Reviewerly/exHarmony huggingface dataset:
Evaluating the Acceptance of Blended-Learning Tools: A Case Study Using SlideWiki Presentation Rooms

As e-learning formats become increasingly important, technological assistance becomes a critical factor for its implementation. The tool SlideWiki Presentation Rooms tries to combine the needs and functions of live interaction with the advantages of e-learning. To evaluate the acceptance of the tool a teaching experiment was conducted at an University of Applied Sciences. The results show, that the actual usage of a new blended-learning tool is more determined by the perceived usefulness than the ease of use and implicates further influence factors on students acceptance towards SlideWiki. They provide valuable insights for the successful implementation of blended-learning tools in higher education and need to be further examined in future studies.
100 Years of Soil Science Society in the U.S.

CSA NewsVolume 65, Issue 6 p. 26-27 MEMBERSHIP 100 Years of Soil Science Society in the U.S. Alfred E. Hartemink, Alfred E. Hartemink University of Wisconsin–Madison, Department of Soil Science, MadisonSearch for more papers by this authorStephen H. Anderson, Stephen H. Anderson University of Missouri, School of Natural Resources, ColumbiaSearch for more papers by this author Alfred E. Hartemink, Alfred E. Hartemink University of Wisconsin–Madison, Department of Soil Science, MadisonSearch for more papers by this authorStephen H. Anderson, Stephen H. Anderson University of Missouri, School of Natural Resources, ColumbiaSearch for more papers by this author First published: 14 May 2020 https://doi.org/10.1002/csan.20144Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume65, Issue6June 2020Pages 26-27 RelatedInformation
A Model for Virtual Hand Ownership in Augmented Reality

In the classic rubber hand illusion participants can experience ownership over a fake limb. Variations across media such as the virtual hand illusion in virtual and augmented reality show similar findings. Previous studies have shown that the ownership experience may be the result of the integration of neurocognitive top-down and bottom-up processes. Yet, there are frequently occurring individual differences between participants that cannot be explained solely in this way. We present a two-level processing model for the experience of virtual hand ownership, based on (1) the construction of a tentative hand model and (2) the testing of ownership over this hand model. While the first level processing closely follows existing ownership models, the novel second level processing is suggested to be influenced by a number of new factors that can lead to individual differences. We support the model through a literature review, and moreover use an experiment for the second level. In this experiment, we show that a participant’s immersive tendency, a personality trait that describes one’s capability to become immersed in mediated environments, influences their susceptibility to owning a virtual hand in augmented reality. Our results illustrate that to a certain extent individual differences in rubber hand illusion studies can be explained by specific personality traits, and we place this in a model to advance our understanding of the underlying mechanisms that shape the experience of ownership.
Analysis of Chinese Tourists Occur Safety Problem in Chiang Mai Thailand

The main purpose of this article was to design a Tourist Safety Knowledge Map for Chinese tourist travel to Chiang Mai, Thailand. The data of this paper were from related Chinese tourism website and Thai government officially department, it would use to identify the research problem of this paper. Then the Focus Group and Common KADS - knowledge model would be representative of Demand side and Supply side in the step of research methodology. The research result of this paper would include the precaution of Chinese tourist visit Chiang Mai and also the solution after Chinese tourist occur safety problem in Chiang Mai. Chinese tourist could check matters that need be attention in the Knowledge Map.
Good News and Bad News About Incentives to Violate the Health Insurance Portability and Accountability Act (HIPAA): Scenario-Based Questionnaire Study

Background The health care industry has more insider breaches than any other industry. Soon-to-be graduates are the trusted insiders of tomorrow, and their knowledge can be used to compromise organizational security systems. Objective The objective of this paper was to identify the role that monetary incentives play in violating the Health Insurance Portability and Accountability Act’s (HIPAA) regulations and privacy laws by the next generation of employees. The research model was developed using the economics of crime literature and rational choice theory. The primary research question was whether higher perceptions of being apprehended for violating HIPAA regulations were related to higher requirements for monetary incentives. Methods Five scenarios were developed to determine if monetary incentives could be used to influence subjects to illegally obtain health care information and to release that information to individuals and media outlets. The subjects were also asked about the probability of getting caught for violating HIPAA laws. Correlation analysis was used to determine whether higher perceptions of being apprehended for violating HIPAA regulations were related to higher requirements for monetary incentives. Results Many of the subjects believed there was a high probability of being caught. Nevertheless, many of them could be incentivized to violate HIPAA laws. In the nursing scenario, 45.9% (240/523) of the participants indicated that there is a price, ranging from US $1000 to over US $10 million, that is acceptable for violating HIPAA laws. In the doctors’ scenario, 35.4% (185/523) of the participants indicated that there is a price, ranging from US $1000 to over US $10 million, for violating HIPAA laws. In the insurance agent scenario, 45.1% (236/523) of the participants indicated that there is a price, ranging from US $1000 to over US $10 million, for violating HIPAA laws. When a personal context is involved, the percentages substantially increase. In the scenario where an experimental treatment for the subject’s mother is needed, which is not covered by insurance, 78.4% (410/523) of the participants would accept US $100,000 from a media outlet for the medical records of a politician. In the scenario where US $50,000 is needed to obtain medical records about a famous reality star to help a friend in need of emergency medical transportation, 64.6% (338/523) of the participants would accept the money. Conclusions A key finding of this study is that individuals perceiving a high probability of being caught are less likely to release private information. However, when the personal context involves a friend or family member, such as a mother, they will probably succumb to the incentive, regardless of the probability of being caught. The key to reducing noncompliance will be to implement organizational procedures and constantly monitor and develop educational and training programs to encourage HIPAA compliance.
Exploring Visual Techniques for Boundary Awareness During Interaction in Augmented Reality Head-Mounted Displays

Mid-air hand interaction has long been proposed as a ‘natural’ input method for Augmented Reality (AR) systems. Current AR Head-Mounted Displays (HMDs) have a limited area for hand-based interactions. Because of this, users may easily move their hand(s) outside this tracked area during interaction, especially in dynamic tasks (e.g., when translating an object). Compared to common midair interaction issues, such as gesture recognition, arm/hand fatigue, and unnatural ways of interacting with virtual objects (e.g., selecting a distant object), boundary awareness issues in AR devices have received little attention. In this research, we explore visual techniques for boundary awareness in AR HMDs, focusing on object translation tasks. Through a systematic formative study, we first identify the challenges that users might face when interacting with AR HMDs without any boundary awareness information (i.e., how current systems work). Based on the findings, we then propose four methods (i.e., static surfaces, dynamic surface(s), static coordinated lines, and dynamic coordinate line(s)) and evaluate them against the benchmark (i.e., baseline condition without boundary awareness) to make users aware of the tracked interaction area. Our results show that visual methods for boundary awareness can help with dynamic mid-air hand interactions in AR HMDs, but their effectiveness and application are user-dependent.
Benefits of Implementing Marketing Automation in Recruitment

Marketing and recruitment operate in similar settings: both strive to address people who most often are not looking for being addressed. While IT-support in marketing has been given its share of attention, the benefits of tools and automation in recruitment process are poorly researched. This paper explores these benefits. Eleven benefits have been identified from the literature and our interviews with recruiters. Five of these benefits are shared between recruitment and marketing, whereas six address relationship building and ethics more specific to recruitment.
Dependency Graph-based Reactivity for Virtual Environments

In Virtual Environments (VEs), the system must quickly respond to user actions and accurately display the result. Current solutions on the Unity3D game engine often respond too slowly and display temporarily inaccurate or misleading states, resulting in low user satisfaction. To alleviate this problem, we develop a reactive programming approach that encodes the complex relationships among Unity3D game components in a dependency graph and then uses the graph to order the updates of the components without violating the dependency constraints. This enables more timely updates and more accurate visualizations, potentially providing users with a more satisfying experience. We evaluate our approach by comparing its performance with native Unity3D and with UniRx, the Reactive Extensions library for the Unity3D platform.
Design and Implementation of a Knowledge-Based Expert System Shell

For the purpose of shortening the development cycle of expert system, an approach of developing a knowledge-based expert system shell is proposed. A friendly human machine interaction expert system shell is developed by the hybrid programming technology based on C Language Integrated Production System (CLIPS) and C++. And an efficient knowledge management mechanism is realized by SQL Server database. The main functional modules of this expert system shell include inference engine, knowledge base management system, knowledge base, fact base, interpreter and human machine interface. The correction of this expert system shell was validated through a case study that an expert system built by the expert system shell successfully aided diagnosed and treated an 11 years old adolescent idiopathic scoliosis patient. The results implied that the expert system shell proposed can build an expert system rapidly and effectively.
A Usability Assessment Of Augmented Situated Visualization

The present work proposes the use of data visualization techniques allied to an Augmented Reality (AR) user interface to provide information for users to define the most convenient location to sit down at an event. This accounts for different sets of arbitrary demands by projecting 3D information directly atop the seats. The users can also rearrange the data to narrow down the search and switch the attribute being displayed, e.g. temperature, stage visibility, exit access or Wi-Fi signal. The proposed approach was tested against a comparable 2D interactive visualization of the same data. Each user performed twelve location choosing tasks in an average sized classroom. Qualitative and quantitative data indicated that the augmented solution is promising in some senses, exposing that AR may help users to make better decisions.
Student Engagement and Smart Spaces

The purpose of this chapter is to provide evidence-based findings on student engagement within smart library spaces. The focus of smart libraries includes spaces that are enhanced with the internet of things (IoT) infrastructure and library collection maps accessed through a library-designed mobile application. The analysis herein explored IoT-based browsing within an undergraduate library collection. The open stacks and mobile infrastructure provided several years (2016-2019) of user-generated smart building data on browsing and selecting items in open stacks. The methods of analysis used in this chapter include transactional analysis and data visualization of IoT infrastructure logs. By analyzing server logs from the computing infrastructure that powers the IoT services, it is possible to infer in greater detail than heretofore possible the specifics of the way library collections are a target of undergraduate student engagement.
Patients’ Disease Risk Predictive Modeling using MIMIC Data

The latest MIMC III (Medical Information Mart for Intensive Care III) database has rich information on over 58k patient’s medical histories for over 11 years. Based on MIMC III database, this paper presents a study of those patient’s primary disease risk prediction modeling, which focuses on assessing future disease risks for an individual who is ready for discharge. We explore a framework that combines regression modeling and deep learning techniques to substantially improve the performance of developed models. Firstly, a regression model will be applied to predicting the length of stay for a patient’s future ICU visit. Secondly, deep learning approach will be adopted to assess individual’s future visit in terms of time and the primary disease. If the modeling gets adopted in a hospital, the predicted results can be promisingly utilized as a reference for medical professionals and experts to oﬀer eﬀective health care guidance for patients. The proposed framework can also be utilized for developing an innovative tool that helps individuals create and maintain a better healthcare plan over time.
Another day at the Office: Visuohaptic schizophrenia VR simulation

This paper presents Virtual Reality 3D interaction and simulation techniques in the context of the 2020 3DUI contest of the IEEE VR conference. This paper discusses the design and development of a scenario-based mental disorder simulation, aiming to empathize the end-user with the symptoms that a schizophrenic person faces. These techniques are integrated in the context of a virtual reality environment which serves as the medium to immerse the user to experience a vast number of schizophrenia symptoms, mainly focusing on the positive ones, such as mind delusions and auditory, visual, haptic hallucinations. The paper concludes with a discussion on the extensibility and translational application of the approaches in practical problem solving.
Real Walking in Place: HEX-CORE-PROTOTYPE Omnidirectional Treadmill

Locomotion is one of the most important problems in virtual reality. Real walking experience is the key to immersively explore the virtual world. Several strategies have been proposed to solve the problem, but most are not suitable to solve the locomotion problem in Room-Scale VR. The omnidirectional treadmill is an effective way to provide a natural walking experience within the Room-Scale VR. This paper proposes a novel omnidirectional treadmill named HEX-CORE-PROTOTYPE (HCP). The principle of synthesis and decomposition of velocity is applied to form an omnidirectional velocity field. Our system could provide a full degree of freedom and real walking experience in place. Compared to the current best system, the height of HCP is only 40% of it. The application shows the effectiveness of our system to solve the locomotion problem in Room-Scale VR.
An Improved Travel Package Framework Utilizing (COPE)

Main classification goals are to make adapted transportable platform endorsements for the sightseers founded on the concerned POI and to progress the recognition exactness and endorsement concert. Lastly, supports toward treasure correct portable correspondences based on the POI. It progresses the endorsement scheme by choosing optimum travel suites constructed on user modified POI. Assistances to determinate the tricky provided an instinctive modified journey scheduling and plans. In this work, we pronounce the evaluations among the prevailing approaches and the planned and proposed algorithm of COPE, technique through treating interruption, exactness, and amount of repetitions besides the treating period aimed at the quantity of records.
Distributed Operating System Security and Protection: A Short Survey

In this paper, we investigate several modern distributed operating systems (DiOSs) and their security policies and mechanisms. We survey the various security and protection issues present in DiOSs and review strategies and techniques used by DiOSs to control access to system resources and protect the integrity of the information stored in the system from accidental events and malicious activities. Further, we distinguish between network security and DiOSs security and explore the attack surface of DiOSs compared to traditional operating systems. We concentrate on a class of distributed operating systems known as cloud operating systems (COSs).
3D Image Reconstruction with Single-Slice CT using Improved Marching Cube Algorithm

Single-slice CT is still widely used in many hospitals because it prolongs the life cycle of the CT device components, especially that of x-ray. Using CT 3D image, it can be very helpful for a doctor in diagnosing medical information. In the development of 3D image reconstruction and computer technology, it is possible for the doctor to communicate with the patient through gadget media. This paper presents the determination of the threshold in single-slice Computerized Tomography (CT) for interactive 3D image reconstruction without user interface. The 3D image reconstruction method is the improved marching cube algorithm. The medical image object that consists of skull bone and sternum-pelvis in Digital Imaging and Communications in Medicine (DICOM) format is taken from single-slice CT. The resulting threshold for bone 3D image object is 200, except for the 3D image with quantity slice less than 10 can not be reconstructed. The difference in the surface volume and surface area between the 3D image reconstruction output from InVesalius software and project, for skull bone and sternum-pelvis is less than 0.5%. The justification of the visual shape match from three radiology doctors for skull bone and sternum-pelvis is approximately 99% match. Processing time to reconstruct the 3D image is around five minutes.
A Comparison Between a Natural and an Inorganic Locomotion Technique

Virtual reality is becoming a more popular attraction every year not only to researchers, but the general public as well. One of the major challenges standing in the way of virtual reality becoming even more widely accepted is the adaptation of new locomotion techniques. This paper attempts to discern between two different locomotion techniques and decide which method is more efficient based on certain parameters. The two techniques being analyzed were tested in a case study, one involving inorganic movement (touch pad control) and the other natural movement. The users tested both forms of locomotion separately by navigating through a predetermined course that is comprised of multiple checkpoints. Data such as efficiency and time were recorded via applications, as well as a post test survey that each of the participants were given. After all the data was collected, the results were analyzed and the most efficient and preferred form of movement was established.
Detection Thresholds for Vertical Gains in VR and Drone-based Telepresence Systems

Several redirected walking techniques have been introduced and analyzed in recent years, while the main focus was on manipulations in horizontal directions, in particular, by means of curvature, rotation, and translation gains. However, less research has been conducted on the manipulation of vertical movements and its possible use as a redirection technique. Actually, vertical movements are fundamentally important, e.g., for remotely steering a drone using a virtual reality headset.In this paper, we explored vertical gains, a novel redirection technique, which enables us to purposefully manipulate the mapping of the user’s physical vertical movements to movements in the virtual space and the remote space. This approach allows natural and more active physical control of a real drone. To demonstrate the usability of vertical gains, we implemented a telepresence drone and vertical redirection techniques for stretching and crouching actions using common VR devices. We conducted two user studies to investigate the effective manipulation ranges and its usability: one study using a virtual environment (VE), and one using a camera stream from a telepresence drone. The results revealed that our technique could manipulate a users vertical movement without her/his noticing.
Deciding Backup Location Methods for Distributed Stream Processing System

A large amount of stream data are generated from some devices such as sensors and cameras. These stream data should be timely processed for real-time applications to satisfy the data latency requirements. To process a large amount of data in a short time, utilizing stream processing on edge/fog computing is a promising technology. In the stream processing system, a snapshot of processes and replications of the stream data are stored on another server, and when server fault or load spike of server occurs, the process is continued by using the stored snapshots and replicated data. Therefore, with edge computing environment, which has low bandwidth resource, process recovery takes a long time due to the transferring of restored data. In this paper, we propose a stream processing system architecture to decide servers to store snapshots and replication data and redeploy processes by considering the load of each server and the network bandwidth. We also propose a semi-optimal algorithm that reduces the computational cost by appropriately sorting servers and tasks according to the network bandwidth and server load. The algorithm can find a solution over 1000 times faster than the Coin or Branch and Cut (CBC) solver.
Manifold Smoothed Class-specific Discriminant Collaborative Representation for Face Recognition

Representation based classifications are extensively used in many applications and have achieved remarkable successes. However, they still suffer from some problems. In one respect, the coefficients obtained are not competitive, which is not beneficial for classification. Also, the intrinsic manifold structure is not taken into consideration. It has been shown that the manifold smoothness is important for classification. To this end, based on collaborative representation, a new algorithm coined Manifold Smoothed Class-specific Discriminant Collaborative Representation, MSCDCR, for short, is proposed. Besides manifold structure, MSCDCR employs the whole training samples to code the test sample in a linear way, so that it can tell which class has the most similarity. The method proposed can reduced to a closed-form solution, which is time-efficient, and it also can exploit the intrinsic manifold geometric structure and discriminant information. Consequently, it bears more discriminant ability. Experiments are carried out on face recognition, and they show the relatively promising performance of the proposed algorithm.