Robust Optimization using a new Volume-Based Clustering approach

We propose a new data-driven technique for constructing uncertainty sets for robust optimization problems. The technique captures the underlying structure of sparse data through volume-based clustering, resulting in less conservative solutions than most commonly used robust optimization approaches. This can aid management in making informed decisions under uncertainty, allowing a better understanding of the potential outcomes and risks associated with possible decisions. The paper demonstrates how clustering can be performed using any desired geometry and provides a mathematical optimization formulation for generating clusters and constructing the uncertainty set. In order to find an efficient solution to the problem, we explore different approaches since the method may be computationally expensive. This contribution to the field provides a novel data-driven approach to uncertainty set construction for robust optimization that can be applied to real-world scenarios

The influence of personal knowledge management on individual decision making in health care medical treatment

In the age of technology, individuals are often confronted with considerable volumes of information when reading through literature relating to healthcare medical treatment. This may create confusion and hinder their decision-making process and they may not know what to do about their situation. With this in mind, this study will investigate how personal knowledge management (PKM) can help individuals better manage complex healthcare issues through well-informed decisions when facing healthcare medical treatment. Grounded action learning, an integration of grounded theory and action learning is adopted for this study. A framework for a PKM-based decision making training program format has been proposed based on action learning methods. Data collection and analysis is based on grounded theory approaches. This study is expected to provide new insights for PKM implementation to help individuals manage information overload and improve their information literacy skills as well as knowledge management (KM) capabilities when confronting health-related decisions

Can science-informed, consensus-based stakeholder negotiations achieve optimal dam decision outcomes?

Integrating science and decision-making in dam management is needed to address complex tradeoffs among environmental, economic, and social outcomes across varied geographic scales and diverse stakeholder interests. In this study, we introduce an approach that integrates system dynamics modeling (SDM) and role-play simulation (RPS) to facilitate use of the best available knowledge in dam decision-making. Using a hypothetical dam decision context in the New England region of the United States, this research investigates: (1) How do science-informed, negotiated outcomes compare to Pareto-optimal outcomes produced by a scientific model that balance selected system performance tradeoffs?; and (2) How do science-informed, negotiated outcomes compare to the status quo outcome? To our knowledge, this research is the first effort to combine SDM and RPS to support dam decisions and compare science-informed, consensus-based outcomes and optimized system outcomes. Our analyses show Pareto-optimal solutions usually involve a multi-dam management approach with diversified management options. Although all negotiated outcomes produced a net loss compared with at least one of the Pareto-optimal solutions balanced across tradeoffs, some yielded benefits close to or better than specific Pareto-optimal solutions. All negotiated outcomes yielded improvements over the status quo outcome. Our findings highlight the potential for science-informed, stakeholder-engaged approaches to inform decision-making and improve environmental and economic outcomes

A Business Analytics Approach to Strategic Management using Uncovering Corporate Challenges through Topic Modeling

Business analytics is a robust strategic management tool, and topic modeling is a technique that can be leveraged to derive insights from vast collections of unstructured data. Topic modeling is an automated method that identifies abstract concepts, or topics, present in various data sources, such as customer feedback, social media posts, and news articles. Through topic modeling, organizations can gain a better understanding of their customers, competitors, and market trends, which can be used to make informed strategic decisions, such as identifying new business opportunities, enhancing product or service offerings, and recognizing potential risks. Moreover, by integrating topic modeling with other business analytics approaches, such as predictive modeling, organizations can gain a more comprehensive perspective of their performance and make data-driven decisions. In essence, topic modeling is a valuable tool for strategic management that provides organizations with the insights they need to stay ahead of the competition and make informed decisions. To make effective strategic decisions, it is crucial to comprehend an organizations internal and external environments fully. The proposed approach utilizes text-mining techniques to augment traditional management tools, such as SWOT analysis or growth-share matrix. By examining narrative materials, such as financial disclosures, we apply topic modeling to identify critical challenges faced by an organization. We then quantify the language used in these materials in terms of risk and optimism, which provides a detailed understanding of a companys strengths and weaknesses and helps identify business units, activities, and processes that may be at risk. Additionally, this approach can be used to compare a company with its competitors or the broader market

Building Information Modeling: Case Study of a Duplex Building Project in Nigeria

Activities involved in construction projects have always been complex and continue to be yet more complex for the high level of sophistication the world have attained today. As the desires of man continue to expand, so do the interests of the stake holders in the built environment industry. But the vast advances in the Information and Communication Technology (ICT) have brought about substantial amounts of research on approaches and applications to reduce the burdens of the built environment complexities. One of these new advances is the Building Information Modeling (BIM). BIM unites Design, Construction, Maintenance, Management and Documentation of building projects thereby enhancing better informed decisions by the project team players and improving the end product. This research engages Building Information Technology on a modest duplex building project. The results obtained demonstrates that Building Information Modeling breaks distance barriers between the team players working on a project, enhances safety, economy, beauty and eliminates waste

Understanding Architectural Iron Conservation: Corrosion Studies at Fort Sumter National Monument

Iron is one of the most overlooked materials in architectural conservation. Its status as a functional construction material, rather than a decorative element, often makes iron the least understood material by architectural conservators. As historic metal becomes increasingly significant in the built environment, new approaches must be developed in order to better predict and understand the corrosion process. The behavior of corrosion has been extensively studied in the engineering and conservation communities, but the two fields have developed different approaches to iron conservation. Typically, engineers classify corrosion on a macroscopic scale, while conservators approach iron on a microscopic level. Both approaches are undeniably useful. There is, however, no middle ground between conservators, engineers, and contractors, to shape better-informed decisions regarding the sustainability, longevity, and integrity of historic iron. Famous for its role in the Civil War, Fort Sumter is now largely a ruin with few original iron artifacts intact. History has not been kind to the fort and the metal has experienced decades of exposure to the harsh marine climate--burial in sand, and multiple rebuilding campaigns. Three well understood causes of iron corrosion, the atmosphere, context, and the metal\u27s composition, were applied to the architectural iron at Fort Sumter to determine which aspect has the greatest impact. The temperature, wind, and airborne chloride levels were tracked at Fort Sumter to determine the atmospheric corrosivity level. As surrounding materials affect the exposure of embedded metal, each material was compared to see how its composition influenced the historic iron. A selection of iron objects was chosen for further analysis using X-ray fluorescence spectroscopy (XRF), Raman spectroscopy. By studying these aspects of iron corrosion, the National Park Service will be able to form a better understanding of the corrosion of historic ironwork and implement appropriate, sensitive conservation treatments

Accuracy of Using Visual Identification of White Sharks to Estimate Residency Patterns

Determining the residency of an aquatic species is important but challenging and it remains unclear what is the best sampling methodology. Photo-identification has been used extensively to estimate patterns of animals' residency and is arguably the most common approach, but it may not be the most effective approach in marine environments. To examine this, in 2005, we deployed acoustic transmitters on 22 white sharks (Carcharodon carcharias) in Mossel Bay, South Africa to quantify the probability of detecting these tagged sharks by photo-identification and different deployment strategies of acoustic telemetry equipment. Using the data collected by the different sampling approaches (detections from an acoustic listening station deployed under a chumming vessel versus those from visual sightings and photo-identification), we quantified the methodologies' probability of detection and determined if the sampling approaches, also including an acoustic telemetry array, produce comparable results for patterns of residency. Photo-identification had the lowest probability of detection and underestimated residency. The underestimation is driven by various factors primarily that acoustic telemetry monitors a large area and this reduces the occurrence of false negatives. Therefore, we propose that researchers need to use acoustic telemetry and also continue to develop new sampling approaches as photo-identification techniques are inadequate to determine residency. Using the methods presented in this paper will allow researchers to further refine sampling approaches that enable them to collect more accurate data that will result in better research and more informed management efforts and policy decisions

A Movement to Transform Foster Parenting

This report explores ways for public agencies to ensure that children receive the care they need by enlisting more volunteers to step forward as foster parents and by encouraging the extraordinary individuals who have already answered the call to continue their commitment to care. The report identifies three major themes for engaging and empowering foster parents: ensuring quality caregiving for children; forging strong relationships; and, finding and keeping more amazing caregivers

Collaborative Governance: A Guide for Grantmakers

Provides a framework for understanding the different tools and approaches within the emerging field of collaborative governance. Includes case examples that illustrate how the process works, and how it can be applied in specific situations