Entanglement detection in hybrid optomechanical systems

We study a device formed by a Bose-Einstein condensate (BEC) coupled to the field of a cavity with a moving end mirror and find a working point such that the mirror-light entanglement is reproduced by the BEC-light quantum correlations. This provides an experimentally viable tool for inferring mirror-light entanglement with only a limited set of assumptions. We prove the existence of tripartite entanglement in the hybrid device, persisting up to temperatures of a few milli-Kelvin, and discuss a scheme to detect it.

Tree-Based Adaptive Spatial Detection for Adaptive Modulated MIMO Systems

Adaptive Multiple-Input Multiple-Output (MIMO) systems achieve a much higher information rate than conventional fixed schemes due to their ability to adapt their configurations according to the wireless communications environment. However, current adaptive MIMO detection schemes exhibit either low performance (and hence low spectral efficiency) or huge computational
complexity. In particular, whilst deterministic Sphere Decoder (SD) detection schemes are well established for static MIMO systems, exhibiting deterministic parallel structure, low computational complexity and quasi-ML detection performance, there are no corresponding adaptive schemes. This paper solves
this problem, describing a hybrid tree based adaptive modulation detection scheme. Fixed Complexity Sphere Decoding (FSD) and Real-Values FSD (RFSD) are modified and combined into a hybrid scheme exploited at low and medium SNR to provide the highest possible information rate with quasi-ML Bit Error
Rate (BER) performance, while Reduced Complexity RFSD, BChase and Decision Feedback (DFE) schemes are exploited in the high SNR regions. This algorithm provides the facility to balance the detection complexity with BER performance with compatible information rate in dynamic, adaptive MIMO communications
environments.

Intrusion Detection System for Network Security in Synchrophasor Systems

Synchrophasor systems will play a crucial role in next generation Smart Grid monitoring, protection and control. However these systems also introduce a multitude of potential vulnerabilities from malicious and inadvertent attacks, which may render erroneous operation or severe damage. This paper proposes a Synchrophasor Specific Intrusion Detection System (SSIDS) for malicious cyber attack and unintended misuse. The SSIDS comprises a heterogeneous whitelist and behavior-based approach to detect known attack types and unknown and so-called ‘zero-day’ vulnerabilities and attacks. The paper describes reconnaissance, Man-in-the-Middle (MITM) and Denial-of-Service (DoS) attack types executed against a practical synchrophasor system which are used to validate the real-time effectiveness of the proposed SSIDS cyber detection method.

PRECYSE: Cyber-attack Detection and Response for Industrial Control Systems

In this short paper, we present an integrated approach to detecting and mitigating cyber-attacks to modern interconnected industrial control systems. One of the primary goals of this approach is that it is cost effective, and thus whenever possible it builds on open-source security technologies and open standards, which are complemented with novel security solutions that address the specific challenges of securing critical infrastructures.

Synchrophasor-Based Islanding Detection for Distributed Generation Systems Using Systematic Principal Component Analysis Approaches

Systematic principal component analysis (PCA) methods are presented in this paper for reliable islanding detection for power systems with significant penetration of distributed generations (DGs), where synchrophasors recorded by Phasor Measurement Units (PMUs) are used for system monitoring. Existing islanding detection methods such as Rate-of-change-of frequency (ROCOF) and Vector Shift are fast for processing local information, however with the growth in installed capacity of DGs, they suffer from several drawbacks. Incumbent genset islanding detection cannot distinguish a system wide disturbance from an islanding event, leading to mal-operation. The problem is even more significant when the grid does not have sufficient inertia to limit frequency divergences in the system fault/stress due to the high penetration of DGs. To tackle such problems, this paper introduces PCA methods for islanding detection. Simple control chart is established for intuitive visualization of the transients. A Recursive PCA (RPCA) scheme is proposed as a reliable extension of the PCA method to reduce the false alarms for time-varying process. To further reduce the computational burden, the approximate linear dependence condition (ALDC) errors are calculated to update the associated PCA model. The proposed PCA and RPCA methods are verified by detecting abnormal transients occurring in the UK utility network.

Fluorescent Logic Systems for Sensing and Molecular Computation: Structure-Activity Relationships in Edge-Detection

Molecular logic-based computation continues to throw up new applications in sensing and switching, the newest of which is the edge detection of objects. The scope of this phenomenon is mapped out by the use of structure-activity relationships, where several structures of the molecules and of the objects are examined. The different angles and curvatures of the objects are followed with good-fidelity in the visualized edges, even when the objects are in reverse video.

A Novel Approach for Axle Detection in Bridge Weigh-In-Motion Systems

Bridge weigh-in-motion (B-WIM), a system that uses strain sensors to calculate the weights of trucks passing on bridges overhead, requires accurate axle location and speed information for effective performance. The success of a B-WIM system is dependent upon the accuracy of the axle detection method. It is widely recognised that any form of axle detector on the road surface is not ideal for B-WIM applications as it can cause disruption to the traffic (Ojio & Yamada 2002; Zhao et al. 2005; Chatterjee et al. 2006). Sensors under the bridge, that is Nothing-on-Road (NOR) B-WIM, can perform axle detection via data acquisition systems which can detect a peak in strain as the axle passes. The method is often successful, although not all bridges are suitable for NOR B-WIM due to limitations of the system. Significant research has been carried out to further develop the method and the NOR algorithms, but beam-and-slab bridges with deep beams still present a challenge. With these bridges, the slabs are used for axle detection, but peaks in the slab strains are sensitive to the transverse position of wheels on the beam. This next generation B-WIM research project extends the current B-WIM algorithm to the problem of axle detection and safety, thus overcoming the existing limitations in current state-of–the-art technology. Finite Element Analysis was used to determine the critical locations for axle detecting sensors and the findings were then tested in the field. In this paper, alternative strategies for axle detection were determined using Finite Element analysis and the findings were then tested in the field. The site selected for testing was in Loughbrickland, Northern Ireland, along the A1 corridor connecting the two cities of Belfast and Dublin. The structure is on a central route through the island of Ireland and has a high traffic volume which made it an optimum location for the study. Another huge benefit of the chosen location was its close proximity to a nearby self-operated weigh station. To determine the accuracy of the proposed B-WIM system and develop a knowledge base of the traffic load on the structure, a pavement WIM system was also installed on the northbound lane on the approach to the structure. The bridge structure selected for this B-WIM research comprised of 27 pre-cast prestressed concrete Y4-beams, and a cast in-situ concrete deck. The structure, a newly constructed integral bridge, spans 19 m and has an angle of skew of 22.7°.

FPGA-based Tabu Search for Detection in Large-Scale MIMO Systems

The increasing scale of Multiple-Input Multiple- Output (MIMO) topologies employed in forthcoming wireless communications standards presents a substantial implementation challenge to designers of embedded baseband signal processing architectures for MIMO transceivers. Specifically the increased scale of such systems has a substantial impact on the perfor- mance/cost balance of detection algorithms for these systems. Whilst in small-scale systems Sphere Decoding (SD) algorithms offer the best quasi-ML performance/cost balance, in larger systems heuristic detectors, such Tabu-Search (TS) detectors are superior. This paper addresses a dearth of research in architectures for TS-based MIMO detection, presenting the first known realisations of TS detectors for 4 × 4 and 10 × 10 MIMO systems. To the best of the authors’ knowledge, these are the largest single-chip detectors on record.

SIC and PIC multiuser detection for prefix-assisted DS-CDMA systems

In this paper we present iterative frequency-domain multiuser detection (MUD) receivers for the uplink transmission of direct sequence code division multiple access systems (DS-CDMA) that combine iterative block decision feedback equalization (IB-DFE) principles with interference cancelation techniques. Both successive interference cancelation (SIC) and parallel interference cancelation (PIC) structures are considered. Our performance results show that the proposed receiver structures have excellent bit error rate (BER) performances, that can be close to the single-user matched filter bound (MFB), even for fully loaded systems and severely time-dispersive channels1.

Frequency- domain multiuser detection for highly overloaded DS-CDMA systems

A DS-CDMA (Direct Sequence-Coded Division Multiple Access) system has maximum spectral efficiency if the system is fully loaded (i.e., the number of users is equal to the spreading factor) and we employ signals with bandwidth equal to the chip rate. However, due to implementation constraints we need to employ signals with higher bandwidth, decreasing the system’s spectral efficiency. In this paper we consider prefixassisted DS-CDMA systems with bandwidth that can be significantly above the chip rate. To allow high spectral efficiency we consider highly overloaded systems where the number of users can be twice the spreading factor or even more. To cope with the strong interference levels we present an iterative frequencydomain receiver that takes full advantage of the total bandwidth of the transmitted signals. Our performance results show that the proposed receiver can have excellent performance, even for highly overloaded systems. Moreover, the overall system performance can be close to the maximum theoretical spectral efficiency, even with transmitted signals that have bandwidth significantly above the chip rate.

Multiuser Detection for the Uplink of Prefix-Assisted DS-CDMA Systems Employing Multiple Transmit and Receive Antennas

In this paper we consider the uplink transmission within a DS-CDMA system employing CP-assisted (Cylic Prefix) block transmission techniques combined with spatial multiplexing techniques that require multiple antennas at both the transmitter and the receiver. We present an efficient frequency-domain receiver structure with iterative MUD (MultiUser Detection). The performance of the proposed receiver can be close to the single user matched filter bound, even for fully loaded systems and/or severely time-dispersive channels.

A Rapid Detection of Meat Spoilage using an Electronic Nose and Fuzzy-Wavelet systems

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. To address the rapid detection of meat spoilage microorganisms during aerobic or modified atmosphere storage, an electronic nose with the aid of fuzzy wavelet network has been considered in this research. The proposed model incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modelling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results against neural networks and neurofuzzy systems indicated that the proposed modelling scheme could be considered as a valuable detection methodology in food microbiology

Detection of quasi-periodic processes in complex systems: how do we quantitatively describe their properties?

It has been shown that in reality at least two general scenarios of data structuring are possible: (a) a self-similar (SS) scenario when the measured data form an SS structure and (b) a quasi-periodic (QP) scenario when the repeated (strongly correlated) data form random sequences that are almost periodic with respect to each other. In the second case it becomes possible to describe their behavior and express a part of their randomness quantitatively in terms of the deterministic amplitude–frequency response belonging to the generalized Prony spectrum. This possibility allows us to re-examine the conventional concept of measurements and opens a new way for the description of a wide set of different data. In particular, it concerns different complex systems when the ‘best-fit’ model pretending to be the description of the data measured is absent but the barest necessity of description of these data in terms of the reduced number of quantitative parameters exists. The possibilities of the proposed approach and detection algorithm of the QP processes were demonstrated on actual data: spectroscopic data recorded for pure water and acoustic data for a test hole. The suggested methodology allows revising the accepted classification of different incommensurable and self-affine spatial structures and finding accurate interpretation of the generalized Prony spectroscopy that includes the Fourier spectroscopy as a partial case.

Antibody Based Diagnostic for Detection Of Vibrios and their Biological Control using Antagonistic Bacteria in Macrobrachium Rosenbergii Larval Rearing Systems

The main objective of the work undertaken here was to develop an appropriate microbial technology to protect the larvae of M.rosenbergii in hatchery from vibriosis. This technology precisely is consisted of a rapid detection system of vibrios and effective antagonistic probiotics for the management of vibrios. The present work was undertaken with the realizations that to stabilize the production process of commercial hatcheries an appropriate, comprehensive and fool proof technology is required primarily for the rapid detection of Vibrio and subsequently for its management. Nine species of Vibrio have been found to be associated with larvae of M. rosenbergii in hatchery. Haemolytic assay of the Vibrio and Aeromonas on prawn blood agar showed that all isolates of V. alginolyticus and Aeromonas sp., from moribund, necrotized larve were haemolytic and the isolates of V.cholerae, V.splendidus II, V.proteolyticus and V.fluvialis from the larvae obtained from apparently healthy larval rearing systems were non-haemolytic. Hydrolytic enzymes such as lipase, chitinase and gelatinase were widespread amongst the Vibrio and Aeromonas isolates. Dominance of V.alginolyticus among the isolates from necrotic larvae and the failure in isolating them from rearing water strongly suggest that they infect larvae and multiply in the larval body and cause mortality in the hatchery. The observation suggested that the isolate V. alginolyticus was a pathogen to the larvae of M.rosenbergii. To sum up, through this work, nine species of Vibrio and genus Aeromonas associated with M.rosenbergii larval rearing systems could be isolated and segregated based on the haemolytic activity and the antibodies (PA bs) for use in diagnosis or epidemiological studies could be produced, based on a virulent culture of V.alginolyticus. This could possibly replace the conventional biochemical tests for identification. As prophylaxis to vibriosis, four isolates of Micrococcus spp. and an isolate of Pseudomonas sp. could be obtained which could possibly be used as antagonistic probiotics in the larval rearing system of M.rosenbergii.

Unusual voltage sag event detection in power systems

Three multivariate statistical tools (principal component analysis, factor analysis, analysis discriminant) have been tested to characterize and model the sags registered in distribution substations. Those models use several features to represent the magnitude, duration and unbalanced grade of sags. They have been obtained from voltage and current waveforms. The techniques are tested and compared using 69 registers of sags. The advantages and drawbacks of each technique are listed