A Comparison of the Missing-Indicator Method and Complete Case Analysis in Case of Categorical Data
Global tendency to democratization of the last decades is interested by a lot of researchers and politicians. While the significant part of the studies is dedicated to indices’ validity is concentrated on measurement that are used in broad cross-country surveys, Professor of Oxford University Stein Ringen pays attention to the insufficient consideration of system characteristics of democracy and suggests to investigate individual people’ perception the level of democracy in their own country (at the same time he doesn’t offer any empirical database). In this research the author by means of regression and correlation analysis concludes that not all indices of democracy can be called valid, in particular, the most invalid index is the widespread index Polity IV.
It is commonly the case in multi-modal pattern recognition that certain modality-specific object features are missing in the training set. We address here the missing data problem for kernel-based Support Vector Machines, in which each modality is represented by the respective kernel matrix over the set of training objects, such that the omission of a modality for some object manifests itself as a blank in the modality-specific kernel matrix at the relevant position. We propose to fill the blank positions in the collection of training kernel matrices via a variant of the Neutral Point Substitution (NPS) method, where the term ”neutral point” stands for the locus of points defined by the ”neutral hyperplane” in the hypothetical linear space produced by the respective kernel. The current method crucially differs from the previously developed neutral point approach in that it is capable of treating missing data in the training set on the same basis as missing data in the test set. It is therefore of potentially much wider applicability. We evaluate the method on the Biosecure DS2 data set.
Despite empirical research showing that countries with higher level of voice and accountability are less prone to suffer from terrorism, it is not yet clear what type of terrorist activity is more likely to appear when vertical accountability is absent. This article investigates the effect of voice and accountability on suicide bombing attacks growth in countries with different institutional conditions. The results are obtained by using QOG and GTD databases for regression analysis. The results lend support to the two hypotheses tested: 1) voice and accountability has significant reductive effect on suicide bombing growth; 2) the effect of voice and accountability on suicide bombing is more profound than the effect on other types of terrorist attacks.
The authors analyzed the population life quality of some regions in Russian Federation with using of multivariate statistical analysis. The authors found that increasing population life quality, in particular, increasing life expectancy can be achieved by adjusting the demographic indicators, cash income, development of health, social and environmental security in the Volga Federal District. While in the municipalities of the Republic of Mari El the growth of employment, wages, migration and natural population growth, the number of doctors and the number of inputs houses, reducing proportion of dilapidated housing and reduced mortality improved the quality o f life and increase fertility.
This book concentrates on in-depth explanation of a few methods to address core issues, rather than presentation of a multitude of methods that are popular among the scientists. An added value of this edition is that I am trying to address two features of the brave new world that materialized after the first edition was written in 2010. These features are the emergence of “Data science” and changes in student cognitive skills in the process of global digitalization. The birth of Data science gives me more opportunities in delineating the field of data analysis. An overwhelming majority of both theoreticians and practition-ers are inclined to consider the notions of ‘data analysis” (DA) and “machine learning” (ML) as synonymous. There are, however, at least two differences between the two. First comes the difference in perspectives. ML is to equip computers with methods and rules to see through regularities of the environment - and behave accordingly. DA is to enhance conceptual understanding. These goals are not inconsistent indeed, which explains a huge overlap between DA and ML. However, there are situations in which these perspectives are not consistent. Regarding the current students’ cognitive habits, I came to the conclusion that they prefer to immediately get into the “thick of it”. Therefore, I streamlined the presentation of multidimensional methods. These methods are now organized in four Chapters, one of which presents correlation learning (Chapter 3). Three other Chapters present summarization methods both quantitative (Chapter 2) and categorical (Chapters 4 and 5). Chapter 4 relates to finding and characterizing partitions by using K-means clustering and its extensions. Chapter 5 relates to hierarchical and separative cluster structures. Using encoder-decoder data recovery approach brings forth a number of mathematically proven interrelations between methods that are used for addressing such practical issues as the analysis of mixed scale data, data standardization, the number of clusters, cluster interpretation, etc. An obvious bias towards summarization against correlation can be explained, first, by the fact that most texts in the field are biased in the opposite direction, and, second, by my personal preferences. Categorical summarization, that is, clustering is considered not just a method of DA but rather a model of classification as a concept in knowledge engineering. Also, in this edition, I somewhat relaxed the “presentation/formulation/computation” narrative struc-ture, which was omnipresent in the first edition, to be able do things in one go. Chapter 1 presents the author’s view on the DA mainstream, or core, as well as on a few Data science issues in general. Specifically, I bring forward novel material on the role of DA, including its successes and pitfalls (Section 1.4), and classification as a special form of knowledge (Section 1.5). Overall, my goal is to show the reader that Data science is not a well-formed part of knowledge yet but rather a piece of science-in-the-making.
The article explores the procedural aspect of constructing structural and logical typologies with the aim of creating the innovation index - workers attitudes guiding innovation and innovation -related behavior at workplace.
This paper presents a preliminary analysis of hotel room prices in several European cities based on the data from Booking.com website. The main question raised in the study is whether early booking is advantageous indeed, and if so, how early should it be? First a script was developed to download more than 600 thousand hotel offers for reservations from 25 March 2013 to 17 March 2014. Then an attempt to discover more details concerning the early booking effect was made via basic statistics, graphical data representation and hedonic pricing analysis. It was revealed that making reservations in advance can be really gainful, although more data and research are needed to measure the exact numbers, as they depend on at least seasonality and city.
This book contains the proceedings of the 4th International Conference on Computer Supported Education (CSEDU 2012) which was organized and sponsored by the Institute for Systems and Technologies of Information, Control and Communication (INSTICC) and technically co-sponsored by SPEE (Portuguese Society for Engineering Education), IGIP (International Society for Engineering Education), ROLE (Responsive Open Learning Environments) and IFIP TC3 (International Federation for Information Processing - Technical Committee 3 - ICT and Education).
CSEDU has become an annual meeting place for presenting and discussing learning paradigms, best practices and case studies that concern innovative computer-supported learning strategies, institutional policies on technology-enhanced learning including learning from distance, supported by technology. The Web is currently a preferred medium for distance learning and the learning practice in this context is usually referred to as e-learning or technology-enhanced learning. CSEDU 2012 is expected to give an overview of the state of the art in technology-enhanced learning and to also outline upcoming trends and promote discussions about the education potential of new learning technologies in the academic and corporate world.
This conference brings together researchers and practitioners interested in methodologies and applications related to the education field. It has five main topic areas, covering different aspects of Computer Supported Education, including "Information Technologies Supporting Learning", "Learning/Teaching Methodologies and Assessment", "Social Context and Learning Environments", "Domain Applications and Case Studies" and "Ubiquitous Learning". We believe the proceedings, demonstrate new and innovative solutions, and highlight technical problems in each field that are challenging and worthwhile.
CSEDU 2012 received 243 paper submissions from 58 countries in all continents. A double-blind review process was enforced, with the help of the 297 experts who are members of the conference program committee, all of them internationally recognized in one of the main conference topic areas. Only 29 papers were selected to be published and presented as full papers, i.e. completed work (10 pages in proceedings / 30' oral presentations). 73 papers, describing work-in-progress, were selected as short papers for 20' oral presentation. Furthermore 37 papers were presented as posters. The full-paper acceptance ratio was thus 12%, and the total oral paper acceptance ratio was less than 42%. These ratios denote a high level of quality, which we intend to maintain and reinforce in the next edition of this conference.
The high quality of the CSEDU 2012 programme is enhanced by three keynote lectures, delivered by distinguished guests who are renowned experts in their fields, including (alphabetically): Joseph Trimmer (Ball State University, United States), David Kaufman (Simon Fraser University, Canada) and Hugh Davis (University of Southampton, United Kingdom).
For the fourth edition of the conference we extended and ensured appropriate indexing of the proceedings of CSEDU including DBLP, INSPEC, EI and Thomson Reuters Conference Proceedings Citation Index. Besides the proceedings edited by SciTePress, a short list of papers presented at the conference will be selected for publication of extended and revised versions in the Journal of Education and Information Technologies. Furthermore, all presented papers will soon be available at the SciTePress digital library.
The conference is complemented with two special sessions, focusing on specialized aspects of computer supported education; namely, a Special Session on Enhancing Student Engagement in e-Learning (ESEeL 2012) and a Special Session on Serious Games on Computer Science Learning (SGoCSL 2012).
Building an interesting and successful program for the conference required the dedicated effort of many people. Firstly, we must thank the authors, whose research and development efforts are recorded here. Secondly, we thank the members of the program committee and additional reviewers for their diligence and expert reviewing. We also wish to include here a word of appreciation for the excellent organization provided by the conference secretariat, from INSTICC, who have smoothly and efficiently prepared the most appropriate environment for a productive meeting and scientific networking. Last but not least, we thank the invited speakers for their invaluable contribution and for taking the time to synthesize and deliver their talks.