Ask Your Data - Supporting Data Science Processes by Combining AutoML and Conversational Interfaces

Data Science is increasingly applied for solving real-life problems, both in industry and in academic research, but mastering Data Science requires an interdisciplinary education that is still scarce on the market. Thus, there is a growing need for user-friendly tools that allow domain experts to directly apply data analysis methods to their datasets, without involving a Data Science expert. In this scenario, we present DSBot, an assistant that can analyze the user data and produce answers by mastering several Data Science techniques. DSBot understands the research question with the help of conversation interaction, produces a data science pipeline and automatically executes the pipeline in order to generate analysis. The strength of DSBot lies in the design of a rich domain specific language for modeling data analysis pipelines, the use of a suitable neural network for machine translation of research questions, the availability of a vast dictionary of pipelines for matching the translation output, and the use of natural language technology provided by a conversational agent. We benchmarked DSBot on two sets of 100 natural language questions and of 30 prediction tasks. We empirically evaluated the translation capabilities and the autoML performance of the system. In the translation task, it obtains a median BLEU score of 0.75. In prediction tasks, DSBot outperforms TPOT, an autoML tool, in 19 datasets out of 30

Multicriteria Decision Analysis and Conversational Agents for children with autism

Conversational agents has emerged as a new means of communication and social skills training for children with autism spectrum disorders (ASD), encouraging academia, industry, and therapeutic centres to investigate it further. This paper aims to develop a methodological framework based on Multicriteria Decision Analysis (MCDA) to identify the best , i.e. the most effective, conversational agent for this target group. To our knowledge, it is the first time the MCDA is applied to this specific domain. Our contribution is twofold: i) our method is an extension of traditional MCDA and we exemplify how to apply it to decision making process related to CA for person with autism: a methodological result that would be adopted for a broader range of technologies for person with impairments similar to ASD; ii) our results, based on the above mentioned method, suggest that Embodied Conversational Agent is most appropriate conversational technology to interact with children with ASD

Silver zeolite antimicrobial activity in aluminium heating, ventilation and air conditioning system ducts

Introduction. Air pollution in confined environments is a serious health problem, in that most people spend long periods indoors (in homes, offices, classrooms etc.). Some people (children, the elderly, heart disease patients, asthmatic or allergic subjects) are at greater risk because of their conditions of frailty. The growing use of air-conditioning systems in many public and private buildings aggravates this health risk, especially when these systems are not correctly installed or regularly serviced. The aim of our study was to verify the capacity of Ag + ions to stop the growth of bacteria and moulds inside the ducts of Heating, Ventilation and Air Conditioning system ducts (HVAC) systems when these ducts were lined with active Ag + ions zeolite-coated panels. Material and methods. A Y-shaped HVAC model with two branches was used; one branch was made of traditional galvanized iron, as was the whole system, while the other was lined with active Ag + zeolite-coated polyurethane panels. During the test, samples of dust present inside both ducts were collected and seeded in liquid and solid media to detect bacteria and moulds. The presence of bacteria was also sought in the air emerging from the outlets of both ducts. Results. Tests made on samples of particulate collected from the two different ducts revealed a lower total bacterial load in the samples collected from the Ag + zeolite-coated duct than in the samples from the traditional Zn galvanized duct. In addition, the values of bacterial load found in the air emerging from the Ag+ ions zeolite-lined duct were 5 times lower than those found in the air from the traditional galvanized iron duct. Conclusions. The utilization of Ag + zeolite-coated panels in air-conditioning systems could improve the quality of the emerging air in comparison with traditional installations in galvanized iron. This innovation could prove particularly advantageous in the event of accidents during the installation of air-conditioning systems or of contaminated aerosols coming from outside

Drug resistance among influenza A viruses isolated in Italy from 2000 to 2005: are the emergence of Adamantane-resistant viruses cause of concern?

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Cross-protection by MF59 TM -adjuvanted influenza vaccine: Neutralizing and haemagglutination-inhibiting antibody activity against A(H3N2) drifted influenza viruses

Summary Adjuvants enhance antibody response against vaccination. We compared the ability of MF59 TM -adjuvanted and non-adjuvanted subunit influenza vaccines, containing A/Wyoming/3/03(H3N2), to confer cross-protection against four consecutive drifted strains in the elderly. Neutralizing and haemagglutination-inhibiting antibody were measured. MF59 TMadjuvanted vaccine induced a stronger booster response against A/Panama/2007/99(H3N2) than non-adjuvanted vaccine. A/Panama/2007/99(H3N2) circulated widely during the previous 5 years and was included in vaccines over four consecutive seasons. Broader serological protection against drifted strains that circulated 1 and 2 years after vaccination with A/Wyoming/3/03(H3N2) was observed with MF59 TM -adjuvanted vaccine. Thus, MF59 TMadjuvanted vaccine confers greater immunogenicity than non-adjuvanted vaccines in vulnerable populations

CANDY: a framework to design Conversational AgeNts for Domestic sustainabilitY

In the 2020s, world countries are called to take action to solve global issues, as defined in the Sustainable Development Goals (SDG). In our research, we are interested in exploring how Conversational Agents can be exploited to pursue the above goals, particularly in domestic spaces where CAs are becoming more and more popular. As a preliminary step in this research work, we organized a focus group with seven participants aimed at: i) investigating the potential of Conversational Agents - integrated with digital devices - to promote a more sustainable behavior at home; ii) eliciting the requirements on conversational interaction that such CAs should meet for this purpose. From the experience and findings of the focus group, we distilled a conceptual framework called CANDY, which highlights the core design dimension of Conversational Agents for Sustainability, and can be used to guide the processes of requirements elicitation and design for this category of CAs

GeCoAgent: A Conversational Agent for Empowering Genomic Data Extraction and Analysis

With the availability of reliable and low-cost DNA sequencing, human genomics is relevant to a growing number of end-users, including biologists and clinicians. Typical interactions require applying comparative data analysis to huge repositories of genomic information for building new knowledge, taking advantage of the latest findings in applied genomics for healthcare. Powerful technology for data extraction and analysis is available, but broad use of the technology is hampered by the complexity of accessing such methods and tools. This work presents GeCoAgent, a big-data service for clinicians and biologists. GeCoAgent uses a dialogic interface, animated by a chatbot, for supporting the end-users’ interaction with computational tools accompanied by multi-modal support. While the dialogue progresses, the user is accompanied in extracting the relevant data from repositories and then performing data analysis, which often requires the use of statistical methods or machine learning. Results are returned using simple representations (spreadsheets and graphics), while at the end of a session the dialogue is summarized in textual format. The innovation presented in this article is concerned with not only the delivery of a new tool but also our novel approach to conversational technologies, potentially extensible to other healthcare domains or to general data science

Leafy: Enhancing Home Energy Efficiency through Gamified Experience with a Conversational Smart Mirror

In the next few years, people will be called upon to try to slow climate change and achieve carbon neutrality collectively. The use of persuasive digital tools and engaging mechanisms can play an important role in matching such objectives. In our research, we explore the usage of a Multimodal Conversational Agent embedded in a Smart Mirror and connected to home automation appliances to help users reduce their energy consumption. The agent employs a variety of gamification techniques to encourage short and long-term sustainable behavior, and it is designed to be an enjoyable and non-intrusive experience. It informs householders about their energy consumption and encourages them regularly to reduce and optimize their electric usage. In order to keep the user engaged, the mirror contains visually appealing components and recommendations for daily challenges

Designing a smart toy: guidelines from the experience with smart dolphin "SAM"

Digitally enriched interactive physical objects, or "smart objects", might enable new educational interventions for persons with Neurodevelopmental Disorder (NDD). This paper presents the experience with SAM, a dolphin-shaped smart toy. SAM is inspired by the practice of Pet Therapy and is designed to engage people with NDD in a variety of tasks through a set of multisensory stimuli and various modes of interaction. SAM can be used alone or integrated with digital content or smart space components such as digitally controlled lights, sounds, and bubble makers. SAM behavior can be customized by therapists to address the specific needs of each person with NDD. We describe the progression of SAM prototypes, from a "stand-alone" tangible object to a multimodal smart toy integrated with multimedia contents or the whole smart environment. The design process of SAM involved NDD specialists at two therapeutic centers as well as persons with NDD. From this experience, we derived some guidelines generalizable to the design of any smart toy for people with NDD