Child-Robot Interactions Using Educational Robots: An Ethical and Inclusive Perspective.

The Qui-Bot H2O project involves developing four educational sustainable robots and their associated software. Robots are equipped with HRI features such as voice recognition and color sensing, and they possess a humanoid appearance. The project highlights the social and ethical aspects of robotics applied to chemistry and industry 4.0 at an early age. Here, we report the results of an interactive study that involved 212 students aged within the range of 3-18. Our educational robots were used to measure the backgrounds, impact, and interest of students, as well as their satisfaction after interacting with them. Additionally, we provide an ethical study of the use of these robots in the classroom and a comparison of the interactions of humanoid versus non-humanoid educational robots observed in early childhood learning. Our findings demonstrate that these robots are useful in teaching technical and scientific concepts in a playful and intuitive manner, as well as in increasing the number of girls who are interested in science and engineering careers. In addition, major impact measures generated by the project within a year of its implementation were analyzed. Several public administrations in the area of gender equality endorsed and participated in the Qui-Bot H2O project in addition to educational and business entities.

Sparking the Interest of Girls in Computer Science via Chemical Experimentation and Robotics: The Qui-Bot H2O Case Study.

We report a new learning approach in science and technology through the Qui-Bot H2O project: a multidisciplinary and interdisciplinary project developed with the main objective of inclusively increasing interest in computer science engineering among children and young people, breaking stereotypes and invisible social and gender barriers. The project highlights the social aspect of robotics applied to chemistry, at early ages. We successfully tested the project activities on girls between 3 to 13 years old. After taking part in the project, the users rated their interest in science and technology to be higher than before. Data collected during experiences included background information on students, measurements of the project's impact and students' interest in it, and an evaluation of student satisfaction of this STEM activity. The Qui-Bot H2O project is supported by the actions of territorial public administrations towards gender equality and the contributions of humanistic and technological universities and entities which specialize in education and business.

Data mining of accidents in Spanish underground mines in the period 2003-2021 caused by a collision with a moving object.

Underground mining is currently one of the Spanish economic sectors with the worst accident rates. Besides, the most frequent type of accident, and with the most serious consequences, is the one in which the injured worker is hit by a moving object. For this reason, this study focuses on the analysis of this type of accident, divided into 3 subgroups to better understand the behavioural patterns. Data mining techniques were applied using the Apriori algorithm to extract as much information as possible about the genesis of these accidents. Similarly, each subset of accidents was processed in two different ways to improve the data analysis, depending on the causal variables used in each case, so that a study of six different scenarios was carried out. The five best association rules or behaviour patterns for each of the six scenarios are shown as a function of their frequency for each rule with 1-4 causal variables.

Exploratory analysis of Spanish energetic mining accidents.

Using data on work accidents and annual mining statistics, the paper studies work-related accidents in the Spanish energetic mining sector in 1999-2008. The following 3 parameters are considered: age, experience and size of the mine (in number of workers) where the accident took place. The main objective of this paper is to show the relationship between different accident indicators: risk index (as an expression of the incidence), average duration index for the age and size of the mine variables (as a measure of the seriousness of an accident), and the gravity index for the various sizes of mines (which measures the seriousness of an accident, too). The conclusions of this study could be useful to develop suitable prevention policies that would contribute towards a decrease in work-related accidents in the Spanish energetic mining industry.

Analysis of Occupational Accidents in the Spanish Mining Sector in the Period 2009-2018.

Occupational accidents in the Spanish mining industry have been substantially reduced over the last decades. However, the incidence rate shows higher values than other leading mining countries. In this regard, the research carried out reveals the factors influencing the high incidence rates of the Spanish mining sector, based on three scenarios: underground mining (UG), quarries and open pit mining (OP) and mineral processing plants (PP). The three most common types of accident for each scenario have been determined, considering the accidents in Spain between 2009 and 2018. The analysis also includes the main deviations, and physical activities that the injured worker was carrying out at the time of the accident. Besides, a model to predict the number of accidents based on the lost working days is also presented together with the incidence and severity risk index adjusted by the number of employees and their worked hours, respectively, in each scenario. These finding can be relevant to define the most effective measures and policies to reduce the number of accidents in the mining sector.

Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques.

An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector-either surface or underground mining-based on the statistical confidence levels of each rule as obtained by Weka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents.

Influence of occupational safety management on the incidence rate of occupational accidents in the Spanish industrial and ornamental stone mining.

BACKGROUND: Mines are hazardous and workers can suffer many types of accidents caused by fire, flood, explosion or collapse. Injury incidence rates in mining are considerably higher than those registered by other economic sectors. One of the main reasons for this high-level incidence rate is the existence of a large number of dangerous workplaces. OBJECTIVE: This work analyzes the influence that occupational safety management had on the accidents that took place in Spanish mining of industrial and ornamental stone during the period 2007-2008. METHODS: Primary data sources are: (a) Results from a statistical study of the occupational health and safety management practices of 71 quarries defined by a questionnaire of 41 items; and (b) Occupational accidents registered in the Spanish industrial and ornamental stone mining throughout the period 2007-2008. RESULTS: The obtained results indicate that workplaces with a low average score in the analysis of occupational safety management have a higher incidence rate of accidents. CONCLUSIONS: Studies on mining workplaces are very important to help detect occupational safety concerns. Results from this study help raise awareness and will encourage the adoption of appropriate measures to improve safety.

Analysis of work related accidents in the Spanish mining sector from 1982-2006.

INTRODUCTION: The rate for work related accidents in the Spanish mining sector is notably higher than in other countries such as the United States. It produces a very negative impact on the mining industry. This paper is the report of a study on serious and fatal accidents in Spanish mining from 1982-2006. It is based on the reports of 212 accidents (serious or fatal) carried out by the General Management of Energy and Mining of Catalonia (Spain). METHOD: The high work-related accident rate in the Spanish mining sector makes it necessary to carry out an analysis and research that can shed light on the causes of this high rate; this is the only way that a solution can be found. The study is based on Feyer and Williamson's analysis of accident causes, as they apply to 212 accidents. The types and causes of the accidents are coded according to the coding system used by the Spanish National Institute for Safety and Hygiene in the Workplace, which allows us to identify a series of direct causes and contributing factors in different accidents. Results If all the causes and factors that are present in the accidents are known, we are able to look for appropriate solutions to reduce them as much as possible. In short, we are able to come up with a series of conclusions that expose the weak links in the management of accident prevention in companies. This is helpful in the struggle to reduce work injuries in the Spanish mining sector.