Quantifying Geometric Changes in BIM-GIS Conversion

Abstract. A conversion process is often carried out to migrate data during BIM and GIS integration, often from the highly detailed BIM to the less detailed GIS environment. Due to the differences between the two systems, information loss occurs during conversion. While research has been focusing on addressing information loss on the semantics, it is also necessary to quantify geometric changes resulted from converting geometry representations used in the two systems. This paper describes a preliminary study which evaluates the geometric changes during conversion for a list of primitives. The outcome shows that the metrics are useful both to those carrying out the conversion to balance between potential information loss and resulting data complexity, and to end users of the converted information to assess the fitness for purpose and impact of the conversion results

Decision Making in the 4th Dimension—Exploring Use Cases and Technical Options for the Integration of 4D BIM and GIS during Construction

In both the Geospatial (Geo) and Building Information Modelling (BIM) domains, it is widely acknowledged that the integration of geo-data and BIM-data is beneficial and a crucial step towards solving the multi-disciplinary challenges of our built environment. The result of this integration—broadly termed GeoBIM—has the potential to be particularly beneficial in the context of the construction of large infrastructure projects, which could make use of data relating to the larger spatial extents typically handled in geographical information systems (GIS) as well as the detailed models generated by BIM. To date, GeoBIM integration has mainly been explored for buildings, in a 3D context and for small projects. This paper demonstrates the results of the next level of integration, exploring the addition of the fourth dimension by linking project schedule information to create 4D GeoBIM, examining interoperability challenges and benefits in the context of a number of use cases relating to the enabling works for a major commercial infrastructure project. The integrating power of location and time—knowing where and when data relate to—allows us to explore data interoperability challenges relating to linking real world construction data, created using commercial software, with other data sources; we are then able to demonstrate the benefits of 4D GeoBIM in the context of three decision making scenarios: examining the potential for prioritisation of noise mitigation interventions by identifying apartments closest to the noisiest construction process; development of a 4D location-enabled risk register allowing, for example, work to continue underground if a risk is specific to the top of a building; ensuring construction safety by using 3D buffering to ensure that the required distances between moving construction equipment and surrounding infrastructure are not breached. Additionally, once integrated, we are able to ‘democratize’ the data—make it accessible beyond the BIM and GIS expert group—by embedding it into a 3D/4D open source Web GIS tool

Racial and Ethnic Differences in Diabetes Care and Health Care Use and Costs

INTRODUCTION: Previous studies have shown racial and ethnic differences in diabetes complication rates and diabetes control. The objective of this study was to examine racial and ethnic differences in diabetes care and health care use and costs for adults with diabetes using a nationally representative sample of the U.S. noninstitutionalized civilian population. METHODS: We performed a cross-sectional analysis of the 2000 Medical Expenditure Panel Survey (MEPS) and its related Diabetes Care Survey. The respondents were adults (aged 18 years and older) with diabetes, including non-Hispanic whites, non-Hispanic African Americans, and Hispanics. Racial and ethnic differences were examined in diabetes process of care and health care use and costs using logistic regression, negative binomial regression, and ordinary least squares regression with log cost. RESULTS: Most of the outcomes in diabetes care management, treatment, and complications were not significantly different among race groups. After adjusting for socioeconomic and demographic characteristics, Hispanics were more likely to have eye problems than whites (odds ratio, 1.56; 95% confidence interval, 1.03–2.56). African Americans and Hispanics had lower total health care costs, lower ambulatory care costs, and lower prescription drug costs than whites (P < .01 for all). CONCLUSION: We found differences in ambulatory care and prescription drug fills among white, African American, and Hispanic adults with diabetes. However, most of the diabetes care measures were not significantly different among the three racial and ethnic groups. Understanding the reason outcomes do not differ when health care use and costs differ significantly should be a focus of future studies

An Overview of Human Activity Recognition Using Wearable Sensors: Healthcare and Artificial Intelligence

With the rapid development of the internet of things (IoT) and artificial intelligence (AI) technologies, human activity recognition (HAR) has been applied in a variety of domains such as security and surveillance, human-robot interaction, and entertainment. Even though a number of surveys and review papers have been published, there is a lack of HAR overview papers focusing on healthcare applications that use wearable sensors. Therefore, we fill in the gap by presenting this overview paper. In particular, we present our projects to illustrate the system design of HAR applications for healthcare. Our projects include early mobility identification of human activities for intensive care unit (ICU) patients and gait analysis of Duchenne muscular dystrophy (DMD) patients. We cover essential components of designing HAR systems including sensor factors (e.g., type, number, and placement location), AI model selection (e.g., classical machine learning models versus deep learning models), and feature engineering. In addition, we highlight the challenges of such healthcare-oriented HAR systems and propose several research opportunities for both the medical and the computer science community

A timely computer-aided detection system for acute ischemic and hemorrhagic stroke on CT in an emergency environment

Standalone Presentations: no. LL-IN1105BACKGROUND: When a patient is accepted in the emergency room suspected of stroke, time is of the most importance. The infarct brain area suffers irreparable damage as soon as three hours after the onset of stroke symptoms. Non-contrast CT scan is the standard first line of investigation used to identify hemorrhagic stroke cases. However, CT brain images do not show hyperacute ischemia and small hemorrhage clearly and thus may be missed by emergency physicians. We reported a timely computer-aided detection (CAD) system for small hemorrhages on CT that has been successfully developed as an aid to ER physicians to help improve detection for Acute Intracranial Hemorrhage (AIH). This CAD system has been enhanced for diagnosis of acute ischemic stroke in addition to hemorrhagic stroke, which becomes a more complete and clinically useful tool for assisting emergency physicians and radiologists. In the detection algorithm, brain matter is first segmented, realigned, and left-right brain symmetry is evaluated. As in the AIH system, the system confirms hemorrhagic stroke by detecting blood presence with anatomical and medical knowledge-based criteria. For detecting ischemia, signs such as regional hypodensity, blurring of grey and white matter differentiation, effacement of cerebral sulci, and hyperdensity in middle cerebral artery, are evaluated …published_or_final_versio

Ultrasonic tomographic imaging of defects in industrial materials

Ultrasonic tomography has been fairly widely applied for imaging of inhomogeneities in isotropic materials, particularly in the medical field, however, little success has been made in its application to industrial materials. This is largely due to the complex nature of ultrasonic wave propagation in these anisotropic materials. The three dimensional characteristics of ultrasonic wave propagation in anisotropic materials have been thoroughly studied for single crystals and also studied recently for different composites [1,2,3]. Understanding these characteristics provides the theoretical background for developing appropriate ultrasonic tomographic imaging methods for industrial materials

f(R) Theories of Supergravities and Pseudo-supergravities

We present f(R) theories of ten-dimensional supergravities, including the fermionic sector up to the quadratic order in fermion fields. They are obtained by performing the conformal scaling on the usual supergravities to the f(R) frame in which the dilaton becomes an auxiliary field and can be integrated out. The f(R) frame coincides with that of M-theory, D2-branes or NS-NS 5-branes. We study various BPS p-brane solutions and their near-horizon AdS \times sphere geometries in the context of the f(R) theories. We find that new solutions emerge with global structures that do not exist in the corresponding solutions of the original supergravity description. In lower dimensions, We construct the f(R) theory of N=2, D=5 gauged supergravity with a vector multiplet, and that for the four-dimensional U(1)^4 gauged theory with three vector fields set equal. We find that some previously-known BPS singular "superstars" become wormholes in the f(R) theories. We also construct a large class of f(R) (gauged) pseudo-supergravities. In addition we show that the breathing mode in the Kaluza-Klein reduction of Gauss-Bonnet gravity on S^1 is an auxiliary field and can be integrated out.Comment: Latex, 46 page

Internet of Vehicles: Motivation, Layered Architecture, Network Model, Challenges, and Future Aspects

© 2013 IEEE. Internet of Things is smartly changing various existing research areas into new themes, including smart health, smart home, smart industry, and smart transport. Relying on the basis of 'smart transport,' Internet of Vehicles (IoV) is evolving as a new theme of research and development from vehicular ad hoc networks (VANETs). This paper presents a comprehensive framework of IoV with emphasis on layered architecture, protocol stack, network model, challenges, and future aspects. Specifically, following the background on the evolution of VANETs and motivation on IoV an overview of IoV is presented as the heterogeneous vehicular networks. The IoV includes five types of vehicular communications, namely, vehicle-to-vehicle, vehicle-to-roadside, vehicle-to-infrastructure of cellular networks, vehicle-to-personal devices, and vehicle-to-sensors. A five layered architecture of IoV is proposed considering functionalities and representations of each layer. A protocol stack for the layered architecture is structured considering management, operational, and security planes. A network model of IoV is proposed based on the three network elements, including cloud, connection, and client. The benefits of the design and development of IoV are highlighted by performing a qualitative comparison between IoV and VANETs. Finally, the challenges ahead for realizing IoV are discussed and future aspects of IoV are envisioned