Generating a Performance Stochastic Model from UML Specifications

Since its initiation by Connie Smith, the process of Software Performance Engineering (SPE) is becoming a growing concern. The idea is to bring performance evaluation into the software design process. This suitable methodology allows software designers to determine the performance of software during design. Several approaches have been proposed to provide such techniques. Some of them propose to derive from a UML (Unified Modeling Language) model a performance model such as Stochastic Petri Net (SPN) or Stochastic process Algebra (SPA) models. Our work belongs to the same category. We propose to derive from a UML model a Stochastic Automata Network (SAN) in order to obtain performance predictions. Our approach is more flexible due to the SAN modularity and its high resemblance to UML' state-chart diagram

Stroke prediction context-aware health care system

This paper proposes a prediction framework based on ontology and Bayesian Belief Networks BBN to support a medical teams in every daily. We propose a Stroke Prediction System (SPS), a new software component to handle the uncertainty of having a stroke disease by determining the risk score level. This is composed of four layers: acquisition of data, aggregation, reasoning and application. SPS senses, collects, and analyzes data of a patient, then uses wearable sensors and the mobile application to interact with the patient and staffs. When the risk reaches critical limits, SPS notifies all concerned parties, the patient, the doctor, and the emergency department. The patient profile is also updated to reflect this urgent intervention requirement. A Bayesian model is designed and implemented using the Netica tool to prove its efficiency i) by handling patient context remotely and verifying its changes locally and ii) on predicting missing probabilities and calculate the probability of high risk level for emergency cases. The SPS system improves the accuracy of decision making and uses a new ontology of stroke disease inspired from our Parkinson ontology already developed

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Intelligent web based on mathematic theory. Case study : service composition validation via distributed compiler and graph theory

This paper discusses a model for verifying service composition by building a distributed semi-compiler of service process. In this talk, we introduce a technique that solves the service composition problems such as infinite loops,deadlock and replicate use of the service. Specifically, the client needs to build a composite service by invoking other services but without knowing the exact design of these loosely coupled services. The proposed Distributed Global Service Compiler, by this article, results dynamically from the business process of each service. As a normal compiler cannot detect loops, we apply a graph theory algorithm, a Depth First Search, on the deduced result taken from business process files

Developing service oriented computing model based on context-aware

SOA and Cloud Computing are making major changes in the way companies build and deploy applications. The challenge is to meet the business expectation of faster delivery of new functionality, while at the same time maintaining control of application performance and availability across a growing network of service providers. SOA facilitates the development cycle by providing common features to everyone. However, SOA has some disadvantages such as the lack of information of what a service can provide and how can we discover it. When working with web services, the number of exposed methods or functions becomes a problem for developers. We do not need to deal with whole services if a developer needs to call one function. This article suggests and validates a new selected service model for the SOA. The layout presentation and the communication is described between client and services

CityPro : an integrated city-protection collaborative platform

It’s a big challenge to deal with security in a city. Technology advancements are influencing our life, cities are evolving, and modern cities are referring more and more to digital technologies. Currently, a huge amount of standalone independent-systems operate in the city, their goal is to satisfy some business activities, e.g. banking, customs, hospitals, etc. Data collected by these systems represents, if integrated, a key element in any decision making process. This paper presents a, working, smart collaborative platform to integrate multiple systems to serve the surveillance activities in a city or country. It consists of a collaborative surveillance system, called CityPro. The architecture that we propose is a future vision to protect people and monitor public infrastructures, such as bridges, roads, buildings, etc.; it is designed to deal with and/or prevent abnormal activities like terrorist attacks. CityPro is expected to operate in live-mode by using (intended to use) city adapted IT-infrastructures. At the end of this paper, a typical case study is given, and challenges and future works are also discussed