Scalability in QoS-aware multicast deployment has become an important research dimension in recent years. In this paper we propose a new scheme named Differentiated QoS Multicast (DQM) based on the Source Specific Multicast (SSM) model in order to provision limited qualitative QoS channels for supporting heterogeneous end users. In a similar fashion to the Differentiated Services paradigm, in D...

There is great potential in using Best Source Selectors (BSS) to improve link availability in aeronautical telemetry applications. While the general notion that diverse data sources can be used to construct a consolidated stream of "better" data is well founded, there is no standardized means of determining the quality of the data streams being merged together. Absent this uniform quality data,...

Increasing applications of laminated composite structures necessitate the development equivalent single layer (ESL) models that can achieve similar accuracy but are more computationally efficient than 3D or layer-wise models. Most ESL displacement-based do not guarantee interfacial continuity shear stresses within laminates. A possible remedy is enforcement interlaminar equilibrium in variation...

In this paper, a numerical algorithm using a coupled Galerkin-Differential Quadrature (DQ) method is proposed for the solution of dam-reservoir interaction problem. The governing differential equation of motion of the dam structure is discretized by the Galerkin method and the DQM is used to discretize the fluid domain. The resulting systems of ordinary differential equations are then solved by...

Data Quality Monitoring (DQM) is the continuous process that evaluates a set of data to determine if they meet the planning objectives of a project. In practice, business managers may prefer to outsource the overall process of DQM, due to either operational or financial reasons. Nowadays, hardwareand service-level outsourcing is usually done by using cloud computing technologies. In this scenar...

Enterprises need high-quality data in order to meet a number of strategic business requirements. Permanent maintenance and sustainable improvement of data quality can be achieved by an enterprise-wide approach only. The paper presents a Maturity Model for Enterprise Data Quality Management (Enterprise DQM), which aims at supporting enterprises in their effort to deliberately design and establis...

Data quality mining (DQM) is a new and promising data mining approach from the academic and the business point of view. Data quality is important to organizations. People use information attributes as a tool for assessing data quality. The goal of DQM is to employ data mining methods in order to detect, quantify, explain and correct data quality deficiencies in very large databases. Data qualit...

Measurement of blood flow rate (Qa) is used to monitor arteriovenous fistulas and grafts that are used for hemodialysis blood access. Most Qa measurements use indicator dilution techniques to measure the recirculation that is induced by the reversal of hemodialysis blood lines. R plus the dialysis circuit flow (Qb) allows the calculation of Qa. The principle of needle reversal also can be used ...

The ultimate goal of data quality management (DQM) is to improve the data quality (DQ) to facilitate enterprises decision-making, and the data quality assessment (DQA) is an important aspect in the process of DQM. Existing research in DQA focuses on the establishment of evaluation indicators and quantified methods in specific areas of application, but does not take into account the evolution of...

The Physics and Data Quality Monitoring (DQM) framework aims at providing a homogeneous monitoring environment across various applications related to data taking at the CMS experiment. In this contribution, the DQM system for the Silicon Strip Tracker will be introduced. The set of elements to assess the status of detector will be mentioned, along with the way to identify problems and trace the...