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

3D-Printed Hermetic Alumina Housings

Ceramics are repeatedly investigated as packaging materials because of their gas tightness, e.g., as hermetic implantable housing. Recent advances also make it possible to print the established aluminum oxide in a Fused Filament Fabrication process, creating new possibilities for manufacturing personalized devices with complex shapes. This study was able to achieve integration of channels with a diameter of 500 m (pre-sintered) with a nozzle size of 250 m (layer thickness 100 m) and even closed hemispheres were printed without support structures. During sintering, the weightbearing feedstock shrinks by 16.7%, resulting in a relative material density of 96.6%. The well-known challenges of the technology such as surface roughness (Ra = 15–20 m) and integrated cavities remain. However, it could be shown that the hollow structures in bulk do not represent a mechanical weak point and that the material can be gas-tight (<1012 mbar s1). For verification, a volume-free helium leak test device was developed and validated. Finally, platinum coatings with high adhesion examined the functionalization of the ceramic. All the prerequisites for hermetic housings with integrated metal structures are given, with a new level of complexity of ceramic shapes available

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

Businesses’ Choice for an Accounting Software

Every business whether small, medium, or big needs a tool to help organize and keep a record of its Finances. Before computers and digitalization, it may have been a notebook, but nowa-days almost every business relies on accounting software. This research-based thesis aims to study how companies choose their accounting system. To reach the required conclusion, the author studied theoretically the different types of accounting systems and studied the structure of the accounting department in different companies. The study also included the possible job positions that companies may have in the field of finance and accounting, the hierarchy between the positions, and the tasks. This thesis consists of a theoretical and empirical part. The theory part aims for developing a good understanding of what is accounting software in general, its features, and types and how does accounting sector operate in a company, and the structure of the accounting department in companies. The empirical part focuses on data collected to answer the research objective. The study employs qualitative research techniques in the form of a fully structured interview. The respondents are professionals in the field of accounting. An interview section will be carried on collecting data on how companies decide on choosing the right accounting software The overall conclusion of the results was presented in the form of findings, which did include patterns and features that companies pursue when choosing an accounting system. The conclu-sion was also presented in the form of two tables that did summarize features that meant the most for the companies and industry-specific features that companies needed as a must

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

Corporate governance and long run performance of seasoned equity issuers

This paper examines the effect of corporate governance on the likelihood of issuing Seasoned Equity Offerings (SEO) between 1990 and 2005. It also examines the long-run post-issue performance using operating and stock return measures. Our results suggest that well-governed firms are less likely to issue equity. Nevertheless, when they do so, they outperform both matching non-issuers and issuers with minimal shareholders' rights from pre- to post-issue--with the highest operating out-performance occurring in the two post-issue years. A negative correlation exists between the post-issue performance and the anti-takeover measures, primarily, the protection associated with management entrenchment. Nonetheless, measures of board structure do not appear to affect the post-issue operating performance. Overall, corporate governance appears to be an effective internal control mechanism that restrains managers' incentives to either take an SEO issuance decision that does not serve the interests of shareholders or invest the capital raised in value-destroying projects.Seasoned equity offers Operating performance Corporate governance Long-run

Simultaneous analysis of multiple big data networks : mapping graphs into a data model

Network analysis is of great interest to web and cloud companies, largely because of the huge number of web-networks users and services. Analyzing web networks is helpful for organizations that profit from how network nodes (e.g. web users) interact and communicate with each other. Currently, network analysis methods and tools support single network analysis. One of the Web 3.0 trends, however, namely personalization, is the merging of several user accounts (social, business, and others) in one place. Therefore, the new web requires simultaneous multiple network analysis. Many attempts have been made to devise an analytical approach that works on multiple big data networks simultaneously. This chapter proposes a new model to map web multi-network graphs in a data model. The result is a multidimensional database that offers numerous analytical measures of several networks concurrently. The proposed model also supports real-time analysis and online analytical processing (OLAP) operations, including data mining and business intelligence analysis