Use of Scripted Role-Play in Evaluation of Multiple-User Multiple-Service Mobile Social and Pervasive Systems

2015 ◽  
Vol 7 (4) ◽  
pp. 35-52 ◽  
Author(s):  
Edel Jennings ◽  
Mark Roddy ◽  
Alexander J. Leckey ◽  
Guy Feigenblat
Keyword(s):  
Role Play ◽  
Physical World ◽  
End Users ◽  
Data Sets ◽  
User Engagement ◽  
Design Development ◽  
Multiple User ◽  
Short Period ◽  
Rich Data ◽  
Social Applications

Mobile and social computing is rapidly evolving towards a deeper integration with the physical world due to the proliferation of smart connected objects. It is widely acknowledged that involving end users in the design, development and evaluation of applications that function within the resulting complex socio-technical systems is crucial. However, reliable methods for managing evaluation of medium fidelity prototypes, whose utility is often dependent on rich data sets and/or the presence of multiple users simultaneously engaging in multiple activities, have not yet emerged. The authors report on the use of scripted role-play as an experimental approach applied in a mixed-methods evaluation of early prototypes of a suite of professional networking applications targeting a conference attendance scenario. Their evaluation was significantly constrained by the limited availability of a small cohort of end users for a relatively short period of time, which pose a challenge to define interactions that would ensure these users could experience and understand the novel application features. The authors observed that participatory role-play facilitated deeper user engagement with, exploration of, and discussion about, the mobile social applications than would have been possible with traditional usability approaches given the small user cohort and the time-constrained conditions.

Plug-in scripts for EFTEM automation

1996 ◽  
Vol 54 ◽  
pp. 546-547
Author(s):  
N. D. Evans ◽  
M. K. Kundmann
Keyword(s):  
Electron Microscopy ◽  
National Laboratory ◽  
Oak Ridge ◽  
Multiple User ◽  
Transmission Electron ◽  
Short Period ◽  
User Facility ◽  
Instrument Control ◽  
And Control ◽  
Research Equipment

Post-column energy-filtered transmission electron microscopy (EFTEM) is inherently challenging as it requires the researcher to setup, align, and control both the microscope and the energy-filter. The software behind an EFTEM system is therefore critical to efficient, day-to-day application of this technique. This is particularly the case in a multiple-user environment such as at the Shared Research Equipment (SHaRE) User Facility at Oak Ridge National Laboratory. Here, visiting researchers, who may oe unfamiliar with the details of EFTEM, need to accomplish as much as possible in a relatively short period of time.We describe here our work in extending the base software of a commercially available EFTEM system in order to automate and streamline particular EFTEM tasks. The EFTEM system used is a Philips CM30 fitted with a Gatan Imaging Filter (GIF). The base software supplied with this system consists primarily of two Macintosh programs and a collection of add-ons (plug-ins) which provide instrument control, imaging, and data analysis facilities needed to perform EFTEM.

scholarly journals Usability and Utility of a Mobile App to Improve Medication Adherence Among Ambulatory Care Patients in Malaysia: Qualitative Study

10.2196/15146 ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. e15146 ◽  
Author(s):  
Sara Chew ◽  
Pauline Siew Mei Lai ◽  
Chirk Jenn Ng
Keyword(s):  
Medication Adherence ◽  
Ambulatory Care ◽  
Usability Testing ◽  
End Users ◽  
Improve Medication Adherence ◽  
Multiple User ◽  
User Friendly ◽  
Beta Testing ◽  
First Interview

Background To date, several medication adherence apps have been developed. However, the existing apps have been developed without involving relevant stakeholders and were not subjected to mobile health app guidelines. In addition, the usability and utility of these apps have not been tested with end users. Objective This study aimed to describe the usability and utility testing of a newly developed medication adherence app—Med Assist—among ambulatory care patients in Malaysia. Methods The Med Assist app was developed based on the Theory of Planned Behavior and the Nielson usability model. Beta testing was conducted from March to May 2016 at a primary care clinic in Kuala Lumpur. Ambulatory care patients who scored ≥40% on the electronic health literacy scale, were aged ≥21 years, and were taking two or more long-term medications were recruited. Two rounds of in-depth interviews were conducted with each participant. The first interview, which was conducted upon participant recruitment, was to assess the usability of Med Assist. Participants were asked to download Med Assist on their phone and perform two tasks (register themselves on Med Assist and enter at least one medication). Participants were encouraged to “concurrently think aloud” when using Med Assist, while nonverbal cues were observed and recorded. The participants were then invited for a second interview (conducted ≥7 days after the first interview) to assess the utility of Med Assist after using the app for 1 week. This was done using “retrospective probing” based on a topic guide developed for utilities that could improve medication adherence. Results Usability and utility testing was performed for the Med Assist app (version P4). A total of 13 participants were recruited (6 men, 7 women) for beta testing. Three themes emerged from the usability testing, while three themes emerged from the utility testing. From the usability testing, participants found Med Assist easy to use and user friendly, as they were able to complete the tasks given to them. However, the details required when adding a new medication were found to be confusing despite displaying information in a hierarchical order. Participants who were caregivers as well as patients found the multiple-user support and pill buddy utility useful. This suggests that Med Assist may improve the medication adherence of patients on multiple long-term medications. Conclusions The usability and utility testing of Med Assist with end users made the app more patient centered in ambulatory care. From the usability testing, the overall design and layout of Med Assist were simple and user friendly enough for participants to navigate through the app and add a new medication. From the participants’ perspectives, Med Assist was a useful and reliable tool with the potential to improve medication adherence. In addition, utilities such as multiple user support and a medication refill reminder encouraged improved medication management.

scholarly journals What Your Tweets Tell Us About You: Identity, Ownership and Privacy of Twitter Data

2012 ◽  
Vol 7 (1) ◽  
pp. 174-197 ◽  
Author(s):  
Heather Small ◽  
Kristine Kasianovitz ◽  
Ronald Blanford ◽  
Ina Celaya
Keyword(s):  
Social Media ◽  
Social Networking Sites ◽  
Data Sets ◽  
Data Set ◽  
Social Media Data ◽  
Twitter Data ◽  
Other Information ◽  
Rich Data ◽  
Additional Value ◽  
Media Data

Social networking sites and other social media have enabled new forms of collaborative communication and participation for users, and created additional value as rich data sets for research. Research based on accessing, mining, and analyzing social media data has risen steadily over the last several years and is increasingly multidisciplinary; researchers from the social sciences, humanities, computer science and other domains have used social media data as the basis of their studies. The broad use of this form of data has implications for how curators address preservation, access and reuse for an audience with divergent disciplinary norms related to privacy, ownership, authenticity and reliability.In this paper, we explore how the characteristics of the Twitter platform, coupled with an ambiguous and evolving understanding of privacy in networked communication, and divergent disciplinary understandings of the resulting data, combine to create complex issues for curators trying to ensure broad-based and ethical reuse of Twitter data. We provide a case study of a specific data set to illustrate how data curators can engage with the topics and questions raised in the paper. While some initial suggestions are offered to librarians and other information professionals who are beginning to receive social media data from researchers, our larger goal is to stimulate discussion and prompt additional research on the curation and preservation of social media data.

Smartphones and the Neuroscience of Mental Health

2021 ◽  
Vol 44 (1) ◽  
Author(s):  
Claire M. Gillan ◽  
Robb B. Rutledge
Keyword(s):  
Mental Health ◽  
Annual Review ◽  
Publication Date ◽  
Data Sets ◽  
Daily Lives ◽  
Neuroscience Research ◽  
Health And Illness ◽  
Passive Data ◽  
Smartphone Sensors ◽  
Rich Data

Improvements in understanding the neurobiological basis of mental illness have unfortunately not translated into major advances in treatment. At this point, it is clear that psychiatric disorders are exceedingly complex and that, in order to account for and leverage this complexity, we need to collect longitudinal datasets from much larger and more diverse samples than is practical using traditional methods. We discuss how smartphone-based research methods have the potential to dramatically advance our understanding of the neuroscience of mental health. This, we expect, will take the form of complementing lab-based hard neuroscience research with dense sampling of cognitive tests, clinical questionnaires, passive data from smartphone sensors, and experience-sampling data as people go about their daily lives. Theory- and data-driven approaches can help make sense of these rich data sets, and the combination of computational tools and the big data that smartphones make possible has great potential value for researchers wishing to understand how aspects of brain function give rise to, or emerge from, states of mental health and illness. Expected final online publication date for the Annual Review of Neuroscience, Volume 44 is July 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Chapter 17. Logic Tensor Networks: Theory and Applications

2021 ◽  
Author(s):  
Luciano Serafini ◽  
Artur d’Avila Garcez ◽  
Samy Badreddine ◽  
Ivan Donadello ◽  
Michael Spranger ◽  
...  
Keyword(s):  
Supervised Learning ◽  
Data Sets ◽  
Symbolic Representations ◽  
Tensor Networks ◽  
Multiple Data ◽  
Abstract Knowledge ◽  
Symbolic Ai ◽  
Rich Data ◽  
Efficient Learning ◽  
High Level

The recent availability of large-scale data combining multiple data modalities has opened various research and commercial opportunities in Artificial Intelligence (AI). Machine Learning (ML) has achieved important results in this area mostly by adopting a sub-symbolic distributed representation. It is generally accepted now that such purely sub-symbolic approaches can be data inefficient and struggle at extrapolation and reasoning. By contrast, symbolic AI is based on rich, high-level representations ideally based on human-readable symbols. Despite being more explainable and having success at reasoning, symbolic AI usually struggles when faced with incomplete knowledge or inaccurate, large data sets and combinatorial knowledge. Neurosymbolic AI attempts to benefit from the strengths of both approaches combining reasoning with complex representation of knowledge and efficient learning from multiple data modalities. Hence, neurosymbolic AI seeks to ground rich knowledge into efficient sub-symbolic representations and to explain sub-symbolic representations and deep learning by offering high-level symbolic descriptions for such learning systems. Logic Tensor Networks (LTN) are a neurosymbolic AI system for querying, learning and reasoning with rich data and abstract knowledge. LTN introduces Real Logic, a fully differentiable first-order language with concrete semantics such that every symbolic expression has an interpretation that is grounded onto real numbers in the domain. In particular, LTN converts Real Logic formulas into computational graphs that enable gradient-based optimization. This chapter presents the LTN framework and illustrates its use on knowledge completion tasks to ground the relational predicates (symbols) into a concrete interpretation (vectors and tensors). It then investigates the use of LTN on semi-supervised learning, learning of embeddings and reasoning. LTN has been applied recently to many important AI tasks, including semantic image interpretation, ontology learning and reasoning, and reinforcement learning, which use LTN for supervised classification, data clustering, semi-supervised learning, embedding learning, reasoning and query answering. The chapter presents some of the main recent applications of LTN before analyzing results in the context of related work and discussing the next steps for neurosymbolic AI and LTN-based AI models.

scholarly journals Short-Period Oscillations of Earth Rotation

2000 ◽  
Vol 178 ◽  
pp. 533-544 ◽  
Author(s):  
B. Kołaczek ◽  
W. Kosek ◽  
H. Schuh
Keyword(s):  
Seasonal Variations ◽  
Earth Rotation ◽  
Polar Motion ◽  
Correlation Coefficients ◽  
Data Sets ◽  
Annual Variations ◽  
Geodetic Vlbi ◽  
Atmospheric Excitation ◽  
Short Period ◽  
Seasonal Oscillations

AbstractSub-seasonal variations and especially sub-seasonal oscillations with periods of about 120, 60, 50, 40 days in polar motion and of about 120, 60–90, and 50 days in LOD are presented. Variations of amplitudes of these sub-seasonal oscillations of polar motion are shown. Maxima of these amplitudes are of the order of 2–4 mas. These oscillations are elliptical ones. The correlation coefficients between geodetic and atmospheric excitation functions in this range of the spectrum are variable and have annual variations. Maxima of correlation coefficients are of the order of 0.6–0.8.Modern geodetic VLBI experiments provide very accurate results in polar motion and UT1–UTC with a temporal resolution of 3–7 minutes. Several irregular, quasi-periodic variations were found. In many UT1–UTC data sets, oscillations with periods around 8 hours and between 5 and 7 hours can be seen.

A Framework for the Forensic Analysis of User Interaction with Social Media

2012 ◽  
Vol 4 (4) ◽  
pp. 15-30 ◽  
Author(s):  
John Haggerty ◽  
Mark C. Casson ◽  
Sheryllynne Haggerty ◽  
Mark J. Taylor
Keyword(s):  
Social Media ◽  
User Interaction ◽  
Large Data ◽  
Forensic Analysis ◽  
Data Sets ◽  
User Engagement ◽  
Online Data ◽  
Use Of Social Media ◽  
Temporal Dimensions ◽  
Media Applications

The increasing use of social media, applications or platforms that allow users to interact online, ensures that this environment will provide a useful source of evidence for the forensics examiner. Current tools for the examination of digital evidence find this data problematic as they are not designed for the collection and analysis of online data. Therefore, this paper presents a framework for the forensic analysis of user interaction with social media. In particular, it presents an inter-disciplinary approach for the quantitative analysis of user engagement to identify relational and temporal dimensions of evidence relevant to an investigation. This framework enables the analysis of large data sets from which a (much smaller) group of individuals of interest can be identified. In this way, it may be used to support the identification of individuals who might be ‘instigators’ of a criminal event orchestrated via social media, or a means of potentially identifying those who might be involved in the ‘peaks’ of activity. In order to demonstrate the applicability of the framework, this paper applies it to a case study of actors posting to a social media Web site.

An Adaptive Vent System for Localized and Customized Thermal Management in Buildings

2020 ◽  
Vol 142 (5) ◽  
Author(s):  
Cem Keskin ◽  
M. Pinar Mengüç
Keyword(s):  
Temperature Distribution ◽  
Thermal Management ◽  
System Modeling ◽  
Ventilation System ◽  
Control Unit ◽  
Thermal Conditions ◽  
User Preferences ◽  
User Engagement ◽  
Design Development ◽  
Modeling Methodology

Abstract This paper introduces an innovative ventilation system that is capable of providing localized and customized thermal conditions in buildings. The system has diffusers with individually operable flaps that facilitate asymmetric air inlet to control air flow inside a room in an effective way. Moreover, the system involves distributed temperature sensors, a user interface, and a control unit that allows creation and management of “thermal subzones” within a room in accordance with the different preferences of occupants. As a specific case, the thermal management of a typical office in an academic building is considered. Both experimental and numerical studies were conducted to show that it is possible to achieve several degrees of temperature differences at different room locations in a transient and controllable fashion. The dynamic management of the temperature distribution in a room can prevent the waste of conditioning energy. It is shown that the system provides a practical and impactful solution by adapting to different user preferences (UPs) and by minimizing the resource use. In order to deal with the complexity of design, development, and operation of the system, it is considered as a cyber-physical-social system (CPSS). The core of the CPSS approach used here is an enhanced hybrid system modeling methodology that couples human dimension with formal hybrid dynamical modeling. Based on a coherent conceptual framing, the approach can combine the three core aspects, like cyber infrastructure, physical dynamics, and social/human interactions of modern building energy systems to accommodate the environmental challenges. Besides physics-based achievements (managing temperature distribution inside a room), the new AVS can also leverage user engagement and behavior change for energy efficiency in buildings by facilitating a new practice for occupants' interaction with heating, ventilation, and air conditioning (HVAC) system.

Cyber-Archaeology

Anthropology ◽  
2019 ◽  
Author(s):  
Maurizio Forte ◽  
Nevio Danelon
Keyword(s):  
Digital Simulation ◽  
Simulation Models ◽  
Physical World ◽  
Data Sets ◽  
Knowledge Domains ◽  
Archaeological Data ◽  
The Past ◽  
Digital Ecosystem ◽  
Interpretation Process ◽  
Real Time Simulations

Cyber-archaeology is a branch of archaeological research concerned with the digital simulation of the past. In this context the past is seen as generated by the interaction of multiple scenarios and simulations and by the creation of different digital embodiments. The term also recalls the ecological cybernetics approach, based on the informative modeling of organism-environment relationships. In fact, cyber-archaeology aims to investigate the past through interactions with multimodal simulation models of archaeological data sets in different areas of knowledge (domains). The cognitive-interpretive process is accomplished through an interaction feedback loop in a virtual reality environment, following a nonlinear cognitive path. This process allows for the formation and validation of scientific theories about archaeological contexts and material cultures. Cyber-archaeology assumes that the past cannot be reconstructed but rather simulated. Whereas virtual archaeology is mainly visual, static, and graphically oriented to photorealism, which conveys a peremptory idea of predefined knowledge, cyber-archaeology is not necessarily visual, but rather interactive, dynamically complex, and autopoietic. It focuses on the potentiality and virtuality of the interpretation, as opposed to the actuality of the physical world. It is more appropriate to think in terms of a potential past, a co-evolving subject in the human evolution generated by cyber-interactions between worlds. In the cyber-archaeological perspective, the focus is the simulation, which is the enactive-dynamic behavior of the virtual actor and the digital ecosystem. As a consequence of this, the workflow able to move and migrate data from the fieldwork to a simulation environment can generate different affordances and cybernetic models, each of which can create feedback, which serves as a new map-code for the interpretation. The increasing use of 3D digital technologies in archaeology, in fact, is identifiable in new digital workflows and real time simulations of archaeological data sets. This digital migration of data and models in such diverse domains creates unexpected results and more advanced knowledge. The study of the code is essential for re-analyzing the interpretation process in the light of a cybernetic perspective: the feedback created by different interactors operating in the same environment/ecosystem generates further feedback and not predetermined interconnections.

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