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Finite element analysis was used to predict the thermal cycle fatigue life of flip chip solder joints. Three different data sets of measured thermal cycle fatigue life were simulated to assess model correlation. Variables in the measured data included solder resist opening diameter, UBM diameter, joint height, solder volume, underfill material, package structure, and temperature range. Viscoplastic...
In recent years, there have been a great interest for combined analysis of functional magnetic resonance imaging (fMRI) and structural MRI (sMRI) data, because they present complementary information of different tissue types. Canonical correlation analysis (CCA) is a simple data fusion scheme to evaluate brain connectivity. We specify the versatility of CCA to extract features of resting state fMRI...
In this paper, a beamforming and cell searching method is proposed for a mobile station (MS) with antenna array to compensate the high attenuation in a millimeter wave (mm-wave) OFDM-based cellular systems. A cell searching and direction-of-arrival (DoA) estimation method is proposed for a multipath environment, even with the existence of the symbol timing offsets (STOs) and carrier frequency offsets...
Data center power optimization has recently received a great deal of research attention. For example, server consolidation has been demonstrated as one of the most effective energy saving methodologies. Likewise, traffic consolidation has also been recently proposed to save energy for data center networks (DCNs). However, current research on data center power optimization focuses on servers and DCN...
In this paper, we study the problem of hedging a basket credit derivatives, in particular, we are interested in basket default swaps. For the pricing of credit derivatives, we consider a factor Copula approach. Single-name credit default swaps will be chosen as the hedging instruments. The hedging mechanism is tested using simulated data with a given measure. Numerical results reveal the efficiency...
Virtual Probe (VP), proposed for characterization of spatial variations and for test time reduction, can effectively reconstruct the spatial pattern of a test item for an entire wafer using measurement values from only a small fraction of dies on the wafer. However, VP calculates the spatial signature of each test item separately, one item at a time, resulting in very long runtime for complex chips...
We demonstrate the measurement of photon-pair joint spectral correlations in optical fiber through stimulated four-wave mixing. This method enables us to study correlations more easily, precisely and quickly than with traditional coincidence counting measurements.
Accurate prediction of received signal strength is pivotal to reliable wireless communications. Unfortunately, wireless signals are often subject to random attenuation due to the environment around the receivers. One of the degradation factors that contributes to such loss is shadowing loss. It is well known that the shadowing losses of two nearby radio links are correlated. In this paper, we study...
In this paper, we consider the problem of correlated data gathering in M2M (machine-to-machine) wireless networks with a large number of machines. Since machines communicate directly with the aggregator, the limited radio resources at the aggregator become the bottleneck for supporting all machines. Unlike related work that employs distributed source coding for minimizing resource usage, we assume...
In this paper, we present a system to learn manipulation motion primitives from human demonstration. This system, based on the statistical model “Mimesis Model”, provides an easy-to-use human-interface for learning manipulation motion primitives, as well as a natural language interface allowing human to modify and instruct robot motions. The human-demonstrated manipulation motion primitives are initially...
We consider an extended wireless network, in which nodes arrive in the network according to a joint spatio-temporal (possibly non-homogenous) Poisson process. We assume that each node remains active for a random duration of time with a certain distribution, independent of the arrival process. During the activity period, each node transmits a signal from a Gaussian alphabet at a fixed power (variance)...
Critical node detection in dynamic networks is of great value in many areas, such as the evolving of friendship in social networks, the development of epidemics, molecular pathogenesis of diseases and so on. As for detecting critical nodes in dynamic Protein-Protein Interaction Networks (PPINs), there are mainly two challenges: the first is to construct the dynamic PPINs that are not available directly...
This paper considers energy efficient distributed data gathering methods for correlated data field monitoring in multi-hop wireless sensor networks (WSNs) via compressed sensing (CS). This signal compression and acquisition method can be used to exploit the inherent temporal and spatial correlation of the sensor signals. Many existing CS-based data gathering methods exploit correlation structures...
This paper investigates the problem of cross-modal retrieval, where users can search results across various modalities by submitting any modality of query. Since the query and its retrieved results can be of different modalities, how to measure the content similarity between different modalities of data remains a challenge. To address this problem, we propose a joint graph regularized multi-modal...
We present a survey of recent research works on multiview image compression and transmission techniques developed for Wireless Multimedia Sensor Networks (WMSNs). We classify them into two categories with respect to the coding methods adopted: (i) in-network processing with joint coding schemes, and (ii) distributed source coding schemes. The survey also includes a comprehensive evaluation of the...
We focus on the privacy-accuracy tradeoff encountered by a user who wishes to release some data to an analyst, that is correlated with his private data, in the hope of receiving some utility. We rely on a general statistical inference framework, under which data is distorted before its release, according to a probabilistic privacy mechanism designed under utility constraints. Using recent results...
Lower bounds for the average probability of error of estimating a hidden variable X given an observation of a correlated random variable Y, and Fano's inequality in particular, play a central role in information theory. In this paper, we present a lower bound for the average estimation error based on the marginal distribution of X and the principal inertias of the joint distribution matrix of X and...
This paper addresses the problem of developing an efficient compression scheme with high quality and low computational complexity for ECG signal compression. Taking into account the joint sparsity existing in ECG data and the temporal dependencies in ECG signal sequence, a novel scheme for JSM-2 based ECG compression is developed to exploit these characteristics. We first predict support information...
We propose a novel joint decoding technique for distributed source-channel (DSC) coded systems for transmission of correlated binary Markov sources over additive white Gaussian noise (AWGN) channels. In the proposed scheme, relatively short-length, low-density parity-check (LDPC) codes are independently used to encode the bit sequences of each source. To reconstruct the original bit sequence, a joint...
Recognising and understanding the activities performed by people is a fundamental research topic in developing a wi de range of applications that would be societally beneficial. In this article, we present and discuss two research projects on human action recognition based on computer vision techniques. We also report an ongoing research project that focuses on learning human activities through low...
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