Reviewerly/exHarmony huggingface dataset:
Flight delay classification warning based on evolutionary under-sampling bagging ensemble learning

With the continuous development of civil aviation, flight delay prediction has become an urgent problem to be solved. However, the class imbalance of the data makes it difficult for us to predict flight delays accurately, and flight delay prediction models constructed by single machine learning algorithms are usually unstable. To solve these problems, in this paper, we proposed a flight delay early warning model based on EUS-Bag algorithm, combining under-sampling and ensemble learning, which can overcome the information loss problem of under-sampling and ensure the performance of each individual classifier in ensemble learning. Experiments on the real flight delay data show that our model can generate more diversified individual classifiers and achieve better performance.
Training Methods for Phishing Detection

Everyone has a responsibility to educate themselves on phishing so that they can recognize and track phishing attacks. Since we live in a digital age, attackers have endless opportunities to alter the information systems of individuals, government institutions, and even major enterprises. As a result, it’s only reasonable to rely on cybersecurity to ensure that relevant systems and data are accessible and secure when needed.
A Distributed Multiple Projector-Camera System

We propose a novel distributed multiple projector-camera system for projecting contents onto a plane surface such as a wall in various environments. The proposed system is composed of mobile Projector-Camera Terminals (PCTs) held by individual users. In each PCT, an agent installed on it controls its projection while cooperating with the agents of other neighboring PCTs. Through the cooperation of the agents, contents are shared among them, and each content is projected separately from a suitable PCT in the appropriate position to project it onto a projection surface. By sharing contents projection among suitable PCTs, this system covers a necessary area on the projection surface, improves the resolution of contents projected onto the surface, and reduces shadows on the projected contents, even if the PCTs move, some of them withdraw, or new ones join in.
Analysis for Implementing Power-Efficient Convolutional Operators on FPGA Platforms

Recently, research on FPGA-based accelerators for deep learning models has been actively conducted to overcome problems of GPUs such as power consumption, size, and price. FPGAs have the characteristic that hardware resource and power consumption vary depending on how the target logic is configured. This paper proposes a more power-efficient FPGA implementation method by analyzing the hardware resource and power consumption according to the implementation method and precision of the convolution operator, which is the core operation of CNN. As a result, proper utilization of DSP can increase the power efficiency of the convolution operator in FPGA design, and optimal CNN accelerator design is possible through a well-balanced implementation that considers the hardware resources required for the implementation of various operations other than the convolution operation (e.g., batch-normalization, activation function).
Explainability for Ensemble Models

Ensemble models are a group of models where the predictions are aggregated using some metric in order to generate a final prediction. As an example, a group of tree-based models can be developed to predict a real valued output, like a regression model. The predictions from all of the trees are averaged and taken for the final output. In a similar way, classification models generate individual class predictions and then take a voting rule. The class with the highest number is taken as final output. The ensemble models are not only difficult to interpret but also difficult to explain to the end user. Consider a scenario where four trees predict Yes, and six trees predict No; we will consider No as the final answer based on the majority rule of 6/4. Here it is hard to explain to the end user why some models predicted yes. Hence it is very important to explain the ensemble models. In this chapter, you are going to use SHAP predominantly to explain ensemble model predictions.
Critical Reflection on the Current Liberal Education Focusing on Creativity and Convergence Competency Enhancement

The University Basic Capability Evaluation conducted nationwide in 2021 made a huge impact on the formation of university curricula. The number of institutions in Korean higher education has rapidly increased during the past four decades, which resulted in the reshuffling of college education per se. Korean universities no longer exist only for social elites; rather they have continuously expanded reaching out to the nation’s broader population. Meanwhile, academic capitalism has come to prevail over higher education in Korea as it does in the US. As the number of college applicants continues to decrease, Korean universities are facing greater pressure from the market and the government alike. In particular, the Ministry of Education looms large as the sole arbiter of their institutional reputation and national funding by evaluating universities. To meet the requirements of the University Basic Capability Evaluation, university administrators have worked hard to create a “Creativity and Convergence Competency Enhancement Curriculum” within the existing framework of liberal arts curriculum. Generally, convergence education in Korea means interdisciplinary eduction. However, many interdisciplinary courses in liberal arts divisions, created in response to the pressure of the government-led evaluation, have exposed many limitations and shortcomings primarity due to the uncertainty of the definition, goal and efficacy of those courses. One possible solution to the problems is to remove the strict division in a credit ditribution system between liberal arts courses and major courses while continuing to build a meaningful bridge between them in a more flexible manner. Another solution is to revise the current government evaluation guidelines in a way that better reflects and increases the diversity of university education.
Robust Graph Neural Networks

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The Application of Correction Algorithm in the Improvement of Accuracy of English Translation Software

In order to improve the translation accuracy of English translation software, this paper will carry out relevant research, mainly discuss the current situation of the accuracy of English translation software, demonstrate the necessity of improving its accuracy, and then put forward the corresponding correction algorithm, introduce the basic model of the algorithm, and finally demonstrate the feasibility of the algorithm. The results show that the algorithm can correct the errors in translation results, so it can improve the accuracy of translation and facilitate the optimization of English translation software.
The Effect of Performance Feedback on Firms’ Decision to Form an International Strategic Alliance and Performance in the Korean Manufacturing Industry

Purpose &#8211; International strategic alliance has been regarded as a strategic decision made by firms’ managerial problems and ensure performance growth. From the perspective of the proactive behavior for changing strategies in a global market, this study aims to identify whether performance feedback influences firms’ decisions to pursue strategic alliances. This study examines the effects of perfor&#65534;mance feedback on performance when firms use strategic alliances. Design/methodology &#8211; To analyze the impact of performance feedback on forming an international strategic alliance, this study adopt the concept of performance feedback to develop a research model and our hypotheses. Thus, this study used a two-stage least squares unbalanced panel data analysis with random effects. This study is based on 24,543 observations from Korean manufacturing firms from 2007 to 2016. Findings &#8211; The results show that firms pursue the formation of strategic alliances more actively, if their past financial and R&D performance are lower than their aspiration level, based on the result of performance feedback. An in split sample analysis for examining the effect of a firm’s technology sophistication based on the OECD’s classification, negative innovation performance discrepancy has positive effects on the probability of international alliance in high-tech and medium-high-tech industries. Financial performance also improves when a firm decides to form a strategic alliance based on the results of performance feedback. Originality/value &#8211; This research extends recent efforts to better understand the effect of performance feedback on firms’ performance when they use strategic alliances. These findings suggest that the CEOs and managers of firms should consider the performance feedback perspective when deciding to pursue a strategic alliance to improve performance. In other words, the decision-makers in a firm must analyze and consider various complex variables inside and outside the firm and expand such subjects of examination to more complex and dynamic factors.
Capability development by educational technology

The capability to identify and make a judgement about the quality of own and work of others is known as evaluative judgement. Such capability is crucial for learners and their learning trajectories, allowing them to become job-ready graduates and life-long learners. The overall concept is newly named but existed in different forms and shapes in the literature. There is sporadic literature investigation of evaluative judgement development by educational technology. Self-assessment, peer-assessment and portfolios in the online learning environment bring various educational values and benefits. Each of these pedagogical activities can contribute to the development of evaluative judgement in an online environment enhanced by educational technology. The primary purpose of this paper is to expand the discussion about the development of evaluative judgement using educational technology. This paper provides some rationale for the inclusion of selected pedagogical activities in the curriculum and actively using them in student-centred education.
A Study on the Non-face-to-face Real Time Korean Language Education Practicum Using Zoom: Focused on the Case of the Institute for Training Korean Language Instructors at Yonsei University

This study is to examine the process and contents of how the Korean language education practicum courses were prepared and operated in the non-degree course of the Institute for Training Korean Language Instructors at Yonsei University in the non-face-to-face era using Zoom. Chapter 2 discussed an overview of Institute for Training Korean Language Instructors at Yonsei University and the contents including the structure of Korean language education practicum courses. Chapter 3 examines the stages of the online Korean language education practicum courses: pre-operation stage and operation stage, and instructional method for each stage. As a result, it is suggested that the entire courses of Korean language education practicum, including on-site class observations, could be conducted online non-face-to-face real time classes rather than offline classes. (Yonsei University)
Concepts, Contexts and Challenges in MALL

This chapter brings together the arguments covered in the previous eight chapters and returns to the title of the book: concepts, contexts and challenges. The concepts that need to be kept in mind for the future of mobile learning are explored, along with the impact of the context on language teaching and learning through mobile technologies. Along with these, the current and prospective challenges are also investigated, with the aim of seeing how these challenges can be overcome to make the most of what MALL can be. The potential future paths in which mobile learning may be considered to evolve will also be discussed here, not in terms of evolving technologies but in terms of directions that the field seems to be headed and how these can relate to meaningful research and practice that is needed in both the shorter and longer term.
Indexes

Indexes are a crucial aspect of your application design. Correct implementation requires an in-depth knowledge of the data, how it is distributed, and how it will be used. Too often, indexes are treated as an afterthought in application development, and performance suffers as a consequence. This chapter examines in detail the different types of indexes, including B*Tree, bitmap, function-based, and application domain indexes, and discusses where they should and should not be used. I’ll also answer some common queries in the “Frequently Asked Questions and Myths About Indexes” section, such as “Do indexes work on views?” and “Why isn’t my index getting used?”
AI Chatbot Builders Utilizaion Plan to Develop AI Chatbots for Korean Language Education

As Artificial Intelligence (AI) technologies advance, chatbots equipped with AI functionalities for different purposes are used in various fields. In response to this trend, educational institutions also strive to use AI chatbots in classroom settings for foreign language education. This study recognizes the need for developing AI chatbots for Korean language education in the near future, and it proposes a plan to develop AI chatbots for Korean education using chatbot builders. To begin with, upon the analysis of previous studies on the use of educational chatbots for foreign languages, the authors examined the characteristics and significance of chatbots. Then four exemplary chatbot builders that allow teachers without previous knowledge of coding to build chatbots were selected. The authors demonstrated in use cases how teachers can use the builders to create Korean educational chatbots, and used these measures to present their utilization plans. By suggesting different ways for teachers to easily manipulate the educational chatbots for use in class, the authors endeavored to expedite future research on chatbots. It is expected that this study will ultimately lay a foundation for further investigations on AI chatbots optimized for Korean education. (Kyung Hee University·George Mason University Korea)
Invariance

This chapter explores the notion of invariance, which is of central normative importance in causal reasoning and is also central to its descriptive characterization, as shown in subsequent chapters. The invariance of a causal relationship has to do with the extent that it continues to be operative across various sorts of changes—in background conditions, changes in the distribution of initial conditions, and different micro-realizations of a cause, to describe just a few of the possibilities that are considered. Invariance is distinguished from exceptionlessness and needs to be understood against the background of our epistemic and calculational limitations.
Four Swedish verbs and a functional distinction

Dalrymple and Lødrup (2000) propose that (tensed) clausal complements have the OBJ function in some languages, the COMP function in others and both functions in still another set. They treat Swedish as a mixed language. In this chapter, Zaenen and Engdahl look more closely at Swedish data discussed in the chapter and supplement them as more electronic data have become available and some of the criteria used have been refined (as is also documented in more recent work by Lødrup (2002), Lødrup (2004), and Lødrup (2012) for Norwegian). Their investigation also illustrates that two related issues need further study: the status of agent phrases in the various forms of passive in Swedish and the status of DP complements in some of the alternations with sentential complements.
Persistent identifiers for ETDs, institutional use cases

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.
Resources for Ethics in Data Publication

Kristen Overstreet walks through published recommendations from the FORCE11 Research Data Publication Ethics Working Group in collaboration with the Committee on Publications Ethics to help Editorial Offices gain greater perspective around ethical issues in data publication.
Explainability for Deep Learning Models

Deep neural network-based models are gradually becoming the backbone of artificial intelligence and machine learning implementations. The future of data mining will be governed by usage of artificial neural network-based advanced modelling techniques. So why are neural networks gaining so much importance when they were invented in the 1950s? Borrowed from the computer science domain, neural networks can be defined as a parallel information processing system where the inputs are connected with each other much like neurons in a human brain to transmit information so that activities like face recognition and image recognition can be performed. In theory, neural networks have existed for more than 50 years, but the execution of neural network projects in practical scenarios became possible after certain advancements in computation, specifically the evolution of GPUs and TPUs in performing high-end calculations, large-scale matrix multiplications, and so on. In this chapter, you are going to learn about the application of neural network-based methods on various data mining tasks like classification, regression, forecasting, and feature reduction. An artificial neural network (ANN) functions similarly to the way the human brain functions, where billions of neurons link to each other for information processing and insight generation.
Medical image alignment based on landmark- and approximate contour-matching

Purpose: Our goal is to propose a landmark- and contour-matching (LCM) registration method that uses both landmark information and approximate point correspondences to boost the similarity between image pairs with sparse landmark information. Approach: A model for registering two-dimensional (2D) medical images with landmark information and contour-approximating landmarks was proposed. The model was also extended to accommodate the registration of three-dimensional (3D) cardiac images. We validated the LCM method on 2D hand x-rays and 3D porcine cardiac magnetic resonance images. The following metrics were used to assess the quality of specific aspects of the registered images: Dice similarity coefficient for the overall image overlap, target registration error for pointwise correspondence, and interior angle for local curvature. Results: Target registrations were reduced from 27.12 to 0.01 mm post-LCM registration. Implementing the proposed algorithm also led to a 112% average improvement in image similarity in terms of Dice coefficients. In addition, interior angle measurements indicate that the proposed method preserved the local curvature at major reference landmarks and mitigated the appearance of deformities in the registered images. Conclusions: The proposed method addressed several issues associated with purely landmark-based techniques, such as iterative closest point registration and thin plate spline interpolation. Furthermore, it provided accurate registration results even in the presence of landmark localization errors.
Information Security Culture Model. A Case Study

This research covers the problem related to user behavior and its relationship with the protection of computer assets in terms of confidentiality, integrity, and availability. The main objective was to evaluate the relationship between the dimensions of awareness, compliance and appropriation of the information security culture and the asset protection variable, the ISCA diagnostic instrument was applied, and social engineering techniques were incorporated for this process. The results show the levels of awareness, compliance and appropriation of the university that was considered as a case study, these oscillate between the second and third level of four levels. Similarly, the performance regarding asset protection ranges from low to medium. It was concluded that there is a significant relationship between the variables of the investigation, verifying that of the total types of incidents registered in the study case, approximately 69% are associated with human behavior. As a contribution, an information security culture model was formulated whose main characteristic is a complementary diagnostic process between surveys and social engineering techniques, the model also includes the information security management system, risk management and security incident handling as part of the information security culture ecosystem in an enterprise.
Pengaruh Perpustakaan Terhadap Sistem Pembelajaran Berbasis Student Centre Learning di Universitas Hasanuddin Makassar

Research purposes is identify, analyze and describe the influence of libraries on the Student Center Learning based learning system at Hasanuddin University. This research is quantitative. The research samples students and lecturers of Hasanuddin University who took advantage of all library services. Respondents were determined using the accidental sampling method, namely whoever comes to use the library when the researcher is doing research and 50 samples from various study programs. Data collection by distributing questionnaires and documentation. Data analysis using the spss program. The research results show that the UPT Hasanuddin University Library at collections, information technology and services are very important, because they support the implementation of learning activities, especially the application of learning methods based on the student center learning system. The library is a center for information sources and science has a function as a teaching facility or facility in meeting the needs of lecturers and students for information. However, the components of collections and information technology based on the research results have no effect. Library collections in universities are very important and must be considered. Good collection is a collection that is complete, adequate, relevant, and updated.Information technology is important, because information technology is a medium for library management activities and automatic dissemination of information. The use of technology can increase the effectiveness and efficiency of library management activities and further provide convenience and efficiency for users to find information sources.
Graph Embedding

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