A hybrid simulation framework to assess the impact of renewable generators on a distribution network

With an increasing number of small-scale renewable generator installations, distribution network planners are faced with new technical challenges (intermittent load flows, network imbalances…). Then again, these decentralized generators (DGs) present opportunities regarding savings on network infrastructure if installed at strategic locations. How can we consider both of these aspects when building decision tools for planning future distribution networks? This paper presents a simulation framework which combines two modeling techniques: agent-based modeling (ABM) and particle swarm optimization (PSO). ABM is used to represent the different system units of the network accurately and dynamically, simulating over short time-periods. PSO is then used to find the most economical configuration of DGs over longer periods of time. The infrastructure of the framework is introduced, presenting the two modeling techniques and their integration. A case study of Townsville, Australia, is then used to illustrate the platform implementation and the outputs of a simulation.

Common DC link in residential LV network to improve the penetration level of Small-Scale Embedded Generators

This paper presents a new approach for network upgrading to improve the penetration level of Small Scale Generators in residential feeders. In this paper, it is proposed that a common DC link can be added to LV network to alleviate the negative impact of increased export power on AC lines, allowing customers to inject their surplus power with no restrictions to the common DC link. In addition, it is shown that the proposed approach can be a pathway from current AC network to future DC network.

Rule-based transit signal priority control method using a real-time transit travel time prediction model

An advanced rule-based Transit Signal Priority (TSP) control method is presented in this paper. An on-line transit travel time prediction model is the key component of the proposed method, which enables the selection of the most appropriate TSP plans for the prevailing traffic and transit condition. The new method also adopts a priority plan re-development feature that enables modifying or even switching the already implemented priority plan to accommodate changes in the traffic conditions. The proposed method utilizes conventional green extension and red truncation strategies and also two new strategies including green truncation and queue clearance. The new method is evaluated against a typical active TSP strategy and also the base case scenario assuming no TSP control in microsimulation. The evaluation results indicate that the proposed method can produce significant benefits in reducing the bus delay time and improving the service regularity with negligible adverse impacts on the non-transit street traffic.

Small signal stability analysis of a DFIG based wind power system with tuned damping controller under super/sub-synchronous mode of operation

This paper focuses on the super/sub-synchronous operation of the doubly fed induction generator (DFIG) system. The impact of a damping controller on the different modes of operation for the DFIG based wind generation system is investigated. The co-ordinated tuning of the damping controller to enhance the damping of the oscillatory modes using bacteria foraging (BF) technique is presented. The results from eigenvalue analysis are presented to elucidate the effectiveness of the tuned damping controller in the DFIG system. The robustness issue of the damping controller is also investigated

An optimal under-frequency load shedding strategy considering distributed generators and load static characteristics

The well-established under-frequency load shedding (UFLS) is deemed to be the last of effective remedial measures against a severe frequency decline of a power system. With the ever-increasing size of power systems and the extensive penetration of distributed generators (DGs) in power systems, the problem of developing an optimal UFLS strategy is facing some new challenges. Given this background, an optimal UFLS strategy for a distribution system with DGs and load static characteristics taken into consideration is developed. Based on the frequency and the rate of change of frequency, the presented strategy consists of several basic rounds and a special round. In the basic round, the frequency emergency can be alleviated by quickly shedding some loads. In the special round, the frequency security can be maintained, and the operating parameters of the distribution system can be optimized by adjusting the output powers of DGs and some loads. The modified IEEE 37-node test feeder is employed to demonstrate the essential features of the developed optimal UFLS strategy in the MATLAB/SIMULINK environment.

Social signal processing for pain monitoring using a hidden conditional random field

utomatic pain monitoring has the potential to greatly improve patient diagnosis and outcomes by providing a continuous objective measure. One of the most promising methods is to do this via automatically detecting facial expressions. However, current approaches have failed due to their inability to: 1) integrate the rigid and non-rigid head motion into a single feature representation, and 2) incorporate the salient temporal patterns into the classification stage. In this paper, we tackle the first problem by developing a “histogram of facial action units” representation using Active Appearance Model (AAM) face features, and then utilize a Hidden Conditional Random Field (HCRF) to overcome the second issue. We show that both of these methods improve the performance on the task of pain detection in sequence level compared to current state-of-the-art-methods on the UNBC-McMaster Shoulder Pain Archive.

Optimized strategy for integrated traffic and transit signal control

This paper proposes a unique and innovative approach to integrate transit signal priority control into a traffic adaptive signal control strategy. The proposed strategy was named OSTRAC (Optimized Strategy for integrated TRAffic and TRAnsit signal Control). The cornerstones of OSTRAC include an online microscopic traffic f low prediction model and a Genetic Algorithm (GA) based traffic signal timing module. A sensitivity analysis was conducted to determine the critical GA parameters. The developed traffic f low model demonstrated reliable prediction results through a test. OSTRAC was evaluated by comparing its performance to three other signal control strategies. The evaluation results revealed that OSTRAC efficiently and effectively reduced delay time of general traffic and also transit vehicles.

Spectrum sensing optimisation for dynamic primary user signal

We propose a multi-layer spectrum sensing optimisation algorithm to maximise sensing efficiency by computing the optimal sensing and transmission durations for a fast changing, dynamic primary user. Dynamic primary user traffic is modelled as a random process, where the primary user changes states during both the sensing period and transmission period to reflect a more realistic scenario. Furthermore, we formulate joint constraints to correctly reflect interference to the primary user and lost opportunity of the secondary user during the transmission period. Finally, we implement a novel duty cycle based detector that is optimised with respect to PU traffic to accurately detect primary user activity during the sensing period. Simulation results show that unlike currently used detection models, the proposed algorithm can jointly optimise the sensing and transmission durations to simultaneously satisfy the optimisation constraints for the considered primary user traffic.

Digital social signal processing - theorectical underpinning and research agenda

Organizations make increasingly use of social media in order to compete for customer awareness and improve the quality of their goods and services. Multiple techniques of social media analysis are already in use. Nevertheless, theoretical underpinnings and a sound research agenda are still unavailable in this field at the present time. In order to contribute to setting up such an agenda, we introduce digital social signal processing (DSSP) as a new research stream in IS that requires multi-facetted investigations. Our DSSP concept is founded upon a set of four sequential activities: sensing digital social signals that are emitted by individuals on social media; decoding online data of social media in order to reconstruct digital social signals; matching the signals with consumers’ life events; and configuring individualized goods and service offerings tailored to the individual needs of customers. We further contribute to tying loose ends of different research areas together, in order to frame DSSP as a field for further investigation. We conclude with developing a research agenda.

Utilizing Wide-Area Signals for off-center SVCs to damp interarea oscillations

Wide-Area Measurement Systems (WAMS) provide the opportunity of utilizing remote signals from different locations for the enhancement of power system stability. This paper focuses on the implementation of remote measurements as supplementary signals for off-center Static Var Compensators (SVCs) to damp inter-area oscillations. Combination of participation factor and residue method is used for the selection of most effective stabilizing signal. Speed difference of two generators from separate areas is identified as the best stabilizing signal and used as a supplementary signal for lead-lag controller of SVCs. Time delays of remote measurements and control signals is considered. Wide-Area Damping Controller (WADC) is deployed in Matlab Simulink framework and is tested under different operating conditions. Simulation results reveal that the proposed WADC improve the dynamic characteristic of the system significantly.

MMP-9 and the epidermal growth factor signal pathway in non-small cell lung cancer

Background Matrix metalloproteinase (MMP)-9 is an endopeptidase that digests basement membrane type-IV collagen. Enhanced expression has been related to tumour progression in a number of systems. The control of MMP expression is complex, but recently epidermal growth actor receptor (EGFR) activity has been implicated in up-regulation of MMP-9 in tumour cells in vitro. Aims To evaluate interrelations between MMP-9 and EGFR expression in non-small cell lung cancer (NSCLC) and to assess the impact of expression on survival. Methods This is a retrospective study of 152 patients who underwent resection for stage I-IIIa NSCLC with a post-operative survival >60 days. Minimum follow-up was 2 years. Standard ABC immunohistochemistry was performed on 4μm paraffin-embedded sections from the tumour periphery using monoclonal antibodies to MMP-9 and EGFR. Results: MMP-9 was expressed in the tumour cells of 79/152 (52%) cases. EGFR expression was found in 86/152 (57%) cases [membranous 51/152 (34%), cytoplasmic 35/152 (23%)]. MMP-9 expression was associated with poor outcome (p=0.04). Membranous, cytoplasmic and overall EGFR expression were not associated with outcome (p=0.29, p=0.85 and p=0.41 respectively). There was a strong correlation between MMP-9 expression and EGFR expression (p=0.001) and EGFR membranous expression (p=0.01) but not with cytoplasmic EGFR expression (p=0.28). Co-expression of MMP-9 and EGFR (36%) conferred a worse prognosis (p=0.003). Subset analysis revealed only MMP-9 and membranous EGFR co-expression (22%) was associated with poor outcome (p=0.008). Conclusions Our results show that MMP-9 and EGFR are co-expressed in NSCLC. This finding suggests the EGFR signalling pathway may play an important role in the invasive behaviour of NSCLC via specific upregulation of MMP-9. The co-expression of these markers also confers a poor prognosis.

An extracellular signal-regulated kinase 2 survival pathway mediates resistance of human mesothelioma cells to asbestos-induced injury

We hypothesized that normal human mesothelial cells acquire resistance to asbestos-induced toxicity via induction of one or more epidermal growth factor receptor (EGFR) - linked survival pathways (phosphoinositol-3-kinase/AKT/ mammalian target of rapamycin and extracellular signal - regulated kinase [ERK] 1/2) during simian virus 40 (SV40) transformation and carcinogenesis. Both isolated HKNM-2 mesothelial cells and a telomerase-immortalized mesothelial line (LP9/TERT-1) were more sensitive to crocidolite asbestos toxicity than an SV40 Tag-immortalized mesothelial line (MET5A) and malignant mesothelioma cell lines (HMESO and PPM Mill). Whereas increases in phosphorylation of AKT (pAKT) were observed in MET5A cells in response to asbestos, LP9/TERT-1 cells exhibited dose-related decreases in pAKT levels. Pretreatment with an EGFR phosphorylation or mitogen-activated protein kinase kinase 1/2 inhibitor abrogated asbestos-induced phosphorylated ERK (pERK) 1/2 levels in both LP9/TERT-1 and MET5A cells as well as increases in pAKT levels in MET5A cells. Transient transfection of small interfering RNAs targeting ERK1, ERK2, or AKT revealed that ERK1/2 pathways were involved in cell death by asbestos in both cell lines. Asbestos-resistant HMESO or PPM Mill cells with high endogenous levels of ERKs or AKT did not show dose-responsive increases in pERK1/ERK1, pERK2/ERK2, or pAKT/AKT levels by asbestos. However, small hairpin ERK2 stable cell lines created from both malignant mesothelioma lines were more sensitive to asbestos toxicity than shERK1 and shControl lines, and exhibited unique, tumor-specific changes in endogenous cell death - related gene expression. Our results suggest that EGFR phosphorylation is causally linkedto pERK and pAKT activation by asbestos in normal and SV40 Tag - immortalized human mesothelial cells. They also indicate that ERK2 plays a role in modulating asbestos toxicity by regulating genes critical to cell injury and survival that are differentially expressed in human mesotheliomas.

Mobile silencing in plants: what is the signal and what defines the target

RNA-mediated silencing in plants can spread from cell to cell and over a long distance, and such mobile silencing has been extensively studied in the past decade. However, major questions remain as to what is the exact nature of the mobile silencing signals, how the components of the RNA-directed DNA methylation pathway are involved, and why systemic spread of silencing has only been observed for transgenes but not endogenous genes. In this review, we provide an overview of the current knowledge on mobile gene silencing in plants and present a model where systemic silencing involves long nuclear RNA transcripts that serve as a template to amplify primary siRNA signals.

Hearing loss and a supportive tactile signal in a navigation system : effects on driving behavior and eye movements

An on-road study was conducted to evaluate a complementary tactile navigation signal on driving behaviour and eye movements for drivers with hearing loss (HL) compared to drivers with normal hearing (NH). 32 participants (16 HL and 16 NH) performed two preprogrammed navigation tasks. In one, participants received only visual information, while the other also included a vibration in the seat to guide them in the correct direction. SMI glasses were used for eye tracking, recording the point of gaze within the scene. Analysis was performed on predefined regions. A questionnaire examined participant's experience of the navigation systems. Hearing loss was associated with lower speed, higher satisfaction with the tactile signal and more glances in the rear view mirror. Additionally, tactile support led to less time spent viewing the navigation display.

Development of a new signal processing diagnostic tool for vibration signals acquired in transient conditions

The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.