This paper addresses the problem of modelling call processing performance (CPP) in a multidomain Next Generation Network (NGN) architecture including the elements of the IP Multimedia Subsystem (IMS) in service stra-tum and based on the Multiprotocol Label Switching (MPLS) technology in transport stratum. An analytical traffic model for such an architecture is proposed by integrating the former-ly implemented submodels of service stratum and MPLS-based transport stratum. The integrated analytical model allows investigation of mean Call Set-up Delay (E(CSD)) and mean Call Disengagement Delay (E(CDD)) for a large set of input variables corresponding to both IMS/NGN strata. The evaluation of E(CSD) and E(CDD), which are a subset of CPP param-eters, is very important for both network users and operators. Details regarding the structure and operation of the integrated traffic model are provided in this paper. Moreover, the results of investigations are described, which demonstrate that this model is correctly implemented, reflects the operation of a multidomain IMS/NGN network and may be used in further research.

ABSTRACT Modern manufacturing firms are globalised organisations that regularly operate multi-plant networks. Network configuration elements, e.g. plant roles or the multi-plant strategy, were intensively examined by scholars. Another complex and less studied task is coordinating the manufacturing strategy of the plants in the network. Efficient distribution of competences and decision-making authorities is crucial for decision-makers. An appropriate level of autonomy has to be found that determines which decisions are centralised and which are delegated to the decentralised plants. The interaction of network coordination and configuration with network capabilities and competitive advantages is examined in this article using an empirical multi-case study. We focus on how manufacturing strategy decisions are made in the intra-firm network and how the distribution of decision-making authorities affects the network capabilities. Results indicate that both network coordination and configuration affect network capabilities, which in turn affect competitive advantages. Network thriftiness reduces costs, while mobility and flexibility promote delivery capabilities and learning effects improve quality and costs. A conceptual research model is developed as a starting point for future studies in this emerging research area. Besides, managers are provided with guidance on the efficient design of distributed manufacturing networks to achieve the desired competitive advantages.

In this paper we present low-complexity method for multichannel lossless compression, dedicated for portable ECG acquisition systems. Each channel is selectively decorrelated using two linear predictors, separately for the heart beats and the background signal. Next, cross-channel correlations are used to determine pairs of strongly dependent channels, which allows for further decorrelation of signals using cross-channel predictors. Prediction is therefore obtained at small computational cost, using a simple QRS detector and three short linear predictors per channel, updated periodically using fast Levinson-Durbin recursion. Finally, the prediction error and the estimate of its variance is used in entropy encoding with highly effective method of asymmetric numeral systems. The average compression ratio depends on the similarity between channels and varies from 2.92 (MIT-BIH ADB, low similarity) to 3.43 (INCART, high similarity).

Current emphasis on diagnosing axial spondyloarthritis (axSpA) in early stage enforced the search for sensitive and specific diagnostic algorithms with the use of imaging methods. The aim of this review was to summarise current recommendations concerning the use of imaging techniques in diagnostics and monitoring of axSpA as well as to outline possible future directions of the development in this field. MEDLINE database was searched between March and April 2018. In the first phase, such keywords were applied: ‘ASAS’, ‘EULAR’, ‘ASAS-EULAR’, ‘ASAS/OMERACT’, ‘axial spondyloarthritis’, while in the second step: ‘axial spondyloarthritis’, ‘ankylosing spondylitis’, ‘magnetic resonance imaging’, ‘computed tomography’, and ‘radiography’, ‘imaging’. An up-to-date summary of European League Against Rheumatism (EULAR) recommendations enriched with recent updates of Assessment of Spondyloarthritis International Society (ASAS) diagnostic criteria regarding imaging in axSpA course was created. Moreover, we outlined the role of new in this field, promising imaging techniques, such as diffusion-weighted imaging and dynamic contrast-enhanced sequences in magnetic resonance imaging (MRI) or low-dose computed tomography (CT). As precise monitoring of axSpA activity is vital, we reviewed the most precise methods: semiquantitative scores (e.g., Spondyloarthritis Research Consortium of Canada scores or CT Syndesmophyte Score) and quantitative analysis of MRI-based apparent diffusion coefficient or perfusion maps and enhancement curves. According to EULAR and ASAS recommendations, radiography and MRI still remain basic methods of axSpA diagnostics and monitoring. However, the knowledge of state-of-the-art international guidelines combined with the awareness of emerging imaging methods is the key to effective management of axSpA.

The main purpose of the work is to present and test the developed web-based tool to identify parameters of rheological equations, whose functionality according to the presented results is comparable to existing desktop applications. The developed web-based application with a user-friendly interface uses selected optimization methods (Powell and Hooke-Jeeves algorithms). Criteria for selecting optimization methods are: robustness and frequent application to identification problems described in literature. Testing the developed application consists of comparing the identified stress-strain curves obtained from mechanical tests using the developed tool and commercial desktop application, and performing efficiency tests for the analyzed examples of rheological equations and optimization methods. For this purpose, two material models were used: a simple Hollomon’s model and a multi-parameter model used for steel, in which the influence of softening during the dynamic recrystallization is insignificant. The presented software is implemented in technologies such as JDK 1.8, Spring Framework and PrimeFaces, and passes the efficiency tests successfully.

In this article we present a novel approach to cellulite classification that can be personlised based on non-contact thermal imaging using IR thermography. By analysing the superficial temperature distribution of the body it is possible to diagnose the stages of cellulite development. The study investigates thermal images of posterior of thighs of female volunteers and identifies cellulite areas in an automatic way using image processing. The Growing Bubble Algorithm has been used for thermal picture conversion into valid input vector for a neural network based classifier scheme. Using machine learning process of training the input database was prepared as the stage of cellulite classifier according to the state of the art Nurnberger-Muller diagnosis scheme. Our work demonstrates that it is possible to diagnose the cellulite with over 70% accuracy using a cost-effective, simple and unsophisticated classifier which operates on low-definition pictures. In essence, our work shows that IR-thermography, when coupled with computer aided image analysis and processing, can be a very convenient and effective tool to enable personalized diagnosis and preventive medicine to improve the quality of life of women suffering from cellulite problems.

The purpose of the study was to develop an automated method for measurement of the selected angular variables, characterizing foot skeleton based on dorsoplantar projection radiographs. The study was a retrospective analysis of radiographic data. Totally, 50 dorsoplantar projection radiographs of a weight-wearing foot were analyzed (24 left and 26 right feet) of 32 patients (23 female, 9 male). Various quantities were measured to assess the severity of hallux valgus. The measurements were performed manually and with an automated method designed in the study. The automated and manual measurements were correlated. Repeated manual measurements were additionally performed to determine the variability of manual assessment of the hallux valgus. High correlation between manual and automated measurements have been observed. The accuracy of the framework is comparable with the accuracy of manual measurements.

The purpose of this paper is to test conjecture that the data related to manual maneuvers with the handle of a catheter of a bronchoscope provides information sufficient for accomplishing the task of estimating the position, orientation and flexure of the distal end of a catheter. To test the conjecture three devices were developed and mounted on the handle of a catheter and on the external opening of the working channel of a bronchoscope. The devices recorded shifts of a catheter, rotations of the catheter handle and the shifts of the ring of the catheter, directly related to the flexure of the tip of the catheter. In laboratory experiments it has been shown that the shift of the catheter can be monitored with accuracy of 2 mm and the catheter tip rotation and flexure angles can be monitored with accuracy of 10 and 20°, respectively. The accuracy of the developed devices compares favorably with the accuracy of the current standard methods for supporting peripheral bronchoscopy.

Diagnostic reasoning is an activity aimed at finding the causes of incorrect behavior of various technological systems. In order to perform diagnosis, a typical diagnostic system should be equipped with the expert knowledge of the domain and statistical evidence of former failures. More advanced solution combines model-based reasoning (MBR ) and abduction. It is assumed that a model of the system under investigation is specified. Such a model allows us to simulate the normal behavior of the system. It can also be used to detect incorrect behavior and perform sophisticated reasoning in order to identify potential causes of the observed failure. Such potential causes form a set of possible diagnoses. In this chapter, formal bases for the so-called model-based diagnostic reasoning paradigm are presented and application examples are discussed in detail. A method of modeling system behavior with the use of causal graphs is put forward. Then, a systematic method for discovering all the so-called conflict sets (disjunctive conceptual faults) is described. Such conflict sets describe sets of elements in such a manner that in order to explain the observed misbehavior at least one of them must be faulty. By selecting and removing such elements from all conflicts sets – for each conflict set one such element – the proper candidate diagnoses are generated. An example of the application of the proposed methods to the three-tank dynamic system is presented and some bases for on-line generation of diagnoses for dynamic systems are outlined, together with some theorems. The chapter introduces an easy and self-contained material being an introduction to modern model-based diagnosis, covering static and dynamic systems.