159 research outputs found
Improved bounds for covering complete uniform hypergraphs
No full textWe consider the problem of covering the complete r-uniform hypergraphs on n vertices using complete r-partite graphs. We obtain lower bounds on the size of such a covering. For small values of r our result implies a lower bound of Ω( ( er/r √r)n log n) on the size of any such covering. This improves the previous bound of O(rn log n) due to Snir. We also obtain good lower bounds on the size of a family of perfect hash function using simple arguments
<i>r</i>-Java: an<i>r</i>-process code and graphical user interface for heavy-element nucleosynthesis
No full textWe present r-Java, an r-process code for open use that performs r-process nucleosynthesis calculations. Equipped with a simple graphical user interface, r-Java is capable of carrying out nuclear statistical equilibrium (NSE), as well as static and dynamic r-process calculations, for a wide range of input parameters. In this introductory paper, we present the motivation and details behind r-Java and results from our static and dynamic simulations. Static simulations are explored for a range of neutron irradiation and temperatures. Dynamic simulations are studied with a parameterized expansion formula. Our code generates the resulting abundance pattern based on a general entropy expression that can be applied to both degenerate and non-degenerate matter, allowing us to track the rapid density and temperature evolution of the ejecta during the initial stages of ejecta expansion. At present, our calculations are limited to the waiting-point approximation. We encourage the nuclear astrophysics community to provide feedback on the code and related documentation, which is available for download from the website of the Quark-Nova Project: http://quarknova.ucalgary.ca
r-Java 2.0: the nuclear physics
No full textAims. We present r-Java 2.0, a nucleosynthesis code for open use that performs r-process calculations as well as a suite of other analysis tools. Methods. Equipped with a straightforward graphical user interface, r-Java 2.0 is capable of; simulating nuclear statistical equilibrium (NSE), calculating r-process abundances for a wide range of input parameters and astrophysical environments, computing the mass fragmentation from neutron-induced fission as well as the study of individual nucleosynthesis processes. Results. In this paper we discuss enhancements made to this version of r-Java, paramount of which is the ability to solve the full reaction network. The sophisticated fission methodology incorporated into r-Java 2.0 which includes three fission channels (beta-delayed, neutron-induced and spontaneous fission) as well as computation of the mass fragmentation is compared to the upper limit on mass fission approximation. The effects of including beta-delayed neutron emission on r-process yield is studied. The role of coulomb interactions in NSE abundances is shown to be significant, supporting previous findings. A comparative analysis was undertaken during the development of r-Java 2.0 whereby we reproduced the results found in literature from three other r-process codes. This code is capable of simulating the physical environment of; the high-entropy wind around a proto-neutron star, the ejecta from a neutron star merger or the relativistic ejecta from a quark nova. As well the users of r-Java 2.0 are given the freedom to define a custom environment. This software provides an even platform for comparison of different proposed r-process sites and is available for download from the website of the Quark-Nova Project
Probing the composition of sub-millisecond rotating compact stars by r-modes instability
No full textWe investigate the implications of the r-modes instability on the composition of a compact star rotating at a sub-millisecond period. In particular, the only viable astrophysical scenario for such an object, wich might present inside the Low Mass X-ray Binary associated with the x-ray transient XTE J1739-285, is that it has a strangeness content. Since previous analysis indicate that hyperonic stars or stars containing a kaon condensate are unlikely because of the mass-shedding constraint, the only remaining possibility is that such an object is either a strange quark star or a hybrid quark-hadron star
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Transfer learning for instance segmentation of waste bottles using Mask R-CNN algorithm
No full textThis paper proposes a methodological approach with a transfer learning scheme for plastic waste bottle detection and instance segmentation using the mask region proposal convolutional neural network (Mask R-CNN). Plastic bottles constitute one of the major pollutants posing a serious threat to the environment both in oceans and on land. The automated identification and segregation of bottles can facilitate plastic waste recycling. We prepare a custom-made dataset of 192 bottle images with pixel-by pixel-polygon annotation for the automatic segmentation task. The proposed transfer learning scheme makes use of a Mask R-CNN model pre-trained on the Microsoft COCO dataset. We present a comprehensive scheme for fine-tuning the base pre-trained Mask-RCNN model on our custom dataset. Our final fine-tuned model has achieved 59.4 mean average precision (mAP), which corresponds to the MS COCO metric. The results indicate promising application of deep learning for detecting waste bottles
Performance Evaluation Of Public And Private R&D Partnerships: (...)
No full text(WP 07/03 Clave pdf) This paper focuses on organizational learning and knowledge management through the intersectoral R&D relationship between government, universities and private organizations and explores the conditions that influence its performance. A study of over 150 of these projects, funded by Spanish government agencies, is presented in this paper. We empirically investigate how participating firm characteristics, the locus of the R&D agreement, and its organizational characteristics influence intersectoral R&D project performance. Expected and unexpected results are presented and discussed. Performance is determined using a data envelopment analysis (DEA)-based model.Learning capacity, Partnerships, R&D, Knowledge management
Redoubtable Sensor Networks
No full textWe give, for the first time, a precise mathematical analysis of the connectivity and security proper-
ties of sensor networks that make use of the random predistribution of keys. We also show how to
set the parameters—pool and key ring size—in such a way that the network is not only connected
with high probability via secure links but also provably resilient, in the following sense: We for-
mally show that any adversary that captures sensors at random with the aim of compromising
a constant fraction of the secure links must capture at least a constant fraction of the nodes of
the network. In the context of wireless sensor networks where random predistribution of keys is
employed, we are the first to provide a mathematically precise proof, with a clear indication of
parameter choice, that two crucial properties—connectivity via secure links and resilience against
malicious attacks—can be obtained simultaneously. We also show in a mathematically rigorous
way that the network enjoys another strong security property. The adversary cannot partition
the network into two linear size components, compromising all the links between them, unless it
captures linearly many nodes. This implies that the network is also fault tolerant with respect to
node failures. Our theoretical results are complemented by extensive simulations that reinforce
our main conclusions
Impact of Shared Electric Vehicles Availability to Provide Peak Reduction through Vehicle-to-Grid. A Case Study
No full textThis paper presents a Mix Integer Linear Programming (MILP) optimization approach to reduce peak demand and maximize revenue in a grid-connected building with a PV-equipped charging station for Shared EVs. The study investigates the impact of EV availability on the effectiveness of the system by comparing the results for different connection times of a fleet of Shared EVs, a private EV used for commuting, and a stationary battery. Results from the case study conducted in The Netherlands demonstrate that not only the duration but also the timing of EV connection significantly influence system effectiveness, emphasizing the need for accurate availability estimation. The trade-off between peak reduction and Peak-to-Average Ratio (PAR) reduction is also highlighted, underscoring the importance of considering both factors for optimizing charging station usage. These findings provide valuable insights for optimizing energy management, reducing peak loads, and increasing the utilization of renewable energy sources in the context of Shared EVs and V2G technology.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.DC systems, Energy conversion & Storag
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