Sustainable forest management using decision theaters : rethinking participatory planning

Involving stakeholders in the decision-making process can be very complex and time consuming. Decision theater (DT), which enables the combination of visualization and decision modeling capabilities together with human capacity of insight and interaction, is proposed for addressing this challenging problem in the forest sector. A generic framework for designing DTs to support participatory planning in the forest sector is proposed. To enable DT implementation and support decision-making in the DT in the province of Québec, Canada, the conceptual design of a decision-support system called Forest Community-DSS (FC-DSS) has been developed. Implementing FC-DSS along with other technologies in a DT environment can contribute to engage the stakeholders in the decision-making process by increasing participation frequency, collecting more inputs from the stakeholders, supporting the development and evaluation of alternative options and the selection of preferred alternatives. A DT-based collaboration approach would contribute to address the multiple issues of the stakeholders involved in participatory planning in Québec. Other Canadian provinces and other countries facing similar issues can benefit from the proposed approach

Multi-level evolutionary algorithms resource allocation utilizing model-based systems engineering

This research presents an innovative approach to solve the resource allocation problems using Multi-level Evolutionary Algorithms. Evolutionary Algorithms are used to solve resource allocation problems in different domains and their results are then incorporated into a higher level system solution using another Evolutionary Algorithm to solve base camp planning problems currently faced by the U.S. Department of Defense. Two models are introduced to solve two domain specific models: a logistics model and a power model. The logistic model evaluates routes for logistics vehicles on a daily basis with a goal of reducing fuel usage by delivery trucks. The evaluation includes distance traveled and other constraints such as available resource levels and priority of refilling. The Power model incorporates an open source electrical distribution simulator to evaluate the placement of structures and generators on a map to reduce fuel usage. These models are used as the fitness function for two separate Evolutionary Algorithms to find solutions that reduce fuel consumption within the individual domains. A multi-level Evolutionary Algorithm is then presented, where the two Evolutionary Algorithms share information with a higher level Evolutionary Algorithm that combines the results to account for problem complexity from the interfacing of these systems. The results of using these methods on 5 different base camp sizes show that the techniques provide a considerable reduction of fuel consumption. While the Evolutionary Algorithms show significant improvement over the current methods, the multi-level Evolutionary Algorithm shows better performance than using individual Evolutionary Algorithms, with the results showing a 19.25 % decrease in fuel consumption using the multi-level Evolutionary Algorithm --Abstract, page iii

人・ユーザー中心の移動サービスと群集マネジメントのためのモデリング，シミュレーションと最適化

Tohoku University博士（情報科学）thesi

Labour ward in Northern Uganda - A locally rooted human centered approach

This thesis work proposes a design for a 100-births per month labour (maternity) ward in the North of Uganda, a low-resource setting challenged by socio-economic and political instability, deteriorated health infrastructure, lack of staff and resources, low accessibility to health services and erosion of medical ethics. The proposal is an addition to an existing medical centre located in Kitgum, Uganda. The region is seeing a rapid growth in population and in need of Maternal and Child Health Facilities to accommodate that growth and help reduce the high maternal and neonatal mortality rates. The architectural aim of this thesis is to design a labour (maternity) ward that spatially supports the woman and the companion’s journey through the facility, from admission to discharge, with a focus on local materials and techniques. Design principles such as natural ventilation, natural light, companion flow, hygiene and privacy strategies have been explored and applied given the remarkable absence of these concepts in current facilities. The wider societal aim is to shift privacy standards of contemporary facilities towards a more personal and intimate experience, through allowing the presence of a companion in all stages of the process. The work of this thesis has been structured in an initial research phase, followed by a one-month field trip in which research methods like interviews and workshops have been applied to collect data about the current health situation as well as traditional materials and techniques, and a design phase that has started while still on site. To sum up, this work offers a building that intends to reframe women’s birthing experience and raise awareness around innovative ways to improve the quality of care while still preserving traditional techniques, skills and materials.Rantanen, MarianaLazaro Rantanen, Marian

Ensuring Network Connectivity for Decentralized Planning in Dynamic Environments

This work addresses the issue of network connectivity for a team of heterogeneous agents operating in a dynamic environment. The Consensus-Based Bundle Algorithm (CBBA), a distributed task allocation framework previously developed by the authors and their colleagues, is introduced as a methodology for complex mission planning, and extensions are proposed to address limited communication environments. In particular, CBBA with Relays leverages information available through already existing consensus phases to predict the network topology at select times and creates relay tasks to strengthen the connectivity of the network. By employing underutilized resources, the presented approach improves network connectivity without limiting the scope of the active agents, thus improving mission performance.United States. Air Force Office of Scientific Research (Grant FA9550-08-1-0086)United States. Air Force Office of Scientific Research. Multidisciplinary University Research Initiative (FA9550-08-1-0356

I-Light Symposium 2005 Proceedings

I-Light was made possible by a special appropriation by the State of Indiana. The research described at the I-Light Symposium has been supported by numerous grants from several sources. Any opinions, findings and conclusions, or recommendations expressed in the 2005 I-Light Symposium Proceedings are those of the researchers and authors and do not necessarily reflect the views of the granting agencies.Indiana University Office of the Vice President for Research and Information Technology, Purdue University Office of the Vice President for Information Technology and CI

A Microscopic Simulation Laboratory for Evaluation of Off-street Parking Systems

The parking industry produces an enormous amount of data every day that, properly analyzed, will change the way the industry operates. The collected data form patterns that, in most cases, would allow parking operators and property owners to better understand how to maximize revenue and decrease operating expenses and support the decisions such as how to set specific parking policies (e.g. electrical charging only parking space) to achieve the sustainable and eco-friendly parking. However, there lacks an intelligent tool to assess the layout design and operational performance of parking lots to reduce the externalities and increase the revenue. To address this issue, this research presents a comprehensive agent-based framework for microscopic off-street parking system simulation. A rule-based parking simulation logic programming model is formulated. The proposed simulation model can effectively capture the behaviors of drivers and pedestrians as well as spatial and temporal interactions of traffic dynamics in the parking system. A methodology for data collection, processing, and extraction of user behaviors in the parking system is also developed. A Long-Short Term Memory (LSTM) neural network is used to predict the arrival and departure of the vehicles. The proposed simulator is implemented in Java and a Software as a Service (SaaS) graphic user interface is designed to analyze and visualize the simulation results. This study finds the active capacity of the parking system, which is defined as the largest number of actively moving vehicles in the parking system under the facility layout. In the system application of the real world testbed, the numerical tests show (a) the smart check-in device has marginal benefits in vehicle waiting time; (b) the flexible pricing policy may increase the average daily revenue if the elasticity of the price is not involved; (c) the number of electrical charging only spots has a negative impact on the performance of the parking facility; and (d) the rear-in only policy may increase the duration of parking maneuvers and reduce the efficiency during the arrival rush hour. Application of the developed simulation system using a real-world case demonstrates its capability of providing informative quantitative measures to support decisions in designing, maintaining, and operating smart parking facilities

Multi-agent cooperative swarm learning for dynamic layout optimisation of reconfigurable robotic assembly cells based on digital twin

To meet the requirement of product variety and short production cycle, reconfigurable manufacturing system is considered as an effective solution in addressing current challenges, such as increasing customisation, high flexibility and dynamic market demand. Dynamic factory layout design and optimisation are the crucial factors in response to rapid change in the mechanical structure, software and hardware integration, as well as production capability and functionality adjustment. Nevertheless, in the current research, the layout design for reconfigurable manufacturing systems is usually simplified with autonomous devices being regarded as 2D shapes. Issues such as overlapping and transportation distance are also addressed in an approximate form. In this paper, we present a novel multi-agent cooperative swarm learning framework for dynamic layout optimisation of reconfigurable robotic assembly cells. Based on its digital twin established in the proposed learning environment (constructed in Visual Components and controlled by TWINCAT), the optimisation framework uses 3D digital representation of the facility models with minimal approximation. Moreover, instead of using a traditional centralised learning manner, multi-agent system could provide an alternative way to address the layout issues combined with the proposed decentralised multi-agent cooperative swarm learning. In order to verify the application feasibility of the learning framework, two aerospace manufacturing use cases were implemented. In the first use case, the layout compactness is reduced by 3.8 times compared with the initial layout setting, the simulated production time is reduced by 2.3 times, and the rearrangement cost decreased by 33.4%. In addition, all manufacturing activity within the cell can be achieved with a feasible robot path, meaning without any joint limits, reachability or singularity issue at each key assembly point. In the second use case, we demonstrated that with the proposed dynamic layout optimisation framework, it is possible to flexibly adjust learning objectives by selecting various weight parameters among layout compactness, rearrangement cost and production time

Partnering with Profs

This thesis will focus on the study of corporate universities and the development of a business plan for the implementation of Bi-State University. Research presented will cause the reader \O consider alternatives 10 accomplish strategic organizational training and development objectives. The reader should keep in mind their organizational culture and the developmental needs of their organization\u27s human resources. The purpose of this commentary is to identify the various options available beyond traditional training methods to develop a corporate university for Bi-State Development Agency. The best way to research approaches to human development is to ask the subject matter experts. Several approaches were used in this research including phone interviews, interviews with practitioners in HR publications, teleconference interviews, journal articles from training/HR national publications, published works of professional trainers and books from the American Society of Training and Development Best Practices Series. The business plan will act as a proposal for a partnership with a local university to offer an on-sight Bachelors program at Bi-State. The degree program will be a study in Management with a major in Transportation. Over twenty Bi-State employees have a Masters or Ph. D. that qualifies their participation as instructors m this joint venture. Many of these people have or are currently teaching in local colleges and universities. The education plan will go beyond theory into practical application using real-world transportation problems and opportunities. Students will learn through a unique challenge of combining classroom theory with practical application of the learned theory on tl1e job at Bi-State. This developmental approach will provide participants with education and practical career building learning. This project is one of a series of HR initiatives to assist Bi-State in creating a Learning Organization and help become the employer of choice in the public sector in the St. Louis region

1996-1998 Course Catalog

1996-1998 Course Catalo