A Smart Assistant for Visual Recognition of Painted Scenes

Nowadays, smart devices allow people to easily interact with the surrounding environment thanks to existing communication infrastructures, i.e., 3G/4G/5G or WiFi. In the context of a smart museum, data shared by visitors can be used to provide innovative services aimed to improve their cultural experience. In this paper, we consider as case study the painted wooden ceiling of the Sala Magna of Palazzo Chiaramonte in Palermo, Italy and we present an intelligent system that visitors can use to automatically get a description of the scenes they are interested in by simply pointing their smartphones to them. As compared to traditional applications, this system completely eliminates the need for indoor positioning technologies, which are unfeasible in many scenarios as they can only be employed when museum items are physically distinguishable. Experimental analysis aimed to evaluate the performance of the system in terms of accuracy of the recognition process, and the obtained results show its effectiveness in a real-world application scenario

Smart assistance for students and people living in a campus

Being part of one of the fastest growing area in Artificial Intelligence (AI), virtual assistants are nowadays part of everyone's life being integrated in almost every smart device. Alexa, Siri, Google Assistant, and Cortana are just few examples of the most famous ones. Beyond these off-the-shelf solutions, different technologies which allow to create custom assistants are available. IBM Watson, for instance, is one of the most widely-adopted question-answering framework both because of its simplicity and accessibility through public APIs. In this work, we present a virtual assistant that exploits the Watson technology to support students and staff of a smart campus at the University of Palermo. Some in progress results show the effectiveness of the approach we propose

Assisted labeling for spam account detection on twitter

Online Social Networks (OSNs) have become increasingly popular both because of their ease of use and their availability through almost any smart device. Unfortunately, these characteristics make OSNs also target of users interested in performing malicious activities, such as spreading malware and performing phishing attacks. In this paper we address the problem of spam detection on Twitter providing a novel method to support the creation of large-scale annotated datasets. More specifically, URL inspection and tweet clustering are performed in order to detect some common behaviors of spammers and legitimate users. Finally, the manual annotation effort is further reduced by grouping similar users according to some characteristics. Experimental results show the effectiveness of the proposed approach

An optimized procedure for preparation of conditioned medium from Wharton’s jelly mesenchymal stromal cells isolated from umbilical cord

Cell-free therapy based on conditioned medium derived from mesenchymal stromal cells (MSCs) has gained attention in the field of protective and regenerative medicine. However, the exact composition and properties of MSC-derived conditioned media can vary greatly depending on multiple parameters, which hamper standardization. In this study, we have optimized a procedure for preparation of conditioned medium starting from efficient isolation, propagation and characterization of MSCs from human umbilical cord, using a culture medium supplemented with human platelet lysate as an alternative source to fetal bovine serum. Our procedure successfully maximizes the yield of viable MSCs that maintain canonical key features. Importantly, under these conditions, the compositional profile and biological effects elicited by the conditioned medium preparations derived from these MSC populations do not depend on donor individuality. Moreover, approximately 120 L of conditioned medium could be obtained from a single umbilical cord, which provides a suitable framework to produce industrial amounts of toxic-free conditioned medium with predictable composition

Whole-body magnetic resonance imaging in the diagnosis and follow-up of multicentric infantile myofibromatosis: A case report

Myofibromatosis is an uncommon disorder of infancy, characterized by proliferation of myofibroblasts in solitary or multiple nodules. The clinical characteristics depend on the involved sites: Myofibromatosis may develop as a musculoskeletal form, with non-painful swellings and eventual mass effect symptoms, or as a generalized form with visceral involvement and organ failure. Prognosis and therapy vary between the abovementioned patterns. When there is no visceral involvement, the tumors may regress spontaneously; however, the visceral form may represent a lifethreatening condition with poor outcome and it requires aggressive management. Imaging assessment of disease spread is mandatory to determine diagnosis, prognosis and therapy. Due to the young age of the patients, a radiation-free evaluation is recommended. We herein describe a case of musculoskeletal myofibromatosis diagnosed in a 3-month-old male infant, investigated by serial wholebody magnetic resonance imaging (MRI) examination. The histological analysis and MRI characteristics enabled a correct diagnosis and organ involvement assessment with no radiation exposure. Moreover, whole-body MRI sequences provided a detailed evaluation of the disease within a short time frame, reducing the time of sedation, which is required to perform MRI in very young patients. Therefore, whole-body MRI was found to be accurate and safe in the diagnosis and follow-up of multicentric infantile myofibromatosis.Myofibromatosis is an uncommon disorder of infancy, characterized by proliferation of myofibroblasts in solitary or multiple nodules. The clinical characteristics depend on the involved sites: Myofibromatosis may develop as a musculoskeletal form, with non-painful swellings and eventual mass effect symptoms, or as a generalized form with visceral involvement and organ failure. Prognosis and therapy vary between the abovementioned patterns. When there is no visceral involvement, the tumors may regress spontaneously; however, the visceral form may represent a lifethreatening condition with poor outcome and it requires aggressive management. Imaging assessment of disease spread is mandatory to determine diagnosis, prognosis and therapy. Due to the young age of the patients, a radiation-free evaluation is recommended. We herein describe a case of musculoskeletal myofibromatosis diagnosed in a 3-month-old male infant, investigated by serial wholebody magnetic resonance imaging (MRI) examination. The histological analysis and MRI characteristics enabled a correct diagnosis and organ involvement assessment with no radiation exposure. Moreover, whole-body MRI sequences provided a detailed evaluation of the disease within a short time frame, reducing the time of sedation, which is required to perform MRI in very young patients. Therefore, whole-body MRI was found to be accurate and safe in the diagnosis and follow-up of multicentric infantile myofibromatosis

Enhanced P2P Services Providing Multimedia Content

The retrieval facilities of most Peer-to-Peer (P2P) systems are limited to queries based on unique identifiers or small sets of keywords. Unfortunately, this approach is very inadequate and inefficient when a huge amount of multimedia resources is shared. To address this major limitation, we propose an original image and video sharing system, in which a user is able to interactively search interesting resources by means of content-based image and video retrieval techniques. In order to limit the network traffic load, maximizing the usefulness of each peer contacted in the query process, we also propose the adoption of an adaptive overlay routing algorithm, exploiting compact representations of the multimedia resources shared by each peer. Experimental results confirm the validity of the proposed approach, that is capable of dynamically adapting the network topology to peer interests, on the basis of query interactions among users