Basim Majeed

Business Process Analysis and Optimization: Beyond Reengineering

There is an abundance of business process modeling techniques that capture and address different aspects of a business process. A limited number of these process models allow further quantitative analysis, and only a few enable structured process improvement. This paper reviews and classifies the main techniques for business process modeling with regard to their analysis and optimization capabilities. Three primary groups are identified, and a selection of representative business process modeling techniques is classified based on these. Similar classification is also presented for the analysis and optimization approaches for business processes that were identified in relevant literature. The main contribution of the paper is that it identifies which types of business process models are suitable for analysis and optimization, and also highlights the lack of such approaches. This paper offers a state-of-the-art review in the areas of business process modeling, analysis, and optimization-underlining that the latter two have not received enough coverage and support in the literature.

Real Time Business Intelligence for the Adaptive Enterprise

In todays competitive environment, analysing data to predict market trends and to improve enterprise performance is an essential business activity. However, it is becoming clear that business success requires such data analysis to be carried out in real-time, and that actions in response to analysis results must also be performed in real-time in order to meet the rapid change in demand from customers and regulators alike. This paper discusses issues and problems of current business intelligence systems, and then outlines our vision of future real-time business intelligence. We present a list of emerging technologies that are being developed within the research program of British Telecommunications plc (BT), which could contribute to the realisation of real-time business intelligence, in addition to some examples of applying these technologies to improve BTs systems and services

A review of business process mining: state‐of‐the‐art and future trends

Purpose – This paper seeks to examine the area of business process mining, providing an overview of state‐of‐the‐art techniques. An outline of the main problems experienced in the practice of process mining is given along with reference to work that addresses the most challenging issues experienced in this field. This paper also aims to examine the application of soft computing techniques to process‐mining problems.Design/methodology/approach – This paper is based on a comprehensive review of literature covering more than 50 research papers. These papers are analysed to identify current trends and future research directions in the field.Findings – Process‐mining techniques are now becoming available as graphical interface‐driven software tools, where flow diagram representations of processes may be manipulated as part of the mining task. A significant number of papers employ mining heuristics to aid in the task of process discovery. Soft computing algorithms are increasingly being investigated to aid the ...

A framework for comparing process mining algorithms

There are many process mining algorithms with different theoretical foundations and aims, raising the question of how to choose the best for a particular situation. A framework is proposed for objectively comparing algorithms for process discovery against a known ground truth, with an implementation using existing tools. Results from an experimental evaluation of five algorithms against basic process structures confirm the validity of the approach. In general, numbers of traces for mining are predictable from the structure and probabilities in the model, but there are some algorithm-specific differences.

Case Study in Process Mining in a Multinational Enterprise

Process mining has become an active area of research and while there are numerous papers on approaches to process mining there are fewer detailing its application to real industrial scenarios and its applicability in these spaces. In this paper we introduce the approach to process mining used in a number of multinational enterprises and then reflect upon the issues that have been encountered during our ongoing work. In our opinion these issues are a clear example of the challenges that need to be addressed during business process discovery from heterogeneous data.

A model driven approach to the design and implementing of fault tolerant Service oriented Architectures

One of the key stages of the development of a fault tolerant service oriented architecture is the creation of diagnosers, which monitors the systempsilas behaviour to identify the occurrence of failure. This paper presents a model driven development (MDD) approach to the automated creation of the diagnosing services and integrating them into the system. The outline of the method is as follows. BPEL models of the services are transformed to deterministic automaton with unobservable event representations using MDD transformations. Then, relying on discrete event system techniques a diagnoser automaton for the deterministic automata are created automatically. Finally, the diagnoser automaton is transformed into a new BPEL representation, which is integrated into the original architecture.

Intelligent systems for wellbeing monitoring

An intelligent monitoring and analysis system that plays the central role in the trial of a telecare environment is described. The system continuously monitors the wellbeing of people with care needs while living at home. In order to achieve this, a sensor network is set up around the monitored person using off-the-shelf devices. The sensors can be fixed inside the home or they can be mobile and are worn by the person. The sensors form art activity-related logical network that allows plug-and-play insertion and removal of sensors at any time. The system is responsible for supervising the sensor network, and for analysing sensor data in order to detect subtle changes in the ability of humans to carry out their daily living activities, and to relate these to specific aspects of their wellbeing status. Fuzzy reasoning is one of the data analysis techniques employed by the system because of its suitability to handle imprecise knowledge.

A Lightweight RDF Data Model for Business Process Analysis

This article presents a lightweight data representation model designed to support real time monitoring of business processes. The model is based on a shared vocabulary defined using open standard representations (RDF) allowing independence and extremely flexible interoperability between applications. The main benefit of this representation is that it is transparent to the data creation and analysis processes; furthermore it can be extended progressively when new information is available. Business Process data represented with this data model can be easily published on-line and shared between applications. After the definition of the data model, in this article, we demonstrate that with the use of this representation it is possible to retrieve and make use of domain specific information without any previous knowledge of the process. This model is a novel approach to real-time process data representation and paves the road to a complete new breed of applications for business process analysis.

A Third-Generation Telecare System using Fuzzy Ambient Intelligence

The automated care and monitoring of vulnerable people is becoming a reality with the rapid development and improvement of networked sensor technologies. Many researchers have shown considerable success in determining immediate causes for concern in well-being, such as detecting falls in the home. To date however, little emphasis has been placed on monitoring well-being in a long-term sense, known as third generation telecare. The system described in this paper involves a customised sensor network, able to detect a person’s movements and use of furniture and household items, coupled with a sophisticated fuzzy data analysis process able to infer activities that the monitored client is undertaking and thus answer high level queries such as “is the person eating regularly”. The system also detects abnormal patterns of behaviour and provides tools for long-term trend analysis such that gradual and subtle changes in behaviour can be clearly understood. Soft computing techniques are needed due to the high degree of uncertainty in the inference process. We also describe a trial of the system, which was installed in two homes. Results indicate that fuzzy analysis enables us to summarise the data in a manner which is useful to the care providers without them needing to be experts in data analysis. www.springerlink.com Artificial Intelligence Group, University of Bristol BS8 1TR UK T. Martin et al.: A Third-Generation Telecare System using Fuzzy Ambient Intelligence, Studies in Compu© Springer-Verlag Berlin Heidelberg 2007 tational Intelligence (SCI) 72, 155–175 (2007)

Dynamic daily-living patterns and association analyses in tele-care systems

Tele-care systems aim to carry out intelligent analyses of a persons wellbeing using data about their daily activities. This is a very challenging task because the massive dataset is likely to be erroneous, possibly with misleading sections due to noise or missing values. Furthermore, the interpretation of the data is highly sensitive to the lifestyle of the monitored person and the environment in which they interact. In our tele-care project, sensor-network domain knowledge is used to overcome the difficulties of monitoring long-term wellbeing with an imperfect data source. In addition, a fuzzy association analysis is leveraged to implement a dynamic and flexible analysis over individual- and environment-dependent data.