Reviewerly/exHarmony huggingface dataset:
A fusion data security protection scheme for sensitive E-documents in the open network environment

E-documents are carriers of sensitive data, and their security in the open network environment has always been a common problem with the field of data security. Based on the use of encryption schemes to construct secure access control, this paper proposes a fusion data security protection scheme. This scheme realizes the safe storage of data and keys by designing a hybrid symmetric encryption algorithm, a data security deletion algorithm, and a key separation storage method. The scheme also uses file filter driver technology to design a user operation state monitoring method to realize real-time monitoring of user access behavior. In addition, this paper designs and implements a prototype system. Through the verification and analysis of its usability and security, it is proved that the solution can meet the data security protection requirements of sensitive E-documents in the open network environment.
Ethics: What is the Research Scenario in the Brazilian Symposium SBIE?

There is no doubt about the relevance of Computing in Education (CE), especially after the COVID-19 pandemic. However, the more we deal with computational artifacts in Education, the more we will have to face ethical dilemmas and concerns behind the engineering of the educational artifact and its values and qualities. In the context of the Brazilian Symposium on Computers in Education (SBIE), this paper aims to answer the question: what is the panorama of the occurrence of ethical aspects in SBIE publications between 2011-2020? To answer this question, we followed the methodology of Systematic Literature Review. We analyze topics such as Informed Consent, Ethics Committee, technological domains, ethical principles, and research contexts.
PARTICLE FILTER OPTIMIZATION TOOLS FOR DYNAMICAL SYSTEMS PROBABILISTIC MODELS

В работе предложены математические инструменты на основе достаточных статистик и декомпозиции выборок в сочетании с алгоритмами распределенных вычислений, позволяющие существенно повысить эффективность процедуры фильтрации. Filtering algorithms are used to assess the state of dynamic systems when solving various practical problems, such as voice synthesis and determining the geo-position and monitoring the movement of objects. In the case of complex hierarchical dynamic systems with a large number of time slices, the process of calculating probabilistic characteristics becomes very time-consuming due to the need to generate a large number of samples. The essence of optimization is to reduce the number of samples generated by the filter, increase their consistency and speed up computational operations. The paper offers mathematical tools based on sufficient statistics and sample decomposition in combination with distributed computing algorithms that can significantly improve the efficiency of the filtering procedure.
SAFPN: Self Adapted Feature Pyramid Networks for Object Detection

Many works show the effectiveness of feature fusion in both segmentation tasks and detection tasks. However, these methods usually integrate features by simply adding or concatenating operations which cause the imbalance of feature information for detecting different size objects. In this paper, we propose a self-adapted framework–SAFPN, to integrate features more smoothly.
Semantic Parsing and Text Generation of Complex Questions Answering Based on Deep Learning and Knowledge Graph

The current semantic parsing method can accurately parse simple question, but its lack of ability to analyze complex questions. Especially, there are many complex problems in the medical, legal fields. Therefore, the semantic analysis method of the complex question and the method of generating the complex answer are particularly important. However, the current complex question answering technology has the problems of low efficiency of compound question parsing methods and loss of semantic information in complex answer generation. To solve this problem, this paper proposes an complex question parsing method based on improved Bi-LSTM and ccomplex answer generation method based on BERT-LSTM. Firstly, we define a complex question parsing model, in which different parsing methods and answer organization methods are formulated for different kind of complex questions. Then the improved Bi-LSTM model is used to analyze the complex question and decompose the original question into multiple sub-questions that answers in the knowledge graph, according to the complex question analysis model. Finally a BERT-LSTM model extract complex answer from sub-answers based on machine-reading comprehension method. In order to test the effect of this method, we make a Chinese complex question and answer corpus, and construct a Chinese complex question answering system. Experimental results show that the accuracy of this system is better than the others. The score of ROUGE-L evaluation increased by 9.3%.
Informational Technologies in Film Production - How ICT shaping Media Industry

This paper will provide a summary of the drivers which makes changes within the media industry and film production based on the progress of Information and Communications Technologies. As for now - the entertainment industry is constantly growing, based on reaching a more international audience and using new, creative ways of developing and delivering content. Despite the fact that entertainment is more close to Art - Information and Communications Technologies makes big and valuable changes to the industry, not only in terms of new devices, hardware, and software but also in the ways of creatively using those resources. Some of the examples in the article shows how technologies can change completely the ways how some instruments were used before, and how more sufficient and handier they can be only because new technologies opened new opportunities. Merging of the industries like game, movie and informational technologies is a matter of time and IT creations like “Unreal Engine” blurs the lines between gaming and filming, taking computer graphics and 3D modeling to a new level. Other big changes to the Art can bring Artificial Intelligence, Machine Learning, and Big Data instruments, although it’s still not so trusted by big production companies and film studios. But the more Information and Communications Technologies are evolving, the more Media Industry is changing.
A Development of Data Interface Middleware for Building Smart Factory

SMEs encounter many difficulties in integrating and operating various information systems introduced to build smart factories. The source of this difficulty comes from integrated management of data interface between information systems. This research proposes a data interface middleware that can operate and manage various data interfaces between information systems in an integrated manner. First, this study identifies the types of information systems and operational information needed to build smart factories and analyzes the ways of data interface and requirements suitable for the manufacturing environment of SMEs. Structure and detailed functions of the data interface middleware are designed based on the analysis results. The proposed data interface middleware consists of the function layer, engine layer, and DB layer. The function layer is a set of functions for operating the middleware, and the engine layer comprises core engines for executing the functions. The DB layer manages all information that gathers when the data interface is executed. We applied the proposed middleware to connect data between the existing ERP and newly introduced smart factory package software in SMEs. Application results show that the associated data types are consistent in the two systems, and accuracy of the data parsing process is reliable.
Exploring Live Cloud Migration on Amazon S3 Instance Using InterCloudFramework

Cloud customers in many enterprises can migrate their virtual machines (VMs) live at a reduced cost through cloud service providers. By default, nested and hardware-assisted virtualization are disabled, making second virtualization installation difficult on IaaS platforms. The cloud consumers’ VMs capable of deploying an application get closely coupled to IaaS providers, which hinders the live migration of VMs across various providers. The proposed work uses InterCloudFramework to demonstrate live cloud migration using file transfer. InterCloudFramework enables users to live migrate VMs with less hassle and disturbance to running services hosted on these existing VMs. We explore the live migration of VMs on Amazon S3 instance having high-performance processors. Also, explore three advanced options: transferring a file from local to cloud and cloud to local, moving files from one cloud to other clouds lively. The next option is transferring from cloud to regional and then cloud. The experimental results are conducted on different file sizes. The time taken for migration is evaluated and studied under implementation.
Digitalization of the economy as a pedagogical problem

The article provides an overview of trends in the digital economy that affect the professional training of a modern specialist. The essence of the concept of digitalization and its main components are determined, the author's interpretation of this concept is given. Particular attention is paid to the signs of a digital economy: the presence of a high-tech IT infrastructure, processing of big data based on modern digital technologies, the creation of digital solutions (products, platforms), the design of new business models. A theoretical analysis of scientific literature was carried out and a list of competencies that a specialist in the digital economy should possess was identified. To confirm the results obtained, an analysis of the opinions of employers was carried out, on the basis of which the most significant competencies and professional qualities of a specialist in the digital economy were identified. Based on the results of the analysis of employers' requirements for modern specialists, the tasks of vocational education for the training of a specialist in the digital economy were identified.
Automation of Society Security Using Deep Learning and IoT

COVID-19 pandemic has created a humongous disturbance all over the world. In such a pandemic crisis, social distancing and face masks have become an important precautionary measure to curb the spread of this deadly disease. Many organizations rely on the traditional biometric systems for logging their attendance or providing authorized access, which are not of much use today because of the contagious nature of disease. Through the proposed system in this paper, an attempt has been made to eliminate human contact as far as possible and facilitate centralized monitoring of all the visits made into the residential society. The proposed system leverages the best of both worlds - IOT and Deep Learning, thereby incorporating an IOT device, voice assistant, a web server and a mobile application for the end users. Furthermore, the system provides an admin with the ability to maintain records automatically for future references and send the critical alerts as and when required. The user can then simply monitor all the visits made to it from a remote location.
What does literature teach about digital pathology? A bibliometric study in Web of Science

Digital pathology (DIPA) has become an effective discipline that generates a graphic environment to diagnose and interpret the pathological information of people. When analyzing the existing literature on DIPA, a knowledge gap was produced by not reporting a study that has bibliometrically analyzed the publications on the subject. The objective of this study is to analyze the scientific production and performance achieved by the term digital pathology in the Web of Science (WoS) database. For this, a methodology based on bibliometrics has been carried out, complemented by the scientific mapping technique to search, recorder, analyze and predict the scientific literature on the state of question. We have worked with an analysis unit of 1222 documents reported from WoS database. The results show that there is no research topic in the field of study of DIPA that stands out from the rest. A conceptual gap can be observed in the thematic development, given that there is no theme that is repeated in all periods, where the connections are more thematic than conceptual. There are key documents for different topics. The main themes have been very different over the years like telepathology and artificial intelligence.
Systematic Review: Tele-Nursing a Universal Access to Care for Oncology Patients

Telenursing is a way of caring for and educating oncology patients to promote self-care management at home. The objective of the study was to analyze the scientific evidence on telenursing in the care of oncology patients. This was a systematic and descriptive review in Spanish, Portuguese and English which was available in 3 databases: BMC, Pubmed and Scielo. The articles were selected in English, Spanish and Portuguese with data from 2010-2020. It was found that tele-nursing, a new form of access to the care service provided by nursing professionals to patients with oncology treatment, including technological tools allow a direct and timely relationship to respond to the detection of adverse events after chemotherapy, promote self-care and control and monitor the patient's health status at home. Conclusions: There is a need to use tele-nursing as an opportunity to care for the patient at home through virtual means by providing relevant information to promote self-care and quality of life.
LDA-CBOW-Based Mining Model for Risky Driving Behavior in Traffic Accidents

Abstract Traffic accident data of traffic management department is recorded in unstructured text form, which contains a large number of characteristic descriptions related to risky driving behavior. However, such data has short text length and abundant professional vocabulary. Many text mining techniques cannot effectively analyze such text data. This paper proposes an improved LDA algorithm based on CBOW—LDA-CBOW model for the study of traffic accident text data containing illegal behaviors. This model can better extract the topics of traffic accident data and filter the keywords under the corresponding topics, which provides a better way to study the dependence relationship between traffic data and illegal behaviors. Experiments show that compared to other models, this model can better extract related topics of traffic accident data with higher model efficiency and better robustness.
Sørensen-Dice Similarity Indexing based Weighted Iterative Clustering for Big Data Analytics

Big data is a collection of large volume of data and extract similar data points from large dataset. Clustering is an essential data mining technique for examining large volume of data. Several techniques have been developed for handling big dataset. However, with much time consumption and space complexity, accuracy is said to be compromised. In order to improve clustering accuracy with less complexity, Sørensen-Dice Indexing based Weighted Iterative X-means Clustering (SDI-WIXC) technique is introduced. SDI-WIXC technique is used for grouping the similar data points with higher clustering accuracy and minimal time. First, number of data points is collected from big dataset. Then, along with the weight value, the given dataset is partitioned into ‘X’ number of clusters. Next, based on the similarity measure, Weighted Iterated X-means Clustering (WIXC) is applied for clustering data points. Sørensen-Dice Indexing Process is used for measuring similarity between cluster weight value and data points. Upon similarity found between weight value of cluster and data point, data points are grouped into a specific cluster. Besides, the WIXC method also improves the cluster assignments through repeated subdivision using Bayesian probability criterion. This in turn helps to group all data points and hence, improving the clustering accuracy. Experimental evaluation is carried out with number of factors such as clustering accuracy, clustering time and space complexity with respect to the number of data points. The experimental results reported that the proposed SDI-WIXC technique obtains high clustering accuracy with minimum time as well as space complexity.
Person image generation through graph-based and appearance-decomposed generative adversarial network

Due to the sophisticated entanglements for non-rigid deformation, generating person images from source pose to target pose is a challenging work. In this paper, we present a novel framework to generate person images with shape consistency and appearance consistency. The proposed framework leverages the graph network to infer the global relationship of source pose and target pose in a graph for better pose transfer. Moreover, we decompose the source image into different attributes (e.g., hair, clothes, pants and shoes) and combine them with the pose coding through operation method to generate a more realistic person image. We adopt an alternate updating strategy to promote mutual guidance between pose modules and appearance modules for better person image quality. Qualitative and quantitative experiments were carried out on the DeepFashion dateset. The efficacy of the presented framework are verified.
Design of Gaussian modulator for continuous-variable quantum key distribution

The continuous-variable quantum key distribution experimental system requires the randomness and speed of a Gaussian modulator. We present the hardware design for a Gaussian random number (GRN) generator based on the Box–Muller method, which can be implemented on a field-programmable gate array (FPGA). An external high-speed true random number generator application-specific integrated circuit (ASIC) is used to this end. The ASIC operates faster and more independently compared with other Gaussian algorithms based on a linear feedback shift register. The trigonometric and logarithmic functions are calculated using the nonuniform piecewise linear approximation. The calculation of the Gaussian random modulus and phase value is realized using this hardware. Compared with an arbitrary waveform generator, the GRN can be uploaded to a computer to estimate the security key rate. Furthermore, the GRN generator accurately provides a Gaussian probability density function that passes the Jarque–Bera inspection and Lilliefors tests. The proposed FPGA-based system is demonstrated to convert eight-channel 320-Mbps uniform random numbers to 40-MHz 16-bit GRN in real time. Finally, the control of the optical module and Gaussian modulation is realized via the FPGA-based outputs of four dual-channel, 16-bit, 1-giga samples per second digital-to-analog converters.
Transformation in the Management Models of Higher Education Institutions in Bulgaria – Challenges and Opportunities in the Digital Age

The article explores the trends and challenges facing higher education institutions in Bulgaria arising from digitalization, internationalization, dynamic regulatory framework and students' attitudes towards the educational process. The possibilities for modification in their governance models are characterized by taking into accounts the policies and strategies for the development of higher education at the European and national levels. The study aims to outline the possibilities for transformation in the management models of the Bulgarian higher schools, focusing on the development of digital competencies and the use of modern technologies in research and teaching processes, as well as funding opportunities through EC programs promoting the role of universities in creating regional innovation ecosystems.
User Evaluation of a Virtual Reality Application for Safety Training in Railway Level Crossing

The railway is one of the safest modes of transport all over the world. However, there are safety concerns for pedestrians and other road users as some of these railways can pass through smaller towns. As a potential technological solution, this study utilised a virtual reality (VR) application to train pedestrians on essential safety skills required to cross a level crossing safely. It builds on the previous work to evaluate the user acceptance of an educational VR railway level crossing application utilising the system usability scale (SUS) and sense of presence (SoP) questionnaire. Overall, the SUS score decreases with age, while the sense of presence score increases with age.
Towards a Semantic Interoperable Flemish Research Information Space: Development and Implementation of a Flemish Application Profile for Research Datasets

In Flanders, Research Performing Organizations (RPO) are required to provide information on publicly financed research to the Flemish Research Information Space (FRIS), a current research information system and research discovery platform hosted by the Flemish Department of Economics, Science and Innovation. FRIS currently discloses information onresearchers, research institutions, publications, and projects. Flemish decrees on Special and Industrial research funding, and the Flemish Open Science policy require RPOs to also provide metadata on research datasets to FRIS. To ensure accurate and uniform delivery of information across all information providing institutions on research datasets to FRIS, it isnecessary to develop a common application profile for research datasets. This article outlines the development of the Flemish application profile for research datasets that was developed by the Flemish Open Science Board (FOSB) WorkingGroup Metadata and Standardization. The main challenge was to achieve interoperability among stakeholders, which in part had existing metadata schemes and research information infrastructures in place, while others were still in the early stages of development.
On the content of the "basic course of informatics" in the project "IT class in Moscow school"

The article discusses approaches to the organization of pre-professional training of students in 10–11th grades within the framework of the project "IT class in Moscow school", the task of which is to create a platform for training specialists in IT sphere. The basis for training students in informatics in the project "IT class in Moscow school" is the discipline "Basic informatics course", designed for two years of study, four hours a week. Thematic course planning is presented in the article. The content of the new textbook for the 11th grade is described in detail, including the following topics: "Graphics and multimedia", "Files and file system", "Modeling and game theory", "Databases", "Web programming", "Uneven coding, noiseproof codes", "Complexity of algorithms", "Algorithms", "Programming paradigms".
Path Planning Scheme for Complete Coverage of UAV radar Survillance Areas using Reciprocation-Backfill Algorithm

In order to accomplish the unmanned aerial vehicle search mission efficiently, this paper develops two complete coverage path planning models to collaborate with the A-star algorithm: the Backfill Reciprocation model and the L-shaped Reciprocation model. The key idea of the two models is to accelerate the searching process for either the unsearched area caused by obstacle avoidance or the new areas. Simulation results show that both models can complete the search mission with a lower repetition rate compared with the traditional Reciprocation model. Moreover, the Backfill Reciprocation model has the advantage of reducing the number of A-star algorithm usage times, while the L-shaped Reciprocation model observably decreases the average U-return times.