An efficient and extendable python library to analyze neuronal morphologies

Peer reviewedFinal Accepted Versio

A comparison of methods to determine neuronal phase-response curves

The phase-response curve (PRC) is an important tool to determine the excitability type of single neurons which reveals consequences for their synchronizing properties. We review five methods to compute the PRC from both model data and experimental data and compare the numerically obtained results from each method. The main difference between the methods lies in the reliability which is influenced by the fluctuations in the spiking data and the number of spikes available for analysis. We discuss the significance of our results and provide guidelines to choose the best method based on the available data.Comment: PDFLatex, 16 pages, 7 figures

Estimating the Effect of Student Aid on College Enrollment: Evidence from a Government Grant Policy Reform

In this paper, we investigate the responsiveness of the demand for college to changes in student aid arising from a Danish reform. We separately identify the effect of aid from that of other observed and unobserved variables such as parental income. We exploit the combination of a kinked aid scheme and a reform of the student aid scheme to identify the effect of direct costs on college enrollment. To allow for heterogeneous responses due to borrowing constraints, we use detailed information on parents' assets. We find that enrollment is less responsive than found in other studies and that the presence of borrowing constraints only deters college enrollment to a minor extent.college attendance, educational subsidies, reform, kink regression

Reliable Identification of RFID Tags Using Multiple Independent Reader Sessions

Radio Frequency Identification (RFID) systems are gaining momentum in various applications of logistics, inventory, etc. A generic problem in such systems is to ensure that the RFID readers can reliably read a set of RFID tags, such that the probability of missing tags stays below an acceptable value. A tag may be missing (left unread) due to errors in the communication link towards the reader e.g. due to obstacles in the radio path. The present paper proposes techniques that use multiple reader sessions, during which the system of readers obtains a running estimate of the probability to have at least one tag missing. Based on such an estimate, it is decided whether an additional reader session is required. Two methods are proposed, they rely on the statistical independence of the tag reading errors across different reader sessions, which is a plausible assumption when e.g. each reader session is executed on different readers. The first method uses statistical relationships that are valid when the reader sessions are independent. The second method is obtained by modifying an existing capture-recapture estimator. The results show that, when the reader sessions are independent, the proposed mechanisms provide a good approximation to the probability of missing tags, such that the number of reader sessions made, meets the target specification. If the assumption of independence is violated, the estimators are still useful, but they should be corrected by a margin of additional reader sessions to ensure that the target probability of missing tags is met.Comment: Presented at IEEE RFID 2009 Conferenc

Convolutional neural networks for segmentation and object detection of human semen

We compare a set of convolutional neural network (CNN) architectures for the task of segmenting and detecting human sperm cells in an image taken from a semen sample. In contrast to previous work, samples are not stained or washed to allow for full sperm quality analysis, making analysis harder due to clutter. Our results indicate that training on full images is superior to training on patches when class-skew is properly handled. Full image training including up-sampling during training proves to be beneficial in deep CNNs for pixel wise accuracy and detection performance. Predicted sperm cells are found by using connected components on the CNN predictions. We investigate optimization of a threshold parameter on the size of detected components. Our best network achieves 93.87% precision and 91.89% recall on our test dataset after thresholding outperforming a classical mage analysis approach.Comment: Submitted for Scandinavian Conference on Image Analysis 201

McStas and Mantid integration

McStas and Mantid are two well established software frameworks within the neutron scattering community. McStas has been primarily used for simulating the neutron transport of instruments, while Mantid has been primarily used for data reduction. We report here the status of our work done on the interoperability between the instrument simulation software McStas and the data reduction software Mantid. This provides a demonstration of how to successfully link together two software that otherwise have been developed independently, and in particular here show how this has been achieved for an instrument simulation software and a data reduction software. This paper will also provide examples of some of the expected future enhanced analysis that can be achieved from combining accurate instrument and sample simulations with software for correcting raw data. In the case of this work for raw data collected at large scale neutron facilities.Comment: 17 pages, 12 figures, POSTPRINT with proofs of article submitted to Journal of Neutron Researc

Learning Paths to Offshore Outsourcing - From Cost Reduction to Knowledge Seeking

A corporation’s offshore outsourcing may be seen as the result of a discrete, strategic decision taken in response to an increasing pressure from worldwide competition. However, empirical evidence of a representative cross-sector sample of international Danish firms indicates that offshore sourcing in low-cost countries is best described as a learning-by-doing process in which the offshore outsourcing of a corporation goes through a sequence of stages towards sourcing for innovation. Initially, a corporation’s outsourcing is driven by a desire for cost minimization. Over a period of time the outsourcing experience lessens the cognitive limitations of decision-makers as to the advantages that can be achieved through outsourcing in low-cost countries: the insourcer/vendor may not only offer cost advantages, but also quality improvement and innovation. The quality improvements that offshore outsourcing may bring about evoke a realization in the corporation that even innovative processes can be outsourced.Offshore outsourcing, cost reduction, innovation, experiential learning, low-cost countries