Reviewerly/exHarmony huggingface dataset:
The Use of Pyrite Chemistry to Vector toward Gold Mineralization, an Example from the Drogo Prospect, Nunavut, Canada

Abstract Anomalous high grade Au mineralization has been found in float material at the Drogo Prospect, Nunavut, Canada. However, traditional exploration methods have thus far been unable to find the bedrock source of the mineralization. Recent studies have shown that pyrite trace element chemistry, as determined using LA-ICP-MS, varies between Au-forming and barren fluids. To test whether this also occurred at the Drogo Prospect, we analyzed pyrite in rock samples, including Au-rich samples, moderate Au grade samples, and barren samples. However, little variation in pyrite trace element chemistry was observed, suggesting that pyrite trace element chemistry may not be an effective exploration tool at the Drogo Prospect. To confirm these observations, cluster analysis was used to determine if natural clustering of the data could highlight which samples were more likely to be Au rich; again, no statistical differences could be found between the samples. In contrast to our working hypothesis, this suggests that pyrite trace element chemistry is not an effective exploration tool to find the bedrock source of the Drogo boulder trend.
An adaptive enhancement method based on stochastic parallel gradient descent of glioma image

Abstract Brain tumour diagnosis is significant for both physicians and patients, but the low contrast and the artefacts of MRI glioma images always affect the diagnostic accuracy. The existing mainstream image enhancement methods are insufficient in improving contrast and suppressing artefacts simultaneously. To enrich the field of glioma image enhancement, this research proposed a glioma image enhancement method based on histogram modification and total variational using stochastic parallel gradient descent (SPGD) algorithm. Firstly, this method modifies the cumulative distribution function on the image histogram and performs gamma correction on the image according to the modified histogram to obtain a contrast‐enhanced image. Then, the method suppresses the artefacts of glioma images by total variational and wavelet denoising algorithm. To get better enhancement images, the optimal parameters in the proposed method are searched by the SPGD algorithm. The statistical studies performed on 580 real glioma images demonstrate that the authors’ approach can outperform the existing mainstream image enhancement methods. The results show that the proposed method increases the discrete entropy of the image by 8.9% and the contrast by 2.8% compared to original images. The enhanced images are produced by the proposed method with a natural appearance, appealing contrast, less degradation, and reasonable detail preservation.
A Systematic Literature Review on 360° Panoramic Applications in Architecture, Engineering, and Construction (AEC) Industry

While the advancement of visualization technologies—virtual-reality, augmented-reality, mixed-reality, and extended reality—has long produced opportunities to create more realistic simulated environments to provoke and study natural human behavior, recent interest in applying 360° panoramic visualizations has been increasing across several disciplines due to these technologies’ lower costs, higher presence, and greater immersive-ness. However, the variety of applications of 360° panoramas (both images and videos) is limited in the architecture, engineering, and construction (AEC) domain compared to other domains. This paper systematically presents an in-depth understanding of 360° panorama research trends and reveals the challenges and opportunities for future research in the AEC area. In particular, this systematic review analyzed eighty studies across two decades (2000-2022) to consider 360° panoramas’ application areas, methodologies, potential benefits, challenges, best practices, and future research directions for both AEC and non-AEC domains. Several prevalent application domains in AEC—namely architectural studies, construction education and training, construction visualization and progress monitoring, and cognitive analysis and human behavior in the construction industry—were identified. This paper indicates that 360° panoramas provide a higher sense of presence than conventional simulation methods (e.g., virtual reality). Moreover, pairing 360° panorama technologies with a head-mounted display significantly increases immersion when compared with other display options. Lastly, limitations of 360° panoramas, such as cybersickness and technical properties, are discussed. This paper is expected to shed light on the potential of these state-of-the-art technologies in the AEC domain, which can serve both academia and industry.
Thoreau, Parrhesia, and the Socratic Tradition of Philosophy

Abstract Most objections against Henry Thoreau aim at his “unfriendly” provocations. In this article, I argue that we need to situate his exhortative style in the context of practicing parrhesia or the bold expression of truth in the Socratic tradition of philosophy. Philosophical parrhesia can be defined as the practice of speaking the truth with an eye to bringing home the realization that one must change one's life. The transformation Thoreau has in mind is hinged upon acquiring the practical knowledge of cultivating the senses through what he calls “excursion.” This, I argue, is his key contribution to the said tradition.
The Hidden History of the Like Button: From Decentralized Data to Semantic Enclosure

Artificial intelligence relies on the use of semantic technologies to represent the shared world of humanity. The story of how this came to be is exemplified by the use of Semantic Web standards by the Facebook “Like” button. In the case of the “Like” button, a decentralized and open Semantic Web was used to fuel the accumulation of personal data for advertising throughout the entire Web. The advent of the “Like button” was shortly followed by Google’s creation of the Google Knowledge Graph, a private corporate version of the Semantic Web. In fact, every major company in Silicon Valley soon created its own knowledge graph. The Semantic Web was transformed from a democratic project for standardized open knowledge to a project of control, collapsing semantics and erasing the difference between the object qua object and the object as represented in a knowledge graph.
HCI-E$$^2$$-2023: Second IFIP WG 2.7/13.4 Workshop on HCI Engineering Education

This second workshop on HCI Engineering Education aims at carrying forward work on identifying, examining, structuring, and sharing educational resources and approaches to support the process of teaching/learning Human-Computer Interaction (HCI) Engineering. The widening range of available interaction technologies and their applications in increasingly varied contexts (private or professional) underlines the importance of teaching HCI Engineering but also the difficulty of taking into account changes and developments in this field in often static university curricula. Besides, as these technologies are taught in diverse curricula (ranging from Human Factors and Psychology to hardcore Computer Science), we are interested in what the best approaches and best practices are to integrate HCI Engineering topics in the curricula of programs in Software Engineering, Computer Science, Human-computer Interaction, Psychology, Design, etc. The workshop is proposed on behalf of the IFIP Working Group 2.7/13.4 on User Interface Engineering.
Understanding HCI Approaches for the Metaverse in Education Applications for the Global South

The recent adoption of the Metaverse in various sectors indicates its potential for digital transformation. Technologies like XR, where X = Augmented/ Virtual/ Mixed Reality, will be its key enablers and can be powerful tools for developing nations’ digital educational transformation. These developing nations are often categorized under the Global South. This workshop presents a first step toward the socio-technical Human-Computer Interaction (HCI) aspects of the Metaverse to understand its impact on education in the Global South. The socio-technical approach helps cover human, social, and organizational factors, leading to more acceptable systems for end users and stakeholders. With the Metaverse, students, and teachers can log in via different immersive devices and experience different virtual environments fabricated to their individual needs, learning, and teaching styles. It will open up possibilities to explore new situations and access facilities that might be impossible due to physical world constraints. Two key concepts will be covered – (i) A socio-technical HCI approach to the Metaverse and (ii) an Interaction Design perspective on Avatar representation and understanding of human work in the Metaverse. This workshop will initiate dialogs on questions: (a) What are the socio-technical issues of the Metaverse for education in the global south? (b) Are there any cross-cultural usability and interaction design concerns regarding digital avatar representation? (c) What considerations will be required for educational Metaverse human-work interaction design?
Sustainable Human-Work Interaction Designs

Sustainability is a multidimensional concept with dimensions intertwined. The field of sustainable HCI explores ways to design interactive systems in a more sustainable way and to make user behavior more sustainable. In addition, social justice and equity aspects became emergent domains in HCI during the last decade. To develop interactive systems for the workplace, research on Human Work Interaction Design integrated work analysis and interaction design methods from HCI. As little HWID research has so far addressed environmental, economic, and social dimensions of sustainability, this workshop is an opportunity to start a discussion on the subject. This workshop on sustainable human-work interaction designs aims to (a) investigate processes and methods for creating sustainable designs and workplaces, (b) collect case studies that analyze experiences with introducing and learning from sustainability at work, and (c) formulate a research agenda for future work on sustainable human-work interaction designs. The target audience for the workshop is researchers and practitioners working on topics related to work analysis, interaction design, green IT, digital transformation, slow design, craft design, system-organization fit, organizational implementation, benefits realization, and in-the-wild evaluation.
Anomaly Detection Using Deep Learning Respecting the Resources on Board a CubeSat

We explore the feasibility of onboard anomaly detection using artificial neural networks for CubeSat systems and related spacecraft where computing resources are limited. We gather data for training and evaluation using a CubeSat in a laboratory for a scenario where a malfunctioning component affects temperature fluctuations across the control system. This data, published in an open repository, guides the selection of suitable features, neural network architecture, and metrics comprising our anomaly detection algorithm. The precision and recall of the algorithm demonstrate improvements as compared to out-of-limit methods, whereas our open-source implementation for a typical microcontroller exhibits small memory overhead, and hence may coexist with existing control software without introducing new hardware. These features make our solution feasible to deploy on board a CubeSat, and thus on other, more advanced types of satellites.
VR Accessibility in Distance Adult Education

As virtual reality (VR) technology becomes more pervasive, it continues to find multiple new uses beyond research laboratories. One of them is distance adult education—the potential of VR to provide valuable education experiences is massive, despite the current barriers to its widespread application. Nevertheless, recent trends demonstrate clearly that VR is on the rise in education settings, and VR-only courses are becoming more popular across the globe. This trend will continue as more affordable VR solutions are released commercially, increasing the number of education institutions that benefit from the technology. No accessibility guidelines exist at present that are created specifically for the design, development, and use of VR hardware and software in distance education. The purpose of this workshop is to address this niche. It gathers researchers and practitioners who are interested in education and intend to work together to formulate a set of practical guidelines for the use of VR in distance adult education to make it accessible to a wider range of people.
Algorithmic Affordances in Recommender Interfaces

Recommenders play a significant role in our daily lives, making decisions for users on a regular basis. Their widespread adoption necessitates a thorough examination of how users interact with recommenders and the algorithms that drive them. An important form of interaction in these systems are algorithmic affordances: means that provide users with perceptible control over the algorithm by, for instance, providing context (‘find a movie for this profile’), weighing criteria (‘most important is the main actor’), or evaluating results (‘loved this movie’). The assumption is that these algorithmic affordances impact interaction qualities such as transparency, trust, autonomy, and serendipity, and as a result, they impact the user experience. Currently, the precise nature of the relation between algorithmic affordances, their specific implementations in the interface, interaction qualities, and user experience remains unclear. Subjects that will be discussed during the workshop, therefore, include but are not limited to the impact of algorithmic affordances and their implementations on interaction qualities, balances between cognitive overload and transparency in recommender interfaces containing algorithmic affordances; and reasons why research into these types of interfaces sometimes fails to cross the research-practice gap and are not landing in the design practice. As a potential solution the workshop committee proposes a library of examples of algorithmic affordances design patterns and their implementations in recommender interfaces enriched with academic research concerning their impact. The final part of the workshop will be dedicated to formulating guiding principles for such a library.
Building Teamwork: Mixed Reality Game for Developing Trust and Communication

Cultivating teamwork and a sense of empathy is an important part of boosting productivity and student and employee satisfaction and well-being. We present the initial development of a mixed-reality game using a LEGO block digitization system. Two participants collaborate, with one in real life and the other in VR. Our initial results indicate a positive impact on empathy and user involvement. Moving forward, we aim to create various teamwork experiences using different VR interactions with digitized LEGO builds both for children’s educational purposes and adult teamwork.
Co-designing Immersive Virtual and Extended Reality Systems for Remote and Unsupervised Interaction, Intervention, Training and Research

We propose a one-day transdisciplinary workshop in the broad area of HCI focused on co-designing immersive virtual reality (IVR) for remote and unsupervised interaction, intervention, training and research. The development and deployment of such systems is a significant and important challenge. While remote and unsupervised systems are more accessible to a wider user-base, their design, implementation and deployment poses unique challenges, related to the need to involve truly transdisciplinary design teams, co-designing solutions with users, providing step-by-step interaction scenarios, and retaining user motivation and engagement over longer periods of time. Moreover, there are multiple ethical considerations related to both the inclusivity and accessibility of such systems and the security of data collected. Therefore, to facilitate the use of IVR systems in various contexts, ranging from unique interactions and research, through psychological interventions, to education and training, we propose to formulate a set of best practices. Taking into account the diverse aspects involved, we will formulate actionable guidelines for co-designing such solutions with users based on review of extant literature, expert knowledge, case studies and insights from the workshop.
ARTour: an augmented reality collaborative experience for enhancing tourism

Abstract Serious games have been recently used for different purposes; a few of them have been developed to support cultural heritage purposes. Pandemics, for instance, change a lot in people’s lives and cause some changes, such as social distancing and lower mobility. Additionally, individuals with physical challenges do not always have the opportunity to experience heritage sites as if they were there. Hence, arises the need for applications that encourage the precautionary measures required without totally isolating the users in similar conditions. The existing serious games in the literature have proven effective for teaching cultural heritage and enhancing tourists’ experiences while at the heritage site. However, less serious games focused on giving the tourists a similar experience, but in the comfort of their homes. Therefore, this study discusses the design, development, and evaluation of ARTour. ARTour is a collaborative serious game that increases players’ engagement and enhances the overall experience, without exposing them to danger during pandemics or similar situations. The player can choose between existing heritage sites, and a timeline, in order to get the full experience.
Calculation and evaluation of similarity in sports information resources based on combined algorithm

Abstract It is helpful for athletes to obtain real-time and accurate sports information resources by integrating various recommendation algorithms into a personalised sports recommendation system. Therefore, this paper designs user-based and content-based recommendation algorithms, and recommends their results to sporters by weighted selection. In addition, by acquiring the characteristics of sporters, the method of the constraint space of core parameters is determined by using ontology rule reasoning, which ensures the rationality of sports parameter extraction, and thus establishes the similarity calculation model of sports resources and designs the strategy and method of model verification. Finally, the validity of the model is evaluated by Mahalanobis distance, and the recommendation effects of different algorithms are compared by similarity grade, which can provide sporters with personalised sports resources with stronger pertinence and better effect.
A Comparative Study of Motion Feature Recognition under Different Learning Methods

Abstract The accurate analysis and prediction of human motion posture can provide effective data support for sports training. With the continuous progress of computer science and technology and the gradual maturity of artificial intelligence technology, there is still some controversy about the recognition effect of motion features under different algorithms. Therefore, this paper compares the recognition effects of different learning methods, including two machine learning methods by using k-means classification, such as SVM and a deep learning method CNN. The motion data of three basic movements, such as running, jumping and turning, are collected and their feature information is extracted by sensor equipment. The recognition effect is compared with the overall accuracy rate as the evaluation index. Among them, when k-means classification is used, through feature extraction and selection, the final combination of mean and variance features is obtained and applied to SVM. When CNN is adopted, its performance can be optimised by adjusting its network structure and some super parameters in the convolution layer and pool layer.
Embracing AI: Using Cat-GPT to Encourage Classroom Discussion

AbstractWhile some resist the use of artificial intelligence (AI) in the classroom, fearing plagiarism and misinformation, others view it as a powerful tool for learning that can help students and instructors alike. Because of students’ enthusiasm for such tools, it is important for instructors to address their use. As such, the purpose of this “quick fix” is to explore one possibility for embracing responsible use of AI in the classroom. Namely, I discuss the utility of introducing students to Cat-GPT, a generative language tool similar to Chat-GPT that generates lighthearted, but still thoughtful, responses to queries, alongside silly cat animations. I discuss utility of the tool for guiding students in exercises meant to help them to find ways to expand upon their knowledge. I find that the contrast of the whimsical language with the power of the tool make it especially fun for class activities and discussion. Students appreciate the silliness, and it captures their attention enough to allow for serious classroom discussions about the benefits and drawbacks of AI tools.Keywords: Artificial IntelligenceCat-GPTgenerative languagelearning tools Disclosure statementNo potential conflict of interest was reported by the authors.
Hybrid data‐driven modeling for accurate prediction of quality parameters in sugarcane milling with fine‐tuning

Abstract The data‐driven model for predicting sugarcane milling quality parameters is crucial for optimization. Current challenges include real‐time data acquisition and limited labeled data, reducing model accuracy and raising data collection costs. There is an urgent need to utilize unlabeled data to establish data‐driven models for sugarcane milling. This study introduces novel hybrid strategies, namely combining Convolutional Neural Network (CNN) with Kernel Extreme Learning Machine (KELM), utilizing pre‐training and fine‐tuning techniques. These strategies include CNN‐KELM and Transfer Learning CNN‐KELM (TL‐CNN‐KELM). Results demonstrate superior accuracy compared to single algorithms. TL‐CNN‐KELM, leveraging unlabeled data through transfer learning, achieves reductions of 0.007 in mean squared error and 0.005 in mean absolute error for extraction rate predictions. For initial juice sugar content predictions, reductions of 0.027 in mean squared error and 0.012 in mean absolute error are attained. This approach demonstrates enhanced accuracy in predicting quality parameters while maintaining robustness to data size. Practical Applications This work can reduce the data acquisition cost for quality parameter prediction and accelerate the intellectualization of sugarcane milling. In production practice, there are many process industries similar to sugarcane milling, so the novel algorithms also provide an idea for the quality parameter optimization and prediction of other process industries.
Time-stage driven pathfinding framework for optimized medical treatments

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Bird's eye view of augmented reality and applications for education and training: A survey of surveys and reviews

Abstract Augmented reality (AR) is a field of knowledge being developed since the middle of the last century. Its use has been spreading because of its usefulness, but more recently because of mobile platforms being widespread and accessible. AR has been applied in several fields of activity, and also in the field of Education and Training, because AR has several advantages over other teaching methods. In this paper, we search and analyze surveys and reviews of AR to present a brief history and its definition. We also present a classification of our sample under a scheme we developed in past work, and present also examples of technologies and applications of AR in each field. Finally, we do a deeper analysis over the publications of Education and Training, advantages and issues of AR in this field, and some research trends.