Description:
Features extraction has always been crucial in rotary machines for Condition based machine health monitoring. Time-domain-segmentation being among the preliminary steps for further classification process plays a momentous role. Vibration signals from bearing are quasistationary in nature therefore calculation of constituent frequencies amplitudes in the vibration signal is dependent upon time-segmentation-window size. The proposed research confers the effects of time-segmentation window size on spectral features amplitudes calculation and its impacts on classification accuracy of the Artificial Neural Network (ANN). Using multi-size time-segmentation-window, for comprehensive spectral features calculation, ANN pattern classifier has been trained for enhanced classification. ANN learning assigns importance based relative weights to the links using supervised learning. Experimental results have shown that multi-size-window spectral features for ANN fault classifier perform efficiently for quasi-stationary bearing vibrations.
Description:
The ordered order-k Voronoi diagram is a popular generalization of the ordinary Voronoi diagram modeling ordered k nearest sites. Despite of the usefulness of the ordered order-k Voronoi diagram, its structural complexity and wealth of information captured result in poor readability. Most research has focused on computational complexity, and visualization/representation of the ordered order-k Voronoi diagram has received little attention. This paper attempts to represent the ordered order-k Voronoi diagram through its relationship with other higher order Voronoi diagrams. The proposed method highlights topo-logical relationships between/among higher order Voronoi diagram families, and enhances the readability of the ordered order-k diagram.
Description:
In rotary machines bearings are a primary cause of failure. In order to estimate the time before failure to provide information for timely bearing replacement strategies, condition-based machine health monitoring techniques are employed. This paper discusses a model for estimating the severity of bearing faults that can be used for residual bearing life estimation by processing the vibration signal. The proposed technique used in this model examines the spectral content of vibration signals across frequency bins and then fits Gaussian distributions to each frequency bin. With the use of these Gaussian models and training set examples with different fault severity levels, characteristic membership functions are constructed. This enables estimation of the severity levels of the bearing faults through a fuzzy-logic inspired process, whereby the severity level corresponds to the maximum of the set of corresponding membership functions. Thus based on discrete fault severity levels, trained Gaussian fittings of spectral bins and characteristic fault membership functions are capable to estimate the fault severity on a continuous scale.
Description:
ISO55000 is the International Organisation for Standardization (ISO) standard for asset management published in 2014. It stipulates that effective control and governance of assets by organizations is essential to realize value through managing risk and opportunity, in order to achieve the desired balance of cost, risk and performance. It is a challenge to industries on how to address this. This paper is on the issues and challenges of balancing cost, performance and risk in heavy haul rail asset management. Illustrative example from heavy haul network is used for this and on how to address some of the important challenges faced by heavy haul sector for managing life of rail assets.
Description:
Fully integrated electronic health records (EHR) provide healthcare providers and patients access to records across a health care system and promise efficient and effective provision of health care. However, fully integrated records have proven to be very expensive and difficult to establish. Currently. EHR's have been developed largely to accommodate Western medicine events. These barriers impact on the introduction of EHR's in Sri Lanka, where health budgets are already stretched and Ayurvedic medicine is routinely practiced alongside Allopathic medicine. This article identifies requirements for EHR in the Sri Lankan context and advances a model for the introduction of EHR's that suits that context. The model is justified by drawing on insights and experiences with EHR in Western nations.
Description:
Fully integrated electronic health records (EHR) provide healthcare providers and patients access to records across a health care system and promise efficient and effective provision of health care. However, fully integrated records have proven to be very expensive and difficult to establish. Currently. EHR's have been developed largely to accommodate Western medicine events. These barriers impact on the introduction of EHR's in Sri Lanka, where health budgets are already stretched and Ayurvedic medicine is routinely practiced alongside Allopathic medicine. This article identifies requirements for EHR in the Sri Lankan context and advances a model for the introduction of EHR's that suits that context. The model is justified by drawing on insights and experiences with EHR in Western nations.
Description:
To ensure customer satisfaction and greater market acceptance, voice over Wi-Fi networks must ensure voice quality under various network parameters, configurations and traffic conditions, and other practical effects, e.g., channel noise, and capturing effects. An accurate voice capacity estimation model considering these factors can greatly assist network designers. In the current work, we propose an analytical model to estimate voice over Internet Protocol (VoIP) capacity over Wi-Fi networks addressing these issues. We employ widely used ITU-T E-model to assess voice quality and VoIP call capacity is presented in the form of an optimization problem with voice quality requirement as a constraint. In particular, we analyze delay and loss in channel access and queue, and their impacts on voice quality. The proposed capacity model is first developed for a single hop wireless local area network (WLAN) and then extended for multihop scenarios. To model real network scenario closely, we also consider channel noise and capture effect, and analyze the impacts of transmission range, interference range, and WLAN radius. In absence of any existing call capacity model that considers all the above factors concomitantly, our proposed model will be extremely useful to network designers and voice capacity planners.
Description:
We develop a realistic pricing modeling for dynamic spectrum access network considering a number of factors that influence real world trading. Our model incorporates the reputation of sellers, incentive mechanism to attract buyers, timing requirement of the contract, signal quality along with bandwidth size and price of the spectrum resources. Reputation information is accumulated from self experience and/or from the recommendations of other users. Trustworthiness of the recommending SUs is also modeled in this paper. An incentive mechanism is applied to encourage in dissemination of recommendations and to attract the buyers by providing discounts. A utility function for the spectrum trading is modeled such that a buyer can trade with the seller which maximizes its utility based on the above factors and the pricing solution is obtained using the market equilibrium model. The performance of the proposed model is evaluated using simulation results which show that our model benefits both the sellers and the buyers in terms of profit and throughput, respectively.
Description:
One of the most challenging issues in cognitive radio networks is to dynamically access the radio frequency spectrum in an uninterrupted manner. To achieve this, omniscient allocation of spectrum bands among cognitive radio users is crucial. Most of the existing spectrum allocation methods select a band from a pool according to the service requirements of a single user, neglecting the demand of multiple users. In this paper, we introduce a collaborative framework for allocating multiple bands among multiple secondary users. The proposed method defines a capacity of service metric based on the optimal sensing parameters and utilizes this metric to assign distinct bands to all or highest possible number of contending users. Performance evaluation suggests that the proposed method exhibits significant superiority over conventional approaches in terms of improved throughput and spectrum utilization, reduced interference loss and collision, and hence, enhances dynamic spectrum access and sharing capabilities.
Description:
Finding the best deployment configuration that maximises energy efficiency while guaranteeing system performance of cloud applications is an extremely challenging task. It requires the evaluation of system performance and energy consumption under a wide variety of realistic workloads and deployment configurations. This paper demonstrates StressCloud, an automatic performance and energy consumption analysis tool for cloud applications in real-world cloud environments. StressCloud supports 1) the modelling of realistic cloud application workloads, 2) the automatic generation and running of load tests, and 3) the profiling of system performance and energy consumption.
Description:
Automatic 3D extraction of building roofs from remotely sensed data is important for many applications including city modeling. This paper proposes a new method for automatic 3D roof extraction through an effective integration of LIDAR (Light Detection And Ranging) data and multispectral orthoimagery. Using the ground height from a DEM (Digital Elevation Model), the raw LIDAR points are separated into two groups. The first group contains the ground points that are exploited to constitute a `ground mask'. The second group contains the non-ground points which are segmented using an innovative image line guided segmentation technique to extract the roof planes. The image lines extracted from the grey-scale version of the orthoimage are classified into several classes such as `ground', `tree', `roof edge' and `roof ridge' using the ground mask and colour and texture information from the orthoimagery. During roof plane extraction the lines from the later two classes are used to fit roof planes to the neighbouring non-ground LIDAR points. Finally, a new rule-based procedure is applied to remove planes constructed on trees. Experimental results show that the proposed method successfully removes vegetation and offers high extraction rates.
Description:
Analytical studies of Medium Access Control (MAC) layer protocols can be used to improve the performance of multi-hop Wireless Sensor Networks (WSNs) in the presence of hidden stations. The selected MAC layer protocol should conform to the distributed nature of the WSNs. The IEEE 802.11 MAC layer with Distributed Coordination Function (DCF) is well suited to WSNs. Analytical studies of IEEE 802.11 DCF in the presence of hidden stations in multi-hop WSNs is very crucial as it is widely used. In this paper, an analytical model considering hidden stations in a multi-hop WSN has been developed to study the cross layer performance of IEEE 802.11 DCF under a deterministic routing protocol. Using this model, theoretically measurements like probability of collision, medium access delay, end to end success probability, and end to end delay of each sensor node in the network can be achieved. Accuracy of the analytical model has been verified with simulation results. The model can be used to determine whether a specific WSN can achieve the expected performance.
Description:
Abstract: The overall objective of this work is to develop a system composed of master, slave and a control system for special medical applications. A PROMIS (Pprime RObot for Minimally Invasive Surgery) system is designed to be cost-effective with a less complication of use and an application-specific for collaborative operations between the surgeon and the robot. This paper focuses on the introduction of a motion safety control methodology for a haptic device. The haptic device is used as a master with a parallel spherical architecture (SPM). The introduced control methodology is based on the workspace of the medical application. Three areas of the workspace are defined with a consideration of the degree of security. An algorithm that constantly keeps the mobile platform in a safe region, when the surgeon moves it, is presented and explained. The developed algorithm runs in real-time using a programmable logic controller (PLC). The control strategy of the haptic device was successfully tested and validated experimentally.
Description:
This paper presents a new segmentation technique to use LIDAR point cloud data for automatic extraction of building roof planes. The raw LIDAR points are first classified into two major groups: ground and non-ground points. The ground points are used to generate a 'building mask' in which the black areas represent the ground where there are no laser returns below a certain height. The non-ground points are segmented to extract the planar roof segments. First, the building mask is divided into small grid cells. The cells containing the black pixels are clustered such that each cluster represents an individual building or tree. Second, the non-ground points within a cluster are segmented based on their coplanarity and neighbourhood relations. Third, the planar segments are refined using a rule-based procedure that assigns the common points among the planar segments to the appropriate segments. Finally, another rule-based procedure is applied to remove tree planes which are generally small in size and randomly oriented. Experimental results on three Australian sites have shown that the proposed method offers high building detection and roof plane extraction rates.
Description:
This paper presents an investigative study in which data were gathered and used in underground mining to improve the planned maintenance program and reliability of the shearer loader in the underground mining. A cost effective maintenance and operation strategy and practices is mandatory to meet the production demand and the required level of service of this critical asset of the plant. The study conducted and presented in this paper includes a detailed review of failure history data and the use of analytical technique available to understand failure characteristics and its effect on the throughput and the overall performance of the longwall operation. This is to achieve further productivity increases to meet business goals. Analytical tools such as Failure Mode and Effect and Criticality Analysis (FMECA) and Weibull analysis were used in this investigation. The study has highlighted the criticality of some failures and the actions needed in this industrial case to improve the reliability and planned maintenance for a better mining productivity.
Description:
Fibre Bragg Grating (FBG) sensors are extremely sensitive to changes of strain, and are therefore an extremely useful candidate for Structural Health Monitoring (SHM) systems of composite structures. Sensitivity of FBGs to strain gradients originating from damage was observed as an indicator of initiation and propagation of damage in composite structures. To date there have been numerous research works done on distorted FBG spectra due to damage accumulation under controlled environments. Unfortunately, a number of related unresolved problems remain in FBG-based SHM systems development, making the present SHM systems unsuitable for real life applications. This paper reveals a novel configuration of FBG sensors to acquire strain reading and an integrated statistical approach to analyse data in real time. The proposed configuration has proven its capability to overcome practical constraints and the engineering challenges associated with FBG-based SHM systems. A fixed filter decoding system and an integrated artificial neural network algorithm for extracting strain from embedded FBG sensor were proposed and experimentally proved. Furthermore, the laboratory level experimental data was used to verify the accuracy of the system and it was found that the error levels were less than 0.3% in strain predictions.
Description:
Runtime anomalies occurring to service-based systems (SBSs) must be located and fixed in a timely manner in order to guarantee successful delivery of outcomes in response to user requests. Monitoring all component services constantly is impractical due to excessive resource consumption. Inspecting all component services upon anomalies is time-consuming and thus also impractical. In this work, we propose a novel approach that employs spectrum-based fault localisation techniques to locate runtime anomalies in SBSs. Large-scale experiments are conducted and experimental results are presented to demonstrate the effectiveness and efficiency of the proposed approach.
Description:
Secondary service providers can buy spectrum resources from primary service providers for a short or long period of time and exploit it to solve the problem of spectrum scarcity. This buying decision of spectrum buyers can depend on several factors including pricing of the spectrum, reputation of a seller, and duration of the contract and spectrum quality. However, existing pricing models for dynamic spectrum access consider mainly bandwidth which makes them unsuitable for real-world trading. In this paper, we consider these issues related to the pricing of spectrum sale in terms of microeconomic theories. First, we consider reputation of spectrum sellers and update it dynamically by considering a buyer's own trading experience with the sellers and collecting recommendations on sellers from other buyers. Second, trustworthiness of recommenders as well as incentive to encourage recommendations are modeled. Third, contract duration and spectrum quality are incorporated such that a buyer's utility is formulated as a function of buyer's resource requirement, reputation of seller and trustworthiness of recommenders. Fourth, the model is analyzed using dynamic pricing of the market and the solution is obtained using market equilibrium. Results demonstrate the superiority of our model over the existing microeconomic models for dynamic spectrum trading.
Description:
Abstract—Gene Regulatory Network (GRN) plays an important role in the understanding of complex biological systems. In most cases, high throughput microarray gene expression data is used for finding these regulatory relationships among genes. In this paper, we present a novel approach, based on decoupled SSystem model, for reverse engineering GRNs. In the proposed method, the genetic algorithm used for scoring the networks contains several useful features for accurate network inference, namely a Prediction Initialization (PI) algorithm to initialize the individuals, a Flip Operation (FO) for better mating of values and a restricted execution of Hill Climbing Local Search over few individuals. It also includes a novel refinement technique which utilizes the fit solutions of the genetic algorithm for optimizing sensitivity and specificity of the inferred network. Comparative studies and robustness analysis using standard benchmark data set show the superiority of the proposed method.
Description:
This paper presents a newly developed parallel gripper prototype capable of sensing grasp force, tangential force and slippage. In this design the gripper itself is used as part of the sensing strategy rather than just being simply a structural support for other sensors. The sensing capability of this gripper is simple in design and reliable. The sensing strategy can be customised to specific applications such as the ability to handle large loads while maintaining its ability to detect slippage as reliably as when handling lighter loads.
Description:
Spectrum utilization in cognitive radio ad hoc network is a critical task due to the fluctuation of spectrum availability temporally and spatially. Reusing the same channel spatially can effectively improve the spectrum utilization as well as reduce the delay in switching and coordination in different channels. In this paper, a dynamic spectrum sharing method is proposed which allows multiple secondary users to reside in the same channel and use the channel concurrently to maximize the spectrum utilization exploiting variable transmission power and location information, while guaranteeing acceptable level of interference protection to the primary users. Results show that the proposed method successfully outperforms the existing method in maximizing the number of concurrent transmissions as well as the spectrum utilization.