Reviewerly/exHarmony huggingface dataset:
Students, Vendor Platforms, and E-textbooks: Using E-books as E-textbooks

Since the summer of 2012, Natsuko has been involved in developing and implementing library data services.After joining the University of Michigan Library in 2009, the majority of her time and effort has been dedicated to textbook initiatives at the University of Michigan Library.Her research orientation and knowledge of both quantitative and qualitative methodological techniques
Mr. Serials Revisits Cataloging: Cataloging Electronic Serials and Internet Resources

This text describes the Alcuin Project, an informal project whose goal is to discover methods for effectively cataloging electronic serials and Internet resources at the North Carolina State University Libraries. The Project builds upon previous work including the Mr. Serials Process, DRA/World Wide Web gateway scripts, the Alex database, the Alcuin database, and cumulating in Son of SID. Each of these projects is briefly outlined and future directions are presented.
Scanning the Literature

Provides an overview of the technical articles and features of interest to readers that appear outside of this publication.
The 2011 State of Manufacturing Education

Abstract Title: The 2010 State of Manufacturing EducationAbstract:The paper will complement the work of other groups such as METEC to describe the status ofmanufacturing education. To this end the paper will document the results of a second annualsurvey of manufacturing educators and professionals assessing opinions about curriculumtopics and the health of manufacturing practice and education.[[[ Please note: The survey will not be conducted until the end of the 2010 calendar year andso the results will not be available until the draft paper submission. However the paper will bebased upon a paper accepted and presented in Louisville and as such should be acceptable forthe abstract review process. ]]]
A Model to Improve Security Questions Through Individualized Assistance

Security questions are considered a viable alternative for secondary and supplementary authentication. Security questions are susceptible to three types of attacks: blind (brute force), focused guess (statistical), and observation (research/personal). This research outlines how informing users of potential security threats through a security meter may improve security with minimal impact on usability and trust. A security-question authentication model is proposed that builds on the strengths of security question responses, chiefly their ease of recall and higher entropy, while mitigating the core weaknesses of the model, which are the lack of uniform answers and public accessibility to answers. Users that were made aware of the entropy of their responses were more likely to provide stronger responses to the security questions without affecting the repeatability of the responses to the questions but negatively impacting the memorability.
The Value of Transfer Activities when Developing Technological Knowledge and Skills

Patrick Rowsome's research areas/interests include the transfer of learning in technology education, pedagogical strategies within technology education, creativity and innovation within technology education, and social constructivism.At present, he is investigating the value of transfer activities in a workshop based context in developing skill and knowledge.This research area involves developing a strategy to facilitate transfer activities and how this can enhance the transfer from context to context.The research aims to identify the key elements needed to design and implement an efficient pedagogical strategy to promote design and innovation.
Understanding Plagiarism Using Boardman's Soft Systems Methodology

This paper explores plagiarism through the system's lens and takes you on a journey through the complex world of plagiarism using the tools of Boardman's Soft Systems Methodology (BSSM) to bring deeper insights into how plagiarism has proliferated the academic landscape.In a recent survey of 11 universities across the United States, DonaldMcCabe of Rutgers, The State University of New Jersey, showed that plagiarism is a growing phenomenon on campuses that, with the evolution of technology, is continuing to grow at an exponential rate.By applying the methods of systems thinking, we plan to present a deeper insight into this growing epidemic.Using BSSM as our lens and Systemigrams (i.e.Systemic Diagrams) as our modeling approach, we will map the multiple perspectives that are involved in understanding plagiarism as a system.Systemigrams allow us to represent the dynamics of a complex system in a graphical form by focusing on the relationships of the system.In this paper we will briefly review a few forms of plagiarism followed by a detailed analysis of plagiarism in the academic environment.We will also look into the reasons why students plagiarize and briefly discuss the role of technology in the manifestation and growth of plagiarism.Finally, we will present and discuss our Systemigram model and conclude with recommendations for the future state of plagiarism within the engineering education environment.
Cognitive Science as the Engine of Innovation: Beyond Human-Computer Interaction

Cognitive Science as the Engine of Innovation: Beyond Human-Computer Interaction Stuart Card (card@parc.com) Information Sciences and Technologies Laboratory, Xerox PARC 3333 Coyote Hill Road Palo Alto, CA 94304 USA Abstract About Stuart Card Successful sciences usually spawn successful applications and application disciplines; in fact, one is suspicious of a science that can’t claim practical results. The na ve view is that results from the science are applied to problems, as in an applied cognitive psychology, for example. The truth is more complex in general and it is particularly more complex for cognitive science. New advances in technology are amplifying still further the human role of informavore and the need for cognitive engineering and invention of cognitive products and government activities. The ability to meet these is a test of a cognitive engineering discipline and of the supporting sciences themselves. I am going to suggest some principles for organizing both cognitive science and the practical innovation around it by reflecting on what we have learned about using cognitive psychology in human- computer interaction. I will use this analysis to suggest a set of initiatives now within reach of the cognitive science community. Stuart Card is a Xerox Research Fellow and the manager of the User Interface Research group at the Xerox Palo Alto Research Center. With Allen Newell and Tom Moran from CMU, he founded an effort to develop models of human performance that could be used in information system design. His thesis at CMU was the first thesis specifically in the new specialty of human-computer interaction. His study of input devices led to the Fitt’s Law characterization of the mouse and was an important factor leading to the mouse’s commercial introduction. He and his group have developed a number of theories of human-machine interaction, including tne Model Human Processor, the GOMS theory of user interaction, and information foraging theory. They have developed new paradigms of human-machine interaction, including the Rooms workspace manager and the Information Visualizer. The work has resulted in nine Xerox products and the founding of Inxight Software, Inc. Card is a co-author of the book, The Psychology of Human-Computer Interaction , a co-editor of the book, Human Performance Models for Computer-Aided Engineering , and has served on many editorial boards. He received his A.B. in Physics from Oberlin College and his Ph.D. in Psychology from Carnegie Mellon, where he pursued an interdisciplinary program in psychology, artificial intelligence, and computer science. His most recent book, Readings in Infomration Visualization , co-written and edited with Jock Mackinlay and Ben Schneiderman, was published in January 1999.
Integration Of Satcom And Gps Into A Technology Curriculum

Satellite communication systems (Satcom) represent the state-of-the-art in advanced communication of digital voice and data.For mobile users, the system requires a hightechnology antenna capable of locking on and tracking a geostationary satellite orbiting the earth, as well as a device capable of both transmitting and receiving modulated information to and from the satellite.Penn State Erie, the Behrend College is working on integrating into their curriculum Satcom technology.This year, two industrial sponsored senior design projects involve electrical engineering technology (EET) students.These projects provide the students involved with hands-on Satcom experience in solving real-world industrial problems.In the first project, one EET student is working with two electrical engineering (EE) students as interdisciplinary teammates to test the link margin effects of a Satcom receiver due to environmental conditions such as rain, snow, ice, etc.In the second project, two EET students are also teamed with two EE students to test bit error rates for a newly-designed Satcom receiver.In the future, it is anticipated that the need for technologists who understand Satcom systems will allow Penn State Behrend to offer a technical elective to teach the design, operation and maintenance of Satcom systems.In addition, the Satcom technology could be expanded to include global positioning satellite (GPS) systems.GPS systems are primarily used for state-of-the-art navigation, position, velocity and precise time information.Systems are now being used in automobiles as intelligent vehicle systems to provide position tracking and speed sensing.They are also used in aircraft for precision approaches, attitude information and will soon provide a means for enhanced detection of terrain obstacles and next-generation air traffic control systems.Other applications exist in the fleet management, agriculture and construction industries.
Study on the Evaluation System of Websites of College Ideological and Political Education Based on RBF Neural Network

Based on the characters and various index attributes of the websites of college ideological and political education, the multi-index hierarchical structure for evaluation on the competitiveness indexes of the websites of college ideological and political education was constructed by using expert grading method. The evaluation index system for competitiveness indexes of the websites of ideological and political education was built. Based on this, the competitiveness indexes of the websites of ideological and political education were measured and calculated to quantify the competitiveness level of the websites. Secondly, evaluation and study were carried out on the competitiveness indexes of the websites of ideological and political education by means of RBF neural network algorithm. The simulation results show that the method combining expert grading method and RBF neural network for measuring and calculating the competitiveness indexes of the websites of ideological and political education has high effectiveness and reliability.
Digital Copyright Protection: Focus on Some Relevant Solutions

Copyright protection of digital content is considered a relevant problem of the current Internet since content digitalization and high performance interconnection networks have greatly increased the possibilities to reproduce and distribute digital content. Digital Rights Management (DRM) systems try to prevent the inappropriate or illegal use of copyrighted digital content. They are promoted by the major global media players, but they are also perceived as proprietary solutions that give rise to classic problems of privacy and fair use. On the other hand, watermarking protocols have become a possible solution to the problem of copyright protection. They have evolved during the last decade, and interesting proposals have been designed. This paper first presents current trends concerning the most significant solutions to the problem of copyright protection based on DRM systems and then focuses on the most promising approaches in the field of watermarking protocols. In this regard, the examined protocols are discussed in order to individuate which of them can better represent the right trade-off between opposite goals, such as, for example, security and easy of use, so as to prove that it is possible to implement open solutions compatible with the current web context without resorting to proprietary architectures or impairing the protection of copyrighted digital content.
STRAINet: Spatially Varying sTochastic Residual AdversarIal Networks for MRI Pelvic Organ Segmentation

Accurate segmentation of pelvic organs is important for prostate radiation therapy. Modern radiation therapy starts to use a magnetic resonance image (MRI) as an alternative to computed tomography image because of its superior soft tissue contrast and also free of risk from radiation exposure. However, segmentation of pelvic organs from MRI is a challenging problem due to inconsistent organ appearance across patients and also large intrapatient anatomical variations across treatment days. To address such challenges, we propose a novel deep network architecture, called “Spatially varying sTochastic Residual AdversarIal Network” (STRAINet), to delineate pelvic organs from MRI in an end-to-end fashion. Compared to the traditional fully convolutional networks (FCN), the proposed architecture has two main contributions: 1) inspired by the recent success of residual learning, we propose an evolutionary version of the residual unit, i.e., stochastic residual unit, and use it to the plain convolutional layers in the FCN. We further propose long-range stochastic residual connections to pass features from shallow layers to deep layers; and 2) we propose to integrate three previously proposed network strategies to form a new network for better medical image segmentation: a) we apply dilated convolution in the smallest resolution feature maps, so that we can gain a larger receptive field without overly losing spatial information; b) we propose a spatially varying convolutional layer that adapts convolutional filters to different regions of interest; and c) an adversarial network is proposed to further correct the segmented organ structures. Finally, STRAINet is used to iteratively refine the segmentation probability maps in an autocontext manner. Experimental results show that our STRAINet achieved the state-of-the-art segmentation accuracy. Further analysis also indicates that our proposed network components contribute most to the performance.
Energy-aware VM placement algorithms for the OpenStack Neat consolidation framework

One of the main challenges in cloud computing is an enormous amount of energy consumed in data-centers. Several researches have been conducted on Virtual Machine(VM) consolidation to optimize energy consumption. Among the proposed VM consolidations, OpenStack Neat is notable for its practicality. OpenStack Neat is an open-source consolidation framework that can seamlessly integrate to OpenStack, one of the most common and widely used open-source cloud management tool. The framework has components for deciding when to migrate VMs and for selecting suitable hosts for the VMs (VM placement). The VM placement algorithm of OpenStack Neat is called Modified Best-Fit Decreasing (MBFD). MBFD is based on a heuristic that handles only minimizing the number of servers. The heuristic is not only less energy efficient but also increases Service Level Agreement (SLA) violation and consequently cause more VM migrations. To improve the energy efficiency, we propose VM placement algorithms based on both bin-packing heuristics and servers’ power efficiency. In addition, we introduce a new bin-packing heuristic called a Medium-Fit (MF) to reduce SLA violation. To evaluate performance of the proposed algorithms we have conducted experiments using CloudSim on three cloud data-center scenarios: homogeneous, heterogeneous and default. Workloads that run in the data-centers are generated from traces of PlanetLab and Bitbrains clouds. The results of the experiment show up-to 67% improvement in energy consumption and up-to 78% and 46% reduction in SLA violation and amount of VM migrations, respectively. Moreover, all improvements are statistically significant with significance level of 0.01.
Perspectives on how to evaluate augmented reality technology tools for education: a systematic review

Education has benefited from augmented reality’s (AR) potential to promote interactive experiences both inside and outside the classroom. A systematic review was conducted on how AR’s impact in the learning process has been evaluated. We selected papers from 2009 to 2017 in three databases, IEEE, ACM, and Science Direct, using an open-source crawler, and in one Brazilian Conference, SBIE. We followed the PRISMA protocol. Forty-five works were selected and used to extract data for our research. They were also analyzed according to quantitative and qualitative criteria. The results from all the papers are available in an online database. Results evidenced an increase in the number of papers evaluating the AR’s impact in education. They also showed that AR has been applied in different areas and contexts. Most papers reported positive outcomes as a result of AR insertion. However, most studies lacked the involvement of the teacher and the use of multiple metrics to evaluate educational gains.
Immersive Virtual Reality Attacks and the Human Joystick

This is one of the first accounts for the security analysis of consumer immersive Virtual Reality (VR) systems. This work breaks new ground, coins new terms, and constructs proof of concept implementations of attacks related to immersive VR. Our work used the two most widely adopted immersive VR systems, the HTC Vive, and the Oculus Rift. More specifically, we were able to create attacks that can potentially disorient users, turn their Head Mounted Display (HMD) camera on without their knowledge, overlay images in their field of vision, and modify VR environmental factors that force them into hitting physical objects and walls. Finally, we illustrate through a human participant deception study the success of being able to exploit VR systems to control immersed users and move them to a location in physical space without their knowledge. We term this the Human Joystick Attack. We conclude our work with future research directions and ways to enhance the security of these systems.
The Influence of Mixed Reality on Satisfaction and Brand Loyalty in Cultural Heritage Attractions: A Brand Equity Perspective

Mixed reality technology is being increasingly used in cultural heritage attractions to enhance visitors’ experiences. However, how the characteristics of mixed reality affect satisfaction and brand loyalty has not been explored in previous research. The purpose of this study is to identify factors affecting satisfaction with mixed reality experiences at cultural and artistic visitor attractions and their influence on brand loyalty, which is connected with management performance. We propose a theoretical model based on brand equity theory in the context of mixed reality experience. Survey data were gathered from 251 respondents visiting a cultural and artistic visitor attraction in Seoul, Korea, using a stratified sampling method. Partial least squares structural equation modeling (PLS-SEM) was employed for the data analysis. The results suggest that the characteristics of mixed reality (interactivity, vividness) not only influence the affective aspects (perceived immersion, perceived enjoyment) of visitors’ experiences, but also positively affect brand awareness, brand association, and brand loyalty.
Fast Haar Transforms for Graph Neural Networks

Graph Neural Networks (GNNs) have become a topic of intense research recently due to their powerful capability in high-dimensional classification and regression tasks for graph-structured data. However, as GNNs typically define the graph convolution by the orthonormal basis for the graph Laplacian, they suffer from high computational cost when the graph size is large. This paper introduces a Haar basis, which is a sparse and localized orthonormal system for a coarse-grained chain on the graph. The graph convolution under Haar basis, called Haar convolution, can be defined accordingly for GNNs. The sparsity and locality of the Haar basis allow Fast Haar Transforms (FHTs) on the graph, by which one then achieves a fast evaluation of Haar convolution between graph data and filters. We conduct experiments on GNNs equipped with Haar convolution, which demonstrates state-of-the-art results on graph-based regression and node classification tasks.
A Selective Overview of Deep Learning

Deep learning has achieved tremendous success in recent years. In simple words, deep learning uses the composition of many nonlinear functions to model the complex dependency between input features and labels. While neural networks have a long history, recent advances have significantly improved their empirical performance in computer vision, natural language processing and other predictive tasks. From the statistical and scientific perspective, it is natural to ask: What is deep learning? What are the new characteristics of deep learning, compared with classical statistical methods? What are the theoretical foundations of deep learning? To answer these questions, we introduce common neural network models (e.g., convolutional neural nets, recurrent neural nets, generative adversarial nets) and training techniques (e.g., stochastic gradient descent, dropout, batch normalization) from a statistical point of view. Along the way, we highlight new characteristics of deep learning (including depth and overparametrization) and explain their practical and theoretical benefits. We also sample recent results on theories of deep learning, many of which are only suggestive. While a complete understanding of deep learning remains elusive, we hope that our perspectives and discussions serve as a stimulus for new statistical research.
The promise of a decentralized internet: What is Web3 and how can firms prepare?

What is Web3, and what does it mean for established companies? Web3 describes a broad range of emerging internet applications for blockchain technology (i.e., a decentralized, public database that allows information to be securely recorded on a network of computers rather than verified and controlled by centralized entities). Central to this evolution of the internet are four distinct blockchain-enabled applications: fungible tokens (cryptocurrencies), nonfungible tokens (NFTs), decentralized autonomous organizations (DAOs), and metaverses. In this article, we define each of these applications and discuss their capacity to increase peer-to-peer interactions, decrease large companies’ control of information and services, and facilitate access to user networks at a much lower cost than currently possible. These distinctions make Web3 both a natural evolution of Web 2.0 and a broader paradigm shift that may fundamentally alter the online interface, organizational structure, and business practices. We conclude by addressing how established companies can prepare for a more decentralized internet.