Formal modelling of organisational goals based on performance indicators

Every organisation exists or is created for the achievement of one or more goals. To ensure continued success, the organisation should monitor its performance with respect to the formulated goals. In practice the performance of an organisation is often evaluated by estimating its performance indicators. In most existing approaches for organisation modelling the relation between performance indicators and goals remains implicit. This paper proposes a formal framework for modelling goals based on performance indicators and defines mechanisms for establishing goal satisfaction, which enable evaluation of organisational performance. Methodological and analysis issues related to goals are also discussed in the paper. The described framework is a part of a general framework for organisation modelling and analysis.     

Using standards to integrate soft real-time components into dynamic distributed architectures

A pervasive application domain today is one in which independently developed real-time components participate in a dynamic and decentralized way from distributed environments. Several challenges arise from this domain, related with participant heterogeneity, transient behavior, scalability or quality of service. The use of standards is important here, where a multidiscipline approach is required. We propose ServiceDDS, a framework that combines different standard technologies to solve the problems related with the integration of components into the described environment. ServiceDDS is based on DDS to support dynamic distributed interactions, XMPP to provide Web access, and RTSJ for real-time performance.     

Automatic parallelisation for LTI MIMO state space systems using FPGAs. An optimisation for cost & performance

The parallelism attained by the use of Field Programmable Gate Arrays (FPGAs) has shown remarkable potential for accelerating control systems applications. This comes at a time when well established methods based on inherited serial Central Processor Units (CPUs) cannot guarantee solutions for the increasing execution speed demands. However, the transition from serial to parallel architectures represents a tremendous challenge due to overwhelming numbers of unexplored options and conflicting factors. The work presented achieves a parallelisation characterisation for generic MIMO systems using stand-alone FPGA implementations. The main contribution is that a very fine subset of possible serial/parallel implementations is obtained. This is used to achieve a flexible trade-off between cost and performance. Automatic optimisation of latency, occupied FPGA area and execution speed is attained and justified in respect to most of the feasible scenarios.     

Performance evaluation of priority CSMA-CA mechanism on ISA100.11a wireless network

The International Society of Automation recently released ISA100.11a as an open standard for reliable wireless networks for industrial automation. ISA100.11a uses the TDMA scheme in the medium access layer to provide deterministic services. However, ISA100.11a adopts the CSMA-CA mechanism with priorities for retransmission from failure on dedicated links, sporadic data, and network configuration.This paper evaluates ISA100.11a CSMA-CA by simulation, considering the effects of backoff procedures and priority settings to probability of collision and successful use of slots. It's demonstrated that a high number of priority classes enable better network utilization resulting in less number of packets exceeding their lifetime.     

A global localization approach based on Line-segment Relation Matching technique

This paper presents a novel global localization approach for mobile robots by exploring line-segment features in any structured environment. The main contribution of this paper is an effective data association approach, the Line-segment Relation Matching (LRM) technique, which is based on a generation and exploration of an Interpretation Tree (IT). A new representation of geometric patterns of line-segments is proposed for the first time, which is called as Relation Table. It contains relative geometric positions of every line-segment respect to the others (or itself) in a coordinate-frame independent sense. Based on that, a Relation-Table-constraint is applied to minimize the searching space of IT therefore greatly reducing the processing time of LRM. The Least Square algorithm is further applied to estimate the robot pose using matched line-segment pairs. Then a global localization system can be realized based on our LRM technique integrated with a hypothesis tracking framework which is able to handle pose ambiguity. Sufficient simulations were specially designed and carried out indicating both pluses and minuses of our system compared with former methods. We also presented the practical experiments illustrating that our approach has a high robustness against uncertainties from sensor occlusions and extraneous observation in a highly dynamic environment. Additionally our system was demonstrated to easily deal with initialization and have the ability of quick recovery from a localization failure.     

Bacteria foraging optimization for protein sequence analysis on the grid

Scientific applications such as protein sequence analysis require a coordination of resources. This is due to hundreds and hundreds of protein sequences being deposited into data banks by the research community which results in an extensive database search when one wants to find a similar protein sequence. This search becomes easier and the time taken is reduced when it is conducted in a grid environment implemented using the Globus tool kit. This paper proposes the use of Bacteria Foraging Optimization (BFO) for finding similar protein sequences in the existing databases. Usage of BFO further reduces the time taken by a resource to execute the user’s requests. Also, the resources utilized in the proposed method are better balanced compared to the existing scheduling algorithms. Also, it is found that the number of tasks executed is more compared to the existing algorithms even though there is a fall in the execution of tasks as the number of resources increases which might be due to network failure etc. The proposed BFO has been compared with the existing First Come First Serve (FCFS) and Minimum Execution Time (MET) scheduling algorithms and it has been found that the proposed BFO performs well compared to the existing algorithms in terms of makespan, resource utilization and minimization in the case of non-execution of client requests.     

Improved estimation of defocus blur and spatial shifts in spatial domain: a homotopy-based approach

This paper presents a homotopy-based algorithm for the recovery of depth cues in the spatial domain. The algorithm specifically deals with defocus blur and spatial shifts, that is 2D motion, stereo disparities and/or zooming disparities. These cues are estimated from two images of the same scene acquired by a camera evolving in time and/or space. We show that they can be simultaneously computed by resolving a system of equations using a homotopy method. The proposed algorithm is tested using synthetic and real images. The results confirm that the use of a homotopy method leads to a dense and accurate estimation of depth cues. This approach has been integrated into an application for relief estimation from remotely sensed images.     

Sliding mode control for two-time scale systems: stability issues

The paper presents some results on global exponential stability of linear time invariant systems with different time scales. The full system is decomposed in two reduced ones by means of singular perturbations and a smooth approximation of a Variable Structure Control is synthesized for each of them using Reaching Law approach. The global closed loop stability is then proved for the whole system using Lyapunov methods and a particular state space decomposition. Moreover a literal form for ε∗ (a parameter which measures the minimum separation between time scales) is derived.     

Dynamic anti-windup based control method for state constrained systems

Based on the dynamic anti-windup strategy, an alternative control methodology for state constrained systems is presented. The proposed method is an a posteriori approach for state constrained systems, which is differentiated from the usual a priori approach. That is, first a linear controller is designed to show a desirable nominal performance by ignoring state constraints. Then, an additional compensator is introduced to account for state constraints. By minimizing a reasonable performance index, a dynamic compensator is derived explicitly, which is expressed in plant and controller parameters. The proposed method not only provides a graceful performance degradation, but it also guarantees the total stability of the resulting systems. An illustrative example is given to show the effectiveness of the proposed method.     

Classification of heart rate data using artificial neural network and fuzzy equivalence relation

The electrocardiogram is a representative signal containing information about the condition of the heart. The shape and size of the P-QRS-T wave, the time intervals between its various peaks, etc. may contain useful information about the nature of disease afflicting the heart. However, these subtle details cannot be directly monitored by the human observer. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the signal parameters, extracted and analysed using computers, are highly useful in diagnostics. This paper deals with the classification of certain diseases using artificial neural network (ANN) and fuzzy equivalence relations. The heart rate variability is used as the base signal from which certain parameters are extracted and presented to the ANN for classification. The same data is also used for fuzzy equivalence classifier. The feedforward architecture ANN classifier is seen to be correct in about 85% of the test cases, and the fuzzy classifier yields correct classification in over 90% of the cases.