scholarly journals Evaluating Group-Robot Interaction in Crowded Public Spaces: A Week-Long Exploratory Study in the Wild with a Humanoid Robot Guiding Visitors Through a Science Museum

2015 ◽  
Vol 12 (04) ◽  
pp. 1550022 ◽  
Author(s):  
Marta Díaz-Boladeras ◽  
Dennys Paillacho ◽  
Cecilio Angulo ◽  
Oriol Torres ◽  
Jonathan González-Diéguez ◽  
...  
Keyword(s):  
Exploratory Study ◽  
Large Scale ◽  
Humanoid Robot ◽  
Group Behavior ◽  
Lessons Learned ◽  
Spatial Behavior ◽  
Science Museum ◽  
Walking Behavior ◽  
The Face ◽  
In The Wild

This paper describes an exploratory study on group interaction with a robot guide in an open large-scale busy environment. For an entire week, a humanoid robot was deployed in the popular Cosmocaixa Science Museum in Barcelona and guided hundreds of people through the museum facilities. The main goal of this experience is to study in the wild the episodes of the robot guiding visitors to a requested destination focusing on the group behavior during displacement. The walking behavior follow-me and the face-to-face communication in a populated environment are analyzed in terms of guide–visitors interaction, grouping patterns and spatial formations. Results from observational data show that the space configurations spontaneously formed by the robot guide and visitors walking together did not always meet the robot communicative and navigational requirements for successful guidance. Therefore, additional verbal and nonverbal prompts must be considered to regulate effectively the walking together and follow-me behaviors. Finally, we discuss lessons learned and recommendations for robot’s spatial behavior in dense crowded scenarios.

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).

Ban Ki-moon, 2007–2016

2018 ◽  
Author(s):  
Richard Gowan
Keyword(s):  
United States ◽  
Decision Making ◽  
Security Council ◽  
Large Scale ◽  
Central African Republic ◽  
The United States ◽  
Cautious Approach ◽  
Peacekeeping Operations ◽  
Council Decision ◽  
The Face

During Ban Ki-moon’s tenure, the Security Council was shaken by P5 divisions over Kosovo, Georgia, Libya, Syria, and Ukraine. Yet it also continued to mandate and sustain large-scale peacekeeping operations in Africa, placing major burdens on the UN Secretariat. The chapter will argue that Ban initially took a cautious approach to controversies with the Council, and earned a reputation for excessive passivity in the face of crisis and deference to the United States. The second half of the chapter suggests that Ban shifted to a more activist pressure as his tenure went on, pressing the Council to act in cases including Côte d’Ivoire, Libya, and Syria. The chapter will argue that Ban had only a marginal impact on Council decision-making, even though he made a creditable effort to speak truth to power over cases such as the Central African Republic (CAR), challenging Council members to live up to their responsibilities.

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 Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation

2021 ◽  
Author(s):  
Mehdi Bahri ◽  
Eimear O’ Sullivan ◽  
Shunwang Gong ◽  
Feng Liu ◽  
Xiaoming Liu ◽  
...  
Keyword(s):  
Large Scale ◽  
Training Time ◽  
3D Face ◽  
In The Wild ◽  
Previous State ◽  
Surface Translation ◽  
Visual Attention Mechanism ◽  
Diverse Data ◽  
Human Faces ◽  
Robust To Noise

AbstractStandard registration algorithms need to be independently applied to each surface to register, following careful pre-processing and hand-tuning. Recently, learning-based approaches have emerged that reduce the registration of new scans to running inference with a previously-trained model. The potential benefits are multifold: inference is typically orders of magnitude faster than solving a new instance of a difficult optimization problem, deep learning models can be made robust to noise and corruption, and the trained model may be re-used for other tasks, e.g. through transfer learning. In this paper, we cast the registration task as a surface-to-surface translation problem, and design a model to reliably capture the latent geometric information directly from raw 3D face scans. We introduce Shape-My-Face (SMF), a powerful encoder-decoder architecture based on an improved point cloud encoder, a novel visual attention mechanism, graph convolutional decoders with skip connections, and a specialized mouth model that we smoothly integrate with the mesh convolutions. Compared to the previous state-of-the-art learning algorithms for non-rigid registration of face scans, SMF only requires the raw data to be rigidly aligned (with scaling) with a pre-defined face template. Additionally, our model provides topologically-sound meshes with minimal supervision, offers faster training time, has orders of magnitude fewer trainable parameters, is more robust to noise, and can generalize to previously unseen datasets. We extensively evaluate the quality of our registrations on diverse data. We demonstrate the robustness and generalizability of our model with in-the-wild face scans across different modalities, sensor types, and resolutions. Finally, we show that, by learning to register scans, SMF produces a hybrid linear and non-linear morphable model. Manipulation of the latent space of SMF allows for shape generation, and morphing applications such as expression transfer in-the-wild. We train SMF on a dataset of human faces comprising 9 large-scale databases on commodity hardware.

scholarly journals Reframing refugee crisis: A “European crisis of migration” or a “crisis of protection”?

2021 ◽  
pp. 239965442198970
Author(s):  
Maissaa Almustafa
Keyword(s):  
Large Scale ◽  
Global South ◽  
Global Media ◽  
Developing Regions ◽  
International Protection ◽  
High Commissioner ◽  
The Face ◽  
Global North ◽  
Displaced People ◽  
Resettlement Programs

The end of 2015 witnessed a global record in the number of forcibly displaced people fleeing because of wars and persecution. The unprecedented total of 65.3 million displaced individuals, out of which 21.3 million were refugees, was the highest number that the United Nations High Commissioner for Refugees (UNHCR) has recorded since its establishment in 1950. During the same year and in the face of this large-scale crisis, only 107,100 refugees were admitted for resettlement through official resettlement programs, whereas 3.2 million people applied for asylum globally. And in spite of the fact that the majority of the world refugees are hosted in ten developing regions, the dominant narrative in the global media was about the “unauthorized” arrival of more than one million asylum seekers in Europe by sea during 2015. This paper argues that the unexpected nature of refugees’ arrivals has proven that refugees were supposed to be contained in their camps in the Global South, deterred from reaching the territories of the Global North, represented here by Europe. Thus, the paper proposes that these arrivals are rather reflections of a crisis of protection that developed in the Global South where containment and deterrence strategies against refugees from the Global South exacerbate their inhumane displacement conditions in home regions. In the same context, the paper discusses how international protection structures have been reconstructed to serve the same goals of containment and deterrence, with the ultimate aim of putting people ‘back in place’ with minimal access to protection and rights.

scholarly journals CNN-Based Classifier as an Offline Trigger for the CREDO Experiment

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4804
Author(s):  
Marcin Piekarczyk ◽  
Olaf Bar ◽  
Łukasz Bibrzycki ◽  
Michał Niedźwiecki ◽  
Krzysztof Rzecki ◽  
...  
Keyword(s):  
Wavelet Transforms ◽  
Exploratory Study ◽  
Large Scale ◽  
Morphological Difference ◽  
Cosmic Ray ◽  
Input Image ◽  
Image Features ◽  
The Earth ◽  
Cmos Sensor ◽  
Competition Process

Gamification is known to enhance users’ participation in education and research projects that follow the citizen science paradigm. The Cosmic Ray Extremely Distributed Observatory (CREDO) experiment is designed for the large-scale study of various radiation forms that continuously reach the Earth from space, collectively known as cosmic rays. The CREDO Detector app relies on a network of involved users and is now working worldwide across phones and other CMOS sensor-equipped devices. To broaden the user base and activate current users, CREDO extensively uses the gamification solutions like the periodical Particle Hunters Competition. However, the adverse effect of gamification is that the number of artefacts, i.e., signals unrelated to cosmic ray detection or openly related to cheating, substantially increases. To tag the artefacts appearing in the CREDO database we propose the method based on machine learning. The approach involves training the Convolutional Neural Network (CNN) to recognise the morphological difference between signals and artefacts. As a result we obtain the CNN-based trigger which is able to mimic the signal vs. artefact assignments of human annotators as closely as possible. To enhance the method, the input image signal is adaptively thresholded and then transformed using Daubechies wavelets. In this exploratory study, we use wavelet transforms to amplify distinctive image features. As a result, we obtain a very good recognition ratio of almost 99% for both signal and artefacts. The proposed solution allows eliminating the manual supervision of the competition process.

Conservation of animal genetic resources: approaches and technologies for in situ and ex situ conservation

2008 ◽  
Vol 42 ◽  
pp. 71-85 ◽  
Author(s):  
J.A. Woolliams ◽  
O. Matika ◽  
J. Pattison
Keyword(s):  
Rural Communities ◽  
Genetic Resources ◽  
Large Scale ◽  
Production Systems ◽  
Regional Distribution ◽  
Livestock Production ◽  
Ex Situ ◽  
Animal Genetic Resources ◽  
The Face ◽  
Livestock Products

SummaryLivestock production faces major challenges through the coincidence of major drivers of change, some with conflicting directions. These are:1. An unprecedented global change in demands for traditional livestock products such as meat, milk and eggs.2. Large changes in the demographic and regional distribution of these demands.3. The need to reduce poverty in rural communities by providing sustainable livelihoods.4. The possible emergence of new agricultural outputs such as bio-fuels making a significant impact upon traditional production systems.5. A growing awareness of the need to reduce the environmental impact of livestock production.6. The uncertainty in the scale and impact of climate change. This paper explores these challenges from a scientific perspective in the face of the large-scale and selective erosion of our animal genetic resources, and concludes thai there is a stronger and more urgent need than ever before to secure the livestock genetic resources available to humankind through a comprehensive global conservation programme.

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