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Journal articleHemakom A, Chanwimalueang T, Carrion A, et al., 2016,
Financial Stress Through Complexity Science
, IEEE Journal of Selected Topics in Signal Processing, Vol: 10, Pages: 1112-1126, ISSN: 1932-4553Abstract:Financial markets typically undergo periods of prosperity followed by periods of stagnation, and this undulation makes it challenging to maintain market efficiency. The efficient market hypothesis (EMH) states that there exist differences in structural complexity in security prices between regular and abnormal situations. Yet, despite a clear link between market acceleration (cf. recession in security prices) and stress in physical systems, indices of financial stress still have significant scope for further development. The overarching aim of this work is therefore to determine the characteristics of financial indices related to financial stress, and to establish a robust metric for the extent of such `stress'. This is achieved based on intrinsic multiscale analysis which quantifies the so called complexity-loss hypothesis in the context of financial stress. The multiscale sample entropy and our proposed Assessment of Latent Index of Stress methods have successfully assessed financial stress, and have served as a measure to establish an analogy between transitions from `normal' (relaxed) to `abnormal' (stressed) financial periods with the sympatho-vagal balance in humans. Four major stock indices of the US economy over the past 25 years are considered: (i) Dow Jones Industrial Average, (ii) NASDAQ Composite, (iii) Standard & Poor's 500, and (iv) Russell 2000, together with FTSE 100, CAC 40 and exchange rates. Our findings support the EMH theory and reveal high stress for both the periods of Internet bubble burst and sub-prime mortgage crisis.
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Journal articleHuang Y, Clerckx B, 2016,
Relaying Strategies for Wireless-Powered MIMO Relay Networks
, IEEE Transactions on Wireless Communications, Vol: 15, Pages: 6033-6047, ISSN: 1558-2248This paper investigates relaying schemes in an amplify-and-forward multiple-input multiple-output relay network, where an energy-constrained relay harvests wireless power from the source information flow and can be further aided by an energy flow (EF) in the form of a wireless power transfer at the destination. However, the joint optimization of the relay matrix and the source precoder for the energy-flow-assisted (EFA) and the non-EFA (NEFA) schemes is intractable. The original rate maximization problem is transformed into an equivalent weighted mean square error minimization problem and optimized iteratively, where the global optimum of the nonconvex source precoder subproblem is achieved by semidefinite relaxation and rank reduction. The iterative algorithm finally converges. Then, the simplified EFA and NEFA schemes are proposed based on channel diagonalization, such that the matrices optimizations can be simplified to power optimizations. Closed-form solutions can be achieved. Simulation results reveal that the EFA schemes can outperform the NEFA schemes. Additionally, deploying more antennas at the relay increases the dimension of the signal space at the relay. Exploiting the additional dimension, the EF leakage in the information detecting block can be nearly separated from the information signal, such that the EF leakage can be amplified with a small coefficient.
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Journal articleEaton DJ, Gaubitch ND, Moore AH, et al., 2016,
Estimation of room acoustic parameters: the ACE challenge
, IEEE Transactions on Audio Speech and Language Processing, Vol: 24, Pages: 1681-1693, ISSN: 2329-9290Reverberation Time (T60) and Direct-to-Reverberant Ratio (DRR) are important parameters which together can characterize sound captured by microphones in non-anechoic rooms. These parameters are important in speech processing applications such as speech recognition and dereverberation. The values of T60 and DRR can be estimated directly from the Acoustic Impulse Response (AIR) of the room. In practice, the AIR isnot normally available, in which case these parameters must be estimated blindly from the observed speech in the microphone signal. The Acoustic Characterization of Environments (ACE) Challenge aimed to determine the state-of-the-art in blind acoustic parameter estimation and also to stimulate research in this area. A summary of the ACE Challenge, and the corpusused in the challenge is presented together with an analysis of the results. Existing algorithms were submitted alongside novel contributions, the comparative results for which are presented in this paper. The challenge showed that T60 estimation is a mature field where analytical approaches dominate whilst DRR estimation is a less mature field where machine learning approaches are currently more successful.
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Journal articleXu P, Cumanan K, Ding Z, et al., 2016,
Group Secret Key Generation in Wireless Networks: Algorithms and Rate Optimization
, IEEE Transactions on Information Forensics and Security, Vol: 11, Pages: 1831-1846, ISSN: 1556-6021This paper investigates group secret key generation problems for different types of wireless networks, by exploiting physical layer characteristics of wireless channels. A new group key generation strategy with low complexity is proposed, which combines the well-established point-to-point pairwise key generation technique, the multisegment scheme, and the one-time pad. In particular, this group key generation process is studied for three types of communication networks: 1) the three-node network; 2) the multinode ring network; and 3) the multinode mesh network. Three group key generation algorithms are developed for these communication networks, respectively. The analysis shows that the first two algorithms yield optimal group key rates, whereas the third algorithm achieves the optimal multiplexing gain. Next, for the first two types of networks, we address the time allocation problem in the channel estimation step to maximize the group key rates. This non-convex max-min time allocation problem is first reformulated into a series of geometric programming, and then, a single-condensation-method-based iterative algorithm is proposed. Numerical results are also provided to validate the performance of the proposed key generation algorithms and the time allocation algorithm.
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Journal articleClerckx B, Joudeh H, Hao C, et al., 2016,
Rate Splitting for MIMO Wireless Networks: A Promising PHY-Layer Strategy for LTE Evolution
, IEEE Communications Magazine, Vol: 54, Pages: 98-105, ISSN: 1558-1896MIMO processing plays a central part towards the recent increase in spectraland energy efficiencies of wireless networks. MIMO has grown beyond theoriginal point-to-point channel and nowadays refers to a diverse range ofcentralized and distributed deployments. The fundamental bottleneck towardsenormous spectral and energy efficiency benefits in multiuser MIMO networkslies in a huge demand for accurate channel state information at the transmitter(CSIT). This has become increasingly difficult to satisfy due to the increasingnumber of antennas and access points in next generation wireless networksrelying on dense heterogeneous networks and transmitters equipped with a largenumber of antennas. CSIT inaccuracy results in a multi-user interferenceproblem that is the primary bottleneck of MIMO wireless networks. Lookingbackward, the problem has been to strive to apply techniques designed forperfect CSIT to scenarios with imperfect CSIT. In this paper, we depart fromthis conventional approach and introduce the readers to a promising strategybased on rate-splitting. Rate-splitting relies on the transmission of commonand private messages and is shown to provide significant benefits in terms ofspectral and energy efficiencies, reliability and CSI feedback overheadreduction over conventional strategies used in LTE-A and exclusively relying onprivate message transmissions. Open problems, impact on standard specificationsand operational challenges are also discussed.
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Journal articleRassouli B, Clerckx B, 2016,
An Upper Bound for the Capacity of Amplitude-Constrained Scalar AWGN Channel
, IEEE Communications Letters, Vol: 20, Pages: 1924-1926, ISSN: 1558-2558This paper slightly improves the upper bound in Thangaraj et al. for thecapacity of the amplitude-constrained scalar AWGN channel. This improvementmakes the upper bound within 0.002 bits of the capacity for$\frac{E_b}{N_0}\leq 2.5$ dB.
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Journal articleDing W, Lu Y, Yang F, et al., 2016,
Spectrally Efficient CSI Acquisition for Power Line Communications: A Bayesian Compressive Sensing Perspective
, IEEE Journal on Selected Areas in Communications, Vol: 34, Pages: 2022-2032, ISSN: 1558-0008Power line communication (PLC) techniques present a no extra wire solution for the communication purpose in a smart grid due to the ubiquity and low cost. Moreover, the through-the-grid property of PLC has naturally extended its possible applications, including but not limited to the automatic meter reading, line quality monitoring, online diagnostics, and network tomography. To guarantee the performance of communications as well as other applications in PLC systems, accurate channel state information (CSI) acquisition should be performed regularly. However, the conventional pilot-based CSI acquisition approaches in PLC systems have not made full use of the channel characteristics and hence suffer from a low spectral efficiency. In this paper, by exploiting the parametric sparsity and discretizing the electrical length in the well-known PLC channel model, we formulate the non-sparse (either time domain or frequency domain) PLC channel into a compressive sensing (CS) applicable problem. Furthermore, we propose a spectrally efficient CSI acquisition scheme under the framework of Bayesian CS and extend it to the multiple-input multiple-output PLC by investigating the channel spatial correlation. Compared with the existing sparse CSI acquisition schemes for PLC, such as the annihilating filter-based and the estimating signal parameters via rotational invariance technique-based ones, the proposed scheme has better mean square error performance and noise robustness.
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PatentEaton DJ, Moore AH, Naylor PA, et al., 2016,
Reverberation estimator
, US20160118038 A1Provided are methods and systems for generating Direct-to-Reverberant Ratio (DRR) estimates. The methods and systems use a null-steered beamformer to produce accurate DRR estimates across a variety of room sizes, reverberation times, and source-receiver distances. The DRR estimation algorithm uses spatial selectivity to separate direct and reverberant energy and account for noise separately. The formulation considers the response of the beamformer to reverberant sound and the effect of noise. The DRR estimation algorithm is more robust to background noise than existing approaches, and is applicable where a signal is recorded with two or more microphones, such as with mobile communications devices, laptop computers, and the like.
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Journal articleSharma D, Naylor PA, Wang Y, et al., 2016,
A Data-Driven Non-intrusive Measure of Speech Quality and Intelligibility
, Speech Communication, Vol: 80, Pages: 84-94, ISSN: 0167-6393Speech signals are often affected by additive noiseand distortion which can degrade the perceived quality andintelligibility of the signal. We present a new measure, NISA, forestimating the quality and intelligibility of speech degraded byadditive noise and distortions associated with telecommunicationsnetworks, based on a data driven framework of feature extractionand tree based regression. The new measure is non-intrusive,operating on the degraded signal alone without the need for areference signal. This makes the measure applicable to practicalspeech processing applications operating in the single-endedmode. The new measure has been evaluated against the intrusivemeasures PESQ and STOI. The results indicate that the accuracyof the new non-intrusive method is around 90% of the accuracy ofthe intrusive measures, depending on the test scenario. The NISAmeasure therefore provides non-intrusive (single-ended) PESQand STOI estimates with high accuracy.
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Journal articleKanna S, Mandic DP, 2016,
Steady-State Behavior of General Complex-Valued Diffusion LMS Strategies
, IEEE Signal Processing Letters, Vol: 23, Pages: 722-726, ISSN: 1558-2361A novel methodology to bound the steady-state mean square performance of the diffusion complex least mean square (D-CLMS) and the diffusion widely linear (augmented) CLMS (D-ACLMS) algorithm is proposed. This is achieved by exploiting the almost identical nature of the steady-state filter weights at all nodes. The proposed approach allows for the consideration of the second-order terms in the recursion for the weight error covariance matrix, without compromising the mathematical tractability of the problem. The closed form expressions for the mean square deviation (MSD) and excess mean square error (EMSE) for both the D-CLMS and D-ACLMS allow for the performance of the algorithms to be quantified as a function of the noncircularity of the input data.
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Journal articleLee H, Lee K-J, Kim H, et al., 2016,
Resource Allocation Techniques for Wireless Powered Communication Networks With Energy Storage Constraint
, IEEE Transactions on Wireless Communications, Vol: 15, Pages: 2619-2628, ISSN: 1558-2248This paper studies multiuser wireless powered communication networks, where energy constrained users charge their energy storages by scavenging energy of the radio frequency signals radiated from a hybrid access point (H-AP). The energy is then utilized for the users' uplink information transmission to the H-AP in time division multiple access mode. In this system, we aim to maximize the uplink sum rate performance by jointly optimizing energy and time resource allocation for multiple users in both infinite capacity and finite capacity energy storage cases. First, when the users are equipped with the infinite capacity energy storages, we derive the optimal downlink energy transmission policy at the H-AP. Based on this result, analytical resource allocation solutions are obtained. Next, we propose the optimal energy and time allocation algorithm for the case where each user has finite capacity energy storage. Simulation results confirm that the proposed algorithms offer about 30% average sum rate performance gain over conventional schemes.
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Conference paperAntoniou ZC, Panayides AS, Pantziaris M, et al., 2016,
Dynamic Network Adaptation for Real-Time Medical Video Communication
, 14th Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON), Publisher: SPRINGER, Pages: 1093-1098, ISSN: 1680-0737The wider adoption of mHealth video communication systems in standard clinical practice requires adequate levels of clinical video quality to support reliable diagnosis. The latter dictates that real-time adaptation to time-varying wireless networks’ state to guarantee clinically acceptable performance throughout the streaming session, while conforming to device capabilities for supporting real-time encoding. In this study we propose a multi-objective optimization framework that jointly maximizes the encoded video’s quality while minimizing bitrate demands and encoding time. Experimental investigation shows that the proposed framework can provide for efficient real-time adaptation at a Group of Pictures (GOP) level, demonstrating significant gains over static approaches.
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Journal articleLiu CH, Zhao J, Zhang H, et al., 2016,
Energy-Efficient Event Detection by Participatory Sensing Under Budget Constraints
, IEEE SYSTEMS JOURNAL, Vol: 11, Pages: 2490-2501, ISSN: 1932-8184Dynamic event detection by using participatory sensing paradigms has received growing interests recently, where detection tasks are assigned to smart-device users who can potentially collect needed sensory data from device-equipped sensors. Typical applications include, but are not limited to, noise and air pollution detections, people gathering, even disaster prediction. Given this problem, although many existing centralized solutions are effective and widely used, they usually cause heavy communication overhead. Thus, it is strongly desired to design distributed solutions to reduce energy consumption, while achieving a high level of detection accuracy with limited sensing task budget. In this paper, we first present two novel centralized detection algorithms as the performance benchmark, which make use of the Minimum Cut theory and support vector machine (SVM)-based pattern recognition techniques. Then, we introduce a novel distributed and energy-efficient event detection framework under task budget constraint, where we formulate an optimization problem and derive an optimal utility function. Finally, based on a real trace-driven data set in an urban area of Beijing, extensive simulation results demonstrate the effectiveness of our proposed algorithms.
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Conference paperJaved HA, Moore AH, Naylor PA, 2016,
Spherical microphone array acoustic rake receivers
, ICASSP, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, Publisher: IEEE, Pages: 111-115, ISSN: 0736-7791Several signal independent acoustic rake receivers are proposed for speech dereverberation using spherical microphone arrays. The proposed rake designs take advantage of multipaths, by separately capturing and combining early reflections with the direct path. We investigate several approaches in combining reflections with the direct path source signal, including the development of beam patterns that point nulls at all preceding reflections. The proposed designs are tested in experimental simulations and their dereverberation performances evaluated using objective measures. For the tested configuration, the proposed designs achieve higher levels of dereverberation compared to conventional signal independent beamforming systems; achieving up to 3.6 dB improvement in the direct-to-reverberant ratio over the plane-wave decomposition beamformer.
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Conference paperWang Y, Brookes D, 2016,
Speech Enhancement Using An {MMSE} Spectral Amplitude Estimator Based On A Modulation Domain Kalman Filter With A Gamma Prior
, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 5225-5229In this paper, we propose a minimum mean square error spectral estimator for clean speech spectral amplitudes that uses a Kalman filter to model the temporal dynamics of the spectral amplitudes in the modulation domain. Using a two-parameter Gamma distribution to model the prior distribution of the speech spectral amplitudes, we derive closed form expressions for the posterior mean and variance of the spectral amplitudes as well as for the associated update step of the Kalman filter. The performance of the proposed algorithm is evaluated on the TIMIT core test set using the perceptual evaluation of speech quality (PESQ) measure and segmental SNR measure and is shown to give a consistent improvement over a wide range of SNRs when compared to competitive algorithms.
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Conference paperLightburn L, Brookes D, 2016,
A Weighted STOI Intelligibility Metric Based On Mutual Information
, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 5365-5369It is known that the information required for the intelligibility of a speech signal is distributed non-uniformly in time. In this paper we propose WSTOI, a modified version of STOI, a speech intelligibility metric. With WSTOI the contribution of each time-frequency cell is weighted by an estimate of its intelligibility content. This estimate is equal to the mutual information between two hypothetical signals at either end of a simplified model of human communication. Listening tests show that the modification improves the prediction accuracy of STOI at all performance levels on both long and short utterances. An improvement was observed across all tested noise types and suppression algorithms.
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Journal articleKoulouri A, Rimpiläinen V, Brookes M, et al., 2016,
Compensation of domain modelling errors in the inverse source problem of the Poisson equation: Application in electroencephalographic imaging
, Applied Numerical Mathematics, Vol: 106, Pages: 24-36, ISSN: 1873-5460 -
Conference paperChanwimalueang T, Aufegger L, von Rosenberg W, et al., 2016,
Modelling stress in public speaking: evolution of stress levels during conference presentations
, International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2016, Publisher: IEEE, Pages: 814-818The Electrocardiogram (ECG) collected in real-life scenarios is often noisy and contaminated with motion artefacts. This study proposes a new framework to analyse the heart rate variability (HRV) in mobile scenarios by introducing novel R-peak detection and HRV detrending algorithms. The R-peak detection combines matched filtering and Hilbert transform, while detrending the HRV is performed using empirical mode decomposition with novel physically meaningful stopping criteria. Next, four quantitative metrics-sample entropy, LFhrv, HFhrv and LF/HF ratio ??? are used to estimate stress levels in two public speaking events: (i) a presentation in front of an audience and (ii) an interactive poster presentation, both at ICASSP 2015. We show that the proposed framework makes it possible to detect distinctive stress-patterns in the structural complexity of the HRV, thus verifying the complexity-loss hypothesis in physiological research.
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Conference paperJoudeh H, Clerckx B, 2016,
A Rate-Splitting Approach To Robust Multiuser MISO Transmission
, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Pages: 3436-3440, ISSN: 2379-190XFor multiuser MISO systems with bounded uncertainties in the Channel State Information (CSI), we consider two classical robust design problems: maximizing the minimum rate subject to a transmit power constraint, and power minimization under a rate constraint. Contrary to conventional strategies, we propose a Rate-Splitting (RS) strategy where each message is divided into two parts, a common part and a private part. All common parts are packed into one super common message encoded using a shared codebook and decoded by all users, while private parts are independently encoded and retrieved by their corresponding users. We prove that RS-based designs achieve higher max-min Degrees of Freedom (DoF) compared to conventional designs (NoRS) for uncertainty regions that scale with SNR. For the special case of non-scaling uncertainty regions, RS contrasts with NoRS and achieves a non-saturating max-min rate. In the power minimization problem, RS is shown to combat the feasibility problem arising from multiuser interference in NoRS. A robust design of precoders for RS is proposed, and performance gains over NoRS are demonstrated through simulations.
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Conference paperEvers C, Moore AH, Naylor PA, 2016,
Acoustic simultaneous localization and mapping (A-SLAM) of a moving microphone array and its surrounding speakers
, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 6-10, ISSN: 1520-6149Acoustic scene mapping creates a representation of positions of audio sources such as talkers within the surrounding environment of a microphone array. By allowing the array to move, the acoustic scene can be explored in order to improve the map. Furthermore, the spatial diversity of the kinematic array allows for estimation of the source-sensor distance in scenarios where source directions of arrival are measured. As sound source localization is performed relative to the array position, mapping of acoustic sources requires knowledge of the absolute position of the microphone array in the room. If the array is moving, its absolute position is unknown in practice. Hence, Simultaneous Localization and Mapping (SLAM) is required in order to localize the microphone array position and map the surrounding sound sources. In realistic environments, microphone arrays receive a convolutive mixture of direct-path speech signals, noise and reflections due to reverberation. A key challenge of Acoustic SLAM (a-SLAM) is robustness against reverberant clutter measurements and missing source detections. This paper proposes a novel bearing-only a-SLAM approach using a Single-Cluster Probability Hypothesis Density filter. Results demonstrate convergence to accurate estimates of the array trajectory and source positions.
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Journal articleDai M, Clerckx B, Gesbert D, et al., 2016,
A Rate Splitting Strategy for Massive MIMO with Imperfect CSIT
, IEEE Transactions on Wireless Communications, Vol: PP, ISSN: 1536-1276In a multiuser MIMO broadcast channel, the rate performance is affected by multiuser interference when the Channel State Information at the Transmitter (CSIT) is imperfect. To tackle the detrimental effects of the multiuser interference, a Rate-Splitting (RS) approach has been proposed recently, which splits one selected user’s message into a common and a private part, and superimposes the common message on top of the private messages. The common message is drawn from a public codebook and decoded by all users. In this paper, we generalize the idea of RS into the large-scale array regime with imperfect CSIT. By further exploiting the channel secondorder statistics, we propose a novel and general framework Hierarchical-Rate-Splitting (HRS) that is particularly suited to massive MIMO systems. HRS simultaneously transmits private messages intended to each user and two kinds of common messages that are decoded by all users and by a subset of users, respectively. We analyse the asymptotic sum rate of RS and HRS and optimize the precoders of the common messages. A closedform power allocation is derived which provides insights into the effects of various system parameters. Finally, numerical results validate the significant sum rate gain of RS and HRS over various baselines.
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Journal articleHemakom A, Goverdovsky V, Looney D, et al., 2016,
Adaptive-projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain-computer interface applications
, Philosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences, Vol: 374, ISSN: 1364-503XAn extension to multivariate empirical mode decomposition (MEMD), termed adaptive-projection intrinsically transformed MEMD (APIT-MEMD), is proposed to cater for power imbalances and inter-channel correlations in real-world multichannel data. It is shown that the APIT-MEMD exhibits similar or better performance than MEMD for a large number of projection vectors, whereas it outperforms MEMD for the critical case of a small number of projection vectors within the sifting algorithm. We also employ the noise-assisted APIT-MEMD within our proposed intrinsic multiscale analysis framework and illustrate the advantages of such an approach in notoriously noise-dominated cooperative brain–computer interface (BCI) based on the steady-state visual evoked potentials and the P300 responses. Finally, we show that for a joint cognitive BCI task, the proposed intrinsic multiscale analysis framework improves system performance in terms of the information transfer rate.
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Conference paperLiu T, Stathaki P, Copin V, 2016,
Human detection from ground truth cameras through combined use of Histogram of Oriented Gradients and body part models
, International Conference and Computer Vision Theory and Applications -
Conference paperStathaki P, Konstantinidis D, Argyriou V, et al., 2016,
A probabilistic feature fusion for building detection in satellite images
, International Conference and Computer Vision Theory and Applications -
Conference paperStathaki P, Konstantinidis D, Argyriou V, et al., 2016,
A 3D feature for building segmentation based on shape-from-shading
, International Conference and Computer Vision Theory and Applications -
Journal articleFeng R-B, Leung C-S, Constantinides AG, 2016,
LCA based RBF training algorithm for the concurrent fault situation
, Neurocomputing, Vol: 191, Pages: 341-351, ISSN: 1872-8286 -
Journal articleWang W, Gao H, Liu CH, et al., 2016,
Credible and energy-aware participant selection with limited task budget for mobile crowd sensing
, Ad Hoc Networks, Vol: 43, Pages: 56-70, ISSN: 1570-8713Crowd sensing campaigns encourage ordinary people to collect and share sensing data by using their carried smart devices. However, new challenges that must be faced have arisen. One of them is how to allocate tasks to the most appropriate participants when considering their different incentive requirements and credibility, in order to best satisfy the quality-of-information (QoI) requirements of multiple concurrent tasks, with different, and limited budget constraints. Another challenge is how to maximize participants’ rewards to encourage them to contribute sensing data continuously. To this end, in this paper, we first propose a crowd sensing system, that aims to address the above two challenges, where the system considers the benefits of both platform and participants. Then, a participant reputation definition and update method is proposed, that takes participant’s willingness and contributed data quality into consideration. Last, we introduce two metrics called “QoI satisfaction” and “Difficulty of Task (DoT)”. The former quantifies how much collected sensing data can satisfy the multi-dimensional task’s QoI requirements in terms of data quality, granularity and quantity, and the later aids participants to choose proper tasks to maximize their rewards. Finally, we compare our proposed scheme with existing methods via extensive simulations based on a real dataset. Extensive simulation results well justify the effectiveness and robustness of our approach.
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Journal articleWu X, Yang Z, Ling C, et al., 2016,
Artificial-noise-aided message authentication codes with information-theoretic security
, IEEE Transactions on Information Forensics and Security, Vol: 11, Pages: 1278-1290, ISSN: 1556-6021In the past, two main approaches for the purposeof authentication, including information-theoretic authenticationcodes and complexity-theoretic message authenticationcodes (MACs), were almost independently developed. In thispaper, we consider to construct new MACs, which are bothcomputationally secure and information-theoretically secure.Essentially, we propose a new cryptographic primitive, namely,artificial-noise-aided MACs (ANA-MACs), where artificial noiseis used to interfere with the complexity-theoretic MACs andquantization is further employed to facilitate packet-based transmission.With a channel coding formulation of key recovery inthe MACs, the generation of standard authentication tags canbe seen as an encoding process for the ensemble of codes, wherethe shared key between Alice and Bob is considered as the inputand the message is used to specify a code from the ensembleof codes. Then, we show that artificial noise in ANA-MACs canbe well employed to resist the key recovery attack even if theopponent has an unlimited computing power. Finally, a pragmaticapproach for the analysis of ANA-MACs is provided, and weshow how to balance the three performance metrics, includingthe completeness error, the false acceptance probability, and theconditional equivocation about the key. The analysis can be wellapplied to a class of ANA-MACs, where MACs with Rijndaelcipher are employed.
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Journal articleNeeld T, Eaton J, Naylor PA, et al., 2016,
A novel method of determining events in combination gas boilers: Assessing the feasibility of a passive acoustic sensor
, Building and Environment, Vol: 100, Pages: 1-9, ISSN: 0360-1323To assess the impact of interventions designed to reduce residential space heating demand, investigators must be armed with field-trial applicable techniques that accurately measure space heating energy use. This study assesses the feasibility of using a passive acoustic sensor to detect gas consumption events in domestic combination gas-fired boilers (C-GFBs). The investigation has shown, for the C-GFB investigated, the following events are discernible using a passive acoustic sensor: demand type (hot water or central heating); boiler ignition time; and pre-mix fan motor speed. A detection algorithm was developed to automatically identify demand type and burner ignition time with accuracies of 100% and 97% respectfully. Demand type was determined by training a naive Bayes classifier on 20 features of the acoustic profile at the start of a demand event. Burner ignition was determined by detecting low frequency (5–10 Hz) pressure pulsations produced during ignition. The acoustic signatures of the pre-mix fan and circulation-pump were identified manually. Additional work is required to detect burner duration, deal with detection in the presence of increased noise and expand the range of boilers investigated. There are considerable implications resulting from the widespread use of such techniques on improving understanding of space heating demand.
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Journal articleMurray-Bruce J, Dragotti PL, 2016,
Physics-driven quantized consensus for distributed diffusion source estimation using sensor networks
, Eurasip Journal on Advances in Signal Processing, Vol: 2016, ISSN: 1687-6180Sensor networks are important for monitoring several physical phenomena. In this paper, we consider the monitoring of diffusion fields and design simple, yet robust, sensing, data processing and communication strategies for estimating the sources of diffusion fields under communication constraints. Specifically, based on our previous work in the area, we firstly show how sources of the field can be recovered analytically through the use of well-chosen sensing functions. Then, by properly extending this scheme to our sensor network setting, we design and propose an effective diffusion field sensing strategy. Next, we introduce a physics-driven quantized gossip scheme, as a joint information processing and communication strategy for handling the network communication constraints: i.e. when a sensor can only communicate with a small subset of nodes over links with a finite capacity. Combining the proposed strategies allows us to develop a fully distributed algorithm for recovering sources of diffusion fields using sensor networks. Numerical simulation results are presented in order to evaluate the effectiveness and robustness of our algorithm.
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