Genetically Enhanced Performance of a UTRA-like Time-Division Duplex CDMA Network

In this contribution a Dynamic Channel Allocation (DCA) algorithm is developed, which minimizes the amount of Multi-User Interference (MUI) experienced at the Base Stations (BSs) by employing Genetic Algorithms (GAs). A GA is utilized for finding a suboptimum, but highly beneficial Uplink (UL) or Downlink (DL) Timeslot (TS) allocation for improving the achievable performance of the third generation UTRA system’s Time Division Duplex (TDD) mode. It is demonstrated that a GA-assisted UL/DL timeslot scheduling scheme may avoid the severe BS to BS inter-cell interference potentially inflicted by the UTRA TDD CDMA air interface owing to allowing all TSs to be used both in the UL and D

ERASE: Energy Efficient Task Mapping and Resource Management for Work Stealing Runtimes

Parallel applications often rely on work stealing schedulers in combination with fine-grained tasking to achieve high performance and scalability. However, reducing the total energy consumption in the context of work stealing runtimes is still challenging, particularly when using asymmetric architectures with different types of CPU cores. A common approach for energy savings involves dynamic voltage and frequency scaling (DVFS) wherein throttling is carried out based on factors like task parallelism, stealing relations, and task criticality. This article makes the following observations: (i) leveraging DVFS on a per-task basis is impractical when using fine-grained tasking and in environments with cluster/chip-level DVFS; (ii) task moldability, wherein a single task can execute on multiple threads/cores via work-sharing, can help to reduce energy consumption; and (iii) mismatch between tasks and assigned resources (i.e., core type and number of cores) can detrimentally impact energy consumption. In this article, we propose EneRgy Aware SchedulEr (ERASE), an intra-application task scheduler on top of work stealing runtimes that aims to reduce the total energy consumption of parallel applications. It achieves energy savings by guiding scheduling decisions based on per-task energy consumption predictions of different resource configurations. In addition, ERASE is capable of adapting to both given static frequency settings and externally controlled DVFS. Overall, ERASE achieves up to 31% energy savings and improves performance by 44% on average, compared to the state-of-the-art DVFS-based schedulers

A forest simulation approach using weighted Voronoi diagrams. An application to Mediterranean fir Abies pinsapo Boiss stands

Aim of study: a) To present a new version of the forest simulator Vorest, an individual-based spatially explicit model that uses weighted Voronoi diagrams to simulate the natural dynamics of forest stands with closed canopies. b) To apply the model to the current dynamics of a Grazalema pinsapo stand to identify the nature of its competition regime and the stagnation risks it is currently facing.Area of study: Sierra del Pinar de Grazalema (S Spain)Material and methods: Two large plots representative of Grazalema pinsapo stands were used to fit and validate the model (plus 6 accesory plots to increase the availability of mortality data). Two inventories were carried out in 1998 and 2007 producing tree size and location data. We developed a forest simulator based on three submodels: growth, competition and mortality. The model was fitted, evaluated and validated for Grazalema plots. The simulation outputs were used to infer the expected evolution of structural diversity of  forest stands.Main results: Vorest has proved to be a good tool for simulating dynamics of natural closed stands. The application to Grazalema pinsapo stands has allowed assessing the nature of the main processes that are driving its development pathway. We have found that the prevailing size-asymmetric competition dominates the self-thinning process in small-sized trees. At the same time, there is an active tree-size differentiation process.Research highlights:Vorest has proved to be a good tool for simulating natural stands with closed canopies.The Grazalema pinsapo stand under consideration is currently undergoing a natural process of differentiation, avoiding long-term stagnation.Keywords: Vorest; stand dynamics; individual-based forest model; spatially explicit forest model; pinsapo

Interval orders based on weak orders

AbstractOne definition of an interval order is as an order isomorphic to that of a family of nontrivial intervals of a linearly ordered set with [a,b] < [c,d] if b ⩽ c. Fishburn's theorem states that an order is an interval order if and only if it has no four-element restriction isomorphic to the ordered set (shown in Fig. 1) “2 + 2”. We show that an order is isomorphic to a family of nontrivial intervals of a weak order, ordered as above, if and only if it has no restriction to one of the four ordered sets (shown in Fig. 2) “3 + 2”, “2 + N”, a six-element crown or a six-element fence

Low complexity scheduling algorithm for the downlink of distributed antenna systems

In this paper we present a low-complexity user selection algorithm for the downlink of a distributed antenna system (DAS) that achieves an optimum solution for a weighted matching problem. The user selection process is modeled as a linear sum assignment problem (LSAP). The proposed solution consists of two phases. In the first phase, a set of potential users to be scheduled is found by combining two complementary approaches: greedy and minimum-throughput-loss selection. In the second phase, the set of scheduled users is refined by selecting the users that maximize sum throughput. We provide numerical results to confirm the optimality of our user selection algorithm and to compare its performance with existing solutions

Control-data separation architecture for cellular radio access networks: a survey and outlook

Conventional cellular systems are designed to ensure ubiquitous coverage with an always present wireless channel irrespective of the spatial and temporal demand of service. This approach raises several problems due to the tight coupling between network and data access points, as well as the paradigm shift towards data-oriented services, heterogeneous deployments and network densification. A logical separation between control and data planes is seen as a promising solution that could overcome these issues, by providing data services under the umbrella of a coverage layer. This article presents a holistic survey of existing literature on the control-data separation architecture (CDSA) for cellular radio access networks. As a starting point, we discuss the fundamentals, concepts, and general structure of the CDSA. Then, we point out limitations of the conventional architecture in futuristic deployment scenarios. In addition, we present and critically discuss the work that has been done to investigate potential benefits of the CDSA, as well as its technical challenges and enabling technologies. Finally, an overview of standardisation proposals related to this research vision is provided

Asymmetric Certified Robustness via Feature-Convex Neural Networks

Recent works have introduced input-convex neural networks (ICNNs) as learning models with advantageous training, inference, and generalization properties linked to their convex structure. In this paper, we propose a novel feature-convex neural network architecture as the composition of an ICNN with a Lipschitz feature map in order to achieve adversarial robustness. We consider the asymmetric binary classification setting with one "sensitive" class, and for this class we prove deterministic, closed-form, and easily-computable certified robust radii for arbitrary $\ell_p$-norms. We theoretically justify the use of these models by characterizing their decision region geometry, extending the universal approximation theorem for ICNN regression to the classification setting, and proving a lower bound on the probability that such models perfectly fit even unstructured uniformly distributed data in sufficiently high dimensions. Experiments on Malimg malware classification and subsets of MNIST, Fashion-MNIST, and CIFAR-10 datasets show that feature-convex classifiers attain state-of-the-art certified $\ell_1$-radii as well as substantial $\ell_2$- and $\ell_{\infty}$-radii while being far more computationally efficient than any competitive baseline.Comment: 37th Conference on Neural Information Processing Systems (NeurIPS 2023

Boston University Chamber Chorus, Concert Choir, and Time's Arrow, March 2, 2013

This is the concert program of the Boston University Chamber Chorus, Concert Choir, and Time's Arrow performance on Saturday, March 2, 2013 at 8:00 p.m., at Marsh Chapel, 735 Commonwealth Avenue, Boston, Massachusetts. Works performed were Centering by Lyle Davidson, Descriptive Jottings of London by Michael Finnissy, Chorus and Instruments II by Morton Feldman, Two Nocturnes by Salvatore Sciarrino, The Bells of Vineta by Bent Sørensen, O Gracious Light by Howard Helvey, Epitaph for Moonlight by R. Murray Schafer, Seek Him that maketh the seven stars by Jonathan Dove, Malinconia by Salvatore Sciarrino, Ettelijke bange eenden - Several Scared Ducks by Michael Finnissy, Melencolia I by Salvatore Sciarrino, Act Without Words by Earl Kim, Quante isole! from 12 Madrigali by Salvatore Sciarrino, The Lost Feed by Rodney Lister, Vertue by Michael Finnissy, and I Am Really a Very Simple Person by Eve Beglarian. Digitization for Boston University Concert Programs was supported by the Boston University Humanities Library Endowed Fund