Built-in Library Research Articles

On-site determination of nerve and mustard gases using a field-portable gas chromatograph-mass spectrometer

A field-portable gas chromatograph-mass spectrometer (the Hapsite system) was evaluated for onsite determination of nerve gases and blistering agents. The analytical sequence involved gas sampling for 1 min, microtrap concentration (1 min), apolar capillary gas chromatographic separation (10 min), electron ionization, quadrupole mass spectrometric data acquisition, and personal computer-based data analysis. Vapor containing 1mg/m3 sarin (GB), 1mg/m3 soman (GD), 3mg/m3 tabun (GA), and 0.5mg/m3 mustard gas (HD) was analyzed using the Hapsite system. The chemical warfare agents (CWAs) were detected within 10 min, and identified from their respective mass spectra according to the built-in NIST library database. Being based on the signal levels of the CWA peaks observed in mass chromatograms for m/z 99 (GB), 126 (GD), 70 (GA), and 109 (HD), the detection limits (S/N = 3) were estimated to be 0.2, 0.5, 8, and 0.3μg/m3, respectively. A carryover phenomenon was observed after injecting actual CWA samples, necessitating several blank-air purges of the system. The extent of adsorption was in the order: HD > GA > GD > GB.

Development of software for structural analysis adapted to construction engineering applications

The paper presents the development and application of software for structural analysis adapted to construction engineering applications. The software consists of data structures, application subroutine libraries and the built-in Matlab subroutine library. For each application, the user writes an application-specific main program using the data structures and routines in the subroutine libraries. This gives the user flexibility to build a main program that is adapted to the specific needs of the current application. The software has been tested in a number of real-world projects, e.g. tunnels and bridges. The examples show that the software is a useful design tool for design work.

Crystal structure of PurE (BA0288) from Bacillus anthracis at 1.8 Å resolution

Crystal structure of PurE (BA0288) from <i>Bacillus anthracis</i> at 1.8 Å resolution

Adhesion measurements for electrostatic powder coatings using a vertical drop test rig and LabVIEW software

The total forces holding a layer of electrostatically charged powder onto a metal work piece results from the combination effect of an interfacial electrochemical phenomenon, an inter-particle/particle cohesive force and a bulk electrostatic image attractive force. An attempt has been made to obtain the total integrated effect by subjecting the powder coating to a mechanical impulsive force parallel to the metal substrate. This is a destructive measurement which is obtained by dropping the work piece down a vertical chute which incorporates an inductive charge pick up device to measure the charge of the powder coating during free fall. The sample is brought to rest at the bottom of the chute and dislodged powder is collected in a micro balance incorporated inside a Faraday cage. The exact charge/mass ratio of dislodged powder can be obtained and the technique enables the calibration of the inductive probe. All the measurements are taken with the powder layer before fusing. LabVIEW by National Instruments is a user friendly and powerful graphical development environment used for signal acquisition, measurement analysis, and data presentation. It is a package designed to acquire, analyse and present. Data acquired from the unit under test can be fed through DAQ cards, instruments or PXI systems and connected to a PC running LabVIEW for analysis. With multiple built-in functions and libraries that cover functions such as analysing and processing and also data visualization and report generation, LabVIEW is highly useful in this application.

A python extension to the ATLAS online software for the thin gap chamber trigger system

A Python extension module for A Toroidal LHC ApparatuS (ATLAS) Online Software has been developed for the Thin Gap Chamber (TGC) trigger system. Python is an interactive scripting language including built-in high-level libraries, and provides an easy way to build Web applications. These features are not included in the Online Software, and are important in developing test software for the TGC trigger system. The Python extension module is designed and implemented using a C++ library, Boost.Python. We have developed a Web application using the extension module and Zope (a Python-based Web application server), which allows one to monitor the TGC trigger system from anywhere in the world. The functionalities of the Python extension module and its application for the TGC trigger system are presented.

CODE COVERAGE-BASED POWER ESTIMATION TECHNIQUES FOR MICROPROCESSORS

We have developed a function-level power estimation methodology for predicting the power dissipation of embedded software. For a given microprocessor core, we empirically build the "power data bank", which stores the power information of the built-in library functions and basic instructions. To estimate the average power of an embedded software on this core, we first decompose the machine code into library functions and user-defined functions. We then use program profiling/tracing tools to get the execution information of the target software. Next, we evaluate the total energy consumption and execution time based on the "power data bank", and their ratio is taken as the average power. High efficiency is achieved because no power simulator is used once the "power data bank" is built. We apply this method to a commercial microprocessor core and get power estimates with an average error of 3%. Using this method, microprocessor vendors can provide users the "power data bank" without releasing details of the core to help users get early power estimates and eventually guide power optimization.

Cognitive modeling with spreadsheets.

Spreadsheet implementations of two different types of cognitive models--a neural network model and a statistical model--are presented. The two examples illustrate how to employ the facilities of spreadsheets, the spreadsheet data structure, array functions, the built-in function library, and the integrated optimizer, for building cognitive models. The two presented models are new extensions of existing models. They are used for simulating data from experiments illustrating that the extended versions are able to explain experimental results that could not be simulated by the original models. The whole simulation study demonstrates that spreadsheets are a handy tool, especially for researchers without programming knowledge who want to build cognitive models and for instructors teaching cognitive modeling.

Comparison Study of Different Implementations of Derivative Pricing Models

A common problem that instructors encounter in teaching financial modeling classes is how to implement these models on a PC. In this project, we survey three different ways to implement derivative pricing models and provide a detailed how-to, extending from writing computer codes to applying the models. The three programming tools chosen are Visual Basic for Applications (VBA), Matlab, and C. The user interface is as important as the speed of execution in justifying our choices. Because of the popularity and user-friendliness of MS Excel, we use Excel as our unified user interface and look for tools that provide an easy connection. In this regard, VBA is an obvious choice because it is the embedded macro language for Excel. C is known for its performance but is relatively difficult to code. Excel provides an interface to work with C (C API), so the user can combine the power of C and the user-friendliness of Excel. Matlab is used by engineers around the world for high power matrix computations. Its built-in library provides many functions that are essential for derivative modeling. In addition, it has a toolbox (Excel Link) that provides a linkage to Excel. This Web site provides both the online and printable hard copies of the user guide for the individual methods. All of the source codes and sample spreadsheets are categorized by programming languages and pricing models for easy downloading. New models are added to the Web site on an ongoing basis. We hope this open-source approach to implementation of pricing models will provide a cyber community for others to share their computer codes for teaching and research purposes.

Field applications of the Scout™ portable MCA

The use of Quantrad Sensor's ScoutTM in field type applications is described. The portability of the ScoutTM enables the user to obtain more accurate information in the field versus a survey meter. Isotopic identification is possible when ancillary information is combined with built-in software libraries. Data from the ScoutTM in remediation at Stanford Linear Accelerator (SLAC), NORM (Naturally Occurring Radioactive Maerial) measurements in California's Central Valley oil fields, medical isotope identification at nuclear pharmaceutical company and emergency response applications are presented. Additionally, custom software enabled the use of the ScoutTM in identification, qualification and detection of Special Nuclear Materials (SNM) in illicit trafficking and portal monitoring applications.

Garf: a tool for programming reliable distributed applications

The authors discuss Garf object-oriented tool that supports the design and programming of reliable distributed applications. Garf lets developers program an application and then replicate its critical components over several machines. Using a built-in library of distributed abstractions, developers can choose a replication strategy for each component of the application.

Multivariate simulation with DATASIM: The Mihal and Barrett study

A general-purpose data simulator,datasim, allows instructors and students to easily generate simulated data for experimental, crossbreak (frequency table), and multivariate research designs. Students can select any of a variety of data analysis problems from the built-in library and then obtain problem descriptions and “individualized” data sets to analyze and interpret.Datasim can also be used to generate, plot, and analyze interesting data sets for discussion in class, to demonstrate principles of sampling theory and research design, and to conduct sampling experiments (Monte Carlo research). Finally, the electronic blackboard capability of the program allows instructors to conveniently display multiple sources of information, such as outlines, graphs, sample data sets, anovas, and the like. The present paper focuses on the techniques and methods required to perform multivariate simulation. To this end, datasim is used to simulate a study by Mihal and Barrett (1976), which predicted auto accidents from measures of perceptual style, reaction time, and selective attention.