46 research outputs found
A context-aware multiple Blockchain architecture for managing low memory devices
Blockchain technology constitutes a paradigm shift in the way we conceive
distributed architectures. A Blockchain system lets us build platforms where
data are immutable and tamper-proof, with some constraints on the throughput
and the amount of memory required to store the ledger. This paper aims to solve
the issue of memory and performance requirements developing a multiple
Blockchain architecture that mixes the benefits deriving from a public and a
private Blockchain. This kind of approach enables small sensors - with memory
and performance constraints - to join the network without worrying about the
amount of data to store. The development is proposed following a context-aware
approach, to make the architecture scalable and easy to use in different
scenarios
Structured Knowledge Representation for Image Retrieval
We propose a structured approach to the problem of retrieval of images by content and present a description logic that has been devised for the semantic indexing and retrieval of images containing complex objects. As other approaches do, we start from low-level features extracted with image analysis to detect and characterize regions in an image. However, in contrast with feature-based approaches, we provide a syntax to describe segmented regions as basic objects and complex objects as compositions of basic ones. Then we introduce a companion extensional semantics for defining reasoning services, such as retrieval, classification, and subsumption. These services can be used for both exact and approximate matching, using similarity measures. Using our logical approach as a formal specification, we implemented a complete clientserver image retrieval system, which allows a user to pose both queries by sketch and queries by example. A set of experiments has been carried out on a testbed of images to assess the retrieval capabilities of the system in comparison with expert users ranking. Results are presented adopting a well-established measure of quality borrowed from textual information retrieval
Development of a Metaverse Platform for Tourism Promotion in Apulia
Metaverse is an engaging way to recreate in a digital environment the real
world. It allows people to connect not by just browsing a website, but by using
headsets and virtual reality techniques. The metaverse is actually in a rapid
development phase, thanks to the advances in different topics. This paper
proposes a smart tourism platform in which tourists can interact with guides
and different kinds of suppliers, without the need to phisically visit the city
they are in. We propose some techniques to scan the real world and transpose it
in a metaverse platform, using the recreation of an Italian city, Bari, as a
real life scenario
PrOnto: an Ontology Driven Business Process Mining Tool
Abstract The main aim of data mining techniques and tools is that of identify and extract, from a set of (big) data, implicit patterns which can describe static or dynamic phenomena. Among these latter business processes are gaining more and more attention due to their crucial role in modern organizations and enterprises. Being able to identify and model processes inside organizations is for sure a key asset to discover their weak and strong points thus helping them in the improvement of their competitiveness. In this paper we describe a prototype system able to discover business processes from an event log and classify them with a suitable level of abstraction with reference to a related business ontology. The identified process, and its corresponding level of abstraction, depends on the knowledge encoded in the reference ontology which is dynamically exploited at runtime. The tool has been validated by considering examples and case studies from the literature on process mining
Digital Age of Consent and Age Verification: Can They Protect Children?
Children are increasingly accessing social media content through mobile devices. Existing data protection regulations have focused on defining the digital age of consent, in order to limit collection of children’s personal data by organizations. However, children can easily bypass the mechanisms adopted by apps to verify their age, and thereby be exposed to privacy and safety threats. We conducted a study to identify how the top 10 social and communication apps among underage users apply age limits in their Terms of Use. We also assess the robustness of the mechanisms these apps put in place to verify the age of their users. Moreover, we discuss how automated age recognition techniques can be adopted to increase the effectiveness of the age verification process. Finally, we provide recommendations to app providers and developers to specify the Terms of Use and implement robust age verification mechanisms
Automatic Support for Verification of Secure Transactions in Distributed Environment using Symbolic Model Checking
Electronic commerce needs the aid of software tools to check the validity of business processes in order to fully automate the exchange of information through the network. Symbolic model checking has been used to formally verify specifications of secure transactions in a system for business-to-business applications. The fundamental principles behind symbolic model checking are presented along with techniques used to model mutual exclusion of processes and atomic transactions. The computational resources required to check the example process are presented, and the faults are detected through symbolic verification
A Smart IoT-Aware System For Crisis Scenario Management
In most dangerous events, involving many people in large buildings, rescue workers need to intervene in a timely and targeted manner in order to help most number of people and secure the environments without wasting resources. This work presents an Internet of Things(IoT)-based framework, aiming at monitoring environmental parameters in order to alert rescuers when they exceed some alarm thresholds. A hardware infrastructure driven by a software layer adds flexibility and adaptability to the Complex Event Processing engine and to a rule engine-based reflective middleware that manages and analyzes raw data in conjunction with a knowledge base modeling the application domain
Description Logics Approach to Semantic Matching of Web Services
As more resources and services become available on the Web, there is a growing need for infrastructures that, based on advertised descriptions, semantically match in a peer-to-peer way providers with requesters of web services. We address the problem of matchmaking of web services from a knowledge representation perspective. Based on our approach we propose match categorization in terms of exact match, potential match – when request and offer though not identical are compatible – and partial match – when one or more inconsistency is present – and rank of matches within categories. Then we report on our implementation of the proposed matchmaking framework in a prototype system
A Smart IoT-Aware System For Crisis Scenario Management
In most dangerous events, involving many people in large buildings, rescue workers need to intervene in a timely and targeted manner in order to help most number of people and secure the environments without wasting resources. This work presents an Internet of Things(IoT)-based framework, aiming at monitoring environmental parameters in order to alert rescuers when they exceed some alarm thresholds. A hardware infrastructure driven by a software layer adds flexibility and adaptability to the Complex Event Processing engine and to a rule engine-based reflective middleware that manages and analyzes raw data in conjunction with a knowledge base modeling the application domain