Reviewerly/exHarmony huggingface dataset:
Managing Student Engagement in Higher Education Institutions: The Case of Curpa

The higher education world around us is changing fast. Mobile learning (M-learning) and apps in education are new and exciting. However, this does not mean that the faculty is less relevant. On the contrary, the faculty are an ever-important factor that is needed to increase student engagement. Disengaged students are in fact more problematic than low achieving students. This is because of the disruption disengaged student bring in the classroom. Therefore, increasing student engagement is a key challenge in higher education today. Research suggests that active learning, value and expectations are important factors that determine student engagement. Some of these factors can be indirectly influenced by the faculty and course designers. Against this background, the objective of this chapter is to examine if dwindling student engagement in higher education can be addressed with CURPA, i.e. a CURriculum and course planning (CURP) App. CURPA is the result of our efforts at Utrecht University to help design courses and curricula by using cards to account for different activities, with the strategic aim being to stimulate student engagement in higher education. Our expert interviews resulted in a MoSCoW-prioritised list of requirements that can be implemented over time, structured in line with Becker's student engagement model.
Tricubic Interpolation in Scientific Data Visualization Problems

The goal of the research is an exploration of the possible algorithm for science visualization problems in interpolation of the visualization arrays of subsets. The subject of the study is a tricubic spline interpolation method (cubic spline interpolation). The methodology of the research is a programming the work of the mathematical model on a c# language with the use of windows presentation forms for the presentation mode work. The results of the study and its' application are important for the science visualization in medicine for the DICOM computer tomography data. Moreover, the applications of the work are relevant for the interpolation of the particle physics interactions. In conclusion, numerical methods study the construction, application and theoretical substantiation of algorithms for the approximate solution of various classes of mathematical problems. Currently, most computational algorithms are focused on the use of high-speed computers. It should be noted some features of numerical methods. First, numerical methods are characterized by multiplicity, i.e., the ability to solve the same problem by various methods. Secondly, the newly emerging natural science problems and the rapid development of computing technology force us to overestimate the importance of existing algorithms and lead to the creation of new ones.
Graph Data Retrieval Algorithm for Knowledge Fragmentation

In this era of big data, data are diversified, strongly connected, fragmented, dynamic, and combined with dynamic knowledge fragments to optimize the distributed storage of graphs and enable fast and efficient knowledge graph query problems. Presently, the distributed storage scheme of graph data has a large number of hop accesses between partitions, which leads to a long retrieval response time and is not conducive to fragment knowledge expansion. According to the characteristics of real-time inflow knowledge fragments and the storage structure and principles of graph databases, the Metis+ algorithm is proposed. The label graph is used as the initial initialization segmentation graph, and it is roughened to reduce the cutting of the large-weight edge. The weighted LND algorithm is proposed to run the balancing strategy for storage and assign the similar nodes and closely related nodes to the same partition to the greatest extent, which minimizes jump accesses between the partitions during retrieval.
Characteristics of CAPTCHA

This chapter presents the core elements characterizing the analysis and study of a CAPTCHA test. Each element is introduced and described by its main features. Then, an overview of advantages and limitations in the context of the core elements regarding the CAPTCHA test is described. It is accomplished by shortly surveying on different relevant works concerning the CAPTCHA elements and previously introduced in the literature, together with their limitations. In the end, a summary of the main open questions about the presented literature is provided.
Target Tracking Based Upon Dominant Orientation Template and Kalman Filter

Due to the proliferationKumar, Nikhil of surveillance systems in defense as well as civilian sectorsDhakrey, Puran, target trackingKandpal, Neeta field has always remained adorable to researchers of the computer vision community. Template matching based approaches are a conventional way to solve target tracking problems. Ironically such approaches are computationally complex due to a requirement of repetitive arithmetic operations. A number of attempts have been made to reduce this computational overhead; Dominant Orientation Template (DOT) based template matching has given a new dimension to solve problems of such a kind using logical operations only. It has been observed that the performance of template matching based approaches degrades drastically in the presence of occlusion. DOT-based template matching is also not an exception to this. Proposed approach introduces a novel target tracking framework having severe occlusion handling capacity by integrating DOT-based template matching and Kalman Filtering. In the present approach, a small target search window is formulated around the Kalman estimated location of the considered frame; rather than exploring the whole frame. DOT-based template matching works inside this window only. A parameter known as Kalman error is defined here which is considered as the measure of occlusion. Initially, DOT calculated location is assumed as measured value but in case of occlusion when this Kalman error becomes sufficiently large the Kalman estimated location is regarded as the measurement. A customized dataset having occluded targets in FLIR as well as visible video sequences is generated to provide a robust testbed for the proposed approach.
Globally optimal page breaking with column balancing

The paper presents a dynamic programming algorithm that finds the globally optimal sequence of page breaks for a book avoiding widows and orphans when the only source of variation is the possibility to break selected paragraphs into varying number of lines by skillful selection of line breaks. The text is set in two-columns, on each last page of a chapter the columns must be balanced. We show how the balancing process can be included in the global optimization.
Designing Curated Conversation-Driven Explanations for Communicating Complex Technical Concepts

The need for learning about emerging technologies and technical concepts among the general population is increasing, but formal explanations from online encyclopedias, textbooks, and articles are often rich in technical jargon and can be challenging to grasp. In this paper, we explore a novel approach for explaining technical concepts to non-technical users through the design of JargonLite, an interactive dictionary that shows how technical concepts can be used in everyday conversations. We evaluated curated conversation-driven explanations with 12 users who had little or no technical training and wanted to learn about big data concepts. We found that users perceived conversation-driven explanations to be easy to understand and these explanations helped them to maintain focus. We discuss the potential of using conversation-driven explanations as a learning tool for non-technical users and reflect on the advantages and disadvantages of this approach.
A Method for User Avatar Authenticity Based on Multi-feature Fusion

Social media provides users with a platform for information sharing and communication. At the same time, there are a large proportion of users use a fake avatar. We attempt to automatically discriminate the authenticity of the user’s uploaded person avatar based on the machine learning method. In this paper, an avatar authenticity discrimination method based on multi-feature fusion is proposed by combining user-based features, avatar features, and text-based features. We use deep learning, image recognition and topic model techniques to process features. The method is verified on the Sina Weibo data set. The experimental results show that the method can achieve 84.1% accuracy.
Temporal Recommendations for Discovering Author Interests

With the advancements in technology, a rich amount of research content is available on the web that creates the situation of a dilemma for the researchers to choose the most appropriate and trending topic for further research that has a wide scope in future too. The prediction of authors' interests has always been a challenging task as interests might change with time. This demands the need for an efficient temporal recommender system that takes into account the drifting interests of users too. This study addresses this major challenge and analyses the authors' interests based on similar authors' interests and their own long-term and short-term interests. The proposed model extends the latent Dirichlet allocation (LDA) model to capture the temporal aspects and utilizes latent semantic analysis (LSA) method along with the word-net feature to incorporate the semantic understanding of the topics with time. The model is implemented on a real NIPS dataset to a collection of 2000 conference papers. The empirical analysis validates that the proposed model achieves an accuracy of about 62% in predictions of the future authors' interests due to the fusion of long-term and short-term interests.
Utilization of Work-Family Balance Support Policy and Factors Associated with Retention Intention among Married Female Officers with Preschool Children

This study aimed to identify utilization of the work-family support policy (WFSP) and factors affecting retention intention among Korean female military officers.This cross-sectional survey recruited 103 married female officers from the Korean Army, Navy, and Air force with preschool-aged children through convenience and snowball sampling. Via online surveys from June to November, 2018, the participants self-reported retention intention, work-family conflict, job satisfaction, and utilization of the WFSP. The data were analyzed using descriptive statistics, independent t-tests, one-way analysis of variance, Pearson's correlation coefficient, and multiple linear regression.Retention intention (22.29±5.98) was reported at the mid-level, lower than scores reported in the literature for female workers. Work-family conflict (32.51±5.29) and job satisfaction (63.10±7.45) were above the midpoint levels. Use of maternity leave (100.0%) and parental leave (92.2%) was high, especially compared to the rates of child-care day off (20.4%) and parenting time (20.4%). 'Noticeable increases in childcare services within the army' (22.8%) was reported as the supportive measure needed the most by female military officers. Job satisfaction (β=.43, p≤.001), the use of parenting time (β=-0.29, p=.002), living type (β=-.18, p=.043), and service type (β=-.16, p=.035) significantly influenced retention intention. CONCLUSIONS: The findings highlight the priority areas of importance within the WFSP and suggest that a family-friendly culture can improve female officers' retention intention. Accordingly, policy changes at the Ministry of National Defense improving the system to enhance a family-friendly culture in the military is expected to strengthen the retention intention of female officers and contribute to excellence in the military workforce.
An Infrastructure-Agnostic Model of Hypertext

This short paper summarizes a new interpretation of the original vision of hypertext: infrastructure-agnostic hypertext is independent from specific formats and protocols. References to existing technologies for implementations are included nevertheless.
Possibilities of Applying the Foreign Experience in Regulation of Digital Currency Circulation in Russia

The research is devoted to the study of the phenomenon of digital currencies and their circulation in the world. The work contains a theoretical part explaining the basic terminology associated with digital assetsDigital assets and in particular digital currencies or cryptocurrencies. Based on the study of federal laws, periodical Russian and foreign publications, as well as internet resources, the key points of the legal status of digital currencies and their circulation in Japan, Australia, and the USA were considered. The authors also studied Russia’s current position on the legalization of virtual currencies in the country. The result of the work is the formation of assumptions about the future legal status and regulation of the circulation of digital currencies in Russia and the assessment of the possibility of using some aspects of the legal regulation of these foreign countries in Russian practice. The main goal of this research is to explore how cryptocurrencyCryptocurrency is regulated in foreign countries and to mention the possibilities of using their experience in a field of Russian laws.
Quantum implementation of the Shor-code on multiple simulator platforms

Running general quantum algorithms on quantum computers is hard, especially in the early stage of development of the quantum computer that we are in today. Many resources are required to transform a general problem to be run on a quantum computer, for instance to satisfy the topology constraints of the quantum hardware. Furthermore, quantum computers need to operate at temperatures close to absolute zero, and hence resources are required to keep the quantum hardware at that level. Therefore, simulating small instances of a quantum algorithm is often preferred over running it on actual quantum hardware. This is both cheaper and gives debugging capabilities which are unavailable on actual quantum hardware, such as the evaluation of the full quantum state, at intermediate points in the algorithm as well as at the end of the algorithm. By simulating small instances of quantum algorithms, the quantum algorithm can be checked for errors and be debugged before implementing and running it on actual quantum hardware for larger instances. There are multiple initiatives to create quantum simulators and while looking alike, there are difference among them. In this work we compare seven often used quantum simulators offered by various parties by implementing the Shor-code, an error-correcting technique. The Shor-code can detect and correct all single qubit errors in a quantum circuit. For most multi-qubit errors, correct detection and correction is not possible. We compare the seven quantum simulators on different aspects, such as how easy it is to implement the Shor-code, what its capabilities are regarding translation to actual quantum hardware and what the possibilities of simulating noise are. We also discuss aspects such as topology restrictions and the programming interface.
Image Encryption Technique Based on Hybridized DNA Cryptography and Compressive Sensing Algorithm

The hybridization of DNA with compressive sensing techniques is an open area of research. This paper has focused on compressive sensing technique and DNA cryptographic operations which are used for compressing and encrypting together for an image. Usually, the image encryption techniques has more focused towards the providing security while there is a still room for an improvement in computational speed. An efficient approach for achieving higher information security at fast speed can be termed as “image encryption using hybridized DNA cryptography and compressive sensing”. The plain image is measured by measurement matrices in two directions to compress and encrypt the image. Then DNA sequence operations are performed on the resultant image for further security. These DNA sequence operations include DNA addition and subtraction using DNA coding rules. The sequences worked under the control of 2D logistic map. Hence, the proposed technique is capable of providing security quickly as compared to existing technique.
Graded Possibilistic Meta Clustering

Meta clustering starts from different clusterings ofFerone, Alessio the same data and aims to group them, reducing the complexity of the choice of the best partitioning and the number ofMaratea, Antonio alternatives to compare. Starting from a collection of single feature clusterings, a graded possibilistic medoid meta clustering algorithm is proposed in this paper, exploiting the soft transition from probabilistic to possibilistic memberships in a way that produces more compact and separated clusters with respect to other medoid-based algorithms. The performance of the algorithm has been evaluated on six publicly available data sets over three medoid-based competitors, yielding promising results.
Supporting decisions with fast and frugal trees for improving trust in public housing services

Maintaining usability and trust of electronic public services is an important topic of research in e-government field. In this paper, we address the problem of identifying descriptive characteristics of clients that, when offered a choice to select between submitting an electronic application form and a paper form, decided not to use the electronic form submission channels due to the lack of trust in the internet technologies. The underlying assumption was that such clients generally perceived electronic services as superfluous digital disruption rather than adding new value. We based our analysis on responses to a survey among the clients of a public service in a tender for buying or renting housing facilities. We demonstrate that the identified characteristics hierarchically organized in the form of a fast and frugal tree can provide classification models for effective real-world decision making to identify delicate citizen groups that might require a more focused communication strategy to reduce the risks of potential electronic services dropouts.
Domain-driven analysis of architecture reconstruction methods

Abstract Software architecture reconstruction (SAR) is a process which aims to obtain the architecture information of any system using various sources. These sources contain documentations, logs, codes, and stakeholder concerns. Various automated and manual approaches have been proposed in the literature for SAR. Manual architecture reconstruction is usually time consuming, costly, error-prone, and complex. Hence different studies have addressed these problems by proposing automatized methods and tools for SAR. In this chapter we present a systematic characterization of the published architecture reconstruction methods. We apply a domain analysis process in which we first define the generic domain model of architecture reconstruction. The model is represented as a set of key terms, a generic business process model, and a feature diagram that represents the common and variant features of architecture reconstruction. We also present the method for deriving concrete architecture reconstruction methods from the generic domain model. We illustrate our approach for deriving two different concrete architecture reconstruction methods.
Evaluation of Power Analysis Attacks on Cryptographic Circuit Using Adiabatic Logic

This paper presents the post-layout simulation of our proposed Current Pass Optimized (CPO) adiabatic logic for cryptographic circuit. By using dummy transistors in the input function, CPO-adiabatic logic circuit consumes uniform current irrespective of the input data being processed; therefore CPO-adiabatic logic is more resistant to differential power analysis attacks than the conventional secure adiabatic logic families. To evaluate the circuit performance, we compare the post-layout simulation results of CPO-SPGAL and CPO-EE-SPFAL GF(2^4) multiplier. From the simulation results we illustrate that the CPO-EE-SPFAL is a secure logic compared with CPO-SPGAL.
Synthesis of human facial expressions based on the distribution of elastic force applied by control points

Synthesis of human facial expressions based on the distribution of elastic force applied by control points
Transforming a Specialized Q&amp;A System to a Chatbot System: A Case of a Simplified Taxation in Korea

In this paper, we propose a way to transform traditional Q&As into conversational Q&As for an efficient information retrieval in special knowledge. Special knowledge involves difficult words. It requires users to raise a series of questions and get the answers to them to pinpoint the desired information. And, conversational Q&A is appropriate than the traditional Q&A because it allows a user to narrow down searches in a solution space. To transform a given set of Q&As to conversational Q&A system for special knowledge search, we first explore not only the present traditional Q&A systems and conversational Q&A systems for general knowledge search, but also those for special knowledge search. From this, we induce an appropriate search process in conversational Q&A systems for special knowledge. Secondly, we build an ontology with the help of machine learning to support the navigation in special knowledge. Finally, we give a way to evaluate performance after embedding the ontology on our search process of conversational Q&A. We apply this procedure to the case of Korean simplified taxation in a Korean Q&A system, Naver Jisik-In Q&A. We found that searching through Jisik-In Q&A with ontology has better usability than using Jisik-In Q&A only. Therefore, this study aims to improve the usability of special knowledge search, lower the threshold of special knowledge, and develop special knowledge as general as common knowledge using conversational Q&A based on ontology. However, as the number of user experimented is limited and the classifier for the extracted words from existing Q&A system should be reviewed by tax expert, so the future work is demanded.
Optimization methods of the industrial robots’ trajectory

Abstract In this paper, we present a part of our wider research regarding modeling, simulation and optimization of the trajectory of the industrial robots. After a short introduction on the importance of the industrial robots, the necessity and widely interest regarding the trajectory optimization, we present a classification of the optimization methods: numerical, computational and hybrid. Then, we make a brief presentation of the main optimization criteria approached in the last few years in several scientific papers, regarding the optimization of the industrial robots’ trajectory.