Integrating an Agent-Based Model into a Web-Enabled Annual Brome Land Management System

The natural fire cycle in the Great Basin area of Nevada has shortened from every 50 to 60 years to 3 to 5 years, putting many natural ecosystems and occupied lands in danger. The spreading phenomenon of the invasive annual brome will be investigated to quantify this fire risk. It is renowned for its invasive nature, flammability, and the detrimental effects it has on native annual and perennial grasses. Based on vegetation classifications and dispersal characteristics, the rules for an agent-based model will be used to simulate the future extents. Agent Analyst software in conjunction with ArcGIS will integrate simulation results into a web-enabled decision support system for land manager

New Knowledge for Old Regions? The Case of the Software Park Hagenberg in the Traditional Industrial Region of Upper Austria

This paper seeks to enhance our understanding about the opportunities and limits of new path creation in traditional regional innovation systems. Due to their inherited historical legacies, such systems are usually thought of being ill-equipped to give rise to high-tech or knowledge intensive activities. Departing from recent insights on research concerned with the transformation of innovation systems and evolutionary economic geography we identify in a conceptual way enabling and constraining factors for the rise of new development paths in traditional regions. Empirically, we focus on the case of the “Software Park Hagenberg†(SPH) located in the old industrial region of Upper Austria. We examine key events triggering the emergence and subsequent evolution of the SPH and explore the role of the RIS in shaping the development trajectory of the SPH. Moreover, applying social network analysis tools, we investigate the pattern of networking between firms, research organisations and educational bodies within the SPH and we provide some evidence on the diffusion of knowledge and innovation generated though these interactions throughout the regional economy.

MIDGARD: A Simulation Platform for Autonomous Navigation in Unstructured Environments

We present MIDGARD, an open-source simulation platform for autonomous robot navigation in outdoor unstructured environments. MIDGARD is designed to enable the training of autonomous agents (e.g., unmanned ground vehicles) in photorealistic 3D environments, and to support the generalization skills of learning-based agents through the variability in training scenarios. MIDGARD's main features include a configurable, extensible, and difficulty-driven procedural landscape generation pipeline, with fast and photorealistic scene rendering based on Unreal Engine. Additionally, MIDGARD has built-in support for OpenAI Gym, a programming interface for feature extension (e.g., integrating new types of sensors, customizing exposing internal simulation variables), and a variety of simulated agent sensors (e.g., RGB, depth and instance/semantic segmentation). We evaluate MIDGARD's capabilities as a benchmarking tool for robot navigation utilizing a set of state-of-the-art reinforcement learning algorithms. The results demonstrate MIDGARD's suitability as a simulation and training environment, as well as the effectiveness of our procedural generation approach in controlling scene difficulty, which directly reflects on accuracy metrics. MIDGARD build, source code and documentation are available at https://midgardsim.org/

Duckietown: An Innovative Way to Teach Autonomy

Teaching robotics is challenging because it is a multidisciplinary, rapidly evolving and experimental discipline that integrates cutting-edge hardware and software. This paper describes the course design and first implementation of Duckietown, a vehicle autonomy class that experiments with teaching innovations in addition to leveraging modern educational theory for improving student learning. We provide a robot to every student, thanks to a minimalist platform design, to maximize active learning; and introduce a role-play aspect to increase team spirit, by modeling the entire class as a fictional start-up (Duckietown Engineering Co.). The course formulation leverages backward design by formalizing intended learning outcomes (ILOs) enabling students to appreciate the challenges of: (a) heterogeneous disciplines converging in the design of a minimal self-driving car, (b) integrating subsystems to create complex system behaviors, and (c) allocating constrained computational resources. Students learn how to assemble, program, test and operate a self-driving car (Duckiebot) in a model urban environment (Duckietown), as well as how to implement and document new features in the system. Traditional course assessment tools are complemented by a full scale demonstration to the general public. The “duckie” theme was chosen to give a gender-neutral, friendly identity to the robots so as to improve student involvement and outreach possibilities. All of the teaching materials and code is released online in the hope that other institutions will adopt the platform and continue to evolve and improve it, so to keep pace with the fast evolution of the field.National Science Foundation (U.S.) (Award IIS #1318392)National Science Foundation (U.S.) (Award #1405259

Applying Software Product Lines to Build Autonomic Pervasive Systems

In this Master Thesis, we have proposed a model-driven Software Product Line (SPL) for developing autonomic pervasive systems. The work focusses on reusing the Variability knowledge from the SPL design to the SPL products. This Variability knowledge enables SPL products to deal with adaptation scenarios (evolution and involution) in an autonomic way.Cetina Englada, C. (2008). Applying Software Product Lines to Build Autonomic Pervasive Systems. http://hdl.handle.net/10251/12447Archivo delegad

Community Rehabilitation Programs and Organizational Change: A Mentor Guide to Increase Customized Employment Outcomes

[Excerpt] For the purpose of this Guide, customized employment is defined as a process for individualizing the employment relationship between an employee and an employer in ways that meet the needs of both. Customized employment is based on an individualized negotiation between the strengths, conditions and interests of the person with a disability and the identified business needs of the employer or the self-employment business chosen by the job seeker. Job negotiation uses job development or restructuring strategies that result in responsibilities being customized and individually negotiated to fit the requirements of the job