Reviewerly/exHarmony huggingface dataset:
Designing an Immersive Virtual Reality Classroom Exploring Behaviour Support Strategies

Abstract In this research the authors explore ClasSimVR, a proof-of-concept immersive virtual reality ( ivr ) application. This software is designed to support pre-service teachers ( pst s) implementation of a School-Wide Positive Behaviour Interventions and Supports ( swpbis ) approach to challenging student behaviours. ClasSimVR offers users the opportunity to engage with immersive hypothetical scenarios, whereby virtual students display challenging behaviours. Users respond to these behaviours with a range of possible actions aligned with a swpbis approach. The authors draw on a research-through-design ( rtd ) methodology to explore the design process of ClasSimVR. The article investigates the implications of an expert evaluation ( n =5) conducted as part of the design process of creating ClasSimVR. More broadly, this research contributes to the discourse surrounding the design and implementation of immersive learning environments in educational contexts.
Multi-Metric Near-Optimal Image Denoising

It is necessary to optimize the parameters for each image input to achieve the maximum denoising performance because the performance of denoising algorithms depends largely on the selection of the associated parameters. The commonly used objective image quality measures in quantitatively evaluating a denoised image are PSNR, SSIM, and MS-SSIM, which assume that the original image exists and is fully available as a reference. However, we do not have access to such reference images in many practical applications. Most existing methods for no-reference denoising parameter optimization either use the estimated noise distribution or a unique no-reference image quality evaluation measure. In the chapter, for BM3D, which is a state-of-the-art denoising algorithm, we introduce a natural image statistics (NIS) based on the generalized Gaussian distribution (GGD) and the elastic net regularization (EN) regression method and propose its use to perform the BM3D parameter optimization for PSNR, SSIM, and MS-SSIM, respectively, which are the popular image quality evaluation measures, without reference image and knowledge of the noise distribution. Experimental results with several images demonstrate the effectiveness of the proposed approach.
The Specifics of the Organization of Educational and Research Activities of High School Students in the Formation of a Social Picture of the World

The article raises the problem of insufficient theoretical understanding of the specifics of the educational and research activities of high school students, its potential for the formation of a social picture of the world. The specifics of the organization of educational and research activities in the framework of the study of subjects of the social and humanitarian cycle are shown.
The Review of Recent Recommendation and Classification Methods for Healthcare Domain

Nowadays, Healthcare services are dependent on Health Information Systems (HIS). The Healthcare recommendation system plays a vital role in healthcare services, work as an essential tool for decision-making tasks. Health recommendation systems improve technology accessibility and simultaneously reduce the overload of information. Although technological advancement inside the medical domain extends back years, there are still numerous difficulties to be resolved. There are various tools and recommendations for doctors in health recommendation systems (HRS). The HRS can be based on collaborative filtering, content filtering, and knowledge filtering based or may be based on hybrid filtering-based techniques. HRS is used to evaluate patient information to derive the quality of content and aid in disease diagnosis and prediction. Patients can take medicine recommendations with the help of HRS. The classification models have discussed the existing performance metrics and comparative analysis such as LSTM, Fuzzy-Logic, CNN, CNN-LSTM, etc. These classification models have improved the precised parameters as compared with the existing deep learning models. It is used to monitor the wellness and critical condition of the patients. This study is seen to be a useful starting point and the foundation for HRS literature evaluation.
Optimizing the Utilization of Game-Based Learning Application for Elementary Students First Phase

Smartphone was a technology-based device that was almost used and owned by every individual, both teachers and students. This study aimed to identify opportunities for using smartphones to support learning activities. This type of research was included in qualitative research, the research subject consists of 30 students of primary education level who were randomly selected. The data collection method used was a survey with a research instrument, namely a questionnaire. Through the questionnaire, it was found that 86.7% of students have smartphones that are used to play games (76.7%), using smartphones in a day for more than 5 hours (63.3%) this was certainly an opportunity for innovative learning media to emerge. with a game format (game-based learning). Referring to the results, it could be concluded that the innovation of learning media with game-based learning has a very big opportunity to be used by teachers to support the learning process.
The Design and Implementation of Geospatial Information Verification Middle Platform for Natural Resources Government Affairs

Geospatial Information Verification Mid-End Platform for Natural Resource Administration is designed in response to issues such as repeated development, low scalability, and inconsistent verification rules in existing approval and supervision application systems. We first discussed the architecture of the middle platform and micro-services and also examined the business requirements. Secondly, we presented the architecture of the spatial information verification platform. Finally, the application method in the construction land approval business is introduced. Practical applications proved that the spatial information verification platform is highly scalable and maintainable, with reusable business components and data services for a variety of government affairs application systems.
Feature transfer learning by reinforcement learning for detecting software defect

Abstract Software defects, produced inevitably in software projects, seriously affect the efficiency of software testing and maintenance. An appealing solution is the software defect prediction (SDP) that has achieved good performance in many software projects. However, the difference between features and the difference of the same feature between training data and test data may degrade defect prediction performance if such differences violate the model's assumption. To address this issue, we propose a SDP method based on feature transfer learning (FTL), which performs a transformation sequence for each feature in order to map the original features to another feature space. Specifically, FTL first uses the reinforcement learning scheme that automatically learns a strategy for transferring the potential feature knowledge from the training data. Then, we use the learned feature knowledge to inspire the transformation of the test data. The classifier is trained by the transformed training data and predicts defects for transformed test data. We evaluate the validity of FTL on 43 projects from PROMISE and NASA MDP using three classifiers, logistic regression, random forest, and Naive Bayes (NB). Experimental results indicate that FTL is better than the original classifiers and has the best performance on the NB classifier. For PROMISE, after using FTL, the average results of F1‐score, AUC, MCC are 0.601, 0.757, and 0.350 respectively, which are 24.9%, 2.6%, and 16.7% higher than the original NB classifier results. The number of projects with improved performance accounts for 83.87%, 83.87%, and 64.52%. Similarly, FTL performs well on NASA MDP. Besides, compared with four feature engineering (FE) methods, FTL achieves an excellent improvement on most projects and the average performance is also better than or close to the FE methods.
ON THE EUCLIDEAN ALGORITHM: RHYTHM WITHOUT RECURSION

Abstract A modified form of Euclid’s algorithm has gained popularity among musical composers following Toussaint’s 2005 survey of so-called Euclidean rhythms in world music. We offer a method to easily calculate Euclid’s algorithm by hand as a modification of Bresenham’s line-drawing algorithm. Notably, this modified algorithm is a nonrecursive matrix construction, using only modular arithmetic and combinatorics. This construction does not outperform the traditional divide-with-remainder method; it is presented for combinatorial interest and ease of hand computation.
Preface

Extract There is a long tradition, stemming from Aristotle, according to which one bears moral responsibility for some event just in case one satisfies two conditions. The first condition is that the event’s occurrence must have been within one’s control. The second is that its occurrence must have been within one’s ken. It is the first condition that has received the lion’s share of attention from philosophers. Much of this attention has been devoted to the puzzle posed by the apparent fact that satisfaction of this condition is consistent with neither determinism nor indeterminism. Indeed, it was my introduction to this puzzle in an undergraduate course that I took over 50 years ago that first sparked my curiosity about moral responsibility, and my interest in the concept has never waned since. It was in part because I despaired of ever finding a satisfactory solution to the puzzle about control that I turned, some 10 years later, to a consideration of the second condition of responsibility. But I quickly ran into another puzzle here, too, which is simply that many of our everyday ascriptions of responsibility apparently fail to conform to this condition. For although we often treat ignorance as an excuse for wrongdoing, we also often don’t. We don’t when we judge that the person in question “should have known better.” Even if this judgment is accurate, though, how is it supposed to suffice for responsibility for the wrongdoing in question? This puzzle struck me as likely to be more tractable, and so I decided to look into it. I came to the conclusion that ignorance provides an excuse for wrongdoing far more often than is commonly thought, and hence that many of our everyday ascriptions of responsibility are mistaken. I took a first stab at presenting my argument for this conclusion in the mid-1980s, and I have offered various versions of it since then in a continuing effort to improve on it.
The Effect of Experience

Abstract This chapter draws on business strategy literature's concept of experience curve effects, to analyze the components that could enhance effectiveness in offensive cyber capability development and deployment. Experience curves are based on the premise that the more often a task is performed, the more effectively the task will be completed. This chapter examines three components of experience effects: learning, scale and technology. The chapter explains that states can become more effective in capability development and deployment over time. Developers and operators can not only become better in writing code but also improve their communication skills. Infrastructure acquisition and use can benefit from scale advantages. And improvements in tooling can make various aspects of the cyber-attack process more effective. That said, the chapter also reveals that states face several obstacles to enhance their operational effectiveness in the cyber domain. Not least, organizations will continue to find it difficult to hire, train, and above all, retain qualified personnel.
What Happens in Vegas Stays in China

Abstract In the United States, the tech sector is at the center of a battle between national security interests and unbridled growth. As the US economy has become dependent on technology firms, which constitute over one-fifth of the S&amp;P 500 stock index, Big Tech’s financial interests have prevailed over the national interests of US digital sovereignty. Chapter 2 argues that a lack of systemic oversight of the US tech sector’s data landscape leaves US consumer data vulnerable to gathering and exfiltration. This oversight vacuum, it shows, protects US firms in the short term but conditions consumers to ignore the question of where their data goes, enabling Chinese tech companies in the United States to harvest and extract this information. By failing to systematically protect consumer data, the US market—from baby monitor manufacturers to social media platforms—has become a treasure trove of data for Chinese firms.
Epilogue

Extract Data trafficking is only in its infancy. The promises of 5G, such as lightning-fast connection, enhanced service delivery, and more immersive digital environments, are still forthcoming. Companies are already preparing for 6G to enhance digital integration in areas ranging from health, transportation, medicine, agriculture, logistics, and beyond. Each of these areas bring new forms of data exploitation and vulnerability not just within nations, but between them. Nowhere are the stakes higher than in the US-China relationship. Trafficking Data offers a framework for understanding the opportunities that China’s extraterritorial data governance practices present to strengthen democracies. The first consideration is learning how to navigate the relationship between the Chinese government and tech companies in democracies that are trying to preserve a global tech sector. The second opportunity is contending with the difficulty of enforcing laws that run up against proprietary corporate resources and decision-making. The third opportunity is reconciling data standards between allied nations to create a more robust global network of data protection. My hope is that as users become more aware of their power, they can advocate for a more stable, transparent future – one where they have greater control of the data they generate not just on social platforms or in games but across all areas that form foundation of our digital world.
ENHANCED REAL-TIME DETECTION OF FACE MASK WITH ALARM SYSTEM USING MOBILENETV2

To prevent the coronavirus from spreading, the government adopted measures such as wearing a face mask in public locations. The researchers aimed to create a face detection system using the MobilenetV2 architecture that would identify a person’s faces and determine whether they were wearing a face mask. The built model will help to reduce the danger of viral transmission. In this study, face mask detection is achieved using a machine learning algorithm and the classification method using MobileNetV2. The steps for building the model are data gathering, data pre-processing, splitting the data, testing the model, and implementing the model. The built model can distinguish between those who are wearing a face mask (with no design patterns) and those who are not wearing it with a 96% accuracy. In terms of classification accuracy, the proposed model using MobileNetV2 outperformed the other models LeNet-5, AlexNet, and ResNet-50. If the detected person is labeled with “no mask”, the system generates an alarm sound. This research will be useful in combating virus spread and avoiding virus contact.
PREVIS - A Combined Machine Learning and Visual Interpolation Approach for Interactive Reverse Engineering in Assembly Quality Control

We present PREVIS, a visual analytics tool, enhancing machine learning performance analysis in engineering applications. The presented toolchain allows for a direct comparison of regression models. In addition, we provide a methodology to visualize the impact of regression errors on the underlying field of interest in the original domain, the part geometry, via exploiting standard interpolation methods. Further, we allow a real-time preview of user-driven parameter changes in the displacement field via visual interpolation. This allows for fast and accountable online change management. We demonstrate the effectiveness with an ex-ante optimization of an automotive engine hood.
Comprehension of Space

Abstract Human understanding of space includes physical properties, but layered with notions of path and place, and shaped by the way our bodies move and this is the subject of this chapter. Three-dimensional space may be experienced as two-dimensional, not just because our eyes flatten the world but because we do not fly and our legs traverse flat surfaces. In our heads we have different models of close and distant space, giving rise to different forms of maps and plans: digital maps typically favour mathematical Cartesian representations, but there are times when more human interpretations are needed. Space and culture intermix: physical locations become socially rich places, lines and routes relate to stories and journeys; even basic perception is shaped by the sharp edges or organic curves of our upbringing. The design of virtual worlds may enable them to become lived, social places, and the design of physical spaces may lead them to become socially barren non-places.
Prototyping and Tool Support

Abstract This chapter discusses some of the ways in which the physicality of our interactions with the world affects, drives, and is exploited in the design process, and in particular how this is embodied in various physical toolkits, design applications, and notations. It looks at how user experience of devices and applications is mediated by their physicality which means that the physical forms used in design prototypes may subtly affect the behaviour of users. There are many tools and techniques available, so that it is possible to explore designs at different levels of physical fidelity. These range from early stage tools such as storyboards and state-transition network representations of interaction, through off-the-shelf products such as video, office applications, and digital toys, to specially designed physical computing kits, and electronics tools that enable bespoke working prototypes. Together, these tools can return physicality to the development process of computer-embedded products.
Tools, Equipment, and Machines

Abstract From stone axes to digital computers and prising open a paint can with a spoon handle, humans are natural tool users and tool creators. This chapter shows that the affordance of tools is not innate but linked to the different times and cultures in which we live; part of a constant co-development of artefacts and understanding. Heidegger argued that, for the skilled craftsperson, the ‘equipment’, the assemblage of tools, becomes ‘ready-to-hand’, almost invisible with focus on the job at hand not the tools used to perform it. Breakdown, when the tool becomes apparent, is often a sign of failure or poor design, but we can use this as a positive design heuristic, by understanding the causes of these failures, and preventing them. Paradoxically, it is these points of breakdown, when we become aware of what we are doing, not simply doing it, which can also be the prompt for reflection and innovation.
Connecting Physical and Digital Worlds

Abstract In language we link our thoughts to the physical world through names, symbols, and pointing. Similarly, there need to be means for the digital and physical worlds to connect. This chapter looks at the various ways in which this is managed from markers, such as the ubiquitous QR code, inserted into the physical world, to digital traces of physical phenomena, such as biometrics or image recognition. Some of the marks in the environment are purely digital, such as NFC tags in clothes or credit cards, invisible to the human eye but capable of tracking a device or person. Others are more apparent and indeed may be aesthetically pleasing as well as functional. Devices around us may be isolated, but they increasingly talk to one another, creating a web of sensing, or maybe surveillance. Crucially, once linked to digital representations they allow the physical world to affect the digital.
The Built Environment

Abstract This chapter focuses on the relationships between the physical environment and the various digital informational augmentations that have been added to it over the years, increasing our understanding of space and perhaps time. Some of these layers are purely in the digital world: viewing streets or satellite views in Google maps. However, digital layers are also overlaying the physical world: viewing past times through augmented reality or hunting virtual Pokémon in the local park. Digital technology allows us to conquer distance and opens new forms of cultural experience. However, the same technologies that allow the world to be sensed and augmented through the Internet of Things, also open the door to surveillance and cyber-warfare. We are at a point when physical computing may degrade or enrich our humanity, the choice is ours to make.
Embodied Computation

Abstract Computation itself seems immaterial, but whether on your smartphone or in ‘the cloud’, it is very physical: electrons moving on silicon wafer, photons streaming along optical fibres. This chapter explores this physicality of computation. Physics puts fundamental limitations on computation, and the chapter shows how this means that computation and information must come together at the same point in time and space. Practically, we have not reached these limits, Moore’s Law drives the miniaturization and commoditization of computation, which in turn enables radical changes including the Internet of Things and even coating every surface with a computation. In robots, autonomous vehicles, drones, and Alexa in the living room computation is physically amongst us. However, physical computation has been around for many years: the success of market economies is due to the physical representation of information in money, a role that is now changing with digital currency and online commerce.
Body and Mind

Abstract In the past, mind and body were seen as separate: the brain like a distant general sending orders to corporeal troops. However, it is virtually impossible to describe one without the other. This chapter considers how we sense ourselves as well as the outside world, so that posture and facial expression affect feelings as well as being caused by them. It shows that simple activities, such as lifting a cup, are the result of a closed-loop control cycle of action and sensing. Fitts’ Law is well known in HCI as a ‘law’ of the human motor system, but it is in fact a cybernetic law of the extended human body – indeed, from the first stone tools to the modern computer, humans have always been cyborgs. Apparently internal plans and intentions turn out to be intermixed with physical sensing and action, so that some regard our very mind as embodied in the world.
Reproducibility

Abstract An idea externalized once is transient or maybe cabalistic, but once reproduced it becomes the driver of culture whether through print in books, or industrial processes in plastic toys. This chapter discusses how the need to reproduce in symbols and language naturally leads to discretization: each ‘A’, whilst written differently is the same letter, each LEGO brick needs to be the same to connect to the next. Reproducibility led to the emergence of industrial and consumer culture, and was essential for the growth of Amazon, and yet in an age of reproduction, scarcity is often the core of value and we seek singularity and irreproducible experiences. Oddly, we then capture the transient in recordings from cave paintings to Flickr. In an age of unremitted recording, the ‘infinite archive’, it seems we ‘capture’ everything, and yet the recording is decontextualized, potentially devaluing or dehumanizing the experience, challenging our notions of privacy, and enabling fake news.