14,267 research outputs found
Second report on containers
In our first report on containers published in January,1967,
we tried to summarise progress in this new mode of
transportation and to define some of the problems which
existed
First report on containers
Everybody agrees that containers are a "good thing";the
actual advantages of transporting cargo, and in particular,
dry cargo, in containers over other forms of transport have,
to our knowledge, nowhere been stated in quantitative terms.
It is claimed that containers will reduce the turn-round time
of ships, ease congestion in the docks, speed-up total transit
time of cargo, reduce the risk of pilferage, reduce packaging
cost and reduce total handling effort in all stages of
transit.
Given that all these advantages are real, it is obvious that
they do not accrue in equal measure to all parties concerned
in the movement of goods from consignor to consignee. There
is indeed a likelihood of a conflict of interest between
these parties.
In this report we shall try to delineate the various problem
areas, indicate the quantitative information that needs to
be collected in order to decide how to solve these problems
and outline an approach to such solutions
Perfect State Transfer: Beyond Nearest-Neighbor Couplings
In this paper we build on the ideas presented in previous works for perfectly
transferring a quantum state between opposite ends of a spin chain using a
fixed Hamiltonian. While all previous studies have concentrated on
nearest-neighbor couplings, we demonstrate how to incorporate additional terms
in the Hamiltonian by solving an Inverse Eigenvalue Problem. We also explore
issues relating to the choice of the eigenvalue spectrum of the Hamiltonian,
such as the tolerance to errors and the rate of information transfer.Comment: 8 pages, 2 figures. Reorganised, more detailed derivations provided
and section on rate of information transfer adde
Procedures for the analysis and use of multiple view angle image data
It is recognised that the majority of vegetative cover types have anisotropic reflectance characteristics that are largely a function of their canopy geometry. Several studies have made attempts at formulating methods for the use of data remotely sensed from off-nadir directions. The best of these methods attempt to utilise the "extra" information implicitly contained in off-nadir image datasets. In this study, an attempt is made to extract information concerning agro-physical parameters of a number of vegetative cover types using imagery acquired by an airborne sensor, the Daedalus Airborne Thematic Mapper (ATM). It is also recognised in the literature that the nature of spatial variance in images is related to the size and distribution of the objects in the scene and the sampling characteristics of the sensor. In previous work this relationship has been explored by examining scenes using images of varying spatial resolutions, using a number of measurements of spatial variance. The underlying trend of these measurements is then used to interpret the nature of the objects in the scene. No previous work exists which attempts to utilise the change in variance of images acquired at different off-nadir view angles. In this study, the understanding of this relationship is developed by examining the change in variance of a number of vegetative cover types from multiple view angle image datasets. The geometry of the ATM sensor is derived to allow an understanding of the sampling characteristics of the instrument. Two important geometric factors are established: first, the area of the ground resolution element increases with view angle, which effectively reduces spatial resolution at off-nadir angles; and second, overlap between adjacent ground resolution elements increases with view angle, increasing the spatial auto-correlation between these samples. The effects of illumination, atmosphere and topography can all influence variance in an image. A parametric procedure for normalising multiple view angle (and therefore multitemporal) datasets for these factors is developed, based upon the production of reflectance images using a sky radiance model of the spectral and spatial distributions of irradiance, ground measurements of irradiance, and a digital terrain model of the study site. Finally, it is shown that image variance is likely to decrease at off-nadir view angles, the magnitude of this decrease being related to the sensor geometry and (more importantly) the geometry of the canopy. By a simple statistical analytical procedure it is possible to construct broad classes within which the nature of the canopy can be classified
Partial Information Decomposition as a Unified Approach to the Specification of Neural Goal Functions
In many neural systems anatomical motifs are present repeatedly, but despite
their structural similarity they can serve very different tasks. A prime
example for such a motif is the canonical microcircuit of six-layered
neo-cortex, which is repeated across cortical areas, and is involved in a
number of different tasks (e.g.sensory, cognitive, or motor tasks). This
observation has spawned interest in finding a common underlying principle, a
'goal function', of information processing implemented in this structure. By
definition such a goal function, if universal, cannot be cast in
processing-domain specific language (e.g. 'edge filtering', 'working memory').
Thus, to formulate such a principle, we have to use a domain-independent
framework. Information theory offers such a framework. However, while the
classical framework of information theory focuses on the relation between one
input and one output (Shannon's mutual information), we argue that neural
information processing crucially depends on the combination of
\textit{multiple} inputs to create the output of a processor. To account for
this, we use a very recent extension of Shannon Information theory, called
partial information decomposition (PID). PID allows to quantify the information
that several inputs provide individually (unique information), redundantly
(shared information) or only jointly (synergistic information) about the
output. First, we review the framework of PID. Then we apply it to reevaluate
and analyze several earlier proposals of information theoretic neural goal
functions (predictive coding, infomax, coherent infomax, efficient coding). We
find that PID allows to compare these goal functions in a common framework, and
also provides a versatile approach to design new goal functions from first
principles. Building on this, we design and analyze a novel goal function,
called 'coding with synergy'. [...]Comment: 21 pages, 4 figures, appendi
Exact partial information decompositions for Gaussian systems based on dependency constraints
The Partial Information Decomposition (PID) [arXiv:1004.2515] provides a
theoretical framework to characterize and quantify the structure of
multivariate information sharing. A new method (Idep) has recently been
proposed for computing a two-predictor PID over discrete spaces.
[arXiv:1709.06653] A lattice of maximum entropy probability models is
constructed based on marginal dependency constraints, and the unique
information that a particular predictor has about the target is defined as the
minimum increase in joint predictor-target mutual information when that
particular predictor-target marginal dependency is constrained. Here, we apply
the Idep approach to Gaussian systems, for which the marginally constrained
maximum entropy models are Gaussian graphical models. Closed form solutions for
the Idep PID are derived for both univariate and multivariate Gaussian systems.
Numerical and graphical illustrations are provided, together with practical and
theoretical comparisons of the Idep PID with the minimum mutual information PID
(Immi). [arXiv:1411.2832] In particular, it is proved that the Immi method
generally produces larger estimates of redundancy and synergy than does the
Idep method. In discussion of the practical examples, the PIDs are complemented
by the use of deviance tests for the comparison of Gaussian graphical models.Comment: 39 pages, 9 figures, 9 table
Historical-institutionalist perspectives on the development of the EU budget system
The EU budget has only recently started to feature in theories of European integration. Studies typically adopt a historical-institutionalist framework, exploring notions such as path dependency. They have, however, generally been rather aggregated, or coarse-grained, in their approach. The EU budget has thus been treated as a single entity rather than a series of inter-linked institutions. This paper seeks to address these lacunae by adopting a fine-grained approach. This enables us to emphasize the connections that exist between EU budgetary institutions, in both time and space. We show that the initial set of budgetary institutions was unable, over time, to achieve consistently their treaty-based objectives. In response, rather than reform these institutions at potentially high political cost, additional institutions were layered on top of the extant structures. We thus demonstrate how some EU budgetary institutions have remained unchanged, whilst others have been added or changed over time
Local Realism of Macroscopic Correlations
We show that for macroscopic measurements which cannot reveal full
information about microscopic states of the system, the monogamy of Bell
inequality violations present in quantum mechanics implies that practically all
correlations between macroscopic measurements can be described by local
realistic models. Our results hold for sharp measurement and arbitrary closed
quantum systems.Comment: 9 pages incl. one Appendix, 2 figure
Distributional Modes for Scalar Field Quantization
We propose a mode-sum formalism for the quantization of the scalar field
based on distributional modes, which are naturally associated with a slight
modification of the standard plane-wave modes. We show that this formalism
leads to the standard Rindler temperature result, and that these modes can be
canonically defined on any Cauchy surface.Comment: 15 pages, RevTe
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