Reviewerly/exHarmony huggingface dataset:
Estimating Multidomain Wall Motion in Polycrystalline Materials

This article presents an approach to estimate multidomain wall motion obtained on video from a grain of polycrystalline material. The first step consists of pre-processing the image to reduce noisy artifacts. Then, an object detection technique is applied to the pre-processed images to locate the position on the domain wall. The location data collected from each image are used to display the estimated movement of domain walls from all input video frames. The experimental results allow the improvement of models based on the behavior of the individual movement of each wall.
Conclusion

This concluding chapter ventures into the future to predict ICT-enabled teaching-learning possibilities in South Asian contexts. The chapter features educational and policy reports and evaluates them against the actual ground realities in South Asia.
Quantification of Privacy Loss (Q)

Differential privacy gives a worst-case guarantee as it quantifies all possible neighboring datasets and overall possible outputs. It is natural to consider relaxations, especially since they often have better composition properties. This chapter of the Brief gives an overview of the corresponding notions
Research on macro financial data classification method based on random forest algorithm

In order to enhance the availability of macro financial data, it is necessary to accurately classify macro financial data. Therefore, a new macro financial data classification method based on random forest algorithm is proposed. Firstly, the macro financial data collection model is constructed in the form of triples to complete the macro financial data collection, and the characteristics of macro financial data are extracted according to the weak correlation characteristics between the data. After feature extraction, the classification sequence of macro financial data is obtained. Under the upper limit constraint of generalization error of the classifier, the random forest classification expression is constructed to complete the classification of macro financial data. The experimental results show that compared with the traditional classification methods, the proposed method improves the classification accuracy and reduces the classification time-consuming, indicating that the classification performance of the proposed method has been significantly enhanced.
Manipulator motion planning based on task-space constraint guidance

Sampling-based motion planning algorithms with task-space guidance have been proved to work efficiently in solving task-constrained manipulator planning problem as the planned end-effector path can satisfy the task constraints directly. However, planning in task-space rather than in configuration space (C-space) may lead to discontinuous motion in joint space, especially the connection of the bidirectional tree. In this paper, a Progressive Constraint Extension Bi-direction Rapidly Exploring Random Trees (PCE-BiRRT) algorithm is presented, which adopts a progressive constraint expansion strategy to make sure that the sampling configurations can satisfy the task constraint directly. For the smoothness of the bidirectional-tree connection, the proposed algorithm deals with the "connection failure problem" of the bidirectional exploring tree by limiting the connecting range and choosing a property redundancy resolution. The effectiveness of the PCE-BiRRT algorithm is tested on the robot operating system (ROS) platform by an orientation-constrained case.
Blockchain and Smart Contracts

New technologies making use of blockchains and smart contracts have been considered an efficient and innovative way to achieve the goal of effective copyright protection in the digital market. It is impossible to deny, however, that these innovative technologies raise serious questions about their compatibility with international, European, and national legislative frameworks, at least if we compare them with the original and most widely-used blockchain model (i.e., the so-called permissionless blockchain). Indeed, permissionless blockchains create a “law-free zone” resistant to any subsequent modification and judicial intervention. In this general context, this chapter aims to analyse the pros and cons of using blockchains and smart contracts in the context of copyright. It will also attempt to investigate possible legislative solutions at the national and supranational levels aimed at encouraging the use of these innovative technologies to the extent they are compatible with the existing regulatory framework.
Advanced reservation system

An important part of the institutions that provide the possibility of reserving spaces is certainly the reservation system. Within this paper, the analysis of reservation systems and subsequent implementation of the reservation system is presented. The reservation system was implemented in the form of a web application, which considered the findings from the analysis of available solutions. The created reservation system consists of two parts, namely the administration panel and the reservation form. The admin panel provides several features, such as managing rooms, reservations, services, calendar, creating forms, statistics, and more. At the same time, the system automates several processes, such as publishing events on a web page or displaying reservations, for example on televisions. Other automated tasks include document generation, data export, or automatic emailing. When creating the booking form, the emphasis was mainly on simplicity, user friendliness and at the same time providing several functionalities. The development of the application also considered security. The resulting system is deployed in a production environment and has become an important part of the UVP TECHNICOM organization, where it has made it possible to optimize several processes.
A Historical and Bibliometric Analysis of the Development of Agile

This chapter starts with a brief history of software development from a summary of traditional approaches and presents the conditions that led to agile approaches such as product complexity, shortened life cycle of the market and eventually to the widespread acceptance of Scrum. The authors then compare the narrative to the bibliometric analysis of abstract records that can be found in the Web of Science database. They parse the terms from the abstract records to identify research trends over time and map the underlying structure of agile research. Finally, they consider the future of Agile-Scrum in light of the current pandemic.
Quantum Criticality Driven by the Cavity Coupling in the Rabi-Dimer Model

The superradiant phase transition (SPT) controlled by the interacting strength between the two-level atom and the photons has been a hot topic in the Rabi model and the Rabi-dimer model. Thelatter describes two Rabi cavities coupled with an inter-cavity hopping parameter. Moreover, theSPT in the Rabi-dimer model is found to be the same universal class that in the Rabi model byinvestigating the correlation-length critical exponent. In this paper, we are concerned about whether theinter-cavity hopping parameter between two Rabi cavities (i.e., the Rabi-dimer model) will inducethe SPT and to which the universal class of the phase transition belongs. We analytically derive thephase boundary of the SPT and investigate the ground-state properties of the system. We uncoverthat the inter-cavity induced SPT can be intuitively reflected from the ground-state energy andthe ground-state photon population, as well as the ground-state expectation value of the squaredanti-symmetric mode. From the scaling analysis of the fidelity susceptibility, we numerically verifythat the SPT driven by the cavity coupling belongs to the same universal class as the one driven bythe atom-cavity interaction. Our work enriches the studies on the SPT and its critical behaviors inthe Rabi-dimer model.
An Interactive Data Imputation System

In this demonstration, we propose an interactive data imputation system, called DITS, built upon ten state-of-the-art imputation algorithms and a novel variational generative adversarial imputation network. It consists of three modules, namely source uploader, algorithm evaluation, and interactive imputation. In the source uploader module, DITS allows users to register new imputation and prediction algorithms. Then, DITS is able to make users more aware of various integrated imputation algorithms via algorithm evaluation module, so as to support both lay and power users to operate a customized data imputation for their target dataset via the interactive imputation module. Using a public incomplete meteorologic dataset, we demonstrate that, DITS is capable of assisting users to effectively address real-life missing data issues.
Investigation of Reading Convenience Factors Based on Graph Theory and Systems Analysis

Problems in the field of development and use of fonts are investigated, prospects of fonts development on various bases are analyzed. With the help of a graphical hierarchical model of the text reading ease factors priority influence, an expert selection of factors was made, the essence of which is related to the qualitative perception of the text. The formulation and solution of the problem are carried out using the means of graph theory and methods of systems analysis. Having established a set of factors through some set, a subset was chosen and the possible interaction between them was presented in the form of an indicative graph. The main task to solve this problem was the choice of factors for the ease of reading the text in electronic publications related to the actual relationship between them. The implementation of this method is provided on the basis of the existing acquisitions of systems analysis, modeling theory, research methodology, and problem-solving. To work out a complex system, the factors were divided into parts and organized as a hierarchical structure. If we consider a set of elements with a certain number of relationships between them, it is important to know the hierarchical structure of this set with the placement of elements on levels with greater or lesser dominance of some elements over others.
Are Social Media Users “Online” with Public Libraries?

This study explores the relationship between social media usage, the use of public libraries, and reading habits. The data were collected using a questionnaire that evaluates the profile of public library users, the use of social media platforms, and reading habits. A total of 222 valid answers were obtained. The results show that only 33.5% of the respondents are regular users of public libraries. The findings suggest that using social media negatively influences being a public library user who spends more time in social media at the expense of reading and using libraries. Since the number of users is a performance indicator for libraries, increased social media use could threaten their survival. However, social media can be an opportunity to reach current users to stimulate non-users to visit and change reading habits.
Contextual Personas - A Method for Capturing the Digital Work Environment of Users

It can be hard to understand the context in which a software system is used and how the whole work environment affects the usage of a particular system. In this project, we modified the Persona method to include aspects of the digital work environment and the context to extend the understanding of these aspects during software development. The modified version of the Persona method is based on the traditional Persona method, on theories on healthy work and research on the digital work environment. The objective of proposing the modifications of the method is to give software developers more insights into the complexity of the digital work environment. University students tried the modified Contextual Persona method in a user-centred software development course. Students worked on designing a new system for 12 weeks using the Contextual Persona method during the fourth week of software development. The students gave feedback on what positive and negative aspects they experienced while using the modified Contextual Persona method and their thoughts on how the method could be improved. In the paper, we analyse reports from 30 students and summarise the feedback gathered. We conclude by summarising the possible improvements to the method based on our findings.
Developing a Real-time Data Acquisition System to Prepare a 3D Accelerometer-based Air-writing Data Set of Bengali Characters

Air-writing is a method of converting hand gestures in 3-dimensional space into visual linguistic characters. Many data sets are available for motion sensor-based air-writing of English characters. However, there is no motion sensor-based air-writing data set is found for Bengali characters. This paper represents a real-time data acquisition system which is developed to prepare a motion sensor-based air-writing data set of Bengali characters. A portable device is developed to capture the motion of the hand during air-writing. Also, a MATLAB application is developed to collect the data from the portable device via Bluetooth. The application has the option to visualize, pre-process and analyze the collected air-writing data of a character before including it in the data set. Analysis is also done to justify the validity of data captured by the proposed system. This data acquisition system can be used to capture any type of hand gesture for preparing data sets or real-time gesture recognition.
A comprehensive study of data intelligence in the context of big data analytics

Modern systems like the Internet of Things, cloud computing, and sensor networks generate a huge data archive. The knowledge extraction from these huge archived data requires modified approaches in algorithm design techniques. The field of study in which analysis of such huge data is carried out is called big data analytics, which helps to optimize the performance with reduced cost and retrieves the information efficiently. The enhancement of traditional data analytics needs to modify to suit big data analytics because it may not manage huge amounts of data. The real thought is how to design the data mining algorithms suitable to handle big data analysis. This paper discusses data analytics at the initial level, to begin with, the insights about the analysis process for big data. Big data analytics have a current research edge in the knowledge extraction field. This paper highlights the challenges and problems associated with big data analysis and provide inner insights into several techniques and methods used.
Insulation Optimization System of Mixed Gas based on Intelligent Particle Swarm Optimization

Particle swarm optimization (PSO) is an intelligent evolutionary method, which is widely used to search the global optimal solution. However, in the early stage of the algorithm, the rapid flight of particle swarm to the current optimal solution may lead to premature convergence, while in the later stage of the algorithm, the convergence of most particles will lead to the decrease of particle swarm velocity. In this paper, the advantages and principles of IPSOA are discussed, and the insulation problem of mixed gas is discussed. By comparing the standard PSOA with the improved PSOA, the results show that the calculation result of the improved PSOA is close to the optimal value of the function itself, which proves that the improved PSOA has better optimization ability.
Impact Patterns of Combining Model Pruning and Continual Learning on Model Performance

Both model pruning and continual learning are essential for the wide range of the deployment of machine learning algorithms on mobile devices. However, the com-bination of the two may result in massive degradation of model performance. In this paper, we investigate the impact of combining different pruning and continual learning algorithms under different models and benchmarks and empirically ex-plain the reason for the impact. It can lay a foundation for future exploration of a better joint algorithm to deploy machine learning on mobile devices better. We first prune the pretrained models according to different prune methods and then run different continual learning algorithms on each pruned model. By comparing the evolvement of the test accuracies of each combination of pruning and continual learning methods under different scenarios, we find out that jointly using replay methods and unstructured methods is generally the best option with a small degree of difference among scenarios.
An Investigation and Examination of Privacy for Big Data

As the world is running over the digitization, it is absolutely unpredictable how much privacy of an individual is preserved. Because the data has to be published, shared in order to extract the knowledge by analyzing and processing. It leads to the breach of privacy which has been shielded by various privacy laws and regularity compliance. So, the privacy preserving is become more noticeable research domain. The big data privacy has been a topic of excessive concern and have not been studied much in broad. This paper studies the research outputs done in both application and theoretical sides of big data privacy. This paper discusses operations and roles of privacy systems, data clustering and privacy frameworks, perspective wise effort of privacy study along with the mathematical expressions to describe, measure and model privacy.
Design of Signal Control System for CRDM Microphone in NPP

In this paper, the CRDM microphone signal control system is designed for the convenience of nuclear power plant overhaul. The control system can select to control the transmission of microphone signal group in remote or local way according to the needs; In addition, the system is equipped with special connectors matching with corresponding equipment of RGL system. The electrical performance, test level and interface equipment level are consistent, so as to improve the test convenience and reliability; The mutual alarm function can be configured, and other alarm points can be expanded according to the requirements, which can help the site engineers of NPP to judge the status of the control box, and reduce the safety risk to the equipment on site in case of failure.
Advanced Encryption Schemes

Advanced encryption schemes include fully homomorphic encryption (FHE) and searchable encryption (SE), which is a particular case of FHE. More than a decade ago when it was introduced, fully homomorphic encryption was considered a revolutionary approach in cryptography, although privacy homomorphism was introduced in the late 1970s [1]. Both types of encryption schemes are important for today’s technologies as they correspond to the current cybersecurity needs. Both are mainly focused on technologies such as cloud computing.
Keyword-aware Multi-modal Enhancement Attention for Video Question Answering

Video question answering (VideoQA) is an intriguing topic in the field of visual language. Most of the current VideoQA models directly harness the global video information to answer questions. However, in VideoQA task, the answers associated with the questions merely appear in a few video contents, and other contents are invalid and redundant information. Therefore, VideoQA is vulnerable to be interfered by a large number of irrelevant contents. To address this challenge, we propose a Keyword-aware Multi-modal Enhancement Attention model for VideoQA. Specifically, a multi-factor keyword extraction (MFKE) algorithm is proposed to emphasize the crucial information in multimodal feature extraction. Furthermore, based on attention mechanisms, a keyword-aware enhancement attention (KAEA) module is designed to correlate the information associated with multiple modalities and fuse multimodal features. The experimental results on publicly available large VideoQA datasets, namely TVQA+ and LifeQA, demonstrate the effectiveness of our model.
Offline Handwritten Word Recognition of Devanagari Script

As we know that, recognizing words manually from a large handwritten document is a tedious task and challenging as it has different styles and strokes between characters. So, a system is needed to recognize words written in Devanagari script from documents via digitization or image processing techniques. So, for classification of words from documents either online or offline, different methods have been surveyed till now, then a new system can be utilized in an efficient way. This paper presents comparative detailed study of various techniques and work done by researchers in context of Devanagari script.
A PGAS-Based Implementation for the Parallel Minimum Spanning Tree Algorithm

The minimum spanning tree is a critical problem for many applications in network analysis, communication network design, and computer science. The parallel implementation of minimum spanning tree algorithms increases the simulation performance of large graph problems using high-performance computational resources. The minimum spanning tree algorithms generally use traditional parallel programming models for distributed and shared memory systems, like Massage Passing Interface or OpenMP. Furthermore, the partitioned global address space model offers new capabilities in the form of asynchronous computations on distributed shared memory, positively affecting the performance and scalability of the algorithms. The paper aims to present a new minimum spanning tree algorithm implemented in a partitioned global address space model. The experiments with diverse parameters have been conducted to study the efficiency of the asynchronous implementation of the algorithm.
Hardware Development of Portable Reader Based on ARM Processor

In order to reduce the power consumption of e-reader, improve its endurance and protect readers&#x2019; eye health, a portable e-reader based on E Ink technology is designed in this paper. Based on Raspberry CM3 + core board, chip selection, circuit principle design and PCB design is carefully carried out for this reader. In this paper, the embedded Linux development environment is built on the hardware equipment, the WiFi network card driver transplantation, E Ink transplantation and Koreader transplantation are carried out, and the GUI is developed by QT. After testing, it is proved that it has realized the basic functions of the reader.
Using a Box-Jenkins model for production factor forecasting in the radio-electronic industry

The need of improvement in the Russian Federation electronic industry enterprise competitiveness presents qualitatively new requirements to the instrumental means of economic analysis. To a certain extent, this applies to the problems of factor analysis. The paper suggests a method of using a Box-Jenkins model for possible production factor increment values forecasting. The paper contains interpretation of the results obtained. The proposed instrument of predictive factor analysis can be used in practice to support management decisions dealing with strategic development of industrial enterprises and increasing their economic efficiency.