Reviewerly/exHarmony huggingface dataset:
Using low-level optical flow to efficiently identify the driving state in automatic driving

The analysis of driving status has always been one of the important research directions in the field of autonomous driving. With the development of deep learning, convolutional neural networks have become a hot spot in optical flow computing technology. This article mainly describes the difference between the calculation method of optical flow in deep learning and low-level optical flow calculation, and uses a low-level optical flow algorithm to realize more accurate and efficient analysis, calculation, and recognition of the driving state of autonomous driving based on the data in the KITTI database. Finally, it summarizes the existing problems and puts forward ideas.
4. Data Analysis of Case Study Examples

The research described in this book searches for the answers on how learners learn in todays open and networked learning environments and how learners, educators, institutions, and researchers can best support this process. There is sufficient data available on virtual learning environments, provided by learning analytics, on student and teacher behaviour and performance, but there is no common practice among teachers in higher education for using this data to improve the learning and teaching process. Learning analytics and data may inform and improve open and online learning from the point of view of teacher and learner awareness about their behaviour and their learning and teaching methods. The idea of describing learning analytics as a metacognitive tool, suggesting a development of metacognitive decision-making skills in teacher education, and focusing on learning design in higher education by using data from learning analytics served as the main focus of this research. The aim of the research was to create the model of application of learning analytics method as a metacognitive tool to enhance student success. The aim of the research was reached through theoretical and empirical objectives, namely: describing the learning analytics method as a metacognitive tool; revealing teacher metacognitive practices
Scientific comparative analysis of professional self-development of future social pedagogue In Kazakstan and abroad

The paper deals with the scientific analysis in the sphere of social and pedagogical education and with the professional self-development of future teachers. In the paper the structure of the professional development that introduces the interconnection of the four members is presented: self-identification, self-esteem, self-determination, self-government. Attention is focused on the integrity of the system of self-development of a social pedagogue as a competent specialist, who also possesses a set of general culture of personality with professionally significant qualities.The theoretical bases of social and pedagogical support, its essence and content are considered. The role of practice as an integrative component of the professional development of a specialist is emphasized. The necessity of introducing the self-development trajectory in the educational process for successful professional formation of a future social teacher is acknowledged. The paper is intended for researchers and educators involved in the training of future social pedagogues.&#x0D; &#x0D; Keywords: professional self-development, social pedagogue, self-development trajectory;
Analysis on Trends in Applied Research of Cognitive Linguistics -Focusing on Dissertations of Korean Linguistics, Contrastive Linguistics, Korean Language Education, and Korean Language Education as a Foreign Language-

This research focuses on dissertations and analyzes research trends in the fields of Korean linguistics, contrastive linguistics, Korean language education, and Korean language education as a foreign language. Based on the results of the study, the application direction of cognitive linguistics theory in the future of Korean language education as a foreign language research is proposed. First, a total of 193 dissertations were collected, and their analysis criteria were divided into four categories: annual, research theme, research object and research method. In order to ensure feasibility, the papers were analyzed according to the criteria. Finally, some suggestions are made for the future research direction of cognitive linguistics in the field of Korean language education as a foreign language. Through this study, it will be possible to have an overall perspective of the coordinates of cognitive linguistics in the field of Korean education as a foreign language in the future, and a qualitative leap in research will be enabled. In addition, the study of trends based on the four criteria in this paper will serve as a meaningful reference for graduate students who are planning their dissertations in Korean language education as a foreign language in the future. (Seoul National University)
Deep Learning on Graphs: An Introduction

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Harvesting Publication Data to the Institutional Repository from Scopus, Dimensions and Unpaywall

Join us for ETD2021 (Electronic Theses and Dissertations) Conference in November 2021 in the United Arab Emirates. Our theme, ‘Open scholarship in a post-pandemic world’ addresses the enhanced need for discoverability of research findings in a virtual world. Since the global impact of the COVID-19 pandemic has constrained international travel and mobility, we have all come to rely on working in the virtual world. These developments have merely accelerated the existing trends towards more electronic and digital repositories. Since 1991, the Networked Digital Libraries of Theses and Dissertations (NDLTD) have contributed to research collaboration by identifying and aggregating digital repositories of theses and dissertations as a previously fugitive class of research resources.
INVESTIGATION OF THE EFFECTS OF USING AUGMENTED REALITY APPS ON STUDENTS' LEARNING ACHIEVEMENT AND MOTIVATION IN ENGINEERING DRAWING COURSES

In engineering education Virtual Reality (VR) and Augmented Reality (AR) technologies have been recently adopted in the teaching of technical subjects showing good potential for visual interaction with the objects. This study aims to investigate the effect of using a specifically developed mobile AR Engineering Drawing (ED) application (Apps) for improving the cognitive learning levels of students and learning achievement. In this study, experimental design with pre-test and post-test control groups and interview were used to measure of participants’ success. For this purpose, a total of 30 participants involved in the experimental group used AR application for training, whereas another 20 participants without AR training were kept as a control group. The increase in performance between pre-test and post-test was 39.7% for the experimental group and 17.2% for the control group. The results indicated a 19.6% higher learning performance in the experimental group through the use of the AR application for training. This result shows the very important effect the mobile AR engineering drawing application had in terms of acquiring new knowledge and skills on the participants. The study also shows that teaching Engineering Drawing subjects using AR Apps significantly increases students' conceptual and cognitive comprehension levels.
Controlling the Flow

The previous chapters have covered ways to create statements, and what operators to use depending on the operand types. Sometimes in the previous chapters elements of logic were added to make the code runnable for you, and this chapter is dedicated to explaining in detail how you can manipulate the execution of your code using fundamental programming conditional and repetitive statements. A solution, an algorithm can be represented using flow charts.
Writing Proficiency Assessment: Regression Analysis of Item Response Theory supported by Machine Learning Techniques

A subject's ability to express himself demonstrates his ability to understand reality. Text production is a way to verify the proficiency of such a skill. This correlation can help in the teaching-learning process since the learning diagnosis depends on the identification of possible instructional gaps, which subsidize the composition of better teaching strategies. In this article, we present an approach to characterizing learning profiles and estimating grades in the assessment of writing tests. For that, we used item response theory and machine learning techniques in the dataset of test scores of the Exame Nacional do Ensino Médio carried out in 2019. The results show that using a portion of only 2k training instances of the 3; 7M instances and only one of the five competencies evaluated, it is possible to have a correct prediction of the skill with a p-value 0:06 and pearson correlation of 0:94. Our approach shows the benefits of employing such techniques in a real-world scenario.
Gaussian Process to Identify Hydrogel Constitutive Model

Unlike traditional structural materials, soft solids can often sustain very large deformation before failure, and many exhibit nonlinear viscoelastic behavior. Modeling nonlinear viscoelasticity is a challenging problem for a number of reasons. In particular, a large number of material parameters are needed to capture material response and validation of models can be hindered by limited amounts of experimental data available. We have developed a Gaussian Process (GP) approach to determine the material parameters of a constitutive model describing the mechanical behavior of a soft, viscoelastic PVA hydrogel. A large number of stress histories generated by the constitutive model constitute the training sets. The low-rank representations of stress histories by Singular Value Decomposition (SVD) are taken to be random variables which can be modeled via Gaussian Processes with respect to the material parameters of the constitutive model. We obtain optimal material parameters by minimizing an objective function over the input set. We find that there are many good sets of parameters. Further the process reveals relationships between the model parameters. Results so far show that GP has great potential in fitting constitutive models.
2-step Clustering for Innovative Activities in Korean Service Enterprises

We classified the types of innovative activities of Korean service enterprises with a two-stage clustering method using the Ward and K-means methods, and analyzed the characteristics of each type. The innovation types of Korean service companies were classified into three types: internal concentration, market concentration, and opportunity exploration. The proportion of service enterprises according to the three types of innovation was 65.9%, 17.2% and 16.8% in 2014, 7.3%, 21.3% and 71.4% in 2016, and 19.8%, 18.3% and 61.9% in 2018. The proportion of internal concentration decreased, the proportion of market concentration remained, and the proportion of opportunity exploration increased. In addition, we analyzed the characteristics of each type of innovation activity in three aspects: input, process and outcome. Korean service enterprises were found to invest the most in internal R&D, while market concentration and opportunity exploration types were analyzed to carry out similar types of innovative activities. The type of innovation that adopted the most process innovation techniques was opportunity exploration, and the number of patent applications, opportunity exploration companies performed the most actively, but were not statistically significant. The results of this study are expected to be used as a basis for in-depth research into innovative activities of service enterprises.
Exploiting social media for fake reviews

We provide an overview of our recent work that studies the market for fake product reviews on Amazon.com where reviews are purchased in large private internet groups on Facebook and other sites. We find that a wide array of products purchase fake reviews, including products with many reviews and high average ratings. Buying fake reviews on Facebook is associated with a significant but short-term increase in average rating and number of reviews. We exploit a sharp but temporary policy shift by Amazon to show that rating manipulation has a large causal effect on sales. Finally, we examine whether rating manipulation harms consumers or whether it is mostly used by high-quality or young products in a manner akin to advertising. We find that after firms stop buying fake reviews, their average ratings fall and the share of one-star reviews increases significantly, particularly for young products, indicating rating manipulation is mostly used by low-quality products and is deceiving and harming consumers.
Research and Implementation of Electronic Medical Record System Based on Blockchain

In order to solve the problem of low efficiency and information islands in the traditional electronic medical record system, this paper designs an electronic medical record system based on Hyperledger Fabric. The system is based on the blockchain distributed storage mechanism, which effectively overcomes the problem of information blockage between different hospitals and low processing efficiency, and realizes the secondary use of data. At the same time, the decentralized nature of the blockchain architecture ensures the transparency and immutability of medical record information, which greatly improves the security of the system, ensures the privacy and security of patients and the authenticity of medical information in the context of media convergence to a certain extent. It is of great significance to the treatment process of patients and the development of medical technology as well as society.
A study on the educational applicability of Chinese animation: Focusing on vocabulary analysis of [Big Fish &amp; Begonia].

Learning Chinese through animation can be of great help to balanced language learning as you can access not only language but also culture. This study extracted and analyzed the vocabulary of the July 8th, 2016 Chinese animation [Big Fish & Begonia] as evaluated by HSK grade. Among the total number of vocabularies and expressions observed, the average proportion of the ‘basic HSK’ grade vocabulary is 53.95% and the average proportion of the ‘modified HSK’ grade vocabulary is 96.98%, which is very meaningful in learning. The composition ratio of HSK grade for each section was generally constant and the difficulty was constant. The animation [Big Fish & Begonia] contains various vocabulary for learning Chinese and is an educational content that embodies the cultural colors and characteristics of China well for children and adult learners in the early stages of learning Chinese. A very positive educational effect can be expected for the development of Chinese language skills, and the possibility of its use is also very high.
Constraint Programming for Itemset Mining with Multiple Minimum Supports

The problem of discovering frequent itemsets including rare ones has received a great deal of attention. The mining process needs to be flexible enough to extract frequent and rare regularities at once. On the other hand, it has recently been shown that constraint programming is a flexible way to tackle data mining tasks. In this paper, we propose a constraint programming approach for mining itemsets with multiple minimum supports. Our approach provides the user with the possibility to express any kind of constraints on the minimum item supports. An experimental analysis shows the practical effectiveness of our approach compared to the state of the art.
A design of self-assessment model using AI chatbot and its application into primary English class

The purpose of this study is to design a self-assessment model and put it into primary English class. This study also aims to investigate not only how teachers perceive the selfassessment they currently use but how students see new self-assessment using AI chatbots. To the research, a model of self-assessment using an AI chatbot was designed and implemented by considering the teaching schedule and the assessment context of the school. A survey was also conducted to gain what the teachers believed regarding the self-assessment, then a meta-cognition questionnaire including interview questions was constructed to obtain what the students did and what they perceived while assessing themselves. According to the results of the study, the self-assessments operated properly. The participant teachers neither use self-assessment as a major assessment method nor utilize it for school records as they believed that the result of the student self-assessment would be subjective and unreliable. However, the results of the study indicate that students are able to play a role as an assessor with an appropriately developed rating scale and careful guidance. The students also used their meta-cognitive strategies properly while doing the assessment. Some implications are presented in the last part of the study.
Welcome Note and Opening Presentations: Dr Edward Fox, Founder and Chairman of NDTLD

Join us for ETD2021 (Electronic Theses and Dissertations) Conference in November 2021 in the United Arab Emirates. Our theme, ‘Open scholarship in a post-pandemic world’ addresses the enhanced need for discoverability of research findings in a virtual world. Since the global impact of the COVID-19 pandemic has constrained international travel and mobility, we have all come to rely on working in the virtual world. These developments have merely accelerated the existing trends towards more electronic and digital repositories. Since 1991, the Networked Digital Libraries of Theses and Dissertations (NDLTD) have contributed to research collaboration by identifying and aggregating digital repositories of theses and dissertations as a previously fugitive class of research resources.
Regression

A regression problem requires you to infer/predict a quantity corresponding to a new observation based on the values of some observed attributes. The problems we briefly discussed in Chapter 1 which aimed at predicting the salary of a person based on their experience and predicting the amount of rainfall based on the temperature, pressure, etc., were both examples of regression problems.
Belief Revision

This chapter first introduces the AGM theory of belief revision. Then it focuses on the problem of iterated belief revisions.
AI Ethics, Biasness, and Reliability

This chapter covers different frameworks using Explainable Artificial Intelligence (XAI) Python libraries to control biasness, execute the principles of reliability, and maintain ethics while generating predictions. As digitalization progresses touch different industries, they open up a whole new set of opportunities for the application of artificial intelligence and machine learning-related solutions. The major challenges with the adoption of these AI technologies are ethics, biasness, and the reliability of the system, plus the transparency of the processes. These AI systems raise fundamental questions. Can I trust the predictions made by the AI system? Can I assume that it is unbiased? What kind of risk does it have? Is there any process where I can control the AI systems and their predictions about the future? AI ethics focus more on the legitimate use of AI for human kind and their wellness. AI should not be used for the destruction of human civilization. In this chapter, we are going to discuss various aspects of AI.
A Study on Instructional Design of Genre Education for Thesis using Genre Analysis

The purpose of this study was to design a instruction of thesis genre education for foreign graduate students accounting for largest portion of academic writings. For the purpose, After reviewing major theories by Swales(1990) such as genre concept, moves and steps, genre analysis, and CaRS model and considering the curriculum of domestic graduate school curriculum, principles of instructional design were derived. In this process, acknowledging criticism that the major theories by Swales(1990) are merely applied in a guiding role in the pre-instructional stage the tasks were used to ensure that the major concepts by Swales(1990) are applied throughout the lecture. The tasks included genre analysis of theses by seniors, genre analysis of journal articles from high-rank academic journals, genre analysis of one’s own theses, and discussion for Discovery Learning. These tasks were designed to help them to understand genre-specific features of specific academic writing such as rhetorical organization and lexico-grammatical features of thesis. It is hoped that active research on writing and education that satisfies the needs of foreign graduate students will help ‘creating a gap of study’ and improving the quality of texts. (Dongguk University)
Quem@PUC - A tool to find researchers at PUC-Rio

Quem@PUC is an Information Retrieval System available on the Web that allows searching for researchers and professors based on a keyword list of research related terms. It publicizes research and teaching activities from the PUC-Rio community to society in general. The idea is to integrate information from professors from administrative systems, courses offered, and researchers’ Lattes CVs. Data sources are converted to RDF format using domain ontologies, then stored in a NoSQL database that supports native free-text indexing on triple objects. Search results include names, academic papers, teaching activities, and contact links.
On My Own: Acquiring Technical Digital Skills for Mobile Phone Use in Chile. Parents-children Perceptions

Despite its relevance, the difficulty in reaching consensus on the definition of digital competence slows down its implementation.The need of prior development of specific skills to advance in digital development has been recently reported.The acquisition of skills involves making the most of the opportunities offered by the digital environment.This article shows the results from a research conducted on 501 parent-child dyads in Chile in which minors aged 10 to 14 reported their self-perceptions on who (parents, siblings and peers) taught them certain technical and operational digital skills on mobile devices.Parents were also surveyed to know their perception about this children's social mediation.Socio-demographic variables are also analysed.Chilean minors have a clear perception of autonomy in the acquisition of digital competence, parents underestimate their ability to influence, and other socialization agents such as siblings play a significant role.Age, gender and socioeconomic level to a lesser extent mark differences in the acquisition of these skills.In addition to providing a comparison on the perception parents and children have on the extent to which minors are accompanied while on their mobile phone, the article goes beyond parental mediation strategies and collects parental reflections on types of mediation.
Model-Agnostic Explanations by Identifying Prediction Invariance

The invariant terminology taken from the field of mathematics explains that predictions generated by a machine learning model remain unchanged if we intervene with the explanatory variables, given the fact that the model is generated through a formal causal relationship. There is a difference between the causal machine learning model and the non-causal machine learning model. The causal model shows a real cause-and-effect relationship between the response variable and the explanatory variables. The non-causal modal model shows an accidental relationship; the predictions do change many times. The only way to understand the difference between the causal and non-causal models is through explanations. In this chapter, you are going to use a Python library named Alibi to generate model-agnostic explanations.