The Impact of Web-Scale Discovery on the Use of Electronic Resources

In 2015, the University of California, Berkeley, launched EBSCO Discovery Service (EDS), a web-scale discovery tool, with a goal of improving visibility and usage of collections. This study applies linear regression analysis to usage data for ebooks, ejournals, and abstracts and indexing (A&I) databases before and after implementation of EDS in order to identify correlations between the discovery layer and usage of library electronic resources across platforms. Our findings diverge from conclusions drawn in the previous literature that indicate that resource use generally increases after a discovery tool is implemented. We examine data from a longer period of time than the previous literature had, looking for statistically significant changes in resource use. The discovery layer at UC Berkeley did not lead to equal increases across platforms, but rather to a complex array of increases and decreases in use according to a variety of factors.

Identification of a Large Amount of Excess Fe in Superconducting Single-Layer FeSe/SrTiO3 Films

The single-layer FeSe films grown on SrTiO3 (STO) substrates have attracted much attention because of its record high superconducting critical temperature (Tc). It is usually believed that the composition of the epitaxially grown single-layer FeSe/STO films is stoichiometric, i.e., the ratio of Fe and Se is 1:1. Here we report the identification of a large amount of excess Fe in the superconducting single-layer FeSe/STO films. By depositing Se onto the superconducting single-layer FeSe/STO films, we find by in situ scanning tunneling microscopy (STM) the formation of the second-layer FeSe islands on the top of the first layer during the annealing process at a surprisingly low temperature ($\sim$150{\deg}C) which is much lower than the usual growth temperature ($\sim$490{\deg}C). This observation is used to detect excess Fe and estimate its quantity in the single-layer FeSe/STO films. The amount of excess Fe detected is at least 20% that is surprisingly high for the superconducting single-layer FeSe/STO films. The discovery of such a large amount of excess Fe should be taken into account in understanding the high-Tc superconductivity and points to a likely route to further enhance Tc in the superconducting single-layer FeSe/STO films

Bio-Inspired Multi-Layer Spiking Neural Network Extracts Discriminative Features from Speech Signals

Spiking neural networks (SNNs) enable power-efficient implementations due to their sparse, spike-based coding scheme. This paper develops a bio-inspired SNN that uses unsupervised learning to extract discriminative features from speech signals, which can subsequently be used in a classifier. The architecture consists of a spiking convolutional/pooling layer followed by a fully connected spiking layer for feature discovery. The convolutional layer of leaky, integrate-and-fire (LIF) neurons represents primary acoustic features. The fully connected layer is equipped with a probabilistic spike-timing-dependent plasticity learning rule. This layer represents the discriminative features through probabilistic, LIF neurons. To assess the discriminative power of the learned features, they are used in a hidden Markov model (HMM) for spoken digit recognition. The experimental results show performance above 96% that compares favorably with popular statistical feature extraction methods. Our results provide a novel demonstration of unsupervised feature acquisition in an SNN

Lightning Presentation: How Discovery Tools Changed Instruction and Reference

In fall 2011, Viterbo University migrated from a legacy ILS and public catalog to a next generation ILS and discovery layer. Learn how the transition to a discovery environment affected reference and instruction services, librarian expectations of students, student interactions with the library, and faculty reactions to student research

Adaptive link-weight routing protocol using cross-layer communication for MANET

Routing efficiency is one of the challenges offered by Mobile Ad-hoc Networks (MANETs). This paper proposes a novel routing technique called Adaptive Link-Weight (ALW) routing protocol. ALW adaptively selects an optimum route on the basis of available bandwidth, low delay and long route lifetime. The technique adapts a cross-layer framework where the ALW is integrated with application and physical layer. The proposed design allows applications to convey preferences to the ALW protocol to override the default path selection mechanism. The results confirm improvement over AODV in terms of network load, route discovery time and link reliability

Context Information for Fast Cell Discovery in mm-wave 5G Networks

The exploitation of the mm-wave bands is one of the most promising solutions for 5G mobile radio networks. However, the use of mm-wave technologies in cellular networks is not straightforward due to mm-wave harsh propagation conditions that limit access availability. In order to overcome this obstacle, hybrid network architectures are being considered where mm-wave small cells can exploit an overlay coverage layer based on legacy technology. The additional mm-wave layer can also take advantage of a functional split between control and user plane, that allows to delegate most of the signaling functions to legacy base stations and to gather context information from users for resource optimization. However, mm-wave technology requires high gain antenna systems to compensate for high path loss and limited power, e.g., through the use of multiple antennas for high directivity. Directional transmissions must be also used for the cell discovery and synchronization process, and this can lead to a non-negligible delay due to the need to scan the cell area with multiple transmissions at different directions. In this paper, we propose to exploit the context information related to user position, provided by the separated control plane, to improve the cell discovery procedure and minimize delay. We investigate the fundamental trade-offs of the cell discovery process with directional antennas and the effects of the context information accuracy on its performance. Numerical results are provided to validate our observations.Comment: 6 pages, 8 figures, in Proceedings of European Wireless 201

The Route towards the ultimate network topology

In this talk I will try to summarize our quest for a realizable network topology that optimizes performance, cost, power consumption and partitionability. We have explored Fat Trees, Dragonflies, variations of dragonflies, Orthogonal Fat Trees, multi-layer HyperX's, Multi-layer Full Meshes and close-to Moore's (graph) bound topologies in an attempt to decide, with the best routing we could find, for a reasonable task-placement, and for a collection of workloads (synthetic and real-world), which topology to choose. Whereas a final decision for a single 'ultimate' topology remains elusive, the route towards it took us to unexpected paths that lead to the discovery of new insights in topology design and properties and in design of routing schemes