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Valerio Bellandi

Researcher at University of Milan

Publications -  99
Citations -  1016

Valerio Bellandi is an academic researcher from University of Milan. The author has contributed to research in topics: Computer science & Big data. The author has an hindex of 17, co-authored 80 publications receiving 901 citations. Previous affiliations of Valerio Bellandi include Siemens & Information Technology University.

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Learning Computer Networking on Open Paravirtual Laboratories

TL;DR: A practical VNL implementation, the open virtual lab (OVL), is used to describe the added value that open source VNLs can give to e-Learning frameworks, achieving a level of students' performance comparable or better than the one obtained when students directly interact with physical networking equipment.
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Concept of Linguistic Variable-Based Fuzzy Ensemble Approach: Application to Interlaced HDTV Sequences

TL;DR: It is demonstrated that the fuzzy ensemble approach model is well suited to image processing and provided case studies in the video-deinterlacing field and can deal with several image types containing motion or detail elements.
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Map-Based Location and Tracking in Multipath Outdoor Mobile Networks

TL;DR: This work presents a technique that provides geolocation and mobility prediction both at network and service level, does not require any change to the existing mobile network infrastructure, and is entirely performed on the mobile network side, making it more robust than other positioning systems with respect to location spoofing and other terminal-based security threats.
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Designing of a type-2 fuzzy logic filter for improving edge-preserving restoration of interlaced-to-progressive conversion

TL;DR: This paper adopted type-2 fuzzy sets concepts to design a weight evaluating approach and proved that the performance of the proposed method was superior, both objectively and subjectively to other different conventional deinterlacing methods.
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Privacy-aware Big Data Analytics as a service for public health policies in smart cities

TL;DR: This paper focuses on balancing quality of life and privacy protection in smart cities by providing a new Big Data-assisted public policy making process implementing privacy-by-design, based on a Big Data Analytics as a Service approach.