Semi-supervised Gaussian process latent variable model with pairwise constraints

In machine learning, Gaussian process latent variable model (GP-LVM) has been extensively applied in the field of unsupervised dimensionality reduction. When some supervised information, e.g., pairwise constraints or labels of the data, is available, the traditional GP-LVM cannot directly utilize such supervised information to improve the performance of dimensionality reduction. In this case, it is necessary to modify the traditional GP-LVM to make it capable of handing the supervised or semi-supervised learning tasks. For this purpose, we propose a new semi-supervised GP-LVM framework under the pairwise constraints. Through transferring the pairwise constraints in the observed space to the latent space, the constrained priori information on the latent variables can be obtained. Under this constrained priori, the latent variables are optimized by the maximum a posteriori (MAP) algorithm. The effectiveness of the proposed algorithm is demonstrated with experiments on a variety of data sets. © 2010 Elsevier B.V.

Fiscal Divergence and Business Cycle Synchronization: Irresponsibility is Idiosyncratic

Using a panel of 21 OECD countries and 40 years of annual data, we find that countries with similar government budget positions tend to have business cycles that fluctuate more closely. That is, fiscal convergence (in the form of persistently similar ratios of government surplus/deficit to GDP) is systematically associated with more synchronized business cycles. We also find evidence that reduced fiscal deficits increase business cycle synchronization. The Maastricht "convergence criteria," used to determine eligibility for EMU, encouraged fiscal convergence and deficit reduction. They may thus have indirectly moved Europe closer to an optimum currency area, by reducing countries’ abilities to create idiosyncratic fiscal shocks. Our empirical results are economically and statistically significant, and robust.

A fiskális divergencia és a konjunktúraciklusok együttmozgása - a felelőtlen fiskális politika az aszimmetrikus sokkok forrása (Fiscal divergence and business cycle synchronization: irresponsibility is idiosyncratic)

A világ 115 országának - köztük 21 OECD-tagország - 40 évnyi adatait vizsgálva, arra a következtetésre jutottunk, hogy a hasonló állami költségvetési pozíciójú országok konjunktúraciklusai között szorosabb együttmozgás mutatható ki. Azaz, a fiskális konvergenciát (amelyet a költségvetési egyenleg GDP-hez viszonyt arányának konvergenciájaként definiáltunk) összehangoltabb konjunktúraciklusokkal lehet összefüggésbe hozni. Kutatásaink során arra is találtunk bizonyítékot, hogy a kisebb mértékű költségvetési deficitek növelik a konjunktúraciklusok együttmozgását. A maastrichti konvergenciakritériumok - amelyek az európai monetáris unió követelményeinek való megfelelést hivatottak meghatározni - a fiskális konvergenciát és a költségvetési deficit csökkentését ösztönözték, s ezzel közvetett módon hozzásegítették Európát egy optimális valutaövezet létrehozásához azáltal, hogy csökkent az egyes országok lehetősége a felelőtlen fiskális politika által gerjesztett sokkhatások létrehozására. Az általunk feltárt empirikus eredmények gazdasági és statisztikai szempontból is szignifikánsak és robusztusak. _____ Using panels of 115 countries of world – including 21 OECD countries – and 40 years of annual data, the authors find that countries with similar government budget positions tend to have business cycles that fluctuate more closely. Thus fiscal convergence (in the form of persistently similar ratios of government surplus/deficit to GDP) is systemati-cally associated with more strongly synchronized business cycles. Evidence is also found that reduced fiscal deficits increase business-cycle synchronization. The Maastricht "con-vergence criteria", used to determine eligibility for EMU, encouraged fiscal convergence and deficit reduction. So they may, indirectly, have moved Europe closer to an optimum currency area, by reducing countries abilities to create idiosyncratic fiscal shocks. The empirical results of the study are economically and statistically significant, and robust.

Factors that motivate RNs to return to school for the BSN and to remain in school to complete the degree

This exploratory descriptive study examined the factors that influence Registered Nurses (RNs) to return to school to pursue a Baccalaureate of Science in Nursing degree (BSN) and the factors that contribute to the decision to remain in school to complete the degree. Students (N = 226) enrolled in RN-BSN programs in three different universities in southeast Florida participated in the study by completing researcher developed questionnaires. The study group included 140 students who were newly enrolled in an RN-BSN program and 86 students who were preparing to graduate from an RN-BSN program. The instruments used in this study were two researcher developed questionnaires, the Corbett Nursing Educational Motivational Inventory - Form A (CNEMI-A), administered to the newly enrolled students, and the Corbett Nursing Educational Motivational Inventory - Form B (CNEMI-B), administered to the graduating students. The questionnaires included researcher-developed items in addition to items derived from a modified form of the Educational Participation Scale used by other researchers. Demographic data were also collected. Findings indicated that changes in health care, career goals, personal satisfaction, and flexible curriculum patterns are the major reasons why RNs return to school for the BSN. Less significant factors were social support, salary increase, and employer expectations. The factors considered most significant in the decision to remain in school to complete the degree were ranked in the following order: personal achievement, changes in health care, career change/advancement, enrollment options, faculty support, social support, and employer support. Implications for nurse educators related to the changing roles of RNs and the need to continue to assist RNs to adapt to new roles in health care. Recommendations for future research on RN-BSN nursing education included studies to identify the courses considered most useful by RN-BSN students as compared to courses considered repetitive of basic nursing programs. Studies were also recommended to examine the differences between the needs of RNs related to experience as an RN and recency of education. Additional studies were recommended to determine the feasibility of dual-enrollment ADN/BSN programs for last semester ADN students. ^

Integration and querying of heterogeneous, autonomous, distributed database systems

Today, databases have become an integral part of information systems. In the past two decades, we have seen different database systems being developed independently and used in different applications domains. Today's interconnected networks and advanced applications, such as data warehousing, data mining & knowledge discovery and intelligent data access to information on the Web, have created a need for integrated access to such heterogeneous, autonomous, distributed database systems. Heterogeneous/multidatabase research has focused on this issue resulting in many different approaches. However, a single, generally accepted methodology in academia or industry has not emerged providing ubiquitous intelligent data access from heterogeneous, autonomous, distributed information sources. ^ This thesis describes a heterogeneous database system being developed at High-performance Database Research Center (HPDRC). A major impediment to ubiquitous deployment of multidatabase technology is the difficulty in resolving semantic heterogeneity. That is, identifying related information sources for integration and querying purposes. Our approach considers the semantics of the meta-data constructs in resolving this issue. The major contributions of the thesis work include: (i) providing a scalable, easy-to-implement architecture for developing a heterogeneous multidatabase system, utilizing Semantic Binary Object-oriented Data Model (Sem-ODM) and Semantic SQL query language to capture the semantics of the data sources being integrated and to provide an easy-to-use query facility; (ii) a methodology for semantic heterogeneity resolution by investigating into the extents of the meta-data constructs of component schemas. This methodology is shown to be correct, complete and unambiguous; (iii) a semi-automated technique for identifying semantic relations, which is the basis of semantic knowledge for integration and querying, using shared ontologies for context-mediation; (iv) resolutions for schematic conflicts and a language for defining global views from a set of component Sem-ODM schemas; (v) design of a knowledge base for storing and manipulating meta-data and knowledge acquired during the integration process. This knowledge base acts as the interface between integration and query processing modules; (vi) techniques for Semantic SQL query processing and optimization based on semantic knowledge in a heterogeneous database environment; and (vii) a framework for intelligent computing and communication on the Internet applying the concepts of our work. ^