scholarly journals Exploring Non-Expert Robot Programming Through Crowdsourcing

2021 ◽  
Vol 8 ◽  
Author(s):  
Sanne van Waveren ◽  
Elizabeth J. Carter ◽  
Oscar Örnberg ◽  
Iolanda Leite
Keyword(s):  
Data Collection ◽  
Real World ◽  
Visual Programming ◽  
Robot Programming ◽  
Successful Completion ◽  
Online Study ◽  
Pick And Place ◽  
Robot Behavior ◽  
Robot Tasks ◽  
Programming Interface

A longstanding barrier to deploying robots in the real world is the ongoing need to author robot behavior. Remote data collection–particularly crowdsourcing—is increasingly receiving interest. In this paper, we make the argument to scale robot programming to the crowd and present an initial investigation of the feasibility of this proposed method. Using an off-the-shelf visual programming interface, non-experts created simple robot programs for two typical robot tasks (navigation and pick-and-place). Each needed four subtasks with an increasing number of programming statements (if statement, while loop, variables) for successful completion of the programs. Initial findings of an online study (N = 279) indicate that non-experts, after minimal instruction, were able to create simple programs using an off-the-shelf visual programming interface. We discuss our findings and identify future avenues for this line of research.

Understanding the complementary nature of paid and volunteer crowds for content creation

2020 ◽  
pp. 37
Author(s):  
Claudia Flores-Saviaga ◽  
Ricardo Granados ◽  
Liliana Savage ◽  
Lizbeth Escobedo ◽  
Saiph Savage
Keyword(s):  
Real World ◽  
Limited Resource ◽  
Cost Effective ◽  
High Quality ◽  
Power Cost ◽  
Non Profit ◽  
Content Creation ◽  
Online Study ◽  
Complementary Nature ◽  
Different Populations

Crowdsourced content creation like articles or slogans can be powered by crowds of volunteers or workers from paid task markets. Volunteers often have expertise and are intrinsically motivated, but are a limited resource, and are not always reliably available. On the other hand, paid crowd workers are reliably available, can be guided to produce high-quality content, but cost money. How can these different populations of crowd workers be leveraged together to power cost-effective yet high-quality crowd-powered content-creation systems? To answer this question, we need to understand the strengths and weaknesses of each. We conducted an online study where we hired paid crowd workers and recruited volunteers from social media to complete three content creation tasks for three real-world non-profit organizations that focus on empowering women. These tasks ranged in complexity from simply generating keywords or slogans to creating a draft biographical article. Our results show that paid crowds completed work and structured content following editorial guidelines more effectively. However, volunteer crowds provide content that is more original. Based on the findings, we suggest that crowd-powered content-creation systems could gain the best of both worlds by leveraging volunteers to scaffold the direction that original content should take; while having paid crowd workers structure content and prepare it for real world use.

Validation of a Musculoskeletal Digital Assessment Routing Tool (DART): Protocol for a Pilot Randomised Crossover Non-Inferiority Trial (Preprint)

2021 ◽  
Author(s):  
Cabella Lowe ◽  
Harry Hanuman Sing ◽  
William Marsh ◽  
Dylan Morrissey
Keyword(s):  
Clinical Trials ◽  
Data Collection ◽  
Real World ◽  
User Satisfaction ◽  
Allocation Concealment ◽  
Trial Methodology ◽  
Primary Analysis ◽  
Digital Assessment ◽  
System Usability Scale ◽  
The Impact

BACKGROUND Musculoskeletal conditions account for 16% of global disability, resulting in a negative effect on millions of patients and an increasing burden on healthcare utilization. Digital technologies to improve health care outcomes and efficiency are considered a priority; however, innovations are rarely tested with sufficient rigor in clinical trials, the gold standard for clinical proof of safety and efficacy. We have developed a new musculoskeletal Digital Assessment Routing Tool (DART) that allows users to self-assess and be directed to the right care. DART requires validation in a real-world setting prior to implementation. OBJECTIVE This pilot study will assess the feasibility of a future trial by exploring key aspects of trial methodology, assess the procedures and collect exploratory data to inform the design of a definitive, randomized, crossover, non-inferiority trial to assess DART safety and effectiveness. METHODS We will collect data from 76 adult participants presenting to an NHS England GP practice with a musculoskeletal condition. Participants will complete both a DART assessment and a physiotherapist-led triage with the order determined by randomization. The primary analysis will involve an absolute agreement ICC (A,1) estimate with 95% confidence intervals between DART and the clinician for assessment outcomes sign-posting to condition management pathways. Data will be collected to allow analysis of participant recruitment and retention, randomization, allocation concealment, blinding, data collection process and bias. In addition, the impact of trial burden and potential barriers to intervention delivery will be considered. DART user satisfaction will be measured using the System Usability Scale. RESULTS A UK NHS ethics submission will be submitted during June 2021 and pending approval, recruitment will commence during August 2021 with data collection anticipated to last for 3 months. Results will be reported in a follow-up paper later in 2021. CONCLUSIONS This study will inform the design of a randomized controlled crossover non-inferiority study that will provide evidence concerning mHealth DART system clinical sign posting in an NHS setting prior to real-world implementation. Success should produce evidence of a safe, effective system with excellent usability, facilitating quicker and easier patient access to appropriate care while reducing the burden on primary and secondary care musculoskeletal services. This rigorous approach to mHealth system testing could be used as a guide for other developers of similar applications. CLINICALTRIAL This trial is registered with Clinical Trials number NCT04904029

scholarly journals A Web GIS-Based Platform to Harvest Georeferenced Data from Social Networks: Examples of Data Collection Regarding Disaster Events

2018 ◽  
Vol 14 (02) ◽  
pp. 165 ◽  
Author(s):  
Cidália Costa Fonte ◽  
Diogo Fontes ◽  
Alberto Cardoso
Keyword(s):  
Social Networks ◽  
Data Collection ◽  
Emergency Response ◽  
Web Gis ◽  
Geographical Information ◽  
Civil Protection ◽  
Physical Sensors ◽  
Access To Data ◽  
Programming Interface ◽  
Fast Access

Whenever disaster situations occur the civil protection authorities need to have fast access to data that may help to plan emergency response. To contribute to the collection and integration of all available data a platform that aims to harvest Volunteered Geographical Information (VGI) from social networks and collaborative projects was created. This enables the integration of VGI with data coming from other sources, such as data collected by physical sensors in real time and made available through Applications Programming Interface (APIs), as well as, for example, official maps. The architecture of the created platform is described and its first prototype presented. Some example queries are performed and the results are analyzed.

scholarly journals Virtual Physics Laboratory with Real World Problem Based on Ngada Local Wisdom in Basic Physics Practicum

2021 ◽  
Vol 5 (4) ◽  
pp. 520
Author(s):  
Maria Yuliana Kua ◽  
Ni Wayan Suparmi ◽  
Dek Ngurah Laba Laksana
Keyword(s):  
Data Collection ◽  
Real World ◽  
Average Score ◽  
Study Program ◽  
Face To Face ◽  
Physics Laboratory ◽  
Real World Problem ◽  
Validation Score ◽  
Basic Physics ◽  
The Media

This research is based on the problem where practical activities in the Basic Physics Practicum course can no longer be carried out optimally due to changes in the learning model from face-to-face (offline) to online (online) during the COVID-19 pandemic. The purpose of this study was to develop a virtual physics laboratory as a medium in carrying out practical activities and to analyze the feasibility of the product through the validation results of experts and the results of product trials on prospective users. This type of research is Research & Development with ADDIE development model. The subjects of this study were 12 lecturers and 47 students of the STKIP Citra Bakti science education study program. Data collection techniques using validation sheets and questionnaires. The data collection instruments are in the form of validation assessment sheets and response questionnaires of prospective users. The data from this study were analyzed qualitatively descriptive to decide the feasibility of the product being developed. The results of the research showed that the average validation score of the material expert was 4.63, the media expert was 4.41, the learning design expert was 4.30, and the linguist was 4.51. The validation results of the four validators are in the very good category. Meanwhile, the results of product trials to lecturers and students as potential users are in the very good category with an average score of 4.53 and 4.57, respectively. Based on these data, this virtual physics laboratory product with real world problems based on Ngada local wisdom is recommended to be applied to the Basic Physics Practicum course and to help students in their independent practicum activities.

OP117 Digital Real-World Evidence In Times Of General Data Protection Regulation

2021 ◽  
Vol 37 (S1) ◽  
pp. 1-1
Author(s):  
Rhodri Saunders ◽  
Rafael Torrejon Torres ◽  
Maximilian Blüher
Keyword(s):  
Data Collection ◽  
Real World ◽  
Data Protection ◽  
Safety Data ◽  
Design Approach ◽  
Data Set ◽  
General Data Protection Regulation ◽  
Real World Evidence ◽  
Quality Markers ◽  
General Data

IntroductionReal-world evidence (RWE) is a useful supplement to a product's evidence base especially for medical devices, which are often unsuitable for randomized controlled trials. Generally, RWE is analyzed retrospectively (for example, healthcare records), which lack granularity for health-economic analysis. Prospective collection of RWE in hospitals can promote device-specific endpoint assessment. The advent of the General Data Protection Regulation (GDPR) requires a privacy-by-design approach. This work describes a workflow for a GDPR-compliant device-specific RWE collection as part of quality improvement initiatives (QII).MethodsA literature review identifies relevant clinical and quality markers as endpoints to the investigated technology. A panel of experts grade these endpoints on their clinical significance, privacy sensitivity, analytic value, and feasibility for collection. Endpoints meeting a predefined cut-off are considered quality markers for the QII. Finally, an RWE data collection app is designed to collect the quality markers using either longitudinal, pseudonymized data or single time-point anonymized data to ensure data protection by design.ResultsUsing this approach relevant clinical markers were identified in a GDPR-compliant manner. The data collection app design ensured that patient data were protected, while maintaining minimum requirements on patient information and consent. The pilot QII collected data on over 5,000 procedures, which represents the largest single data set available for the tested technology. Due to its prospective nature this programme was the first to collect patient outcomes in sufficient quantity for analysis, while previous studies only recorded adverse events.ConclusionsGDPR and RWE can co-exist in harmony. A design approach, which has data protection in mind from the start can combine high quality RWE collection of efficacy and safety data with maximum patient privacy.

Real-world outcomes and clinical characteristics of patients with brain metastases from EGFR mutated non-small cell lung cancer: Data from a large retrospective study (REFLECT).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 9086-9086
Author(s):  
Urska Janzic ◽  
Alfredo Addeo ◽  
Elizabeth Dudnik ◽  
Andriani Charpidou ◽  
Adam Pluzanski ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Data Collection ◽  
Brain Metastases ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Real World ◽  
Clinical Characteristics ◽  
Small Cell ◽  
Small Cell Lung ◽  
Cancer Data

9086 Background: Brain metastases (BM) frequently occur in patients (pts) with epidermal growth factor receptor mutated non-small cell lung cancer (EGFRm NSCLC) and represent a poor prognostic marker. This study aimed to describe the clinical characteristics, treatment patterns and survival outcomes in EGFRm NSCLC pts treated with 1st or 2nd generation tyrosine-kinases inhibitors (TKIs) in first-line (1L). Methods: The retrospective real-world study REFLECT (NCT04031898) collected data from 896 pts initiating 1L TKI between 1 January 2015-30 June 2018 in Europe and Israel. Descriptive statistics were used to assess demographic and clinical characteristics in subgroups of patients with and without BM. Kaplan-Meier methods were used to estimate median real world progression free survival (mPFS) and overall survival (mOS) from start of 1L. Results: Out of 896 pts, 198 (22.1%) had BM at start of 1L, 134 (15%) developed BM later (any time), and 564 (62.9%) had no sign of BM at the time of data collection. Among pts who later developed BM the median time between the start of 1L and first diagnosis of BM was 13.5 months. Median duration of follow-up was 21.5 months. Of 332 pts with BM at any time 64.2% were female, similar to the ratio in pts without BM (64.0%). At diagnosis, median age was 65 years in pts with BM vs. 70 in those who never developed BM. Of pts with BM at any time, 50.9% had exon 19 deletion, 30.4% L858R point mutation and 18.7 % uncommon EGFR mutations at baseline, compared to 56.6%, 31.7% and 11.7% in pts without BM, respectively. At data collection, 94.9% of the pts with BM at diagnosis had progressed compared to 79.8% among those with no BM. Overall, whole brain radiation was the most frequently used treatment for BM (31.0%) followed by stereotactic radiosurgery (18.1%) and targeted therapies (13.3%). T790M testing rates were highest among pts developing BM later (85.7%) and lowest among those with BM from start (66.1%). The T790M positivity rate was highest in pts developing BM later (65.7%) and lowest among those with BM from start (50.4%). More pts received osimertinib in later lines among those with BM at any time compared to those without BM (51.3% vs 43.8%). Median real world PFS and OS (95% CI) were shorter among pts with BM at baseline compared to those never developing BM: 10.2 (8.8, 11.5) vs 15.2 (13.7, 16.1) months, and 19.4 (17.1, 22.1) vs 30.3 (27.1, 33.8) months, respectively. At the time of data collection, 77.3% of pts with BM at baseline were deceased compared to 52.5% pts with no BM. Conclusions: More than one third of pts included in REFLECT had BM at any time. Uncommon EGFR variants at baseline were observed more frequently in pts with BM. mPFS and mOS were shorter in pts with BM at baseline compared to those never developing BM. These data highlight the need for improved treatment and CNS control in pts with EGFRm NSCLC. Clinical trial information: NCT04031898.

Learning Scrum

2021 ◽  
pp. 169-189
Author(s):  
Simon Bourdeau ◽  
Alejandro Romero-Torres ◽  
Marie-Claude Petit
Keyword(s):  
Data Collection ◽  
Software Development ◽  
Real World ◽  
Learning Experience ◽  
Project Managers ◽  
Development Projects ◽  
Simulation Based ◽  
Realistic Representation ◽  
Learn By Doing ◽  
Agile Approach

The LEGO®-Scrum simulation-based training (SBT) described here shows how LEGO® bricks can help professionals learn first-hand about Scrum methodology, an Agile approach to software development projects. The chapter's objectives are 1) to present the modalities of the LEGO®-Scrum SBT, 2) to demonstrate how LEGO® bricks can help professionals learn, first-hand, about Scrum, and 3) to illustrate how this learning can be relevant and impactful for participants. Based on observations, interviews, and a data collection by questionnaire carried out with 198 participants, the proposed SBT appears to provide a significant, relevant, and valuable learning experience. In addition, four experienced Scrum masters and IT project managers, who played key roles in the SBT, argued that the LEGO®-Scrum SBT provides a realistic representation of real-world Scrum projects; that it is dynamic, complex, challenging, and motivating; and that participants' learning is evocative and relevant, since they learn by doing.

Reducing Negative Complexity by a Computational Semiotic System

2007 ◽  
pp. 330-342 ◽  
Author(s):  
Gerd Doben-Henisch
Keyword(s):  
Virtual Machines ◽  
Fault Tolerant ◽  
Visual Programming ◽  
State Machine ◽  
Learning Systems ◽  
Semiotic System ◽  
Abstract State Machine ◽  
Set Up ◽  
Self Learning ◽  
Programming Interface

The chapter describes the set-up for an experiment in computational semiotics. Starting with a hypothesis about negative complexity in the environment of human persons today it describes a strategy, how to assist human persons to reduce this complexity by using a semiotic system. The basic ingredients of this strategy are a visual programming interface with an appropriate abstract state machine, which has to be realized by distributed virtual machines. The distributed virtual machines must be scalable, have to allow parallel processing, have to be fault tolerant, and should have the potential to work in real time. The objects, which have to be processed by these virtual machines, are logical models (LModels), which represent dynamic knowledge, including self learning systems. The descriptions are based on a concrete open source project called Planet Earth Simulator.

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