Hossein Seif Zadeh

Influential it Management Trends: An International Study

This paper is based on data collected as part of an 11-year authors’ survey research on IT trends in different geographic regions, including North America, Europe, Asia, Australia, Africa, and Latin America. This study focuses on global similarities and differences in technology trends (e.g., management concerns, influential technologies, budgets/spending, organizational considerations) among geographies to gain insight into the challenges that IT and non-IT executives face today as well as provide an understanding of the impact these technologies have on the organization’s long-term plans and investments. The results for the 11-year period show that the top five management concerns are: (i) IT-business alignment; (ii) business agility; (iii) business cost reduction/controls; (iv) business productivity; and (v) security/privacy. The five most influential technologies are: (i) analytics/business intelligence; (ii) cloud computing; (iii) ERP systems; (iv) CRM systems; and (v) security technologies. Taken together, these findings suggest that the alignment of IT and the business and leveraging IT to reduce business expenses and generate revenue are and will remain essential. The results also suggest that the role of the CIO is evolving and offshore outsourcing is on the rise. Budgets, hiring, and salaries are also increasing, albeit cautiously. This research provides important implications for IT managers to benchmark considerations such as organizational, sourcing, spending, issues/concerns, and technologies across geographies, and sheds light on a perspective on leveraging important IT trends to make thoughtful decisions about them over the coming years, and address current business challenges.

An Intelligence e-Risk Detection Model to Improve Decision Efficiency in the Context of the Orthopaedic Operating Room

Decision making in healthcare is unstructured, complex and critical. Today, given the healthcare professionals are continually under immense time pressure to make appropriate treatment decisions. Moreover, in order to make such decisions it is necessary for them to process large amounts of disparate data and information. We contend that such a context is appropriate for the application of real time intelligent risk detection decision support system. To illustrate the benefits of risk detection to improve decision efficacy in healthcare contexts we focus on the case of the orthopaedic operating room for hip and knee replacements. In the orthopaedic operating room complex high risk decisions must be made which have for reaching implications on the success of the surgery and ongoing quality of life of the patient.

An Intelligence Risk Detection Framework to Improve Decision Efficiency in Healthcare Contexts: The Example of Pediatric Congenital Heart Disease

Superior decision making in healthcare can literally mean the difference between life and death. Given the time pressures faced by healthcare professionals coupled with the need to process large amounts of disparate data and information to make appropriate treatment decisions, these professionals are faced with an increasingly challenging work context. We contend that such a context is appropriate for the application of real time intelligent risk detection decision support systems and try to develop a suitable model. To illustrate the benefits of risk detection to improve decision efficacy in healthcare contexts we focus on the case of Congenital Heart Disease (CHD), an area which requires complex high risk decisions to facilitate identification of appropriate treatment strategies.

NaMOS; scheduling Patrol Boats and crews for the Royal Australian Navy

A system for optimum allocating of crews to a new class of Patrol Boats was developed by Horn et al [1] as part of a feasibility study commissioned by Australian Defence Forces. In their work, Horn et al [1] implemented a pilot study of multicrewing via simulated annealing coupled with unique heuristic techniques within a multi-stage problem-solving framework. This paper outlines an extension of that work that was carried out under contract by the research arm of the Australian Department of Defence (Defence Science and Technology Organisation, aka DSTO). This work not only embraces, but also extends, the work of Horn et al [1]. As part of this research an open and extendable optimization platform was developed. Two optimization routines (including Adaptive Simulated Annealing (ASA)) were developed and implemented as plug-ins to the framework. Additionally, human-computer interaction (HCI) principles were used to develop a new user interface for the optimization framework. The system was successfully deployed and is now being used by the Patrol Boat Force Element Group of the Royal Australian Navy.

Succeeding Through Service Innovation: Consumer Directed Care in the Aged Care Sector

The growing challenge and diversity of ageing populations is a key global issue for struggling health systems. Consumer Directed Care (CDC), an innovative service delivery system, opens up possibilities for re-defining consumer expectations, prompting change in how health service providers operate. As a service delivery model, CDC offers improved responsiveness to individual requirements; and increased transparency in the use of allocated funding. Where implemented, CDC has established new relationships and interactions between key stakeholders, co-creating value for older citizens. This chapter reviews some drivers for the development of service innovation, surveys various in-country approaches, highlights current trends in CDC delivery and describes an EU policy impact assessment instrument to aid funding bodies. The chapter concludes by speculating on organizational outcomes from CDC and the likelihood that the introduction of this innovative service delivery model will require closer collaborative relationships between service providers and information technology specialists.

Robustness of an optimized fuzzy logic controller to plant variations

The application of a stochastic optimizer to the problem of the control of a highly flexible space structure, and its robustness, is examined. The optimized fuzzy logic controller is used to perform a certain maneuver. A model of the flexible space structure was developed in a rigid multi-body dynamics software package called Odessa, and this model was used as a basis for deriving a number of other simulation models that have physical properties deviating from those of the ideal model. These models are used to check robustness of the optimized fuzzy logic controller with respect to various degrees of physical property deviation of the structure. Model variations were classified into a number of categories. Results of the simulations are presented in a convenient format to make comparison of the controller performance under various system parameter deviations easier. These simulations show the fuzzy logic controller to be remarkably robust

Implementation and applications of a constrained multi-objective optimization method

This paper starts by introducing a very flexible aerospace structure and defines the problem of attitude control (π/2 rad rotation) as well as vibration suppression of the structure. A nominal fuzzy logic controller had been designed and used as a basis for design of a constrained optimized fuzzy controller with multiple objectives. Optimization algorithm and procedure are explained. Furthermore this paper proposes an innovative application of the optimization and the optimized controller in the field of rover goal-seeking. Rover goal-seeking problem, and use of the optimization methodology are explained.