Reviewerly/exHarmony huggingface dataset:
GMDA: An Automatic Data Analysis System for Industrial Production

Data-driven method has shown many advantages over experience- and mechanism-based approaches in optimizing production. In this paper, we propose an AI-driven automatic data analysis system. The system is developed for small and medium-sized industrial enterprises who are lack of expertise on data analysis. To achieve this goal, we design a structural and understandable task description language for problem modeling, propose an supervised learning method for algorithm selecting and implement a random search algorithm for hyper-parameter optimization, which makes our system highly-automated and generic. We choose R language as the algorithm engine due to its powerful analysis performance. The system reliability is ensured by an interactive analysis mechanism. Examples show how our system can apply to representative analysis tasks in manufactory.
Methods and tools for teaching programming at university

Abstract The paper is devoted to the methods and tools for teaching programming developed in the A.P. Ershov Institute of Informatics Systems. Practical work on programming and an introductory course of programming on the basis of the Zonnon language are considered. The paper also describes the development of an adaptive system for distance learning and a visual cloud system that supports parallel and functional programming.
Research on the method of ship sway isolation for the antenna of shipborne TT&amp;C radar

This paper introduces the influence of ship sway on the work of ship borne TT & C radar, compares and analyzes three kinds of ship sway isolation technologies commonly used at present, deduces the calculation method of ship sway isolation degree corresponding to the three technologies, and verifies the superiority of gyro speed feedforward compensation method to isolate ship sway through experiments, so as to realize stable tracking and give full play to the equipment efficiency of ship borne TT & C radar system It provides theoretical support and practical scheme.
The Mechanism of Intelligent Technology Reforming Education Based on the Perspective of Embodied Cognitive Theory

The development of intelligent technology has given birth to the emergence of new elements and relations in education, as well as the upgrading and transformation of the notification of old ones. An education model can help us better clarifying the core elements and their relations in education, so as to accurately discovering and grasping the primary contradictions and problems in the future work. This paper makes a literature review and finds that there are gaps between theory and technology, technology and industry, which make obstacles to the application of intelligent technology in education. The research first proposes a four-factor education reference model based on the perspective of embodied cognitive theory, and further elaborates the research status of each element in the model and its corresponding education problems. Secondly, the research and application of intelligent technology in solving educational problems are mainly discussed. Then, from three perspectives of teaching, learning, resources and space construction, this paper discusses how to solve the education problems with intelligent technology in recent years. Finally, this paper integrates the existing experience and the development trend of intelligent technology and proposes strategies for advancing the development of intelligent technology in the field of education from two aspects: dialogue between theory and technology, technology landing industry.
Research on the Fast Retrieval Algorithm of English Sentences Based on Simhash

In the current situation, the case-based translation method is becoming more and more popular. The advantage of using machine translation is that machine translation does not need to analyze a sentence word by word, but to replace it under the same word meaning in the original language database. When there are more cases, the translation results will be more accurate. This paper mainly studies the case-based machine translation method. In order to find more accurate similarity, some similar cases of the system in the retrieval process. This paper first introduces the current situation of case-based machine translation and the practical problems of the system, and studies the relevant principles of the simhash algorithm and the principles of the simhash algorithm, so as to realize the purpose of the simhash algorithm to quickly retrieve similar cases, and carefully handle the details in the process of using the simhash algorithm, which can reduce the number of similar cases to be retrieved. With the time, the larger the corpus size, the more accurate the results can be brought to the retrieval in the detection. If synonyms appear in the similar situation, the similarity of the two words can be calculated by the above method, and the real similarity can be seen more objectively from the results.
A Proposal for Edge Application Framework for Smart Factory

In order to improve the productivity of a factory, it is often the case to create an inference model by analyzing data from the machines in the production line, and then to develop an edge application which judges the quality of the products or diagnoses faults of the machines in real time. However, it is difficult to generate an edge application only by deploying the model, because of the variety of data collection and preprocessing methods. To solve this problem, a framework for developing edge applications semi-automatically from inference models is proposed. An actual edge application is prototyped, which proves that the proposed framework concept is feasible.
Standards and Scientific and Pedagogical Freedom in Universities: the Issue of Correlation within the Framework of a Unified Educational Process

The present study considers the issues of improving an educational process in Russian universities in the context of Russia's participation in the Bologna system. The author also addresses the problem of introduction of educational and professional standards and the development of democratic principles in the field of scientific and pedagogical activity. It is noted that Russia has noticeably reduced its activity in brining higher education into line with international standards. In many universities, students are taught mainly according to patterns formed by practice and determined by federal state educational standards (FSES). The curricula and methodological materials also conform to the specified standards. This situation is largely due to excessive top-down approach in management of higher education in Russia and, as a consequence, there is no real competitive component among universities. There is also an insufficient stimulation of generation of both new knowledge and methods of transferring it to students. The present study provides proposals on improving the structure of the Federal State Educational Standard as well as the procedure of compiling educational and methodological literature, aimed at expanding the autonomy of higher educational institutions. There are substantiated proposals on realization of creative potential of the teaching staff and increasing educational activity of students.
The main structural components of the STEM-environment of the educational institution

The article deals with the creation of an educational STEM-environment of an educational institution. The definition of the concept of such an educational phenomenon as the STEM-environment of the institution is substantiated. The most important structural components of the STEM-environment of the educational institution and the main tasks of its functioning are identified. The interpretation of the concept of an educational STEM-environment of an educational institution is proposed as the combination of intellectual and material conditions for the implementation of researches, technologies, engineering, integrated knowledge that ensure self-development of a free and active person, realization of the child’s creative potential. The idea that the child's personality is the most important element of the STEM-educational environment which is the complex and open system that is constantly self-developing is outlined.
Stochastic Workflow Authorizations with Queueing Constraints

Cloud-based workflow architecture has been widely used in e-science, e-business, smart city, and others, to automate business processes and improve their flexibility and maintainability. Online workflow executes in a collaborative and distributed environment and is prone to fraud and information leakage. Workflow authorization models are implemented to ensure that tasks are performed by authorized subjects with compliance of security/privacy polices. However, existing workflow authorization models have some limitations. First, most of the existing research focuses on static workflows, where an order arriving at a workflow traverses tasks in a fixed sequence. In many real applications, however, task routing is not deterministic, having a probability distribution or pattern that may be estimated from historical data. Second, existing research ignores practical resource constraints, like user utilization, order waiting time, etc. To address the limitations, this article studies the workflow authorization model under the more realistic dynamic settings. We formulate a workflow as a queueing system, so business constraints can be analytically represented, under reasonable assumptions. We model the studied problems as pseudo-Boolean satisfiaiblity problems and investigate their theoretical properties. We also develop algorithms and carry out computational studies. The experimental results show the effectiveness and efficiency of our developed solutions. Our research results are useful for production and process design in many real-life settings such as health care, online banking and electronic payment systems.
Type Preserving Representation of Heterogeneous Information Networks

In the current information explosion era, many complex systems can be modeled using networks/graphs. The development of artificial intelligence and machine learning has also provided more means for graph analysis tasks. However, the high-dimensional large-scale graphs cannot be used as input to machine learning algorithms directly. One typically needs to apply representation learning to transform the high-dimensional graphs to low-dimensional vector representations. As for network embedding/representation learning, the study on homogeneous graphs is already highly adequate. However, heterogeneous information networks are more common in real-world applications. Applying homogeneous-graph embedding methods to heterogeneous graphs will incur significant information loss. In this paper, we propose a numerical signature based method, which is highly pluggable—given a target heterogeneous graph G, our method can complement any existing network embedding method on either homogeneous or heterogeneous graphs and universally improve the embedding quality of G, while only introducing minimum overhead. We use real datasets from four different domains, and compare with a representative homogeneous network embedding method, a representative heterogeneous network embedding method, and a state-of-the-art heterogeneous network embedding method, to illustrate the improvement effect of the proposed framework on the quality of network embedding, in terms of node classification, node clustering, and edge classification tasks.
Jumphair: Improving Jumping Performance in First-Person Video Games Through Visual Assistance

Performing jumps in 3D video games from first-person perspective can be excessively challenging because of the difficulty of estimating distances and lack of precision. To address this problem, we created a jumping assistance tool called jumphair that dynamically visualizes distances between the player character and forthcoming edges before performing a jump. Our aim was to create a jumping assistance that helps players to enhance their distance perception for performing their jumps more successfully without being distracted by the tool. We integrated the jumphair into a self-developed video game called Couch Jumper and evaluated user performance and user experience in comparison to using a static icon in two user studies (each N = 30) on a 2D display and a 3D head-mounted display (HMD), respectively. On a 2D output device, results show that the jumphair can improve jumping performances without distracting players. The jumphair is also rated helpful and can be considered an accepted game element. When used on a 3D HMD, the jumphair did not yield advantages in terms of jumping performances in its current implementation but significantly reduced simulator sickness. Our studies have implications for game research and for interface design in first-person video games with jumping mechanics.
Automated Summarization of Bug Reports to speed-up software development/maintenance process by using Natural Language Processing (NLP)

Bug reports can provide a great deal of assistance for developers during the process of development. But due to the large size of bug repositories, it is sometimes difficult to take advantage of these artifacts in the available time. One way of helping developers to provide summaries of these reports and provide relevant details only. Once it's decided that this is the required report then one can study the details. As text mining technology advances, many substantial approaches have been proposed to generate optimized summaries for bug reports. In this paper, we have proposed an extractive based methodology for the generation of summaries of bug reports by using the sentence embedding. We achieved improved rouge-1 and rouge- 2 results than the previous state of the art systems for the bug report summary generation.
Constructing Quality Evaluation System of Teaching Interaction for Intelligent Classroom

The intelligent classroom uses some advanced information technology to realize informationized and intelligent teaching, which makes it different from traditional teaching and network teaching in interaction elements and types. The existing quality evaluation system of teaching interaction is not enough to give an objective and effective evaluation to teaching interaction of intelligent classroom. Therefore, a more reasonable quality evaluation system of teaching interaction is crucial to promote effective implementation and development of intelligent classroom. In this paper, the qualitative research methods are used to explore those key factors affecting the interactive quality of intelligent classroom teaching. Moreover, based on the analysis of relevant factors, a new quality evaluation system of teaching interaction and its operation mechanism are built. The relevant research results will provide theoretical basis and practical supports for the quality assurance of teaching interaction in intelligent classroom.
Morphological Error Analysis of Muhasabah Column at Sabili Islamic Magazine

This study aims to describe the morphological errors in the Muhasabah of Sabili Islamic Magazine March 10 edition which are caused by the wrong choice of affixes, wrong rephrasing, wrong composing of compound words, and wrong choice of word forms. The research method used in this research was a qualitative method. The steps taken by the writer in analyzing the data were as follows: (1) counting the number of sentences, (2) identifying sentences, (3) analyzing errors, (4) calculating the frequency of the error, (5) calculating the percentage of error, (6) interpreting the research results, and (7) concluding the research results. The result concludes that (1) the error frequency is 23 cases; (2) the percentage of errors is 43.40%; (3) medium error category (25% - 50%); (4) the morphological error was caused by the wrong choice of affixes, the wrong use of repeating words, the wrong formulation of compound words, and the wrong form; and (5) mistakes that are often made by language users should be reduced or completely eliminated if possible.
Research on Grey Clustering Weighting of Expert Group Based on Information Entropy

To improve the objectivity and scientificity of weighting the evaluation index, the grey clustering weighting of expert group based on information entropy is introduced to weight the evaluation index. The actual example on flight training airspace environment safety indicates that the method can weight the evaluation index, and shows good operability and logicality.
Evaluating two security systems for mobile voting fortification

The developments in Information and Communication Technology transformed almost every aspect of everyday life. Modern societies are now fully dependent on ICT for commercial, labor, and leisure activities, excluding in the voting area. Using ICT for democratic elections is quiet in its early stages. Nevertheless, utilizing ICT, specifically mobile phones, traditional voting processes can be streamlined to except the cost of social assets and time. Other researchers have already developed a mobile voting system, which is the use of a mobile phone to cast a vote. However, using a fast-growing device like mobile phones to vote poses security vulnerabilities. Mobile phones are exposed to security challenges, including malicious threats and intrusions as they are increasingly utilized to store sensitive personal data, such as financial data used for mobile banking. This paper is concerned with the security of the mobile phone as a utensil to vote amid the election. The paper evaluated two security systems to check, among the two-security systems, the one that best guards mobile voting. Simulations were utilized to evaluate the security systems and the findings were that Suricata is more reliable and effective than Snort in protecting XaP mobile application. This paper provides a significant contribution to the literature in mobile voting security as no research has been piloted that evaluates two security systems for mobile voting protection.
Information Entropy Squeezing and Non-local Correlation Between a Two-Level Atom and Two-Mode Field Under the Classical Field Effect

This paper examines the squeezing on information entropy and entanglement on the basis of a quantum scheme contains two-mode interaction with time dependence of a two-level atom included external field. The proposed model is formulated by eliminating the external field after applying a certain transformation. The dynamics of information entropy squeezing and nonlocal correlation information for the system Hamiltonian are investigated. The influence of the classical field on the evolution of the squeezing and entanglement are estimated. Through the results will obtain the dynamic behavior of squeezing and entanglement is controlled using the external field.
“Get ’Em Out!”: The Meaning of Ejecting Protesters

This chapter analyzes over fifty cases in which Trump sought to remove confrontational protestors during his campaign rallies. Consideration of the linguistic and semiotic form of Trump’s instructions shows that, most often, they consisted of a grammatical imperative, “Get them out,” addressed to his supporters or to event security. The activity of removing protestors became a tool of interactional messaging which not only allowed Trump to signify about his own self-image but also created opportunities for supporters to embody and enact the political project that Trump advocated. The semiotic notion of “iconicity,” in which a sign represents by way of a resemblance or similarity with its object, provides a key to understanding these events. Trump’s ejecting protestors not only allowed Trump to communicate an image of strong, masculine leadership, but also diagrammed aspects of his proposed policies. The very action of ejecting protestors served as a kind of portrait in miniature of Trump’s promised immigration policy; ejected protestors stood for those persons labelled illegal immigrants who would, Trump promised, be deported. “Get them out” thus came to allude to a large-scale redistribution of power and agency, a new morally righteous populism, that his leadership would bring about.
Lexical and Compositional Stream Learning for Event Detection with Sememe Knowledge

As one of the most significant subtasks for event extraction, event detection(ED) aims to identify the trigger words in a sentence and classify them with correct event types. Most methods in previous work rely on various neural networks to extract trigger features automatically which still suffer a lot from word-trigger mismatch and disability of sparse triggers detecting, especially in Chinese corpus. In this paper, we propose a lexical and compositional stream learning approach to alleviate these two limitations in ED task with sememes in How Net as the external knowledge base. Concretely, we employ convolutional neural network (CNN) to learn lexical representation and compositional representation separately, and we consolidate event sememe information into structural features where the event sememe embeddings provide sememe trigger clues in sentence-level and word sememe-type tertiary structure enriches the compositional features. Then we fuse both of them into a hybrid representation to achieve trigger identification and event type classification. Experiments conducted on ACE2005 dataset show our model outperforms the state-of-the-art method especially for event type classifier.
Features addition and dimensionality reduction in classification

Abstract In the paper additional features are constructed in order to increase accuracy or other precision values in the original classification task. This technique is implemented vey often in a lot of machine learning tasks of various domains of knowledge. Usually the second degrees of source features and their products are used. But this process can be continued further to higher degrees. At the same time it increases dimensionality of tasks dramatically. The balance between the dimensionality problems and new features addition is discussed in the present work. The principal component analysis is used to reduce the dimensionality. These sequential steps allow to construct new space containing new features that depend from the source parameters non-linearly. The technique is discussed on the example of the heart diseases dataset. Also functional dependencies in the medical dataset are observed.
The Design of the Assistant System for College Students

In order to solve the problems of tedious workflow and difficult communication in traditional student work, this paper proposes a design scheme of student assistant system based on Spring MVC framework with reference to old version. The system interface is simple and easy to operate and concurrently controlled.