Reviewerly/exHarmony huggingface dataset:
The Role of Gameful Elements, Bodily Interactions, and Musical Features in Fostering Engagement and Learning in Musical Serious Games

This contribution explores the connections between gameful elements, bodily interactions, and musical features in the context of three case studies of music learning applications, demonstrating the role of these components in accomplishing the application's task. The critical essential element common to the three case studies is engagement due to gameful elements and other design characteristics such as the choice of music materials and the link between their structural elements and full body/gestural interaction. Assessment and experimental results demonstrate that these characteristics deeply influence users' involvement, memory, and learning.
State Space Model and Queuing Network Based Cloud Resource Provisioning for Meshed Web Systems

Functions provided by Web applications are increasingly diverse which make their structures complicated and meshed. Cloud computing platforms provide elastic computing capacities for these meshed Web systems to guarantee Service Level Agreement (SLA). Though workloads of meshed Web systems usually change steadily and periodically in total, sometimes there are sudden fluctuations. In this paper, a hybrid State-space-model-and-Queuing-network based Feedback control method (SQF) is developed for auto-scaling Virtual Machines (VMs) allocated to each tier of meshed Web systems. For the case with workloads changing steadily, a State-space-model based static Feedback Control method (SFC) is proposed in SQF to stabilize request response times near the reference time. For unsteadily changing workloads, a Queuing-network based multi-tier collaborative Feedback Control method (QFC) is proposed for effectively eliminating bottlenecks. QFC builds a control system for each tier individually and uses the queuing network to measure the interaction relationships among different tiers. Experimental results show that QFC is able to improve the efficiency of eliminating bottlenecks (decreasing upper-limit SLA violation ratios by 31.99% <inline-formula><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula> 56.52%) with similar or a little bit high VM rental costs compared to existing methods while SFC obtains more stable response times for requests with reasonable additional costs.
Rosita's Cocina: Fun and Engaging Virtual Cooking and Spanish Education

When removed from their home immigrants often find it hard to maintain their culture, one of the ways they often hang on to it is through food. Rosita's Cocina is designed to help kids learn about their family's history, language, and traditional food. Rosita's Cocina is an app designed to teach kids to cook in a digital environment while their parents or grandparents cook the real dish. The digital twins of the ingredients and tools will allow the child to experiment with cooking techniques traditional to Mexican cooking in a safe way, while using familiar Mexican recipes like flan or chiles rellenos in order to teach new words and enforce and master old vocab. As they learn more about their traditional cuisine and the history behind their favorite dishes, they will also practice their Spanish to be better able to communicate with their elders who may have a language barrier. Rosita's Cocina also helps engage children in the process of cooking using tools they are familiar with and excited to use, integrating technology into meaningful cultural experiences. The simple recipe tool allows elders to record the dishes they remember from their childhoods and pass it down to the younger generations in a fun and engaging way for the elder and the child. Rosita's Cocina was designed in AdobeXD as a prototype and visualization for the ultimate goals of the application.
Arithmagical: Magical Platform Technology Towards a Strong AI Virtual Tutor

Arithmagical is an iOS/Android/Chrome app that lets you feed your real math homework to a virtual magical dragon, where AI turns correct answers into dragon food and incorrect answers into mathemagical adventures, with UX that exposes AR themes and seamless non-intrusive computer vision capture in a way accessible to toddlers (with shaky hands and short attention spans). Virtual pet emotional-connection interactivity, memory retention and additional open-ended AI-guided game creation generalize this towards a strong AI virtual tutor platform.
Towards an Inclusive Society: Review of Google Trends Data of User Interest in the Deaf Comparing to the Blind and the Disabled

The COVID-19 pandemic has brought great difficulties for the deaf, the blind and people with disabilities in general, in addition to the difficulties of everyday life. This study aims to examine the public interest in the social integration of the deaf and hard of hearing community during the pandemic and the pre-pandemic period in the context of an inclusive society. The empirical study is based on the analysis of statistical data provided by Google Trends, which is a big data analysis, relative measurement and information visualisation tool that allowed to get insight on gaps and inconstancy of information seekers’ interest within categories of science, people and society, law and government, and health. The study encourages researchers and social policy makers to pay extra attention to the social inclusion of the deaf, which, according to the research data, worsened during the pandemic more than other groups of the disabled.
Remote medical video region tamper detection system based on Wireless Sensor Network

INTRODUCTION: A new telemedicine video tamper detection system based on wireless sensor network is proposed and designed in this paper. OBJECTIVES: This work is proposed to improve the performance of telemedicine video communication and accurately detect the tamper area in telemedicine video. METHODS: The sensor nodes in the sensing layer are responsible for collecting telemedicine video information and transmitting the information to the data layer. The data layer completes the storage of information and transmits it to the processing layer. The detection module of the processing layer detects the tampered area of the telemedicine video through two parts: suspicious moving point calculation and tamper detection, and transmits the detection results to the application display layer for display. RESULTS: The experimental results show that the designed detection system can accurately detect the tampered area in the telemedicine video, and the packet loss rate is significantly reduced, and the maximum packet loss rate is no more than 1%. CONCLUSION: The proposed detection system for remote medical video based on wireless sensor network can better meet the requirements of region tamper detection.
A Multivariate-Based Provably Secure Certificateless Signature Scheme With Applications To The Internet Of Medical Things

Abstract Over the last few years, Internet of Medical Things (IoMT) has completely transformed the healthcare industry. It is bringing out the most notable, and unprecedented impacts on human health, and has totally changed the way we look at the healthcare industry. The healthcare sector all around the globe are leapfrogging, and adopting the technology, helping in transforming drastically in a very short span of time. However, as more and more number of medical devices are being connected to IoMT, security issues like ensuring authenticity and integrity of the transmitted data are also on the rise. In view of the context, there is a need of an efficient cryptographic primitive that can address these issues in a viable manner. A signature scheme seems to be the natural choice to mitigate the security concerns. But, traditional signature schemes, both public-key-infrastructure-based and Identity-based, have their own disadvantages, which makes them unsuitable for IoMT networks. Thus, to address the security issues and problems like certificate management and key escrow, herein, we put forward the first multivariate-based certificateless signature scheme, namely, Multivariate Certificateless Signature (Mul-CLS), which is built on top of the intractability of multivariate-quadratic (MQ) problem. The fact that multivariate public key cryptosystem provides fast, post-quantum safe and efficient primitives makes it a front-runner candidate among the other post-quantum cryptography candidates. Our scheme Mul-CLS provides existential unforgeability against chosen message and chosen identity Super Type I and Super Type II adversary if solving the MQ problem is NP-hard. In addition to that, our proposed Mul-CLS presents itself as a robust and cost-friendly cryptographic building block for building IoMT networks.
Frequent pattern mining algorithms in fog computing environments: A systematic review

Summary Recent advances in technology have resulted in generating or collecting massive volumes of data from rich data resources such as sensors and mobile devices in Internet of Things (IoT). Using data mining techniques can help overcome the mining problem in Fog computing environments which include millions of IoT devices. In addition, it can optimize response times, recourse consumption, and scalability in IoT applications. Frequent pattern mining, as one of the fundamental data mining tasks, is used for finding hidden patterns in such large datasets. The traditional data mining algorithms have many challenges such as scalability and resource consumption. This systematic review aimed to investigate the data mining algorithms, which focus on handling massive datasets, and present a technical taxonomy including the transaction‐centric, item‐centric, distributed, and parallel topics. The transaction‐centric and MapReduce‐based approaches were mostly utilized by 37% and 38%, respectively. Additionally, item‐centric, distributed, and parallel algorithms were employed 12% and 13%, respectively. The response time as a Quality of Service (QoS) factor had the highest percentage in the estimations of data mining algorithms (55%), followed by scalability (25%), and cost (20%). To the best of our knowledge, no study has focused on fog‐computing frequent pattern mining algorithms as one of the most important data mining tasks. This article aims to present a systematic review of the frequent pattern mining algorithms in fog computing and discuss the issues, challenges, and research perspectives for helping academia and industry leverage the power of data mining algorithms in fog computing.
Algorithm of Scenic Spot Tourism Route Planning Based on Convolution Neural Network

Based on convolution neural network, a tourism route planning method for scenic spots is proposed. The method of performing primitive trajectory adaptive learning is used to plan and design the tourism route nodes and path space. On this basis, the shortest distribution grid structure model of tourism routes is constructed. Using the visual servo mobile route optimization control method, the constraint parameters of tourism route planning are optimized. In order to avoid the crowded area of tourists and the shortest path as the planning standard, the path planning problem is regarded as a constraint problem. The convolution neural network is used to activate the constraint function with the shortest path, and the output planning results are calculated iteratively. The simulation results show that this method has good learning control ability and convergence performance and improves the reliability of scenic spot tourism route planning.
Combining Log Files and Monitoring Data to Detect Anomaly Patterns in a Data Center

Context—Anomaly detection in a data center is a challenging task, having to consider different services on various resources. Current literature shows the application of artificial intelligence and machine learning techniques to either log files or monitoring data: the former created by services at run time, while the latter produced by specific sensors directly on the physical or virtual machine. Objectives—We propose a model that exploits information both in log files and monitoring data to identify patterns and detect anomalies over time both at the service level and at the machine level. Methods—The key idea is to construct a specific dictionary for each log file which helps to extract anomalous n-grams in the feature matrix. Several techniques of Natural Language Processing, such as wordclouds and Topic modeling, have been used to enrich such dictionary. A clustering algorithm was then applied to the feature matrix to identify and group the various types of anomalies. On the other side, time series anomaly detection technique has been applied to sensors data in order to combine problems found in the log files with problems stored in the monitoring data. Several services (i.e., log files) running on the same machine have been grouped together with the monitoring metrics. Results—We have tested our approach on a real data center equipped with log files and monitoring data that can characterize the behaviour of physical and virtual resources in production. The data have been provided by the National Institute for Nuclear Physics in Italy. We have observed a correspondence between anomalies in log files and monitoring data, e.g., a decrease in memory usage or an increase in machine load. The results are extremely promising. Conclusions—Important outcomes have emerged thanks to the integration between these two types of data. Our model requires to integrate site administrators’ expertise in order to consider all critical scenarios in the data center and understand results properly.
An approach to enhance topic modeling by using paratext and nonnegative matrix factorizations

Abstract Given the growing expansion in the development and use of computational methods in humanities research, it is necessary to propose methodologies that properly explore the questions posed by different disciplines, considering the locality of both data and the process behind its generation. In the present work, we explore the problem of automatically identifying the main topics in collections of Nahua discourses known as huehuetlahtollis. Each document in the collections is introduced through an extended title, and it is a natural question if enhancing the role of title terms during the unsupervised learning process could enrich results. Aiming at explainability, we consider a model based on nonnegative matrix factorizations (NMF). An overview of the historical process behind the composition of the explored corpora suggests that titles reflect the point of view of the collection’s compiler in manners that justify viewing the paratext as a supplementary source on the material. Therefore, we propose a bi-objective NMF scheme that appropriately reflects the a priori knowledge on the corpus, linking and combining the information of titles and content to improve the accuracy in identifying topic groups and relevant terms within a corpus. By comparing three different schemes against the labels assigned by an expert, we show that our model better reflects the nature of data, translating into higher accuracy. Finally, we present some insights on the studied corpora derived from our analysis of identified relevant terms.
The scholarly record of the future: A technologist's perspective

This article is adapted from Todd Carpenter’s keynote presentation at the APE Annual Conference on January 11, 2022. It focuses on the scholarly record of the future from a technological perspective. It describes how the transition to data-driven science and an increased focus on discovery and interoperability of content, will shape the article of the future. For a “digitally native” scholarly record, developing and maintaining a digital infrastructure with high-quality metadata and identifiers is crucial. It is also emphasized that technology does not determine the direction or eventual destination of the scholarly record of the future.
Knowledge-aware hierarchical attention network for recommendation

Knowledge graphs have been introduced into recommender systems due to the rich connectivity information. Many knowledge-aware recommendation methods use graph neural networks (GNNs) to capture the high-order structural and semantic information of knowledge graphs. However, previous GNN-based methods have the following limitations: (1) they fail to make full use of the neighborhood information of entities and (2) they ignore the importance of user interaction sequences on reflecting user preferences. As such, these models are insufficient for generating accurate representations of users and items. In this study, we propose a Knowledge-aware Hierarchical Attention Network (KHAN) to provide better recommendation. Specifically, the proposed model mainly consists of an item encoder and a user encoder. The item encoder is equipped with a hierarchical attention network, which is used to generate entity (item) representations by carefully aggregating neighborhood information of entities. The user encoder is also designed to learn more informative user representations from user interaction sequences using multi-head self-attention. The learned user representations are then combined with user representations introduced in the item encoder through a gating mechanism to generate the final user representations. Extensive experiments on two real-world datasets about movie and restaurant recommendation demonstrate the effectiveness of our model.
Implementation of Neuro Nadi Method in Al-Qur’an Studies in Brunei

Neuro Nadi Method or known as Al-Baghdadi Method is a new method in the study of Qur’an in Brunei Darussalam. The diversity of forms and techniques in the study of Qur’an should be emphasized in order to increase the Qur’an reading among the community especially in Brunei. Therefore, surveys have been conducted on respondents studying using Neuro Nadi Method. Observations were also made to see its effectiveness in the study of Qur’an. The important elements have been discussed including the teaching techniques and aids used. Through positive effects and reactions from the respondents, Neuro Nadi Method in al-Qur’an studies that following the current teaching and learning will be able to help attract the people in this country to pursue the study of Qur’an and subsequently produce a generation who are morally noble and educated in the Qur’an studies.
TEI in the Wild

chapter Share on TEI in the Wild Authors: Brygg Ullmer Clemson University Clemson UniversitySearch about this author , Orit Shaer Wellesley College Wellesley CollegeSearch about this author , Ali Mazalek Toronto Metropolitan University Toronto Metropolitan UniversitySearch about this author , Caroline Hummels Search about this author Authors Info & Claims Weaving Fire into Form: Aspirations for Tangible and Embodied InteractionJuly 2022https://doi.org/10.1145/3544564.3544571Published:26 July 2022Publication History 0citation5DownloadsMetricsTotal Citations0Total Downloads5Last 12 Months4Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Mediating Technologies

chapter Share on Mediating Technologies Authors: Brygg Ullmer Clemson University Clemson UniversitySearch about this author , Orit Shaer Wellesley College Wellesley CollegeSearch about this author , Ali Mazalek Toronto Metropolitan University Toronto Metropolitan UniversitySearch about this author , Caroline Hummels Search about this author Authors Info & Claims Weaving Fire into Form: Aspirations for Tangible and Embodied InteractionJuly 2022https://doi.org/10.1145/3544564.3544574Published:26 July 2022Publication History 0citation3DownloadsMetricsTotal Citations0Total Downloads3Last 12 Months3Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Paths Forward: Aspirations for TEI

chapter Share on Paths Forward: Aspirations for TEI Authors: Brygg Ullmer Clemson University Clemson UniversitySearch about this author , Orit Shaer Wellesley College Wellesley CollegeSearch about this author , Ali Mazalek Toronto Metropolitan University Toronto Metropolitan UniversitySearch about this author , Caroline Hummels Search about this author Authors Info & Claims Weaving Fire into Form: Aspirations for Tangible and Embodied InteractionJuly 2022https://doi.org/10.1145/3544564.3544577Published:26 July 2022Publication History 0citation1DownloadsMetricsTotal Citations0Total Downloads1Last 12 Months1Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Summary

chapter Share on Summary Authors: Brygg Ullmer Clemson University Clemson UniversitySearch about this author , Orit Shaer Wellesley College Wellesley CollegeSearch about this author , Ali Mazalek Toronto Metropolitan University Toronto Metropolitan UniversitySearch about this author , Caroline Hummels Search about this author Authors Info & Claims Weaving Fire into Form: Aspirations for Tangible and Embodied InteractionJuly 2022https://doi.org/10.1145/3544564.3544578Published:26 July 2022Publication History 0citation1DownloadsMetricsTotal Citations0Total Downloads1Last 12 Months1Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Authors’ Biographies

chapter Share on Authors’ Biographies Authors: Brygg Ullmer Clemson University Clemson UniversitySearch about this author , Orit Shaer Wellesley College Wellesley CollegeSearch about this author , Ali Mazalek Toronto Metropolitan University Toronto Metropolitan UniversitySearch about this author , Caroline Hummels Search about this author Authors Info & Claims Weaving Fire into Form: Aspirations for Tangible and Embodied InteractionJuly 2022https://doi.org/10.1145/3544564.3544583Published:26 July 2022Publication History 0citation1DownloadsMetricsTotal Citations0Total Downloads1Last 12 Months1Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access