High‐pressure rocks from the island of Ios in the Greek Cyclades were examined to resolve the P–T conditions reached during subduction of the two distinct lithotectonic units that are separated by ...the South Cycladic Shear Zone (SCSZ)—the footwall complex composed of Hercynian basement gneisses, schists and amphibolites, and the hangingwall complex composed of blueschists and eclogites. A combination of elastic tensor quartz inclusion in garnet (QuiG) barometry and Zr‐in‐rutile (ZiR) trace element thermometry was used to constrain minimum garnet growth conditions. Garnet from the hangingwall (blueschist) unit record formation pressures that range from 1.5 to 1.9 GPa and garnet from the footwall basement complex record garnet formation pressures of 1.65–2.05 GPa. ZiR thermometry on rutile inclusions within garnet establishes the minimum temperature for garnet formation to be ~480–500°C. That is, there is no evidence in the QuiG and ZiR results that the rocks of the blueschist hangingwall and basement experienced different metamorphic histories during subduction. This is the first reported observation of blueschist facies metamorphism in the Hercynian basement complex. A model is proposed in which initial subduction occurred along a relatively shallow P–T trajectory of ~11°C/km and then transitioned to a steeper, nearly isothermal trajectory at a depth of ~45 km reaching similar peak metamorphic conditions of ~500–525°C at 2.0 GPa for all samples. Such a change in the subduction path could be accomplished by either an increase in the rate of subduction or an increase in the angle of the subduction zone. The present juxtaposition of samples with contrasting mineral assemblages and garnet growth histories is interpreted to have arisen from differences in bulk compositions and variations in the preservation of high‐pressure prograde mineral assemblages during exhumation. The existence of similar P–T conditions and prograde paths in the two units does not require that the rocks were all metamorphosed at the same time and that the SCSZ experienced little movement. Rather, it is suggested that the two units experienced prograde and peak metamorphism at different times and were subsequently juxtaposed along the SCSZ.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
As a result of the spread in the mobile market, new kinds of malware have developed. Many malicious users began to produce harmful applications for open-source operating systems such as Android, and ...closed-source operating systems like iOS. For this reason, new anti-malware methodologies are necessary to identify them. Currently, most of them base their approach on the signature, and it does not allow users to defend themselves from current threats. In this article, we propose an automatic tool able to identify dangerous iOS applications by defining a system model through Milner's Calculus of Communicating Systems and the consequence use of the State Transitions System to evaluate the behaviors of an application, to categorize if it is malware or a legitimate application. As a result of the experiments conducted, we obtained relevant performances with good precision and recall levels.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPUK, ZAGLJ, ZRSKP
•Internal damping effects due to interface resulting in rotordynamic instability.•Novel linear model combining a GW contact with the Yoshimura damping models.•Instability onset speed (IOS) change for ...contact number, preload, Brg. Dyn. Coeff.•Validation of the predicted IOS with Jafri Single-Disk test with interference fits.
Rotating machinery shafting is typically comprised of multiple components that are assembled to ensure reliable operation, proper alignment minimal vibration. However, conventional rotordynamics approximates the shafting as a single, continuous member, neglecting contact interfaces between the components. The presence of an interface can induce microslip, which generates internal friction that may cause instability and machinery failure. A novel approach of modeling the interface viscous damping effect on rotordynamics is proposed by combining a GW (Greenwood and Williamson) contact model with the Yoshimura damping model. All structural components are modeled using 3D solid finite elements. Modal damping ratio is utilized to identify the instability onset speed (IOS). The results show that internal friction has a destabilizing effect on whirl motion above the first critical speed, but has a stabilizing effect on the motion below the first critical speed. The destabilizing effect can be reduced by increasing the bearing damping, however excessive bearing damping can drive the effective damping towards negative values. Increasing the number of interfaces reduces stability while increasing an interface preload prevents microslip, and increases stability. Lastly, smoother surfaces at the interfaces increase the IOS.
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The massive adoption of hand-held devices has led to the explosion of mobile traffic volumes traversing home and enterprise networks, as well as the Internet. Traffic classification (TC), i.e., the ...set of procedures for inferring (mobile) applications generating such traffic, has become nowadays the enabler for highly valuable profiling information (with certain privacy downsides), other than being the workhorse for service differentiation/blocking. Nonetheless, the design of accurate classifiers is exacerbated by the raising adoption of encrypted protocols (such as TLS), hindering the suitability of (effective) deep packet inspection approaches. Also, the fast-expanding set of apps and the moving-target nature of mobile traffic makes design solutions with usual machine learning, based on manually and expert-originated features, outdated and unable to keep the pace. For these reasons deep learning (DL) is here proposed, for the first time, as a viable strategy to design practical mobile traffic classifiers based on automatically extracted features, able to cope with encrypted traffic, and reflecting their complex traffic patterns. To this end, different state-of-the-art DL techniques from (standard) TC are here reproduced, dissected (highlighting critical choices), and set into a systematic framework for comparison, including also a performance evaluation workbench. The latter outcome, although declined in the mobile context, has the applicability appeal to the wider umbrella of encrypted TC tasks. Finally, the performance of these DL classifiers is critically investigated based on an exhaustive experimental validation (based on three mobile datasets of real human users' activity), highlighting the related pitfalls, design guidelines, and challenges.
This research examines the predictors of open interorganizational systems (IOS) adoption by using RosettaNet as a case study. The model used in this research derived its theoretical supports from ...literature related to interorganizational relationships and knowledge management studies. A sequential, multi-method approach integrating both structural equation modeling (SEM) and neural network analysis was employed in this research. Data was collected from 136 small and medium sized enterprises (SME). Our result showed that interorganizational relationships such as communication, collaboration and information sharing play an important role in SMEs’ RosettaNet adoption decisions. Knowledge management practices such as knowledge application, knowledge acquisition and knowledge dissemination also influenced SMEs’ decision to adopt RosettaNet. The findings are useful for decision makers to understand how they can improve the adoption of RosettaNet in their organizations. Unlike previous studies, this research provided additional insights into what influence the adoption of RosettaNet by examining variables beyond the traditional technological attributes which have been studied quite extensively. By integrating SEM with artificial intelligence techniques such as neural network, this study also examined the non-linear and non-compensatory relationships involved in the adoption of RosettaNet.
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Increasingly, big data (including sensitive and commercial-in-confidence data) is being accessible and stored on a range of Internet of Things (IoT) devices, such as our mobile devices. Therefore, ...any vulnerability in IoT devices, operating system or software can be exploited by cybercriminals seeking to exfiltrate our data. In this paper, we use iOS devices as case studies and highlight the potential for pairing mode in iOS devices (which allows the establishment of a trusted relationship between an iOS device and a personal computer) to be exploited for covert data exfiltration. In our three case studies, we demonstrate how an attacker could exfiltrate data from a paired iOS device by abusing a library and a command line tool distributed with iTunes. With the aim of avoiding similar attacks in the future, we present two recommendations.
Recently, Internet of Things (IoT) and cloud computing (CC) have been widely studied and applied in many fields, as they can provide a new method for intelligent perception and connection from M2M ...(including man-to-man, man-to-machine, and machine-to-machine), and on-demand use and efficient sharing of resources, respectively. In order to realize the full sharing, free circulation, on-demand use, and optimal allocation of various manufacturing resources and capabilities, the applications of the technologies of IoT and CC in manufacturing are investigated in this paper first. Then, a CC- and IoT-based cloud manufacturing (CMfg) service system (i.e., CCIoT-CMfg) and its architecture are proposed, and the relationship among CMfg, IoT, and CC is analyzed. The technology system for realizing the CCIoT-CMfg is established. Finally, the advantages, challenges, and future works for the application and implementation of CCIoT-CMfg are discussed.
Sikinos and Ios Islands, located in the Southern Cyclades, represent part of a Cenozoic metamorphic core complex system that exposes subduction‐related metamorphic rocks in the highly extended ...back‐arc region of the Hellenic subduction zone. These exhumed HP‐LT metamorphic units are composed of Mesozoic metasedimentary rocks of the Cycladic Blueschist Unit (CBU) and the Paleozoic Cycladic Basement (CB). The magmatic and stratigraphic evolution of these units, as well as the nature of the contact between the CBU and CB, have remained poorly understood. We used zircon U‐Pb dating to determine crystallization ages of the CB on Sikinos and the maximum deposition ages and detrital provenance of the metasedimentary units to reconstruct the Mesozoic to early Cenozoic stratigraphic and tectonic evolution of the CBU on both islands. The results reveal that the CB in Sikinos is composed of Cambrian‐Silurian metasedimentary rocks intruded by Carboniferous granites and is overlain by metasedimentary rocks of the CBU with depositional ages spanning from Permo‐Triassic to Late Cretaceous. The provenance data from the CBU records a long‐lived tectonic evolution from Paleo‐Tethys subduction and rifting, to passive margin formation, and to subduction of the Neo‐Tethyan Pindos basin. The continuous stratigraphic record and provenance evolution from the CB into the CBU imply a para‐autochthonous relationship. On NE Sikinos and Ios, stratigraphic constraints suggest older‐over‐younger relationships along cryptic‐thrusts, supporting premetamorphic or synmetamorphic structural repetition of the CBU by imbrication, likely during subduction underplating.
Key Points
Zircon U‐Pb analyses on Sikinos argue for a para‐autochthonous CB‐CBU contact and against an allochthonous contact
Deposition of CBU is initially sourced in local synrift basins and transitions to passive continental margin and a cosmopolitan DZ spectrum
MDAs from Sikinos and Ios reveal distinct tectono‐stratigraphic packages and thrust relationships within the CBU formed during subduction
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The growing usage of smartphones in everyday life is deeply (and rapidly) changing the nature of traffic traversing home and enterprise networks, and the Internet. Different tools and middleboxes, ...such as performance enhancement proxies, network monitors and policy enforcement devices, base their functions on the knowledge of the applications generating the traffic. This requirement is tightly coupled to an accurate traffic classification, being exacerbated by the (daily) expanding set of apps and the moving-target nature of mobile traffic. On the top of that, the increasing adoption of encrypted protocols (such as TLS) makes classification even more challenging, defeating established approaches (e.g., Deep Packet Inspection).
To this end, in this paper we aim to improve the performance of classification of mobile apps traffic by proposing a multi-classification (viz. fusion) approach, intelligently-combining outputs from state-of-the-art classifiers proposed for mobile and encrypted traffic classification. Under this framework, four classes of different combiners (differing in whether they accept soft or hard classifiers' outputs, the training requirements, and the learning philosophy) are taken into account and compared. The present approach enjoys modularity, as any classifier may be readily plugged-in/out to improve performance further. Finally, based on a dataset of (true) users' activity collected by a mobile solutions provider, our results demonstrate that classification performance can be improved according to all considered metrics, up to +9.5% (recall score) with respect to the best state-of-the-art classifier. The proposed system is also capitalized to validate a novel pre-processing of traffic traces, here developed, and assess performance sensitivity to traffic object (temporal) segmentation, before actual classification.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPUK, ZRSKP
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