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As traditional spectrum sensing approaches unable to deal with the contradiction between detection accuracy and complexity in cognitive radio network, a novel q-weighed sequential cooperative energy detection method for spectrum sensing in time varying channel is proposed in this paper to achieve better performance with lower complexity. By adding the q- weighted log likelihood ratio (LLR) of the...
In this paper, we propose a signal-centric medium access control scheme that simultaneously exploits spatial and temporal correlations among sensing results for machine-to-machine communications. To model sensing results with spatial and temporal correlations, we propose using a vector autoregressive process. To minimize the overall prediction error, we propose using the space- time predictive polling...
This paper presents a cyclic autocorrelation function (CAF) diversity combining technique for spectrum sensing using test statistics shared among multiple receive antennas with time-averaged weights. We recently reported a weighted CAF diversity combining technique, however, the weight factor has a noise component, which negatively affects the performance. This technique reduces the noise component...
Data collection in wireless networked sensing systems (WNSS) is usually not reliable due to sensor faults and/or security attacks. This makes detection of an event (e.g., structural damage) through data aggregation unreliable. In this paper, we propose a trustworthy and protected data collection (TPDC) framework for event detection in WNSS. This framework facilitates reliable data for aggregation...
Time-of-flight (ToF) imaging is an active method that utilizes a temporally modulated light source and a correlation-based (or lock-in) imager that computes the round-trip travel time from source to scene and back. Much like conventional imaging ToF cameras suffer from the trade-off between depth of field (DOF) and light throughput-larger apertures allow for more light collection but results in lower...
Compressed sensing enables the acquisition of sparse signals at a rate that is much lower than the Nyquist rate. Various greedy recovery algorithms have been proposed to achieve a lower computational complexity compared to the optimal ℓ1 minimization, while maintaining a good reconstruction accuracy. We propose a new greedy recovery algorithm for compressed sensing, called the Adaptive Reduced-set...
Covariance sketching has been recently introduced as an effective strategy to reduce the data dimensionality without sacrificing the ability to reconstruct second-order statistics of the data. In this paper, we propose a novel covariance sketching scheme with reduced complexity for spatial-temporal data, whose covariance matrices satisfy the Kronecker product expansion model recently introduced by...
Prairie voles are socially monogamous rodents that form social bonds similar to those seen in primates. Social behavior investigation in these species, that include studying their breathing regulation, can provide us with an invaluable psychological model to understand social and emotional functions in both animals and humans. There have been several studies associated with the respiratory pattern...
The industrial, scientific and medical band is widely used by different wireless systems. The identification of other wireless technologies in the common environment is one of the keys for correct system coexistence. In this work, a sensing platform for the detection of IEEE 802.11g and IEEE 802.15.4 primary signals in the 2.4 GHz band is proposed. The sensing platform makes use of a combined scheme...
Energy expenditure (EE) estimation from accelerometer-based wearable sensors is important to generate accurate assessment of physical activity (PA) in individuals. Approaches hitherto have mainly focused on using accelerometer data and features extracted from these data to learn a regression model to predict EE directly. In this paper, we propose a novel framework for EE estimation based on statistical...
In order for any obesity therapy to be successful real behavior change by the individual is required. We present an implantable obesity therapy that combines gastric electrical stimulation for satiety with onboard sensors that provide self-monitoring for the patient and compliance reporting to the clinician. An algorithm for processing data from the onboard three axis accelerometer for use in physical...
In this work stress is assessed based on EEG features. We focus our efforts on the correlation between subjective ratings and cerebral indices during virtual navigation scenarios. Ten male paraplegic subjects took part in the experiment and navigated in a virtual indoor environment. They had to fulfill two missions where time pressure parameter is introduced. Subjects were equipped with Electroencephalography...
Trust model has been suggested as an effective security mechanism in distributed network environment. Considerable researches have been done on trust evaluation and trust prediction. Traditional methods take the historical behavior data into consideration to predict the trust value of the network entity. However, the context of the network entity is seldom taken into account. It is obvious that the...
This paper focuses on oxygen consumption (VO2) estimation using 6-axis motion data (3-axis acceleration and 3-axis angular velocity) that are obtained from small motion sensors attached to people playing sports with different intensities. In order to achieve high estimation accuracy over a wide range of intensities of exercises, we apply neural network that is trained by experimental data consisting...
Alpha-band rhythm is thought to be involved in memory processes, similarly to other spontaneous brain rhythms. Ten right-handed healthy volunteers participated in our proposed sequential short-term memory task that provides a serial position effect in accuracy rate. We recorded alpha-band rhythms by magnetoencephalography during performance of the task and observed that the amplitude of the rhythm...
We investigate the spectral and spatial characteristics of the ego-noise of a multirotor micro aerial vehicle (MAV) using audio signals captured with multiple onboard microphones and derive a noise model that grounds the feasibility of microphone-array techniques for noise reduction. The spectral analysis suggests that the ego-noise consists of narrowband harmonic noise and broadband noise, whose...
To help consumers enjoy healthy food, technology investigation for food freshness sensing are conducted. In this study meat is selected as the detection target based on a consumer survey. Near infrared spectroscopy, pH, CO2, TVOC, and auto fluorescence are investigated. The results showed that CO2 and TVOC could be a used for meat freshness sensing in a closed space such as box. Near infrared spectroscopy...
The opportunities to empirically study temporal networks nowadays are immense thanks to Internet of Things technologies along with ubiquitous and pervasive computing that allow a real-time fine-grained collection of social network data. This empowers data analytics and data scientists to reason about complex temporal phenomena, such as disease spread, residential energy consumption, political conflicts...
A key assumption of distributed data fusion is that individual nodes have no knowledge of the global network topology and use only information which is available locally. This paper considers the weighted exponential product (WEP) rule as a methodology for conservatively fusing estimates with an unknown degree of correlation between them. We provide a preliminary investigation into how the methodology...
Consider MMV problem YM ×L = AM×N XN×L with X being D-row sparse. In this work, we first we analyze the MSBL algorithm by Wipf and Rao, and provide its limit in the M ≤ D regime. To improve support recovery, we further develop Bayesian methods for learning the correlation structures both temporally or spatially. In particular, we use the Inverse Wishart distribution, the conjugate prior for the covariance...
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