Reviewerly/exHarmony huggingface dataset:
Automated Health Monitoring System Using the Internet of Things for Improving Healthcare

The aim of this chapter is to investigate the applicability of the four pillars of Industry 4.0 namely, Internet of Things (IoT), Big data, Cloud Computing, and Artificial Intelligence, in the healthcare domain with suitable authors’ findings. The industry 4.0 architecture for healthcare domain includes health sensors that gather data from the patient. Thus collected data is relayed to a microcontroller and then sent to the cloud wirelessly. At present almost 70% of the production data in the healthcare domain are unused. Industry 4.0 paves the way for maximum utilization of collected data for on-time diagnosis using machine learning algorithms. The experimental results of authors’ findings will be outlined by a comparative analysis of various machine learning algorithms such as Naive Bayes, Random Forest Tree, Support Vector Machine (SVM), and Classification and Regression Trees (CART). Apart from remote health monitoring, it is possible to connect medical devices to help clinicians to make data driven decisions using IoT. 272A case study of integrating an IoT-based pill dispensing unit to use the compared techniques and protocols is detailed.
The Latent Transition Analysis of Career Development Competencies on Career Disadvantaged High School Students and Influential Factors

The purpose of this study is to explore the possibility of change in the career development type of high school students from the disadvantaged group in career preparation over time, and explore the influence of role of individuals, parents, teachers, peers, and school career education in the process of shift in career development competency types. To answer the above research questions, a latent profile analysis and a latent transition analysis were conducted using high school data from「Korean Education &amp; Employment Panel Ⅱ」, and the results are as follows.&#x0D; First, based on individual differences in career development competencies in the second and third years of high school, the students were classified into three types including “career confusion group,” “career suspension group,” and “career achievement group” (second year) and two types including “career confusion group” and “career achievement group” (third year). career development competency transition types were largely divided into “unchanged type” and “stable type” and “changed type”, and the profile of more than half of students was changed in their third year of high school.&#x0D; Third, gender and experience in vocational psychological testing and counseling, the experience of career education as an independent course and the sum of career exploration experiences did have an effect on predicting such transition patterns.
Full-Reference Objective Quality Metric for Three-Dimensional Deformed Models

Three-dimensional data are generally represented by triangular meshes. The 3D data are used in several fields including remote 3D games, 3D medical application, 3D virtual worlds and 3D augmented reality application. These applications require displaying, printing or exchanging the 3D models through the network to optimize the rendering of the 3D models and 3D applications, which include different treatments, for example, smoothing, compression, re-meshing, simplification, watermarking, etc. However, these processes generate distortions that affect the quality of the rendered 3D data. Thus, subjective or objective metrics are required for assessing the visual quality of the deformed models to evaluate the efficiency of the applied algorithms. In this context, we introduce a new perceptual full-reference metric that compare two 3D meshes based on their 3D content information. The proposed metric integrates the relativity and selectivity properties of the Human visual system (HVS) independent of the mesh type and connectivity (e.g. Triangular, Quadrilateral, Tetrahedron, Hexahedron), which represent a limit in the existing method, in order to capture the perceptual quantity of the distortion by the observer. The results of the proposed approach outperform the existing metrics and have a high correlation with the subjective measures. We use the two correlation coefficients Spearman Rank ([Formula: see text]) and Pearson Rank (Rp) in order to assess the performance of the proposed metric.
STUDENTS� PERCEPTION ON THE ONLINE LEARNING: A CASE STUDY OF EFL LEARNERS

ABSTRACTThis case study aims at describing students perception especially EFL learners on the online learning during the pandemic covid 19. The data was taken from English Department students who are in the second semester which are taught by the researcher in her class. The data collection was done by using online interview by using zoom meeting in which the students enter the meeting one by one to have the interview. Based on the analysis, it revealed that according to students perception, online learning is not effective and not liked by the students. They prefer face-to-face or offline class. In details, they stated some reasons, they are: the unstable signal, cannot adjust yet with the online class, the instruction of the assignment is not clear, not effective group assignment because of online interaction, the material of online learning is not so clear. So, they hope the offline class will be done soon. The online learning tools they like the most is zoom meeting because it is almost like the face to face class.Keywords: Students perception; online learning; EFL Learners.
Unsupervised Echocardiography Registration Through Patch-Based MLPs and Transformers

Image registration is an essential but challenging task in medical image computing, especially for echocardiography, where the anatomical structures are relatively noisy compared to other imaging modalities. Traditional (non-learning) registration approaches rely on the iterative optimization of a similarity metric which is usually costly in time complexity. In recent years, convolutional neural network (CNN) based image registration methods have shown good effectiveness. In the meantime, recent studies show that the attention-based model (e.g., Transformer) can bring superior performance in pattern recognition tasks. In contrast, whether the superior performance of the Transformer comes from the long-winded architecture or is attributed to the use of patches for dividing the inputs is unclear yet. This work introduces three patch-based frameworks for image registration using MLPs and transformers. We provide experiments on 2D-echocardiography registration to answer the former question partially and provide a benchmark solution. Our results on a large public 2D echocardiography dataset show that the patch-based MLP/Transformer model can be effectively used for unsupervised echocardiography registration. They demonstrate comparable and even better registration performance than a popular CNN registration model. In particular, patch-based models better preserve volume changes in terms of Jacobian determinants, thus generating robust registration fields with less unrealistic deformation. Our results demonstrate that patch-based learning methods, whether with attention or not, can perform high-performance unsupervised registration tasks with adequate time and space complexity. Our codes are available https://gitlab.inria.fr/epione/mlp\_transformer\_registration
Research on a defect detection method on carbon composite laminates based on digital shearography

Subject of study. Carbon composite laminates are one of the major aviation structural materials. Owing to its merits of being non-contact, self-coherent, non-destructive, and full field, digital shearing speckle pattern interferometry (DSSPI) has the potential to be effective in the detection of defects on carbon composites with various surface shapes, especially the close-type defect on composite laminates. Method. In this paper, a DSSPI system containing both simulation and experiment, used for the measurement of carbon composite laminates with different curvature radii, is established. Main results. Based on our proposed criterion to evaluate whether the defects can be judged or not, the experiment loading parameters are applied, and the detection abilities under variable loading parameters are predicted. The effectiveness of the experiment system is verified through comparison with the X-ray and the ultrasound techniques. The simulation results are consistent with the experiments, showing its effectiveness. Practical significance. The work in this paper can provide reliable guidance to the loading parameters and predict the detection performance in a real DSSPI experiment system.
Bibliography

Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. “Try This!” exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specific homework problems across the sciences and engineering.
JQuery Implementation of Online Platform for University Human Resource Management Mode Based on Multi-Centralized Networking Algorithm

Firstly, the simulation task community service QoS model is introduced, and the service composition process of the task community is evaluated; then the STCSSA operation process is introduced in detail, and the dynamic change strategy of the inertia weight of the algorithm is designed. The idea is to build a localized human resource management model, and improve the efficiency and effect of human resource management based on scientific incentive methods. From the perspective of JQquery’s characteristics and business process processing framework, the requirements of human resources work in colleges and universities, and the combination of JQquery’s characteristics and practical work.
Introduction

This chapter introduces the basic concepts of cybersecurity and the data analytics perspective to cybersecurity. It lays out the areas of study and how data analytics should be a key part of the spectrum of cybersecurity solutions.
Make It Correct: Linting and Unit Testing

Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. “Try This!” exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specific homework problems across the sciences and engineering.
Anomaly Detection Methods

This chapter focuses on techniques of detecting anomalies, starting with some of the basic statistical techniques and going into data analytics techniques.
The Elements of Formal Language Theory

AbstractDigital computers became a staple in the kit bags of both scholars and practitioners in the 1950s. Language processing—both natural languages and artificial ones (such as programming languages)—was a significant beneficiary of this new tool.
Getting Basic Tasks Done

Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. “Try This!” exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specific homework problems across the sciences and engineering.
PEMANFAATAN MEDIA PEMBELAJARAN DARING PADA MATA PELAJARAN PENDIDIKAN AGAMA ISLAM DI SMK MIFTAHUL HUDA KECAMATAN NGADIROJO KABUPATEN PACITAN

ABSTRACT&#x0D; Utilization of online learning media is the focus of research, teachers must be able to adapt to online learning. The change in the learning process that was originally conventional has now changed to online learning. In its implementation there are obstacles both from internal and external factors. Teachers must be able to find efforts to improve the learning process. So that the results of the media used by PAI teachers are youtube, WhatsApp, google classroom. The use of learning media is less varied so that media is needed for face-to-face virtual. Constraints in the use of online learning media tend to be tired and drain energy and time, so that the efforts to implement offline learning can maximize the use of learning media. And conduct home visits as an approach to students and parents.&#x0D; &#x0D; Keywords : Learning Media, Online Learning, PAI Learning
The Control Structure: How to Describe the Workflow

If different statements are required to be executed based on various conditions or if statements need to be executed repeatedly, then so-called control structures can be used. They allow different statements to be executed depending, for example, on a value of a Boolean expression. These control structures are another important tool to express the program behavior. In this chapter, you will learn the four main kinds of control structures of the Python language: the if statement, the match statement, the while statement, and the for statement. All these statements can be embedded into each other arbitrarily.
Bifurcation Fusion Network for RGB-D Salient Object Detection

With the rapid development of sensor technology, multi-modal data fusion methods based on deep neural networks provide a reliable guarantee for object recognition and detection in complex scenarios. Most of the existing RGB-D image salient object detection methods improve the salient object detection methods in 2D scenes, which have many problems, such as ineffective fusion of feature information, incomplete image feature extraction and so on. Aiming at these problems, we proposed a salient object detection method based on bifurcated fusion network. First, we use the high- level features of the global context to locate the salient object, then we use the low-level features of the local details to extract the edge information. Second, we model the RGB information and depth information through the gate channel transformation control mechanism, and construct the bifurcation backbone network model and generate the initial salient map. Finally, based on the initial salient map and low-level features, the final salient map is generated. Experimental results show that the proposed method can fully utilize the multi-layer feature information of the image and effectively detect the salient object.
Pencarian Jalur Terdekat Pada Pemetaan Sekolah Dasar Dengan Algoritma A-Star (A*) Berbasis Web

Elementary school is the starting place for a child to start education and get various kinds of experiences. Elementary school is the highest level of education compared to Junior High School and Senior High School. The large number of elementary schools makes parents/guardians not know for sure where the elementary school is located. This makes parents/guardians not have many references to send their children to school in the future. Based on the existing problems, the author proposes a web-based geographic information system that uses the A-Star Algorithm (A*) to be used as a means of information and also to add references to parents/guardians. The A-Star Algorithm (A*) is a method to search for information about the distance to reach the destination by selecting the closest route. The reason for using this algorithm is because the calculations are easy to understand. The result of this research is a web-based geographic information system that can provide information about 6 samples of elementary schools along with the location and the closest route that can be passed in the Mustikajaya District area.
Prologue: Preparing to Program

Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. “Try This!” exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specific homework problems across the sciences and engineering.
Non-Convex High-Order TV and <i>ℓ</i> <sub>0</sub>-Norm Wavelet Frame-Based Speckle Noise Reduction

To obtain natural restorations from the noisy images contaminated by speckle noise, this brief presents a novel hybrid non-convex regularizers model for image denoising. The proposed new variational model closely combines the superiorities of non-convex high-order total variation function and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{0}$ </tex-math></inline-formula> -norm wavelet frame. This combination helps to avoid the staircase artifacts and maintain discontinuities while removing noise. Numerically, by integrating two popular tools: iteratively reweighted <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> algorithm and variable splitting method, a modified alternating minimization method is adopted to optimize the resulting minimization problem. Finally, compared with several despeckling methods, numerical experiments indicate the competitive performance of our solver in visual improvement and objective measurement.
Cybersecurity through Network and Graph Data

This chapter extends the ideas of complex data by looking into cybersecurity through network and graph data.
Magical Tower VR - Examining Orientation in Non-Euclidean Spaces

Immersive virtual reality applications and games do not necessarily have to be bound to reality. Non-euclidean VR environments permit the developer to stack more virtual space into a small room-scale VR area than otherwise physically possible. In order to test whether such environments are suitable for VR, a game was developed to investigate the acceptance of such a non-logical environment and the wellbeing of the players. Also the orientation of the players in non-Euclidean virtual environments was examined. In the game, the player in the role of the magician’s apprentice has the task of finding four hidden items and returning them to the starting room. To find the items, the players have to solve some puzzles using their orientation skills. The game level consists of many unique rooms connected by portals creating the impression of a non-Euclidean environment. First tendencies show that orientation in non-Euclidean VR environments is possible and that the players enjoyed the expanded possibilities of actions.
An Interpretable Question Answering Method Based on Heterogeneous Graph Neural Networks

Community question answering has gradually become the primary path for people to acquire knowledge. Existing community answer prediction research mainly faces the challenges of multi-type entity feature fusion and low answer interpretability. In this paper, we propose an interpretable Question Answering Method Based on Heterogeneous Graph Neural Networks, called IQAGNN. Firstly, we construct a heterogeneous information network to fuse multi-type entity relationships in question answering communities. Secondly, we employ the heterogeneous graph neural network to obtain multi-type entity embeddings. Finally, we predict the answer to the new question based on entity correlation and give an interpretation analysis of the answer via meta-paths. Comparative experiments on three real datasets show that IQAGNN has advantages in interpretive question-answering research.
An Analysis on the Use of Blockchain by Developers and Application Users

Blockchain is an emerging technology that is being studied more and more in academia and applied in industry. Some of these characteristics are immutability, traceability, and security. Several areas can be benefiting from Blockchain, such as health, transport, and agriculture. With its diffusion, it is natural that the application development areas start to use it, involving different types of professionals. This paper aims to provide an overview of blockchain technology users’ profiles and opinions, whether developers or application users. To meet this objective, an online questionnaire with demographic, technical and open questions was designed. Regarding to open questions, a qualitative analysis was performed, through Grounded Theory. We identified as the main conclusions from our work: (i) security is a feature very well seen by users, (ii) there are difficulties in blockchain learning, and (iii) there are many tools for blockchain development, however, support is needed.
Multidimensional Cluster States Using a Single Spin-photon Interface Coupled Strongly to an Intrinsic Nuclear Register

We propose the generation of multi-dimensional cluster states using a single, efficient spin-photon interface coupled strongly to a nuclear register. We show numerically that for SiV- in diamond a 2×5- sized cluster state is achievable.