Device-free Passive (DfP) localization is a system envisioned to detect, track, and identify entities that do not carry any device, nor participate actively in the localization process. A DfP system allows using nominal WiFi equipment for intrusion detection, without using any extra hardware, adding smartness to any WiFi-enabled device. In this paper, we focus on the detection function of the DfP

Subsequent duplication events are responsible for the evolution of the minisatellite maps. Alignment of two minisatellite maps should therefore take these duplication events into account, in addition to the well-known edit operations. All algorithms for computing an optimal alignment of two maps, including the one presented here, first deduce the costs of optimal duplication scenarios for all

In this paper we investigate admission control and power allocation for cognitive radios in an underlay network. We consider the problem of maximizing the number of supported secondary links under their minimum QoS requirements without violating the maximum tolerable interference on primary receivers in a cellular network. An optimal solution to our problem is shown in previous works to be NP-hard

A new method is proposed for the blind subspace-based identification of the coefficients of time-varying (TV) single-input multiple-output (SIMO) FIR channels. The TV channel coefficients are represented via a finite basis expansion model, i.e. linear combination of known basis functions. In contrast to earlier related works, the basis functions need not be limited to complex exponentials, and

Device-free Passive (DfP) localization is a new concept in location determination where the tracked entity does not carry any device nor participate actively in the localization process. A DfP system operates by processing the received physical signal of a wireless transmitter at one or more monitoring points. The previously introduced DfP system was shown to enable the tracking of a single

In this paper we propose distributed storage algorithms for large-scale wireless sensor networks. Assume a wireless sensor network with n nodes that have limited power, memory, and bandwidth. Each node is capable of both sensing and storing data. Such sensor nodes might disappear from the network due to failures or battery depletion. Hence it is desired to design efficient schemes to collect data

An efficient fat suppression method is presented for MR tagging with complementary spatial modulation of magnetization (CSPAMM). In this method, the complementary modulation is applied to the water content of the tissues, while in-phase modulation is applied to the fat content. Therefore, during image reconstruction, the subtraction of the acquired images increases the tagging contrast of the

In this study, we propose a novel data acquisition and image reconstruction method for parallel magnetic resonance imaging (MRI). The proposed method improves the GRAPPA algorithm by simultaneously collecting data using the body coil in addition to localized surface coils. The body coil data is included in the GRAPPA reconstruction as an additional coil. The reconstructed body coil image shows

In this paper an approach is proposed to develop a computer-aided diagnosis (CAD) system that can be very helpful for radiologist in diagnosing microcalcifications' patterns in digitized mammograms earlier and faster than typical screening programs and showed the efficiency of feature selection on the CAD system. The proposed method has been implemented in four stages: (a) the region of interest

We propose a model that describes the interaction of several Brain Regions based on Functional Magnetic Resonance Imaging (FMRI) time series to make inferences about functional integration and segregation within the human brain. The method is demonstrated using dynamic causal modeling (OeM) using real data to show how such models are able to characterize interregional dependence. We extend