Monitoring reliability for a gamma distribution with a double progressive mean control chart

Control charting technique for time between events (TBE) is very important in high-yield processes for monitoring reliability. For a regularly maintained system, the interfailure times can be modeled by a gamma distribution. This article proposes a new control chart based on the double progressive mean statistic for monitoring the time between k (≥1 ) failures of a maintained gamma distributed system (referred as DPM-TBE chart). The performance of the proposed scheme is measured in terms of the average run-length (ARL) for the case when the scale parameter is known as well as when it is unknown and is estimated from an in-control (IC) reference sample. A comparison study with other TBE charts shows that the DPM-TBE chart is more effective. In addition, the proposed chart is shown to be very robust for large shifts when the true distribution of time between failures is a Weibull or a lognormal. Finally, an illustrative example is given to demonstrate the implementation of the proposed chart.     

A double exponentially weighted moving average control chart for monitoring COM‐Poisson attributes

The Conway‐Maxwell‐Poisson (COM‐Poisson) distribution is a two‐parameter generalization of the Poisson distribution, which can be used for overdispersed or underdispersed count data and also contains the geometric and Bernoulli distributions as special cases. This article presents a double exponentially weighted moving average control chart with steady‐state control limits to monitor COM‐Poisson attributes (regarded as CMP‐DEWMA chart). The performance of the proposed control chart has been evaluated in terms of the average, the median, and the standard deviation of the run‐length distribution. The CMP‐DEWMA control chart is studied not only to detect shifts in each parameter individually but also in both parameters simultaneously. The design parameters of the proposed chart are provided, and through a simulation study, it is shown that the CMP‐DEWMA chart is more effective than the EWMA chart at detecting downward shifts of the process mean. Finally, a real data set is presented to demonstrate the application of the proposed chart.     

Cyber risk management for autonomous passenger ships using threat-informed defense-in-depth

Recent innovations in the smart city domain have led to the proposition of a new mode of transportation utilizing Autonomous Passenger Ships (APS) or ferries in inland waterways. The novelty of the APS concept influenced the cyber risk paradigm and led to different considerations regarding attack objectives, techniques as well as risk management approaches. The main factor that has led to this is the autoremote operational mode, which refers to autonomous operations and remote supervision and control in case of emergency. The autoremote operational mode influences the risk of cyber attacks due to the increased connectivity and reliance on technology for automating navigational functions. On the other hand, the presence of passengers without crew members imposes a safety risk factor in cyber attacks. In this paper, we propose a new cyber risk management approach for managing the cyber risks against cyber physical systems in general and Autonomous Passenger Ships in particular. Our proposed approach aims to improve the Defense-in-Depth risk management strategy with additional components from the Threat-Informed Defense strategy allowing for more evolved cyber risk management capabilities. Moreover, we have utilized the proposed cyber risk management approach for the proposition of a cybersecurity architecture for managing the cyber risks against an APS use case named milliAmpere2. Additionally, we present our results after conducting a Systematic Literature Review (SLR) in cybersecurity evaluation in the maritime domain. Then, the findings of the SLR were utilized for a suitable evaluation of the proposed risk management approach. Our findings suggest that our proposed risk management approach named Threat-Informed Defense-in-Depth is capable of enriching several risk management activities across different stages in the system development life cycle. Additionally, a comprehensive evaluation of the cybersecurity posture of milliAmpere2 has been conducted using several approaches including risk evaluation, simulation, checklist, and adversary emulation. Our evaluation has uncovered several limitations in the current cybersecurity posture and proposed actions for improvement.

     

Capsule endoscopy image analysis using texture information from various colour models

Wireless capsule endoscopy (WCE) is a novel imaging technique that is gradually gaining ground as it enables the non-invasive and efficacious visualization of the digestive track, and especially the entire small bowel including its middle part. However, the task of reviewing the vast amount of images produced by a WCE examination is a burden for the physicians. To tackle this major drawback, an innovative scheme for discriminating endoscopic images related to one of the most common intestinal diseases, ulceration, is presented here. This new approach focuses on colour-texture features in order to investigate how the structure information of healthy and abnormal tissue is distributed on RGB, HSV and CIE Lab colour spaces. The WCE images are pre-processed using bidimensional ensemble empirical mode decomposition so as to facilitate differential lacunarity analysis to extract the texture patterns of normal and ulcerous regions. Experimental results demonstrated promising classification performance (mean accuracy>95%), exhibiting a high potential towards automatic WCE image analysis.     

Deploying AL-FEC protection with online algorithms for multicast services over cellular networks

Reliability control is a key concern on the evolution of mobile multicast services. To this direction, the use of forward error correction (FEC) on the application layer is widely adopted in several mobile multicast standards. FEC is a feedback free error control method, where the transmitter introduces in advance redundant information within the source data to enable receivers recovering arbitrary data erasures. On multicast delivery where retransmission-based error recovery methods are not efficient, the most suitable error control method is the use of application layer forward error correction (AL-FEC) codes. In this work, we introduce novel AL-FEC deployment policies over mobile multicast environments utilizing online algorithms. We aim at the efficient application of AL-FEC protection with RaptorQ codes over multicast delivery in the context of competitive analysis. We provide a competitiveness analysis model of AL-FEC application over mobile multicast environments. Furthermore, we propose two online algorithms adjusting the introduced redundancy of AL-FEC protection according to several FEC encoding parameters and constraints of mobile multicast delivery.     

Random access prediction structures for light field video coding with MV-HEVC

Multimedia Tools and Applications - Computational imaging and light field technology promise to deliver the required six-degrees-of-freedom for natural scenes in virtual reality. Already existing...     

Nonparametric triple exponentially weighted moving average signed-rank control chart for monitoring shifts in the process location

Nonparametric (or distribution-free) control charts are used for monitoring processes where there is a lack of knowledge about the underlying distribution. In this article, a triple exponentially weighted moving average control chart based on the signed-rank statistic (referred as TEWMA-SR chart) is proposed for monitoring shifts in the location parameter of an unknown, but continuous and symmetric, distribution. The run-length characteristics of the proposed chart are evaluated performing Monte Carlo simulations. A comparison study with other existing nonparametric control charts based on the signed-rank statistic, the TEWMA sign chart, and the parametric TEWMA-$\overline{X}$ chart indicates that the proposed chart is more effective in detecting small shifts, while it is comparable with the other charts for moderate and large shifts. Finally, two illustrative examples are provided to demonstrate the application of the proposed chart.     

Monitoring of time between events with a double generally weighted moving average control chart

Monitoring of time between events (TBE) instead of the number of events is used in high‐quality processes where the events occur rarely. This article presents a double generally weighted moving average control chart with a lower time‐varying control limit to monitor the TBE (regarded as DGWMA‐TBE chart). The design parameters of the proposed chart are provided, and through a simulation study, it is shown that the DGWMA‐TBE chart is more effective than the DEWMA and GWMA charts in detecting moderate to large shifts. Furthermore, the DGWMA‐TBE chart is very robust for the same range of shifts when the TBE observations follow a Weibull or a lognormal distribution. Finally, examples are also presented to enhance the performance of the proposed chart.     

A hierarchical method to integrated solvent and process design of physical CO2 absorption using the SAFT‐γ Mie approach

Molecular‐level decisions are increasingly recognized as an integral part of process design. Finding the optimal process performance requires the integrated optimization of process and solvent chemical structure, leading to a challenging mixed‐integer nonlinear programming (MINLP) problem. The formulation of such problems when using a group contribution version of the statistical associating fluid theory, SAFT‐γ Mie, to predict the physical properties of the relevant mixtures reliably over process conditions is presented. To solve the challenging MINLP, a novel hierarchical methodology for integrated process and solvent design (hierarchical optimization) is presented. Reduced models of the process units are developed and used to generate a set of initial guesses for the MINLP solution. The methodology is applied to the design of a physical absorption process to separate carbon dioxide from methane, using a broad selection of ethers as the molecular design space. The solvents with best process performance are found to be poly(oxymethylene)dimethylethers. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3249–3269, 2015