Ontological Reengineering for Reuse

This paper presents the concept of Ontological Reengineering as the process of retrieving and transforming a conceptual model of an existing and implemented ontology into a new, more correct and more complete conceptual model which is reimplemented. Three activities have been identified in this process: reverse engineering, restructuring and forward engineering. The aim of Reverse Engineering is to output a possible conceptual model on the basis of the code in which the ontology is implemented. The goal of Restructuring is to reorganize this initial conceptual model into a new conceptual model, which is built bearing in mind the use of the restructured ontology by the ontology/application that reuses it. Finally, the objective of Forward Engineering is output a new implementation of the ontology. The paper also discusses how the ontological reengineering process has been applied to the Standard-Units ontology [18], which is included in a Chemical-Elements [12] ontology. These two ontologies will be included in a Monatomic-Ions and Environmental-Pollutants ontologies

A Study of the Dynamics of Dust from the Kuiper Belt: Spatial Distribution and Spectral Energy Distribution

The dust produced in the Kuiper Belt (KB) spreads throughout the Solar System forming a dust disk. We numerically model the orbital evolution of KB dust and estimate its equilibrium spatial distribution and its brightness and spectral energy distributions (SED), assuming greybody absorption and emission by the dust grains. We show that the planets modify the KB disk SED, so potentially we can infer the presence of planets in spatially unresolved debris disks by studying the shape of their SEDs. We point out that there are inherent uncertainties in the prediction of structure in the dust disk, owing to the chaotic dynamics of dust orbital evolution imposed by resonant gravitational perturbations of the planets.Comment: 19 pages, 14 figures in jpg, accepted to A

Development of a Non-Iterative Balance Load Prediction Algorithm for the NASA Ames Unitary Plan Wind Tunnel

A non-iterative load prediction algorithm for strain-gage balances was developed for the NASA Ames Unitary Plan Wind Tunnels that computes balance loads from the electrical outputs of the balance bridges and a set of state variables. A state variable could be, for example, a balance temperature difference or the bellows pressure of a flow-through balance. The algorithm directly uses regression models of the balance loads for the load prediction that were obtained by applying global regression analysis to balance calibration data. This choice greatly simplifies both implementation and use of the load prediction process for complex balance configurations as no load iteration needs to be performed. The regression model of a balance load is constructed by using terms from a total of nine term groups. Four term groups are derived from a Taylor Series expansion of the relationship between the load, gage outputs, and state variables. The remaining five term groups are defined by using absolute values of the gage outputs and state variables. Terms from these groups should only be included in the regression model if calibration data from a balance with known bi-directional outputs is analyzed. It is illustrated in detail how global regression analysis may be applied to obtain the coefficients of the chosen regression model of a load component assuming that no linear or massive near-linear dependencies between the regression model terms exist. Data from the machine calibration of a six-component force balance is used to illustrate both application and accuracy of the non-iterative load prediction process

Wireless telecommunications technology

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2008.Includes bibliographical references (leaves 26-29).This thesis attempts to study the technological progress of wireless technology and the wireless industry throughout history, using high-level, non-device specific performance metrics. Such metrics are developed by following the broad functional category approach. The analysis performed is both qualitative and quantitative. Firstly, the quantitative study provides a general perspective of how the technology has evolved through history, looking for signs of constant evolution and/or signs of technological saturation or acceleration. Following this, the qualitative section aims to provide the basis of a strategic framework that could be of importance to organizations in the industry, in particular to those interested in making the right decisions regarding technology selection, new spectrum licensing, and new services pricing, by using a cost-benefit approach. It was found that, in concordance with the two previous analyses performed on the information and energy technology domains, a continuous progress in the metrics identified is observed in the three Functional Performance Metrics (FPM) determined for this study. Still, some weak signs of eventual saturation were observed in one of the metrics identified in the study for the first time in this kind of study. A rate of yearly progress of 15% was obtained from the spectral efficiency Functional Performance Metric (FPM), while significantly higher rates, close to 50%, were obtained for both the throughput and coverage density FPMs. The time series comprises over 100 years of data, from the late 1800's / early 1900's until the present.by Mario A. Amaya.S.M

Tunable organization of cellulose nanocrystals for controlled thermal and optical response

The biorenewable nature of cellulose nanocrystals (CNCs) has opened up new opportunities for cost-effective, sustainable materials design. By taking advantage of their distinctive structural properties and self-assembly, promising applications have started to nurture the fields of flexible electronics, biomaterials, and nanocomposites. CNCs exhibit two fundamental characteristics: rod-like morphology (5-20 nm wide, 50-500 nm long), and lyotropic behavior (i.e., liquid crystalline mesophases formed in solvents), which offer unique opportunities for structural control and fine tuning of thermal and optical properties based on a proper understanding of their individual behavior and interactions at different length scales. In the present work, we attempt to provide an integral description of the influence of single crystals in the thermal and optical response exhibited by nanostructured films. Our approach involved the connection of experimental evidence with predictions of molecular dynamics (MD) simulations. In order to assess the effect of CNC orientation in the bulk response, we produced cellulose nanostructured films under two different mechanisms, namely, self-organization and shear orientation. Self-organized nanostructured films exhibited the typical iridescent optical reflection generated by chiral nematic organization. Shear oriented films disrupted the cholesteric organization, generating highly aligned structures with high optical transparency. The resultant CNC organization present in all nanostructured films was estimated by a second order statistical orientational distribution based on two- dimensional XRD signals. A new method to determine the coefficient of thermal expansion (CTE) in a contact-free fashion was developed to properly characterize the thermal expansion of thin soft films by excluding other thermally activated phenomena. The method can be readily extended to other soft materials to accurately measure thermal strains in a non-destructive way. By evaluating the magnitude of film CTEs relative to those of individual CNC crystals, we highlighted the significant role played by crystalline interfaces. Likewise, after measuring the thermal conductivity of a single crystal and CNC films having multiple organizations, the interfacial thermal resistance arose as a governing factor for heat transport. We will offer further insights into the intricate connection of thermal and optical properties towards a future efficient manufacture and optimal CNC based-materials desig

Addressing the Impact of Artificial Intelligence on Journalism: the perception of experts, journalists and academics

Over the last decade, Artificial Intelligence (AI) has become gradually more prevalent in mass media and news agency newsrooms. This growing tendency has prompted intense debate about the negative impact on journalism, particularly on quality standards and ethical principles. Taking an explorative approach, this study aims to analyse the application of AI in newsrooms, focusing on the impact on news-making processes, media routines and profiles, highlighting the benefits and shortcomings, and finally, analysing the rise of ethical dilemmas. For this purpose, 15 in-depth interviews were conducted in two rounds, in 2019 and 2021, with a sample of journalists and other media professionals, academics, experts on the media industry, and providers of technology leading the work on AI. The international sample includes interviewees from the United States, the United Kingdom, Germany and Spain. The interviewees agree that AI will enhance journalists’ capabilities by saving time, augmenting the efficiency of the news-making processes and, therefore, increasing mass media industry productivity. However, a change of mind-set in the media environment is needed, and training on the use of these tools must be a priority given the lack of knowledge observed. Finally, the emergence of ethical issues underlines the need for continuous control and supervision of the processes undertaken by AI

Third Bose Fugacity Coefficient in One Dimension, as a Function of Asymptotic Quantities

In one of the very few exact quantum mechanical calculations of fugacity coefficients, Dodd and Gibbs (\textit{J. Math.Phys}.,\textbf{15}, 41 (1974)) obtained $b_{2}$ and $b_{3}$ for a one dimensional Bose gas, subject to repulsive delta-function interactions, by direct integration of the wave functions. For $b_{2}$, we have shown (\textit{Mol. Phys}.,\textbf{103}, 1301 (2005)) that Dodd and Gibbs' result can be obtained from a phase shift formalism, if one also includes the contribution of oscillating terms, usually contributing only in 1 dimension. Now, we develop an exact expression for $b_{3}-b_{3}^{0}$ (where $b_{3}^{0}$ is the free particle fugacity coefficient) in terms of sums and differences of 3-body eigenphase shifts. Further, we show that if we obtain these eigenphase shifts in a distorted-Born approximation, then, to first order, we reproduce the leading low temperature behaviour, obtained from an expansion of the two-fold integral of Dodd and Gibbs. The contributions of the oscillating terms cancel. The formalism that we propose is not limited to one dimension, but seeks to provide a general method to obtain virial coefficients, fugacity coefficients, in terms of asymptotic quantities. The exact one dimensional results allow us to confirm the validity of our approach in this domain.Comment: 29 page

The Progress in Wireless Data Transport and its Role in the Evolving Internet

The progress of wireless technology through the past 105 years is quantitatively reviewed in this paper. Spectral efficiency and coverage density are both found to increase in a relatively continuous exponential fashion over the entire period with spectral efficiency increasing at about 15% per year and coverage density at about 33% per year. Throughput by wireless technology was not found to follow a single exponential but instead followed an exponential with annual increase of only 5% up to the late 70s and since then (and the introduction of the cellular concept) has followed an exponential with annual increases of greater than 50%. These high rates of progress in the functional performance of wireless technology are an essential enabler for wireless interfaces to become the dominant mode for connecting to the Internet