The Relationship Between the Intelligence & Emotional Stability of Seventh & Eighth Grade Pupils

A question nearly as old as the intelligence test itself led the author to make the investigation upon which this thesis is based. For years people in education and related fields have speculated as to whether the most intelligent children were the most stable emotionally or whether these brighter children tended more readily than the dull or average child to exhibit undesirable personality variations. Practically everyone has, at some time in his life, used one or two isolated circumstances to prove the point that the more intelligent children were emotionally unstable or that the duller children were more unstable , than the brighter children. Each person, of course, In an argument of this nature always has at least one case to back up his belief. In keeping with modern educational practices of objective measurement rather than subjective opinion, the author has made an effort to died additional light upon this controversy by giving a series of objective examinations of intelligence and personality the students cf the seventh and eighth grades of the Warren County Schools

Motion compensated micro-CT reconstruction for in-situ analysis of dynamic processes

This work presents a framework to exploit the synergy between Digital Volume Correlation ( DVC) and iterative CT reconstruction to enhance the quality of high-resolution dynamic X-ray CT (4D-mu CT) and obtain quantitative results from the acquired dataset in the form of 3D strain maps which can be directly correlated to the material properties. Furthermore, we show that the developed framework is capable of strongly reducing motion artifacts even in a dataset containing a single 360 degrees rotation

Chemo-mechanics of salt and ice crystallization in rocks : a 4D study using X-ray micro computed tomography

COMInternational audienc

Investigating the influence of dynamic effects on two-phase flow at the pore scale with fast laboratory-based X-ray micro-CT

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Stipulation of Facts, \u3cem\u3eTVA v. Hill et al\u3c/em\u3e, Civil Action No. 3-76-48

Stipulation of facts agreed upon by the plaintiffs and defendants in the case of TVA v. Hill et al in the United States District Court for the Eastern District of Tennessee, Northern Division

Effect of an initial solution in iterative reconstruction of dynamically changing objects

Visualizing and analyzing dynamic processes in 3D is an emerging topic, e.g. in geosciences (Berg et al., 2009; Cnudde and Boone, 2013; Bultreys et al., accepted), which has only recently become possible due to fast, high-resolution CT scanning. However; dynamically changing objects pose a challenge in CT-imaging because the existing reconstruction algorithms, which reconstruct the sample volume from a number of scan images, presume an unchanging sample during the acquisition of the projection images. Movements or changes during the scan cause artefacts in the resulting volume. Furthermore, when fast processes are visualized, the acquisition time needs to be reduced, thus drastically decreasing the signal-to-noise ratio (SNR). To address these issues, an iterative reconstruction technique is applied, where an initial solution is provided to the algorithm. In this work, we present an evaluation of this method based on both simulations and real experimental data

Improving the reconstruction of dynamic processes by including prior knowledge

Visualizing and analyzing dynamic processes in 3 dimensions is an increasingly important topic. High-resolution CT-scanning is a suitable technique for this, as it is non-destructive and therefore does not hinder the dynamic process while it is advancing. However, CT reconstruction algorithms, which reconstruct a 3D volume from a series of projection images, assume a static sample. Motion artefacts are introduced when this assumption is invalid. This is usually solved by dividing the set of projection images in smaller subsets, each representing a time frame in which the change to the sample is assumed to be sufficiently small. Each subset can be reconstructed separately. However, due to the small size of the subsets and/or the high speed (and therefore lower statistics and higher noise) at which is scanned, the reconstruction quality is reduced. One method to improve reconstruction quality is using a priori knowledge. Of the two most used reconstruction algorithms, the iterative reconstruction scheme is best suited for this. The simultaneous algebraic reconstruction technique or SART starts from a (typically empty) volume and improves this gradually by back projecting the difference between a simulated projection from this volume and the measured projection. The resulting volume is used for the next iteration step. After a number of iterations, the solution converges to the final volume which represents the sample. In this research, this algorithm is used and adapted to take prior knowledge into account. Prior knowledge can take various forms. Using an initial volume (to start the reconstruction algorithm with) that resembles the sample is the most well-known and already presents a great improvement. This can be a volume that is reconstructed from a previous scan of the same sample, before the dynamic process is initiated, or one from after the process has finished. It is also possible to incorporate information in the algorithm about the regions in the volume where the changes are most likely to occur. The voxels in these regions are assigned a higher contribution from the back projection in comparison with their 'static' neighboring voxels which are assumed to be valid in the initial volume. This reduces the number of projections needed significantly. These forms of prior knowledge already pose a great improvement to the reconstruction quality, as is shown by the preliminary results. There are however numerous other possibilities to improve the reconstruction of dynamic processes. Other forms of prior knowledge, e.g. the continuity of changes or external measurements, can be included. Spatio-temporal correlations present another way to improve 4D-reconstruction. The projections will no longer be divided into completely separate subsets. Instead, the correlations between different projections will be used. This means that projections 'far' away from the time point that is being reconstructed will also (partially) be included. In this way the limitation of a small subset is (partially) removed, since much larger sets of projections are considered. The reconstructions that lie some time away from the reconstruction point cannot be straightforwardly included, since this would include exactly the artefacts that made the scanning of dynamic processes hard in the first place. This is a subject of further and current research. REFERENCES [1] M. Beister, D. Kolditz, W. A. Kalender, “Iterative reconstruction methods in X-ray CT,” Physica Medica, vol. 28, no. 2, pp. 94-108, Apr. 2012. [2] S. Berg, H. Ott, S. A. Klapp, A. Schwing, R. Neiteler, N. Brussee, A. Makurat, L. Leu, F. Enzmann, J.-O. Schwarz, “Real-time 3D imaging of Haines jumps in porous media flow,” Proc Natl Acad Sci U S A, vol. 110(10), pp. 3755–3759, Mar. 2013. [3] T. Bultreys, M. A. Boone, M. N. Boone, T. De Schryver, B. Masschaele, L. Van Hoorebeke, V. Cnudde, “Fast laboratory-based micro-computed tomography for pore-scale research: illustrative experiments and perspectives on the future,” Adv. Wat. Res., In Press. Available online May 2015. [4] V. Cnudde, M. N. Boone, “High-resolution X-ray computed tomography in geosciences: A review of the current technology and applications,” Earth-Science Reviews, vol. 123, pp. 1-17, Aug. 2013. [5] G. Van Eyndhoven, K. J. Batenburg, J. Sijbers, “Region-based iterative reconstruction of structurally changing objects in CT”, IEEE Trans. Image Processing, vol. 23, no. 2, pp. 909-919, Feb. 2014. [6] L. Brabant, “Latest developments in the improvement and quantification of high resolution X-ray tomography data,” Ph.D. dissertation, Dep. Phys. and Astr., Fac. Sciences, Ghent Univ., Ghent, Belgium, 2013