Search results

In the field of information systems, workflow modelling has attracted a lot of researchers. Most works in the domain do not take into consideration the concrete execution of resulting workflows. This failure puts beside the time and resource concepts. The aim of this paper is to develop a model that allows to deal with the execution of workflows based on the constraints of the resources.

Based on the domain engineering approach, one describes models of a business processes, and resources in an incremental manner. At each step of the modelling, one defines some requirements for the validation of the models.

The formalization gives the core features that are suitable to deal with the organisational aspect of business process management. These features are generic as they can be extended to capture the representation of various stages in the resource and business process management.

This paper does not deal with the concrete assignment of tasks to resources, and does not show how these features can be refined in order to model real world business processes. This work can be extended by defining some case studies, developing a supporting tool and carrying analysis.

By applying these models in daily work, enterprises will improve their productivity and deal with the competitive pressure of the network economy.

This paper defines an ontological framework for the business process, resource and correctness of a workflow within an enterprise that may be used by enterprise managers in the delivery of goods and services.

This paper describes research work carried out with the aim to investigate dynamically evolving database environments and corresponding schemata, allowing storage and manipulation of variable length data, a variable number of fields per record, variable length records, manipulation of authority records and links between records and fields, and dynamically defined objects (relations in the traditional sense). The paper proposes a new framework for the definition of a unified schema that eliminates completely the need for reorganisation at both logical and internal levels. Retrieval of data is optimised through self‐contained storage chunks that also vary dynamically.

This article attempts to examine the impact that traditional island cultural events have on tourism development in some of the West Indian (Commonwealth Caribbean) islands, how national tourist boards and hotels use these mega‐events for promotional purposes, how these cultural events are looked upon by the tourists themselves, and the possible dilution of the basic traditions and cultures of the territories if they are abused for tourist gain only.

The question of responsibility is not new to labour law. The earliest developments in labour law and social law sprang from a “legal revolution” to borrow the words of Georges Scelle, considering the concept of responsibility that prevailed in common law. Civil responsibility which was originally based on fault could now be based on the risk inherent to a socially useful activity so as to ensure that the responsibility for damages that might result from it be equitably shared. This development took place under the generalization of the industrial production mode, first within the frame work of laws respecting compensation for industrial accidents.

The purpose of this paper is to present the ability of Z‐notation to formulate formal requirements specification of huge application software based on an example of the Manufacturing Resource Planning (MRP II) Standard System. Z‐notation is using formal transformation approach to obtain operating software instead of traditional programming. The original MRP II software requirement specification possesses descriptive form extended by list of control questions. To make formal requirements specification, the original specification must be extending by some definition taken after APICS Dictionary. The definitions respect such concept as: item, item code, location, and order.

Writing schemas based on subsystem order of MRP II Standard System and treating the system as three level structures (user interface, business logic, and database), the schemas described business logic level only. As a conclusion was necessity to extend descriptive requirements specification by definitions. The limited size of the presentation contains few examples of formalization process only mainly limited to the main schemas as: item system (full definition), inventory system, bill of material, work centers and routings, generic order system, master production schedule, and material requirement planning.

As a result of the research, it can be said that Z‐notation apparatus is sufficient to build requirements specifications of big application systems like MRP II, enterprise resource planning, or customer relationship management.

Libraries of typical algorithms like MRP II designed through formal approach could replace traditional programming and open new prospects in the future development of broad computerization.

This paper aims to consider a soft computing approach to pattern classification using the basic tools of fuzzy relational calculus (FRC) and genetic algorithm (GA).

The paper introduces a new interpretation of multidimensional fuzzy implication (MFI) to represent the author's knowledge about the training data set. It also considers the notion of a fuzzy pattern vector (FPV) to handle the fuzzy information granules of the quantized pattern space and to represent a population of training patterns in the quantized pattern space. The construction of the pattern classifier is essentially based on the estimate of a fuzzy relation Ri between the antecedent clause and consequent clause of each one‐dimensional fuzzy implication. For the estimation of Ri floating point representation of GA is used. Thus, a set of fuzzy relations is formed from the new interpretation of MFI. This set of fuzzy relations is termed as the core of the pattern classifier. Once the classifier is constructed the non‐fuzzy features of a test pattern can be classified.

The performance of the proposed scheme is tested on synthetic data. Subsequently, the paper uses the proposed scheme for the vowel classification problem of an Indian language. In all these case studies the recognition score of the proposed method is very good. Finally, a benchmark of performance is established by considering Multilayer Perceptron (MLP), Support Vector Machine (SVM) and the proposed method. The Abalone, Hosse colic and Pima Indians data sets, obtained from UCL database repository are used for the said benchmark study. The benchmark study also establishes the superiority of the proposed method.

This new soft computing approach to pattern classification is based on a new interpretation of MFI and a novel notion of FPV. A set of fuzzy relations which is the core of the pattern classifier, is estimated using floating point GA and very effective classification of patterns under vague and imprecise environment is performed. This new approach to pattern classification avoids the curse of high dimensionality of feature vector. It can provide multiple classifications under overlapped classes.

Discusses US use of drug testing in the workplace, screening employees for smoking, AIDS, genetic traits and reproductive hazards. Attributes this to the costs employers face in insurance, litigation and compensation. Points out that the purpose of drug testing is to circumvent management responsibility for: accidents in the workplace, stress, bad management practices, and disregarding health and safety initiatives. Acknowledges that the tests are harmful and indefensible. Reports that 81 per cent of members of the American Management Association in 1996 conducted drug testing. Claims that screening is the alternative to monitoring – that is screening out individuals who are seen as high risk in some way – yet that misses the point – the focus should be on making hazardous working conditions safe. Indicates that companies may use drug testing as a means of deterring drug users from gravitating towards their organization. Mentions that workplace‐induced stress can lead to substance abuse and that, therefore it is management driven, rather than being a problem the worker brings to the workplace. Quotes a number of company physicians who object to policing drug use. Indicates that drug testing has diverted attention away from health and safety issues and hazardous working conditions.

Estimating the pose – position and orientation – of a moving object such as a robot is a necessary task for many applications, e.g., robot navigation control, environment mapping, and medical applications such as robotic surgery. The purpose of this paper is to introduce a novel method to fuse the information from several available sensors in order to improve the estimated pose from any individual sensor and calculate a more accurate pose for the moving platform.

Pose estimation is usually done by collecting the data obtained from several sensors mounted on the object/platform and fusing the acquired information. Assuming that the robot is moving in a three-dimensional (3D) world, its location is completely defined by six degrees of freedom (6DOF): three angles and three position coordinates. Some 3D sensors, such as IMUs and cameras, have been widely used for 3D localization. Yet, there are other sensors, like 2D Light Detection And Ranging (LiDAR), which can give a very precise estimation in a 2D plane but they are not employed for 3D estimation since the sensor is unable to obtain the full 6DOF. However, in some applications there is a considerable amount of time in which the robot is almost moving on a plane during the time interval between two sensor readings; e.g., a ground vehicle moving on a flat surface or a drone flying at an almost constant altitude to collect visual data. In this paper a novel method using a “fuzzy inference system” is proposed that employs a 2D LiDAR in a 3D localization algorithm in order to improve the pose estimation accuracy.

The method determines the trajectory of the robot and the sensor reliability between two readings and based on this information defines the weight of the 2D sensor in the final fused pose by adjusting “extended Kalman filter” parameters. Simulation and real world experiments show that the pose estimation error can be significantly decreased using the proposed method.

To the best of the authors’ knowledge this is the first time that a 2D LiDAR has been employed to improve the 3D pose estimation in an unknown environment without any previous knowledge. Simulation and real world experiments show that the pose estimation error can be significantly decreased using the proposed method.

The principles of sustainable development argue that organizations should make decisions not only based on economic or financial factors but also based on the long-term social and environmental consequences. The Code on Corporate Governance is one of the drivers for corporate social responsibility (CSR) reporting in Malaysia. Additionally, the way managers execute their responsibilities may be affected by their own tradition, beliefs, values, and culture. Thus, this chapter aims to examine the relationship between corporate governance characteristics and CSR disclosure and to investigate the influence of cultural values (Board’s Culture Domination) on the relationship between corporate governance and corporate social responsibility. A sample of 150 companies from the main board of Bursa Malaysia for year ended 2006 are chosen for the purpose of this study due to the year of the introduction of Bursa Malaysia CSR Framework. Based on available data, a CSR index is constructed. Hierarchical regression analysis is used to examine the relationship between the CSR disclosure index and the independent variables and also the moderating effect of Board’s Culture Domination. Results show that government ownership and audit committees have a positive and significant influence on CSR disclosure. Furthermore, the findings show that the Board’s Culture Domination moderate the relationship between audit committee, number of shareholders, foreign ownership, and CSR disclosure.

Simultaneous localization and mapping (SLAM) is the problem of determining the pose (position and orientation) of an autonomous robot moving through an unknown environment. The classical FastSLAM is a well-known solution to SLAM. In FastSLAM, a particle filter is used for the robot pose estimation, and the Kalman filter (KF) is used for the feature location’s estimation. However, the performance of the conventional FastSLAM is inconsistent. To tackle this problem, this study aims to propose a mutated FastSLAM (MFastSLAM) using soft computing.

The proposed method uses soft computing. In this approach, particle swarm optimization (PSO) estimator is used for the robot’s pose estimation and an adaptive neuro-fuzzy unscented Kalman filter (ANFUKF) is used for the feature location’s estimation. In ANFUKF, a neuro-fuzzy inference system (ANFIS) supervises the performance of the unscented Kalman filter (UKF) with the aim of reducing the mismatch between the theoretical and actual covariance of the residual sequences to get better consistency.

The simulation and experimental results indicate that the consistency and estimated accuracy of the proposed algorithm are superior FastSLAM.

The main contribution of this paper is the introduction of MFastSLAM to solve the problems of FastSLAM.