Markovian Analysis Research Articles

Elementary depinning processes of magnetic domain walls under fields and currents.

The probability laws associated to domain wall depinning under fields and currents have been studied in NiFe and FePt nanowires. Three basic domain wall depinning processes, associated to different potential landscapes, are found to appear identically in those systems with very different anisotropies. We show that these processes constitute the building blocks of any complex depinning mechanism. A Markovian analysis is proposed, that provides a unified picture of the depinning mechanism and an insight into the pinning potential landscape.

Adaptive Zone-Based Bandwidth Management in IEEE 802.16j Multi- Hop Relay Network

By comparing with the characteristics of the traditional mobile Quality-of-Service mechanisms, the idea of zone-based bandwidth allocation for mobile users in the IEEE 802.16j multi-hop relay network (IEEE 802.16-MR) is proposed in the paper. The zone of a mobile user includes the current relay station and its neighboring relay stations within the zone size in hop count. Bandwidth allocation is made for the mobile user roaming within the zone, and calculation of the required bandwidth is presented in the paper. Adaptive selection of the zone size fit for user mobility is the main focus of the paper. Markovian analysis is used to determine the proper zone size. Simulation study has demonstrated the effectiveness of the adaptive zone scheme.

Is Joint-Audit Regulation Likely to Mitigate the Audit Market Concentration in the Long Run? The French Experience

Policy makers have considered joint-audits as a solution to mitigate the audit market concentration and the “systemic” risk associated with Big 4 auditors. Using the French system as a relevant joint-audit laboratory, we implement a Markovian analysis to infer the long-term market structure by considering that audit clients chose between different types of joint-audit combinations. Main findings support the view that the French joint-audit system is effective in maintaining market openness, and in mitigating the Big 4 domination in the long run. The “mixed” joint-audit arrangement remains the choice of a majority of audit clients. Also, joint-audits involving two non-Big 4 auditors would outperform those made of two Big 4 auditors, and Mid-Tier auditors seem to play a significant role on that point. Overall, this study supports the European Commission’s (2011) position on the potential benefits of joint-audits in mitigating the market concentration; it also suggests that it might not be necessary to impose “mixed” joint-audits to achieve that objective.

Multiple sclerosis lesion detection with local multimodal Markovian analysis and cellular automata ‘GrowCut’

Abstract Multiple sclerosis affect over 2.5 million people world‐wide. This autoimmune disease of the central nervous system causes damage to the insulating myelin sheaths around the axons in the brain. The disease progresses at different rates in different people and can have periods of remission and relapse. A fast and accurate method for evaluating the number and size of MS lesions in the brain is a key component in evaluating the progress of the disease and the efficacy of treatments. Manual segmentation is slow and difficult and the results can be somewhat subjective. It requires a physician to consider several MRI slices across multiple modalities. The power and speed of computer systems provide an obvious avenue to help. While many automated methods exist, they have not reached human‐level accuracy of the segmentation results. There exists a need for a robust, fast and accurate method to improve the results of automatic MS lesion segmentation methods. We propose a post‐processing stage to improve the segmentation results of an existing system. It uses two different strategies to improve the segmentation results of an automated system based on whole‐brain tissue classification and lesion detection. The first strategy leverages the current processing system at a granularity finer than the whole brain to detect lesions at a local level. This reflects the way that a physician considers only a part of the brain at a time. It then combines the series of local results to produce a whole‐brain segmentation. This approach better captures the local lesion properties and produces encouraging results, with a general improvement in the detection rate of lesions. The second method dives deeper and looks at the individual voxel level. Just as a physician might look more closely at a lesion, it considers the local neighborhood around a lesion detection. The method selects seed points from the existing results and uses a region growing method based on cellular automata. It grows the lesion areas based on a local neighborhood similarity in intensity. Over the eleven patients examined, some results improved over the base case and show the efficiency of the proposed approach.

A Markovian analysis of bacterial genome sequence constraints

The arrangement of nucleotides within a bacterial chromosome is influenced by numerous factors. The degeneracy of the third codon within each reading frame allows some flexibility of nucleotide selection; however, the third nucleotide in the triplet of each codon is at least partly determined by the preceding two. This is most evident in organisms with a strong G + C bias, as the degenerate codon must contribute disproportionately to maintaining that bias. Therefore, a correlation exists between the first two nucleotides and the third in all open reading frames. If the arrangement of nucleotides in a bacterial chromosome is represented as a Markov process, we would expect that the correlation would be completely captured by a second-order Markov model and an increase in the order of the model (e.g., third-, fourth-…order) would not capture any additional uncertainty in the process. In this manuscript, we present the results of a comprehensive study of the Markov property that exists in the DNA sequences of 906 bacterial chromosomes. All of the 906 bacterial chromosomes studied exhibit a statistically significant Markov property that extends beyond second-order, and therefore cannot be fully explained by codon usage. An unrooted tree containing all 906 bacterial chromosomes based on their transition probability matrices of third-order shares ∼25% similarity to a tree based on sequence homologies of 16S rRNA sequences. This congruence to the 16S rRNA tree is greater than for trees based on lower-order models (e.g., second-order), and higher-order models result in diminishing improvements in congruence. A nucleotide correlation most likely exists within every bacterial chromosome that extends past three nucleotides. This correlation places significant limits on the number of nucleotide sequences that can represent probable bacterial chromosomes. Transition matrix usage is largely conserved by taxa, indicating that this property is likely inherited, however some important exceptions exist that may indicate the convergent evolution of some bacteria.

Análise de eficiência e desempenho no longo prazo: ilustração empírica de um modelo para avaliação de bibliotecas públicas

This paper presents a stepwise approach to organizational assessment from an efficiency standpoint. The empirical illustration originates from data referring to the period 2000-2007 and collected from a sample of 37 libraries affiliated to a federal university in Rio de Janeiro; this sample covers more than 80% of this affiliated universe. Employing efficiency scores computed from estimated dea (Data Envelopment Analysis) models, the stepwise approach ranks libraries and provides proefficiency allocative corrections. In the third step, long run evaluation is accomplished by Markovian analysis. Nonparametric tests are applied to investigate whether efficiency might be associated to demographic attributes. Findings generally indicated that efficiency scores were undistinguishable in the period. Although public libraries were the object of this study, the researchers argue that the approach is generally valid; as such the model can be applied to private organizations as well.

An analytical model for all-optical packet switching networks with finite FDL buffers

Signal loss and noise accumulation can cause fading in optical buffers implemented by fiber delay lines (FDLs). Optical packets that excessively recirculate through FDLs are easily dropped from their routing paths. Therefore, analytical models and packet scheduling schemes require additional considerations for FDL buffers. This work proposes an analytical model for all-optical packet switching networks with finite FDL buffers and a general class of scheduling schemes including many basic scheduling schemes. We intend to minimize the packet loss probability by ranking packets to achieve an optimal balance between latency and residual lifetime in the general class of scheduling schemes. The analytical model is based on a non-homogeneous Markovian analysis to study the effects of various scheduling schemes on packet loss probability and average latency. Analytical results show how various network parameters affect the optimal balance, and illustrate how properly balancing latency and residual distance can significantly improve network performance.

Kanban‐controlled exponential production lines: analysis and design

PurposeThe purpose of this paper is to study kanban‐controlled pull‐systems with machines having the exponential reliability model and with buffers finite capacities.Design/methodology/approachUsing Markovian analysis closed formulas are derived for the performance metrics such as customer service level, average inventory level, and throttling of raw part release, for one‐machine systems. Then, a recursive procedure is developed to extend the performance evaluation technique to multi‐machine systems.FindingsOnce system‐theoretic properties of the systems under consideration are investigated, the paper reveals methods for evaluating the smallest, i.e. lean, number of kanbans that ensure the desired level of customer service which are developed.Originality/valueProduction systems can operate in either push or pull regime. The push‐systems have been analyzed extensively for over 50 years, while the pull‐systems have been studied to a much lesser extent.

Changes in the phytoplankton community at Helgoland, North Sea: lessons from single spot time series analyses

In recent regime shift analyses, the phytoplankton compartment of the marine food web was essentially represented by phytoplankton color or chlorophyll concentration. A detection of changes directly at the species level is highly desirable. The Helgoland Roads data series, a collection of high frequency long-term time series comprising biological and physico-chemical components of the southern North Sea, allow such an investigation at the level of single species. Aiming at a detection and characterization of habitat and community changes in the observation period (1962 until the end of 2008), we selected six species as representatives of certain classes, for example, benthic or neritic species, and applied a combination of novel analysis methods—a fitness-based analysis of the realized niche, a bloom-triggered averaging and a Markovian analysis of co-occurrence and succession patterns—to related abundance time series and concurrent environmental parameter time series. We found a general trend toward enlargement of niche size and shifts of the niche position, interesting salinity patterns around bloom events of two species, and statistically highly significant changes of a phytoplankton community segment after 1965 and after 1998. Interpreting our observations in ecological terms leads to the formulation of testable hypotheses.

Library performance management in Rio de Janeiro, Brazil

PurposeThis paper intends to illustrate an application of data envelopment analysis (DEA) to assess library performance from an efficiency standpoint.Design/methodology/approachDEA modeling was applied to a convenience sample of 37 libraries affiliated to a federal university in Rio de Janeiro. Data were collected from the university's managerial database and refer to three inputs – number of employees, area and number of volumes – and four outputs – consultations, loans, enrolments and (user) traffic. Markovian analysis of transitions between efficient and inefficient states along time allowed a long‐term distribution between those states to be computed.FindingsThe retained DEA model provides a list of estimated scores that quantify efficiency status for each library unit and from which both rankings and operation plans can be determined for each unit to assist managers in their quest for library efficiency. In fact, (re)allocative measures, expressed as operation plans, indicate that, for each unit, some input(s) may be decreased and nonetheless some output(s) will increase. Those indicators may also be used to further or avoid either promised or planned changes.Originality/valueAs long as the efficiency principle is accepted the paper provides a three‐step procedure whereby any set of library units may be simultaneously assessed and ranked in relative terms and a set of quantitative operation plans may be used to (re)direct inefficient units toward efficiency. Whenever historical (e.g. annual) data are available, more adequate long‐term efficiency profiles will be computed, as well as some (e.g. yearly) durations relating to time spent in or before visiting (in)efficiency states. This model, combining short‐ and long‐term assessment, may be seen as a novelty contributed by the paper.

Path-based calculation of MTTFF, MTTFR, and asymptotic unavailability with the stochastic process algebra tool CASPA

CASPA is a stochastic process algebra tool for performance and dependability modelling, analysis, and verification. It is based entirely on the symbolic data structure of the multi-terminal binary decision diagram (MTBDD) which enables the tool to handle models with very large state space. This paper describes an extension of CASPA’s solving engine for path-based approximation of the mean time to first failure, the mean time to first recovery, and asymptotic unavailability by MTBDD algorithms. A non-trivial case study illustrates the use of path-based analysis and comparisons between the path-based unavailability calculations and results obtained from standard Markovian analysis are presented.

A tutorial on hypercube queueing models and some practical applications in Emergency Service Systems

This paper presents some extensions and applications of hypercube queueing models todescribe server-to-customer type Emergency Service Systems. The classical hypercube is a well-known spatially distributed queueing model effective in analyzing these systems, based on Markovian analysis approximations. Experience has shown that each real life Emergency Service System may have its own unique characteristics so that each system may require a particular hypercube queueing model incorporating those characteristics. Some of these distinctive characteristics are considered in the extensions presented in this tutorial such as dispatch policy based on random selection of the server to take an incoming call; partial cooperation among servers whereby depending on where the call is coming from, some servers cannot take the call; servers with additional workload coming from walk-in nonemergency customers such as in customer-to-server systems; existence of calls requiring the dispatch of more than one server; existence of more than one type of servers in the system, for instance paramedical and medical units in emergency medical systems. In this study, we present a set of these models based on the smallest non-trivial service systems. For each model, the construction of the system of equations for equilibrium hypercube state probabilities and the evaluation of particular operational characteristics are described.

Computational Markovian analysis of large systems

PurposeMarkov chains and queuing theory are widely used analysis, optimization and decision‐making tools in many areas of science and engineering. Real life systems could be modelled and analysed for their steady‐state and time‐dependent behaviour. Performance measures such as blocking probability of a system can be calculated by computing the probability distributions. A major hurdle in the applicability of these tools to complex large problems is the curse of dimensionality problem because models for even trivial real life systems comprise millions of states and hence require large computational resources. This paper describes the various computational dimensions in Markov chains modelling and briefly reports on the author's experiences and developed techniques to combat the curse of dimensionality problem.Design/methodology/approachThe paper formulates the Markovian modelling problem mathematically and shows, using case studies, that it poses both storage and computational time challenges when applied to the analysis of large complex systems.FindingsThe paper demonstrates using intelligent storage techniques, and concurrent and parallel computing methods that it is possible to solve very large systems on a single or multiple computers.Originality/valueThe paper has developed an interesting case study to motivate the reader and have computed and visualised data for steady‐state analysis of the system performance for a set of seven scenarios. The developed methods reviewed in this paper allow efficient solution of very large Markov chains. Contemporary methods for the solution of Markov chains cannot solve Markov models of the sizes considered in this paper using similar computing machines.

Performance Analysis of Optical Packet Switches with Reconfiguration Overhead

In optical packet switches, the overhead of reconfiguring a switch fabric is not negligible with respect to the packet transmission time and can adversely affect switch performance. The overhead increases the average waiting time of packets and worsens throughput performance. Therefore, scheduling packets requires additional considerations on the reconfiguration frequency. This work intends to analytically find the optimal reconfiguration frequency that minimizes the average waiting time of packets. It proposes an analytical model to facilitate our analysis on reconfiguration optimization for input-buffered optical packet switches with the reconfiguration overhead. The analytical model is based on a Markovian analysis and is used to study the effects of various network parameters on the average waiting time of packets. Of particular interest is the derivation of closed-form equations that quantify the effects of the reconfiguration frequency on the average waiting time of packets. Quantitative examples are given to show that properly balancing the reconfiguration frequency can significantly reduce the average waiting time of packets. In the case of heavy traffic, the basic round-robin scheduling scheme with the optimal reconfiguration frequency can achieve as much as 30% reduction in the average waiting time of packets, when compared with the basic round-robin scheduling scheme with a fixed reconfiguration frequency.

Reuse efficiency of wireless access networks under physical carrier sense: A Markovian analysis

The setting of the physical carrier sense is critical in wireless networks, since it often has to account for contrasting objectives like limiting the overall interference while ensuring high concurrency among wireless transmissions. This paper proposes an analytical approach for evaluating the impact of carrier sense setting on the throughput efficiency of wireless access networks. A time continuous Markov chain is used to describe the system, and to further gathering performance measures in terms of throughput and collision probability. Numerical results obtained through the model and further validated against simulations are used to derive qualitative dimensioning criteria for the carrier sense under different network conditions.

A latency-aware scheduling algorithm for all-optical packet switching networks with FDL buffers

Optical buffers implemented by fiber delay lines (FDLs) have a volatile nature due to signal loss and noise accumulation. Packets suffer from excessive recirculation through FDLs, and they may be dropped eventually in their routing paths. Because of this, packet scheduling becomes more difficult in FDL buffers than in RAM buffers, and requires additional design considerations for reducing packet loss. We propose a latency-aware scheduling scheme and an analytical model for all-optical packet switching networks with FDL buffers. The latency-aware scheduling scheme is intended to minimize the packet loss rate of the networks by ranking packets in the optimal balance between latency and residual distance. The analytical model is based on non-homogeneous Markovian analysis to study the effect of the proposed scheduling scheme on packet loss rate and average delay. Furthermore, our numerical results show how various network parameters affect the optimal balance. We demonstrate quantitatively how to achieve the proper balance between latency and residual distance so that the network performance can be improved significantly. For instance, we find that under a given latency limit and light traffic load our scheduling scheme achieves a packet loss rate 71% lower than a scheduling scheme that ranks packets simply based on latency.

Partially-shared zero-suppressed multi-terminal BDDs: concept, algorithms and applications

Multi-Terminal Binary Decision Diagrams (MTBDDs) are a well accepted technique for the state graph (SG) based quantitative analysis of large and complex systems specified by means of high-level model description techniques. However, this type of Decision Diagram (DD) is not always the best choice, since finite functions with small satisfaction sets, and where the fulfilling assignments possess many 0-assigned positions, may yield relatively large MTBDD based representations. Therefore, this article introduces zero-suppressed MTBDDs and proves that they are canonical representations of multi-valued functions on finite input sets. For manipulating DDs of this new type, possibly defined over different sets of function variables, the concept of partially-shared zero-suppressed MTBDDs and respective algorithms are developed. The efficiency of this new approach is demonstrated by comparing it to the well-known standard type of MTBDDs, where both types of DDs have been implemented by us within the C++-based DD-package JINC. The benchmarking takes place in the context of Markovian analysis and probabilistic model checking of systems. In total, the presented work extends existing approaches, since it not only allows one to directly employ (multi-terminal) zero-suppressed DDs in the field of quantitative verification, but also clearly demonstrates their efficiency.

MAC for Networks with Multipacket Reception Capability and Spatially Distributed Nodes

The physical layer of future wireless networks will be based on novel radio technologies such as UWB and MIMO. One of the important capabilities of such technologies is the ability to capture a few packets simultaneously. This capability has the potential to improve the performance of the MAC layer. However, we show that in networks with spatially distributed nodes, reusing backoff mechanisms originally designed for narrow-band systems (e.g., CSMA/CA) is inefficient. It is well known that when networks with spatially distributed nodes operate with such MAC protocols, the channel may be captured by nodes that are near the destination, leading to unfairness. We show that when the physical layer enables multipacket reception, the negative implications of reusing the legacy protocols include not only such unfairness, but also a significant throughput reduction. We present alternative backoff mechanisms and evaluate their performance via Markovian analysis, approximations, and simulation. We show that our alternative backoff mechanisms can improve both overall throughput and fairness.

De-Noising Single Molecule FRET Trajectories using Wavelent and Bayesian Techniques

Extracting quantitative information from low signal-to-noise single molecule FRET trajectories remains a significant challenge. In particular, biological systems that derive their function from shallowly defined or continua of states are not amenable to recent Markovian analysis algorithms. A method to de-noise single-molecule fluorescence resonance energy (smFRET) trajectories using wavelet detail thresholding and Bayesian inference is presented. Bayesian methods are developed to identify fluorophore photoblinks in the time trajectories. Simulated data are used to quantify the improvement in static and dynamic data analysis. Application of the method to experimental smFRET data shows that it distinguishes photoblinks from large shifts in smFRET efficiency while maintaining the important advantage of an unbiased approach. Known sources of experimental noise are examined and quantified as a means to remove their contributions via soft thresholding of wavelet coefficients. A wavelet decomposition algorithm is described, and thresholds are produced through the knowledge of noise parameters in the discrete-time photon signals. Reconstruction of the signals from thresholded coefficients produces signals that contain noise arising only from unquantifiable parameters. The method is applied to simulated and observed smFRET data, and it is found that the denoised data retain their underlying dynamical properties, but with increased resolution.

Self‐employment among Italian female graduates

PurposeThe purpose of this paper is to investigate the gender impact of tertiary education on the probability of entering and remaining in self‐employment.Design/methodology/approachA data set on labour market flows produced by the Italian National Statistical Office is exploited by interviewing about 62,000 graduate and non‐graduate individuals in transition between five labour market states: dependent workers; self‐employed workers; unemployed persons; and non‐active persons. From these data, an average ten‐year transition matrix (1993‐2003) is constructed and the flows between labour market conditions by applying Markovian analysis are investigated.FindingsThe data show that education significantly increases the probability of entering self‐employment for both male and female graduates, but it also significantly increases the transition from self‐employment to dependent employment for female graduates, thereby increasing the percentage of female graduates in paid employment and reducing the percentage of women in entrepreneurial activities. It is argued that the disappointment provoked by the gender wage gap in paid employment may induce some female graduates with low‐entrepreneurial ability to set‐up on their own, but once in self‐employment they have lower survival rates than both men in self‐employment and women in paid employment. Thus, what is observed overall is that education widens the gender gap between self‐employed workers and employees for individuals persisting in the same working condition.Originality/valueThe data are enabled to shift the focus of the relationship between education and entrepreneurship from the probability of being self‐employed to the probability of entering and surviving in this condition.