ARCHIE: An Automated Data Collection Method for Physical Prototyping Efforts in Authentic Design Situations

2019 ◽  
Author(s):  
Jacob Nelson ◽  
Andrew Berlin ◽  
Jessica Menold
Keyword(s):  
Data Collection ◽  
Design Research ◽  
Continuous Data ◽  
Geometric Complexity ◽  
Automated Data Collection ◽  
Collection Method ◽  
Design Evolution ◽  
Material Choice ◽  
Design Projects ◽  
Over Time

Abstract Effective data collection can be one of the most challenging aspects of engineering design research. Design projects often occur over periods of weeks, months, or years, making continuous data collection a time-intensive task. Further, interrupting the design process to collect data can be intrusive and disrupt the flow of design. ARCHIE is a system designed to take photos of designers’ physical prototypes, link them to designer perceptions of the design, and maintain a record of design evolution over time. This device will allow researchers to collect data on physical prototyping efforts in design environments without researcher intervention, reducing the burden of data collection in authentic design settings. The device provides designers with an easier way to document physical prototyping efforts and record the evolution of their design with photos and descriptions and promises to allow for researchers to leverage machine learning to automatically analyze aspects of the prototype such as geometric complexity or material choice by facilitating the creation of databases of design artifacts. This work describes the rationale, method, implementation, and testing of ARCHIE using student design projects.

scholarly journals Smart Glasses as a Surgical Pathology Grossing Tool

2020 ◽  
Author(s):  
Ozlem Kulak ◽  
Anastasia Drobysheva ◽  
Neda Wick ◽  
Simone Arvisais-Anhalt ◽  
Sharon Koorse Germans ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Data Collection ◽  
Surgical Pathology ◽  
Field Of View ◽  
Google Glass ◽  
Automated Data Collection ◽  
Smart Glasses ◽  
Free Data ◽  
Protocol Performance ◽  
Over Time

Context.— Smart glasses are a wearable technology that enable hands-free data acquisition and entry. Objective.— To develop a surgical pathology grossing application on a smart glass platform. Design.— An existing logistics software for the Google Glass Enterprise smart glass platform was used to create surgical pathology grossing protocols. The 2 grossing protocols were developed to simulate grossing a complex (heart) and a simple (kidney) specimen. For both protocols, users were visually prompted by the smart glass device to perform each task, record measurements, or document the field of view. In addition to measuring the total time of the protocol performance, each substep within the protocol was automatically recorded. Subsequently, a report was generated that contained the dictation, images, voice recordings, and the timing of each step. The application was tested by 3 users using the 2 grossing protocols. The users were tracked across 3 grossing procedures for each protocol. Results.— For the complex specimen grossing the average time across repeated procedures was not significantly different between users (P = .999). However, when grossing times of the complex specimen were compared for repeated performances of the same user, a significant reduction in grossing times was observed with each repetition (P = .002). For the simple specimen, the average grossing time across multiple attempts was different among users (P = .03); however, no improvement in grossing time was observed with repeated performance (P = .499). Conclusions.— Augmented reality based grossing applications can provide automated data collection to track the changes in grossing performance over time.

Moving an Established Survey Online – or not?

2013 ◽  
Vol 55 (2) ◽  
pp. 187-199 ◽  
Author(s):  
Tim Barber ◽  
Dave Chilvers ◽  
Sumran Kaul
Keyword(s):  
Data Collection ◽  
Collection Method ◽  
Face To Face ◽  
Data Collection Method ◽  
Novel Technique ◽  
Trends Over Time ◽  
Over Time ◽  
Longitudinal Dataset

This paper details an experiment to migrate a long-established survey from a face-to-face to an online methodology. The survey - Ofcom's Media Tracker - has been running for more than ten years and has generated a longitudinal dataset of great value for assessing trends over time. The value of this dataset needs to be protected against any discontinuity caused by methodological change. A novel technique was developed to determine which variables in addition to demographics should be used to reweight the data from an offline survey to best replicate what would have been achieved had the traditional data collection method continued. The results helped Ofcom to make a decision about migration for this particular survey and, more generally, provide a useful addendum to existing knowledge regarding successful modal migration.

scholarly journals One-Sentence, One-Word: An Innovative Data Collection Method to Enhance Exploration of the Lived Experiences

2018 ◽  
Author(s):  
Shannon Sibbald ◽  
Dylan Brennan ◽  
Aleksandra Zecevic
Keyword(s):  
Data Collection ◽  
Design Research ◽  
Phenomenological Study ◽  
Research Process ◽  
Subjective Experiences ◽  
Master Athletes ◽  
Research Strategies ◽  
Collection Method ◽  
Data Collection Method ◽  
Qualitative Approaches

Experienced-based methods are growing in popularity and are increasingly being utilized in a variety of research programs and investigations. They enable researchers and participants to co-design research strategies and outcomes and subsequently propose solutions to potential problems in the partnership. By applying an experience-based methods lens, we sought to augment traditional qualitative interviewing methodologies by using a novel method we named “one-sentence, one-word” (1S1W). To apply our 1S1W method, we used a phenomenological study that examined the relationship between the risk of falling and the desire of master athletes to engage in competitive sports. Participants reflected and recorded their subjective experiences in the form of one-sentence and one-word responses, at the beginning and end of the interview, respectively. Half of all participants associated the risk of falls with negative words; however, all participants used positive sentences to describe their experience as master athletes. Considering other qualitative findings, this method, while brief and relatively simple, gave a very rich and accurate depiction of participants’ overall experiences (e.g., themes). The 1S1W data collection method complements traditional qualitative approaches and encourages participant reflection; we believe our method has applicability across the research process. In one word, it isolates the ESSENCE.

eGovernment Adoption Determinants From Citizens' Perspective

2019 ◽  
Vol 10 (1) ◽  
pp. 18-30 ◽  
Author(s):  
Gideon Mekonnen Jonathan ◽  
Lazar Rusu
Keyword(s):  
Information Systems ◽  
Data Collection ◽  
Literature Review ◽  
Research Methods ◽  
Design Research ◽  
Empirical Studies ◽  
Research Strategy ◽  
Current Status ◽  
Research Strategies ◽  
Collection Method

The lack of adoption of eGovernment by citizens has been cited to be one of the reasons for failures of most eGovernment initiatives. A systematic literature review was conducted to shade light on the current status of the research in this area with a focus on the research goals, research design, research strategies, scientific theories used and research methods. Major databases indexing reputable journals in information systems and e-government area were searched by using keywords to collect relevant articles for analysis. A total of 19 articles were identified which indicated that empirical studies with survey as research strategy and questionnaires as a data collection method dominates the publications list while the use of case studies as research strategy was found to be scarce. The review has also highlighted several limitations related to the choice of research methods and its implication on furthering the understanding of the research on this topic.

scholarly journals Comparison of Manual versus Automated Data Collection Method for an Evidence-Based Nursing Practice Study

2013 ◽  
Vol 04 (01) ◽  
pp. 61-74 ◽  
Author(s):  
T.R. Jordan ◽  
T. Welle ◽  
M.D. Byrne
Keyword(s):  
Quality Assurance ◽  
Data Collection ◽  
Nursing Practice ◽  
Evidence Based ◽  
Automated Data Collection ◽  
Collection Method ◽  
Data Collection Method ◽  
Practice Study ◽  
Data Elements ◽  
Evidence Based Nursing

SummaryObjective: The objective of this study was to investigate and improve the use of automated data collection procedures for nursing research and quality assurance.Methods: A descriptive, correlational study analyzed 44 orthopedic surgical patients who were part of an evidence-based practice (EBP) project examining post-operative oxygen therapy at a Midwestern hospital. The automation work attempted to replicate a manually-collected data set from the EBP project.Results: Automation was successful in replicating data collection for study data elements that were available in the clinical data repository. The automation procedures identified 32 “false negative” patients who met the inclusion criteria described in the EBP project but were not selected during the manual data collection. Automating data collection for certain data elements, such as oxygen saturation, proved challenging because of workflow and practice variations and the reliance on disparate sources for data abstraction. Automation also revealed instances of human error including computational and transcription errors as well as incomplete selection of eligible patients.Conclusion: Automated data collection for analysis of nursing-specific phenomenon is potentially superior to manual data collection methods. Creation of automated reports and analysis may require initial up-front investment with collaboration between clinicians, researchers and information technology specialists who can manage the ambiguities and challenges of research and quality assurance work in healthcare.Citation: Byrne MD, Jordan TR, Welle T. Comparison of Manual versus Automated Data Collection Method for an Evidence-Based Nursing Practice Study. Appl Clin Inf 2013; 4: 61–74http://dx.doi.org/10.4338/ACI-2012-09-RA-0037

Validation of an automated data collection method for quantifying social networks in collective behaviours

2014 ◽  
Vol 68 (8) ◽  
pp. 1379-1391 ◽  
Author(s):  
Fumiaki Y. Nomano ◽  
Lucy E. Browning ◽  
Shinichi Nakagawa ◽  
Simon C. Griffith ◽  
Andrew F. Russell
Keyword(s):  
Social Networks ◽  
Data Collection ◽  
Automated Data Collection ◽  
Collection Method ◽  
Data Collection Method

Automated electron tomography: from data collection to image processing

1995 ◽  
Vol 53 ◽  
pp. 26-27
Author(s):  
Weiping Liu ◽  
Jennifer Fung ◽  
W.J. de Ruijter ◽  
Hans Chen ◽  
John W. Sedat ◽  
...  
Keyword(s):  
Image Processing ◽  
Data Collection ◽  
Structural Information ◽  
Imaging Technique ◽  
Electron Tomography ◽  
Ccd Camera ◽  
Automated Data Collection ◽  
Full Control ◽  
Transmission Electron ◽  
Amorphous Structures

Electron tomography is a technique where many projections of an object are collected from the transmission electron microscope (TEM), and are then used to reconstruct the object in its entirety, allowing internal structure to be viewed. As vital as is the 3-D structural information and with no other 3-D imaging technique to compete in its resolution range, electron tomography of amorphous structures has been exercised only sporadically over the last ten years. Its general lack of popularity can be attributed to the tediousness of the entire process starting from the data collection, image processing for reconstruction, and extending to the 3-D image analysis. We have been investing effort to automate all aspects of electron tomography. Our systems of data collection and tomographic image processing will be briefly described.To date, we have developed a second generation automated data collection system based on an SGI workstation (Fig. 1) (The previous version used a micro VAX). The computer takes full control of the microscope operations with its graphical menu driven environment. This is made possible by the direct digital recording of images using the CCD camera.

Percutaneous Tracheostomy: A Multidisciplinary Approach

2008 ◽  
Vol 18 (2) ◽  
pp. 87-98 ◽  
Author(s):  
Vinciya Pandian ◽  
Thai Tran Nguyen ◽  
Marek Mirski ◽  
Nasir Islam Bhatti
Keyword(s):  
Health Care ◽  
Quality Assurance ◽  
Data Collection ◽  
Health Care Professionals ◽  
Multidisciplinary Approach ◽  
Percutaneous Tracheostomy ◽  
Johns Hopkins Hospital ◽  
Prospective Data ◽  
Comprehensive Service ◽  
Over Time

Abstract The techniques of performing a tracheostomy has transformed over time. Percutaneous tracheostomy is gaining popularity over open tracheostomy given its advantages and as a result the number of bedside tracheostomies has increased necessitating the need for a Percutaneous Tracheostomy Program. The Percutaneous Tracheostomy Program at the Johns Hopkins Hospital is a comprehensive service that provides care to patients before, during, and after a tracheostomy with a multidisciplinary approach aimed at decreasing complications. Education is provided to patients, families, and health-care professionals who are involved in the management of a tracheostomy. Ongoing prospective data collection serves as a tool for Quality Assurance.

Automated data collection

1983 ◽  
Author(s):  
Peter J. Kennedy ◽  
James R. Lewis
Keyword(s):  
Data Collection ◽  
Automated Data Collection
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