Search results for "CLU"

showing 10 items of 14395 documents

Dexamethasone premedication suppresses vaccine-induced immune responses against cancer

2020

ABSTRACT Glucocorticosteroids (GCS) have an established role in oncology and are administered to cancer patients in routine clinical care and in drug development trials as co-medication. Given their strong immune-suppressive activity, GCS may interfere with immune-oncology drugs. We are developing a therapeutic cancer vaccine, which is based on a liposomal formulation of tumor-antigen encoding RNA (RNA-LPX) and induces a strong T-cell response both in mice as well as in humans. In this study, we investigated in vivo in mice and in human PBMCs the effect of the commonly used long-acting GCS Dexamethasone (Dexa) on the efficacy of this vaccine format, with a particular focus on antigen-specif…

t-cell primingPremedicationmedicine.medical_treatmentImmunologyPriming (immunology)dexamethasoneglucocorticosteroidsProinflammatory cytokineMice03 medical and health sciences0302 clinical medicineImmune systemAntigenCancer immunotherapyNeoplasmsAnimalsHumansImmunology and AllergyMedicineRC254-282Original ResearchMice Inbred BALB Ccancer immunotherapybusiness.industryrna vaccineImmunityNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC581-607Mice Inbred C57BLCytokineOncology030220 oncology & carcinogenesisImmunologyt-cell vaccineFemaleCancer vaccineImmunologic diseases. AllergybusinessT-cell vaccineResearch Article030215 immunologyOncoImmunology
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Adaptive framework for network traffic classification using dimensionality reduction and clustering

2012

Information security has become a very important topic especially during the last years. Web services are becoming more complex and dynamic. This offers new possibilities for attackers to exploit vulnerabilities by inputting malicious queries or code. However, these attack attempts are often recorded in server logs. Analyzing these logs could be a way to detect intrusions either periodically or in real time. We propose a framework that preprocesses and analyzes these log files. HTTP queries are transformed to numerical matrices using n-gram analysis. The dimensionality of these matrices is reduced using principal component analysis and diffusion map methodology. Abnormal log lines can then …

ta113Computer scienceNetwork securitybusiness.industryDimensionality reductionintrusion detectionk-meansdiffusion mapServer logcomputer.software_genreanomaly detectionTraffic classificationkoneoppiminenWeb log analysis softwareAnomaly detectionData miningWeb servicetiedonlouhintaCluster analysisbusinesscomputern-grams
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A novel heuristic memetic clustering algorithm

2013

In this paper we introduce a novel clustering algorithm based on the Memetic Algorithm meta-heuristic wherein clusters are iteratively evolved using a novel single operator employing a combination of heuristics. Several heuristics are described and employed for the three types of selections used in the operator. The algorithm was exhaustively tested on three benchmark problems and compared to a classical clustering algorithm (k-Medoids) using the same performance metrics. The results show that our clustering algorithm consistently provides better clustering solutions with less computational effort.

ta113Determining the number of clusters in a data setBiclusteringClustering high-dimensional dataDBSCANComputingMethodologies_PATTERNRECOGNITIONTheoretical computer scienceCURE data clustering algorithmCorrelation clusteringCanopy clustering algorithmCluster analysisAlgorithmMathematics2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP)
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Gear classification and fault detection using a diffusion map framework

2015

This article proposes a system health monitoring approach that detects abnormal behavior of machines. Diffusion map is used to reduce the dimensionality of training data, which facilitates the classification of newly arriving measurements. The new measurements are handled with Nyström extension. The method is trained and tested with real gear monitoring data from several windmill parks. A machine health index is proposed, showing that data recordings can be classified as working or failing using dimensionality reduction and warning levels in the low dimensional space. The proposed approach can be used with any system that produces high-dimensional measurement data. peerReviewed

ta113Diffusion (acoustics)Training setta214Computer scienceDimensionality reductiondiffusion mapExtension (predicate logic)computer.software_genreFault detection and isolationfault detectionsystem health monitoringArtificial IntelligenceSignal ProcessingComputer Vision and Pattern RecognitionData miningCluster analysiscomputerSoftwareCurse of dimensionalityclustering
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Twister Tries

2015

Many commonly used data-mining techniques utilized across research fields perform poorly when used for large data sets. Sequential agglomerative hierarchical non-overlapping clustering is one technique for which the algorithms’ scaling properties prohibit clustering of a large amount of items. Besides the unfavorable time complexity of O(n 2 ), these algorithms have a space complexity of O(n 2 ), which can be reduced to O(n) if the time complexity is allowed to rise to O(n 2 log2 n). In this paper, we propose the use of locality-sensitive hashing combined with a novel data structure called twister tries to provide an approximate clustering for average linkage. Our approach requires only lin…

ta113Hierarchical agglomerative clusteringta112Fuzzy clusteringBrown clusteringComputer scienceSingle-linkage clusteringcomputer.software_genreHierarchical clusteringLocality-sensitive hashingData setCURE data clustering algorithmlocality-sensitive hashingaverage linkageData miningHierarchical clustering of networkslinear complexityCluster analysishierarchical clusteringAlgorithmcomputerTime complexityProceedings of the 2015 ACM SIGMOD International Conference on Management of Data
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A Hybrid Multigroup Coclustering Recommendation Framework Based on Information Fusion

2015

Collaborative Filtering (CF) is one of the most successful algorithms in recommender systems. However, it suffers from data sparsity and scalability problems. Although many clustering techniques have been incorporated to alleviate these two problems, most of them fail to achieve further significant improvement in recommendation accuracy. First of all, most of them assume each user or item belongs to a single cluster. Since usually users can hold multiple interests and items may belong to multiple categories, it is more reasonable to assume that users and items can join multiple clusters (groups), where each cluster is a subset of like-minded users and items they prefer. Furthermore, most of…

ta113Information retrievalComputer sciencebusiness.industrydata miningRecommender systemcomputer.software_genreTheoretical Computer ScienceInformation fusionKnowledge baseArtificial IntelligenceCollaborative FilteringScalabilityCluster (physics)Collaborative filteringLearning to rankData miningrecommender systemsCluster analysisbusinesscomputercluster analysisACM Transactions on Intelligent Systems and Technology
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Understanding Social OER Environments—A Quantitative Study on Factors Influencing the Motivation to Share and Collaborate

2014

Social software environments are increasingly used for open education: teachers and learners share and collaborate in these environments. While there are various possibilities for the inclusion of such social functionalities for OER, many organizational, individual and technological challenges can hinder the motivation of teachers to share and collaborate in these environments. Current research cannot explain what barriers teachers face in social OER environments and how those challenges influence their motivation to engage in such environments. An exploratory factor analysis was used in the context of schools and higher education institutions to investigate the possible barriers to engagin…

ta113Knowledge managementHigher educationComputer sciencebusiness.industrySocial softwareGeneral EngineeringContext (language use)computer.software_genreExploratory factor analysisComputer Science ApplicationsEducationKnowledge sharingOpen educationta516Social mediabusinessInclusion (education)computerIEEE Transactions on Learning Technologies
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Understanding differences among coding club students

2014

Scholars and instructors have been carrying out a multitude of actions to increase students' interest in computer science during the past years. Still, there is a need for knowledge on how these attempts develop student interest. In this qualitative study, we construct illustrative categories out of students who have attended our K-12 coding club and game programming summer course activities. We found four categories: Inactivity, Lack of self-direction, Experimenting, and Professionalism. We also briefly project this abstraction onto a four-phase model of interest development.

ta113OutreachGame programmingComputer scienceMultitudePedagogyComputingMilieux_COMPUTERSANDEDUCATIONMathematics educationClubCoding (social sciences)Qualitative researchProceedings of the 2014 conference on Innovation & technology in computer science education - ITiCSE '14
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Cluster-Based RF Fingerprint Positioning Using LTE and WLAN Outdoor Signals

2015

In this paper we evaluate user-equipment (UE) positioning performance of three cluster-based RF fingerprinting methods using LTE and WLAN signals. Real-life LTE and WLAN data were collected for the evaluation purpose using consumer cellular-mobile handset utilizing ‘Nemo Handy’ drive test software tool. Test results of cluster-based methods were compared to the conventional grid-based RF fingerprinting. The cluster-based methods do not require grid-cell layout and training signature formation as compared to the gridbased method. They utilize LTE cell-ID searching technique to reduce the search space for clustering operation. Thus UE position estimation is done in short time with less comput…

ta113PercentileK-nearest neighborComputer sciencebusiness.industrycell-IDFingerprint (computing)Real-time computingFingerprint recognitionGridHandsetlaw.inventionminimization of drive testsEuclidean distanceLTElawEmbedded systemgrid-based RF fingerprintingRadio frequencyCluster analysisbusinessfuzzy C-meanshierarchical clustering
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BioImageXD: an open, general-purpose and high-throughput image-processing platform

2012

BioImageXD puts open-source computer science tools for three-dimensional visualization and analysis into the hands of all researchers, through a user-friendly graphical interface tuned to the needs of biologists. BioImageXD has no restrictive licenses or undisclosed algorithms and enables publication of precise, reproducible and modifiable workflows. It allows simple construction of processing pipelines and should enable biologists to perform challenging analyses of complex processes. We demonstrate its performance in a study of integrin clustering in response to selected inhibitors.

ta113SIMPLE (military communications protocol)Computer sciencebusiness.industryta1182Computational BiologyImage processingCell BiologyBioinformaticsBiochemistryVisualizationHigh-Throughput Screening AssaysUser-Computer InterfaceSoftwareWorkflowImaging Three-DimensionalHuman–computer interactionbusinessCluster analysisMolecular BiologyThroughput (business)AlgorithmsSoftwareBiotechnologyGraphical user interfaceNATURE METHODS
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