930 research outputs found
Distributed fusion of PHD filters via exponential mixture densities
Full text linkIn this paper, we consider the problem of Distributed Multi-sensor Multi-target Tracking (DMMT) for networked fusion systems. Many existing approaches for DMMT use multiple hypothesis tracking and track-to-track fusion. However, there are two difficulties with these approaches. First, the computational costs of these algorithms can scale factorially with the number of hypotheses. Second, consistent optimal fusion, which does not double count information, can only be guaranteed for highly constrained network architectures which largely undermine the benefits of distributed fusion. In this paper, we develop a consistent approach for DMMT by combining a generalized version of Covariance Intersection, based on Exponential Mixture Densities (EMDs), with Random Finite Sets (RFS). We first derive explicit formulae for the use of EMDs with RFSs. From this, we develop expressions for the probability hypothesis density filters. This approach supports DMMT in arbitrary network topologies through local communications and computations. We implement this approach using Sequential Monte Carlo techniques and demonstrate its performance in simulations
Fusion of finite set distributions : pointwise consistency and global cardinality
Full text linkA recent trend in distributed multi-sensor fusion is to use random finite set filters at the sensor nodes and fuse the filtered distributions algorithmically using their exponential mixture densities (EMDs). Fusion algorithms which extend the celebrated covariance intersection and consensus based approaches are such examples. In this article, we analyse the variational principle underlying EMDs and show that the EMDs of finite set distributions do not necessarily lead to consistent fusion of cardinality distributions. Indeed, we demonstrate that these inconsistencies may occur with overwhelming probability in practice, through examples with Bernoulli, Poisson and independent identically distributed (IID) cluster processes. We prove that pointwise consistency of EMDs does not imply consistency in global cardinality and vice versa. Then, we redefine the variational problems underlying fusion and provide iterative solutions thereby establishing a framework that guarantees cardinality consistent fusion
The Fairy as Hero(ine) and Author: Representations of Female Power in Murat\u27s Le Turbot
No full textHenriette-Julie de Castelnau de Murat\u27s Le Turbot (1699) is remarkable because its fairy Turbodine is both the tale\u27s true hero and heroine and its author, a character both devel- oping the plot—her own and others\u27—and narrating it. Turbodine is the protagonist, and her heroic male power, integral to her authorship of the plot, is both highlighted and disguised by the text. Her power and its limitations are representative of the simultaneous influence and marginality of the woman writer of 1690s France
A Cooperative Approach to Sensor Localisation in Distributed Fusion Networks
Full text linkWe consider self-localisation of networked sensor platforms, which are located disparately and collect cluttered and noisy measurements from an unknown number of objects (or, targets). These nodes perform local filtering of their measurements and exchange posterior densities of object states over the network to improve upon their myopic performance. Sensor locations need to be known, however, in order to register the incoming information in a common coordinate frame for fusion. In this work, we are interested in scenarios in which these locations need to be estimated solely based on the multi-object scene. We propose a cooperative scheme which features nodes using only the information they already receive for distributed fusion: we first introduce node-wise separable parameter likelihoods for sensor pairs, which are recursively updated using the incoming multi-object information and the local measurements. Second, we establish a network coordinate system through a pairwise Markov random field model which has the introduced likelihoods as its edge potentials. The resulting algorithm consists of consecutive edge potential updates and Belief Propagation message passing operations. These potentials are capable of incorporating multi-object information without the need to find explicit object-measurement associations and updated in linear complexity with the number of measurements. We demonstrate the efficacy of our algorithm through simulations with multiple objects and complex measurement models
Zorunlu müdafiin hükmü temyiz etme yükümlülüğü ve görevi kötüye kullanma suçu
No full textBalcı, Murat (Dogus Author)Türkiye, Avrupa Birliğine uyum süreci çerçevesinde, ceza hukuku mevzuatında birçok alanda değişikliğe gitmiştir. Bu kapsamda insan hak ve özgürlerinin korunması bakımından önemli düzenlemelerden olan 5271 Sayılı Ceza Muhakemesi Kanun da değiştirilmiştir
Plein / Nur Syafiqah Murat
Full text linkThis report is about doing entrepreneurship using social media platform. In this task, the author is given to promote her products using a Facebook page for her online marketing campaign. The author chooses food and beverages as her business category and the name of her company is PLEIN and Sdn.Bhd. as her type of business. She chooses to sell bread and desserts as product selling.
Here in this report, contains Go-Ecommerce registration for her to register every detail of her business including her business official Facebook page with its URL. In PLEIN official Facebook page consists of 7 teasers, 16 copywriting of hard sell and 16 copywriting of soft sell with some graphics to make the content more interesting. This report also mentions the organizational chart, business mission, its descriptions of products and services and the price list of every category of the food
Liminal Minorities: Religious Difference and Mass Violence in Muslim Societies
No full textThis supplementary document to Liminal Minorities includes two appendixes created by the author, Günes Murat Tezcür: Table AO.1 List of In-Depth Interviews and Table AO.2 Variables used in Models about Discrimination against Religious Minorities
Block Sparse Bayesian Learning with Applications to Spectral Unmixing for Plasma Optical Emission Spectra
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