A Fuzzy Logic Approach in Modeling and Simulation of a Scheduling System for Hospital Admissions Using ARENA® simulation software

The aim of this project is to develop a simulation model of a scheduling system based on practical situation implemented on ARENA® simulation software. Besides, this project also seeks to incorporate Fuzzy Logic Control in decision making processes. This project mainly focuses to develop a model of a scheduling system for admission of hospital Emergency Department (ED) using ARENA® simulation software

Taxonomic classification of planning decisions in health care: a review of the state of the art in OR/MS

We provide a structured overview of the typical decisions to be made in resource capacity planning and control in health care, and a review of relevant OR/MS articles for each planning decision. The contribution of this paper is twofold. First, to position the planning decisions, a taxonomy is presented. This taxonomy provides health care managers and OR/MS researchers with a method to identify, break down and classify planning and control decisions. Second, following the taxonomy, for six health care services, we provide an exhaustive specification of planning and control decisions in resource capacity planning and control. For each planning and control decision, we structurally review the key OR/MS articles and the OR/MS methods and techniques that are applied in the literature to support decision making

Fuzzy-logic-based control, filtering, and fault detection for networked systems: A Survey

This paper is concerned with the overview of the recent progress in fuzzy-logic-based filtering, control, and fault detection problems. First, the network technologies are introduced, the networked control systems are categorized from the aspects of fieldbuses and industrial Ethernets, the necessity of utilizing the fuzzy logic is justified, and the network-induced phenomena are discussed. Then, the fuzzy logic control strategies are reviewed in great detail. Special attention is given to the thorough examination on the latest results for fuzzy PID control, fuzzy adaptive control, and fuzzy tracking control problems. Furthermore, recent advances on the fuzzy-logic-based filtering and fault detection problems are reviewed. Finally, conclusions are given and some possible future research directions are pointed out, for example, topics on two-dimensional networked systems, wireless networked control systems, Quality-of-Service (QoS) of networked systems, and fuzzy access control in open networked systems.This work was supported in part by the National Natural Science Foundation of China under Grants 61329301, 61374039, 61473163, and 61374127, the Hujiang Foundation of China under Grants C14002 andD15009, the Engineering and Physical Sciences Research Council (EPSRC) of the UK, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

v-Mapper: an application-aware resource consolidation scheme for cloud data centers

Cloud computing systems are popular in computing industry for their ease of use and wide range of applications. These systems offer services that can be used over the Internet. Due to their wide popularity and usage, cloud computing systems and their services often face issues resource management related challenges. In this paper, we present v-Mapper, a resource consolidation scheme which implements network resource management concepts through software-defined networking (SDN) control features. The paper makes three major contributions: (1) We propose a virtual machine (VM) placement scheme that can effectively mitigate the VM placement issues for data-intensive applications; (2) We propose a validation scheme that will ensure that a cloud service is entertained only if there are sufficient resources available for its execution and (3) We present a scheduling policy that aims to eliminate network load constraints. We tested our scheme with other techniques in terms of average task processing time, service delay and bandwidth usage. Our results demonstrate that v-Mapper outperforms other techniques and delivers significant improvement in system’s performance

Application of computational intelligence to explore and analyze system architecture and design alternatives

Systems Engineering involves the development or improvement of a system or process from effective need to a final value-added solution. Rapid advances in technology have led to development of sophisticated and complex sensor-enabled, remote, and highly networked cyber-technical systems. These complex modern systems present several challenges for systems engineers including: increased complexity associated with integration and emergent behavior, multiple and competing design metrics, and an expansive design parameter solution space. This research extends the existing knowledge base on multi-objective system design through the creation of a framework to explore and analyze system design alternatives employing computational intelligence. The first research contribution is a hybrid fuzzy-EA model that facilitates the exploration and analysis of possible SoS configurations. The second contribution is a hybrid neural network-EA in which the EA explores, analyzes, and evolves the neural network architecture and weights. The third contribution is a multi-objective EA that examines potential installation (i.e. system) infrastructure repair strategies. The final contribution is the introduction of a hierarchical multi-objective evolutionary algorithm (MOEA) framework with a feedback mechanism to evolve and simultaneously evaluate competing subsystem and system level performance objectives. Systems architects and engineers can utilize the frameworks and approaches developed in this research to more efficiently explore and analyze complex system design alternatives --Abstract, page iv

Towards a cyber physical system for personalised and automatic OSA treatment

Obstructive sleep apnea (OSA) is a breathing disorder that takes place in the course of the sleep and is produced by a complete or a partial obstruction of the upper airway that manifests itself as frequent breathing stops and starts during the sleep. The real-time evaluation of whether or not a patient is undergoing OSA episode is a very important task in medicine in many scenarios, as for example for making instantaneous pressure adjustments that should take place when Automatic Positive Airway Pressure (APAP) devices are used during the treatment of OSA. In this paper the design of a possible Cyber Physical System (CPS) suited to real-time monitoring of OSA is described, and its software architecture and possible hardware sensing components are detailed. It should be emphasized here that this paper does not deal with a full CPS, rather with a software part of it under a set of assumptions on the environment. The paper also reports some preliminary experiments about the cognitive and learning capabilities of the designed CPS involving its use on a publicly available sleep apnea database

Mining association rules for admission control and service differentiation in e-commerce applications

Workload demands in e-commerce applications are very dynamic in nature, therefore it is essential for internet service providers to manage server resources effectively to maximise total revenue in server overloading situations. In this paper, a data mining technique is applied to a typical e-commerce application model for identification of composite association rules that capture user navigation patterns. Two algorithms are then developed based on the derived rules for admission control, service differentiation and priority scheduling. Our approach takes the following into consideration: a) only final purchase requests result in company revenue; b) any other request can potentially lead to a final purchase, depending upon the likelihood of the navigation sequence that starts from current request and leads to final purchase; c) service differentiation and priority assignment are based on aggregated confidence and average support of the composite association rules. As identification of composite association rules and computation of confidence and support of the rules can be pre-computed offline, the proposed approach incurs minimum performance overheads. The evaluation results suggest that the proposed approach is effective in terms of request management for revenue maximisation