technical guideline for maize seed technology

technical guideline for maize seed technology

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technical guideline for maize seed technologyMay 4, 2011June 9, 2020Where the content of the eBook requires a specific layout, or contains maths or other special characters, the eBook will be available in PDF (PBK) format, which cannot be reflowed. For both formats the functionality available will depend on how you access the ebook (via Bookshelf Online in your browser or via the Bookshelf app on your PC or mobile device). A reference for statistically sophisticated individuals, the Handbook is also accessible to those lacking the theoretical or mathematical background required for understanding subject matter typically documented in statistics reference books. I cannot think of a single-volume text which is close to the range and depth of this handbook.I also recommend it for teachers who will find a lot of good examples they can use within their courses. —Philippe Castagliola, Journal of Applied Statistics, November 2007 I am sure I will come back to it to check a statistical test. —Kostas Triantafyllopoulos, Significance, December 2007 To learn how to manage your cookie settings, please see our. The 13-digit and 10-digit formats both work. Please try again. Used: GoodSomething we hope you'll especially enjoy: FBA items qualify for FREE Shipping and Amazon Prime. Learn more about the program. Please choose a different delivery location or purchase from another seller.New in the Fifth Edition: Substantial updates and new material throughout New chapters on path analysis, meta-analysis, and structural equation modeling Index numbers and time series analysis applications in business and economics Statistical quality control applications in industry Random- and fixed-effects models for the analysis of variance Broad in scope, the Handbook is intended for individuals involved in a wide spectrum of academic disciplines encompassing the fields of mathematics, the social, biological, and environmental sciences, business, and education.http://fleshlight-tw.com/userfiles/bosch-mum-4655-profimixx-46-manual.xml

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A reference for statistically sophisticated individuals, the Handbook is also accessible to those lacking the theoretical or mathematical background required for understanding subject matter typically documented in statistics reference books. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required. I cannot think of a single-volume text which is close to the range and depth of this handbook. I also recommend it for teachers who will find a lot of good examples they can use within their courses. ?Philippe Castagliola, Journal of Applied Statistics, November 2007 This book occupies a unique place in the literature.Full content visible, double tap to read brief content. Videos Help others learn more about this product by uploading a video. Upload video To calculate the overall star rating and percentage breakdown by star, we don’t use a simple average. Instead, our system considers things like how recent a review is and if the reviewer bought the item on Amazon. It also analyzes reviews to verify trustworthiness. Please try again later. M. Gosse 5.0 out of 5 stars This text is excellent for reminding one which null hypothesis, exactly, one is testing, and is clear on the assumptions beibg made (e.g. iid observations). It is particularly useful in refreshing knowledge of tests, and explaining various modifications to statistical tests. As with the previous version, each test is shown with an example set of data and associated hypothesis. The book does assume some statistics knowledge, and would be suitable as a reference statistics text for computer scientists and operations researchers, as well as applied statisticians. Social scientists with a statistics background should also get value out of this book. This is the book I wish I knew about when I was a statistics student.It gives every variation on every test, with detailed examples and tables.http://geodez.com/pliki/bosch-mum4405-manual.xml It has plenty of equations for those who want to do calculations themselves. But it is does not derive any equations or prove any theorems. It explains concepts in words (with examples), not equations. This makes it quite understandable by scientists (as well as statisticians). It is extremely well written. Although it purports to be comprehensive, no book really can be. It makes no mention of nonlinear regression, or model comparisons. Its coverage of survival curves is a bit weak (compared to the rest of the book), as is its coverage of modern (computer intensive) statistical methods. If you analyze data, you should have access to this book as a reference. No other book is so comprehensive and yet readable. Its price, per page, makes it an amazing bargain.Many worked examples (by hand) so you can see how it's all done, followed by really excellent explanations on how to interpret the results. Do not expect the same treatment for some of the more exotic tests like factor analysis or principal component analysis. It's just not there.More helpful than a simple google search -- no. Easy to use - no. This book somewhat accomplishes that, but in a way that has not been helpful most of the time. For example, it goes on ad-nauseum about the Z and t tests, yet the discussion about boostrapping and, to a greater extent, the multivariate techniques, is insufficient to really understand what is going on. I gave it two stars because, in terms of its breadth of topics, this book is indeed a compendium of the most commonly used procedures. Another feature that some may like is the copious referencing, which may be helpful for justifying the use of a particular test. However, I find that the rapid pace of statistical research means you can't rely on a smattering of papers to make your case. You really just need to dig into your actual dataset to find out what works.http://www.drupalitalia.org/node/72987 In conclusion, I found myself turning to other books (read: more specialized or more basic) or to trusted internet sources when I needed to find a method. Trying to go from a research problem to a test using this book is next to impossible, as you will need to slog though its somewhat tedious layout. Bottom line: If you know what test you want to do, then you can find the procedure for free (internet). If you don't know what you're doing, then this book won't teach you (too terse and verbose.at the same time!). If you want a nice looking paperweight that makes you feel better, then perhaps you can get it. But it offers very little new material that cannot be found, more easily and coherently, from more basic or internet-based sources. As such, its unclear who would benefit from this book.It can assist with statistical design selections as it provides numerous examples and explanations regarding the statistical results from the selected method.The pages are very thin and delicate, which is rather odd for a hardcover textbook. Overall I was not satisfied and I returned it.The pages are thin and the print is for boring- it reminds me of a dictionary. The book is so dull and unengaging that i am stressed out after reading.The delivery was made without a problem: a good deal. I write scientific papers. The book was not as complete as I would have liked.While I own a number of additional statistics books, I found this book to be all encompassing and it will be used as a one stop reference book on statistics. I didn't own the fourth edition and since I will be re-analyzing my data for future publication I felt it would be a handy reference book to own.Consigliato a chi vuole avere sempre un valido riferimento per l'approfondimento della statistica. Breadcrumbs Section. Click here to navigate to respective pages.http://atlantichurricane.com/images/bose-acoustimass-10-iv-manual.pdf Book Book Handbook of Parametric and Nonparametric Statistical Procedures DOI link for Handbook of Parametric and Nonparametric Statistical Procedures Handbook of Parametric and Nonparametric Statistical Procedures book Handbook of Parametric and Nonparametric Statistical Procedures DOI link for Handbook of Parametric and Nonparametric Statistical Procedures Handbook of Parametric and Nonparametric Statistical Procedures book By David J. Sheskin Edition 5th Edition First Published 2011 eBook Published 9 June 2020 Pub. An Empirical Study, ACM Transactions on Software Engineering and Methodology, 30:3, (1-56), Online publication date: 1-May-2021. Liu X, Zhai D, Bai Y, Ji X and Gao W (2020) Contrast Enhancement via Dual Graph Total Variation-Based Image Decomposition, IEEE Transactions on Circuits and Systems for Video Technology, 30:8, (2463-2476), Online publication date: 1-Aug-2020. Hamidzadeh J, Kashefi N and Moradi M (2020) Combined weighted multi-objective optimizer for instance reduction in two-class imbalanced data problem, Engineering Applications of Artificial Intelligence, 90:C, Online publication date: 1-Apr-2020. Saleh A, Shehata S and Labeeb L (2019) A fuzzy-based classification strategy (FBCS) based on brain---computer interface, Soft Computing - A Fusion of Foundations, Methodologies and Applications, 23:7, (2343-2367), Online publication date: 1-Apr-2019. Xue X (2019) Compact memetic algorithm-based process model matching, Soft Computing - A Fusion of Foundations, Methodologies and Applications, 23:13, (5249-5257), Online publication date: 1-Jul-2019. Huang Y, Costa D, Zhang F and Zou Y (2019) An empirical study on the issue reports with questions raised during the issue resolving process, Empirical Software Engineering, 24:2, (718-750), Online publication date: 1-Apr-2019.http://www.insurancedirectcanada.ca/wp-content/plugins/formcraft/file-upload/server/content/files/1627101f45251a---bowflex-weight-bench-manual.pdf Silva Firmino A, Abreu Silva R and Times V (2019) A reactive GRASP metaheuristic for the container retrieval problem to reduce crane's working time, Journal of Heuristics, 25:2, (141-173), Online publication date: 1-Apr-2019. Deldjoo Y, Dacrema M, Constantin M, Eghbal-Zadeh H, Cereda S, Schedl M, Ionescu B and Cremonesi P (2019) Movie genome, User Modeling and User-Adapted Interaction, 29:2, (291-343), Online publication date: 1-Apr-2019. Aniche M, Bavota G, Treude C, Gerosa M and Deursen A (2018) Code smells for Model-View-Controller architectures, Empirical Software Engineering, 23:4, (2121-2157), Online publication date: 1-Aug-2018. Hadizadeh H and Bajic I (2018) Full-Reference Objective Quality Assessment of Tone-Mapped Images, IEEE Transactions on Multimedia, 20:2, (392-404), Online publication date: 1-Feb-2018. Sousa B, Bigonha M and Ferreira K A systematic literature mapping on the relationship between design patterns and bad smells Proceedings of the 33rd Annual ACM Symposium on Applied Computing, (1528-1535) Fischer S, Lopez-Herrejon R and Egyed A Towards a fault-detection benchmark for evaluating software product line testing approaches Proceedings of the 33rd Annual ACM Symposium on Applied Computing, (2034-2041) Mohammadi M, Atashin A, Hofman W and Tan Y (2018) Comparison of Ontology Alignment Systems Across Single Matching Task Via the McNemar’s Test, ACM Transactions on Knowledge Discovery from Data, 12:4, (1-18), Online publication date: 13-Jul-2018. Gerostathopoulos I, Prehofer C and Bures T Adapting a system with noisy outputs with statistical guarantees Proceedings of the 13th International Conference on Software Engineering for Adaptive and Self-Managing Systems, (58-68) Dosea M, Sant'Anna C and da Silva B How do design decisions affect the distribution of software metrics.www.denizraf.com/image/files/boxxer-race-2008-manual.pdf Das S, Bhattacharya A and Chakraborty A (2018) Quasi-reflected ions motion optimization algorithm for short-term hydrothermal scheduling, Neural Computing and Applications, 29:6, (123-149), Online publication date: 1-Mar-2018. Hamidzadeh J and Moradi M (2018) Improved one-class classification using filled function, Applied Intelligence, 48:10, (3263-3279), Online publication date: 1-Oct-2018. Erdelyi A, Winkler T and Rinner B (2018) Privacy protection vs.Haunschild R and Bornmann L (2018) Field- and time-normalization of data with many zeros, Scientometrics, 116:2, (997-1012), Online publication date: 1-Aug-2018. Zhou B, Song B, Hassan M and Alamri A (2018) Multilinear rank support tensor machine for crowd density estimation, Engineering Applications of Artificial Intelligence, 72:C, (382-392), Online publication date: 1-Jun-2018. Bolivar M (2018) Governance in Smart Cities, International Journal of E-Planning Research, 7:2, (1-19), Online publication date: 1-Apr-2018. Elahi M, Deldjoo Y, Bakhshandegan Moghaddam F, Cella L, Cereda S and Cremonesi P Exploring the Semantic Gap for Movie Recommendations Proceedings of the Eleventh ACM Conference on Recommender Systems, (326-330) Yao Y, Xiao Z, Wang B, Viswanath B, Zheng H and Zhao B Complexity vs. Filho J and Diniz P (2017) A recursive least square algorithm for online kernel principal component extraction, Neurocomputing, 237:C, (255-264), Online publication date: 10-May-2017. Bornmann L (2017) Is collaboration among scientists related to the citation impact of papers because their quality increases with collaboration. An analysis based on data from F1000Prime and normalized citation scores, Journal of the Association for Information Science and Technology, 68:4, (1036-1047), Online publication date: 1-Apr-2017. Yuan Q, Dai G and Zhang Y (2017) A novel multi-objective evolutionary algorithm based on LLE manifold learning, Engineering with Computers, 33:2, (293-305), Online publication date: 1-Apr-2017.http://www.agrosystem.com.tr/wp-content/plugins/formcraft/file-upload/server/content/files/16271020015a68---bowflex-users-manual.pdf Wang S, Ali S, Gotlieb A and Liaaen M (2017) Automated product line test case selection, Software and Systems Modeling (SoSyM), 16:2, (417-441), Online publication date: 1-May-2017. De K and Masilamani V (2017) No-reference image contrast measure using image statistics and random forest, Multimedia Tools and Applications, 76:18, (18641-18656), Online publication date: 1-Sep-2017. Unal P, Temizel T and Eren P (2017) What installed mobile applications tell about their owners and how they affect users download behavior, Telematics and Informatics, 34:7, (1153-1165), Online publication date: 1-Nov-2017. Liu J, Chung F and Wang S (2017) Bayesian zero-order TSK fuzzy system modeling, Applied Soft Computing, 55:C, (253-264), Online publication date: 1-Jun-2017. Srisukkham W, Zhang L, Neoh S, Todryk S and Lim C (2017) Intelligent leukaemia diagnosis with bare-bones PSO based feature optimization, Applied Soft Computing, 56:C, (405-419), Online publication date: 1-Jul-2017. Liu Z, Blasch E and John V (2017) Statistical comparison of image fusion algorithms, Information Fusion, 36:C, (251-260), Online publication date: 1-Jul-2017. Peng L, Zhang H, Zhang H and Yang B (2017) A fast feature weighting algorithm of data gravitation classification, Information Sciences: an International Journal, 375:C, (54-78), Online publication date: 1-Jan-2017. Abdul Manap R, Shao L and Frangi A (2017) PATCH-IQ, Information Sciences: an International Journal, 420:C, (329-344), Online publication date: 1-Dec-2017. Taba S, Keivanloo I, Zou Y and Wang S (2017) An exploratory study on the usage of common interface elements in android applications, Journal of Systems and Software, 131:C, (491-504), Online publication date: 1-Sep-2017. Niu H, Keivanloo I and Zou Y (2017) API usage pattern recommendation for software development, Journal of Systems and Software, 129:C, (127-139), Online publication date: 1-Jul-2017.https://www.etoiles-recrutement.com/wp-content/plugins/formcraft/file-upload/server/content/files/16271020d2306a---bowflex-workout-manual-download.pdf Jaafar F, Lozano A, Guhneuc Y and Mens K (2017) Analyzing software evolution and quality by extracting Asynchrony change patterns, Journal of Systems and Software, 131:C, (311-322), Online publication date: 1-Sep-2017. Lucca G, Sanz J, Dimuro G, Bedregal B, Asiain M, Elkano M and Bustince H (2017) CC-integrals, Knowledge-Based Systems, 119:C, (32-43), Online publication date: 1-Mar-2017. Hiew B, Tan S and Lim W (2017) A double-elimination-tournament-based competitive co-evolutionary artificial neural network classifier, Neurocomputing, 249:C, (345-356), Online publication date: 2-Aug-2017. Cernadas E, Fernndez-Delgado M, Gonzlez-Rufino E and Carrin P (2017) Influence of normalization and color space to color texture classification, Pattern Recognition, 61:C, (120-138), Online publication date: 1-Jan-2017. Nguyen B, Morell C and De Baets B (2017) Supervised distance metric learning through maximization of the Jeffrey divergence, Pattern Recognition, 64:C, (215-225), Online publication date: 1-Apr-2017. Ping Y, Tian Y, Guo C, Wang B and Yang Y (2017) FRSVC, Pattern Recognition, 69:C, (286-298), Online publication date: 1-Sep-2017. Knezevic K, Picek S and Miller J Amplitude-oriented mixed-type CGP classification Proceedings of the Genetic and Evolutionary Computation Conference Companion, (1415-1418) Rathore S and Kumar S (2017) A decision tree logic based recommendation system to select software fault prediction techniques, Computing, 99:3, (255-285), Online publication date: 1-Mar-2017. Bornmann L and Haunschild R (2017) An empirical look at the nature index, Journal of the Association for Information Science and Technology, 68:3, (653-659), Online publication date: 1-Mar-2017. Mei Y, Omidvar M, Li X and Yao X (2016) A Competitive Divide-and-Conquer Algorithm for Unconstrained Large-Scale Black-Box Optimization, ACM Transactions on Mathematical Software, 42:2, (1-24), Online publication date: 3-Jun-2016.www.denizlihurda.com/image/files/boxxer-race-2007-manual.pdf Hidalgo-Paniagua A, Vega-Rodriguez M and Ferruz J (2016) Applying the MOVNS (multi-objective variable neighborhood search) algorithm to solve the path planning problem in mobile robotics, Expert Systems with Applications: An International Journal, 58:C, (20-35), Online publication date: 1-Oct-2016. Daqi G, Ahmed D, Lili G, Zejian W and Zhe W (2016) Pseudo-inverse linear discriminants for the improvement of overall classification accuracies, Neural Networks, 81:C, (59-71), Online publication date: 1-Sep-2016. Yue T and Ali S (2016) Empirically evaluating OCL and Java for specifying constraints on UML models, Software and Systems Modeling (SoSyM), 15:3, (757-781), Online publication date: 1-Jul-2016. Samma H, Lim C and Mohamad Saleh J (2016) A new Reinforcement Learning-based Memetic Particle Swarm Optimizer, Applied Soft Computing, 43:C, (276-297), Online publication date: 1-Jun-2016. Czajkowski M and Kretowski M (2016) The role of decision tree representation in regression problems - An evolutionary perspective, Applied Soft Computing, 48:C, (458-475), Online publication date: 1-Nov-2016. Pedemonte M, Luna F and Alba E (2016) A Systolic Genetic Search for reducing the execution cost of regression testing, Applied Soft Computing, 49:C, (1145-1161), Online publication date: 1-Dec-2016.Paternain D, Bustince H, Pagola M, Sussner P, Kolesrov A and Mesiar R (2016) Capacities and overlap indexes with an application in fuzzy rule-based classification systems, Fuzzy Sets and Systems, 305:C, (70-94), Online publication date: 15-Dec-2016. Wu J, Lin W, Fang Y, Li L, Shi G and S I (2016) Visual structural degradation based reduced-reference image quality assessment, Image Communication, 47:C, (16-27), Online publication date: 1-Sep-2016. Han D, Yang Q, Xing J, Li J and Wang H (2016) FAME, Information and Software Technology, 76:C, (118-134), Online publication date: 1-Aug-2016. Trunfio G, Topa P and Wzs J (2016) A new algorithm for adapting the configuration of subcomponents in large-scale optimization with cooperative coevolution, Information Sciences: an International Journal, 372:C, (773-795), Online publication date: 1-Dec-2016. Idri A, Abnane I and Abran A (2016) Missing data techniques in analogy-based software development effort estimation, Journal of Systems and Software, 117:C, (595-611), Online publication date: 1-Jul-2016. Pacheco F, Valente de Oliveira J, Sanchez R, Cerrada M, Cabrera D, Li C, Zurita G and Artes M (2016) A statistical comparison of neuroclassifiers and feature selection methods for gearbox fault diagnosis under realistic conditions, Neurocomputing, 194:C, (192-206), Online publication date: 19-Jun-2016. Nguyen B, Morell C and De Baets B (2016) Large-scale distance metric learning for k-nearest neighbors regression, Neurocomputing, 214:C, (805-814), Online publication date: 19-Nov-2016. Erfani S, Rajasegarar S, Karunasekera S and Leckie C (2016) High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning, Pattern Recognition, 58:C, (121-134), Online publication date: 1-Oct-2016. Hooshmand Moghaddam V and Hamidzadeh J (2016) New Hermite orthogonal polynomial kernel and combined kernels in Support Vector Machine classifier, Pattern Recognition, 60:C, (921-935), Online publication date: 1-Dec-2016. Dawadi P, Cook D and Schmitter-Edgecombe M (2016) Modeling patterns of activities using activity curves, Pervasive and Mobile Computing, 28:C, (51-68), Online publication date: 1-Jun-2016. Saxena D, Sinha A, Duro J and Zhang Q (2016) Entropy-Based Termination Criterion for Multiobjective Evolutionary Algorithms, IEEE Transactions on Evolutionary Computation, 20:4, (485-498), Online publication date: 1-Aug-2016. Damiani E, Ceravolo P, Frati F, Bellandi V, Maier R, Seeber I and Waldhart G (2015) Applying recommender systems in collaboration environments, Computers in Human Behavior, 51:PB, (1124-1133), Online publication date: 1-Oct-2015. Hirschprung R, Toch E and Maimon O (2015) Simplifying Data Disclosure Configurations in a Cloud Computing Environment, ACM Transactions on Intelligent Systems and Technology, 6:3, (1-26), Online publication date: 20-May-2015. Bornmann L (2015) Interrater reliability and convergent validity of F1000Prime peer review, Journal of the Association for Information Science and Technology, 66:12, (2415-2426), Online publication date: 1-Dec-2015. Dasari S, Lavesson N, Andersson P and Persson M Tree-Based Response Surface Analysis Revised Selected Papers of the First International Workshop on Machine Learning, Optimization, and Big Data - Volume 9432, (118-129) Olivera A, Garcia-Nieto J and Alba E (2015) Reducing vehicle emissions and fuel consumption in the city by using particle swarm optimization, Applied Intelligence, 42:3, (389-405), Online publication date: 1-Apr-2015. Bodei C, Bortolussi L, Chiarugi D, Guerriero M, Policriti A and Romanel A (2015) On the impact of discreteness and abstractions on modelling noise in gene regulatory networks, Computational Biology and Chemistry, 56:C, (98-108), Online publication date: 1-Jun-2015. Rakshit P and Konar A (2015) Extending multi-objective differential evolution for optimization in presence of noise, Information Sciences: an International Journal, 305:C, (56-76), Online publication date: 1-Jun-2015. Wang S, Ali S and Gotlieb A (2015) Cost-effective test suite minimization in product lines using search techniques, Journal of Systems and Software, 103:C, (370-391), Online publication date: 1-May-2015. Mittas N, Papatheocharous E, Angelis L and Andreou A (2015) Integrating non-parametric models with linear components for producing software cost estimations, Journal of Systems and Software, 99:C, (120-134), Online publication date: 1-Jan-2015. Yeguas E, Luzon M, Pavon R, Laza R, Arroyo G and Diaz F (2014) Automatic parameter tuning for Evolutionary Algorithms using a Bayesian Case-Based Reasoning system, Applied Soft Computing, 18:C, (185-195), Online publication date: 1-May-2014. Fazzolari M, Alcala R and Herrera F (2014) A multi-objective evolutionary method for learning granularities based on fuzzy discretization to improve the accuracy-complexity trade-off of fuzzy rule-based classification systems, Applied Soft Computing, 24:C, (470-481), Online publication date: 1-Nov-2014. Lanzaro A, Natella R, Winter S, Cotroneo D and Suri N An empirical study of injected versus actual interface errors Proceedings of the 2014 International Symposium on Software Testing and Analysis, (397-408) Khan M, Khan E and Abbasi Z (2014) Segment dependent dynamic multi-histogram equalization for image contrast enhancement, Digital Signal Processing, 25:C, (198-223), Online publication date: 1-Feb-2014. Peng L, Zhang H, Yang B and Chen Y (2014) A new approach for imbalanced data classification based on data gravitation, Information Sciences: an International Journal, 288:C, (347-373), Online publication date: 20-Dec-2014. Chaves-Gonzalez J and Vega-Rodriguez M (2014) A multiobjective approach based on the behavior of fireflies to generate reliable DNA sequences for molecular computing, Applied Mathematics and Computation, 227:C, (291-308), Online publication date: 15-Jan-2014. Berrocal-Plaza V, Vega-Rodriguez M and Sanchez-Perez J (2014) On the use of multiobjective optimization for solving the Location Areas strategy with different paging procedures in a realistic mobile network, Applied Soft Computing, 18:C, (146-157), Online publication date: 1-May-2014. Introne J and Drescher M Analyzing the flow of knowledge in computer mediated teams Proceedings of the 2013 conference on Computer supported cooperative work, (341-356) Fernandez-Saez A, Chaudron M, Genero M and Ramos I Are forward designed or reverse-engineered UML diagrams more helpful for code maintenance. Helms T, Luboschik M, Schumann H and Uhrmacher A An Approximate Execution of Rule-Based Multi-level Models Proceedings of the 11th International Conference on Computational Methods in Systems Biology - Volume 8130, (19-32) Chaves-Gonzalez J, Vega-Rodriguez M and Granado-Criado J (2013) A multiobjective swarm intelligence approach based on artificial bee colony for reliable DNA sequence design, Engineering Applications of Artificial Intelligence, 26:9, (2045-2057), Online publication date: 1-Oct-2013. Moreno-Torres J, Llori X, Goldberg D and Bhargava R (2013) Repairing fractures between data using genetic programming-based feature extraction, Information Sciences: an International Journal, 222, (805-823), Online publication date: 1-Feb-2013. Wu Y, Zhou Y, Saveriades G, Agaian S, Noonan J and Natarajan P (2013) Local Shannon entropy measure with statistical tests for image randomness, Information Sciences: an International Journal, 222, (323-342), Online publication date: 1-Feb-2013. Shahrabi J, Hadavandi E and Asadi S (2013) Developing a hybrid intelligent model for forecasting problems, Knowledge-Based Systems, 43, (112-122), Online publication date: 1-May-2013. FernaNdez A, LoPez V, Galar M, Del Jesus M and Herrera F (2013) Analysing the classification of imbalanced data-sets with multiple classes, Knowledge-Based Systems, 42, (97-110), Online publication date: 1-Apr-2013. Carmona C, Gonzalez P, Garcia-Domingo B, del Jesus M and Aguilera J (2013) MEFES, Knowledge-Based Systems, 54:C, (73-85), Online publication date: 1-Dec-2013. Ishibuchi H and Nojima Y (2013) Repeated double cross-validation for choosing a single solution in evolutionary multi-objective fuzzy classifier design, Knowledge-Based Systems, 54:C, (22-31), Online publication date: 1-Dec-2013. Lopez V, Fernandez A, Moreno-Torres J and Herrera F (2012) Analysis of preprocessing vs.Open problems on intrinsic data characteristics, Expert Systems with Applications: An International Journal, 39:7, (6585-6608), Online publication date: 1-Jun-2012. Gomez-Lorente D, Triguero I, Gil C and Espin Estrella A (2012) Evolutionary algorithms for the design of grid-connected PV-systems, Expert Systems with Applications: An International Journal, 39:9, (8086-8094), Online publication date: 1-Jul-2012. Macia Bertran I, Garcia A and von Staa A An exploratory study of code smells in evolving aspect-oriented systems Proceedings of the tenth international conference on Aspect-oriented software development, (203-214) Garcia-Nieto J and Alba E Empirical computation of the quasi-optimal number of informants in particle swarm optimization Proceedings of the 13th annual conference on Genetic and evolutionary computation, (147-154) Chicano F, Luna F, Nebro A and Alba E Using multi-objective metaheuristics to solve the software project scheduling problem Proceedings of the 13th annual conference on Genetic and evolutionary computation, (1915-1922) Scholer F, Turpin A and Sanderson M Quantifying test collection quality based on the consistency of relevance judgements Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval, (1063-1072) Marinescu C Are the classes that use exceptions defect prone. Reijers H, Mendling J and Dijkman R (2011) Human and automatic modularizations of process models to enhance their comprehension, Information Systems, 36:5, (881-897), Online publication date: 1-Jul-2011.