Showing 1141–1152 of 1333 results
Self-Deployment of Mobile Sensors to Achieve Target Coverage in the Presence of Obstacles Abstract? Target coverage is one of the major requirements in wireless sensor network applications, the purpose of which is to monitor a set of known targets in the region of interest. In this paper, we propose a localized self-deployment scheme, named as…
Self-Deployment of Randomly Scattered Mobile Sensors to Achieve Barrier Coverage Abstract? Constructing sensor barrier is a critical issue in wireless sensor networks for military and homeland security applications, which aims to detect intruders crossing into a protected area. In this letter, we propose two distributed, localized deployment schemes for self-adjustment of randomly deployed mobile sensor…
Semantic-Aware Blocking for Entity Resolution Abstract? a semantic-aware blocking framework for entity resolution (ER). The proposed framework is built using locality-sensitive hashing (LSH) techniques, which efficiently unifies both textual and semantic features into an ER blocking process. In order to understand how similarity metrics may affect the effectiveness of ER blocking, we study the robustness…
Semantic-Aware Blocking for Entity Resolution Abstract? A semantic-aware blocking framework for entity resolution (ER). The proposed framework is built using locality-sensitive hashing (LSH) techniques, which efficiently unifies both textual and semantic features into an ER blocking process. In order to understand how similarity metrics may affect the effectiveness of ER blocking, we study the robustness…
Semi-automatic detection and segmentation algorithm of saccular aneurysms in 2D cerebral DSA images Abstract?Abstract To detect and segment cerebral saccular aneurysms (CSAs) in 2D Digital Subtraction Angiography (DSA) images.Patients and methods: Ten patients underwent Intra-arterial DSA procedures. Patients were injected with Iodine-containing radiopaque material. A scheme for semi-automatic detection and segmentation of intracranial aneurysms is…
Semisupervised Hyperspectral Image Classification Using Small Sample Sizes Abstract-Hyperspectral image classification is a challenging task when only a small number of labeled samples are available due to the difficult, expensive, and time-consuming ground campaigns required to collect the ground-truth information. It is also known that the classification performance is highly dependent on the size of…
Sensitivity Analysis on Locations of Energy Storage in Power Systems with Wind Integration Abstract?Abstract The penetration of renewable energy sources, particularly wind energy, into power systems has been rapidly increasing in recent years. However, the integration of wind power has posed many challenges for power system operation.For instance, this type of energy source is relatively…
SentiHealth-Cancer: A sentiment analysis tool to help detecting moodof patients in online social networks Abstract?Abstract Cancer is a critical disease that affects millions of people and families around the world. In2012 about 14.1 million new cases of cancer occurred globally. Because of many reasons like the severityof some cases, the side effects of some treatments…
Sentiment Analyis of Indian Movie Review with Various Feature Selection Techniques Abstract-In the first place, Sentiment analysis and opinion mining is an emerging area of research for analysing web data and capturing the sentiment of the users.In addition,research presents sentiments analysis on Indian movie review corpus using machine learning classifier. In contrast, Bayesian Classifier has…
Sentiment Analyis of Indian Movie Review with Various Feature Selection Techniques AbstractIn the first place, Data Mining Sentiment analysis and opinion mining is an emerging area of research for analysing web data and capturing the sentiment of the users. In addition, research presents sentiments analysis on Indian movie review corpus using machine learning classifier although…
Set Matching Measures for External Cluster Validity Abstract? Comparing two clustering results of a data set is a challenging task in cluster analysis. Many external validity measures have been proposed in the literature. A good measure should be invariant to the changes of data size, cluster size and number of clusters. We give an overview…
Set Matching Measures for External Cluster Validity Abstract? Comparing two clustering results of a data set is a challenging task in cluster analysis. Many external validity measures have been proposed in the literature. A good measure should be invariant to the changes of data size, cluster size and number of clusters. We give an overview…
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