Calibration of Computational Models with Categorical Parameters and Correlated Outputs via Bayesian Smoothing Spline ANOVA

It has become commonplace to use complex computer models to predict outcomes in regions where data does not exist. Typically these models need to be calibrated and validated using some experimental data, which often consists of multiple correlated outcomes. In addition, some of the model parameters may be categorical in nature, such as a pointer variable to alternate models (or submodels) for some of the physics of the system. Here we present a general approach for calibration in such situations where an emulator of the computationally demanding models and a discrepancy term from the model to reality are represented within a Bayesian Smoothing Spline (BSS) ANOVA framework. The BSS-ANOVA framework has several advantages over the traditional Gaussian Process, including ease of handling categorical inputs and correlated outputs, and improved computational efficiency. Finally this framework is then applied to the problem that motivated its design; a calibration of a computational fluid dynamics model of a bubbling fluidized which is used as an absorber in a CO2 capture system

The Operational Impacts of Chief Supply Chain Officers in Manufacturing Firms

Many firms have elevated their supply chain management decision-making responsibilities through the creation of ‘Chief Supply Chain Officer’ (CSCO) positions. This is widely attributed to the recognition that superior supply chain operations can generate a competitive advantage. Prior studies have found that firms with CSCOs outperform firms without CSCOs along many financial dimensions. However, these prior efforts did not examine the pathways by which these improvements occur. This study addresses this gap in the literature by investigating whether supply chain characteristics of manufacturing firms differ within firms with CSCOs. To explore this, we investigate the relationship between CSCOs and operational dimensions of supply chain performance using data from the 10-year period between 2008 and 2017. We find that the presence of a CSCO in a firm is associated with shorter cash conversion cycles, lower levels of operational slack, and larger buffers of inventory during periods of high market instability

Automated Structural-level Alignment of Multi-view TLS and ALS Point Clouds in Forestry

Access to highly detailed models of heterogeneous forests from the near surface to above the tree canopy at varying scales is of increasing demand as it enables more advanced computational tools for analysis, planning, and ecosystem management. LiDAR sensors available through different scanning platforms including terrestrial, mobile and aerial have become established as one of the primary technologies for forest mapping due to their inherited capability to collect direct, precise and rapid 3D information of a scene. However, their scalability to large forest areas is highly dependent upon use of effective and efficient methods of co-registration of multiple scan sources. Surprisingly, work in forestry in GPS denied areas has mostly resorted to methods of co-registration that use reference based targets (e.g., reflective, marked trees), a process far from scalable in practice. In this work, we propose an effective, targetless and fully automatic method based on an incremental co-registration strategy matching and grouping points according to levels of structural complexity. Empirical evidence shows the method's effectiveness in aligning both TLS-to-TLS and TLS-to-ALS scans under a variety of ecosystem conditions including pre/post fire treatment effects, of interest to forest inventory surveyors

Metro Meals on Wheels Treasure Valley Employs a Low-Cost Routing Tool to Improve Deliveries

In this paper, we discuss a project in which we developed a spreadsheet-based system that interfaces with a no-fee driving-directions application programming interface to quickly and accurately build a travel time and distance matrix and then rapidly determine near-optimal delivery-route schedules using a modified genetic algorithm. To the best of our knowledge, the method we used to create the travel matrix had not been employed previously in an academic study. The tool was tested and refined in a humanitarian setting—a local branch of the Meals on Wheels Association of America (now Meals on Wheels America), an organization that combats hunger and poverty by providing food to individuals who are in need. The tool, which is currently being utilized by Metro Meals on Wheels Treasure Valley, has substantially reduced the time required to plan deliveries and has also reduced the delivery driving times by approximately 15 percent

Generating Efficient Rebalancing Routes for Bikeshare Programs Using a Genetic Algorithm

Growth in urban areas often leads to problems such as increased traffic congestion and poor air quality. To help alleviate these issues, shared mobility networks have been launched in hundreds of cities worldwide to provide citizens with alternatives to personal autos and to other less sustainable methods of transport (Fishman, 2016; Zhang et al., 2015). Shared mobility includes carsharing, ridesharing, scooter sharing and bikesharing (SAE, 2018). Bikeshare programs allow users to pick up bicycles (often at hub locations), utilize the bicycle for a journey, and return it to a location within the system (DeMaio, 2009). While bicycle sharing has been in existence for many years in various forms, the advent of modern telecommunications (i.e., cellular technology and the internet) have enabled these programs to proliferate

Operational Leanness and Retail Firm Performance Since 1980

Lean is one of the most pervasive and powerful paradigms in Operations and Supply Chain Management. As a theory, lean has been well tested in manufacturing. Lean in retail has received less attention. There is good reason to think that seminal constructs from lean, such as inventory slack reduction and capacity slack reduction, may explain a great deal of the variance in retail firm performance. Therefore this paper tests lean-based propositions pertaining to the relationships between inventory slack, capacity slack, market instability and firm market performance. Using retail firm data from a 35 year period, we find that lean thinking in its basic unadorned form helps explain retail performance remarkably well. From both a snapshot and quarterly difference perspective and regardless of whether we look at capacity slack or inventory slack, lean produces superior, lasting returns for retailers

Misalignment Between Societal Well-Being and Business Profit Maximization: The Case of New York Taxis Drivers’ Incentive System

Objectives of business sustainability efforts commonly include increasing consumer safety, decreasing resource consumption, and decreasing pollution. Even though there is a societal interest in attaining these goals, business and other economic agents often operate under incentive structures that run counter to these objectives. Taxi drivers operate as economic independents. Their revenue depends on their fares and tips. Moreover they choose how many hours to work, how fast to drive, and which route to take. Using New York City taxi data from 2013, we test the level of alignment between the revenue maximizing behavior of drivers versus safety, conservation and pollution- related outcomes that are valued by stakeholders. We find substantial misalignment—i.e., in order to maximize revenue, drivers take inefficient routes and they exceed the speed limit thus decreasing safety, increasing fuel consumption and increasing air pollution. Based on these empirical results, we suggest methods of aligning societal goals with those of revenue maximizing taxi drivers

Assessing confidence in phylogenetic trees : bootstrap versus Markov chain Monte Carlo

Recent implementations of Bayesian approaches are one of the largest advances in phylogenetic tree estimation in the last 10 years. Markov chain Monte Carlo (MCMC) is used in these new approaches to estimate the Bayesian posterior probability for each tree topology of interest. Our goal is to assess the confidence in the estimated tree (particularly in whether prespecified groups are monophyletic) using MCMC and to compare the Bayesian estimate of confidence to a bootstrap-based estimate of confidence. We compare the Bayesian posterior probability to the bootstrap probability for specified groups in two real sets of influenza sequences and two sets of simulated sequences for our comparison. We conclude that the bootstrap estimate is adequate compared to the MCMC estimate except perhaps if the number of DNA sites is small

A system for interpretation of line drawings

Abstract-A system for interpretation of images of paper-based line drawings is described. Since a typical drawing contains both test strings and graphics, an algorithm has been developed to locate and separate text strings of various font size, style, and orientation. This is accom-plished by applying the Hough transform to the centroids of connected components in the image. The graphics in the segmented image is pro-cessed to represent thin entities by their core-lines and thick objects by their boundaries. The core-lines and boundaries are segmented into straight line segments and curved lines. The line segments and their interconnections are analyzed to locate minimum redundancy loops which are adequate to generate a succinct description of the graphics. Such a description includes the location and attributes of simple po-lygonal shapes, circles, and interconnecting lines, and a description of the spatial relationships and occlusions among them. Hatching and fill-ing patterns are also identified. The performance of the system is eval-uated using several test images and the results are presented. The su-periority of these algorithms in generating meaningful interpretations of graphics, compared to conventional data compression schemes, is clear from these results. Index Terns-Document image analysis, drawing conversion, fea-ture extraction, graphics recognition, image understanding, knowl-edge-based systems, line-drawing interpretation, pattern recognition, text segmentation, vectorization. I