03072nam 2200517 450 991046716160332120200520144314.03-11-054718-X3-11-054906-910.1515/9783110549065(CKB)4340000000208926(MiAaPQ)EBC5106147(DE-B1597)481892(OCoLC)1011440346(DE-B1597)9783110549065(Au-PeEL)EBL5106147(CaPaEBR)ebr11462166(OCoLC)1009243556(EXLCZ)99434000000020892620171118h20172017 uy 0gerurcnu||||||||rdacontentrdamediardacarrierLuthers bleiche Erben Kulturgeschichte der evangelischen Geistlichkeit des 17. Jahrhunderts /Wolfgang E. J. WeberBerlin, [Germany] ;Boston, [Massachusetts] :De Gruyter Oldenbourg,2017.©20171 online resource (234 pages) illustrations3-11-054681-7 Includes bibliographical references and index.Frontmatter -- Inhalt -- Vorwort -- Einführung -- 1. Aufbruch und Ernüchterung: Die Anfänge im 16. Jahrhundert -- 2. Vocatio und Eigeninteresse: Die Wege in die Pfarrstelle -- 3. Professionelle Routine und heiliger Eifer: das Spektrum der Pastorentätigkeit -- 4. Vergebliche Mühen: Der Kampf gegen Unzucht, Tanz und Eigennutz -- 5. Das Verstummen der Wachhunde: Vom Strafamt zur Herrschaftszuarbeit -- 6. Die Kosten: Selbstdisziplinierung, Melancholie und Devianz -- 7. Nicht nur um Gotteslohn: Das Einkommen -- 8. (Selbst‐)Kritik und Krise -- Bilanz -- Anmerkungen -- Anhang -- Personenregister For the first time, this monograph examines Luther’s heirs, the pastors of the next generation. They were responsible for the survival of the Reformation, yet they always remained in the shadows of their great predecessor. How did they obtain their ministries? How did they live? How did they manage to rescue the Lutheran church enterprise despite massive internal quarreling in an epoch marked by perpetual war and crisis? Luthers Erben der dritten Generation, die Pastoren des 17. Jahrhunderts, sicherten die Reformation in einer Epoche des Krieges, der Krisen und Umbrüche. Dennoch stehen sie bis heute im Schatten ihres großen Vorgängers. Wie sahen sie sich selbst, was befähigte sie zu ihrer Leistung, und welche Anpassungen an ihre Welt nahmen sie vor? Erst die Kenntnis dieser ebenso faszinierenden wie ernüchternden Vorgänge macht die Entwicklung des Luthertums bis zur Gegenwart verständlich. ReformationGermany17th centuryElectronic books.Reformation274.306Weber Wolfgang E. J.1053902MiAaPQMiAaPQMiAaPQBOOK9910467161603321Luthers bleiche Erben2486082UNINA07589nam 2200601 450 99646551050331620210313005213.03-540-73871-110.1007/978-3-540-73871-8(CKB)1000000000490209(SSID)ssj0000315718(PQKBManifestationID)11212740(PQKBTitleCode)TC0000315718(PQKBWorkID)10255226(PQKB)10502823(DE-He213)978-3-540-73871-8(MiAaPQ)EBC3063397(MiAaPQ)EBC6413195(PPN)123164036(EXLCZ)99100000000049020920210313d2007 uy 0engurnn#008mamaatxtccrAdvanced data mining and applications Third international conference, ADMA 2007, Harbin, China, August 6-8, 2007 : proceedings /Reda Alhajj [and four others]1st ed. 2007.Berlin, Germany ;New York, New York :Springer,[2007]℗20071 online resource (XVI, 636 p. 201 illus.)Lecture Notes in Artificial Intelligence ;4632Bibliographic Level Mode of Issuance: Monograph3-540-73870-3 Includes bibliographical references and index.Invited Talk -- Mining Ambiguous Data with Multi-instance Multi-label Representation -- Regular Papers -- DELAY: A Lazy Approach for Mining Frequent Patterns over High Speed Data Streams -- Exploring Content and Linkage Structures for Searching Relevant Web Pages -- CLBCRA-Approach for Combination of Content-Based and Link-Based Ranking in Web Search -- Rough Sets in Hybrid Soft Computing Systems -- Discovering Novel Multistage Attack Strategies -- Privacy Preserving DBSCAN Algorithm for Clustering -- A New Multi-level Algorithm Based on Particle Swarm Optimization for Bisecting Graph -- A Supervised Subspace Learning Algorithm: Supervised Neighborhood Preserving Embedding -- A k-Anonymity Clustering Method for Effective Data Privacy Preservation -- LSSVM with Fuzzy Pre-processing Model Based Aero Engine Data Mining Technology -- A Coding Hierarchy Computing Based Clustering Algorithm -- Mining Both Positive and Negative Association Rules from Frequent and Infrequent Itemsets -- Survey of Improving Naive Bayes for Classification -- Privacy Preserving BIRCH Algorithm for Clustering over Arbitrarily Partitioned Databases -- Unsupervised Outlier Detection in Sensor Networks Using Aggregation Tree -- Separator: Sifting Hierarchical Heavy Hitters Accurately from Data Streams -- Spatial Fuzzy Clustering Using Varying Coefficients -- Collaborative Target Classification for Image Recognition in Wireless Sensor Networks -- Dimensionality Reduction for Mass Spectrometry Data -- The Study of Dynamic Aggregation of Relational Attributes on Relational Data Mining -- Learning Optimal Kernel from Distance Metric in Twin Kernel Embedding for Dimensionality Reduction and Visualization of Fingerprints -- Efficiently Monitoring Nearest Neighbors to a Moving Object -- A Novel Text Classification Approach Based on Enhanced Association Rule -- Applications of the Moving Average of n th -Order Difference Algorithm for Time Series Prediction -- Inference of Gene Regulatory Network by Bayesian Network Using Metropolis-Hastings Algorithm -- A Consensus Recommender for Web Users -- Constructing Classification Rules Based on SVR and Its Derivative Characteristics -- Hiding Sensitive Associative Classification Rule by Data Reduction -- AOG-ags Algorithms and Applications -- A Framework for Titled Document Categorization with Modified Multinomial Naivebayes Classifier -- Prediction of Protein Subcellular Locations by Combining K-Local Hyperplane Distance Nearest Neighbor -- A Similarity Retrieval Method in Brain Image Sequence Database -- A Criterion for Learning the Data-Dependent Kernel for Classification -- Topic Extraction with AGAPE -- Clustering Massive Text Data Streams by Semantic Smoothing Model -- GraSeq: A Novel Approximate Mining Approach of Sequential Patterns over Data Stream -- A Novel Greedy Bayesian Network Structure Learning Algorithm for Limited Data -- Optimum Neural Network Construction Via Linear Programming Minimum Sphere Set Covering -- How Investigative Data Mining Can Help Intelligence Agencies to Discover Dependence of Nodes in Terrorist Networks -- Prediction of Enzyme Class by Using Reactive Motifs Generated from Binding and Catalytic Sites -- Bayesian Network Structure Ensemble Learning -- Fusion of Palmprint and Iris for Personal Authentication -- Enhanced Graph Based Genealogical Record Linkage -- A Fuzzy Comprehensive Clustering Method -- Short Papers -- CACS: A Novel Classification Algorithm Based on Concept Similarity -- Data Mining in Tourism Demand Analysis: A Retrospective Analysis -- Chinese Patent Mining Based on Sememe Statistics and Key-Phrase Extraction -- Classification of Business Travelers Using SVMs Combined with Kernel Principal Component Analysis -- Research on the Traffic Matrix Based on Sampling Model -- A Causal Analysis for the Expenditure Data of Business Travelers -- A Visual and Interactive Data Exploration Method for Large Data Sets and Clustering -- Explorative Data Mining on Stock Data – Experimental Results and Findings -- Graph Structural Mining in Terrorist Networks -- Characterizing Pseudobase and Predicting RNA Secondary Structure with Simple H-Type Pseudoknots Based on Dynamic Programming -- Locally Discriminant Projection with Kernels for Feature Extraction -- A GA-Based Feature Subset Selection and Parameter Optimization of Support Vector Machine for Content – Based Image Retrieval -- E-Stream: Evolution-Based Technique for Stream Clustering -- H-BayesClust: A New Hierarchical Clustering Based on Bayesian Networks -- An Improved AdaBoost Algorithm Based on Adaptive Weight Adjusting.The Third International Conference on Advanced Data Mining and Applications (ADMA) organized in Harbin, China continued the tradition already established by the first two ADMA conferences in Wuhan in 2005 and Xi’an in 2006. One major goal of ADMA is to create a respectable identity in the data mining research com- nity. This feat has been partially achieved in a very short time despite the young age of the conference, thanks to the rigorous review process insisted upon, the outstanding list of internationally renowned keynote speakers and the excellent program each year. The impact of a conference is measured by the citations the conference papers receive. Some have used this measure to rank conferences. For example, the independent source cs-conference-ranking.org ranks ADMA (0.65) higher than PAKDD (0.64) and PKDD (0.62) as of June 2007, which are well established conferences in data mining. While the ranking itself is questionable because the exact procedure is not disclosed, it is nevertheless an encouraging indicator of recognition for a very young conference such as ADMA.Lecture Notes in Artificial Intelligence ;4632Computer scienceArtificial intelligenceData miningComputer science.Artificial intelligence.Data mining.005.74Alhajj RedaMiAaPQMiAaPQMiAaPQBOOK996465510503316Advanced Data Mining and Applications771989UNISA