Automatic input rectification

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 51-55).We present a novel technique, automatic input rectification, and a prototype implementation, SOAP. SOAP learns a set of constraints characterizing typical inputs that an application is highly likely to process correctly. When given an atypical input that does not satisfy these constraints, SOAP automatically rectifies the input (i.e., changes the input so that it satisfies the learned constraints). The goal is to automatically convert potentially dangerous inputs into typical inputs that the program is highly likely to process correctly. Our experimental results show that, for a set of benchmark applications (Google Picasa, ImageMagick, VLC, Swfdec, and Dillo), this approach effectively converts malicious inputs (which successfully exploit vulnerabilities in the application) into benign inputs that the application processes correctly. Moreover, a manual code analysis shows that, if an input does satisfy the learned constraints, it is incapable of exploiting these vulnerabilities. We also present the results of a user study designed to evaluate the subjective perceptual quality of outputs from benign but atypical inputs that have been automatically rectified by SOAP to conform to the learned constraints. Specifically, we obtained benign inputs that violate learned constraints, used our input rectifier to obtain rectified inputs, then paid Amazon Mechanical Turk users to provide their subjective qualitative perception of the difference between the outputs from the original and rectified inputs. The results indicate that rectification can often preserve much, and in many cases all, of the desirable data in the original input.by Fan Long.S.M

Edge Shear Flows and Particle Transport near the Density Limit in the HL-2A Tokamak

Edge shear flow and its effect on regulating turbulent transport have long been suspected to play an important role in plasmas operating near the Greenwald density limit $n_G$. In this study, equilibrium profiles as well as the turbulent particle flux and Reynolds stress across the separatrix in the HL-2A tokamak are examined as $n_G$ is approached in ohmic L-mode discharges. As the normalized line-averaged density $\bar{n}_e/n_G$ is raised, the shearing rate of the mean poloidal flow $\omega_{\rm sh}$ drops, and the turbulent drive for the low-frequency zonal flow (the Reynolds power $\mathcal{P}_{Re}$) collapses. Correspondingly, the turbulent particle transport increases drastically with increasing collision rates. The geodesic acoustic modes (GAMs) gain more energy from the ambient turbulence at higher densities, but have smaller shearing rate than low-frequency zonal flows. The increased density also introduces decreased adiabaticity which not only enhances the particle transport but is also related to a reduction in the eddy-tilting and the Reynolds power. Both effects may lead to the cooling of edge plasmas and therefore the onset of MHD instabilities that limit the plasma density

Essays on data-driven optimization

The estimation of a data matrix contains two parts: the well estimated and the poorly estimated. The latter is usually throwing away because the estimations are off. As argued in this paper, ignoring is the wrong thing to do as the poorly estimated part is orthogonal to the well estimated. I will show how to use such orthogonality information via robust optimization and provide application in portfolio optimization, least-square regression, and dimension reduction. Across a large number of experiments, utilizing the orthogonality information consistently improves the performance.Information, Risk, and Operations Management (IROM

High magnetisation, monodisperse and water-dispersible CoFe@Pt core/shell nanoparticles

High magnetisation and monodisperse CoFe alloy nanoparticles are desired for a wide range of biomedical applications. However, these CoFe nanoparticles are prone to oxidation, resulting in the deterioration of their magnetic properties. In the current work, CoFe alloy nanoparticles were prepared by thermal decomposition of cobalt and iron carbonyls in organic solvents at high temperatures. Using a seeded growth method, we successfully synthesised chemically stable CoFe@Pt core/shell nanostructures. The obtained core/shell nanoparticles have high saturation magnetisation up to 135 emu g−1. The magnetisation value of the core/shell nanoparticles remains 93 emu g−1 after being exposed to air for 12 weeks. Hydrophobic CoFe@Pt nanoparticles were rendered water-dispersible by encapsulating with poly(maleic anhydride-alt-1-octadecene) (PMAO). These nanoparticles were stable in water for at least 3 months and in a wide range of pH from 2 to 11

Elaboration and characterization of Fe1–xO thin films sputter deposited from magnetite target

Majority of the authors report elaboration of iron oxide thin films by reactive magnetron sputtering from an iron target with Ar–O2 gas mixture. Instead of using the reactive sputtering of a metallic target we report here the preparation of Fe1–xOthin films, directly sputtered froma magnetite target in a pure argon gas flow with a bias power applied. This oxide is generally obtained at very low partial oxygen pressure and high temperature.We showed that bias sputtering which can be controlled very easily can lead to reducing conditions during deposition of oxide thin film on simple glass substrates. The proportion of wustite was directly adjusted bymodifying the power of the substrate polarization. Atomic force microscopy was used to observe these nanostructured layers. Mössbauer measurements and electrical properties versus bias polarization and annealing temperature are also reported

Survey of the needs of patients with spinal cord injury: impact and priority for improvement in hand function in tetraplegics\ud

Objective: To investigate the impact of upper extremity deficit in subjects with tetraplegia.\ud \ud Setting: The United Kingdom and The Netherlands.\ud \ud Study design: Survey among the members of the Dutch and UK Spinal Cord Injury (SCI) Associations.\ud \ud Main outcome parameter: Indication of expected improvement in quality of life (QOL) on a 5-point scale in relation to improvement in hand function and seven other SCI-related impairments.\ud \ud Results: In all, 565 subjects with tetraplegia returned the questionnaire (overall response of 42%). Results in the Dutch and the UK group were comparable. A total of 77% of the tetraplegics expected an important or very important improvement in QOL if their hand function improved. This is comparable to their expectations with regard to improvement in bladder and bowel function. All other items were scored lower.\ud \ud Conclusion: This is the first study in which the impact of upper extremity impairment has been assessed in a large sample of tetraplegic subjects and compared to other SCI-related impairments that have a major impact on the life of subjects with SCI. The present study indicates a high impact as well as a high priority for improvement in hand function in tetraplegics.\ud \u

Structural reliability analysis of multiple limit state functions using multi-input multi-output support vector machine

Selecting and using an appropriate structural reliability method is critical for the success of structural reliability analysis and reliability-based design optimization. However, most of existing structural reliability methods are developed and designed for a single limit state function and few methods can be used to simultaneously handle multiple limit state functions in a structural system when the failure probability of each limit state function is of interest, for example, in a reliability-based design optimization loop. This article presents a new method for structural reliability analysis with multiple limit state functions using support vector machine technique. A sole support vector machine surrogate model for all limit state functions is constructed by a multi-input multi-output support vector machine algorithm. Furthermore, this multi-input multi-output support vector machine surrogate model for all limit state functions is only trained from one data set with one calculation process, instead of constructing a series of standard support vector machine models which has one output only. Combining the multi-input multi-output support vector machine surrogate model with direct Monte Carlo simulation, the failure probability of the structural system as well as the failure probability of each limit state function corresponding to a failure mode in the structural system can be estimated. Two examples are used to demonstrate the accuracy and efficiency of the presented method

Re: Response to Request for Relevant Information on Bisphenol A Dear Ms. Oshita,

Authoritative Bodies Mechanism: Bisphenol-A). The Polycarbonate/BPA Global Group consists of the leading global manufacturers of bisphenol A and polycarbonate plastic, which for many years have supported and conducted scientific research to understand whether bisphenol A has the potential to cause health or environmental effects and to support scientifically sound public policy. As indicated by the signatures at the end of the attachment, the comments were prepare

New mobilities across the lifecourse: A framework for analysing demographically-linked drivers of migration

Date of acceptance: 17/02/2015Taking the life course as the central concern, the authors set out a conceptual framework and define some key research questions for a programme of research that explores how the linked lives of mobile people are situated in time–space within the economic, social, and cultural structures of contemporary society. Drawing on methodologically innovative techniques, these perspectives can offer new insights into the changing nature and meanings of migration across the life course.Publisher PDFPeer reviewe

Magnetic and Structural Properties of Nd₂Fe₁₇₋ₓMnₓ Solid Solutions

A series of Nd2Fe17-xMnx solid solutions with x values between 0 and and 6 were prepared and analyzed using magnetic measurements, neutron diffraction, and Mössbauer spectroscopy. All of the Nd2Fe17-xMnx samples crystallized in the Th2Zn17-x-type rhombohedral structure. The lattice parameters and unit cell volumes decrease with increasing manganese content up to ∼ x equal to 2, and then increase for higher manganese content. The magnetizations of Nd2Fe17-xMnx decrease with increasing manganese content and Nd2Fe17-xMnx is paramagnetic at room temperature for x greater than 3. The Curie temperature in Nd2Fe17-xMnx solid solutions is maximum for x equal to 0.5 and decreases at a rate of ∼ 10° per substituted manganese up to x equal to 3, after which it drops sharply. These results are discussed in terms of the manganese she occupancies in Nd2Fe17-xMnx