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  • 1
    In: Media in the Ubiquitous Era, Chapter 4, p.66-93
    Description: With the advances in ubiquitous computing, there is an increasing focus on personalization of user information especially in web-based applications and services. Currently those personalized user profiles are scattered, mostly stored for each individual service. Therefore, this prohibits the usage of those profiles in different environments such as other web-based services, shopping in local stores or sharing interests among people. The so-called Portable Personality focuses on the management and distribution of personalized profiles (in form of a digital personality representing the real-world user) through mobile devices. These portability aspects merge with the idea of cross-system personalization using a single generic user profile. We will briefly introduce some aspects related to profile representation and management with focus on attempts towards such a generic representation. The main discussion will be concentrated around profile portability and its effects on personalization especially towards cross-system support. We include different portable profile scenarios and their personalization methodologies. Furthermore, current personalization algorithms are considered with possible associations towards the presented portable scenarios. At the end, we reflect on existing challenges of current approaches in the field of portable personalization and try to provide some recommendations.
    ISBN: 978-1-60960-774-6
    Source: Books (IGI Global)
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  • 2
    Language: English
    In: Cancer Research, 08/01/2015, Vol.75(15 Supplement), pp.241-241
    ISSN: 0008-5472
    E-ISSN: 1538-7445
    Source: CrossRef
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  • 3
    Language: English
    In: PLoS ONE, 01 January 2013, Vol.8(9), p.e73413
    Description: Recent development of high-throughput, multiplexing technology has initiated projects that systematically investigate interactions between two types of components in biological networks, for instance transcription factors and promoter sequences,...
    Keywords: Sciences (General)
    E-ISSN: 1932-6203
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  • 4
    In: Stroke, 2017
    Description: BACKGROUND AND PURPOSE—: Circulating microRNAs (miRNAs) are emerging biomarkers for stroke because of their high stability in the bloodstream and association with pathophysiologic conditions. However, the circulating whole-genome miRNAs (miRNome) has not been characterized comprehensively in the acute phase of stroke. METHODS—: We profiled the circulating miRNome in mouse models of acute ischemic and hemorrhagic stroke by next-generation sequencing. Stroke models were compared with sham-operated and naive mice to identify deregulated circulating miRNAs. Top-ranked miRNAs were validated and further characterized by quantitative reverse transcription polymerase chain reaction. RESULTS—: We discovered 24 circulating miRNAs with an altered abundance in the circulation 3 hours after ischemia, whereas the circulating miRNome was not altered after intracerebral hemorrhage compared with sham-operated mice. Among the upregulated miRNAs in ischemia, the top-listed miR-1264/1298/448 cluster was strongly dependent on reperfusion in different ischemia models. A time course experiment revealed that the miR-1264/1298/448 cluster peaked in the circulation around 3 hours after reperfusion and gradually decreased thereafter. CONCLUSIONS—: Alteration of the miRNome in the circulation is associated with cerebral ischemia/reperfusion, but not hemorrhage, suggesting a potential to serve as biomarkers for reperfusion in the acute phase. The pathophysiological role of reperfusion-inducible miR-1264/1298/448 cluster, which is located on chromosome X within the introns of the serotonin receptor HTR2C, requires further investigation.
    Keywords: Medicine;
    ISBN: 0003955514000
    ISSN: 0039-2499
    E-ISSN: 15244628
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  • 5
    Language: English
    In: ISPRS Journal of Photogrammetry and Remote Sensing, April 2014, Vol.90, pp.10-22
    Description: Fully and partially polarimetric SAR data in combination with textural features have been used extensively for terrain classification. However, there is another type of visual feature that has so far been neglected from polarimetric SAR classification: Color. It is a common practice to visualize polarimetric SAR data by color coding methods and thus it is possible to extract powerful color features from such pseudo color images so as to gather additional crucial information for an improved terrain classification. In this paper, we investigate the application of several individual visual features over different pseudo color generated images along with the traditional SAR and texture features for a novel supervised classification application of dual- and single-polarized SAR data. We then draw the focus on evaluating the effects of the applied pseudo coloring methods on the classification performance. An extensive set of experiments show that individual visual features or their combination with traditional SAR features introduce a new level of discrimination and provide noteworthy improvement of classification accuracies within the application of land use and land cover classification for dual- and single-pol image data.
    Keywords: Synthetic Aperture Radar ; Classification ; Image Analysis ; Visual Features ; Color ; Texture ; Engineering ; Geography
    ISSN: 0924-2716
    E-ISSN: 1872-8235
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  • 6
    Language: English
    In: IEEE Transactions on Geoscience and Remote Sensing, April 2014, Vol.52(4), pp.2197-2216
    Description: Polarimetric synthetic aperture radar (PolSAR) data are used extensively for terrain classification applying SAR features from various target decompositions and certain textural features. However, one source of information has so far been neglected from PolSAR classification: Color. It is a common practice to visualize PolSAR data by color coding methods and thus, it is possible to extract powerful color features from such pseudocolor images so as to provide additional data for a superior terrain classification. In this paper, we first review previous attempts for PolSAR classifications using various feature combinations and then we introduce and perform in-depth investigation of the application of color features over the Pauli color-coded images besides SAR and texture features. We run an extensive set of comparative evaluations using 24 different feature set combinations over three images of the Flevoland- and the San Francisco Bay region from the RADARSAT-2 and the AIRSAR systems operating in C- and L-bands, respectively. We then consider support vector machines and random forests classifier topologies to test and evaluate the role of color features over the classification performance. The classification results show that the additional color features introduce a new level of discrimination and provide noteworthy improvement in classification performance (compared with the traditionally employed PolSAR and texture features) within the application of land use and land cover classification.
    Keywords: Classification ; Color Features ; Evaluation ; Feature Extraction ; Polarimetric Radar ; Synthetic Aperture Radar (SAR) ; Engineering ; Physics
    ISSN: 0196-2892
    E-ISSN: 1558-0644
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  • 7
    Language: English
    In: Neuropsychiatry, August, 2011, Vol.1(4), p.349(12)
    Description: SUMMARY Schneiderian first rank symptoms are still associated with the diagnosis of schizophrenia. Auditory hallucinations in the 'third person perspective' in combination with impaired functioning are sufficient for the diagnosis according to Diagnostic and Statistical Manual of Mental Disorders-IV-text revision and International Classification of Diseases-10. However, identical symptoms can be observed in severe dissociative disorders. This article reflects the history of Schneiderian first rank symptoms, shared and nonshared symptoms of schizophrenia and dissociative disorders and the hypothetical role of traumatic events in the origin of these symptoms. Based on the nonshared psychopathological symptoms such as negative symptoms, formal thought disorder and disorganization, suggestions for the differential diagnosis of both disorders and implications for therapy are outlined.
    Keywords: Schizophrenia
    ISSN: 1758-2008
    E-ISSN: 17582016
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  • 8
    Language: English
    In: Molecular and Cellular Biology, 2012, Vol. 32(3), p.633
    Description: MicroRNA-200c (miR-200c) has been shown to suppress epithelial-mesenchymal transition (EMT), which is attributed mainly to targeting of ZEB1/ZEB2, repressors of the cell-cell contact protein E-cadherin. Here we demonstrated that modulation of miR-200c in breast cancer cells regulates cell migration, cell elongation, and transforming growth factor β (TGF-β)-induced stress fiber formation by impacting the reorganization of cytoskeleton that is independent of the ZEB/E-cadherin axis. We identified FHOD1 and PPM1F, direct regulators of the actin cytoskeleton, as novel targets of miR-200c. Remarkably, expression levels of FHOD1 and PPM1F were inversely correlated with the level of miR-200c in breast cancer cell lines, breast cancer patient samples, and 58 cancer cell lines of various origins. Furthermore, individual knockdown/overexpression of these target genes phenocopied the effects of miR-200c overexpression/inhibition on cell elongation, stress fiber formation, migration, and invasion. Mechanistically, targeting of FHOD1 by miR-200c resulted in decreased expression and transcriptional activity of serum response factor (SRF), mediated by interference with the translocation of the SRF coactivator mycocardin-related transcription factor A (MRTF-A). This finally led to downregulation of the expression and phosphorylation of the SRF target myosin light chain 2 (MLC2) gene, required for stress fiber formation and contractility. Thus, miR-200c impacts on metastasis by regulating several EMT-related processes, including a novel mechanism involving the direct targeting of actin-regulatory proteins.
    Keywords: Breast Neoplasms -- Pathology ; Fetal Proteins -- Metabolism ; Micrornas -- Metabolism ; Nuclear Proteins -- Metabolism ; Phosphoprotein Phosphatases -- Metabolism;
    ISSN: 1098-5549
    ISSN: 10985549
    ISSN: 02707306
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  • 9
    Language: English
    In: IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), August 2012, Vol.42(4), pp.1169-1186
    Description: Terrain classification over polarimetric synthetic aperture radar (SAR) images has been an active research field where several features and classifiers have been proposed up to date. However, some key questions, e.g., 1) how to select certain features so as to achieve highest discrimination over certain classes?, 2) how to combine them in the most effective way?, 3) which distance metric to apply?, 4) how to find the optimal classifier configuration for the classification problem in hand?, 5) how to scale/adapt the classifier if large number of classes/features are present?, and finally, 6) how to train the classifier efficiently to maximize the classification accuracy?, still remain unanswered. In this paper, we propose a collective network of (evolutionary) binary classifier (CNBC) framework to address all these problems and to achieve high classification performance. The CNBC framework adapts a "Divide and Conquer" type approach by allocating several NBCs to discriminate each class and performs evolutionary search to find the optimal BC in each NBC. In such an (incremental) evolution session, the CNBC body can further dynamically adapt itself with each new incoming class/feature set without a full-scale retraining or reconfiguration. Both visual and numerical performance evaluations of the proposed framework over two benchmark SAR images demonstrate its superiority and a significant performance gap against several major classifiers in this field.
    Keywords: Neurons ; Scattering ; Covariance Matrix ; Training ; Matrix Decomposition ; Indexes ; Measurement ; Evolutionary Classifiers ; Multidimensional Particle Swarm Optimization (MD-Pso) ; Polarimetric Synthetic Aperture Radar (SAR) ; Sciences (General) ; Engineering
    ISSN: 1083-4419
    E-ISSN: 1941-0492
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  • 10
    Language: English
    In: Remote Sensing, 01 May 2014, Vol.6(6), pp.4801-4830
    Description: In recent years, the interest in semi-supervised learning has increased, combining supervised and unsupervised learning approaches. This is especially valid for classification applications in remote sensing, while the data acquisition rate in current systems has become fairly large considering...
    Keywords: Semi-Supervised ; Machine Learning ; Ensemble ; SAR ; Superpixel ; Geography
    E-ISSN: 2072-4292
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