265 research outputs found
Gesture tracking and neural activity segmentation in head-fixed behaving mice by deep learning methods
The typical approach used by neuroscientists is to study the response of laboratory animals to a stimulus while recording their neural activity at the same time. With the advent of calcium imaging technology, researchers can now study neural activity at sub-cellular resolutions in vivo. Similarly, recording the behaviour of laboratory animals is also becoming more affordable. Although it is now easier to record behavioural and neural data, this data comes with its own set of challenges. The biggest challenge, given the sheer volume of the data, is annotation. A traditional approach is to annotate the data manually, frame by frame. With behavioural data, manual annotation is done by looking at each frame and tracing the animals; with neural data, this is carried out by a trained neuroscientist. In this research, we propose automated tools based on deep learning that can aid in the processing of behavioural and neural data. These tools will help neuroscientists annotate and analyse the data they acquire in an automated and reliable way.La configuración tÃpica empleada por los neurocientÃficos consiste en estudiar la respuesta de los animales de laboratorio a un estÃmulo y registrar al mismo tiempo su actividad neuronal. Con la llegada de la tecnologÃa de imágenes del calcio, los investigadores pueden ahora estudiar la actividad neuronal a resoluciones subcelulares in vivo. Del mismo modo, el registro del comportamiento de los animales de laboratorio también se está volviendo más asequible. Aunque ahora es más fácil registrar los datos del comportamiento y los datos neuronales, estos datos ofrecen su propio conjunto de desafÃos. El mayor desafÃo es la anotación de los datos debido a su gran volumen. Un enfoque tradicional es anotar los datos manualmente, fotograma a fotograma. En el caso de los datos sobre el comportamiento, la anotación manual se hace mirando cada fotograma y rastreando los animales, mientras que, para los datos neuronales, la anotación la hace un neurocientÃfico capacitado. En esta investigación, proponemos herramientas automatizadas basadas en el aprendizaje profundo que pueden ayudar a procesar los datos de comportamiento y los datos neuronales.La configuració tÃpica emprada pels neurocientÃfics consisteix a estudiar la resposta dels animals de laboratori a un estÃmul i registrar al mateix temps la seva activitat neuronal. Amb l'arribada de la tecnologia d'imatges basades en calci, els investigadors poden ara estudiar l'activitat neuronal a resolucions subcel·lulars in vivo. De la mateixa manera, el registre del comportament dels animals de laboratori també ha esdevingut molt més assequible. Tot i que ara és més fà cil registrar les dades del comportament i les dades neuronals, aquestes dades ofereixen el seu propi conjunt de reptes. El major desafiament és l'anotació de les dades, degut al seu gran volum. Un enfocament tradicional és anotar les dades manualment, fotograma a fotograma. En el cas de les dades sobre el comportament, l'anotació manual es fa mirant cada fotograma i rastrejant els animals, mentre que per a les dades neuronals, l'anotació la fa un neurocientÃfic capacitat. En aquesta investigació, proposem eines automatitzades basades en laprenentatge profund que poden ajudar a modelar les dades de comportament i les dades neuronals
Guarding Networks Through Heterogeneous Mobile Guards
In this article, the issue of guarding multi-agent systems against a sequence
of intruder attacks through mobile heterogeneous guards (guards with different
ranges) is discussed. The article makes use of graph theoretic abstractions of
such systems in which agents are the nodes of a graph and edges represent
interconnections between agents. Guards represent specialized mobile agents on
specific nodes with capabilities to successfully detect and respond to an
attack within their guarding range. Using this abstraction, the article
addresses the problem in the context of eternal security problem in graphs.
Eternal security refers to securing all the nodes in a graph against an
infinite sequence of intruder attacks by a certain minimum number of guards.
This paper makes use of heterogeneous guards and addresses all the components
of the eternal security problem including the number of guards, their
deployment and movement strategies. In the proposed solution, a graph is
decomposed into clusters and a guard with appropriate range is then assigned to
each cluster. These guards ensure that all nodes within their corresponding
cluster are being protected at all times, thereby achieving the eternal
security in the graph.Comment: American Control Conference, Chicago, IL, 201
A Tight Lower Bound on the Controllability of Networks with Multiple Leaders
In this paper we study the controllability of networked systems with static
network topologies using tools from algebraic graph theory. Each agent in the
network acts in a decentralized fashion by updating its state in accordance
with a nearest-neighbor averaging rule, known as the consensus dynamics. In
order to control the system, external control inputs are injected into the so
called leader nodes, and the influence is propagated throughout the network.
Our main result is a tight topological lower bound on the rank of the
controllability matrix for such systems with arbitrary network topologies and
possibly multiple leaders
Impact of Learning & Market Orientation on Business Performance & Innovation: The Mediating Role of Business Resilience & CRM effectiveness
This study discussed the mediating role of business resilience and customer relationship management effectiveness (CRMe) in the context of learning and market orientation, business innovation and business performance. Structural Equation Modelling was used to test the model with a sample size of 390 respondents from tourism ministry, travel agencies and hotels. The outcome of the study confirms that business resilience and customer relationship management effectiveness significantly mediates the relationship resulting into enhanced business performance and innovation. Keywords: Learning and Market Orientation, Business Resilience, CRM Effectiveness, Innovation & Business Performanc
Anomalous origin of left coronary artery : an unusual case
Anomalies of the coronary arteries are rare but are an important cause of sudden cardiac arrest in young athletes. Sudden cardiac arrest has been reported in patients with congenital anomalies of the coronary arteries. We present a rare case of sudden cardiac arrest caused by anomalous left main coronary artery originating high from the posterior aspect of left sinus of Valsalva with intramural retroaortic segment, associated with bicuspid aortic valve.peer-reviewe
Sensor placement for fault location identification in water networks: A minimum test cover approach
This paper focuses on the optimal sensor placement problem for the
identification of pipe failure locations in large-scale urban water systems.
The problem involves selecting the minimum number of sensors such that every
pipe failure can be uniquely localized. This problem can be viewed as a minimum
test cover (MTC) problem, which is NP-hard. We consider two approaches to
obtain approximate solutions to this problem. In the first approach, we
transform the MTC problem to a minimum set cover (MSC) problem and use the
greedy algorithm that exploits the submodularity property of the MSC problem to
compute the solution to the MTC problem. In the second approach, we develop a
new \textit{augmented greedy} algorithm for solving the MTC problem. This
approach does not require the transformation of the MTC to MSC. Our augmented
greedy algorithm provides in a significant computational improvement while
guaranteeing the same approximation ratio as the first approach. We propose
several metrics to evaluate the performance of the sensor placement designs.
Finally, we present detailed computational experiments for a number of real
water distribution networks
Deploying robots with two sensors in -free graphs
Let be a graph of minimum degree at least two with no induced subgraph
isomorphic to . We prove that if is not isomorphic to one of eight
exceptional graphs, then it is possible to assign two-element subsets of
to the vertices of in such a way that for every
and every vertex the label is assigned to
or one of its neighbors. It follows that has fractional domatic number
at least . This is motivated by a problem in robotics and generalizes a
result of Fujita, Yamashita and Kameda who proved that the same conclusion
holds for all -regular graphs
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