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Andrzej Pelc - One of the best experts on this subject based on the ideXlab platform.
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constant length labeling schemes for deterministic Radio Broadcast
ACM Transactions on Parallel Computing, 2021Co-Authors: Faith Ellen, Barun Gorain, Avery Miller, Andrzej PelcAbstract:Broadcast is one of the fundamental network communication primitives. One node of a network, called the source, has a message that has to be learned by all other nodes. We consider Broadcast in Radio networks, modeled as simple undirected connected graphs with a distinguished source. Nodes communicate in synchronous rounds. In each round, a node can either transmit a message to all its neighbours, or stay silent and listen. At the receiving end, a node v hears a message from a neighbour w in a given round if v listens in this round and if w is its only neighbour that transmits in this round. If more than one neighbour of a node v transmits in a given round, we say that a collision occurs at v. We do not assume collision detection: in case of a collision, node v does not hear anything (except the background noise that it also hears when no neighbour transmits). We are interested in the feasibility of deterministic Broadcast in Radio networks. If nodes of the network do not have any labels, deterministic Broadcast is impossible even in the four-cycle. On the other hand, if all nodes have distinct labels, then Broadcast can be carried out, e.g., in a round-robin fashion, and hence O(log n)-bit labels are sufficient for this task in n-node networks. In fact, O(log Δ)-bit labels, where Δ is the maximum degree, are enough to Broadcast successfully. Hence, it is natural to ask if very short labels are sufficient for Broadcast. Our main result is a positive answer to this question. We show that every Radio network can be labeled using 2 bits in such a way that Broadcast can be accomplished by some universal deterministic algorithm that does not know the network topology nor any bound on its size. Moreover, at the expense of an extra bit in the labels, we can get the following additional strong property of our algorithm: there exists a common round in which all nodes know that Broadcast has been completed. Finally, we show that 3-bit labels are also sufficient to solve both versions of Broadcast in the case where it is not known a priori which node is the source.
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constant length labeling schemes for deterministic Radio Broadcast
ACM Symposium on Parallel Algorithms and Architectures, 2019Co-Authors: Faith Ellen, Barun Gorain, Avery Miller, Andrzej PelcAbstract:Broadcast is one of the fundamental network communication primitives. One node of a network, called the source, has a message that has to be learned by all other nodes. We consider Broadcast in Radio networks, modeled as simple undirected connected graphs with a distinguished source. Nodes communicate in synchronous rounds. In each round, a node can either transmit a message to all its neighbours, or stay silent and listen. At the receiving end, a node v hears a message from a neighbour w in a given round if v listens in this round and if w is its only neighbour that transmits in this round. If more than one neighbour of a node v transmits in a given round, we say that a collision occurs at v. We do not assume collision detection: in case of a collision, node v does not hear anything (except the background noise that it also hears when no neighbour transmits). We are interested in the feasibility of deterministic Broadcast in Radio networks. If nodes of the network do not have any labels, deterministic Broadcast is impossible even in the four-cycle. On the other hand, if all nodes have distinct labels, then Broadcast can be carried out, e.g., in a round-robin fashion, and hence O(log n)-bit labels are sufficient for this task in n-node networks. In fact, O(log Δ)-bit labels, where Δ is the maximum degree, are enough to Broadcast successfully. Hence, it is natural to ask if very short labels are sufficient for Broadcast. Our main result is a positive answer to this question. We show that every Radio network can be labeled using 2 bits in such a way that Broadcast can be accomplished by some universal deterministic algorithm that does not know the network topology nor any bound on its size. Moreover, at the expense of an extra bit in the labels, we can get the following additional strong property of our algorithm: there exists a common round in which all nodes know that Broadcast has been completed.
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constant length labeling schemes for deterministic Radio Broadcast
arXiv: Distributed Parallel and Cluster Computing, 2017Co-Authors: Faith Ellen, Barun Gorain, Avery Miller, Andrzej PelcAbstract:Broadcast is one of the fundamental network communication primitives. One node of a network, called the $\mathit{source}$, has a message that has to be learned by all other nodes. We consider the feasibility of deterministic Broadcast in Radio networks. If nodes of the network do not have any labels, deterministic Broadcast is impossible even in the four-cycle. On the other hand, if all nodes have distinct labels, then Broadcast can be carried out, e.g., in a round-robin fashion, and hence $O(\log n)$-bit labels are sufficient for this task in $n$-node networks. In fact, $O(\log \Delta)$-bit labels, where $\Delta$ is the maximum degree, are enough to Broadcast successfully. Hence, it is natural to ask if very short labels are sufficient for Broadcast. Our main result is a positive answer to this question. We show that every Radio network can be labeled using 2 bits in such a way that Broadcast can be accomplished by some universal deterministic algorithm that does not know the network topology nor any bound on its size. Moreover, at the expense of an extra bit in the labels, we get the additional strong property that there exists a common round in which all nodes know that Broadcast has been completed. Finally, we show that 3-bit labels are also sufficient to solve both versions of Broadcast in the case where the labeling scheme does not know which node is the source.
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centralized deterministic Broadcasting in undirected multi hop Radio networks
Untitled Event, 2004Co-Authors: Dariusz R Kowalski, Andrzej PelcAbstract:We consider centralized deterministic Broadcasting in Radio networks. The aim is to design a polynomial algorithm, which, given a graph G, produces a fast Broadcasting scheme in the Radio network represented by G. The problem of finding an optimal Broadcasting scheme for a given graph is NP-hard, hence we can only hope for a good approximation algorithm. We give a deterministic polynomial algorithm which produces a Broadcasting scheme working in time \({\cal O}(D \log n + \log ^2 n)\), for every n-node graph of diameter D. It has been proved recently [15,16] that a better order of magnitude of Broadcasting time is impossible unless \(NP \subseteq BPTIME(n^{{\cal O}(\log \log n)})\). In terms of approximation ratio, we have a \({\cal O}(\log (n/D))\)-approximation algorithm for the Radio Broadcast problem, whenever D=Ω (log n).
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centralized deterministic Broadcasting in undirected multi hop Radio networks
International Workshop and International Workshop on Approximation Randomization and Combinatorial Optimization. Algorithms and Techniques, 2004Co-Authors: Dariusz R Kowalski, Andrzej PelcAbstract:We consider centralized deterministic Broadcasting in Radio networks. The aim is to design a polynomial algorithm, which, given a graph G, produces a fast Broadcasting scheme in the Radio network represented by G. The problem of finding an optimal Broadcasting scheme for a given graph is NP-hard, hence we can only hope for a good approximation algorithm. We give a deterministic polynomial algorithm which produces a Broadcasting scheme working in time O(D log n + log 2 n), for every n-node graph of diameter D. It has been proved recently [15, 16] that a better order of magnitude of Broadcasting time is impossible unless NP C BPTIME(n O(log log n) ). In terms of approximation ratio, we have a O(log(n/D))-approximation algorithm for the Radio Broadcast problem, whenever D = Ω(log n).
Sube Banerjee - One of the best experts on this subject based on the ideXlab platform.
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artificially synthesising data for audio classification and segmentation to improve speech and music detection in Radio Broadcast
International Conference on Acoustics Speech and Signal Processing, 2021Co-Authors: Satvik Venkatesh, David Moffat, Alexis Kirke, Gozel Shakeri, Stephen Brewster, Jorg Fachner, Helen Odellmiller, Alexander J Street, Nicolas Farina, Sube BanerjeeAbstract:Segmenting audio into homogeneous sections such as music and speech helps us understand the content of audio. It is useful as a pre-processing step to index, store, and modify audio recordings, Radio Broadcasts and TV programmes. Deep learning models for segmentation are generally trained on copyrighted material, which cannot be shared. Annotating these datasets is time-consuming and expensive and therefore, it significantly slows down research progress. In this study, we present a novel procedure that artificially synthesises data that resembles Radio signals. We replicate the workflow of a Radio DJ in mixing audio and investigate parameters like fade curves and audio ducking. We trained a Convolutional Recurrent Neural Network (CRNN) on this synthesised data and outperformed state-of-the-art algorithms for music-speech detection. This paper demonstrates the data synthesis procedure as a highly effective technique to generate large datasets to train deep neural networks for audio segmentation.
Faith Ellen - One of the best experts on this subject based on the ideXlab platform.
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constant length labeling schemes for deterministic Radio Broadcast
ACM Transactions on Parallel Computing, 2021Co-Authors: Faith Ellen, Barun Gorain, Avery Miller, Andrzej PelcAbstract:Broadcast is one of the fundamental network communication primitives. One node of a network, called the source, has a message that has to be learned by all other nodes. We consider Broadcast in Radio networks, modeled as simple undirected connected graphs with a distinguished source. Nodes communicate in synchronous rounds. In each round, a node can either transmit a message to all its neighbours, or stay silent and listen. At the receiving end, a node v hears a message from a neighbour w in a given round if v listens in this round and if w is its only neighbour that transmits in this round. If more than one neighbour of a node v transmits in a given round, we say that a collision occurs at v. We do not assume collision detection: in case of a collision, node v does not hear anything (except the background noise that it also hears when no neighbour transmits). We are interested in the feasibility of deterministic Broadcast in Radio networks. If nodes of the network do not have any labels, deterministic Broadcast is impossible even in the four-cycle. On the other hand, if all nodes have distinct labels, then Broadcast can be carried out, e.g., in a round-robin fashion, and hence O(log n)-bit labels are sufficient for this task in n-node networks. In fact, O(log Δ)-bit labels, where Δ is the maximum degree, are enough to Broadcast successfully. Hence, it is natural to ask if very short labels are sufficient for Broadcast. Our main result is a positive answer to this question. We show that every Radio network can be labeled using 2 bits in such a way that Broadcast can be accomplished by some universal deterministic algorithm that does not know the network topology nor any bound on its size. Moreover, at the expense of an extra bit in the labels, we can get the following additional strong property of our algorithm: there exists a common round in which all nodes know that Broadcast has been completed. Finally, we show that 3-bit labels are also sufficient to solve both versions of Broadcast in the case where it is not known a priori which node is the source.
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constant length labelling schemes for faster deterministic Radio Broadcast
ACM Symposium on Parallel Algorithms and Architectures, 2020Co-Authors: Faith Ellen, Seth GilbertAbstract:In this paper, we consider the problem of Broadcast from a specified source node in a known synchronous Radio network. In 2019, Ellen, Gorain, Miller and Plc showed that this is possible if each node in the network only stores 2 (carefully chosen) bits of information. They proved that in an n-node network, their algorithm ensures that the Broadcast completes within 2n-3 rounds. We show that storing only a small constant number of additional bits, it is possible to Broadcast significantly faster when the source eccentricity, D, of the network is o(n). We begin by presenting a modification of Ellen, Gorain, Miller and Pelc's algorithm that stores 4 bits per node and completes within O(√Dn) rounds. Then we define a class of Broadcast algorithms that includes both these algorithms and prove that any algorithm in this class requires Ω(√nD) rounds. Next, we show (non-constructively) that there exists a Broadcast algorithm which stores only 3 bits of information per node, but completes within O(D log n+log2 n) rounds. Finally, using ideas from Chlamtac and Weinstein (1991), we show how to construct the relevant information and do almost as well, giving an algorithm using 3 bits per node that runs in O(D log^2 n) rounds.
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constant length labeling schemes for deterministic Radio Broadcast
ACM Symposium on Parallel Algorithms and Architectures, 2019Co-Authors: Faith Ellen, Barun Gorain, Avery Miller, Andrzej PelcAbstract:Broadcast is one of the fundamental network communication primitives. One node of a network, called the source, has a message that has to be learned by all other nodes. We consider Broadcast in Radio networks, modeled as simple undirected connected graphs with a distinguished source. Nodes communicate in synchronous rounds. In each round, a node can either transmit a message to all its neighbours, or stay silent and listen. At the receiving end, a node v hears a message from a neighbour w in a given round if v listens in this round and if w is its only neighbour that transmits in this round. If more than one neighbour of a node v transmits in a given round, we say that a collision occurs at v. We do not assume collision detection: in case of a collision, node v does not hear anything (except the background noise that it also hears when no neighbour transmits). We are interested in the feasibility of deterministic Broadcast in Radio networks. If nodes of the network do not have any labels, deterministic Broadcast is impossible even in the four-cycle. On the other hand, if all nodes have distinct labels, then Broadcast can be carried out, e.g., in a round-robin fashion, and hence O(log n)-bit labels are sufficient for this task in n-node networks. In fact, O(log Δ)-bit labels, where Δ is the maximum degree, are enough to Broadcast successfully. Hence, it is natural to ask if very short labels are sufficient for Broadcast. Our main result is a positive answer to this question. We show that every Radio network can be labeled using 2 bits in such a way that Broadcast can be accomplished by some universal deterministic algorithm that does not know the network topology nor any bound on its size. Moreover, at the expense of an extra bit in the labels, we can get the following additional strong property of our algorithm: there exists a common round in which all nodes know that Broadcast has been completed.
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constant length labeling schemes for deterministic Radio Broadcast
arXiv: Distributed Parallel and Cluster Computing, 2017Co-Authors: Faith Ellen, Barun Gorain, Avery Miller, Andrzej PelcAbstract:Broadcast is one of the fundamental network communication primitives. One node of a network, called the $\mathit{source}$, has a message that has to be learned by all other nodes. We consider the feasibility of deterministic Broadcast in Radio networks. If nodes of the network do not have any labels, deterministic Broadcast is impossible even in the four-cycle. On the other hand, if all nodes have distinct labels, then Broadcast can be carried out, e.g., in a round-robin fashion, and hence $O(\log n)$-bit labels are sufficient for this task in $n$-node networks. In fact, $O(\log \Delta)$-bit labels, where $\Delta$ is the maximum degree, are enough to Broadcast successfully. Hence, it is natural to ask if very short labels are sufficient for Broadcast. Our main result is a positive answer to this question. We show that every Radio network can be labeled using 2 bits in such a way that Broadcast can be accomplished by some universal deterministic algorithm that does not know the network topology nor any bound on its size. Moreover, at the expense of an extra bit in the labels, we get the additional strong property that there exists a common round in which all nodes know that Broadcast has been completed. Finally, we show that 3-bit labels are also sufficient to solve both versions of Broadcast in the case where the labeling scheme does not know which node is the source.
Joachim Schuz - One of the best experts on this subject based on the ideXlab platform.
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an evaluation of exposure metrics in an epidemiologic study on Radio and television Broadcast transmitters and the risk of childhood leukemia
Bioelectromagnetics, 2009Co-Authors: Sven Schmiedel, Hiltrud Merzenich, Hauke Bruggemeyer, Johannes Philipp, Jost Wendler, Joachim SchuzAbstract:Electric field strength values calculated by wave propagation modeling were applied as an exposure metric in a case–control study conducted in Germany to investigate a possible association between Radio frequency electromagnetic fields (RF-EMF) emitted from television and Radio Broadcast transmitters and the risk of childhood leukemia. To validate this approach it was examined at 850 measurement sites whether calculated RF-EMF are an improvement to an exposure proxy based on distance from the place of residence to a transmitter. Further, the agreement between measured and calculated RF-EMF was explored. For dichotomization at the 90% quantiles of the exposure distributions it was found that distance agreed less with measured RF-EMF (Kappa coefficient: 0.55) than did calculated RF-EMF (Kappa coefficient: 0.74). Distance was a good exposure proxy for a single transmitter only which uses the frequency bands of amplitude modulated Radio, whereas it appeared to be of limited informative value in studies involving several transmitters, particularly if these are operating in different frequency bands. The analysis of the agreement between calculated RF-EMF and measured RF-EMF showed a sensitivity of 76.6% and a specificity of 97.4%, leading to an exposure misclassification that still allows one to detect a true odds ratio as low as 1.4 with a statistical power of >80% at a two-sided significance level of 5% in a study with 2,000 cases and 6,000 controls. Thus, calculated RF-EMF is confirmed to be an appropriate exposure metric in large-scale epidemiological studies on Broadcast transmitters. Bioelectromagnetics 30:81–91, 2009. © 2008 Wiley-Liss, Inc.
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childhood leukemia in relation to Radio frequency electromagnetic fields in the vicinity of tv and Radio Broadcast transmitters
American Journal of Epidemiology, 2008Co-Authors: Hiltrud Merzenich, Sven Schmiedel, Sabrina Bennack, Hauke Bruggemeyer, Johannes Philipp, Maria Blettner, Joachim SchuzAbstract:A case-control study of Radio frequency electromagnetic fields (RF-EMFs) and childhood leukemia was conducted in West Germany. The study region included municipalities near high-power Radio and TV Broadcast towers, including 16 amplitude-modulated and 8 frequency-modulated transmitters. Cases were aged 0–14 years, were diagnosed with leukemia between 1984 and 2003, and were registered at the German Childhood Cancer Registry. Three age-, gender-, and transmitter-area-matched controls per case were drawn randomly from population registries. The analysis included 1,959 cases and 5,848 controls. Individual exposure to RF-EMFs 1 year before diagnosis was estimated with a field strength prediction program. Considering total RF-EMFs, the odds ratio derived from conditional logistic regression analysis for all types of leukemia was 0.86 (95% confidence interval: 0.67, 1.11) when upper (� 95%/0.701 V/m) and lower (<90%/0.504 V/m) quantiles of the RF-EMF distribution were compared. An analysis of amplitude-modulated and frequency-modulated transmitters separately did not show increased risks of leukemia. The odds ratio for all types of leukemia was 1.04 (95% confidence interval: 0.65, 1.67) among children living within 2 km of the nearest Broadcast transmitter compared with those living at a distance of 10–<15 km. The data did not show any elevated risks of childhood leukemia associated with RF-EMFs.
Satvik Venkatesh - One of the best experts on this subject based on the ideXlab platform.
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artificially synthesising data for audio classification and segmentation to improve speech and music detection in Radio Broadcast
International Conference on Acoustics Speech and Signal Processing, 2021Co-Authors: Satvik Venkatesh, David Moffat, Alexis Kirke, Gozel Shakeri, Stephen Brewster, Jorg Fachner, Helen Odellmiller, Alexander J Street, Nicolas Farina, Sube BanerjeeAbstract:Segmenting audio into homogeneous sections such as music and speech helps us understand the content of audio. It is useful as a pre-processing step to index, store, and modify audio recordings, Radio Broadcasts and TV programmes. Deep learning models for segmentation are generally trained on copyrighted material, which cannot be shared. Annotating these datasets is time-consuming and expensive and therefore, it significantly slows down research progress. In this study, we present a novel procedure that artificially synthesises data that resembles Radio signals. We replicate the workflow of a Radio DJ in mixing audio and investigate parameters like fade curves and audio ducking. We trained a Convolutional Recurrent Neural Network (CRNN) on this synthesised data and outperformed state-of-the-art algorithms for music-speech detection. This paper demonstrates the data synthesis procedure as a highly effective technique to generate large datasets to train deep neural networks for audio segmentation.
