Holistic Leadership: A Model for Leader-Member Engagement and Development

Dr. Candis Best explores the theory of holistic leadership and further provides the model and framework for it to be empirically tested. At present, Best opines that holistic leadership produces leadership which supports the development of self-leadership capacity while preparing participating members for the exercise of increasing levels of self-determination and participatory decision-making

The role of supervisory neglect in childhood injury

This paper explores the theoretical understandings of supervisory neglect and how these understandings might assist in delivering practical responses using a public health approach to child protection.Injury is the leading cause of death in Australians 1–44 years of age (McClure, Stevenson, & McEvoy, 2004). Transport-related injury, drowning, and assault/homicide were the three leading causes of injury-related deaths in Australian children between 2004 and 2006 (AIHW, 2009). Children are particularly vulnerable to different types of injury depending on their stage of growth and development. This vulnerability is dependent on a combination of the child’s developmental stage, exposure to environmental risk factors and the presence of protective factors (Towner & Dowswell, 2002). Due to the diverse nature of injury in the population, prevention programs are mainly targeted at similar types of injury or circumstances in specific population groups. Examples of such targeted programs include preventing car crashes in newly licensed young drivers or educating beach goers to swim between the flags

A canonical theory of dynamic decision-making

Decision-making behavior is studied in many very different fields, from medicine and eco- nomics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptual- ization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering

Path planning algorithm for a car-like robot based on cell decomposition method

This project proposes an obstacle avoiding path planning algorithm based on cell decomposition method for a car-like robot. Dijkstra’s algorithm is applied in order to find the shortest path. Using cell decomposition, the free space of the robot is exactly partitioned into cells. Then, the connectivity graph is created followed by calculating the shortest path by Dijkstra’s algorithm. This project also concerns the robot kinematic constraints such as minimum turning radius. Thus, kinematic modeling and Bezier curve have been used to obtain a feasible path. The algorithm is able to obtain a curvature bounded path with sub-optimal curve length while taking cell decomposition as reference skeleton. The C-space concept has been applied in this situation. The obstacles on the map are expanded according to the size of car-like robot, so that the robot could be treated as points on this map and the coordinates of the map is corresponding to these points. The simulation and experimental result shows the algorithm can obtain the collision free path which satisfies the curvature constraint and approaches the minimal curve length for a car-like robot

Integrated Dynamic Facade Control with an Agent-based Architecture for Commercial Buildings

Dynamic façades have significant technical potential to minimize heating, cooling, and lighting energy use and peak electric demand in the perimeter zone of commercial buildings, but the performance of these systems is reliant on being able to balance complex trade-offs between solar control, daylight admission, comfort, and view over the life of the installation. As the context for controllable energy-efficiency technologies grows more complex with the increased use of intermittent renewable energy resources on the grid, it has become increasingly important to look ahead towards more advanced approaches to integrated systems control in order to achieve optimum life-cycle performance at a lower cost. This study examines the feasibility of a model predictive control system for low-cost autonomous dynamic façades. A system architecture designed around lightweight, simple agents is proposed. The architecture accommodates whole building and grid level demands through its modular, hierarchical approach. Automatically-generated models for computing window heat gains, daylight illuminance, and discomfort glare are described. The open source Modelica and JModelica software tools were used to determine the optimum state of control given inputs of window heat gains and lighting loads for a 24-hour optimization horizon. Penalty functions for glare and view/ daylight quality were implemented as constraints. The control system was tested on a low-power controller (1.4 GHz single core with 2 GB of RAM) to evaluate feasibility. The target platform is a low-cost ($35/unit) embedded controller with 1.2 GHz dual-core cpu and 1 GB of RAM. Configuration and commissioning of the curtainwall unit was designed to be largely plug and play with minimal inputs required by the manufacturer through a web-based user interface. An example application was used to demonstrate optimal control of a three-zone electrochromic window for a south-facing zone. The overall approach was deemed to be promising. Further engineering is required to enable scalable, turnkey solutions

Semi-Structured Decision Processes: A Conceptual Framework for Understanding Human-Automation Decision Systems

The purpose of this work is to improve understanding of existing and proposed decision systems, ideally to improve the design of future systems. A "decision system" is defined as a collection of information-processing components -- often involving humans and automation (e.g., computers) -- that interact towards a common set of objectives. Since a key issue in the design of decision systems is the division of work between humans and machines (a task known as "function allocation"), this report is primarily intended to help designers incorporate automation more appropriately within these systems. This report does not provide a design methodology, but introduces a way to qualitatively analyze potential designs early in the system design process. A novel analytical framework is presented, based on the concept of "semi-Structured" decision processes. It is believed that many decisions involve both well-defined "Structured" parts (e.g., formal procedures, traditional algorithms) and ill-defined "Unstructured" parts (e.g., intuition, judgement, neural networks) that interact in a known manner. While Structured processes are often desired because they fully prescribe how a future decision (during "operation") will be made, they are limited by what is explicitly understood prior to operation. A system designer who incorporates Unstructured processes into a decision system understands which parts are not understood sufficiently, and relinquishes control by deferring decision-making from design to operation. Among other things, this design choice tends to add flexibility and robustness. The value of the semi-Structured framework is that it forces people to consider system design concepts as operational decision processes in which both well-defined and ill-defined components are made explicit. This may provide more insight into decision systems, and improve understanding of the implications of design choices. The first part of this report defines the semi-Structured process and introduces a diagrammatic notation for decision process models. In the second part, the semi-Structured framework is used to understand and explain highly evolved decision system designs (these are assumed to be representative of "good" designs) whose components include feedback controllers, alerts, decision aids, and displays. Lastly, the semi-Structured framework is applied to a decision system design for a mobile robot.Charles Stark Draper Laboratory, Inc., under IR&D effort 101