Reviewerly/exHarmony huggingface dataset:
Chatbot enabled college management system

In a world of growing technology,to know more details about the college,either visiting the campus or checking out the college websites that provide information about the college seems to be time consuming and boring.This traditional way can be eradicated by introducing a college chat bot for efficiently answering any queries of the user.It also provides a more comfortable interface as though the user is talking to a real human.In this paper we have come up with an idea to build a chat bot using Google Dialogflow to answer any queries related to college.
A Family of Novel Fast Algorithms to Improve Computing Efficiency of Set-Based Direct Visual Servoing

Visual servoing (VS) is a technique which uses feedback information obtained from a camera to control the motion of a robot. With respect to approaches that rely on feature-based perception processes to recover the relative pose between the target and the robot, direct visual servoing (DVS) does not require pose estimation, nor featur extraction, tracking and matching, but uses the images as a whole feature directly. Set-based DVS (SDVS) algorithms are based on theory of mutation analysis of shapes or sets and these algorithms have been proposed by researchers recently. However, the computational efficiency for SDVS is relatively slow. In this paper, we proposed a family of novel fast algorithms to improve computing efficiency of SDVS. Simulation results demonstrate the validation of our algorithms as well as the computation efficiency advantage over other SDVS work.
A New State of Organized Crime

Organized crime is often associated with traditional criminal groups, such as the mafia or outlaw motorcycle gangs; however, new research suggests that cybercrime is emerging as a new branch of organized crime. This paper is focused on the changing nature of organized crime and the factors that influence this shift, particularly in the online space. It will address the question: Can the law identify cybercrime as organized crime? The results of this paper are informed by an in-depth analysis of peer-reviewed articles from Canada, the United States (US), and Europe. This paper concludes that cybercrime groups are structured and operate similarly to traditional organized crime groups and should, therefore, be classified as a part of traditional organized crime; however, cybercrime groups are capable of conducting illicit activities that surpass those typically associated with traditional organized crime. This shift suggests that these groups may represent a larger threat creating a new challenge for law enforcement agencies.
PENERAPAN PLATFORM LEARN SOCIAL DALAM KETERAMPILAN BAHASA INGGRIS MAHASISWA

Developing revolution industry 4.0 encourage human to be able for implementation information technology in which use internet. This give effect to the students’STKIP Kusuma Negara English Education Program first semester. They have to mastery in using technology in order that they can follow development. Also students can learn with Platform Learn Social. Platform learn social is a media or tools that use for transferring material in learning. Platform learn social is kind of media in which can access by handphone or laptop. It can access by students if they have already account platform learn social. Advantages platform learn social is available kind of levels so students can know their capability in learning English skills. Disadvantages platform learn social, there is no relation with the syllabus. Keywords : Learn social platform, Learning English
GRAFFL: Gradient-free Federated Learning of a Bayesian Generative Model

Federated learning platforms are gaining popularity. One of the major benefits is to mitigate the privacy risks as the learning of algorithms can be achieved without collecting or sharing data. While federated learning (i.e., many based on stochastic gradient algorithms) has shown great promise, there are still many challenging problems in protecting privacy, especially during the process of gradients update and exchange. This paper presents the first gradient-free federated learning framework called GRAFFL for learning a Bayesian generative model based on approximate Bayesian computation. Unlike conventional federated learning algorithms based on gradients, our framework does not require to disassemble a model (i.e., to linear components) or to perturb data (or encryption of data for aggregation) to preserve privacy. Instead, this framework uses implicit information derived from each participating institution to learn posterior distributions of parameters. The implicit information is summary statistics derived from SuffiAE that is a neural network developed in this study to create compressed and linearly separable representations thereby protecting sensitive information from leakage. As a sufficient dimensionality reduction technique, this is proved to provide sufficient summary statistics. We propose the GRAFFL-based Bayesian Gaussian mixture model to serve as a proof-of-concept of the framework. Using several datasets, we demonstrated the feasibility and usefulness of our model in terms of privacy protection and prediction performance (i.e., close to an ideal setting). The trained model as a quasi-global model can generate informative samples involving information from other institutions and enhances data analysis of each institution.
Upbringing in foreign language lessons: a perspective-scenario approach

The article proposes a solution to the following urgent pedagogical problem in a modern rapidly developing society: how to ensure the prognostic orientation of upbringing in foreign language lessons? The purpose of the article is to develop and describe a perspective-scenario approach to the upbringing of schoolchildren in foreign language lessons, to present the results of its experimental testing. The authors obtained the following results: (1) the education of the future citizen is justified as the target point of upbringing in foreign language lessons, a portrait of the future national is developed consisting of five groups of qualities; (2) a new, perspective-scenario approach to organizing the upbringing in a foreign language lessons has been proposed, which allows to individualize this process, direct it towards achieving the students’ perspective life goals, strengthen the futuristic and prognostic topics of the subject content of speech, develop a conscious, moral, active attitude of students to their future and the future of their country, to integrate the educational and upbringing goals of the lesson, to develop in schoolchildren the qualities of a person of the future and national of the Russian Federation, universal moral qualities; (3) the essence and principles of this approach, the algorithm for its implementation are disclosed; (4) the results of its experimental testing are described.
Studies of geological, mineralization and magnetite exploration geophysics in Senjedak-III area, the eastern anomaly of Sangan mine (Khorasan Razavi)

Studies of geological, mineralization and magnetite exploration geophysics in Senjedak-III area, the eastern anomaly of Sangan mine (Khorasan Razavi)
Market Analysis of Agri-Food Tech 2020

Agriculture Economics and Agribusiness is an actual persistent sickness that takes place both when the pancreas does no longer create enough insulin or on the other hand while the frame can’t viably utilize the insulin it produces. Neurological Disorders is a huge public medical issue, one of the 4 pre-eminent non communicable diseases. The occurrence of Food Microbiology has been relentlessly increasing in the beyond few years.
Using "TBT Shell" Software for Online Testing in "Water Treatment" Education Course

The article describes usage of TBT Shell software (developed in Moscow Power Engineering Institute) for providing online testing for specific Water Treatment education course. Few challenges in Water Treatment course, online testing investigated for last three years.
Grounded Theory on Teaching and Learning of Speech Knowledge - Focusing on pre-service Korean language arts teachers’ problem recognition on principles of conversation -

This study applied a paradigm model based on the methodology of grounded theory of Strauss and Corbin (1990), analyzed the pre-service Korean language arts teachers'' problem recognition on the principles of conversation in an educational context, and suggested the teaching and learning direction of speech knowledge. Educational implications for teaching and learning speech knowledge derived from 48 participants'' data are as follows: first, speech knowledge should be identified in conjunction with practical activities; second, the concept of speech should be perceived in a balanced manner, including the addressee''s judgment and comprehension (i.e., "listening"), away from what was defined as merely the addresser''s regulatory compliance and expression (i.e., "speaking"); and third, conditional knowledge should be developed to manage prepositional and procedural knowledge and help learners'' metacognition. This study is meaningful in that it considers both the internal and external factors in a balanced manner and approaches speech knowledge as a socio-scientific issue.
Data Processing and Artificial Neural Network under Big Data

The origin of characters is that human beings can't remember all things, so they must be recorded to convey and inherit. Character is essentially a kind of coding for things. As a kind of text, numbers are concise, easy to understand, and convenient to write and verify. Understanding sentences is a decoding process. With the development of computer science, the question arises: can a computer understand language and apply it to life? For example, the translation is actually the decoding and recoding of words.&#x0D; In previous studies, researchers focused on exploring whether computers can think and calculate like human brains. This needs to follow the grammar rules, word by word correspondence analysis. But this method is effective for short sentences and simple sentences, and it is very difficult to apply it to long and difficult sentences. At the same time, with the development of language, the different meanings and contexts of words also have a great impact on the decoding.&#x0D; With the development of civilization, the decoding analysis of regular sentences is gradually replaced by statistics, because the semantic analysis of sentences is largely affected by the context. Therefore, the mathematical model is applied to decoding analysis.
Adaptively Meshed Video Stabilization

Video stabilization is essential for improving visual quality of shaky videos. The current video stabilization methods usually take feature trajectories in the background to estimate one global transformation matrix or several transformation matrices based on a fixed mesh, and warp shaky frames into their stabilized views. However, these methods may not model the shaky camera motion well in complicated scenes, such as scenes containing large foreground objects or strong parallax, and may result in notable visual artifacts in the stabilized videos. To resolve the above issues, this paper proposes an adaptively meshed method to stabilize a shaky video based on all of its feature trajectories and an adaptive blocking strategy. More specifically, we first extract feature trajectories of the shaky video and then generate a triangle mesh according to the distribution of the feature trajectories in each frame. Then transformations between shaky frames and their stabilized views over all triangular grids of the mesh are calculated to stabilize the shaky video. Since more feature trajectories can usually be extracted from all regions, including both background and foreground regions, a finer mesh will be obtained and provided for camera motion estimation and frame warping. We estimate the mesh-based transformations of each frame by solving a two-stage optimization problem. Moreover, foreground and background feature trajectories are no longer distinguished and both contribute to the estimation of the camera motion in the proposed optimization problem, which yields better estimation performance than previous works, particularly in challenging videos with large foreground objects or strong parallax.
The Analysis of the Implementation of School Literacy Movement (GLS) Program in Public Junior High Schools and Private Junior High Schools/Islamic Junior High Schools in Surabaya

Background :  Indonesia ranks 60th out of 65 countries in a global literacy awareness survey. The  School Literacy Movement (Gerakan Literasi Sekolah or GLS) is capable of encouraging literacy culture and improving students’ literacy at school.Objective : This research aims to discover the school inclination toward the School Literacy Movement (GLS) in aspects of standard reference, GLS activity stages implementation, and school literacy team in State Junior High Schools and Private Junior High Schools/Islamic Junior High Schools in Surabaya.Methodology: This research employed descriptive quantitative research. The research population was 388. In addition, the sample collection employed Taro Yamane formula, and it obtained 80 schools as the research sample. Moreover, the sample collection technique was conducted by a multistage random sampling technique. Afterward, the research result was collected by distributing a questionnaire which was then descriptively analyzed.Result : The research result identified an achievement indicator Point 1, namely the completeness of national standard reference. In addition, the students’ literacy awareness improved on the indicator of teacher training administration. Nevertheless, this indicator had not been carried out comprehensively. Additionally, the achievement indicator Point 10, establishing the School Literacy Team to support GLS activity at school, indicated a result where there were more schools that had not formed a School Literacy Team.Conclusion: The research result concludes that there are 14 implementation achievement indicators of the School Literacy Movement program which have not been comprehensively carried out by the Secondary Education Units in Surabaya City Government.
Philosophical Interpretation of Relevant Problems of Interethnic Interaction in Domestic Education

The article considers relevant problems of interethnic interaction in education, which nowadays becomes a key factor in formation of modern thinking. This process turns out to be very contradictive. To overcome these contradictions, the authors propose a model of mutual enrichment of national cultures. Scientific originality of the study lies in the fact that the researchers for the first time consider the problem of using reflective techniques in educational activity in the process of ethno-national self-identification. The research findings are as follows: the authors provide a philosophical and theoretical analysis of conditions for constructive interethnic interaction in education.
To Boldly Query What No One Has Annotated Before? The Frontiers of Corpus Querying

Corpus query systems exist to address the multifarious information needs of any person interested in the content of annotated corpora. In this role they play an important part in making those resources usable for a wider audience. Over the past decades, several such query systems and languages have emerged, varying greatly in their expressiveness and technical details. This paper offers a broad overview of the history of corpora and corpus query tools. It focusses strongly on the query side and hints at exciting directions for future development.
Showing the Brilliance of Human Nature of Mathematics Under the Concept of Cultural Education

Under the concept of cultural education, through the life experience of mathematical knowledge, deeply excavate the mathematical culture hidden deep in mathematical knowledge, so that mathematical knowledge shines out of the brilliance of human nature, thus sublimating people's ideological character, the psychological complex of the people, the philosophy of human life, The spiritual freedom of viewing people makes mathematics education a kind of life education of enlightenment, education, aesthetic beauty and perfection under the concept of cultural education.
Battle Of Chaos

Battle of Chaos is a 2D Battle Royale game that can support 200 player in one match. Battle of Chaos is also a 2D top down view game on mobile platform. Currently there are hard to find 200 players in one match game or the game developer just adding more AI players into the game and let the game just let the game looks like have 200 players or more. The objective of this game is to show that there is a way to make the game able to support 200 players in one match without any problem.This project are handle by 2 team members which are Tee Kok Fong and Wong Liang Zer. Tee Kok Fong will be focus on the game design and game mechanics while Wong Liang Zer will be focus on networking part. This project will be using Unity engine to develop since Unity is a free engine and already had provide a lot of feature to make a 2D game. The programming language that will be used will be C#. The game currently is still a prototype, so there are still some of the feature doesn’t include into the game but the game is still playable.
Design of Automatic Testing System for Electrical Equipment Based on PCI Bus

In view of the fact that the traditional safety detection system has incorrect detection of errors of electromechanical devices, an automatic detection system design of electrical equipment based on PCI bus is proposed. Through the optimization of system hardware configuration, the operation performance of the automatic detection system is improved, the software flow of the automatic detection system of electrical equipment is further improved, the structure and operation steps of the sensing module are simplified, and the collection and accurate display of safety data are ensured. Furthermore, the abnormal information and error information collected in the automatic detection process of electrical equipment are collected and fault-tolerant analyzed by using calculation and C language framework, and corrected and improved according to the analysis results, so as to finally realize the effective design of the automatic detection system of electrical equipment.
EchoIA: Implicit Authentication System Based on User Feedback

Implicit authentication (IA) transparently authenticates users by utilizing their behavioral data sampled from various sensors. Identifying the illegitimate user through constantly analyzing current users' behavior, IA adds another layer of protection to the smart device. Due to the diversity of human behavior, the existing research works tend to simultaneously utilize many different features to identify users, which is less efficient. Irrelevant features may increase system delay and reduce the authentication accuracy. However, dynamically choosing the best suitable features for each user (personal features) requires a massive calculation, especially in the real environment. In this paper, we proposed EchoIA to find personal features with a small amount of calculation by utilizing user feedback. In the authentication phase, our approach maintains the transparency, which is the major advantage of IA. In the past two years, we conducted a comprehensive experiment to evaluate EchoIA. We compared it with other state-of-the-art IA schemes in the aspect of authentication accuracy and efficiency. The experiment results show that EchoIA has better authentication accuracy (93\%) and less energy consumption (23-hour battery lifetimes) than other IA schemes.
Utility-Based Graph Summarization: New and Improved

A fundamental challenge in graph mining is the ever-increasing size of datasets. Graph summarization aims to find a compact representation resulting in faster algorithms and reduced storage needs. The flip side of graph summarization is the loss of utility which diminishes its usability. The key questions we address in this paper are: (1)How to summarize a graph without any loss of utility? (2)How to summarize a graph with some loss of utility but above a user-specified threshold? (3)How to query graph summaries without graph reconstruction?} We also aim at making graph summarization available for the masses by efficiently handling web-scale graphs using only a consumer-grade machine. Previous works suffer from conceptual limitations and lack of scalability. In this work, we make three key contributions. First, we present a utility-driven graph summarization method, based on a clique and independent set decomposition, that produces significant compression with zero loss of utility. The compression provided is significantly better than state-of-the-art in lossless graph summarization, while the runtime is two orders of magnitude lower. Second, we present a highly scalable algorithm for the lossy case, which foregoes the expensive iterative process that hampers previous work. Our algorithm achieves this by combining a memory reduction technique and a novel binary-search approach. In contrast to the competition, we are able to handle web-scale graphs in a single machine without a performance impediment as the utility threshold (and size of summary) decreases. Third, we show that our graph summaries can be used as-is to answer several important classes of queries, such as triangle enumeration, Pagerank, and shortest paths. This is in contrast to other works that incrementally reconstruct the original graph for answering queries, thus incurring additional time costs.
Measuring Social Personas

This study's goal was to develop a valid and reliable scale for measuring "personas".Three different samples with self-report scales were used.Samples from Studies 1 and 2 produced similar factor loadings for all items.The results of the two studies supported a four-factor solution for the persona scale as follows: social mask, social influence, identity, and role.To assess criterion validity, the correlation between peer evaluations and persona scales was analyzed.To assess criterion validity, the correlation between peer evaluations and persona scales was analyzed.Samples from Study 3 indicate that the scale was valid.The internal consistency of the persona scale indicated that the scale had satisfactory reliability, and results of a test-retest suggested that responses on the scale were stable.The most important contribution of this research to persona theory is the explanation of persona personalities.How does a high or low persona personality affect the organization, for example, through creativity, harmony, or negotiation ability?This scale helps investigate these questions.
Structure and Content of Teacher-Designer Educational Programs in Russia and China: Comparative Analysis

The research objective involves a comparative analysis of teacher-designer educational programs in Russia and China by the example of pedagogical universities of Saint Petersburg and Shenyang. Special attention is paid to analysing chromatic competences acquired within the framework of the discipline “Chromatics”. The article describes the designer’s professional competencies relevant in the modern information environment, identifies personal qualities required in the future society, the society of interaction with artificial intelligence, provides a comparative analysis of programs on chromatics at pedagogical universities of Russia and China. Scientific originality of the paper lies in the fact that the author develops a theoretical foundation for studying specificity of the teacher-designer’s chromatic training with a view to identify obligatory professional competencies specified in the state standards and educational programs of pedagogical universities. The research findings are as follows: comparing educational programs of the Russian and Chinese universities, the author justifies the necessity for a new approach aimed to improve the quality of the student-designer’s training under the conditions of a higher education institution and to stimulate the formation of a professional chromatic competence.