Using Sensor Metadata Streams to Identify Topics of Local Events in the City

In this paper, we study the emerging Information Retrieval (IR) task of local event retrieval using sensor metadata streams. Sensor metadata streams include information such as the crowd density from video processing, audio classifications, and social media activity. We propose to use these metadata streams to identify the topics of local events within a city, where each event topic corresponds to a set of terms representing a type of events such as a concert or a protest. We develop a supervised approach that is capable of mapping sensor metadata observations to an event topic. In addition to using a variety of sensor metadata observations about the current status of the environment as learning features, our approach incorporates additional background features to model cyclic event patterns. Through experimentation with data collected from two locations in a major Spanish city, we show that our approach markedly outperforms an alternative baseline. We also show that modelling background information improves event topic identification

CentralNet: a Multilayer Approach for Multimodal Fusion

This paper proposes a novel multimodal fusion approach, aiming to produce best possible decisions by integrating information coming from multiple media. While most of the past multimodal approaches either work by projecting the features of different modalities into the same space, or by coordinating the representations of each modality through the use of constraints, our approach borrows from both visions. More specifically, assuming each modality can be processed by a separated deep convolutional network, allowing to take decisions independently from each modality, we introduce a central network linking the modality specific networks. This central network not only provides a common feature embedding but also regularizes the modality specific networks through the use of multi-task learning. The proposed approach is validated on 4 different computer vision tasks on which it consistently improves the accuracy of existing multimodal fusion approaches

Investigating non-classical correlations between decision fused multi-modal documents

Correlation has been widely used to facilitate various information retrieval methods such as query expansion, relevance feedback, document clustering, and multi-modal fusion. Especially, correlation and independence are important issues when fusing different modalities that influence a multi-modal information retrieval process. The basic idea of correlation is that an observable can help predict or enhance another observable. In quantum mechanics, quantum correlation, called entanglement, is a sort of correlation between the observables measured in atomic-size particles when these particles are not necessarily collected in ensembles. In this paper, we examine a multimodal fusion scenario that might be similar to that encountered in physics by firstly measuring two observables (i.e., text-based relevance and image-based relevance) of a multi-modal document without counting on an ensemble of multi-modal documents already labeled in terms of these two variables. Then, we investigate the existence of non-classical correlations between pairs of multi-modal documents. Despite there are some basic differences between entanglement and classical correlation encountered in the macroscopic world, we investigate the existence of this kind of non-classical correlation through the Bell inequality violation. Here, we experimentally test several novel association methods in a small-scale experiment. However, in the current experiment we did not find any violation of the Bell inequality. Finally, we present a series of interesting discussions, which may provide theoretical and empirical insights and inspirations for future development of this direction

Phasor Analysis of Pulse Tube Refrigerator

Presented at the 16th International Cryocooler Conference, held May 17-20, 2008 in Atlanta, Georgia.A phasor diagram for a pulse tube refrigerator (PTR) is a vectorial representation of mass flow rate, pressure, and temperature at different locations as a function of time. With the help of a phasor diagram, the operation of different types of pulse tube refrigerators can be well understood. Phasor analysis based on these diagrams gives an idea regarding the underlying complex phenomena of the PTR. In the present work, a simplified model has been presented based on the assumption that there is no phase difference between temperature and pressure throughout the working space. The phasor analysis is extended to a two-stage Orifice Pulse Tube Refrigerator (OPTR) and to a Double Inlet PTR (DIPTR). The important contribution of the work is that it highlights the condition for which the DIPTR will work better than the OPTR

Theoretical and Experimental Investigation of Flow Straighteners in U-type Pulse Tube Cryocoolers

Presented at the 16th International Cryocooler Conference, held May 17-20, 2008 in Atlanta, Georgia.The U-type Pulse Tube Cryocooler (PTC) involves a change in the direction of gas flow as it proceeds from the regenerator to the pulse tube. The sharp U-bend has an adverse effect on pulse tube cooling action due to formation of eddies and undesirable mixing in the cold end of the pulse tube. The present work deals with experimentation and CFD modeling related to U-type PTCs. Two cases of ‘U’ bends have been studied; gradual ‘U’ bends and sharp ‘U’ bends. Experimentation has been carried out using copper screens of 100-mesh size as flow straighteners. The optimum performance in terms of low temperature for the case of a gradual U bend was achieved with a stack of 18 flow-straightener screens. The no-load temperature for this case of a gradual ‘U’ bend, with and without flow straighteners, was 57.7 K and 88.8 K, respectively, for a charging pressure of 16 bar. When the gradual 180 degree bend at the cold end was replaced by a sharp U bend, the no load temperature increased from 88.8 K to 137 K without flow straighteners. In order to understand the role of flow straighteners in PTC, a CFD model was developed in FLUENT. The flow straighteners are modeled as a homogeneous porous medium. The results show that the flow straighteners significantly affect velocity patterns in the pulse tube. The theoretical study showed that there exists an optimum number of flow straighteners which improve the cooling power and efficiency of the pulse tube cryocooler. This was in agreement with the experimental results obtained earlier