Emotion and Adaptation

The complete title of this book runs ‘Analyzing Linguistic Data: A Practical Introduction to Statistics using R’ and as such it very well reflects the purpose and spirit of the book. The author guides the reader in about 350 pages from descriptive and basic statistical methods over classification and clustering to (generalised) linear and mixed models. Each of the methods is introduced in the context of concrete linguistic problems and demonstrated on exciting datasets from current research in the language sciences. In line with its practical orientation, the book focuses primarily on using the methods and interpreting the results. This implies that the mathematical treatment of the techniques is held at a minimum if not absent from the book. In return, the reader is provided with very detailed explanations on how to conduct the analyses using R [1]. The first chapter sets the tone being a 20-page introduction to R. For this and all subsequent chapters, the R code is intertwined with the chapter text and the datasets and functions used are conveniently packaged in the languageR package that is available on the Comprehensive R Archive Network (CRAN). With this approach, the author has done an excellent job in enabling researchers and students alike to reproduce the analyses and learn by doing. Another quality as a textbook is the fact that every chapter ends with Workbook sections where the user is invited to exercise his or her analysis skills on supplemental datasets. Full solutions including code, results and comments are given in Appendix A (30 pages). Instructors are therefore very well served by this text, although they might want to balance the book with some more mathematical treatment depending on the target audience. After the introductory chapter on R, the book opens on graphical data exploration. Chapter 3 treats probability distributions and common sampling distributions. Under basic statistical methods (Chapter 4), distribution tests and tests on means and variances are covered. Chapter 5 deals with clustering and classification. Strangely enough, the clustering section has material on PCA, factor analysis, correspondence analysis and includes only one subsection on clustering, devoted notably to hierarchical partitioning methods. The classification part deals with decision trees, discriminant analysis and support vector machines. The regression chapter (Chapter 6) treats linear models, generalised linear models, piecewise linear models and a substantial section on models for lexical richness. The final chapter on mixed models is particularly interesting as it is one of the few text book accounts that introduce the reader to using the (innovative) lme4 package of Douglas Bates which implements linear mixed-effects models. Moreover, the case studies included in this

Analyzing linguistic data: a practical introduction to statistics using R

PROMETHEE: A comprehensive literature review on methodologies and applications

Mobile devices such as laptops, personal digital assistants, and mobile phones have become a learning tool with great potential in both classrooms and outdoor learning. Although there have been qualitative analyses of the use of mobile devices in education, systematic quantitative analyses of the effects of mobile-integrated education are lacking. This study performed a meta-analysis and research synthesis of the effects of integrated mobile devices in teaching and learning, in which 110 experimental and quasiexperimental journal articles published during the period 1993-2013 were coded and analyzed. Overall, there was a moderate mean effect size of 0.523 for the application of mobile devices to education. The effect sizes of moderator variables were analyzed and the advantages and disadvantages of mobile learning in different levels of moderator variables were synthesized based on content analyses of individual studies. The results of this study and their implications for both research and practice are discussed. This is a meta-analysis and research synthesis study for mobile-integrated education.110 published journal articles that were written over a 20-year period were coded and analyzed.The application of mobile devices to education has a moderate mean effect size.The effect sizes of moderator variables were analyzed.The benefits and drawbacks of mobile learning were synthesized.

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The effects of integrating mobile devices with teaching and learning on students' learning performance

Handbook of the International Phonetic Association: A Guide to the Use of the International Phonetic Alphabet

Cloud computing is a new trend that is expected to reshape the information technology landscape. It can provide a new process to user such as software, infrastructure and platforms as a service over the Internet. In this trend, traditional way for manufacturing system has been changed from set up the system software in the machine to access internet and use it at anytime. Manufacturing system has process consists of many production parts and stages. And control and operate status is necessary to monitor, observe and mange the system very often. In this paper, we propose component model for manufacturing system in cloud computing environment. This model consists of three layers; manufacturing cloud, service cloud and user cloud. And each layer relate their role to other factor in the cloud.

A Component Model for Manufacturing System in Cloud Computing

Social network service (SNS) has become in a powerful diffusion media and technique in several fields such as communication, e-commerce and business marketing And, nowadays, the relationship between the people in our society is also very important role to keep their concern or interest In this environment, the people use SNS such as Twitter, Me2Day, Facebook, Linknow and so on In this paper, we propose relationship management system using topic map for SNS In order to make this system architecture, topic map that is to analyze and design the relation of human factor as a topic was used

Topic map based management system for social network service

Generally, CSP used to analyze and describe the system’s process. And SCORM proposed the international standard to manage the learning contents for e-learning system. Therefore we developed e-learning system that is able to support learning materials include learning contents and topics according to SCORM interface. We also used CSP to the system to analyze the system’s process and identified the logics efficiently.

CSP Based SCORM Interface for E-Learning System

The manufacturing system in the factory has been changing more complex, and the user who is system engineer or operator wants more powerful and efficient manufacturing system. Therefore the system developer and designer needs to know the factor what is important quality for the manufacturing system with their needs. This paper propose quality model for success manufacturing system. For this work, we extracted the quality attributes from exist work fitting on their needs. And we construct a quality model to consider their relation each other. Finally we expect our model can be help and give guideline to the system engineers or designers when they make a plan to develop the manufacturing system.

A Quality Model for Success Manufacturing System

To promote productivity is very important work in manufacturing system. For this work, manufacturing system has to operate with high performance without jam or system error. And it has to perform to interface and control with unit component or process in high speed communication and handing the signal and data. In this paper, we propose dual CPU based process for manufacturing system. To perform the process reducing any jam or system error in manufacturing system, we use dual CPU. This framework is able to get more efficient operation performance better than existence method.

Hwa-Young Jeong

Papers

A Component Model for Manufacturing System in Cloud Computing

Topic map based management system for social network service

CSP Based SCORM Interface for E-Learning System

A Quality Model for Success Manufacturing System

A Dual CPU Based Fault Tolerance Technique for Manufacturing System