
INTERACTION OF LIGHT AND SHADOW AS A PROJECTION IN THE PROCESS OF CREATING A SHADOW PERFORMANCE, A PHOTO AND A FILM

For many centuries, the name of one of the types of theater that exists in different forms has been recorded under the name "shadow theater". By this name, we mean many different principles of interaction between light and an object that create shadows. Since projection involves the use of light to achieve "light scenes" as well as the use of light as a tool for creating shadows, it is fair to call such a theater "theater of light and shadows." If we use the name “puppet theater”, since the puppet is the main performer in the performance, then in this case both light and shadows equally participate in their performing roles in the “light and shadow theater”. Light without shadow would not be light, and conversely, a shadow without light would not be a shadow. Their uses have evolved over time. Technological progress has also opened up great opportunities for the play of light and shadow. But the principle and essence of the function of the relationship between light and shadow did not change. Light, just like shadow, played a certain role on the screen within the framework of the plot presented in the play. Unfortunately, in theater studies there is still no professional theatrical terminology that allows you to communicate easily and understandably to all participants in the creation of such a performance. Right, professional terminology for working in the shadow theater technique is currently absent. The establishment of such a terminological system would help, first of all, to more easily define and distinguish between the varieties of shadows and light used, and also to raise this type of theater to a higher professional level.
Secure Data Transformation and Remove the Anomalies in Cloud Computing

In this article, I focus on the problem of verifiable outsourced data deletion, insert and update in cloud computing. If the cloud server does not honestly maintain/delete the data and generate corresponding evidences, users can easily detect the cloud server's malicious behaviours with an overwhelming probability. I propose an efficient fine-grained outsourced data anomalies scheme based on a Bloom filter that can also achieve public and private verifiability of the storage and deletion results. Cloud storage, one of the most attractive services offered by cloud computing, can provide users with boundless storage capacity.
The COVID-19 Pandemic and the Higher Education Sector in Africa: A Tragedy for an Awareness of the Sector’s Resilience

Despite of enormous efforts since independence to alleviate poverty and improve its people’s quality of life, the African continent continues to face frequent political unrest and has low to moderate economic growth rate, with the exception of few countries now classified as emerging states. For decades, the economic growth of the African continent has been widely dominated by private consumption. Lately, there is a shift and investment becomes now the main contributing sector and human capital is expected to play an important role. In Africa, the contribution of the HEIs sector to the economic growth of the continent is relatively modest and, most of the time, not counted or under-estimated. Because of the very limited capacity of countries, HEIs sector has not given its due importance and is receiving a meaningless part of national budgets. This poor funding allocated to the HEIs sector is considered by many as a proof of how the sector is badly perceived by governments in the continent. The lack of or insufficient funding to the sector impacts negatively its capacity to be competitive and also the capability of its actors to properly play their role, especially in terms of research and academic activities. The shock caused by the COVID-19 pandemic was too important for the sector. Universities were closed and the lockdown lasts for many months during which no activity was performed. The very limited resources they are allocated to were not sufficient even to mitigate partly the impact of the pandemic to the sector. In many countries, distance learning was not possible because most students and teachers were not provided with relevant materials and equipment. Offices were closed and universities administration could not operate from the campus. Internet infrastructure exists but was limited to cover only some places of the campus. In many cases, it became clear that business continuity plans were not in place. The impact of this COVID-19 pandemic is so important, and HEIs sector actors are now wondering if this tragedy could be the starting point of government awareness for HEIs’ resilience building.