Twenty-two cases of ameloblastoma and ten cases of adenomatoid odontogenic tumour (AOT) were analyzed comparatively by the AgNOR technique. Ameloblastomas were distributed into three groups according to their clinical behaviour: primary lesions without recurrences (PLWTR), 5 cases; primary lesions with recurrences (PLWR), 4 cases; and recurrences, 13 cases. The cases were also regrouped according to their histological pattern: follicular (9 cases), plexiform (7 cases), acanthomatous (4 cases) and unicystic (2 cases). Considering histological patterns, there was a significant statistical difference only between follicular and plexiform types. There were no significant differences between the group of ameloblastomas and the group of AOTs or between the three groups of ameloblastomas with different clinical behaviour. Our results strongly suggest that the distinct clinical behaviour of ameloblastomas and AOT is not correlated with their cellular proliferation ratio. Thus, the infiltrative ability of the ameloblastomas is probably not related to the cellular proliferation index of these tumours. 相似文献
Analyzing videos and images captured by unmanned aerial vehicles or aerial drones is an emerging application attracting significant attention from researchers in various areas of computer vision. Currently, the major challenge is the development of autonomous operations to complete missions and replace human operators. In this paper, based on the type of analyzing videos and images captured by drones in computer vision, we have reviewed these applications by categorizing them into three groups. The first group is related to remote sensing with challenges such as camera calibration, image matching, and aerial triangulation. The second group is related to drone-autonomous navigation, in which computer vision methods are designed to explore challenges such as flight control, visual localization and mapping, and target tracking and obstacle detection. The third group is dedicated to using images and videos captured by drones in various applications, such as surveillance, agriculture and forestry, animal detection, disaster detection, and face recognition. Since most of the computer vision methods related to the three categories have been designed for real-world conditions, providing real conditions based on drones is impossible. We aim to explore papers that provide a database for these purposes. In the first two groups, some survey papers presented are current. However, the surveys have not been aimed at exploring any databases. This paper presents a complete review of databases in the first two groups and works that used the databases to apply their methods. Vision-based intelligent applications and their databases are explored in the third group, and we discuss open problems and avenues for future research.
A robust Fault Diagnosis (FD) scheme for a real quadrotor Unmanned Aerial Vehicle (UAV) is proposed in this paper. Firstly, a novel Adaptive Thau observer (ATO) is developed to estimate the quadrotor system states and build a set of offset residuals to indicate actuators’ faults. Based on these residuals, some rules of Fault Diagnosis (FD) are designed to detect and isolate the faults as well as estimate the fault offset parameters. Secondly, a synthetic robust optimization scheme is presented to improve Fault Estimation (FE) accuracies, three key issues include modeling uncertainties, and magnitude order unbalances as well as noises are addressed. Finally, a typical fault of rotors is simulated and injected into one of four rotors of the quadrotor, and experiments for the FD scheme have been carried out. Unlike former research works on the FD schemes for quadrotors, our proposed FD scheme based on the ATO can not only detect and isolate the failed actuators, but also estimate the fault severities. Regardless of roughness of the real flying data, the FD results still have sufficient FE accuracies. 相似文献
To prevent unauthorized access to protected trusted platform module (TPM) objects, authorization protocols, such as the object-specific authorization protocol (OSAP), have been introduced by the trusted computing group (TCG). By using OSAP, processes trying to gain access to the protected TPM objects need to prove their knowledge of relevant authorization data before access to the objects can be granted. Chen and Ryan’s 2009 analysis has demonstrated OSAP’s authentication vulnerability in sessions with shared authorization data. They also proposed the Session Key Authorization Protocol (SKAP) with fewer stages as an alternative to OSAP. Chen and Ryan’s analysis of SKAP using ProVerif proves the authentication property. The purpose of this paper was to examine the usefulness of Colored Petri Nets (CPN) and CPN Tools for security analysis. Using OSAP and SKAP as case studies, we construct intruder and authentication property models in CPN. CPN Tools is used to verify the authentication property using a Dolev–Yao-based model. Verification of the authentication property in both models using the state space tool produces results consistent with those of Chen and Ryan. 相似文献
We propose a new formulation of quantum algorithm which allows to distribute amplitudes over two copies of small quantum subsystems. The new method gives a fixed number of copies and applied to the control of multi-qubit system. The analysis for the amount of error due to the distribution process has been presented for a system of 10 qubits with a small quantum subsystems to be copied. The present scheme provides a new way to distribute amplitudes over small quantum subsystems. 相似文献
In this paper, we describe how to use geodesic energies defined on various sets of objects to solve several distance related
problems. We first present the theory of metamorphoses and the geodesic distances it induces on a Riemannian manifold, followed
by classical applications in landmark and image matching. We then explain how to use the geodesic distance for new issues,
which can be embedded in a general framework of matching with free extremities. This is illustrated by results on image and
shape averaging and unlabeled landmark matching.
Laurent Garcin is a former student of the Ecole Polytechnique. He obtained his Ph.D. in 2004 at the Ecole Normale de Cachan, working on
matching methods for landmarks and images. He is an engineer at the French National Geographic Institute.
Laurent Younes is a former student of the Ecole Normale Superieure in Paris. He was awarded the Ph.D. from the University Paris Sud in 1989,
and the thesis advisor certification from the same university in 1995. He works on the statistical analysis of images and
shapes, and on modeling shape deformations and shape spaces.
Laurent Younes entered CNRS, the French National Research Center in October 1991, in which he has been a “Directeur de Recherche"
until 2003. He is now a professor at the Department of Applied Mathematics and Statistics Department and the Center for Imaging
Science at Johns Hopkins University in July 2003. 相似文献
Powder Metallurgy and Metal Ceramics - This work aims to study the effect of mechanical milling of Fe, ZnO, and Ni elemental powders and thermal spraying processes on chemical composition,... 相似文献