scholarly journals Creating a corpus of multilingual parent-child speech remotely: Lessons learned in a large-scale onscreen picturebook sharing task

2021 ◽  
Author(s):  
Fei Ting Woon ◽  
Eshwaaree C Yogarrajah ◽  
Seraphina Fong ◽  
Nur Sakinah Mohd Salleh ◽  
Shamala Sundaray ◽  
...  
Keyword(s):  
Observational Studies ◽  
Large Scale ◽  
Surveys And Questionnaires ◽  
Lessons Learned ◽  
The Novel ◽  
Online Environment ◽  
Research Teams ◽  
Project Monitoring ◽  
Child Speech ◽  
Parent Child

With lockdowns and the implementation of social distancing measures in place, research teams looking to collect naturalistic parent-child speech interactions have to look for methods alternative to in-lab recordings and observational studies with long-stretch recordings. We designed a novel micro-longitudinal study, the Talk Together Study, which allowed us to create a rich corpus of parent-child speech interactions in a fully online environment (N participants = 142, N recordings = 414). In this paper, we discuss the novel methods we used, and the lessons learned during adapting and running the study. These lessons learned cover 10 domains of research design, monitoring and feedback: Recruitment strategies; Surveys and Questionnaires; Video-call scheduling; Speech elicitation tools; Videocall protocols; Participant remuneration strategies; Project monitoring; Participant retention; Parental feedback; and Research team feedback, and may be used as recommendations for teams who are planning to conduct remote studies in the future.

scholarly journals Creating a Corpus of Multilingual Parent-Child Speech Remotely: Lessons Learned in a Large-Scale Onscreen Picturebook Sharing Task

2021 ◽  
Vol 12 ◽  
Author(s):  
Fei Ting Woon ◽  
Eshwaaree C. Yogarrajah ◽  
Seraphina Fong ◽  
Nur Sakinah Mohd Salleh ◽  
Shamala Sundaray ◽  
...  
Keyword(s):  
Observational Studies ◽  
Large Scale ◽  
Surveys And Questionnaires ◽  
Lessons Learned ◽  
Recruitment Strategies ◽  
Online Environment ◽  
Research Teams ◽  
Project Monitoring ◽  
Child Speech ◽  
Parent Child

With lockdowns and social distancing measures in place, research teams looking to collect naturalistic parent-child speech interactions have to develop alternatives to in-lab recordings and observational studies with long-stretch recordings. We designed a novel micro-longitudinal study, the Talk Together Study, which allowed us to create a rich corpus of parent-child speech interactions in a fully online environment (N participants = 142, N recordings = 410). In this paper, we discuss the methods we used, and the lessons learned during adapting and running the study. These lessons learned cover nine domains of research design, monitoring and feedback: Recruitment strategies, Surveys and Questionnaires, Video-call scheduling, Speech elicitation tools, Videocall protocols, Participant remuneration strategies, Project monitoring, Participant retention, and Data Quality, and may be used as a primer for teams planning to conduct remote studies in the future.

KAMEDO Report No. 92 Evacuation of Swedes from Lebanon—Observational Studies in Connection with the War in Lebanon in Summer 2006

2008 ◽  
Vol 23 (5) ◽  
pp. 476-480 ◽  
Author(s):  
Per Kulling ◽  
Susannah Sigurdsson ◽  
Bertil Hamberger
Keyword(s):  
Medical Care ◽  
Armed Conflict ◽  
Observational Studies ◽  
Large Scale ◽  
Lessons Learned ◽  
Tsunami Disaster

AbstractA large-scale armed conflict between Hezbollah and Israel in July 2006 caused the evacuation of a large number of Swedish residents from Lebanon. This report describes the evacuation throughout its various stages. Swedish authorities were prepared for an event of this type from the experience of the 2004 Asian tsunami disaster. Lessons learned from the management and medical care during the evacuations are presented in this report.

Experiences With and Lessons Learned From Developing, Implementing, and Evaluating a Support Program for Older Hearing Aid Users and Their Communication Partners in the Hearing Aid Dispensing Setting

2020 ◽  
Vol 29 (3S) ◽  
pp. 638-647 ◽  
Author(s):  
Janine F. J. Meijerink ◽  
Marieke Pronk ◽  
Sophia E. Kramer
Keyword(s):  
Large Scale ◽  
Hearing Aid ◽  
Critical Discussion ◽  
Lessons Learned ◽  
Research Note ◽  
Support Program ◽  
Large Sample Size ◽  
Long Term Effects ◽  
Communication Program ◽  
Communication Partners

Purpose The SUpport PRogram (SUPR) study was carried out in the context of a private academic partnership and is the first study to evaluate the long-term effects of a communication program (SUPR) for older hearing aid users and their communication partners on a large scale in a hearing aid dispensing setting. The purpose of this research note is to reflect on the lessons that we learned during the different development, implementation, and evaluation phases of the SUPR project. Procedure This research note describes the procedures that were followed during the different phases of the SUPR project and provides a critical discussion to describe the strengths and weaknesses of the approach taken. Conclusion This research note might provide researchers and intervention developers with useful insights as to how aural rehabilitation interventions, such as the SUPR, can be developed by incorporating the needs of the different stakeholders, evaluated by using a robust research design (including a large sample size and a longer term follow-up assessment), and implemented widely by collaborating with a private partner (hearing aid dispensing practice chain).

Covalent Atomic Bridges Enable Unidirectional Enhancement of Electronic Transport in Aligned Carbon Nanotubes

2019 ◽  
Author(s):  
Mingguang Chen ◽  
Wangxiang Li ◽  
Anshuman Kumar ◽  
Guanghui Li ◽  
Mikhail Itkis ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Electrical Transport ◽  
Large Scale ◽  
The Novel ◽  
Electrical Measurements ◽  
Metal Atoms ◽  
Aligned Carbon Nanotubes ◽  
Transport Channels ◽  
Walled Carbon Nanotubes ◽  
Bulk Structures

<p>Interconnecting the surfaces of nanomaterials without compromising their outstanding mechanical, thermal, and electronic properties is critical in the design of advanced bulk structures that still preserve the novel properties of their nanoscale constituents. As such, bridging the p-conjugated carbon surfaces of single-walled carbon nanotubes (SWNTs) has special implications in next-generation electronics. This study presents a rational path towards improvement of the electrical transport in aligned semiconducting SWNT films by deposition of metal atoms. The formation of conducting Cr-mediated pathways between the parallel SWNTs increases the transverse (intertube) conductance, while having negligible effect on the parallel (intratube) transport. In contrast, doping with Li has a predominant effect on the intratube electrical transport of aligned SWNT films. Large-scale first-principles calculations of electrical transport on aligned SWNTs show good agreement with the experimental electrical measurements and provide insight into the changes that different metal atoms exert on the density of states near the Fermi level of the SWNTs and the formation of transport channels. </p>

scholarly journals The graph neural networking challenge

2021 ◽  
Vol 51 (3) ◽  
pp. 9-16
Author(s):  
José Suárez-Varela ◽  
Miquel Ferriol-Galmés ◽  
Albert López ◽  
Paul Almasan ◽  
Guillermo Bernárdez ◽  
...  
Keyword(s):  
Machine Learning ◽  
Computer Networks ◽  
Real World ◽  
Large Scale ◽  
Lessons Learned ◽  
Educational Resources ◽  
Global Competition ◽  
International Telecommunication Union ◽  
International Telecommunication ◽  
Broad Audience

During the last decade, Machine Learning (ML) has increasingly become a hot topic in the field of Computer Networks and is expected to be gradually adopted for a plethora of control, monitoring and management tasks in real-world deployments. This poses the need to count on new generations of students, researchers and practitioners with a solid background in ML applied to networks. During 2020, the International Telecommunication Union (ITU) has organized the "ITU AI/ML in 5G challenge", an open global competition that has introduced to a broad audience some of the current main challenges in ML for networks. This large-scale initiative has gathered 23 different challenges proposed by network operators, equipment manufacturers and academia, and has attracted a total of 1300+ participants from 60+ countries. This paper narrates our experience organizing one of the proposed challenges: the "Graph Neural Networking Challenge 2020". We describe the problem presented to participants, the tools and resources provided, some organization aspects and participation statistics, an outline of the top-3 awarded solutions, and a summary with some lessons learned during all this journey. As a result, this challenge leaves a curated set of educational resources openly available to anyone interested in the topic.

scholarly journals IoT Traffic: Modeling and Measurement Experiments

IoT ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 140-162
Author(s):  
Hung Nguyen-An ◽  
Thomas Silverston ◽  
Taku Yamazaki ◽  
Takumi Miyoshi
Keyword(s):  
Smart Home ◽  
Large Scale ◽  
Traffic Modeling ◽  
The Novel ◽  
Network Behavior ◽  
Performance Accuracy ◽  
Traffic Generator ◽  
Multiple Devices ◽  
Iot Devices ◽  
The Internet Of Things

We now use the Internet of things (IoT) in our everyday lives. The novel IoT devices collect cyber–physical data and provide information on the environment. Hence, IoT traffic will count for a major part of Internet traffic; however, its impact on the network is still widely unknown. IoT devices are prone to cyberattacks because of constrained resources or misconfigurations. It is essential to characterize IoT traffic and identify each device to monitor the IoT network and discriminate among legitimate and anomalous IoT traffic. In this study, we deployed a smart-home testbed comprising several IoT devices to study IoT traffic. We performed extensive measurement experiments using a novel IoT traffic generator tool called IoTTGen. This tool can generate traffic from multiple devices, emulating large-scale scenarios with different devices under different network conditions. We analyzed the IoT traffic properties by computing the entropy value of traffic parameters and visually observing the traffic on behavior shape graphs. We propose a new method for identifying traffic entropy-based devices, computing the entropy values of traffic features. The method relies on machine learning to classify the traffic. The proposed method succeeded in identifying devices with a performance accuracy up to 94% and is robust with unpredictable network behavior with traffic anomalies spreading in the network.

scholarly journals Strategies for Vaccination: Conventional Vaccine Approaches Versus New-Generation Strategies in Combination with Adjuvants

Pharmaceutics ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 140
Author(s):  
Abdellatif Bouazzaoui ◽  
Ahmed A. H. Abdellatif ◽  
Faisal A. Al-Allaf ◽  
Neda M. Bogari ◽  
Saied Al-Dehlawi ◽  
...  
Keyword(s):  
Viral Vectors ◽  
Protein Production ◽  
Vaccine Development ◽  
Effective Vaccine ◽  
The Novel ◽  
Research Teams ◽  
Advantages And Disadvantages ◽  
Rapid Spread ◽  
New Generation ◽  
Conventional Vaccine

The current COVID-19 pandemic, caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), has raised significant economic, social, and psychological concerns. The rapid spread of the virus, coupled with the absence of vaccines and antiviral treatments for SARS-CoV-2, has galvanized a major global endeavor to develop effective vaccines. Within a matter of just a few months of the initial outbreak, research teams worldwide, adopting a range of different strategies, embarked on a quest to develop effective vaccine that could be effectively used to suppress this virulent pathogen. In this review, we describe conventional approaches to vaccine development, including strategies employing proteins, peptides, and attenuated or inactivated pathogens in combination with adjuvants (including genetic adjuvants). We also present details of the novel strategies that were adopted by different research groups to successfully transfer recombinantly expressed antigens while using viral vectors (adenoviral and retroviral) and non-viral delivery systems, and how recently developed methods have been applied in order to produce vaccines that are based on mRNA, self-amplifying RNA (saRNA), and trans-amplifying RNA (taRNA). Moreover, we discuss the methods that are being used to enhance mRNA stability and protein production, the advantages and disadvantages of different methods, and the challenges that are encountered during the development of effective vaccines.

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