Performance measurement with fuzzy data envelopment analysis

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

Grid Infrastructure for Satellite Data Processing in Ukraine

In this paper conceptual foundations for the development of Grid systems that aimed for satellite data processing are discussed. The state of the art of development of such Grid systems is analyzed, and a model of Grid system for satellite data processing is proposed. An experience obtained within the development of the Grid system for satellite data processing in the Space Research Institute of NASU-NSAU is discussed.

Ontological Presentation of East-Christian Iconographical Art Domain

In the recent years the East-Christian iconographical art works have been digitized providing a large volume of data. The need for effective classification, indexing and retrieval of iconography repositories was the motivation of the design and development of a systemized ontological structure for description of iconographical art objects. This paper presents the ontology of the East-Christian iconographical art, developed to provide content annotation in the Virtual encyclopedia of Bulgarian iconography multimedia digital library. The ontology’s main classes, relations, facts, rules, and problems appearing during the design and development are described. The paper also presents an application of the ontology for learning analysis on an iconography domain implemented during the SINUS project “Semantic Technologies for Web Services and Technology Enhanced Learning”.

Large-scale data for multiple-view stereopsis

The seminal multiple-view stereo benchmark evaluations from Middlebury and by Strecha et al. have played a major role in propelling the development of multi-view stereopsis (MVS) methodology. The somewhat small size and variability of these data sets, however, limit their scope and the conclusions that can be derived from them. To facilitate further development within MVS, we here present a new and varied data set consisting of 80 scenes, seen from 49 or 64 accurate camera positions. This is accompanied by accurate structured light scans for reference and evaluation. In addition all images are taken under seven different lighting conditions. As a benchmark and to validate the use of our data set for obtaining reasonable and statistically significant findings about MVS, we have applied the three state-of-the-art MVS algorithms by Campbell et al., Furukawa et al., and Tola et al. to the data set. To do this we have extended the evaluation protocol from the Middlebury evaluation, necessitated by the more complex geometry of some of our scenes. The data set and accompanying evaluation framework are made freely available online. Based on this evaluation, we are able to observe several characteristics of state-of-the-art MVS, e.g. that there is a tradeoff between the quality of the reconstructed 3D points (accuracy) and how much of an object’s surface is captured (completeness). Also, several issues that we hypothesized would challenge MVS, such as specularities and changing lighting conditions did not pose serious problems. Our study finds that the two most pressing issues for MVS are lack of texture and meshing (forming 3D points into closed triangulated surfaces).

Decision support based on genomics:integration of data-and knowledge-driven reasoning

The breadth and depth of available clinico-genomic information, present an enormous opportunity for improving our ability to study disease mechanisms and meet the individualised medicine needs. A difficulty occurs when the results are to be transferred 'from bench to bedside'. Diversity of methods is one of the causes, but the most critical one relates to our inability to share and jointly exploit data and tools. This paper presents a perspective on current state-of-the-art in the analysis of clinico-genomic data and its relevance to medical decision support. It is an attempt to investigate the issues related to data and knowledge integration. Copyright © 2010 Inderscience Enterprises Ltd.

A generalized multidimensional index structure for multimedia data to support content-based similarity searches in a collaborative search environment

Since multimedia data, such as images and videos, are way more expressive and informative than ordinary text-based data, people find it more attractive to communicate and express with them. Additionally, with the rising popularity of social networking tools such as Facebook and Twitter, multimedia information retrieval can no longer be considered a solitary task. Rather, people constantly collaborate with one another while searching and retrieving information. But the very cause of the popularity of multimedia data, the huge and different types of information a single data object can carry, makes their management a challenging task. Multimedia data is commonly represented as multidimensional feature vectors and carry high-level semantic information. These two characteristics make them very different from traditional alpha-numeric data. Thus, to try to manage them with frameworks and rationales designed for primitive alpha-numeric data, will be inefficient. An index structure is the backbone of any database management system. It has been seen that index structures present in existing relational database management frameworks cannot handle multimedia data effectively. Thus, in this dissertation, a generalized multidimensional index structure is proposed which accommodates the atypical multidimensional representation and the semantic information carried by different multimedia data seamlessly from within one single framework. Additionally, the dissertation investigates the evolving relationships among multimedia data in a collaborative environment and how such information can help to customize the design of the proposed index structure, when it is used to manage multimedia data in a shared environment. Extensive experiments were conducted to present the usability and better performance of the proposed framework over current state-of-art approaches.

The Influence of Psychological Predictors and Cognitive Behavioral Stress Management Intervention on Antiretroviral Therapy (ART) Adherence Among HIV-Positive Female Haitian Alcohol Users

Purpose: Over half the HIV-infected persons in the Caribbean, the second most HIV-impacted region in the world, live in Haiti. Using secondary data from a parent study, this research assessed the effects of psychological and social factors on antiretroviral therapy (ART) adherence among Haitian, HIV-positive, female alcohol users. Theoretical Foundation and Research Questions: Using the Theory of Planned Behavior/Reasoned Action and the Information, Motivation, Behavior skills model as guiding theoretical frameworks, the study examined the effectiveness of an adapted cognitive behavioral stress management (CBSM-A) intervention in improving ART adherence. The effect of psychological factors (depression, anxiety, beliefs about medicine, and social support), social factors (stigma, relationship status, and educational attainment), and alcohol on adherence to ART was assessed. Methods: The sample consisted of 116 female ART patients who were randomly assigned to the CBSM-A intervention or the wait-list control group. Participants completed intervention sessions as well as pre- and post-test assessments. Analyses of variance, t-tests, and point biserial correlations were used to test hypotheses. Results: Surprisingly, ART adherence rates significantly decreased for both groups combined [F (1, 108) = 8.79, p = .004]; there was no significant difference between the intervention and control groups with regard to the magnitude of change between baseline and post assessment. On average, depression decreased significantly among participants in the CBSM-A group only [(t (62) = 5.54, p < .001)]. For both groups combined, alcohol use significantly decreased between baseline and post-assessment [(F (1, 78) = 34.70, p < .001)]; there was no significant difference between the intervention and control groups with regard to the magnitude of change between baseline and post-assessment. None of the variables were significantly correlated with ART adherence. Discussion: Adherence to ART did not improve in this sample, nor were any of the variables significantly associated with adherence. The findings suggest that additional supportive and psychological services may be needed in order to promote higher adherence to ART among HIV-positive females. More research may be needed on this sample; a focus on mental health issues, partner conflict, family and sexual history may allow for better targeting and more successful interventions.

Navigation and meteorological data during campaign TARA_20110826Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20110928Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20110626Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20110716Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20101126Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20100410Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20100508Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20091004Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.