Reviewerly/exHarmony huggingface dataset:
Скорочтение как инструмент развития личности

The article provides an overview of theoretical approaches to speed reading in russian and foreign science, discusses practical methods for increasing reading speed, and analyzes the impact of reading speed on the individual. In the introduction, the author reveals the relevance of the topic, which is determined by the social demand for innovative teaching methods in general and effective reading methods. In theoretical background the author considers the works of Russian and foreign authors devoted to the study of the phenomenon of speed reading as an acquired skill, ways of developing this skill and hindrances that hinder learning, analysis of reading as a psychophysiological process, its technical and semantic components, as well as the impact of reading on the individual.  The success of using training tools to develop speed and quality of reading depends on the accuracy and depth of theoretical understanding of the psychological mechanisms underlying based on mastering the speed reading skill. Reading is a complex cognitive skill. Mastering the skill of rapid reading without losing the quality of learning requires a special organization of the learning process, taking into account the understanding of the cognitive mechanisms underlying speed reading, on the one hand, and the motivational and semantic component of the student's personality, on the other. The novelty of the research lies in the synthesis of scientific knowledge in the field of cognitive skills development and a semantic-didactic approach to the organization of the speed reading learning process. In Discussion, the author proves that with the above approach to understanding the competence of speed reading, it can become not only a method of optimizing and improving the efficiency of intellectual labor, but also a way to improve and develop the individual as a whole.
To Explore the Manifestation of Linguaculture Potentials in the English Lecturer’s Teaching

This study was attempted to explore what sorts of linguaculture potentials had been manifested by English language lecturers, and how did the lectures manifest the linguaculture potentials in English class.In general, this study applied qualitative research thoroughly.Data collection was collected in in-class observation, in which seven classes had been observed in a sum.Coding derived from the in-class observation transcript was separately analyzed, by then findings were synthesized as themes to illustrate the main points of linguaculture implements in English class.Based on the themes, there were two aspects presented from the findings.The first one was the ways of linguaculture incorporation, and second was the content of linguaculture incorporation.The study suggested the innovation in linguaculture implemented English teaching.
PiPACT: Examining the Feasibility of Automatic Bluetooth Proximity Detection for Digital Contact Tracing

As cases of the coronavirus disease (COVID-19) soar worldwide, contact tracing has proven to be an essential and effective method of slowing the virus propagation. This paper explores the feasibility of an automatic contact tracing technology that uses Bluetooth signals to determine proximity between two devices. While without obstruction Bluetooth signal strength is effective at proximity sensing, obstructions and variations in device orientation provide sufficient ambiguity such that Bluetooth signal strength alone cannot reliably determine proximity. It is also found that the duration of contact can be accurately measured by the number of transmissions received. More factors other than signal strength, such as those accounting for suboptimal conditions, must be considered to reliably determine proximity.
Research on Organization Name Matching Based on Word Vector

Abstract Organization names usually exist in the form of abbreviations, aliases, etc. in daily use, which brings great difficulties to online search and matching in the Internet era. Through extensive analysis of Chinese organization name data and research on word embedding technology based on neural network, this paper proposes a BERT model based on organization name field data training to achieve organization name matching. The experimental results show that the accuracy is improved by 17% compared with the method based on edit distance.
Better Modeling the Hierarchical Structure of Language for Sentence Semantic Matching

Abstract Sentence semantic matching requires understanding the semantic relationship between two sentences, which is widely used in various natural language tasks such as paraphrase identification, natural language inference and question answering. Usually, the underlying structure of sentence is not strictly sequential, this structure is hierarchical. This paper studies how to better model the hierarchical structure of sentence for semantic matching. Recent research suggests that BERT implicitly captures classical, tree-like structures. Based on this, this paper proposes to further enhance the strength of modeling hierarchical structure of language with an advanced variant of LSTM – Ordered Neurons LSTM(ON-LSTM), which introduces a syntax-oriented inductive bias to perform the composition of classical tree structure. Experimental results demonstrate that the proposed approach, which enhances hierarchical structure of language, significantly improves the performance of sentence semantic matching.
Proposing the Development of Dataset of Cartoon Character using DCGAN Model

In this paper, we propose to create animated images using the deep convolutional generative adversarial network (DCGAN) model for creative design of publications for entertainment applications. We have built a set of image data for machine learning with nearly 1000 images in order to increase their quality while reducing the machine learning execution time. The results show that the proposal model not only improves the accuracy of the image with 21 dB but also reduces the execution time to less than a week (with transposed convolution up to $$stride = 2, kernel = 3$$ and size of image from $$64\, \times \,64 \,\times \,32$$ to $$128 \,\times \,128 \,\times \,3$$ ). The results meet for requirements of future real-time applications.
Peningkatkan Keterampilan Mengomunikasikan Hasil Diskusi pada Materi Kegiatan Ekonomi Melalui Penerapan Model Pembelajaran Numbered Head Together (NHT) pada Peserta Didik Kelas IV Sekolah Dasar

The purpose of this research is improving the skill of communicating the result of the discussion by applying numbered head together model. This Classroom Action Research consists of two cycles. The subjects of this research were 20-grade 4th elementary school students in Surakarta in the 2019/2020 academic year. The data collection techniques used interview, observation, and documentation. Data analysis techniques using triangulation. The analysis of the data used the interactive analysis model of Miles and Huberman that consists of data collection, data reduction, data display, and conclusion verifying. Research data shows that the score of the skills of communicating the result of the discussion on the pre-cycle is 20,8 %, in the first cycle is 41, 6 %, and the second cycle is 8 7 , 5 %. Based on the result of the research, it can be concluded that the skill of communicating the result of the discussion on grade 4th elementary school students in the 2019/2020 academic year can be improved through the Numbered Head Together model.
Platform Governance: A Mechanism Design Perspective

Over the past decade, the rise of blockchain technology has led to the emergence of a growing number of decentralized platforms that are governed less by platform owners and more through community efforts. The emergence of blockchain platforms offers a unique opportunity to examine alternative structures for platform governance and to develop a theory around the value of centralized, semi-decentralized, and decentralized governance. Drawing on mechanism design theory, we evaluate the tradeoffs between centralization and decentralization and hypothesize semi-decentralization as a higher-performing governance structure. Empirical evidence from the blockchain industry shows that decentralization has an inverted U-shaped relationship with platforms’ market capitalization, developer attention, and development activity. We further examine factors driving the decentralization of platform governance and find that digital platforms of the infrastructure layer—relative to those of the application layer—have a tendency to become more decentralized. This tendency, nevertheless, can be offset by experienced leaders to achieve semi-decentralization. Overall, this study contributes new insights on the characteristics, antecedents, and consequences of effective platform governance.
The Role of Open Data in Healthcare Research

The generation and storage of data have dramatically increased worldwide in the last two decades. Computing and networking capabilities combined with openness enhance the potential impact of the accumulated data, offering society an opportunity to drive massive social, political, and economic change. Open data is a recent approach. In summary, open data can be freely used, shared, and built-on by anyone, anywhere, for any purpose. Though health open data are not regularly available, it is estimated that the value of a more effective use of data resources in the US health care sector alone could be worth USD 300 billion annually. To date, Open Government data count more than 10,000 datasets in Italy but only a few concern healthcare. In this chapter, we will try to clarify what open data are and, after having recalled the principles of Open Government, the attention will draw on open data in the health and pharmaceutical context, focusing on the state of the art in Italy and worldwide.
The Telephonist: a communication system for telematic performance

This article describes a communications system for telematic performance developed during the COVID-19 pandemic of 2020. Taking the form of an antique telephone switchboard, the system is designed specifically for a solo performer to interact with voice recordings, music and sound synthesis mechanisms and engage with local and remote audiences via telephone.
Ogene Bunch music analyzed through the visualization and sonification of beat-class theory with ski-hill and cyclic graphs

Traditional Ogene music (metal gong) is a music genre originating in the eastern communities of Nigeria which retains an intrinsic communicative function and music style of Igboland characterized by call and response vocals, polyrhythms and improvisation. Through applying a psychoacoustic approach using visualizations and sonifications of beat-class theory with ski-hill and cyclic graphs, a listener is enabled to represent their experience of both music and mathematics embodied acoustics. This paper demonstrates the evolution of Western music theory to have the capacity to represent rhythm, meter, and pitch by visualizing beat-class theory through ski-hill and cyclic graphs (mathematical music theory). This new approach is suitable for understanding Igbo music which, like the majority of the world's music, is transmitted aurally and not notated. Applying a psychoacoustic approach, this paper illustrates how Igbo music can be accurately preserved for future generations and included in the scholarly discussion. The paper also reveals structural details of the music which may not be accounted for previously through the use of traditional Western music theory.
Users behavior tracking for Education Assisting by using Multiple Kinect sensors

It is difficult to track multiple people effectively in a complex environment because people's clothes and body shapes may be similar, and their postures may be constantly changing. This paper proposes a novel method for detecting and tracking multiple people in crowded places where people can be partially or completely occluding each other is proposed in this paper. In the method, the features of multiple people are detected and tracked by using a particle filter. Meanwhile, accurate color information is obtained by integrating color image and depth information by using YOLO human detection method. The effectiveness of the proposed method is proven by experiments tracking multiple children in a classroom. It is difficult to track multiple people effectively in a complex environment because people's clothes and body shapes may be similar, and their postures may be constantly changing.
Morphometric Analysis of Lake Langano Watershed using Geographic Information System

An understanding of watershed characteristics like areal, linear and relief aspect has paramount significance for watershed planning and management.An automatic extraction of these characteristics from digital elevation model is so effective and efficient.The main objective of this research work was Morphometric analysis of Lake Langano watershed characteristics from Digital Elevation model using GIS.This research work employs an automatic extraction of hydrological characteristics using Geographical Information system.The results of finding show that the watershed has highly permeable soil type which absorbs the water passing over the soil.Drainage texture of the watershed is very coarse and the watershed is less affected by erosion.There is high runoff in the watershed due to large number of overland flow length.The shape of the watershed is elongated shape and experiences low peak flow over longer duration of time.Circulatory value of the watershed indicates that lake Langano watershed is not under flood risk.Relief characteristics of the watershed indicate that most part of the watershed is characterized by gentle slope and the peak of south eastern part is characterized by steep slope.
ISLAMIC FEFAC AS AN INTERESTING LEARNING MEDIA TO IMPROVE STUDENTS’ ENGLISH ABILITY AND DEVELOP THEIR CHARACTER VALUES IN MAN REJANG LEBONG

The article aims to improve students’ English ability and develop character values in MAN Rejang Lebong. The subject of Community Service was 40 (fourty) students from low economic category that studied in MAN Rejang Lebong. The result showed that the service activities have been carried out well and smoothly without any obstacles; this community service showed improvement in students’ English ability. It can be seen in the result of pre-test and post-test (65 and 79). Then, this community service is also can develop students’ character such as active, independent, brave, responsibility, discussion, polite in the classroom. Students are very enthusiastic in receiving the learning material that has been delivered by the servant; and school  plays an active role in supporting the implementation of this community service.
Identification and Recognition of facial images

Face detection is the power to identify a face and recognition is the ability to recognize whose face it is by means of facial characteristics. Face is multivariate and requires a lot of mathematical summation. Almost all imperative applications use a face recognition system. There are many methods that have been already proposed which provides low recognition rate. Hence, the main task of research is to develop a face recognition system with higher recognition capability and better accuracy. This paper proposes Face recognition system by combining two techniques Viola Jones and Principal Component Analysis. An approach of Eigen faces is employed in Principle Component Analysis(PCA). The face recognition system is implemented in MATLAB.
Parallelizing Digital Signal Processing for GPU

Because of the increasing importance of signal processing in today's society, there is a need to easily experiment with new ways to process signals. Usually, fast-performing digital signal processi ...
Providing Software Asset Management Compliance in Green Deployment Algorithm

Today, the use of software is generally regulated by licenses, whether they are free or paid and with or without access to their sources. The world of licenses is very vast and unknown. Often only the public version is known (a software purchase corresponds to a license). For enterprises, the reality is much more complex, especially for main software publishers. Very few, if any, deployment algorithm takes software asset management (SAM) considerations into account when placing software on Cloud architecture. This could have huge financial impact on the company using theses software. In this article, we present the SAM problem more deeply; then, after expressing our problem mathematically, we present GreenSAM, our multi-parametric heuristic handling performance and energy parameters as well as SAM considerations. We will then show the use of this heuristic on two realistic situations, first with an Oracle Database deployment and second with a larger scenario of managing a small OpenStack platform deployment. In both cases, we will compare GreenSAM with other heuristics to show how it handles the performance/energy criteria and the SAM compliance.
1<sup>st</sup> International Workshop on Essence in Education &amp; Training (WEE&amp;T 2020)

The workshop connects to the central theme “Educating for the Future” of CSEE&T 2020 and thus explores opportunities to improve Software Engineering education and training by using Essence. Essence, an OMG Standard, delivers essential, universal elements found in all Software Engineering (SE) endeavours and a language to describe and extend these elements and their use in concrete practices to tailor SE methods to teams' needs. Its Kernel separates the stable What and Why from the more adaptable How. That way, it provides an essential thinking framework facilitating the adoption and customization of practices and methods. As such, it supports multiple ways of educating SE students as well as training practitioners for the future. The first deployments of Essence in industry and academic courses around the globe show promising results. But since it is an entirely new way to think about SE practices, methods, and their building blocks—it requires some effort and thought to dive into the standard. This workshop facilitates the adoption by sharing experiences, best practices, and lessons learned.
The Mining of IP Landmarks for Internet Webcams

IP geolocation, which is important for the security of devices, heavily relies on the number of high-quality landmarks. As one kind of widely used Internet of Things (IoT) devices, Internet webcams are exposed to the Internet intentionally or unintentionally. While there are few researches on the methodology to extract landmarks for Internet webcams by now. In this paper, we proposed a framework GeoWAT to automatically generate landmarks from the watermarks of the webcams, which are accurate enough to improve some IP geolocation services. GeoWAT uses Optical Character Recognition (OCR) techniques to get text locations from the watermarks of public webcams on the Internet websites. Then GeoWAT queries the locations through online maps to get latitudes/longitudes of webcams as landmarks. We conducted experiments to evaluate the performance and effectiveness of GeoWAT in real world. Our results show that GeoWAT could automatically extract the locations of webcams with high precision and recall. Also, GeoWAT have got more accurate landmarks than other IP location services, such as IPIP, GeoLites2 and ipstack, on the webcams dataset we collected from the whole world.
Physicists and Computer Algebra

The Bateman project is the end product of the random growth of the subject with a gradual superimposition of uncorrelated notations and as such it is highly inefficient. Computer algebra should be used to simplify the notation, generalize the final results, and make it easier to discover old results which are potentially useful. Computer algebra is here to stay and there is no way to go back; in a few years new monstrously large and cheap memories will contain an immense variety of computational tools and will make it accessible to a personal computer. The problem is how to manage it efficiently. Quite possibly most manuals on this subject have been written by secret agents of the competition and as a rule they are remarkably unclear, user unfriendly, and smartproof. Many computations, such as traces or raising or lowering of indices, do not need an a priori knowledge of the dimension and should be excised in a separate package.
FAKE NEWS DETECTION USING MACHINE LEARNING TECHNIQUES

Information preciseness on Internet, especially on social media, is an more and more vital concern, but web-scale data hampers, potential to identify, consider and correct such data, or so referred to as fake news present in these systems in the present literature. There exists a giant physique of lookup on the subject matter of computer gaining knowledge of methods for deception detection, most of it has been focusing on classifying online opinions and publicly on hand social media posts and there are many algorithms used for fake information detection, and present authors cannot use benchmark dataset for this detection respectively. In this mini project, we will a suggest a approach for pretend information detection and ways to follow it on LIAR data set, it is a benchmark records set. This approach uses different computing device learning classification models to predict whether the information will be labelled as REAL or FAKE.
Photonic discrete-time quantum walks using spatial light modulators

We report a novel scheme for photonic discrete-time quantum walks, using transverse spatial modes of photons and programmable spatial light modulators (SLM). Our scheme enables simulation of arbitrary steps, only limited by the SLM resolution.
In-depth Analysis and Application of Power Grid Data for Location of Task Difficultie

This paper has presented an idea of using substation and monitoring data to locate the key operations and difficulties in operations of staff working in substation. The analysis also make it possible for related department of majors find out the training needs of staff and technique development needs in power grid. With the help of field data, the conclusion of above analysis will be more clear and objective.
EFEKTIVITAS METODE PEMBELAJARAN DARING TERHADAP MOTIVASI BELAJAR MAHASISWA SAAT PANDEMI COVID 19 DI KOTA PEKANBARU

Humanity is currently in deep sadness due to the outbreak of Coronavirus Disease (Covid-19) which has hit almost all parts of the world. Indonesia spontaneously implemented policies of learning from home, working from home, and worshiping at home. One of the learning methods used by the Indonesian education system is online or the abbreviation for the network. Online or online is a learning method that is carried out online. While online courses are courses that are wholly or partly held online or online, using learning management. Learning methods used in the learning process affect student motivation or interest in participating in the learning process. Modifying the learning process so that it attracts student attention will increase student motivation to learn even in the covid 19 pandemic conditions. This study used a pre-experimental design with a descriptive correlation design with a cross-sectional approach. The population in this study were all university students in Pekanbaru City. Sampling using the accidental sampling technique with 103 respondents and using t-test data analysis. Based on the influence test using the Paired sample T-test, it was found that the correlation of the Effect of Online Learning Methods on Student Learning Motivation had a significance of p = 0.000 <0.05. Thus it can be concluded that there is a significant effect of online learning methods on Student Motivation in Pekanbaru City.