1,226 research outputs found

    A Proximity based Retransmission Scheme for Power Line Ad-hoc LAN

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    Power line as an alternative for data transmission is being explored, and also being used to a certain extent. But from the data transfer point of view, power line, as a channel is highly dynamic and hence not quite suitable. To convert the office or home wiring system to a Local Area Network (LAN), adaptive changes are to be made to the existing protocols. In this paper, a slotted transmission scheme is suggested, in which usable timeslots are found out by physically sensing the media. Common usable timeslots for the sender-receiver pair are used for communication. But these will not ensure safe packet delivery since packets may be corrupted on the way during propagation from sender to receiver. Therefore, we also suggest a proximity based retransmission scheme where each machine in the LAN, buffers good packet and machines close to the receiver retransmit on receiving a NACK.Comment: Already published in IJDP

    Event-Object Reasoning with Curated Knowledge Bases: Deriving Missing Information

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    The broader goal of our research is to formulate answers to why and how questions with respect to knowledge bases, such as AURA. One issue we face when reasoning with many available knowledge bases is that at times needed information is missing. Examples of this include partially missing information about next sub-event, first sub-event, last sub-event, result of an event, input to an event, destination of an event, and raw material involved in an event. In many cases one can recover part of the missing knowledge through reasoning. In this paper we give a formal definition about how such missing information can be recovered and then give an ASP implementation of it. We then discuss the implication of this with respect to answering why and how questions.Comment: 13 page

    Encoding Higher Level Extensions of Petri Nets in Answer Set Programming

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    Answering realistic questions about biological systems and pathways similar to the ones used by text books to test understanding of students about biological systems is one of our long term research goals. Often these questions require simulation based reasoning. To answer such questions, we need formalisms to build pathway models, add extensions, simulate, and reason with them. We chose Petri Nets and Answer Set Programming (ASP) as suitable formalisms, since Petri Net models are similar to biological pathway diagrams; and ASP provides easy extension and strong reasoning abilities. We found that certain aspects of biological pathways, such as locations and substance types, cannot be represented succinctly using regular Petri Nets. As a result, we need higher level constructs like colored tokens. In this paper, we show how Petri Nets with colored tokens can be encoded in ASP in an intuitive manner, how additional Petri Net extensions can be added by making small code changes, and how this work furthers our long term research goals. Our approach can be adapted to other domains with similar modeling needs

    Explicit Reasoning over End-to-End Neural Architectures for Visual Question Answering

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    Many vision and language tasks require commonsense reasoning beyond data-driven image and natural language processing. Here we adopt Visual Question Answering (VQA) as an example task, where a system is expected to answer a question in natural language about an image. Current state-of-the-art systems attempted to solve the task using deep neural architectures and achieved promising performance. However, the resulting systems are generally opaque and they struggle in understanding questions for which extra knowledge is required. In this paper, we present an explicit reasoning layer on top of a set of penultimate neural network based systems. The reasoning layer enables reasoning and answering questions where additional knowledge is required, and at the same time provides an interpretable interface to the end users. Specifically, the reasoning layer adopts a Probabilistic Soft Logic (PSL) based engine to reason over a basket of inputs: visual relations, the semantic parse of the question, and background ontological knowledge from word2vec and ConceptNet. Experimental analysis of the answers and the key evidential predicates generated on the VQA dataset validate our approach.Comment: 9 pages, 3 figures, AAAI 201

    Preon Model and Family Replicated E_6 Unification

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    Previously we suggested a new preon model of composite quark-leptons and bosons with the 'flipped' E6Γ—E6~E_6\times \widetilde{E_6} gauge symmetry group. We assumed that preons are dyons having both hyper-electric gg and hyper-magnetic g~\tilde g charges, and these preons-dyons are confined by hyper-magnetic strings which are an N=1{\bf N}=1 supersymmetric non-Abelian flux tubes created by the condensation of spreons near the Planck scale. In the present paper we show that the existence of the three types of strings with tensions Tk=kT0T_k=k T_0 (k=1,2,3)(k = 1,2,3) producing three (and only three) generations of composite quark-leptons, also provides three generations of composite gauge bosons ('hyper-gluons') and, as a consequence, predicts the family replicated [E6]3[E_6]^3 unification at the scale ∼1017\sim 10^{17} GeV. This group of unification has the possibility of breaking to the group of symmetry: [SU(3)C]3Γ—[SU(2)L]3Γ—[U(1)Y]3Γ—[U(1)(Bβˆ’L)]3 [SU(3)_C]^3\times [SU(2)_L]^3\times [U(1)_Y]^3 \times [U(1)_{(B-L)}]^3 which undergoes the breakdown to the Standard Model at lower energies. Some predictive advantages of the family replicated gauge groups of symmetry are briefly discussed.Comment: This is a contribution to the Proc. of the Seventh International Conference ''Symmetry in Nonlinear Mathematical Physics'' (June 24-30, 2007, Kyiv, Ukraine), published in SIGMA (Symmetry, Integrability and Geometry: Methods and Applications) at http://www.emis.de/journals/SIGMA
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