The Case of Microsoft\u27s Surface Tablet: Going Behind the Strategy with SWOT

Following its development at Harvard Business School in the 1950s, the SWOT framework became a frequently used decision tool. While the complexity organizations confront in the modern business world has increased, SWOT provides an intuitive way to organize information into internal “Strengths and Weaknesses” and external “Opportunities and Threats.” Another reason that SWOT remains relevant is its flexibility that enables integrating other analysis tools. It also encompasses multiple steps of strategy development to cover analysis, formulating options, and implementation

Data-Driven Generalized Integer Aperture Bootstrapping for Real-Time High Integrity Applications

A new method is developed for integer ambiguity resolution in carrier-phase differential GPS (CDGPS) positioning. The method is novel in that it is (1) data-driven, (2) generalized to include partial ambiguity resolution, and (3) amenable to a full characterization of the prior and posterior distributions of the three-dimensional baseline vector that results from CDGPS. The technique is termed generalized integer aperture bootstrapping (GIAB). GIAB improves the availability of integer ambiguity resolution for high-integrity, safety-critical systems. Current high-integrity CDGPS algorithms, such as EPIC and GERAFS, evaluate the prior risk of position domain biases due to incorrect integer ambiguity resolution without further validation of the chosen solution. This model-driven approach introduces conservatism which tends to reduce solution availability. Common data-driven ambiguity validation methods, such as the ratio test, control the risk of incorrect ambiguity resolution by shrinking an integer aperture (IA), or acceptance region. The incorrect fixing risk of current IA methods is determined by functional approximations that are inappropriate for use in safety-of-life applications. Moreover, generalized IA (GIA) methods incorrectly assume that the baseline resulting from partial ambiguity resolution is zero mean. Each of these limitations is addressed by GIAB, and the claimed improvements are validated by Monte Carlo simulation. The performance of GIAB is then optimized by tuning the integer aperture size to maximize the prior probability of full ambiguity resolution. GIAB is shown to provide higher availability than EPIC for the same integrity requirements.Aerospace Engineering and Engineering Mechanic

A Fight to the Death: Two Catalog Search Interfaces Battle it Out

Our old OPAC just couldn’t keep up with the search needs of our patrons. So, we looked for something easier to use with better results. Enter Encore and WorldCat Local — not just one, but two new search interfaces. We could only keep one, so find out how our students, faculty, and staff helped decide the outcome of this epic duel

The SPASE Data Model for Heliophysics Data: Is it Working?

The Space Physics Archive Search and Extract (SPASE) Data Model was developed to provide a metadata standard for describing Heliophysics (Space and Solar Physics) data within that science discipline. The SPASE Data Model has matured over the many years of its creation and is presently represented by Version 2.2.1. Information about SPASE can be obtained from the website group.org. The Data Model defines terms and values as well as the relationships between them in order to describe the data resources in the Heliophysics data environment. This data environment is quite complex, consisting of Virtual Observatories, Resident Archives, Data Providers, Partnering Data Centers, Services, Final Archives, and a Deep Archive. SPASE is the metadata language standard intended to permeate the complexity and provide a common method of obtaining and understanding data. Is it working in this capacity? SPASE has been used to describe a wide range of data. Examples range from ground-based magnetometer data to interplanetary satellite measurements to space weather model results. Has it achieved the goal of making the data easier to find and use? To find data of interest it is necessary that all the data of importance be described using the SPASE Data Model. Within the part of the data community associated with NASA (supported through NASA funding) there are obligations to use SPASE and (0 describe the old and new data using the SPASE XML schema. Although this pan of the community is not near 100% compliance with the mandate, there is good progress being made and the goal should be reachable in the future. Outside of the NASA data community there is still work to be done to convince the international community that SPASE descriptions are w011h the cost of their generation. Some of these groups such as Cluster, HELlO, GAIA, NOAA/NGDe. CSSDP, VSTO, SuperMAG, and IUGONET have agreed to use SPASE. but there are still other groups of importance that need (0 be reached. It is also assumed that the terminology is sufficiently broad and the descriptions are sufficiently complete that researchers needing data of a specific type or from a specific period can find and acquire what they need. A valid SPASE description can be very brief or very thorough depending on the willingness of the author to spend the time necessary to make the description useful. There is evidence that users are finding what they need through the SPASE descriptions, and this standard is a big step forward in Heliophysics data location. Does SPASE make it easier to use the data once they are found,) Thorough descriptions of data using SPASE can describe the data down to the level of individual parameters and exactly how the data are organized and stored. Should the SPASE data descriptions be written in such a way that they can be automatically ingested and understood by software tools'? Heliophysics instruments are becoming morc versatile all the time and the complexity of the data makes it tedious and time consuming to write SPASE descriptions with this level of sophistication even with the improvement of the tools used to generate the descriptions. Is it better to just write human-readable descriptions of the data at the parameter level or to refer to references that provide this information? This is a debate that is presently taking place and software is being developed to test what is possible

Issues in knowledge representation to support maintainability: A case study in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and runtime estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks. Because the scientific data processing modules (called fittings) evolve to match scientists' needs, issues regarding maintainability are of prime importance in PIPE. This paper describes the PIPE system and describes how issues in maintainability affected the knowledge representation used in PIPE to capture knowledge about the behavior of fittings

The Heliophysics Data Environment, Virtual Observatories, NSSDC, and SPASE

Heliophysics (the study of the Sun and its effects on the Solar System, especially the Earth) has an interesting data environment in that the data are often to be found in relatively small data sets widely scattered in archives around the world. Within the last decade there have been more concentrated efforts to organize the data access methods and create a Heliophysics Data and Model Consortium (HDMC). To provide data search and access capability a number of Virtual Observatories (VO's) have been established both via funding from the U.S. National Aeronautics and Space Administration (NASA) and through other funding agencies in the U.S. and worldwide. At least 15 systems can be labeled as Heliophysics Virtual Observatories, 9 of them funded by NASA. Other parts of this data environment include Resident Archives, and the final, or "deep" archive at the National Space Science Data Center (NSSDC). The problem is that different data search and access approaches are used by all of these elements of the HDMC and a search for data relevant to a particular research question can involve consulting with multiple VO's - needing to learn a different approach for finding and acquiring data for each. The Space Physics Archive Search and Extract (SPASE) project is intended to provide a common data model for Heliophysics data and therefore a common set of metadata for searches of the VO's and other data environment elements. The SPASE Data Model has been developed through the common efforts of the HDMC representatives over a number of years. We currently have released Version 2.1. of the Data Model. The advantages and disadvantages of the Data Model will be discussed along with the plans for the future. Recent changes requested by new members of the SPASE community indicate some of the directions for further development

Intelligent assistance in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and run time estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks

PERVASIVE TECHNOLOGY TO REDUCE ROAD RAGE: A STUDY ON THE EFFECTS OF METABOLIC CHANGES IN INDIVIDUALS WHILE DRIVING

poster abstractSince 1990, there have been 250,000 fatalities from car accidents in the United States (Warp, 2006). According to the United States Department of Transportation (nhtsa.dot.com), two-thirds of those fatalities are from acci-dents caused by road rage. That means 166,666 people died due to driver’s inability to control their anger on the road. Road rage is a serious issue that should be addressed. Often times, people don’t even realize they are becom-ing dangerously agitated until it is too late. The purpose of this study is to measure a drivers’ reaction to diverse stimuli in a simulated environment in order to examine how raising the awareness of the symptoms described might allow the driver to modify his/her behavior before engaging in disas-trous consequences. The stimuli used in testing for this study would include an array of graphics, videos and sounds. This study uses an Arduino board that connects to three bio-metric sensors which will track the users pulse, temperature and skin-conductivity. Whenever the human body is under mental stress, the parasympathetic activities of his/her heart decreases and the sympathetic activity increases (Rani, 2002). In other words, their pulse increases dramatically. Other signs of agitation include, but are not limited to: conductivity of skin increases and the tensing of muscles which causes the temperature of their extremities (fingers, hands and feet) to drop signifi-cantly. Upon IRB approval, this research will be conducted with fifty partici-pants. The data extracted from testing will be analyzed and finding’s report-ed