Leader election in SINR model with arbitrary power control

Post-print (lokagerð höfundar)We consider the Leader Election Problem in the Signal-to-Interference-plusNoise-Ratio (SINR) model where nodes can adjust their transmission power. We show that in this setting it is possible to elect a leader in two communication rounds, with high probability. Previously, it was known that Θ(log n) rounds were sufficient and necessary when using uniform power, where n is the number of nodes in the network. We then examine how much power control is needed to achieve fast leader election. We show that every 2-round leader election algorithm in the SINR model running correctly w.h.p. requires a power range 2Ω(n) , even when n is known. We complement this with an algorithm that uses power range 2O˜(n)1, when n is known, and 2O˜(n 1.5 ) , when n is not known. We also explore tradeoffs between time and power used, and show that to elect a leader in t rounds, a range of possible power levels of size exp(n 1/Θ(t) ) is sufficient and necessaryThis work was funded by Icelandic Research Fund grants 152679-05, 174484-05, AFOSR FA9550-13-1-0042, NSF CCF-1461559 and NSF CCF-0939370."Peer Reviewed

Pruning Algorithms for Low-Dimensional Non-metric k-NN Search: A Case Study

We focus on low-dimensional non-metric search, where tree-based approaches permit efficient and accurate retrieval while having short indexing time. These methods rely on space partitioning and require a pruning rule to avoid visiting unpromising parts. We consider two known data-driven approaches to extend these rules to non-metric spaces: TriGen and a piece-wise linear approximation of the pruning rule. We propose and evaluate two adaptations of TriGen to non-symmetric similarities (TriGen does not support non-symmetric distances). We also evaluate a hybrid of TriGen and the piece-wise linear approximation pruning. We find that this hybrid approach is often more effective than either of the pruning rules. We make our software publicly available

A Platform for Processing Expression of Short Time Series (PESTS)

<p>Abstract</p> <p>Background</p> <p>Time course microarray profiles examine the expression of genes over a time domain. They are necessary in order to determine the complete set of genes that are dynamically expressed under given conditions, and to determine the interaction between these genes. Because of cost and resource issues, most time series datasets contain less than 9 points and there are few tools available geared towards the analysis of this type of data.</p> <p>Results</p> <p>To this end, we introduce a platform for Processing Expression of Short Time Series (PESTS). It was designed with a focus on usability and interpretability of analyses for the researcher. As such, it implements several standard techniques for comparability as well as visualization functions. However, it is designed specifically for the unique methods we have developed for significance analysis, multiple test correction and clustering of short time series data. The central tenet of these methods is the use of biologically relevant features for analysis. Features summarize short gene expression profiles, inherently incorporate dependence across time, and allow for both full description of the examined curve and missing data points.</p> <p>Conclusions</p> <p>PESTS is fully generalizable to other types of time series analyses. PESTS implements novel methods as well as several standard techniques for comparability and visualization functions. These features and functionality make PESTS a valuable resource for a researcher's toolkit. PESTS is available to download for free to academic and non-profit users at <url>http://www.mailman.columbia.edu/academic-departments/biostatistics/research-service/software-development</url>.</p

Time-series clustering of gene expression in irradiated and bystander fibroblasts: an application of FBPA clustering

<p>Abstract</p> <p>Background</p> <p>The radiation bystander effect is an important component of the overall biological response of tissues and organisms to ionizing radiation, but the signaling mechanisms between irradiated and non-irradiated bystander cells are not fully understood. In this study, we measured a time-series of gene expression after α-particle irradiation and applied the Feature Based Partitioning around medoids Algorithm (FBPA), a new clustering method suitable for sparse time series, to identify signaling modules that act in concert in the response to direct irradiation and bystander signaling. We compared our results with those of an alternate clustering method, Short Time series Expression Miner (STEM).</p> <p>Results</p> <p>While computational evaluations of both clustering results were similar, FBPA provided more biological insight. After irradiation, gene clusters were enriched for signal transduction, cell cycle/cell death and inflammation/immunity processes; but only FBPA separated clusters by function. In bystanders, gene clusters were enriched for cell communication/motility, signal transduction and inflammation processes; but biological functions did not separate as clearly with either clustering method as they did in irradiated samples. Network analysis confirmed p53 and NF-κB transcription factor-regulated gene clusters in irradiated and bystander cells and suggested novel regulators, such as KDM5B/JARID1B (lysine (K)-specific demethylase 5B) and HDACs (histone deacetylases), which could epigenetically coordinate gene expression after irradiation.</p> <p>Conclusions</p> <p>In this study, we have shown that a new time series clustering method, FBPA, can provide new leads to the mechanisms regulating the dynamic cellular response to radiation. The findings implicate epigenetic control of gene expression in addition to transcription factor networks.</p

Knowledge production in the information and communication technology sector in Greece

This paper examines knowledge production in the ICT sector in Greece based on patent grants and its relative weight in the international production of knowledge during the period 1988-2010. The Information and Communication Technology (ICT) sector has become a key element in the new knowledge economy. Its technologies are very pervasive and underpin growth in all sectors of the economy. In the EU, the USA, and Japan, the ICT sector is by far the largest R&amp;D-investing sector of the economy. In 2007, while the ICT sector represented 4.8% of GDP and 3% of total employment in the EU, it accounted for 25% of overall business expenditure in R&amp;D and employed 33% of all business sector researchers. Based on these facts, what has Greece done so far in this domain? This study presents a general overview of knowledge production in the ICT sector in Greece, mainly based on its internal patent activity in this domain. In this context this study, focusing on the technological sub-class level of analysis, presents the technological and economic content of those sub-classes, highlighting this way both important and pervasive ICT technologies and dynamic industrial sectors for the their development. Depending on the results, this analysis could add to the discussion on what Greece needs to do in order to improve its competitiveness at the international level. © Common Ground, Maria Markatou, All Rights Reserved

Greek regions and cities in the knowledge economy: The dominance of large cities and their regions

This paper examines the development of new knowledge and the production of innovation across Greek regions and cities towards the establishment of a knowledge economy. We rely on patent data and we try to bring more light into an area that has been little studied in Greece. Our analysis confirms the theoretical and empirical argument of both concentration and importance of large-urban regions and particular cities. Few Greek large cities and some cities related to the metropolitan area of &apos;Attiki&apos; concentrate most of knowledge creation and innovation production. These regions and cities are also the major economic, industrial and commercial centres, while most of Greeks live there. Our results could be used in the development of both regional policy and management, aiming at strengthening Greek regions and cities and supporting and encouraging knowledge creation and innovation production. Copyright © 2012 Inderscience Enterprises Ltd