The Iron Age Clay Figurines from Karkemish (2011-2015 Campaigns) and the Coroplastic Art of the Syro-Anatolian Region

This is a study concerning the Iron Age coroplastic production in the Northern Levant. The research is mostly based on new data gathered from the Joint Turco-Italian Expedition at Karkemish (Gaziantep, Turkey). Figurines presented in this study are limited to the 2011-2015 excavation seasons and they are analyzed from a range of aspects. The work in fact primarily focuses on contextual data, being the starting point for the research. A preliminary typological and chronological framing is also provided, while a tentative functional interpretation is suggested by means of a careful examination of the local iconographic and written repertoires. Furthermore, ethnographic comparisons are sometimes used in order to better define the semantic meaning beyond this production. Comparisons with other key sites located in the Middle Euphrates basin are also presented with the main aim to define a peculiar regional pattern. A minor part of this dissertation is also dedicated to the study of the coroplastic art in the entire northern Levantine region. The aim, in this case, is evidently that of identifying different regional productions, which at the state of the research could be traced back just for a few regions. Thus new important data are provided for the Amuq Plain, the Islahiye Valley and the rest of Inner Syria.

Wireless Network Analytics for Next Generation Spectrum Awareness

The importance of networks, in their broad sense, is rapidly and massively growing in modern-day society thanks to unprecedented communication capabilities offered by technology. In this context, the radio spectrum will be a primary resource to be preserved and not wasted. Therefore, the need for intelligent and automatic systems for in-depth spectrum analysis and monitoring will pave the way for a new set of opportunities and potential challenges. This thesis proposes a novel framework for automatic spectrum patrolling and the extraction of wireless network analytics. It aims to enhance the physical layer security of next generation wireless networks through the extraction and the analysis of dedicated analytical features. The framework consists of a spectrum sensing phase, carried out by a patrol composed of numerous radio-frequency (RF) sensing devices, followed by the extraction of a set of wireless network analytics. The methodology developed is blind, allowing spectrum sensing and analytics extraction of a network whose key features (i.e., number of nodes, physical layer signals, medium access protocol (MAC) and routing protocols) are unknown. Because of the wireless medium, over-the-air signals captured by the sensors are mixed; therefore, blind source separation (BSS) and measurement association are used to estimate the number of sources and separate the traffic patterns. After the separation, we put together a set of methodologies for extracting useful features of the wireless network, i.e., its logical topology, the application-level traffic patterns generated by the nodes, and their position. The whole framework is validated on an ad-hoc wireless network accounting for MAC protocol, packet collisions, nodes mobility, the spatial density of sensors, and channel impairments, such as path-loss, shadowing, and noise. The numerical results obtained by extensive and exhaustive simulations show that the proposed framework is consistent and can achieve the required performance.