Search results for " Mach"
showing 10 items of 1388 documents
Benefits of learning technologies in medical training, from full-scale simulators to virtual reality and multimedia presentations
2010
The rapid growth of technology provides a wide range of new learning tools such as multimedia presentations of materials, interactive animated images for anatomy learning, 3-D models, full-scale (FS) patient simulators, and microworld training software, which are virtual reality tools that include high-level interactive haptic properties. These new learning approaches have been recently used in medical training and education.
CH of masonry materials via meshless meso-modeling
2014
In the present study a multi-scale computational strategy for the analysis of masonry structures is presented. The structural macroscopic behaviour is obtained making use of the Computational Homogenization (CH) technique based on the solution of the boundary value problem (BVP) of a detailed Unit Cell (UC) chosen at the meso-scale and representative of the heterogeneous material. The smallest UC is composed by a brick and half of its surrounding joints, the former assumed to behave elastically while the latter considered with an elastoplastic softening response. The governing equations at the macroscopic level are formulated in the framework of finite element method while the Meshless Meth…
Multiset Kernel CCA for multitemporal image classification
2013
The analysis of multitemporal remote sensing images is becoming an increasingly important problem because of the upcoming scenario of multispectral satellite constellations monitoring our Planet. Algorithms that can analyze such amount of heterogeneous information are necessary. While linear techniques have been extensively deployed, this work considers a kernel method that finds nonlinear correlations between all image sources and the class labels. We introduce in this context the Kernel Canonical Correlation Analysis (KCCA) to exploit the wealth of temporal image information and to handle nonlinear relations in a natural way via kernels. To achieve this goal, we use the generalization of …
Application of deep convolutional neural networks for the detection of anthracnose in olives using VIS/NIR hyperspectral images
2021
Abstract Anthracnose is one of the primary diseases that affect olive production before and after harvest, causing severe damage and economic losses. The objective of this work is to detect this disease in the early stages, using hyperspectral images and advanced modelling techniques of Deep Learning (DL) and convolutional neural networks (CNN). The olives were artificially inoculated with the fungus. Hyperspectral images (450–1050 nm) of each olive were acquired until visual symptoms of the disease were observed, in some cases up to 9 days. The olives were classified into two classes: control, inoculated with water, and fungi composed of olives inoculated with the fungus. The ResNet101 arc…
Fracture strength of endodontically treated lateral incisors restored with new zirconia reinforced rice husk nanohybrid composite
2020
Background This study aimed to compare the fracture strength, fracture pattern and type of fracture of endodontically treated maxillary lateral incisors restored with new zirconia reinforced rice husk nanohybrid composite. Material and Methods Eighty mature permanent maxillary lateral incisors from patients age range of 30-60 years with single canal were selected and randomly divided into: Group 1 – RCT + nanofilled composite (Filtek), Group 2 – RCT + microhybrid composite (Zmack), Group 3 – RCT + new nanohybrid composite (Zr-Hybrid) and Group 4 - Intact teeth (control). Standardized mesio-palatal-distal cavity was prepared, and endodontic treatment was carried out using crown-down techniqu…
Quantum Finite One-Counter Automata
1999
In this paper the notion of quantum finite one-counter automata (QF1CA) is introduced. Introduction of the notion is similar to that of the 2-way quantum finite state automata in [1]. The well-formedness conditions for the automata are specified ensuring unitarity of evolution. A special kind of QF1CA, called simple, that satisfies the well-formedness conditions is introduced. That allows specify rules for constructing such automata more naturally and simpler than in general case. Possible models of language recognition by QF1CA are considered. The recognition of some languages by QF1CA is shown and compared with recognition by probabilistic counterparts.
A New Genetic Approach for the Partitioning Problem in Distributed Virtual Environment Systems
2004
The Partitioning problem is a key issue in the design of Distributed Virtual Environment (DVE) systems based on a server-network architecture. This problem consist of efficiently assigning the clients of the simulation (avatars) to the system servers. Despite the existing literature proposes different evolutive approaches for solving this NP-hard problem, an approach based on genetic algorithms is considered as the current best partitioning mechanism.
Massive Lesions Classification using Features based on Morphological Lesion Differences
2007
Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based on morphological lesion differences. Some classifiers as a Feed Forward Neural Network, a K-Nearest Neighbours and a Support Vector Machine are used to distinguish the pathological records from the healthy ones. The results obtained in terms of sensiti…
Multitasking associative networks.
2012
We introduce a bipartite, diluted and frustrated, network as a sparse restricted Boltzman machine and we show its thermodynamical equivalence to an associative working memory able to retrieve multiple patterns in parallel without falling into spurious states typical of classical neural networks. We focus on systems processing in parallel a finite (up to logarithmic growth in the volume) amount of patterns, mirroring the low-level storage of standard Amit-Gutfreund-Sompolinsky theory. Results obtained trough statistical mechanics, signal-to-noise technique and Monte Carlo simulations are overall in perfect agreement and carry interesting biological insights. Indeed, these associative network…
A new type of hydraulic cylinder system controlled by the new-type hydraulic transformer
2013
In order to enhance the efficiency of the hydraulic system, one new-type hydraulic transformer is presented in this paper. First, the basic structure and the principle of the new-type hydraulic transformer are explained. Then, the mathematical models including both the inner and outer loops are analyzed. Moreover, two kinds of control methods are discussed corresponding to the two loops, respectively. Furthermore, the proposed strategies are translated into the simulation languages, and the simulation is made in Simulink. Finally, the prototypes of new-type hydraulic transformer and the test rig are constructed to test the performance. Both the simulated and experimental results show that …