145 research outputs found
Wearable with integrated piezoelectric energy harvester for geolocation of people with Alzheimer's
Alzheimer's is a progressive disease that affects memory, causing disorientation in the patient, which causes them to lose themselves, generating anguish in families who have to resort to expensive searches. The objective of this research was to implement a device that can remotely provide the location of the Alzheimer's patient over a long period to relatives for greater security. For this, in this research, a mobile application was developed that receives information from a wearable that applies the internet of things using ong-range wide area technology to show the patient's real-time location and uses piezoelectrics for greater battery autonomy. The real-time location of the person and the radius of the safe zone in the application were obtained as results, the received signal strength indicator value where the signal was excellent or good had a value of -30 to -89 dB between 0 to 400 meters and the battery discharge time was 11 hours and 44 minutes. It was concluded that the application is interactive, that the piezoelectric system increased the autonomy of the wearable, and that the long-range wide area (LoRa) technology allowed monitoring of the patient's location with great precision at 400 meters
Responsible AI in Africa
This open access book contributes to the discourse of Responsible Artificial Intelligence (AI) from an African perspective. It is a unique collection that brings together prominent AI scholars to discuss AI ethics from theoretical and practical African perspectives and makes a case for African values, interests, expectations and principles to underpin the design, development and deployment (DDD) of AI in Africa. The book is a first in that it pays attention to the socio-cultural contexts of Responsible AI that is sensitive to African cultures and societies. It makes an important contribution to the global AI ethics discourse that often neglects AI narratives from Africa despite growing evidence of DDD in many domains. Nine original contributions provide useful insights to advance the understanding and implementation of Responsible AI in Africa, including discussions on epistemic injustice of global AI ethics, opportunities and challenges, an examination of AI co-bots and chatbots in an African work space, gender and AI, a consideration of African philosophies such as Ubuntu in the application of AI, African AI policy, and a look towards a future of Responsible AI in Africa. This is an open access book
Prototype of a robotic system to assist the learning process of English language with text-generation through DNN
In the last ongoing years, there has been a significant ascending on the
field of Natural Language Processing (NLP) for performing multiple tasks
including English Language Teaching (ELT). An effective strategy to favor the
learning process uses interactive devices to engage learners in their
self-learning process. In this work, we present a working prototype of a
humanoid robotic system to assist English language self-learners through text
generation using Long Short Term Memory (LSTM) Neural Networks. The learners
interact with the system using a Graphic User Interface that generates text
according to the English level of the user. The experimentation was conducted
using English learners and the results were measured accordingly to
International English Language Testing System (IELTS) rubric. Preliminary
results show an increment in the Grammatical Range of learners who interacted
with the system.Comment: Paper presented in the Mexican International Conference on Artificial
Intelligence 202
Towards structured neural spoken dialogue modelling.
195 p.In this thesis, we try to alleviate some of the weaknesses of the current approaches to dialogue modelling,one of the most challenging areas of Artificial Intelligence. We target three different types of dialogues(open-domain, task-oriented and coaching sessions), and use mainly machine learning algorithms to traindialogue models. One challenge of open-domain chatbots is their lack of response variety, which can betackled using Generative Adversarial Networks (GANs). We present two methodological contributions inthis regard. On the one hand, we develop a method to circumvent the non-differentiability of textprocessingGANs. On the other hand, we extend the conventional task of discriminators, which oftenoperate at a single response level, to the batch level. Meanwhile, two crucial aspects of task-orientedsystems are their understanding capabilities because they need to correctly interpret what the user islooking for and their constraints), and the dialogue strategy. We propose a simple yet powerful way toimprove spoken understanding and adapt the dialogue strategy by explicitly processing the user's speechsignal through audio-processing transformer neural networks. Finally, coaching dialogues shareproperties of open-domain and task-oriented dialogues. They are somehow task-oriented but, there is norush to complete the task, and it is more important to calmly converse to make the users aware of theirown problems. In this context, we describe our collaboration in the EMPATHIC project, where a VirtualCoach capable of carrying out coaching dialogues about nutrition was built, using a modular SpokenDialogue System. Second, we model such dialogues with an end-to-end system based on TransferLearning
Responsible AI in Africa: Challenges and Opportunities
This open access book contributes to the discourse of Responsible Artificial Intelligence (AI) from an African perspective. It is a unique collection that brings together prominent AI scholars to discuss AI ethics from theoretical and practical African perspectives and makes a case for African values, interests, expectations and principles to underpin the design, development and deployment (DDD) of AI in Africa. The book is a first in that it pays attention to the socio-cultural contexts of Responsible AI that is sensitive to African cultures and societies. It makes an important contribution to the global AI ethics discourse that often neglects AI narratives from Africa despite growing evidence of DDD in many domains. Nine original contributions provide useful insights to advance the understanding and implementation of Responsible AI in Africa, including discussions on epistemic injustice of global AI ethics, opportunities and challenges, an examination of AI co-bots and chatbots in an African work space, gender and AI, a consideration of African philosophies such as Ubuntu in the application of AI, African AI policy, and a look towards a future of Responsible AI in Africa
IoT and Sensor Networks in Industry and Society
The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users.
The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes.
Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives.
This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments.
The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration.
The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services.
As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents.
The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs.
Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management.
The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring.
We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society
Learning Outcomes of Classroom Research
Personal pronouns are a linguistic device that is used to engage students at various educational levels. Personal pronouns are multifunctional, and their functions range from inclusion to exclusion, and include establishing of rapport with students. In this chapter, we compare the use of personal pronouns at university and secondary school levels. Our previous study (Yeo & Ting, 2014) showed the frequent use of you in lecture introductions (2,170 instances in the 37,373-word corpus) to acknowledge the presence of students. The arts lecturers were more inclusive than the science lecturers, reflected in the less frequent use of exclusive-we and we for one, as well as the frequent use of you-generalised. We have also compiled and analysed a 43,511-word corpus from 15 English lessons in three Malaysian secondary schools. This corpus yielded 2,019 instances of personal pronoun use. The results showed that you was the most frequently used personal pronoun, followed by we and I. You-audience was used more than you-generalised, and the main function was to give instructions to students. The teachers appeared to be more directive than the lecturers in the previous study, who sometimes used the inclusive-we for you and I and we for I to lessen the social distance with students, indicating that the discourse functions of personal pronouns vary with the educational context. The findings suggest that educators can be alerted to the versatility of personal pronouns, for example, for engaging students in the lesson and for asserting authority in the subject matter.
Keywords: student engagement; personal pronouns; lecture; classroom; teache
Leveraging Conversational User Interfaces and Digital Humans to Provide an Accessible and Supportive User Experience on an Ophthalmology Service
Designing E-Health services that are accessible, engaging, and provide valuable information to patients is an endeavor that requires research and validation with potential users. The information needs to be perceived as trustworthy and reliable, in order to promote people’s ability to make informed decisions about their health. This Master’s thesis work focused on understanding the potential of conversational user interfaces (CUIs) featuring digital humans (DHs) as communication agents to provide healthcare-related information to users. The case study underlying the research was proposed by Roche: the company wanted to create an informational ophthalmology website featuring a digital human to substitute the traditional text-based website. The main goal of this work was to understand whether CUIs and DHs can provide a higher level of accessibility and engagement for users, with a special focus on people starting to live with low vision (potential ophthalmology patients).
Managing to address these aspects would allow providing a better user experience for people visiting the website. Since digital humans are not yet extensively adopted in the healthcare domain, few design guidelines are available. The work employed a human-centered design approach, to gather requirements and feedback from users, and led to defining six guidelines and an extensive set of observations about user experience and accessibility. These guidelines are: ensure that the digital human is as realistic as possible; create a clear and easy to follow conversation; present options simply and allow flexibility in choice methods; provide a text version of the content; ensure that easy and self-explanatory navigation; ensure compatibility with assistive technologies and provide flexibility, personalization and integration.
The user research was divided into two phases. First, an exploratory research session was conducted, where ten participants were recruited to investigate the needs and expectations of people living with eye conditions towards an informative service and their first impressions of DHs. This session employed the semi-structured interview methodology, and the results informed the further development of the service. When the first proof of concept prototype version of the website was built, an evaluative research phase with eighteen participants was conducted. This session was conducted using the participant observation methodology paired with semi-structured elicitation interviews. Afterwards focus group sessions were organized to have the participants further discuss their experience. The user-based research was paired with expert evaluation using the cognitive walkthrough methodology and a simplified WCAG 2.1 accessibility assessment. Combining the two approaches gave a good overview of the merits and issues of the approach.
The results of the research allowed building a good understanding of the positive and negative aspects of using a digital human as an agent in a conversational user interface. Users generally appreciated the concept: they found it engaging, trustworthy and easy to use. However, there are some aspects that could not be addressed during this research, and which need further understanding. The primary areas that need to be addressed are guidance, navigation, and error management. Nonetheless, the positive feedback gathered from the participants of the evaluation sessions proves that it is worth investing in the research and development of this relatively new kind of service. In fact, the results of the work show that having a digital human as agent for a conversation-based informative service in healthcare has strong potential, in terms of both accessibility and engagement
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