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In this article we argue that smart items and cloud computing can be powerful enablers of servitization as business trend. This is exemplified by an application scenario in healthcare that was developed in the context of the OpSIT-Project in Germany. We present a three-level architecture for a smart healthcare infrastructure. The approach is based on a service-oriented architecture and extends established architectural approaches developed previously at our group. More specifically, it integrates a role model, a layered cloud computing architecture, as well as a fog-computing-informed paradigm in order to provide a viable architecture for healthcare and elderly-care applications. The integration of established paradigms is beneficial with respect to providing adequate quality of service and governance (e.g., data privacy and compliance). It has been verified by expert interviews with healthcare specialists and IT professionals. To further demonstrate the validity of this architectural model, we provide an example use-case as a template for any kind of smart sensor-based healthcare infrastructure.
Interactions among people have substantially changed since the emergence of social networks, the expansion of the Internet and the proliferation of connected mobile devices, and so have the possibilities of collaborative learning, with the inclusion of new e-learning platforms. From this point, assessing human knowledge in these virtual environments is not a trivial task. This work presents a novel cloud-computing-based service which relies on advanced artificial intelligence mechanisms to infer knowledge and interest from users considering the aggregated data presented from/to these users in different social networks. This way it is possible to assess with a certain degree of confidence the user knowledge level in different topics as well as recommend additional specific education related to his/her former studies in order to get a better/desired job.
The present paper introduces a hybrid technique to measure the expertise of users by analyzing their profiles and activities in social networks. Currently, both job seekers and talent hunters are looking for new and innovative techniques to filter jobs and candidates where candidates are trying to improve and make their profiles more attractive. In this sense, the Skillrank approach is based on the conjunction of existing and well-known information and expertise retrieval techniques that perfectly fit the existing web and social media environment to deliver an intelligent component to integrate the user context in the analysis of skills confidence. A major outcome of this approach is that it actually takes advantage of existing data and information available on the web to perform both a ranked list of experts in a field and a confidence value for every professional skill. Thus, expertise and experts can be detected, verified, and ranked using a suited trust metric. An experiment to validate the Skillrank technique based on precision and recall metrics is also presented using two different datasets: (1) ad hoc created using real data from a professional social network and (2) real data extracted from the LinkedIn API.
The complexity of providing medical care in a high-tech environment with a highly specialized, limited labour force makes hospitals more crisis-prone than other industries. An effective defence against crises is only possible if the organizational resilience and the capacity to handle crises become part of the hospitals’ organizational culture. To become more resilient to crises, a raised awareness — especially in the area of human resource (HR) — is necessary. The aim of this paper is to contribute to the process robustness against crises through the identification and evaluation of relevant HR crises and their causations in hospitals.
Qualitative and quantitative methods were combined to identify and evaluate crises in hospitals in the HR sector. A structured workshop with experts was conducted to identify HR crises and their descriptions, as well as causes and consequences for patients and hospitals. To evaluate the findings, an online survey was carried out to rate the occurrence (past, future) and dangerousness of each crisis.
Six HR crises were identified in this study: staff shortages, acute loss of personnel following a pandemic, damage to reputation, insufficient communication during restructuring, bullying, and misuse of drugs. The highest occurrence probability in the future was seen in staff shortages, followed by acute loss of personnel following a pandemic. Staff shortages, damage to reputation, and acute loss of personnel following a pandemic were seen as the most dangerous crises.
The study concludes that coping with HR crises in hospitals is existential for hospitals and requires increased awareness. The six HR crises identified occurred regularly in German hospitals in the past, and their occurrence probability for the future was rated as high.
Information overload is becoming bigger as internet grows. This entails several problems such as difficulty in finding information and redundancy of knowledge. In this paper, a solution of these problems is presented as a global representation of knowledge based on human perception, and modelled by means of ontologies. In this study we present the approach with several advantages as well as some drawbacks related to state of the art technologies.
The aim of this paper is to investigate the motivations that lead higher education students to replace several Learning Management Systems (LMS) services with cloud file hosting services for information sharing and collaboration among them. The research approach is based on the Technology Acceptance Model (TAM). More specifically, the model is devoted to identifying barriers and enablers to the acceptance of these technologies. A questionnaire comprising three factors (Attitude toward using technology, Perceived ease of use and Perceived usefulness) was applied to a sample consisting of 121 higher education students. Results show that the
perceived ease of use of cloud file hosting services is above that of LMS tools and services and that cloud file hosting services presented higher levels of perceived usefulness than standard learning management tools. In addition, attitude toward using cloud file hosting services is well above that of using LMS tools.
Use of cloud computing in healthcare is a promising trend, particularly in utilization of smart items. Access, affordability and quality to proper healthcare is a great challenge in world society. With the utilization of smart sensors, there are possibilities to improve the quality of healthcare services whenever needed. Hence, such smart items services lead to economic advantages for the whole healthcare system. Keeping in mind these opportunities as well as challenges such as security or legal issues, it is important to bring healthcare and IT together. As a result, healthcare business processes need to be modeled in order to provide IT solutions tailored for practice-oriented applications. In this paper, we present a three-level architecture for a smart healthcare infrastructure. Our approach is based on recent literature work and results from conducted expert interviews with healthcare specialists and IT professionals. To demonstrate the applicability of this architecture model, we provide an example use-case as a template for any kind of smart sensor-based healthcare infrastructure.