Reviewerly/exHarmony huggingface dataset:
2015 개정 실과 교육과정에 대한 교육 현장의 의견 분석과 차기 교육과정의 개선 방향 탐색

Objectives This study analyzed the actual application of the 2015 revised curriculum in the educational field and explored the direction of improvement for the next curriculum.&#x0D; Methods First, Using literature analysis, the composition and characteristics of the characteristics, goals, areas, and achievement standards of the 2015 revised Practical Art curriculum were analyzed. Second, the supervisors of the Office of Education and the Office of Education Support and 3% by the size of elementary schools in 17 cities and provinces nationwide were randomly sampled and a survey was conducted for teachers and parents. Third, Interviews were conducted with 7 elementary school teachers and 1 supervisor.&#x0D; Results First, as a result of literature analysis, it was found that the characteristics of practical education was not properly reflected throughout the 2015 revised Practical Art curriculum. Second, as a result of the survey, the most common opinion was that it is necessary to integrate Home Economics, Technology, and Information in Practical Arts for grades 5-6. Also. Third, as a result of the interview survey, it was revealed that the contents of Practical Arts had little relevance to daily life, the insufficient practice time and environment, overlapped contents with other subjects, and had not enough integration between the areas within the subject.&#x0D; Conclusions In order to improve the next Practical Art curriculum, this study suggested mutual communication between related subjects, appropriateness of educational contents, and securing the possibility of practice.&#x0D;
Cybersecurity Risk

This chapter gives an all-inclusive view of cybersecurity risk. The main aim of this chapter is to explain what cybersecurity risk entails. This chapter starts by describing why cybersecurity risk is vital to organizations. The authors explain cybersecurity, vulnerabilities, and common cyber threats/attacks. This chapter also highlights some literature on cybersecurity risks in different sectors and gives an idea about the numerous cyber-attacks during the COVID-19 pandemic. The other sections of this chapter explain risk, risk assessment methods/approaches used in determining the level and type of risk, and risk management frameworks alongside examples from literature and how they were employed to manage risks. Finally, this chapter concludes with the role of organizations in handling and managing cybersecurity risks and the steps governments, organizations, stakeholders, and individuals should take when trying to mitigate or manage cybersecurity risks now and in the future.
Demonstrating DIY Methods for Actuating Morphing Matter

The field of Morphing Matter (MM) is often associated with high-tech equipment or inaccessible lab environments. In this work, we explore morphing matter applications within the context of DIY craft, showcasing different actuation methods for morphing artifacts created using compact, inexpensive, and easily replicable toolkits. This demo presents three morphing matter toolsets that enable novice learners to design shape-changing food, artistic figurines that transform underwater and inflatable wearables. We aim to thoroughly demonstrate each step in the design process for morphing arts and crafts projects triggered by various stimuli such as heat, moisture, and air pressure. Through open-source simulation tools, readily available materials, and easy-to-follow tutorials, morphing matter toolkits can empower users to express their creativity in new ways while learning science and engineering concepts, skills, and techniques.
Exploring ESL students' perceived engagement in and experience of content vocabulary learning through virtual reality games

English as a second language (ESL) students generally struggle to learn mainstream school subjects (Humanities, Social Sciences, Science, and Art) due to the lack of adequate content-specific vocabulary support. Their mainstream teachers attribute this to students' limited vocabulary in addition to their low English proficiency. To address this pedagogical concern, this case study explored the perceptions of six Year 9 Middle Eastern students during their engagement with virtual reality (VR) games to learn content-specific vocabulary using Google Cardboard headsets. Qualitative data was collected using class observations of VR implementation and student responses to exit slip prompts targeting their VR experiences, followed by a semi-structured group interview. A thematic analysis approach was employed to interpret their experiences and provide in-depth descriptions, supported by triangulated data sources. Two thematic categories emerged: ESL learners' attitudes towards headset-enabled 3D educational VR games, and the impact of those games on vocabulary acquisition. Findings indicated that, despite technical issues encountered and the lack of adequate educational features, the VR games provided a fun element that not only enhanced students' engagement but also reinvigorated content and vocabulary learning.
Sarrus Linkage Aerial Drone Arm

The final goal of this project is to design an advanced robotic sampling mechanism that can be deployed by an unmanned aerial vehicle (UAV) to obtain small objects. The focus of this part of the research is only on designing the lightweight, foldable robotic arm for this system. The arm will be designed to utilize Sarrus linkages to efficiently retract and extend. This arm has one degree of freedom and the motion in this arm can be controlled by torsional springs and one actuator. In the final design, the arm, initially, will be in the retracted position, which will allow it to be stored in a streamlined case to minimize interference with the objects in the path of the drone as it flies. Once the drone has reached the desired location, the arm will extend to its full length to reach the target object. In this paper, a foldable arm has been completely analyzed, designed in SolidWorks, and a prototype of it was built and successfully tested. In the next stage of this project, a novel gripper would be designed for this mechanism.
RECAPP: Crafting a More Efficient Catalyst for Convex Optimization

The accelerated proximal point algorithm (APPA), also known as "Catalyst", is a well-established reduction from convex optimization to approximate proximal point computation (i.e., regularized minimization). This reduction is conceptually elegant and yields strong convergence rate guarantees. However, these rates feature an extraneous logarithmic term arising from the need to compute each proximal point to high accuracy. In this work, we propose a novel Relaxed Error Criterion for Accelerated Proximal Point (RECAPP) that eliminates the need for high accuracy subproblem solutions. We apply RECAPP to two canonical problems: finite-sum and max-structured minimization. For finite-sum problems, we match the best known complexity, previously obtained by carefully-designed problem-specific algorithms. For minimizing $\max_y f(x,y)$ where $f$ is convex in $x$ and strongly-concave in $y$, we improve on the best known (Catalyst-based) bound by a logarithmic factor.
Detecting Proxies Relaying Streaming Internet Traffic

Internet Service Providers (ISPs) have to manage vast quantities of data being transmitted by customers on their networks. They can also be responsible for hosting broadcast material, such as live sports. One of the main issues in handling broadcasts is preventing piracy, in this case a customer relaying broadcast material to non customers. A challenge for detecting illegal relays of content is the incompleteness of information arising from packet sampling commonly seen in an ISP perspective. In this paper, we explore how to extract strong signals of content relay that are robust to sampling by using a weighted metric to efficiently measure correlation of content streams. Our results indicate that this signal provides a clear distinction between proxy-traffic and non-relayed network behaviour.
Rapid 3D measurement of colour objects based on three-channel sinusoidal fringe projection

A rapid 3D measurement method based on three-channel projection is proposed in this paper. Project a composite color fringe map and an all-white map to the object to be measured. Firstly, crosstalk correction is performed on the composite color fringe pattern collected by the camera then the reflectivity of fringe image is corrected by all-white image. Then, the background normalization principle is used to solve the spectrum aliasing problem when the Fourier transform obtains a truncated phase. Finally, the three-frequency heterodyne method is used for phase unwrapping to obtain the continuous phase and 3D shape. Compared with the traditional color fringe projection method, this method not only eliminates the spectrum aliasing problem but also solves the uneven fringe reflectivity problem when measuring color objects using an all-white map. This method only requires two images to achieve measurement of 3D color dynamic objects.
Perancangan Aplikasi Informasi Cuaca Berbasis Android Menggunakan API dan JSON

Weather conditions are an inseparable part of human life. Weather conditions are very important and can affect daily activities. Weather conditions are also different in an area / city around the world. This study aims to produce weather information applications in an area / city around the world. This research was conducted with the steps of the waterfall method, planning in the form of pictures and weather information in accordance with OpenWeatherMap data information, needs analysis in the form of functional requirements and non-functional requirements, navigation structure design, use case diagrams, and user interfaces, programming with coding and implementation of the application interface, testing using variations of the Android operating system version and testing the user acceptance test (UAT). This research succeeded in building a weather information application with the name WeatherApp.apk measuring 3.3 MB and embedded with API and JSON. This application is composed of a home menu, finding city, and a splashscreen. Based on the blackbox test results, the WeatherApp.apk application can run on six versions of the Android operating system, namely, Android 5.1.1 (Lollipop), Android 6.0.1 (Marshmallow), Android 8.1.0 (Oreo), Android 11 (R), Android 10 (Q), Android 9.0 (Pie), Based on the user acceptance test (UAT) using a questionnaire to 10 respondents, and processed with a linkert scale, the results obtained are 86.67% in terms of appearance, 85% in terms of user convenience, and 87 ,5% in terms of benefits.
Quantum Circuits and Multi-Qubit Applications

Abstract The devices that carry out manipulations on qubit states are called quantum circuits, built from collections of quantum gates. Alice and Bob describe several two-qubit quantum gates and illustrate their actions on quantum states. They show that it is impossible to clone an unknown quantum state—the so-called No-Cloning Theorem. That theorem severely limits an eavesdropper’s ability to listen in on quantum communications without being detected. Alice and Bob then introduce and explain in detail two quantum communications algorithms: Superdense Coding (transmitting two bits of classical information with only one qubit) and Quantum State Teleportation (the ability to send enough information over a long distance to reconstruct a quantum state). Each of these applications highlights the book’s leitmotif of state preparation, state manipulation, and state measurement.
RRT and RRT* Using Vehicle Dynamics

The trajectory derived from RRT and RRT* is zagged. A holonomic drive is able to follow this trajectory. But real-life vehicle which has dynamical constraints cannot follow this trajectory. In this work, we are going to modify the RRT and RRT* algorithm to generate a trajectory that a vehicle with dynamical constraint can follow. The continuous nature of steering control and acceleration control in a real-world vehicle introduces the complexity in its model. To introduce constraint in the vehicle's motion, while reducing the number of control and hence complexity, we are modeling our vehicle as a Dubins car. A Dubins car has only three controls (turning left, turning right, and moving forward) with a fixed velocity which makes our model simple. We use dubins curve (path that dubins car can follow) to trace the trajectory in RRT and RRT* algorithm.
Speaker Diarization and BERT-Based Model for Question Set Generation from Video Lectures

The year 2020 and the onset of the pandemic has, by and large, rendered the traditional classroom-based learning experiences obsolete. This rapid change in the learning experience has brought with it the opportunity to explore new avenues such as online learning. In this paper, we outline a methodology that aims to aid this paradigm shift by proposing an automated question set generation model based on the video lectures delivered by the teacher. We study the usage of pre-trained Scientific Bidirectional Encoder Representations from Transformers (SCIBERT) checkpoints for question generation on text derived from video lectures. The proposed methodology takes into consideration the presence of multiple speakers in the video lectures and employs speaker diarization for obtaining the audio corresponding to the teacher’s voice. Diarization is implemented using the mean shift clustering algorithm. For the purpose of answer-agnostic question generation, pre-trained SCIBERT checkpoint is used to warm start an encoder–decoder model. The model is fine-tuned using the SQuAD dataset. The results show that the model is able to successfully generate questions for a given context derived from the transcript of a diarized video lecture.
Current Status of Industrial Engineering through Quantitative Analysis

In this study, the current status of industrial engineering major is identified through quantitative data analysis to prepare for the fourth industrial revolution and a sharp drop in the school-age population. We have conducted a comparative analysis of industrial engineering with other majors in terms of various indicators related to students, graduates, and research. In addition, we have compared industrial engineering departments by the region and establishment type of universities.
Classification of the Video Type and Device Used in 360-Degree Videos from the Trajectories of its Viewers’ Orientations with LSTM Neural Network Models

360-degree videos are consumed in diverse devices: some based in immersive interfaces, such as viewed through Virtual Reality headsets and some based in non-immersive interfaces, as in a computer with a pointing device or mobile devices with touchscreens. We have found, in prior work, significant differences in user behavior between these devices. From a dataset of the trajectories of the users’ head orientation in 775 video reproductions, we classify which kind of video was played (two values) and which of the four possible devices was used to reproduce these videos. We found that recurrent neural network models based on LSTM layers are able to classify the video type and the device used to play the video with an average accuracy of over 90% with only four seconds of trajectory. We are convinced that this knowledge can improve techniques to predict future viewports used in viewport-adaptive streaming when diverse devices are used.
Retraction notice to “The role of creative musical activity in learning foreign languagesThe role of creative musical activity in learning foreign languages” [ Thinking Skills and Creativity Volume 41, September 2021, 100917]

This article has been retracted: please see Elsevier Policy on Article Withdrawal ( https://www.elsevier.com/about/our-business/policies/article-withdrawal ). This article has been retracted at the request of the Editors-in-Chief. After a thorough investigation, the Editors have concluded that the acceptance of this article was partly based upon the positive advice of one unreliable reviewer report. The report was submitted from an email account which was provided to the journal as a suggested reviewer during the submission of the article. The reviewer account did not respond to the journal request to confirm the reviewer identity, and the Editors decided to retract the article. This manipulation of the peer-review process represents a clear violation of the fundamentals of peer review, our publishing policies, and publishing ethics standards. Apologies are offered to the readers of the journal that this deception was not detected during the submission process.
An Energy and Carbon Footprint Analysis of Distributed and Federated  Learning

Classical and centralized Artificial Intelligence (AI) methods require moving data from producers (sensors, machines) to energy hungry data centers, raising environmental concerns due to computational and communication resource demands, while violating privacy. Emerging alternatives to mitigate such high energy costs propose to efficiently distribute, or federate, the learning tasks across devices, which are typically low-power. This paper proposes a novel framework for the analysis of energy and carbon footprints in distributed and federated learning (FL). The proposed framework quantifies both the energy footprints and the carbon equivalent emissions for vanilla FL methods and consensus-based fully decentralized approaches. We discuss optimal bounds and operational points that support green FL designs and underpin their sustainability assessment. Two case studies from emerging 5G industry verticals are analyzed: these quantify the environmental footprints of continual and reinforcement learning setups, where the training process is repeated periodically for continuous improvements. For all cases, sustainability of distributed learning relies on the fulfillment of specific requirements on communication efficiency and learner population size. Energy and test accuracy should be also traded off considering the model and the data footprints for the targeted industrial applications.
The Integration of Machine Learning into Automated Test Generation: A  Systematic Literature Review

Background: Machine learning (ML) may enable effective automated test generation. Aims: We characterize emerging research, examining testing practices, researcher goals, ML techniques applied, evaluation, and challenges. Method: We perform a systematic literature review on a sample of 97 publications. Results: ML generates input for system, GUI, unit, performance, and combinatorial testing or improves the performance of existing generation methods. ML is also used to generate test verdicts, property-based, and expected output oracles. Supervised learning - often based on neural networks - and reinforcement learning - often based on Q-learning - are common, and some publications also employ unsupervised or semi-supervised learning. (Semi-/Un-)Supervised approaches are evaluated using both traditional testing metrics and ML-related metrics (e.g., accuracy), while reinforcement learning is often evaluated using testing metrics tied to the reward function. Conclusions: Work-to-date shows great promise, but there are open challenges regarding training data, retraining, scalability, evaluation complexity, ML algorithms employed - and how they are applied - benchmarks, and replicability. Our findings can serve as a roadmap and inspiration for researchers in this field.
Systematic Analysis and Comparison of Security Advice Datasets

A long list of documents have been offered as security advice, codes of practice, and security guidelines for building and using security products, including Internet of Things (IoT) devices. To date, little or no systematic analysis has been carried out on the advice datasets themselves. Contributing in this direction, we begin with an informal analysis of two documents offering advice related to IoT security -- the ETSI Provisions and the UK DCMS Guidelines -- and then carry out what we believe is the first systematic analysis of these advice datasets. Our analysis explains in what ways the ETSI Provisions are a positive evolution of the UK DCMS Guidelines. We also suggest aspects of security advice that might be given special attention by those offering security advice.
A Blockchain-Based Conceptual Model for Curbing Institutional Academic Certificate Fraud

There is need of certificate authentication mechanism in Africa, specifically in Kenya that will solve internal fraud activities. This is because there are many fake certificates in circulation that appear to be genuine but were obtained illegal from accredited universities. This is caused by the assumption that certificates being issued at the university are authentic. While authentication of the final academic certificate has been studied in previous research, many researchers focused on securing the final academic certificate and assumed that all certificates issued by universities are genuine thus creating a loophole for institutional certificate fraud. It’s possible for clients looking to get an academic certificate illegally to collude with university staff, who are responsible for generating the certificates, to acquire a legitimate academic certificate without going through the academic process. The purpose of this research is to develop a blockchain based model that solves the current problem of institutional certificate fraud. The research targets only Kenya public universities. Sampling will be done using simple random sampling to identify a few universities that will participate in the study. A combination of secondary data and primary data will be used in the research. Secondary data will be used to test the model while primary data will be used to construct the data mapping structure/model. Primary Data will be collected from the registry department using questionnaires and interviews while the sample will be obtained using stratified sampling. The model will be deployed using permissioned blockchain. The proposed model will have controls to ensure a student goes through the entire learning process before he is awarded an academic certificate.
The Study Of ‘V1+connective ending+V2’Korean Serial Constructions

This paper aims to examine that a structure of ‘V1-a V2’ is separated by focus particles. The categories of verb linking constructions which combine focus particles are the same in terms of the morphological identity, but not the syntactic-semantical identity. In addition, it violates the Lexical Island Constraint and causes a contradiction between form and meaning when focus particles are combined with compound verbs. It seems to be induced by the specificity of each category of the ‘V1-a V2’ and the application of variable semantic domains of focus particles. Therefore, this paper argues the phenomenon mentioned above based on Copy Theory. As a result, the higher copy of the focus particles is not realized in the PF layer due to phonological restrictions while the copies of the focus particles are realized differently depending on the discourse semantic situation in the LF layer.