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Although Business process modelling is an increasingly popular research area for both organisations and enterprises due to its usefulness in optimizing resources management, business re-engineering and business performance, it is not yet widely accepted in Small and Medium size Enterprises (SMEs), which are vital for sustainable economy development. The understanding of Business Process is an essential approach for an Organization to achieve set objectives and improve its operations. It has been able to show Business Analysts, and Managers where bottleneck exists in the system, how to optimize the Business Process to reduce cost of running the Organization, and the required resources needed for an Organization. This is clear for large scale organizations and enterprises but under research investigation for SMEs. Business Process Modelling (BPM) is a representation of the processes of the Organization. Several modelling techniques have been proposed and used to capture the characteristics of business processes. However, limited guidelines exist for selecting appropriate modelling techniques based on the characteristics of the problem and its requirements. This is even more accurate in the case of selecting proper BPM software tools to achieve those BPM modelling and simulation goals. This paper aims at presenting a comparative analysis of some relatively popular business process modelling techniques focusing on the associated software tools. The comparative framework proposed is based on the following major criteria: data flow capability, logical reasoning and understandability, specification of roles, and capability of simulation, flexibility and ease of use, simulation support and scope. However, the emphasis of this investigation is put on SME applicability of these tools and techniques. Therefore, the first goal is to define proper selection criteria for the application of BPM tools to SMEs. The proposed framework can serve as the basis for evaluating further modelling techniques and generating selection procedures focusing on a comparison of existing tools to implement these techniques properly for SMEs. This is to enable a potential user/modeller choose the right technique and tool in modelling critical SME Business Processes in order to analyse and optimize its operations.

Undoubtedly, Business process modelling is an increasingly popular research area for both organisations and enterprises due to its usefulness in facilitating better planning of resources, business re-engineering and optimized business performance. The understanding of Business Process is an essential approach for an Organization to achieve set objectives and improve its operations. Business Process Modelling is a representation of the processes of the organization. Several modelling techniques have been proposed and used to capture the characteristics of business processes. However, available techniques view business processes from different perspectives and have different features and capabilities. Furthermore, to date limited guidelines exist for selecting appropriate modelling techniques based on the characteristics of the problem and its requirements. Recent development has shown the importance of representing processes to carry out continuous improvement. The modelling and simulation of Business Processes has been able to show Business Analysts, and Managers where bottleneck exists in the system, how to optimise the Business Process to reduce cost of running the organization, and the required resources needed for an organization. This paper presents a comparative analysis of some popular business process modelling techniques. The comparative framework is based on the following major criteria: data flow capability, logical reasoning and understandability, specification of roles, and capability of simulation, flexibility and ease of use, simulation support and scope. The proposed framework can serve as the basis for evaluating further modelling techniques and generating selection procedures focusing on a comparison of existing tools to implement these techniques. This is to enable a potential user/modeller choose the right technique and tool in modelling critical Business Processes in order to analyse and optimise the operations of an organization.

This study aims to examine the impact of long-term treatment with the anti-TNF antibody infliximab on radiographic progression of hip arthritis in ankylosing spondylitis. Anteroposterior X-rays of the pelvis obtained at baseline from consecutive patients with ankylosing spondylitis and bilateral hip arthritis were compared with X-rays obtained after 6 ± 2.5 years (mean ± SD) of continuous infliximab treatment. Analysis was performed by the Bath Ankylosing Spondylitis Radiology Hip Index (BASRI-h) scoring system (min 0, max 4). Hip joint space width was also assessed by the average of measurements at three distinct sites between the acetabulum and femoral head. In 23 patients with active disease (21 men, mean age and disease duration of 45 and 16 years, respectively), the BASRI-h score at baseline was 1 in 7, 2 in 16, 3 in 16, and 4 in 7 hips (including two arthroplasties). Individual BASRI-h scores at baseline (2.50 ± 0.86, mean ± SD) remained unchanged in all patients at end of follow-up. At baseline, the average width of the whole joint space (3.56 ± 0.70 mm, n = 44) was not associated with disease activity measurements but negatively correlated with BAS functional index (Spearman r = -0.5, P = 0.007). After 2-10 years of infliximab treatment, the average width of the whole joint space in these patients (3.59 ± 0.79 mm) was not reduced. These results suggest that radiographic progression of hip arthritis in ankylosing spondylitis may be arrested during infliximab treatment. © 2013 Clinical Rheumatology.

Imaging systems and techniques have found widespread application in medical and biological imaging, security and surveillance systems, remote sensing, biometrics, non-destructive testing, computer sciences, materials research, and most recently also in various types of customer products. Imaging systems may be based on different physical measuring principles, such as optical, infrared, acoustic, microwave, terahertz, electrical, X-ray and gamma ray sensing techniques, for example. But behind the imaging sensor there is strong common ground in electronics concepts and circuits for signal conversion, processing, acquisition, and storage as well as algorithms for image enhancement, image reconstruction and image analysis. Imaging systems are increasingly complex and therefore challenge electronic engineers and computer scientists. Concurrently to an ongoing trend of increasing the spatial and temporal resolution of such systems, there is a growing demand for hardware-supported image processing, multi-modality imaging, data reduction as well as improved sensitivity, specificity and robustness.

Coverage is one of the metrics used to quantify the quality of service (QoS) of sensor networks. In general, we use this term to measure the ability of the network to interact with – observe or react to – the phenomena taking place in the area of interest. In addition, coverage is associated with connectivity and energy consumption, both important aspects of the design process of a Wireless SensorNetwork (WSN). This paper aims at offering a critical overview and presentation of the problem as well as the main strategies developed so far.