Impact estimation: IT priority decisions

Given resource constraints, prioritization is a fundamental process within systems engineering to decide what to implement. However, there is little guidance about this process and existing IT prioritization methods have several problems, including failing to adequately cater for stakeholder value. In response to these issues, this research proposes an extension to an existing prioritization method, Impact Estimation (IE) to create Value Impact Estimation (VIE). VIE extends IE to cater for multiple stakeholder viewpoints and to move towards better capture of explicit stakeholder value. The use of metrics offers VIE the means of expressing stakeholder value that relates directly to real world data and so is informative to stakeholders and decision makers. Having been derived from prioritization factors found in the literature, stakeholder value has been developed into a multi-dimensional, composite concept, associated with other fundamental system concepts: objectives, requirements, designs, increment plans, increment deliverables and system contexts. VIE supports the prioritization process by showing where the stakeholder value resides for the proposed system changes. The prioritization method was proven to work by exposing it to three live projects, which served as case studies to this research. The use of the extended prioritization method was seen as very beneficial. Based on the three case studies, it is possible to say that the method produces two major benefits: the calculation of the stakeholder value to cost ratios (a form of ROI) and the system understanding gained through creating the VIE table

How Bob Laughlin Tamed the Giant Graviton from Taub-NUT space

In this paper we show how two dimensional electron systems can be modeled by strings interacting with D-branes. The dualities of string theory allow several descriptions of the system. These include descriptions in terms of solitons in the near horizon D6-brane theory, non-commutative gauge theory on a D2-brane, the Matrix Theory of D0-branes and finally as a giant graviton in M-theory. The soliton can be described as a D2-brane with an incompressible fluid of D0-branes and charged string-ends moving on it. Including an NS5 brane in the system allows for the existence of an edge with the characteristic massless chiral edge states of the Quantum Hall system.Comment: 26 pages, 4 figures, discussions adde

A data science axiology: the nature, value, and risks of data science

Data science is not a science. It is a research paradigm with an unfathomed scope, scale, complexity, and power for knowledge discovery that is not otherwise possible and can be beyond human reasoning. It is changing our world practically and profoundly already widely deployed in tens of thousands of applications in every discipline in an AI Arms Race that, due to its inscrutability, can lead to unfathomed risks. This paper presents an axiology of data science, its purpose, nature, importance, risks, and value for problem solving, by exploring and evaluating its remarkable, definitive features. As data science is in its infancy, this initial, speculative axiology is intended to aid in understanding and defining data science to recognize its potential benefits, risks, and open research challenges. AI based data science is inherently about uncertainty that may be more realistic than our preference for the certainty of science. Data science will have impacts far beyond knowledge discovery and will take us into new ways of understanding the world

Near-IR Spectroscopy of a Young Super-Star Cluster in NGC 6946: Chemical Abundances and Abundance Patterns

Using the NIRSPEC spectrograph at Keck II, we have obtained H and K-band echelle spectra for a young (10-15 Myr), luminous (MV=-13.2) super-star cluster in the nearby spiral galaxy NGC 6946. From spectral synthesis and equivalent width measurements we obtain for the first time accurate abundances and abundance patterns in an extragalactic super-star cluster. We find [Fe/H]=-0.45+/-0.08 dex, an average alpha-enhancement of +0.22+/-0.1 dex, and a relatively low 12C/13C~ 8+/-2 isotopic ratio. We also measure a velocity dispersion of ~9.1 km/s, in agreement with previous estimates. We conclude that integrated high-dispersion spectroscopy of massive star clusters is a promising alternative to other methods for abundance analysis in extragalactic young stellar populations.Comment: 5 pages, incl. 2 figures. Accepted for publication in MNRAS Letters. The definitive version will be available at http://www.blackwell-synergy.co

Defining data science: a new field of inquiry

Data science is not a science. It is a research paradigm. Its power, scope, and scale will surpass science, our most powerful research paradigm, to enable knowledge discovery and change our world. We have yet to understand and define it, vital to realizing its potential and managing its risks. Modern data science is in its infancy. Emerging slowly since 1962 and rapidly since 2000, it is a fundamentally new field of inquiry, one of the most active, powerful, and rapidly evolving 21st century innovations. Due to its value, power, and applicability, it is emerging in 40+ disciplines, hundreds of research areas, and thousands of applications. Millions of data science publications contain myriad definitions of data science and data science problem solving. Due to its infancy, many definitions are independent, application-specific, mutually incomplete, redundant, or inconsistent, hence so is data science. This research addresses this data science multiple definitions challenge by proposing the development of coherent, unified definition based on a data science reference framework using a data science journal for the data science community to achieve such a definition. This paper provides candidate definitions for essential data science artifacts that are required to discuss such a definition. They are based on the classical research paradigm concept consisting of a philosophy of data science, the data science problem solving paradigm, and the six component data science reference framework (axiology, ontology, epistemology, methodology, methods, technology) that is a frequently called for unifying framework with which to define, unify, and evolve data science. It presents challenges for defining data science, solution approaches, i.e., means for defining data science, and their requirements and benefits as the basis of a comprehensive solution

Observations of storm morphodynamics using Coastal Lidar and Radar Imaging System (CLARIS): Importance of wave refraction and dissipation over complex surf-zone morphology at a shoreline erosional hotspot

Elevated water levels and large waves during storms cause beach erosion, overwash, and coastal flooding, particularly along barrier island coastlines. While predictions of storm tracks have greatly improved over the last decade, predictions of maximum water levels and variations in the extent of damage along a coastline need improvement. In particular, physics based models still cannot explain why some regions along a relatively straight coastline may experience significant erosion and overwash during a storm, while nearby locations remain seemingly unchanged. Correct predictions of both the timing of erosion and variations in the magnitude of erosion along the coast will be useful to both emergency managers and homeowners preparing for an approaching storm. Unfortunately, research on the impact of a storm to the beach has mainly been derived from pre and post storm surveys of beach topography and nearshore bathymetry during calm conditions. This has created a lack of data during storms from which to ground-truth model predictions and test hypotheses that explain variations in erosion along a coastline. We have developed Coastal Lidar and Radar Imaging System (CLARIS), a mobile system that combines a terrestrial scanning laser and an X-band marine radar system using precise motion and location information. CLARIS can operate during storms, measuring beach topography, nearshore bathymetry (from radar-derived wave speed measurements), surf-zone wave parameters, and maximum water levels remotely. In this dissertation, we present details on the development, design, and testing of CLARIS and then use CLARIS to observe a 10 km section of coastline in Kitty Hawk and Kill Devil Hills on the Outer Banks of North Carolina every 12 hours during a Nor\u27Easter (peak wave height in 8 m of water depth = 3.4 m). High decadal rates of shoreline change as well as heightened erosion during storms have previously been documented to occur within the field site. In addition, complex bathymetric features that traverse the surf-zone into the nearshore are present along the southern six kilometers of the field site. In addition to the CLARIS observations, we model wave propagation over the complex nearshore bathymetry for the same storm event. Data reveal that the complex nearshore bathymetry is mirrored by kilometer scale undulations in the shoreline, and that both morphologies persist during storms, contrary to common observations of shoreline and surf-zone linearization by large storm waves. We hypothesize that wave refraction over the complex nearshore bathymetry forces flow patterns which may enhance or stabilize the shoreline and surf-zone morphology during storms. In addition, our semi-daily surveys of the beach indicate that spatial and temporal patterns of erosion are strongly correlated to the steepness of the waves. Along more than half the study site, fifty percent or more of the erosion that occurred during the first 12 hours of the storm was recovered within 24 hours of the peak of the storm as waves remained large (\u3e2.5 m), but transitioned to long period swell. In addition, spatial variations in the amount of beach volume change during the building portion of the storm were strongly correlated with observed wave dissipation within the inner surf zone, as opposed to predicted inundation elevations or alongshore variations in wave height

Babies Behind Bars: Should Incarcerated Mothers be Allowed to Keep Their Newborns with Them in Prison?

Society\u27s traditional approach to women offenders has been focused on women as prisoners and not.., prisoners as women. Harsh implications for female offenders who are mothers can result from the view that incarceration not only curtails the prisoner\u27s freedom of movement but also terminates many of the individual\u27s civil rights as well. In reality, these women are doubly penalized with a prison sentence as well as temporary or permanent loss of their parental rights. Modern courts are beginning to recognize that [a] prisoner retains all of the rights of an ordinary citizen except those expressly, or by necessary implication, taken from him by law. This comment focuses on what impact this trend will have on one facet of a female offender\u27s parental rights: her right to keep a child she bears while incarcerated. An analysis will be made of the current situation nationwide with particular emphasis on Virginia\u27s treatment of this phenomenon

Towards a general framework for evaluating intelligent environments methodologies

Recent studies reveal that there are different methodologies for developing Intelligent Environments. Thus, it has become essential to scrutinize and evaluate the methodologies to increase our understanding of their strengths, weaknesses and features. However, these concerns have not been the target of recent research efforts. This paper presents an evaluation framework for qualitative evaluation of Intelligent Environment methodologies. It is a step towards standardization of current Intelligent Environments methodologies. The framework has been defined through studying, abstracting and unifying best practices from systems engineering. It is based on a generic life cycle model. As an initial validation, we evaluated the User Centred Intelligent Environment Development Process against the proposed framework. We note that this methodology at its current state presents some limitations which will be addressed in future works