Network Strategy for Entrepreneurs

Networks are an emerging area within the literature related to how entrepreneurs transfer knowledge, seek partnerships, and ultimately interact with others. Some terms with which this area has been defined are Business Networks, Knowledge Networks & Collaboration Networks. It is a cross-cutting phenomenon in various areas of knowledge, such as open innovation and entrepreneurship. However, the relevance of the use of networks for entrepreneurs and the development of global start-ups leads us to the need to propose a conceptual framework for the planning and administration of these business networks. It is an analytical investigation with a case study methodology. They are cases of the cities of Sao Paulo (Brazil) and Santiago (Chile) mainly of consulting and software services. From the models usually used in entrepreneurship, those with integrated tools and methodologies for the development of business networks by founders or administrators of start-ups.

Scalability resilience framework using application-level fault injection for cloud-based software services

This paper presents an investigation into the effect of faults on the scalability resilience of cloud-based software services. The study introduces an experimental framework using the Application-Level Fault Injection (ALFI) to investigate how the faults at the application level affect the scalability resilience and behaviour of cloud-based software services. Previous studies on scalability analysis of cloud-based software services provide a baseline of the scalability behaviour of such services, allowing to conduct in-depth scalability investigation of these services. Experimental analysis on the EC2 cloud using a real-world cloud-based software service is used to demonstrate the framework, considering delay latency of software faults with two varied settings and two demand scenarios. The experimental approach is explained in detail. Here we simulate delay latency injection with two different times, 800 and 1600 ms, and compare the results with the baseline data. The results show that the proposed approach allows a fair assessment of the fault scenario’s impact on the cloud software service’s scalability resilience. We explain the use of the methodology to determine the impact of injected faults on the scalability behaviour and resilience of cloud-based software services.

Edge Computing for Secured IoT Analytics on the Cloud

This chapter provides an insight into building healthcare applications that are deployed in the cloud storage using edge computing and IoT data analytics approaches. Data is collected from environments both within or external to the hospital. The devices that are connected enable the healthcare providers to monitor patients at large distances, manage chronic disease, and manage medication dosages. The data from these devices can be added to clinical research to gain an insight into the participant's experiences. Artificial intelligence techniques like machine learning or deep learning can be employed at the edge of the networks for IoT analytics of multiple data streams in online mode. The industrial edge computing is growing rapidly from 7% in 2019 to being expected to reach approximately 16% by 2025. The total market for intelligent industrial edge computing that includes hardware, software, services has reached $11.6B in 2019 and is expected to increase to $30.8B by 2025.

Semantic models for assessing the influence of a combination of factors on the development of diseases

The analysis of approaches and solutions to the problem of risk assessment and prognosis of conditions and development of diseases is presented. It is shown that the implementation of software services on various platforms complicates the possibility of their comprehensive use and the choice between the available solutions. This has risen the urgency of creating a unified semantic model of diseases that integrates various methods and approaches to solving this problem and accumulates knowledge about risks and prognosis in a unified information space. A new semantic model is proposed to take into account influence of a combination of factors on development of various events that threaten health and life. The feature of the model is its independence from a specific disease or a group of diseases, which allows it to be used in various branches of medicine. This model has been tested on the IACPaaS platform. A software solver has been implemented that allows generating a clear explanation based on the knowledge base and analysis of the patient's electronic medical record. The application of the new model for the formation of knowledge is shown on the example of risk assessment and prognosis of cardiovascular events.

Information and Communication Security Mechanisms For Microservices-based Systems

Security has become paramount in modern software services as more and more security breaches emerge, impacting final users and organizations alike. Trends like the Microservice Architecture bring new security challenges related to communication, system design, development, and operation. The literature presents a plethora of security-related solutions for microservices-based systems, but the spread of information difficult practitioners' adoption of novel security related solutions. In this study, we aim to present a catalogue and discussion of security solutions based on algorithms, protocols, standards, or implementations; supporting principles or characteristics of information security, considering the three possible states of data, according to the McCumber Cube. Our research follows a Systematic Literature Review, synthesizing the results with a meta-aggregation process. We identified a total of 30 primary studies, yielding 75 security solutions for the communication of microservices.

The Biomedical Research Hub: A Federated Platform for Patient Research Data

Objective. The objective was to develop and operate a cloud-based federated system for managing, analyzing and sharing patient data for research purposes, while allowing each resource sharing patient data to operate their component based upon their own governance rules. The federated system is called the Biomedical Research Hub (BRH). Methods. The BRH is a cloud-based federated system built over a core set of software services called framework services. BRH framework services include authentication and authorization, services for generating and assessing FAIR data, and services for importing and exporting bulk clinical data. The BRH includes data resources providing data operated by different entities and workspaces that can access and analyze data from one or more of the data resources in the BRH. Results. The BRH contains multiple data commons that in aggregate provide access to over 6 PB of research data from over 400,000 research participants. Discussion and conclusion. With the growing acceptance of using public cloud computing platforms for biomedical research, and the growing use of opaque persistent digital identifiers for datasets, data objects, and other entities, there is now a foundation for systems that federate data from multiple independently operated data resources that expose FAIR APIs, each using a separate data model. Applications can be built that access data from one or more of the data resources.

Lithuania probe hurts China's high-end phone market

Significance Notably, the report suggests censorship in China may be increasingly hardware-based, triggering international concerns about Chinese-made phones. Lithuania's defence ministry has called on citizens to stop purchasing Chinese smartphones and, if possible, to dispose of those they already own. Impacts The Chinese-language nature of the report’s findings may cause a greater spotlight on diaspora communities in Europe. Other Chinese smartphones will likely face similar scrutiny as governments try to gauge the prevalence of the censorship hardware. The Xiaomi story will feed growing distrust of Chinese hardware and software services, especially in advanced markets.