The main knowledge management challenges are to capture, store and reuse contextual knowledge generated during interactions that occur daily in an organization. In this paper, we propose an activity context-aware arch...
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Determining the factors that contribute to the healthcare disparity in United States is a substantial problem that healthcare professionals have confronted for decades. In this study, our objective is to build precise...
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Cluster analysis is used in several research areas to classify data sets in groups by their similar characteristics. Metaheuristic-based techniques, such as Genetic Algorithms (GAs) and Ant Colony Optimization (ACO), ...
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Cluster analysis is used in several research areas to classify data sets in groups by their similar characteristics. Metaheuristic-based techniques, such as Genetic Algorithms (GAs) and Ant Colony Optimization (ACO), have been applied in order to increase the clustering algorithm performance. GA and ACO-based clustering algorithms are capable of efficiently and automatically forming natural groups from a pre-defined number of clusters. This paper presents a GA and an ACO algorithm to the clustering problem. Both algorithms were refined using local search in order to improve the clustering accuracy. The results are compared on numeric UCI databases.
The paper developed a block-wise approach for ICA algorithms which can improve the computational efficiency of ICA without the degradation of performance for the separation of biomedical signals. Source signals includ...
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The decisions made by the operation commander in emergency situations should be made quickly to save lives. To avoid late or bad decisions, the commander must construct a situational awareness. The irregular arrival f...
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The decisions made by the operation commander in emergency situations should be made quickly to save lives. To avoid late or bad decisions, the commander must construct a situational awareness. The irregular arrival flow of information, uncertainty, information overload and lack of persistence are the main factors that hinder this task. To minimize these effects we propose an architecture composed of mobile devices and a decision support system to be used in the command post. The main point in the system design is the cognitive overload. Therefore, heuristics about the usage of the information by experienced commanders were elicited and implemented.
Our work concerns the elucidation of the cancer (epi)genome, transcriptome and proteome to better understand the complex interplay between a cancer cell's molecular state and its response to anti-cancer therapy. T...
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Our work concerns the elucidation of the cancer (epi)genome, transcriptome and proteome to better understand the complex interplay between a cancer cell's molecular state and its response to anti-cancer therapy. To study the problem, we have previously focused on data warehousing technologies and statistical data integration. In this paper, we present recent work on extending our analytical capabilities using Semantic Web technology. A key new component presented here is a SPARQL endpoint to our existing data warehouse. This endpoint allows the merging of observed quantitative data with existing data from semantic knowledge sources such as Gene Ontology (GO). We show how such variegated quantitative and functional data can be integrated and accessed in a universal manner using Semantic Web tools. We also demonstrate how Description Logic (DL) reasoning can be used to infer previously unstated conclusions from existing knowledge bases. As proof of concept, we illustrate the ability of our setup to answer complex queries on resistance of cancer cells to Decitabine, a demethylating agent.
An important problem in Wireless Sensor Networks (WSN) is the occurrence of failures that lead to the disconnection of parts of the network, compromising the final results achieved by the WSN operation. A way to overc...
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An important problem in Wireless Sensor Networks (WSN) is the occurrence of failures that lead to the disconnection of parts of the network, compromising the final results achieved by the WSN operation. A way to overcome such problem is to provide a reliable connection to support the connectivity via other types of nodes that communicate with the sensor nodes. This paper proposes the usage of a network composed by Unmanned Aerial Vehicles (UAVs) as a relay network to guarantee the delivery of data produced by WSN nodes on the ground to the users. Results from simulations of the proposed technique are provided and discussed.
The paper developed a block-wise approach for ICA algorithms which can improve the computational efficiency of ICA without the degradation of performance for the separation of biomedical signals. Source signals includ...
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The paper developed a block-wise approach for ICA algorithms which can improve the computational efficiency of ICA without the degradation of performance for the separation of biomedical signals. Source signals including electrocardiogram (ECG), electromyogram (EMG) and 60-Hz sinusoid are linearly mixed for experimental tests. The mean-square errors (MSE) between the original sources and the separated signals are calculated for the evaluation of separation performance. These results demonstrated that the proposed block-wise approach can achieve the desired separation performance of signals in a more efficient way.
The main knowledge management challenges are to capture, store and reuse contextual knowledge generated during interactions that occur daily in an organization. In this paper, we propose an activity context-aware arch...
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The main knowledge management challenges are to capture, store and reuse contextual knowledge generated during interactions that occur daily in an organization. In this paper, we propose an activity context-aware architecture to support knowledge management in working processes. The required features for this architecture are processing, reasoning and sharing contextual knowledge involving information about activities performed. We also present results from evaluation of our proposal — A-CoBrA — for a specific domain.
Active modeling is required in learning settings to cope with the dynamic evolution of the knowledge, since learners competences evolves over time as they participate in the course activities. Moreover, one of the mai...
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ISBN:
(纸本)9781424444823
Active modeling is required in learning settings to cope with the dynamic evolution of the knowledge, since learners competences evolves over time as they participate in the course activities. Moreover, one of the main issues in a competence based eLearning process is to deliver personalized instructional designs adjusted to both 1) intrinsic characteristics of users (i.e. learning styles) and 2) the desired and achieved competences in the learning process (i.e. specific and generic competences). This delivery includes the adaptation of the content and the activities in a learning scenario based on a dynamic user model that evolves according to user interactions. In this paper, an approach to support Conditional Plans Generation (IMS Learning Designs) in the context of a virtual learning environment is presented The process is supported by a pervasive usage of standards and specifications (IMS family of specifications) in conjunction with an integral user modeling.
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