ICADS: A cooperative decision making model with CLIPS experts

A cooperative decision making model is described which is comprised of six concurrently executing domain experts coordinated by a blackboard control expert. The focus application field is architectural design, and the domain experts represent consultants in the area of daylighting, noise control, structural support, cost estimating, space planning, and climate responsiveness. Both the domain experts and the blackboard were implemented as production systems, using an enhanced version of the basic CLIPS package. Acting in unison as an Expert Design Advisor, the domain and control experts react to the evolving design solution progressively developed by the user in a 2-D CAD drawing environment. A Geometry Interpreter maps each drawing action taken by the user to real world objects, such as spaces, walls, windows, and doors. These objects, endowed with geometric and nongeometric attributes, are stored as frames in a semantic network. Object descriptions are derived partly from the geometry of the drawing environment and partly from knowledge bases containing prototypical, generalized information about the building type and site conditions under consideration

A Behavioral Research Model for Small Unmanned Aircraft Systems for Data Gathering Operations

According to Hitlin (2017) of the Pew Research Center, only 8% of U.S. citizens own an unmanned aircraft. Additionally, regarding feelings if U.S. citizens saw an unmanned aircraft flying close to where they live, 26% say they would be nervous, 12% feel angry, and 11% are scared. As of March 9, 2018, there were 1,050,328 U.S. small unmanned aircraft system (sUAS) registrations compared to 947,970 November 29, 2017. While sUAS use has increased in the U.S., it has lagged when compared to other items for personal use available to U.S. citizens as 92% own cell phones (Anderson, 2015). This slower acceptance rate identifies a potential need for more research as to why. No studies have specifically focused on individual factors for the behavioral intention of using sUAS for data gathering, encompassing the variables used in this study, nor a Structural Equation Model that shows relevant factors and associated relationships. Also, current ground theories fall short, lacking appropriate variables or modeling ability. Thus, this dissertation study developed a new behavioral research model termed VMUTES to determine the factors that influenced individuals’ intentions to operate small sUASs for data gathering and relationships between those factors. A sUAS system is comprised of integrated hardware, software, processes, or firmware. Data gathering is defined in this study as the transmission or recording of audio, pictures, videos, or collection of other data for modeler, civil, or public use. The new VMUTES model integrates portions of the technology acceptance model (TAM) and theory of planned behavior (TPB) model integrated with new factors: perceived risk and knowledge of regulations. The study used random sampling of Amazon Mechanical Turk® (AMT) members using an AMT Human Intelligence Task (HIT) that included a link to an online cross-sectional large-scale survey to collect data. Data Analysis included descriptive statistics analysis and the SEM process. Besides developing and validating a model and determining influencing factors, attention was also on verifying the relationships between constructs. Study limitations and future research recommendations are also discussed. Results indicated the VMUTES model had a strong predictive power of sUAS use for data gathering with seven of the ten original hypotheses supported while having a good model fit. Four new hypotheses were also identified with three supported. Additionally, all VMUTES model factors except for facilitating conditions were determined to have either a direct or indirect effect on behavioral intention and/or actual behavior with the TAM and TPB related factors having the strongest effects. Practically, this study filled an aviation research knowledge gap for sUAS use for data gathering. It also provided a research model and identified influencing factors of individuals’ behavioral intentions related to sUAS for data gathering. Thus, the newly developed model incorporating new variables can be used for further sUAS research and can provide an adaptable model for aviation and other technology areas to predict and facilitate new technology implementation where current models fall short. Finally, this study explored new and verified previously existing demographic variables for individuals who use sUASs for data gathering

Peak Ventilation Reference Standards from Exercise Testing: From the FRIEND Registry

Peak Ventilation Reference Standards from Exercise Testing: From the FRIEND Registry. Med. Sci. Sports Exerc., Vol. 50, No. 12, pp. 2603–2608, 2018. Purpose: Cardiopulmonary exercise testing (CPX) provides valuable clinical information, including peak ventilation (V˙ Epeak), which has been shown to have diagnostic and prognostic value in the assessment of patients with underlying pulmonary disease. This report provides reference standards for V˙ Epeak derived from CPX on treadmills in apparently healthy individuals. Methods: Nine laboratories in the United States experienced in CPX administration with established quality control procedures contributed to the Fitness Registry and the Importance of Exercise National Database from 2014 to 2017. Data from 5232 maximal exercise tests from men and women without cardiovascular or pulmonary disease were used to create percentiles ofV˙ Epeak for both men and women by decade between 20 and 79 yr. Additionally, prediction equations were developed for V˙ Epeak using descriptive information. Results: V˙ Epeak was found to be significantly different between men and women and across age groups (P G 0.05). The rate of decline in V˙ Epeak was 8.0% per decade for both men and women. A stepwise regression model of 70% of the sample revealed that sex, age, and height were significant predictors ofV˙ Epeak. The equation was cross-validated with data from the remaining 30% of the sample with a final equation developed from the full sample (r = 0.73). Additionally, a linear regression model revealed forced expiratory volume in 1 s significantly predicted V˙ Epeak (r = 0.73). Conclusions: Reference standards were developed for V˙ Epeak for the United States population. Cardiopulmonary exercise testing laboratories will be able to provide interpretation of V˙ Epeak from these age and sex-specific percentile reference values or alternatively can use these nonexercise prediction equations incorporating sex, age, and height or with a single predictor of forced expiratory volume in 1 s

Implementation of a frame-based representation in CLIPS

Knowledge representation is one of the major concerns in expert systems. The representation of domain-specific knowledge should agree with the nature of the domain entities and their use in the real world. For example, architectural applications deal with objects and entities such as spaces, walls, and windows. A natural way of representing these architectural entities is provided by frames. This research explores the potential of using the expert system shell CLIPS, developed by NASA, to implement a frame-based representation that can accommodate architectural knowledge. These frames are similar but quite different from the 'template' construct in version 4.3 of CLIPS. Templates support only the grouping of related information and the assignment of default values to template fields. In addition to these features frames provide other capabilities including definition of classes, inheritance between classes and subclasses, relation of objects of different classes with 'has-a', association of methods (demons) of different types (standard and user-defined) to fields (slots), and creation of new fields at run-time. This frame-based representation is implemented completely in CLIPS. No change to the source code is necessary

Executing CLIPS expert systems in a distributed environment

This paper describes a framework for running cooperating agents in a distributed environment to support the Intelligent Computer Aided Design System (ICADS), a project in progress at the CAD Research Unit of the Design Institute at the California Polytechnic State University. Currently, the systems aids an architectural designer in creating a floor plan that satisfies some general architectural constraints and project specific requirements. At the core of ICADS is the Blackboard Control System. Connected to the blackboard are any number of domain experts called Intelligent Design Tools (IDT). The Blackboard Control System monitors the evolving design as it is being drawn and helps resolve conflicts from the domain experts. The user serves as a partner in this system by manipulating the floor plan in the CAD system and validating recommendations made by the domain experts. The primary components of the Blackboard Control System are two expert systems executed by a modified CLIPS shell. The first is the Message Handler. The second is the Conflict Resolver. The Conflict Resolver synthesizes the suggestions made by the domain experts, which can be either CLIPS expert systems, or compiled C programs. In DEMO1, the current ICADS prototype, the CLIPS domain expert systems are Acoustics, Lighting, Structural, and Thermal; the compiled C domain experts are the CAD system and the User Interface

Using PVM to host CLIPS in distributed environments

It is relatively easy to enhance CLIPS (C Language Integrated Production System) to support multiple expert systems running in a distributed environment with heterogeneous machines. The task is minimized by using the PVM (Parallel Virtual Machine) code from Oak Ridge Labs to provide the distributed utility. PVM is a library of C and FORTRAN subprograms that supports distributive computing on many different UNIX platforms. A PVM deamon is easily installed on each CPU that enters the virtual machine environment. Any user with rsh or rexec access to a machine can use the one PVM deamon to obtain a generous set of distributed facilities. The ready availability of both CLIPS and PVM makes the combination of software particularly attractive for budget conscious experimentation of heterogeneous distributive computing with multiple CLIPS executables. This paper presents a design that is sufficient to provide essential message passing functions in CLIPS and enable the full range of PVM facilities

MARBLE: A system for executing expert systems in parallel

This paper details the MARBLE 2.0 system which provides a parallel environment for cooperating expert systems. The work has been done in conjunction with the development of an intelligent computer-aided design system, ICADS, by the CAD Research Unit of the Design Institute at California Polytechnic State University. MARBLE (Multiple Accessed Rete Blackboard Linked Experts) is a system of C Language Production Systems (CLIPS) expert system tool. A copied blackboard is used for communication between the shells to establish an architecture which supports cooperating expert systems that execute in parallel. The design of MARBLE is simple, but it provides support for a rich variety of configurations, while making it relatively easy to demonstrate the correctness of its parallel execution features. In its most elementary configuration, individual CLIPS expert systems execute on their own processors and communicate with each other through a modified blackboard. Control of the system as a whole, and specifically of writing to the blackboard is provided by one of the CLIPS expert systems, an expert control system

Wilson Loops as Precursors

There is substantial evidence that string theory on AdS_5 x S_5 is a holographic theory in which the number of degrees of freedom scales as the area of the boundary in Planck units. Precisely how the theory can describe bulk physics using only surface degrees of freedom is not well understood. A particularly paradoxical situation involves an event deep in the interior of the bulk space. The event must be recorded in the (Schroedinger Picture) state vector of the boundary theory long before a signal, such as a gravitational wave, can propagate from the event to the boundary. In a previous paper with Polchinski, we argued that the "precursor" operators which carry information stored in the wave during the time when it vanishes in a neighborhood of the boundary are necessarily non-local. In this paper we argue that the precursors cannot be products of local gauge invariant operators such as the energy momentum tensor. In fact gauge theories have a class of intrinsically non-local operators which cannot be built from local gauge invariant objects. These are the Wilson loops. We show that the precursors can be identified with Wilson loops whose spatial size is dictated by the UV-IR connection.Comment: 23 pages, no figure

Systematic Review and Regression Modeling of the Effects of Age, Body Size, and Exercise on Cardiovascular Parameters in Healthy Adults

Purpose Blood pressure, cardiac output, and ventricular volumes correlate to various subject features such as age, body size, and exercise intensity. The purpose of this study is to quantify this correlation through regression modeling. Methods We conducted a systematic review to compile reference data of healthy subjects for several cardiovascular parameters and subject features. Regression algorithms used these aggregate data to formulate predictive models for the outputs—systolic and diastolic blood pressure, ventricular volumes, cardiac output, and heart rate—against the features—age, height, weight, and exercise intensity. A simulation-based procedure generated data of virtual subjects to test whether these regression models built using aggregate data can perform well for subject-level predictions and to provide an estimate for the expected error. The blood pressure and heart rate models were also validated using real-world subject-level data. Results The direction of trends between model outputs and the input subject features in our study agree with those in current literature. Conclusion Although other studies observe exponential predictor-output relations, the linear regression algorithms performed the best for the data in this study. The use of subject-level data and more predictors may provide regression models with higher fidelity. Significance Models developed in this study can be useful to clinicians for personalized patient assessment and to researchers for tuning computational models