In this paper, we describe Swoop, a hypermedia inspired Ontology Browser and Editor based on OWL, the recently standardized Web-oriented ontology language. After discussing the design rationale and architecture of Swoop, we focus mainly on its features, using illustrative examples to highlight its use. We demonstrate that with its Web-metaphor, adherence to OWL recommendations and key unique features, such as Collaborative Annotation using Annotea, Swoop acts as a useful and efficient Web Ontology development tool. We conclude with a list of future plans for Swoop, that should further increase its overall appeal and accessibility. 相似文献
In real world, the automatic detection of liver disease is a challenging problem among medical practitioners. The intent of this work is to propose an intelligent hybrid approach for the diagnosis of hepatitis disease. The diagnosis is performed with the combination of k‐means clustering and improved ensemble‐driven learning. To avoid clinical experience and to reduce the evaluation time, ensemble learning is deployed, which constructs a set of hypotheses by using multiple learners to solve a liver disease problem. The performance analysis of the proposed integrated hybrid system is compared in terms of accuracy, true positive rate, precision, f‐measure, kappa statistic, mean absolute error, and root mean squared error. Simulation results showed that the enhanced k‐means clustering and improved ensemble learning with enhanced adaptive boosting, bagged decision tree, and J48 decision tree‐based intelligent hybrid approach achieved better prediction outcomes than other existing individual and integrated methods. 相似文献
Microsystem Technologies - “Zero drift” behavior of an optical intraocular pressure sensor is studied using an analytical model based on the deflection of a circular membrane. Results... 相似文献
Neural Computing and Applications - This work presents an efficient hybridized approach for the classification of electrocardiogram (ECG) samples into crucial arrhythmia classes to detect heartbeat... 相似文献
Neural Computing and Applications - Induction machines have extensive demand in industries as they are used for large-scale production and, therefore, vulnerable to both electrical and mechanical... 相似文献
Dense (~97%) CaO-stabilized ZrO2 ceramic was stabilized with minimum (3 mol%) doping (reported to date) and processed via conventional sintering at a low temperature (~1200°C); compositional analysis via X-ray florescence confirmed the CaO doping accuracy. Phase-pure tetragonal structure (characterized via both X-ray diffraction and Raman spectroscopy) along with uniform nanograins (90 nm) of the ceramic ensured the evolution of no monoclinic phase even after vigorous low-temperature degradation experiments (both thermal and hydrothermal aging for 80-100 h). The sintered ceramic recorded a high hardness (~15 GPa); the indentation toughness value was also comparable to a 3 mol% yttria-stabilized zirconia system. The remarkable structure–property correlations in the 3 mol% CaO-stabilized ZrO2 ceramic suggests that the same may be worth examining for suitable future applications (e.g., in dental ceramics). 相似文献
Perovskite light-emitting diodes (PeLEDs) are advancing because of their superior external quantum efficiencies (EQEs) and color purity. Still, additional work is needed for blue PeLEDs to achieve the same benchmarks as the other visible colors. This study demonstrates an extremely efficient blue PeLED with a 488 nm peak emission, a maximum luminance of 8600 cd m−2, and a maximum EQE of 12.2% by incorporating the double-sided ethane-1,2-diammonium bromide (EDBr2) ligand salt along with the long-chain ligand methylphenylammonium chloride (MeCl). The EDBr2 successfully improves the interaction between 2D perovskite layers by reducing the weak van der Waals interaction and creating a Dion–Jacobson (DJ) structure. Whereas the pristine sample (without EDBr2) is inhibited by small stacking number (n) 2D phases with nonradiative recombination regions that diminish the PeLED performance, adding EDBr2 successfully enables better energy transfer from small n phases to larger n phases. As evidenced by photoluminescence (PL), scanning electron microscopy (SEM), and atomic force microscopy (AFM) characterization, EDBr2 improves the morphology by reduction of pinholes and passivation of defects, subsequently improving the efficiencies and operational lifetimes of quasi-2D blue PeLEDs. 相似文献
Detection of the selfish node in a delay tolerant network (DTN) can sharply reduce the loss incurred in a network. The algorithm's current pedigree mainly focuses on the rely on nodes, records, and delivery performance. The community structure and social aspects have been overlooked. Analysis of individual and social tie preferences results in an extensive detection time and increases communication overhead. In this article, a heterogeneous DTN topology with high-power stationary nodes and mobile nodes on Manhattan's accurate map is designed. With the increasing complexity of social ties and the diversified nature of topology structure, there need for a method that can effectively capture the essence within the speculated time. In this article, a novel deep autoencoder-based nonnegative matrix factorization (DANMF) is proposed for DTN topology. The topology of social ties projected onto low-dimensional space leads to effective cluster formation. DANMF automatically learns an appropriate nonlinear mapping function by utilizing the features of data. Also, the inherent structure of the deep autoencoder is nonlinear and has strong generalization. The membership matrices extracted from the DANMF are used to design the weighted cumulative social tie that eventually, along with the residual energy, is used to detect the network's selfish node. The testing of the designed model is carried out on the real dataset of MIT reality. The proficiency of the developed algorithm has been well tested and proved at every step. The methods employed for social tie extraction are NMF and DANMF. The methodology is rigorously experimented on various scenarios and has improved around 80% in the worst-case scenario of 40% nodes turning selfish. A comprehensive comparison is made with the other existing state-of-the-art methods which are also incentive-based approaches. The developed method has outperformed and has shown the supremacy of the current methods to capture the latent, hidden structure of the social tie.
From information security point of view, an enterprise is considered as a collection of assets and their interrelationships.
These interrelationships may be built into the enterprise information infrastructure, as in the case of connection of hardware
elements in network architecture, or in the installation of software or in the information assets. As a result, access to
one element may enable access to another if they are connected. An enterprise may specify conditions on the access of certain
assets in certain mode (read, write etc.) as policies. The interconnection of assets, along with specified policies, may lead
to managerial vulnerabilities in the enterprise information system. These vulnerabilities, if exploited by threats, may cause
disruption to the normal functioning of information systems. This paper presents a formal methodology for detection of managerial
vulnerabilities of, and threats to, enterprise information systems in linear time. 相似文献