Quality management (QM) implementation in the Kuwaiti Oil Industry:An empirical study and a proposed generic framework

In an Arab oil producing country in the Middle East such as Kuwait, Oil industry is considered as the main and most important industry of the country. This industry’s importance emerged from the significant role it plays in both country’s national economy and also global economy. Moreover, Oil industry’s criticality comes from its interconnectivity with national security and power in the Middle East region. Hence, conducting this research in this crucial industry had certainly added values to companies in this industry as it investigated thoroughly the main components of the TQM implementation process and identified which components affects significantly TQM’s implementation and its gained business results. In addition, as the Oil sector is a large sector that is known for its richness of employees with different national cultures and backgrounds. Thus, this culture-heterogeneous industry seems to be the most appropriate environment to address and satisfy a need in the literature to investigate the national culture values’ effects on TQM implementation process. Furthermore, this research has developed a new conceptual model of TQM implementation process in the Kuwaiti Oil industry that applies in general to operations and productions organizations at the Kuwaiti business environment and in specific to organizations in the Oil industry, as well it serves as a good theoretical model for improving operations and production level of the oil industry in other developing and developed countries. Thus, such research findings minimized the literature’s gap found the limited amount of empirical research of TQM implementation in well-developed industries existing in an Arab, developing countries and specifically in Kuwait, where there was no coherent national model for a universal TQM implementation in the Kuwaiti Oil industry in specific and Kuwaiti business environment in general. Finally, this newly developed research framework, which emerged from the literature search, was validated by rigorous quantitative analysis tools including SPSS and Structural Equation Modeling. The quantitative findings of questionnaires collected were supported by the qualitative findings of interviews conducted.

Data envelopment analysis model for the appraisal and relative performance evaluation of nurses at an intensive care unit

The appraisal and relative performance evaluation of nurses are very important and beneficial for both nurses and employers in an era of clinical governance, increased accountability and high standards of health care services. They enhance and consolidate the knowledge and practical skills of nurses by identification of training and career development plans as well as improvement in health care quality services, increase in job satisfaction and use of cost-effective resources. In this paper, a data envelopment analysis (DEA) model is proposed for the appraisal and relative performance evaluation of nurses. The model is validated on thirty-two nurses working at an Intensive Care Unit (ICU) at one of the most recognized hospitals in Lebanon. The DEA was able to classify nurses into efficient and inefficient ones. The set of efficient nurses was used to establish an internal best practice benchmark to project career development plans for improving the performance of other inefficient nurses. The DEA result confirmed the ranking of some nurses and highlighted injustice in other cases that were produced by the currently practiced appraisal system. Further, the DEA model is shown to be an effective talent management and motivational tool as it can provide clear managerial plans related to promoting, training and development activities from the perspective of nurses, hence increasing their satisfaction, motivation and acceptance of appraisal results. Due to such features, the model is currently being considered for implementation at ICU. Finally, the ratio of the number DEA units to the number of input/output measures is revisited with new suggested values on its upper and lower limits depending on the type of DEA models and the desired number of efficient units from a managerial perspective.

An iterative method based on boundary integrals for elliptic Cauchy problems in semi-infinite domains

In this study, we investigate the problem of reconstruction of a stationary temperature field from given temperature and heat flux on a part of the boundary of a semi-infinite region containing an inclusion. This situation can be modelled as a Cauchy problem for the Laplace operator and it is an ill-posed problem in the sense of Hadamard. We propose and investigate a Landweber-Fridman type iterative method, which preserve the (stationary) heat operator, for the stable reconstruction of the temperature field on the boundary of the inclusion. In each iteration step, mixed boundary value problems for the Laplace operator are solved in the semi-infinite region. Well-posedness of these problems is investigated and convergence of the procedures is discussed. For the numerical implementation of these mixed problems an efficient boundary integral method is proposed which is based on the indirect variant of the boundary integral approach. Using this approach the mixed problems are reduced to integral equations over the (bounded) boundary of the inclusion. Numerical examples are included showing that stable and accurate reconstructions of the temperature field on the boundary of the inclusion can be obtained also in the case of noisy data. These results are compared with those obtained with the alternating iterative method.

Managing diversity in organizations:an integrative model and agenda for future research

The literature on policies, procedures, and practices of diversity management in organizations is currently fragmented and often contradictory in highlighting what is effective diversity management, and which organizational and societal factors facilitate or hinder its implementation. In order to provide a comprehensive and cohesive view of diversity management in organizations, we develop a multilevel model informed by the social identity approach that explains, on the basis of a work motivation logic, the processes by, and the conditions under which employee dissimilarity within diverse work groups is related to innovation, effectiveness, and well-being. Building on this new model, we then identify those work group factors (e.g., climate for inclusion and supervisory leadership), organizational factors (e.g., diversity management policies and procedures, and top management's diversity beliefs), and societal factors (e.g., legislation, socioeconomic situation, and culture) that are likely to contribute to the effective management of diversity in organizations. In our discussion of the theoretical implications of the proposed model, we offer a set of propositions to serve as a guide for future research. We conclude with a discussion of possible limitations of the model and practical implications for managing diversity in organizations. © 2014 Taylor & Francis.

A new DEA model for technology selection in the presence of ordinal data

This paper suggests a data envelopment analysis (DEA) model for selecting the most efficient alternative in advanced manufacturing technology in the presence of both cardinal and ordinal data. The paper explains the problem of using an iterative method for finding the most efficient alternative and proposes a new DEA model without the need of solving a series of LPs. A numerical example illustrates the model, and an application in technology selection with multi-inputs/multi-outputs shows the usefulness of the proposed approach. © 2012 Springer-Verlag London Limited.

The core critical success factors in implementation of enterprise resource planning systems

The Implementation of Enterprise Resource Planning (ERP) systems require huge investments while ineffective implementations of such projects are commonly observed. A considerable number of these projects have been reported to fail or take longer than it was initially planned, while previous studies show that the aim of rapid implementation of such projects has not been successful and the failure of the fundamental goals in these projects have imposed huge amounts of costs on investors. Some of the major consequences are the reduction in demand for such products and the introduction of further skepticism to the managers and investors of ERP systems. In this regard, it is important to understand the factors determining success or failure of ERP implementation. The aim of this paper is to study the critical success factors (CSFs) in implementing ERP systems and to develop a conceptual model which can serve as a basis for ERP project managers. These critical success factors that are called “core critical success factors” are extracted from 62 published papers using the content analysis and the entropy method. The proposed conceptual model has been verified in the context of five multinational companies.

Uncertainty analysis in the Model Web

This thesis provides a set of tools for managing uncertainty in Web-based models and workflows.To support the use of these tools, this thesis firstly provides a framework for exposing models through Web services. An introduction to uncertainty management, Web service interfaces,and workflow standards and technologies is given, with a particular focus on the geospatial domain.An existing specification for exposing geospatial models and processes, theWeb Processing Service (WPS), is critically reviewed. A processing service framework is presented as a solutionto usability issues with the WPS standard. The framework implements support for Simple ObjectAccess Protocol (SOAP), Web Service Description Language (WSDL) and JavaScript Object Notation (JSON), allowing models to be consumed by a variety of tools and software. Strategies for communicating with models from Web service interfaces are discussed, demonstrating the difficultly of exposing existing models on the Web. This thesis then reviews existing mechanisms for uncertainty management, with an emphasis on emulator methods for building efficient statistical surrogate models. A tool is developed to solve accessibility issues with such methods, by providing a Web-based user interface and backend to ease the process of building and integrating emulators. These tools, plus the processing service framework, are applied to a real case study as part of the UncertWeb project. The usability of the framework is proved with the implementation of aWeb-based workflow for predicting future crop yields in the UK, also demonstrating the abilities of the tools for emulator building and integration. Future directions for the development of the tools are discussed.

A fuzzy decision tree-based duration model for Standard Yorùbá text-to-speech synthesis

In this paper, we present syllable-based duration modelling in the context of a prosody model for Standard Yorùbá (SY) text-to-speech (TTS) synthesis applications. Our prosody model is conceptualised around a modular holistic framework. This framework is implemented using the Relational Tree (R-Tree) techniques. An important feature of our R-Tree framework is its flexibility in that it facilitates the independent implementation of the different dimensions of prosody, i.e. duration, intonation, and intensity, using different techniques and their subsequent integration. We applied the Fuzzy Decision Tree (FDT) technique to model the duration dimension. In order to evaluate the effectiveness of FDT in duration modelling, we have also developed a Classification And Regression Tree (CART) based duration model using the same speech data. Each of these models was integrated into our R-Tree based prosody model. We performed both quantitative (i.e. Root Mean Square Error (RMSE) and Correlation (Corr)) and qualitative (i.e. intelligibility and naturalness) evaluations on the two duration models. The results show that CART models the training data more accurately than FDT. The FDT model, however, shows a better ability to extrapolate from the training data since it achieved a better accuracy for the test data set. Our qualitative evaluation results show that our FDT model produces synthesised speech that is perceived to be more natural than our CART model. In addition, we also observed that the expressiveness of FDT is much better than that of CART. That is because the representation in FDT is not restricted to a set of piece-wise or discrete constant approximation. We, therefore, conclude that the FDT approach is a practical approach for duration modelling in SY TTS applications. © 2006 Elsevier Ltd. All rights reserved.

An integrated assessment model for cross-country pipelines

The cross-country petroleum pipelines are environmentally sensitive because they traverse through varied terrain covering crop fields, forests, rivers, populated areas, desert, hills and offshore. Any malfunction of these pipelines may cause devastating effect on the environment. Hence, the pipeline operators plan and design pipelines projects with sufficient consideration of environment and social aspects along with the technological alternatives. Traditionally, in project appraisal, optimum technical alternative is selected using financial analysis. Impact assessments (IA) are then carried out to justify the selection and subsequent statutory approval. However, the IAs often suggest alternative sites and/or alternate technology and implementation methodology, resulting in revision of entire technical and financial analysis. This study addresses the above issues by developing an integrated framework for project feasibility analysis with the application of analytic hierarchy process (AHP), a multiple attribute decision-making technique. The model considers technical analysis (TA), socioeconomic IA (SEIA) and environmental IA (EIA) in an integrated framework to select the best project from a few alternative feasible projects. Subsequent financial analysis then justifies the selection. The entire methodology has been explained here through a case application on cross-country petroleum pipeline project in India.

Bayesian precalibration of a large stochastic microsimulation model

Calibration of stochastic traffic microsimulation models is a challenging task. This paper proposes a fast iterative probabilistic precalibration framework and demonstrates how it can be successfully applied to a real-world traffic simulation model of a section of the M40 motorway and its surrounding area in the U.K. The efficiency of the method stems from the use of emulators of the stochastic microsimulator, which provides fast surrogates of the traffic model. The use of emulators minimizes the number of microsimulator runs required, and the emulators' probabilistic construction allows for the consideration of the extra uncertainty introduced by the approximation. It is shown that automatic precalibration of this real-world microsimulator, using turn-count observational data, is possible, considering all parameters at once, and that this precalibrated microsimulator improves on the fit to observations compared with the traditional expertly tuned microsimulation. © 2000-2011 IEEE.

Towards the in silico identification of class II restricted T-cell epitopes:a partial least squares iterative self-consistent algorithm for affinity prediction

Motivation: The immunogenicity of peptides depends on their ability to bind to MHC molecules. MHC binding affinity prediction methods can save significant amounts of experimental work. The class II MHC binding site is open at both ends, making epitope prediction difficult because of the multiple binding ability of long peptides. Results: An iterative self-consistent partial least squares (PLS)-based additive method was applied to a set of 66 pep- tides no longer than 16 amino acids, binding to DRB1*0401. A regression equation containing the quantitative contributions of the amino acids at each of the nine positions was generated. Its predictability was tested using two external test sets which gave r pred =0.593 and r pred=0.655, respectively. Furthermore, it was benchmarked using 25 known T-cell epitopes restricted by DRB1*0401 and we compared our results with four other online predictive methods. The additive method showed the best result finding 24 of the 25 T-cell epitopes. Availability: Peptides used in the study are available from http://www.jenner.ac.uk/JenPep. The PLS method is available commercially in the SYBYL molecular modelling software package. The final model for affinity prediction of peptides binding to DRB1*0401 molecule is available at http://www.jenner.ac.uk/MHCPred. Models developed for DRB1*0101 and DRB1*0701 also are available in MHC- Pred

Conceptual Model and Security Requirements for DRM Techniques Used for e-Learning Objects Protection

This paper deals with the security problems of DRM protected e-learning content. After a short review of the main DRM systems and methods used in e-learning, an examination is made of participators in DRM schemes (e-learning object author, content creator, content publisher, license creator and end user). Then a conceptual model of security related processes of DRM implementation is proposed which is improved afterwards to reflect some particularities in DRM protection of e-learning objects. A methodical way is used to describe the security related motives, responsibilities and goals of the main participators involved in the DRM system. Taken together with the process model, these security properties are used to establish a list of requirements to fulfill and a possibility for formal verification of real DRM systems compliance with these requirements.

Mathematical Model and Simulation of a Pneumatic Apparatus for In-Drilling Alignment of an Inertial Navigation Unit during Horizontal Well Drilling

Conventional methods in horizontal drilling processes incorporate magnetic surveying techniques for determining the position and orientation of the bottom-hole assembly (BHA). Such means result in an increased weight of the drilling assembly, higher cost due to the use of non-magnetic collars necessary for the shielding of the magnetometers, and significant errors in the position of the drilling bit. A fiber-optic gyroscope (FOG) based inertial navigation system (INS) has been proposed as an alternative to magnetometer -based downhole surveying. The utilizing of a tactical-grade FOG based surveying system in the harsh downhole environment has been shown to be theoretically feasible, yielding a significant BHA position error reduction (less than 100m over a 2-h experiment). To limit the growing errors of the INS, an in-drilling alignment (IDA) method for the INS has been proposed. This article aims at describing a simple, pneumatics-based design of the IDA apparatus and its implementation downhole. A mathematical model of the setup is developed and tested with Bloodshed Dev-C++. The simulations demonstrate a simple, low cost and feasible IDA apparatus.

Verification and Application of Conceptual Model and Security Requirements on Practical DRM Systems in E-Learning

The paper represents a verification of a previously developed conceptual model of security related processes in DRM implementation. The applicability of established security requirements in practice is checked as well by comparing these requirements to four real DRM implementations (Microsoft Media DRM, Apple's iTunes, SunnComm Technologies’s MediaMax DRM and First4Internet’s XCP DRM). The exploited weaknesses of these systems resulting from the violation of specific security requirements are explained and the possibilities to avoid the attacks by implementing the requirements in designing step are discussed.

Networks of Evolutionary Processors: Java Implementation of a Threaded Processor

This paper is focused on a parallel JAVA implementation of a processor defined in a Network of Evolutionary Processors. Processor description is based on JDom, which provides a complete, Java-based solution for accessing, manipulating, and outputting XML data from Java code. Communication among different processor to obtain a fully functional simulation of a Network of Evolutionary Processors will be treated in future. A safe-thread model of processors performs all parallel operations such as rules and filters. A non-deterministic behavior of processors is achieved with a thread for each rule and for each filter (input and output). Different results of a processor evolution are shown.