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The objective of this paper is to address a new method based on trend extraction for isolating faults in the nonstationary and nonlinear processes. Firstly, a concise review of the traditional methods for fault isolation based on Hotelling statistic are introduced, a rigorous analysis of their weaknesses, especially the smearing (coupling) phenomena, is provided, and the possible handling strategies...
We present a novel Cyber Security analytics framework. Wedemonstrate a comprehensive cyber security monitoring system toconstruct cyber security correlated events with feature selection toanticipate behaviour based on various sensors.
Due to the prevalence of Multi-set high-dimensional data in the era of big data, visualization and visual analysis of multiple sets of high-dimensional data are critical to the discovery of data patterns. Parallel Coordinates Plot (PCP) is mainly used for visual analysis of different attributes of the same set. The classic method for visualization on multi-set high-dimensional data is to use a conventional...
Complex industrial processes are often non-linear and non-Gaussian, while the traditional principal component analysis (PCA) method assumes that the data are Gaussian and linear. In this paper, a novel process monitoring method based on maximum information coefficient-PCA (MIC-PCA) and support vector data description (SVDD) is proposed. First, the covariance matrix is replaced by the MIC matrix which...
A wireless sensor network (WSN) is a conglomeration of scattered self organized sensor nodes to agreeably monitor the physical and surrounding conditions. These sensor nodes are equipped with limited resources such as memory, processing capability, battery power and transceiver for monitoring, processing and communicating the observed phenomena to make critical decisions with respect to collected...
Information from different bio-signals such as speech, handwriting, and gait have been used to monitor the state of Parkinson's disease (PD) patients, however, all the multimodal bio-signals may not always be available. We propose a method based on multi-view representation learning via generalized canonical correlation analysis (GCCA) for learning a representation of features extracted from handwriting...
We study the sensor selection problem for field estimation, where a best subset of sensors is activated to monitor a spatially correlated random field. Different from most commonly used centralized selection algorithms, we propose a decentralized architecture where sensor selection can be carried out in a distributed way and by the sensors themselves. A decentralized approach is essential since each...
In this paper, we present an approach for automated profiling of cloud-based distributed applications. The failure dependencies within or between application nodes can be methodically elucidated by dynamically applying a series of unitary perturbations on the underlying computing resources. Each such perturbation in a node acts as a stimulus which propagates to performance meters of dependent nodes...
In this paper, we evaluate the usefulness of metrics that assess susceptibility to cascading blackouts. The metrics are computed using a matrix of Line Outage Distribution Factors (LODF, or DFAX matrix). The metrics are compared for several base cases with different load levels of the Western Interconnection (WI). A case corresponding to the September 8, 2011 pre-blackout state is used to compute...
As we move to higher data rates, the performance of clock and data recovery (CDR) circuits becomes increasingly important in maintaining low bit error rates (BER) in wireline links. Digital CDRs are popular in part for their robustness, but their use of bang-bang phase detectors (BB-PD) makes their performance sensitive to changes in jitter caused by PVT variations, crosstalk or power supply noise...
The increasingly-stringent power and energy requirements of emerging embedded applications have led to a strong recent interest in aggressive power gating techniques. Conventional techniques for aggressive power gating perform module-based power gating in processors, where power domains correspond to RTL modules. We observe that there can be significant power benefits from module-oblivious power gating,...
Data collected by fitness trackers could play an important role in improving the health and well-being of the individuals who wear them. Many insurance companies even offer monetary rewards to participants who meet certain steps or calorie goals. However, in order for it to be useful, the collected data must be accurate and also reflect real-world performance. While previous studies have compared...
Tremendous interest prevails in developing a convenient and effective wearable medical device for evaluating sleep at home. The current study presents the clinical validation of VitalPatch®, a wireless adhesive patch sensor for screening of sleep architecture compared to the gold standard polysomnograph (PSG). A group of 45 volunteers were attached to a standard 22-channel PSG and a VitalPatch sensor...
With the increasing scale and complexity of the network, how to maintain a level of network performance and robustness for network operators to satisfy customers becomes more and more challenging. Network anomaly detection and localization are critical for ensuring network performance. In this paper, a novel framework for detecting and localizing network anomalies using active measurements is presented...
The emergence and existence of coverage holes in WSNs will dramatically degrade the network coverage performance and quality of service. To diminish the negative effects of coverage holes, this paper studies the confident information coverage hole detection problem(CICHD) based on the proposed novel confident information coverage model(CIC). For solving the CICHD problem, we design an effective heuristic...
Reliable information processing is an indispensable task in Smart City environments. Heterogeneous sensor infrastructures of individual information providers and data portal vendors tend to offer a hardly revisable information quality. This paper proposes a correlation model-based monitoring approach to evaluate the plausibility of smart city data sources. The model is based on spatial, temporal,...
GNSS signals are vulnerable to various types of interference including jamming and spoofing attacks. Spoofing signals are designed to deceive target GNSS receivers without being detected by conventional receiver quality monitoring metrics. This paper focuses on detecting an overlapped spoofing attack where the correlation peaks of the authentic and spoofing signals interact during the attack. Several...
Today's dynamic computing deployment for commercial and scientific applications is propelling us to an era where minor inefficiencies can snowball into significant performance and operational bottlenecks. Data center operations is increasingly relying on sensors based control systems for key decision insights. The increased sampling frequencies, cheaper storage costs and prolific deployment of sensors...
Among many Big Data applications are those that deal with data streams. A data stream is a sequence of data points with timestamps that possesses the properties of transiency, infiniteness, uncertainty, concept drift, and multi-dimensionality. In this paper we propose an outlier detection technique called Orion that addresses all the characteristics of data streams. Orion looks for a projected dimension...
Because a huge number of base stations are deployed due to the recent development of mobile access services, network monitoring in mobile networks becomes more challenging. In this paper, we propose a novel change-point detection scheme to efficiently detect a time instant (change-point) when the spatial distribution of mobile terminals connecting to base stations is changed dramatically. In the proposed...
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