Leader's competencies. Approaches to effective management of medical organization

Due to the increasing demands on the heads of medical organizations in terms of ensuring the proper quality of medical care, there is a need to pay more and more attention to the leadership qualities of not only the direct head of the institution. It is equally important to form the leader’s competencies among managers at any level: deputy chief medical oficer, head of the medical department, head nurses, and technical service manager.

Aufbruch in die Zukunft: Klima- und Umweltschutz des Mittelstands rund um das Mare Balticum

<p>Struktur und Bedeutung kleiner und mittlerer Unternehmen (KMU) in 11 Ostseeländern; bestehende Engpässe sowie Wachstumsfelder Energie, Klima- und Umweltschutz; Realisierung von Ökonomie durch Ökologie und nachhaltiges Wirtschaften der KMU; Beispiele für Leistungen und realisierte Projekte im Klima- und Umweltschutz: Cradle to Cradle, Corporate Social Responsibility, Skills Alliance Energy saving and sustainable Construction, Energy Service Manager in SMEs, Management and Technologies of Water, Wastewater, Waste and Circular Economy, Entwicklung und Export angepasster Energie- und Umwelttechnologien in Schwellen- und Entwicklungsländern; Ausblick auf künftige Beiträge im Klima- und Umweltschutz.</p>

Analisis Kebutuhan Bahasa Inggris Pramusaji di Hotel Berbintang 5 di Bali

This study aimed at analyzing the English language skills functions and expressions needed as a waiter/ss. This research was a qualitative descriptive. The method used in obtaining the required information were interviews and documentation, in which subjects in this research were Asst. F&B Service Manager, Restaurant Manager, Supervisor, and Restaurant Staff in 5-Star Hotel in Bali. The results of this study indicated that (1) Speaking & listening skills are the main poins that must be mastered by a waiter/ss, and the accuracy of grammar and fluency in communication also have an equally important role, (2) The expression of the language used adjusts to predetermined language functions based on the implementation of Sequence of Service (SOS) in restaurants. From the results of this study it may be necessary to further research on analyzing the needs of English Waiters in a broader scope.

A Lightweight Slice-Based Quality of Service Manager for IoT

Industry 4.0 and digital farming rely on modern communication and computation technologies such as the Internet of Things (IoT) to provide smart manufacturing and farming systems. Having in mind a scenario with a high number of heterogeneous connected devices, with varying technologies and characteristics, the deployment of Industry 4.0 and digital farming solutions faces innovative challenges in different domains (e.g., communications, security, quality of service). Concepts such as network slicing and Software-Defined Networking (SDN) provide the means for faster, simpler, scalable and flexible solutions in order to serve a wide range of applications with different Quality-of-Service (QoS) requirements. Hence, this paper proposes a lightweight slice-based QoS manager for non-3GPP IoT focusing on different use cases and their varying requirements and characteristics. Our focus in this work is on non-3GPP IoT unlicensed wireless technologies and not specifically the end-to-end network slice perspective as described in 5G standards. We implemented and evaluated different QoS models in distinct scenarios in a real experimental environment in order to illustrate the potential of the proposed solution.

Smart SDN Management of Fog Services

<p>We present a smart Service Manager whose role is</p> <p>to direct user requests (such as those coming from IoT devices)</p> <p>at the edge towards appropriate servers where the services they</p> <p>request can be satisfied, when services can be housed at different</p> <p>Fog locations, and the system is subject to variations in workload.</p> <p>The approach we propose is based on using an SDN controller as</p> <p>a decision element, and to incorporate measurement data based</p> <p>machine learning that uses Reinforcement Learning to make the</p> <p>best choices. The system we have developed is illustrated with</p> <p>experimental results on a test-bed in the presence of time-varying</p> <p>loads at the servers. The experiments confirm the ability of the</p> <p>system to adapt to significant changes in system load so as to</p> <p>preserve the QoS perceived by end users.</p>

Smart SDN Management of Fog Services

<p>We present a smart Service Manager whose role is</p> <p>to direct user requests (such as those coming from IoT devices)</p> <p>at the edge towards appropriate servers where the services they</p> <p>request can be satisfied, when services can be housed at different</p> <p>Fog locations, and the system is subject to variations in workload.</p> <p>The approach we propose is based on using an SDN controller as</p> <p>a decision element, and to incorporate measurement data based</p> <p>machine learning that uses Reinforcement Learning to make the</p> <p>best choices. The system we have developed is illustrated with</p> <p>experimental results on a test-bed in the presence of time-varying</p> <p>loads at the servers. The experiments confirm the ability of the</p> <p>system to adapt to significant changes in system load so as to</p> <p>preserve the QoS perceived by end users.</p>