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Record Nr. |
UNISA990001774420203316 |
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Autore |
SCIUMBATA, Letizia Rita |
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Titolo |
I trasporti nella normativa europea : atti del seminario Roma, 29 maggio 2002 / a cura di Letizia Rita Sciumbata |
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Pubbl/distr/stampa |
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ISBN |
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Descrizione fisica |
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Collana |
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Quaderni per la ricerca ; 14 |
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Disciplina |
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Soggetti |
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Collocazione |
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XXIV.3. Coll. 24/ 14 (Coll. PSB 14) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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In testa al front.: Associazione di promozione europea (APE), Istituto di studi europei Alcide De Gasperi |
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2. |
Record Nr. |
UNINA9910462689603321 |
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Autore |
Brumberger Eva |
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Titolo |
Designing Texts [[electronic resource] ] : Teaching Visual Communication : Teaching Visual Communication |
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Pubbl/distr/stampa |
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Amityville, : Baywood Publishing Company, Inc., 2013 |
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ISBN |
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Descrizione fisica |
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1 online resource (341 p.) |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Interdisciplinary approach in education |
Visual communication -- Study and teaching (Higher) |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di contenuto |
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""Designing Texts: Teaching Visual Communication""; ""Cover""; ""Title Page""; ""Copyright Page""; ""Table of Contents""; ""Introduction: Meeting the Challenge of Teaching Visual Communication""; ""PART 1 Visual Thinking and Problem Solving""; ""CHAPTER 1 How to Read Landscapes: A Method for Integrating Visual Communication in the Technical Communication Classroom""; ""CHAPTER 2 Design as Problem Solving""; ""CHAPTER 3 Designing a Visual Argument Course in an Era of Accelerating Technological Change""; ""CHAPTER 4 Teaching Form and Color as Emotion Triggers"" |
""PART 2 Contexts for Teaching and Learning""""CHAPTER 5 Teaching Visual Communication Through Community-Based Projects""; ""CHAPTER 6 Teaching Visual Communication Online: Methods for a Changing Classroom""; ""CHAPTER 7 Integrating Visual and Verbal: A Framework for Teaching and Assessment""; ""PART 3 Evaluation and Assessment""; ""CHAPTER 8 Evaluating Visual Communication""; ""CHAPTER 9 A Practical Guide to Classroom Assessment in Visual Communication Design""; ""CHAPTER 10 Evaluating and Assessing Designed Documents: Assignments, Projects, Portfolios, and More"" |
""PART 4 Tools and Technologies""""CHAPTER 11 Balancing Act: A Guide to Analyzing Context and Developing a Technologically Appropriate Approach to Visual Communication Instruction""; ""CHAPTER 12 Teaching Students to Design Rhetorically: A Low-Tech Process |
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Approach""; ""CHAPTER 13 Filling in the Gaps: Learning to Live With�and Teach With�Microsoft SmartArt""; ""PART 5 Concluding Thoughts""; ""CHAPTER 14 Teaching Visual Rhetoric""; ""Appendix""; ""Contributors""; ""Index""; ""Back Cover"" |
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3. |
Record Nr. |
UNINA9910298568303321 |
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Autore |
Maji Pradipta |
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Titolo |
Scalable Pattern Recognition Algorithms : Applications in Computational Biology and Bioinformatics / / by Pradipta Maji, Sushmita Paul |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 |
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ISBN |
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Edizione |
[1st ed. 2014.] |
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Descrizione fisica |
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1 online resource (316 p.) |
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Disciplina |
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006.3 |
006.3/1 |
006.312 |
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Soggetti |
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Bioinformatics |
Pattern recognition systems |
Artificial intelligence |
Data mining |
Radiology |
Computational and Systems Biology |
Automated Pattern Recognition |
Artificial Intelligence |
Data Mining and Knowledge Discovery |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters and index. |
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Nota di contenuto |
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Introduction to Pattern Recognition and Bioinformatics -- Part I Classification -- Neural Network Tree for Identification of Splice Junction and Protein Coding Region in DNA -- Design of String Kernel to Predict Protein Functional Sites Using Kernel-Based Classifiers -- Part II Feature Selection -- Rough Sets for Selection of Molecular |
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Descriptors to Predict Biological Activity of Molecules -- f -Information Measures for Selection of Discriminative Genes from Microarray Data -- Identification of Disease Genes Using Gene Expression and Protein-Protein Interaction Data -- Rough Sets for Insilico Identification of Differentially Expressed miRNAs -- Part III Clustering -- Grouping Functionally Similar Genes from Microarray Data Using Rough-Fuzzy Clustering -- Mutual Information Based Supervised Attribute Clustering for Microarray Sample Classification -- Possibilistic Biclustering for Discovering Value-Coherent Overlapping d -Biclusters -- Fuzzy Measures and Weighted Co-Occurrence Matrix for Segmentation of Brain MR Images. |
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Sommario/riassunto |
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Recent advances in high-throughput technologies have resulted in a deluge of biological information. Yet the storage, analysis, and interpretation of such multifaceted data require effective and efficient computational tools. This unique text/reference addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The book reviews both established and cutting-edge research, following a clear structure reflecting the major phases of a pattern recognition system: classification, feature selection, and clustering. The text provides a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Topics and features: Reviews the development of scalable pattern recognition algorithms for computational biology and bioinformatics Integrates different soft computing and machine learning methodologies with pattern recognition tasks Discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets Presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images Includes numerous examples and experimental results to support the theoretical concepts described Concludes each chapter with directions for future research and a comprehensive bibliography This important work will be of great use to graduate students and researchers in the fields of computer science, electrical and biomedical engineering. Researchers and practitioners involved in pattern recognition, machine learning, computational biology and bioinformatics, data mining, and soft computing will also find the book invaluable. |
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