Towards Informative Statistical Flow Inversion

This is the accepted version of 'Towards Informative Statistical Flow Inversion', archived originally at arXiv:0705.1939v1 [cs.NI] 14 May 2007.A problem which has recently attracted research attention is that of estimating the distribution of flow sizes in internet traffic. On high traffic links it is sometimes impossible to record every packet. Researchers have approached the problem of estimating flow lengths from sampled packet data in two separate ways. Firstly, different sampling methodologies can be tried to more accurately measure the desired system parameters. One such method is the sample-and-hold method where, if a packet is sampled, all subsequent packets in that flow are sampled. Secondly, statistical methods can be used to ``invert'' the sampled data and produce an estimate of flow lengths from a sample. In this paper we propose, implement and test two variants on the sample-and-hold method. In addition we show how the sample-and-hold method can be inverted to get an estimation of the genuine distribution of flow sizes. Experiments are carried out on real network traces to compare standard packet sampling with three variants of sample-and-hold. The methods are compared for their ability to reconstruct the genuine distribution of flow sizes in the traffic

MODELLING THE ELECTRON WITH COSSERAT ELASTICITY

Interactions between a finite number of bodies and the surrounding fluid, in a channel for instance, are investigated theoretically. In the planar model here the bodies or modelled grains are thin solid bodies free to move in a nearly parallel formation within a quasi-inviscid fluid. The investigation involves numerical and analytical studies and comparisons. The three main features that appear are a linear instability about a state of uniform motion, a clashing of the bodies (or of a body with a side wall) within a finite scaled time when nonlinear interaction takes effect, and a continuum-limit description of the body–fluid interaction holding for the case of many bodies

Sharps injury in Hospital Universiti Kebangsaan Malaysia (HUKM): Experiences of health care workers and students

Sharps injury among health care workers in HUKM has received serious attention lately due to the possible transmission of diseases like HIV, Hepatits B and Hepatitis C, which can cause serious consequences for the victim. The aim of the study was to gain a deeper understanding of the emotional problems experienced by health care workers who had incurred a sharps injury and the coping strategies adopted by them to overcome the problem. A 28 item semi-structured questionnaire was designed by the supervisors and the researcher as there was no existing questionnaire to be adopted, as no research had been carried out in this area prior to this. The target group consisted of 64 health care workers of different categories working in HUKM. Data was collected over a period of five months from November 2000 to March 2001. The results of the study revealed that the most frequently injured were the staff nurses, nearly 90% of whom were emotionally upset and were worried that they might contract a disease. There was no significant difference in the emotional stress experienced by the different categories of the health care workers, all were equally upset about the injury but each category of staff adopted different methods to overcome the tragedy. Open comments and opinions about prevention and the management of the sharps injury in HUKM as given by the respondents here are taken into account. Several views given by the participants were explored and discussed. Finally, several implications for nursing and recommendations have been presente

Two-stage estimation in inverse problems using a combined wavelet thresholding and penalized maximum likelihood

Inverse problems occur in a wide range of practical scientific investigations where the variables of interest are only observed indirectly, such as magnetic and seismic imaging in geophysics, electrical tomography in industrial process monitoring, or PET scanning in medicine. Linear inverse problems can be thought of as highly multivariate regression problems with strong multicollinearity where the aim is to interpret regression parameters-prediction is not of interest. Estimation, to give a fitted model, is known as an inverse problem which can be ill-posed and ill-conditioned, making estimation using least-squares or maximum likelihood unstable or even impossible. Instead, one approach is to introduce additional constraints through a penalty term and a penalized least-squares or penalized maximum likelihood approach taken. The major cause of numerical problems in the estimation is noise in the data and hence using a pre-processing which reduces noise may be helpful. Wavelet thresholding has proven to be highly efficient at separating useful information from noise but there has been very little work considering the use of wavelet methods for inverse problems. Hence it is of great interest to investigate the usefulness of this as an additional step in estimation for inverse problems. In particular a two stage process is proposed combining inversion and wavelet thresholding. The thresholding will be considered as either a pre-inversion or post-inversion filter and the results compared. A simulation investigation is described and reported which compares these two alternative, and also which uses a minimum mean-squared error approach to choose the penalty parameter, in the inversion, and the threshold, in the wavelet thresholding, either sequentially or jointly. The results demonstrate that a combined approach is worthwhile and that for the piecewise constant test function considered, it is better to post-process after the inversion step than it is to use the more intuitive wavelet thresholding pre-processing step for noise reduction before inversion. This new approach hence has the potential to enhance the estimation results in a wide range of applied inverse problems

Parameterized Algorithms for Graph Partitioning Problems

We study a broad class of graph partitioning problems, where each problem is specified by a graph $G=(V,E)$, and parameters $k$ and $p$. We seek a subset $U\subseteq V$ of size $k$, such that $\alpha_1m_1 + \alpha_2m_2$ is at most (or at least) $p$, where $\alpha_1,\alpha_2\in\mathbb{R}$ are constants defining the problem, and $m_1, m_2$ are the cardinalities of the edge sets having both endpoints, and exactly one endpoint, in $U$, respectively. This class of fixed cardinality graph partitioning problems (FGPP) encompasses Max $(k,n-k)$-Cut, Min $k$-Vertex Cover, $k$-Densest Subgraph, and $k$-Sparsest Subgraph. Our main result is an $O^*(4^{k+o(k)}\Delta^k)$ algorithm for any problem in this class, where $\Delta \geq 1$ is the maximum degree in the input graph. This resolves an open question posed by Bonnet et al. [IPEC 2013]. We obtain faster algorithms for certain subclasses of FGPPs, parameterized by $p$, or by $(k+p)$. In particular, we give an $O^*(4^{p+o(p)})$ time algorithm for Max $(k,n-k)$-Cut, thus improving significantly the best known $O^*(p^p)$ time algorithm

Adaptive Measurement Network for CS Image Reconstruction

Conventional compressive sensing (CS) reconstruction is very slow for its characteristic of solving an optimization problem. Convolu- tional neural network can realize fast processing while achieving compa- rable results. While CS image recovery with high quality not only de- pends on good reconstruction algorithms, but also good measurements. In this paper, we propose an adaptive measurement network in which measurement is obtained by learning. The new network consists of a fully-connected layer and ReconNet. The fully-connected layer which has low-dimension output acts as measurement. We train the fully-connected layer and ReconNet simultaneously and obtain adaptive measurement. Because the adaptive measurement fits dataset better, in contrast with random Gaussian measurement matrix, under the same measuremen- t rate, it can extract the information of scene more efficiently and get better reconstruction results. Experiments show that the new network outperforms the original one.Comment: 11pages,8figure

Degree spectra for transcendence in fields

We show that for both the unary relation of transcendence and the finitary relation of algebraic independence on a field, the degree spectra of these relations may consist of any single computably enumerable Turing degree, or of those c.e. degrees above an arbitrary fixed $\Delta^0_2$ degree. In other cases, these spectra may be characterized by the ability to enumerate an arbitrary $\Sigma^0_2$ set. This is the first proof that a computable field can fail to have a computable copy with a computable transcendence basis

Promiscuous, non-catalytic, tandem carbohydrate-binding modules modulate the cell-wall structure and development of transgenic tobacco (Nicotiana tabacum) plants

We have compared heterologous expression of two types of carbohydrate binding module (CBM) in tobacco cell walls. These are the promiscuous CBM29 modules (a tandem CBM29-1-2 and its single derivative CBM29-2), derived from a non-catalytic protein1, NCP1, of the Piromyces equi cellulase/hemicellulase complex, and the less promiscuous tandem CBM2b-1-2 from the Cellulomonas fimi xylanase 11A. CBM-labelling studies revealed that CBM29-1-2 binds indiscriminately to every tissue of the wild-type tobacco stem whereas binding of CBM2b-1-2 was restricted to vascular tissue. The promiscuous CBM29-1-2 had much more pronounced effects on transgenic tobacco plants than the less promiscuous CBM2b-1-2. Reduced stem elongation and prolonged juvenility, resulting in delayed flower development, were observed in transformants expressing CBM29-1-2 whereas such growth phenotypes were not observed for CBM2b-1-2 plants. Histological examination and electron microscopy revealed layers of collapsed cortical cells in the stems of CBM29-1-2 plants whereas cellular deformation in the stem cortical cells of CBM2b-1-2 transformants was less severe. Altered cell expansion was also observed in most parts of the CBM29-1-2 stem whereas for the CBM2b-1-2 stem this was observed in the xylem cells only. The cellulose content of the transgenic plants was not altered. These results support the hypothesis that CBMs can modify cell wall structure leading to modulation of wall loosening and plant growth