Análisis de la relación entre la accidentalidad y el incremento de trabajo en un proyecto de la construcción en Colombia durante los años 2012 y 2013

La construcción es una de las industrias que mayores accidentes laborales genera, en esta investigación se realizó un análisis retrospectivo para determinar si existe alguna relación entre la ocurrencia de accidentes y la fecha de entrega de una meta, debido al incremento en la cantidad de trabajo expresado por la cantidad de días y horas extras trabajados, se cuenta con información de la accidentalidad de cinco empresas constructoras de un gran proyecto vial en Colombia en los años de 2012 y 2013. Se analizó la información correspondiente a la nómina de las mismas empresas, con el valor de la nómina mensual, el valor de las incapacidades mensuales y la cantidad de trabajadores por cada empresa en cada periodo. El manejo de los datos se hizo con EXCEL y el análisis estadístico con STATA 11.1, se usó la correlación de Spearman para encontrar la relación entre la cantidad de accidentes acumulados y: la cantidad acumulada de días trabajados en cada mes, la cantidad acumulada de horas extras trabajadas mensualmente y el costo acumulado en porcentaje de la nómina mensual, encontrándose en todos los casos una relación lineal. Por otra parte, se realizó una prueba binomial para establecer la relación de la fecha de entrega de la meta con la accidentalidad 30 días antes y después, encontrando que la accidentalidad aumenta en la proximidad previa a la entrega de la meta

An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

Verificação da segurança sísmica de um edifício existente em betão armado

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Estruturas

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

Practical Solutions for Increased Safety in Paper Mill Operations

Tämä diplomityö käsittelee työterveys- ja työturvallisuushallinnan (TTT) sekä ympäristönsuojelun ongelmia ja riskejä, joita tehdasalueen toiminnanharjoittaja kohtaa ulkoistaessaan tehdastoimintojaan ja siirtyessään käyttämään 24 h ulkoisia kunnossapitopalveluja. Teoriaosa selventää ulkoistukseen liittyviä lainmukaisia määräyksiä ja vaatimuksia koskien terveyden, turvallisuuden ja ympäristöongelmien hallintaa sellu-, paperi- ja kartonkitehtaissa Euroopassa, Yhdysvalloissa ja Suomessa. TTT-toiminnan tason sekä ympäristönsuojelun tason mittaamisen ongelmat tuodaan esille. Olemassa olevia kansainvälisiä TTT-johtamisjärjestelmien ja ympäristöjärjestelmien standardeja, riskien hallintatyökaluja ja ohjelmia esitellään lyhyesti. Käytännön osa toteutettiin tapaustutkimuksena, jonka kohteena oli Äänekosken tehdaskombinaatti ja kemianteollisuuden laitos, Noviant CMC Oy. TTT-hallintatoimien ja ympäristönsuojelun ongelmia tutkitaan tehdastoimintoja ulkoistettaessa. Integroidun johtamisjärjestelmän auditointimenettelyt, ulkoistuksen kohdealueet, pk-yrityksien riskien hallinta ja ulkoisten työntekijöiden turvallisuuskoulutus ovat erityisen tarkastelun alla. Käyttäen hyväksi kerättyä TTT- ja ympäristöaineistoa, suunniteltiin malli ja sisältöehdotus uudelle internet-selain tyyppiselle työkalulle TTT- ja ympäristöasioiden hallinnan avuksi. Työkalu on tarkoitettu palvelemaan Noviant CMC Oy:n eri sidosryhmien tarpeita. Diplomityön käytännön osa muodostaa pohjan JP MILLSAFE - pilottiprojektille, joka käynnistettiin internet-selain tyyppisen turvallisuuspalvelusovelluksen kehittämiseksi palvelemaan Äänekosken tehdaskombinaatin eri sidosryhmien tarpeita.

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Development and Effect Analysis of the Asteri Consultative Auditing Process - Safety and Security Management in Educational Institutions

The Finnish legislation requires for a safe and secure learning environment. However, the comprehensive, risk based safety and security management (SSM) and the management commitment in the implementation and development of the SSM are not mentioned in the legislation. Multiple institutions, operators and researchers have studied and developed safety and security in educational institutions over the past decade. Typically the approach has been fragmented and without bringing up the importance of the comprehensive SSM. The development needs of the safety and security operations in universities have been studied. However, in universities of applied sciences (UASs) and in elementary schools (ESs), the performance level, strengths and weaknesses of the comprehensive SSM have not been studied. The objective of this study was to develop the comprehensive, risk based SSM of educational institutions by developing the new Asteri consultative auditing process and study its effects on auditees. Furthermore, the performance level in the comprehensive SSM in UASs and ESs were studied using Asteri and the TUTOR model developed by the Keski-Uusimaa Department for Rescue Services. In addition, strengths, development needs and differences were identified. In total, 76 educational institutions were audited between the years 2011 and 2014. The study is based on logical empiricism, and an observational applied research design was used. Auditing, observation and an electronic survey were used for data collection. Statistical analysis was used to analyze the collected information. In addition, thematic analysis was used to analyze the development areas of the organizations mentioned by the respondents in the survey. As one of the main contributions, this research presents the new Asteri consultative auditing process. Organizations with low performance levels on the audited subject benefit the most from the Asteri consultative auditing process. Asteri may be usable in many different types of audits, not only in SSM audits. As a new result, this study provides new knowledge on attitudes related to auditing. According to the research findings, auditing may generate negative attitudes and the auditor should take them into account when planning and preparing for audits. Negative attitudes can be compensated by producing added value, objectivity and positivity for the audit and, thus, improve the positive effects of auditing on knowledge and skills. Moreover, as the results of this study shows, auditing safety and security issues do not increase feelings of insecurity, but rather increase feelings of safety and security when using the new Asteri consultative auditing process with the TUTOR model. The results showed that the SSM in the audited UASs was statistically significantly more advanced than that in the audited ESs. However, there is still room for improvement in the ESs and the UASs as the approach to the SSM was fragmented. It can be assumed that the majority of Finnish UASs and ESs do not likely meet the basic level of the comprehensive, risk based the SSM.

Interaction and Intelligent Behavior

We introduce basic behaviors as primitives for control and learning in situated, embodied agents interacting in complex domains. We propose methods for selecting, formally specifying, algorithmically implementing, empirically evaluating, and combining behaviors from a basic set. We also introduce a general methodology for automatically constructing higher--level behaviors by learning to select from this set. Based on a formulation of reinforcement learning using conditions, behaviors, and shaped reinforcement, out approach makes behavior selection learnable in noisy, uncertain environments with stochastic dynamics. All described ideas are validated with groups of up to 20 mobile robots performing safe--wandering, following, aggregation, dispersion, homing, flocking, foraging, and learning to forage.

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Ações educativas sobre prevenção de acidentes infantis com professoras de educação infantil

Pós-graduação em Educação - FFC