Index Creation Research Articles

EFFECTS OF APPLYING STATISTICAL METHODS IN GLOBAL SUSTAINABLE COMPETITIVENESS INDEX CREATION

Linking the concept of sustainable development, as demanding per capita prosperity does not decline over a long period of time, and the concept of competitiveness, which reflects the level of productivity of national economies, is a new approach to development called sustainable competitiveness. The care for the scarcity of resources and the preservation of their base so that future generations will have the same level of well-being as today's generation have, requires the incorporation of environmental and social issues and problems into the concept of competitiveness. In this way, a new context of competitiveness analysis is introduced and is meeting the challenges of the concept of sustainable development.The methodology of the composite index of sustainable competitiveness was first developed by the World Economic Forum (WEF), followed by organizations such as SolAbility - Sustainable Intelligence. SolAbility methodology of Global Sustainable Competitiveness Index (GSCI) creation is the subject of research in this paper. The aim of research is the proposal of a new methodology for calculating GSCI based on different weights assigned to the pillars included in the Index. The paper concludes that the highest relative importance in the structure of the GSCI belongs to the Intellectual capital dimension. The originality of this work is reflected in the creation of a new ranking of countries in terms of sustainable competitiveness. An analysis of possible changes in the ranking list is a good basis for a new analysis of the sustainable competitiveness of countries, in which some of the professional and statistical rules comments on its calculation methodology are accepted.

199 Beef cattle genetic technology utilization - survey of stakeholders 2018

Abstract A web-based survey was conducted to understand the utilization of digital and genetic information by beef producers to inform the development of an online beef cattle selection decision support tool allowing creation of customized selection indices. Of 1,656 respondents, responses from U.S. seedstock, commercial cow-calf, stocker and feedlot sectors in 43 states formed a subset (n = 1,065) used in this analysis. Of respondents, 89% were owners, 76% and 47% identified involvement in the commercial cow-calf sector and seedstock sector, respectively (responses were permitted for multiple sectors). Respondents averaged 55 years old with 31 years beef industry experience. Percentages with 100 or fewer females for breeding, 100–500 cows, 500–1,000 cows and more than 1,000 cows were 47, 38, 8, and 6%, respectively. Bull purchases per year were 0 (21%), 1–2 (53%), 3–5 (15%), 6–10 (5%), 11–20 (2%), and >20 (2%). Seedstock producers and industry meetings were most frequently cited as good sources of genetics information. Expected progeny differences were the most commonly reported/used source of genetic information. Nearly 70% (57%) reported keeping very or somewhat detailed animal production/performance (cost of production) records. The majority (90%) have a smart phone while only 45% use a tablet/iPad. Most producers (65%) used the internet as a source of agriculture data/information at least daily. Of all respondents, 44% spend 10 hours or more per week on the internet and 59% had greater than DSL speed. Two-thirds correctly identified the definition of a selection index with 80% indicating that selection indexes provide an efficient, consistent and objective method of ranking selection candidates. Nearly 64% would probably or definitely use an online tool to generate customized indexes. Willingness to pay annually for a tool varied with 36% only using it if free/sponsored, 17% would pay $50–99, 14% would pay $100–249, with 3% would pay $500 or more.

Creating small-area deprivation indices: a guide for stages and options

The creation and use of composite indices for capturing various complex or multidimensional concepts (eg, deprivation, geographic access, green space, sustainability, corruption, transparency) has become extremely popular. Measures are created...

About features remote crops of wheat, with use of the UAV, on a condition of a flag leaf

Question of use of local resources for ensuring energy needs and in particular production of biogas remains relevant. Grain crops which condition at initial stages of vegetation is inadmissible for receiving a qualitative harvest can become a prospect of raw materials for creation of biogas. The optimum tool for monitoring of a condition of vegetable cultures is considered UAV which use does not depend on the existence of clouds. The purpose of this research is an assessment by results of the use of the UAV of potential quality of winter wheat in the phrase "exit in a tube" about the expediency of its use for the production of biogas. Measurements of intensity of components of the color of wheat were taken in the conditions of a research hospital, the condition of a flag leaf was estimated visually at land researches. By results of work it was offered the indicator stressful index, it is constructed on the definition of a condition of a flag leaf which is the indicator of the formation of grain yield in wheat. It was shown expediency of account on monitoring of wheat, except the average value of intensity, the brightness of the channel of color and size of semi-distribution. This size can be considered as an additional parameter during the creation of stressful indexes, and also to testify about a condition of transition between stages of growth and development of plants. It is experimentally proved that color portraits of wheat have to be created under concrete stages of organogenesis. Taking into account that the duration of stages is several days, namely the UAV that can directly be used by agricultural producers, is the optimum tool for requirements of exact agriculture.

Progressive indexes

Interactive exploration of large volumes of data is increasingly common, as data scientists attempt to extract interesting information from large opaque data sets. This scenario presents a difficult challenge for traditional database systems, as (1) nothing is known about the query workload in advance, (2) the query workload is constantly changing, and (3) the system must provide interactive responses to the issued queries. This environment is challenging for index creation, as traditional database indexes require upfront creation, hence a priori workload knowledge, to be efficient. In this paper, we introduce Progressive Indexing , a novel performance-driven indexing technique that focuses on automatic index creation while providing interactive response times to incoming queries. Its design allows queries to have a limited budget to spend on index creation. The indexing budget is automatically tuned to each query before query processing. This allows for systems to provide interactive answers to queries during index creation while being robust against various workload patterns and data distributions.

Overrun by averages: An empirical analysis into the consistency of social vulnerability components across multiple scales

Social vulnerability indices have become widely accepted as key elements of disaster risk reduction (DRR) frameworks despite significant conceptual and technical concerns over their creation. Despite increasingly complex theorization, it remains commonplace to determine vulnerability dimensions by applying principal component or factor analysis on aggregated, sub-national level statistical data. The primary focus of this paper is in showing that social vulnerability dimensions derived from aggregate statistics may not be consistent with those derived at the household level. I first provide empirical support for this problem using household level micro-data from Nepal, then illustrate how differences in determined dimensions impact composite index creation at both household and regional levels. I show that qualitative differences in index components are not required to produce large magnitude changes or sign reversals in index scores. These findings raise questions over whether regional vulnerability components can be sufficiently represented with household characteristics. These results reiterate the necessity of addressing issues of scale in the development of empirical social vulnerability indicators.

The role of competitor, stress-tolerant and opportunist species in the development of indexes based on rocky shore assemblages for the assessment of ecological status

Abstract The existence of three different ecological strategies (competitor, stress-tolerant, opportunist) has been widely recognized in the scientific literature and in the development of several biotic indexes using marine macroinvertebrates. However, its use has been totally neglected in the creation of indexes dealing with macroalgal assemblages and developed to fulfill the requirements of the European Water Framework Directive. In this study we apply a new method considering these different ecological strategies to assess the Ecological Status (ES) in rocky shores, which are mostly macroalgal-dominated. We use a large data set consisting of 653 samples collected between 1999 and 2017 in Catalonia (northwestern Mediterranean). In this approach we distinguish four basic strategies (competitor, indifferent, stress-tolerant and opportunist). Our results emphasize the importance in the distinction between competitor and stress-tolerant species when calculating the ES and highlight the importance of good natural history knowledge prior to appropriately assign every species to the proper ecological strategy. On the other hand, the comparison of ES obtained with the application of the new method based on the four strategies and the Ecological Evaluation Index (EEI-c) and R/P ratio Index (R/P rt. I) shows that the combination of eco-physiological traits, morphology and life-history strategies involved in EEI-c and R/P rt. I indices does not work in detecting differences in ES. Finally, if we take into account not only the algae but also the invertebrates that sometimes are dominant organisms in rocky shore assemblages (e.g. mussels), results become more accurate.

Massively Distributed Time Series Indexing and Querying

Indexing is crucial for many data mining tasks that rely on efficient and effective similarity query processing. Consequently, indexing large volumes of time series, along with high performance similarity query processing, have became topics of high interest. For many applications across diverse domains though, the amount of data to be processed might be intractable for a single machine, making existing centralized indexing solutions inefficient. We propose a parallel indexing solution that gracefully scales to billions of time series, and a parallel query processing strategy that, given a batch of queries, efficiently exploits the index. Our experiments, on both synthetic and real world data, illustrate that our index creation algorithm works on four billion time series in less than five hours, while the state of the art centralized algorithms do not scale and have their limit on 1 billion time series, where they need more than five days. Also, our distributed querying algorithm is able to efficiently process millions of queries over collections of billions of time series, thanks to an effective load balancing mechanism.

Historian, Archivist, Bibliographer: P.A. Zaionchkovskij and the Russian State Library

At present, when the majority of users in search for information excessively turn to the Internet as a primary data source, the problem of reliability of the obtained data is particularly acute. Libraries, whose main function is to store and provide access to information existing both in print and electronic forms, traditionally tend to maintain the exceptional level of completeness and validity of the data and sources provided. One of the ways to achieve such reliability is interaction of libraries with scientists in the field of data systematization, verification, storage and access providing. The article analyses the scientific work of the outstanding Russian historian P.A. Zaionchkovskij in the V.I. Lenin State Library of the USSR (now — the Russian State Library, RSL) and considers his scientific cooperaction with the Library for several decades as a successful example of library-scientists’ partnership. In 1944—1952, he served as the Head of the Department of manuscripts of the V.I. Lenin State Library. Under his supervision, the accounting of the Department’s stock was reorganized, preservation of the existing and newly acquired collections was ensured; the user access of researches to the information on the collections’ content and composition was significantly improved; the unique team of scientific personnel was formed. The article gives thorough overview of the scientific and publication activity of the Department during that period. The authors also review the contribution of P.A. Zaionchkovskij to the development of the problem of bibliographic providing for historical science. In the 1960s — 1980s, under his scientific supervision, the bibliographic staff of the V.I. Lenin State Library of the USSR and other major Russian libraries prepared the unique publications — “Reference Books on the History of Pre-revolutionary Russia” and multivolume annotated Index “The History of Pre-revolutionary Russia in Diaries and Memoirs”. P.A. Zaionchkovskij laid the foundation for the lasting many years and still developing project on creation of retrospective scientific auxiliary indices of memoir literature. The partnership of P.A. Zaionchkovskij and the V.I. Lenin State Library is an excellent example of the successful and fruitful interaction of scientists and library staff.

Governance through shame and aspiration: Index creation and corporate behavior

After decades of de-prioritizing shareholders’ economic interests and low corporate profitability, Japan introduced the JPX-Nikkei400 in 2014. The index highlighted the country’s “best-run” companies by annually selecting the 400 most profitable of its large and liquid firms. We find that managers competed for inclusion in the index by significantly increasing return on equity (ROE), and they did so at least in part due to their reputational or status concerns. The ROE increase was predominantly driven by improvements in margins, which were in turn partially driven by cutting research and development (R&D) intensity. Our findings suggest that indexes can affect managerial behavior through reputational or status incentives.

The risk and return of private equity real estate funds

This study employs an asset pricing approach to quantify the exposure of private real estate funds to both private and publicly traded real estate risk factors. The analysis includes the creation of specific performance indices and the use of methods seeking to address some of the inherent issues with private real estate fund data, such as the high degree of serial correlation in observed total returns. The use of the Driessen et al. (2012) estimator leads to markedly higher risk factor coefficient estimates than seen in the prior literature and estimated with time series regression.

Comparing index-based vulnerability assessments in the Mississippi Delta: Implications of contrasting theories, indicators, and aggregation methodologies

There are many index-based approaches for assessing vulnerability to socio-natural hazards with differences in underlying theory, indicator selection and aggregation methodology. Spatially explicit output scores depend on these characteristics and contrasting approaches can therefore lead to very different policy implications. These discrepancies call for more critical reflection on index design and utility, a discussion that has not kept pace with the impetus for vulnerability assessments and respective index creation and application following the Hyogo Framework for Action 2005–2015. Comparing index outputs is an effective approach in this regard. Here, the Social Vulnerability Index (SoVI®) and the vulnerability component of the Global Delta Risk Index (GDRI) are applied at census tract level in the Mississippi Delta and visually and quantitatively compared. While the SoVI® is grounded in the hazard/risk research paradigm with primarily socio-economic indicators and an inductive principal component methodology, the GDRI incorporates advancements from sustainability science with ecosystem-based indicators and a modular hierarchical design. Maps, class rank changes, and correlations are used to assess the convergence and divergence of these indexes across the delta. Results show that while very different theoretical frameworks influence scores through indicator selection, methodology of index calculation has an even greater effect on output. Within aggregative methodology, the treatment of inter-indicator correlation is decisive. Implications include the need for an increased focus on index methodology and validation of results, transparency, and critical reflection regarding assessment limitations, as our results imply that contradictory risk reduction policies could be considered depending on the assessment methodology used.

Increase the effectiveness of search databases queries using the algorithm of bitmap scales

Query optimization is an important part of any database application. The most effective method of an acceleration of search queries is use of index structures. It is known that queries which use the indexes (clustered and not clustered) are effective in the case of low percent of the repeating values in columns. If indexable data are not selective, use of the majority of types of indexes is not effective. Main objective of the performed work is extending of SQL Server MS for creation of indexes and increase in productivity of search queries. In the furtherance of this goal the high level language Net-application using C# is created. Embedded algorithm creates a bit scales for processing of relational tables columns with a large count of the duplicated values. In article it was conducted the review of the main existing methods of search query efficiency increasing and types of the index structures used in different database management systems. Examples of action of application for selection of values with use of bit indexes are shown. Testing of the created software product on tables with different cardinality allows to draw conclusions about the considerable abbreviation of time of data handling in case of using of bit indexes in comparison with other search algorithms.

A Multi-Keyword Ranked Search Method On Encrypted Data Using Symmetric Encryption Over Cloud

Data security and privacy have grown to be key concerns as cloud computing usage increases. It is difficult to do effective keyword-based searches on encrypted data kept in the cloud due to the inherent tension between searchability and confidentiality. This study suggests a brand-new multi-keyword ranked search methodology that permits effective searching on material that has been encrypted with symmetric encryption methods. The suggested approach guarantees data privacy while enabling users to get appropriate search results based on a variety of terms. To protect data privacy and accomplish effective search operations, the method makes use of secure encryption techniques and index creation methods. Experimental findings show that the suggested strategy is successful and efficient.

Sustainable development from millennium 2015 to Sustainable Development Goals 2030

AbstractIn modern economies, the advancement of well‐being of the citizens should be in an inclusive and sustainable way. In this respect, the sustainable welfare targets should exclusively include three main pillars: economic growth, social inclusion, and environmental protection. These pillars consist of qualitative and nonmonetary, as well as monetary and quantitative indicators to monitor. Although sustainable development today is well‐appreciated in most governments' agenda, yet it is generally not a trivial task to measure its progress especially due to multidimensional nature of some targets. In this article, sustainable development is measured by using a wide range of indicators within multidimensional perspective of Millennium Development Goals (MDGs) 2015. Indicators cover wide spectrum of areas such as poverty reduction, health, education, gender equality, and environment. An index creation method is developed for measuring the level and the performance of countries' progress through achieving MDGs. The index score levels and the rankings of countries are compared with similar indexes developed by United Nations. Finally, countries are classified according to their achievements relative to other countries (which is measured by the index) versus their self‐achievement performances (in terms of improvement of the index over years) in a big matrix. Results demonstrate the importance of measuring country performances in both dimensions. Understanding the progress in MDGs can help settle on binding targets for achieving the country specific goals in economic and noneconomic areas and on the mechanisms to implement the Sustainable Development Goals (SDGs) of the 2030, which set amid on the success of MDGs.

Enhanced Security for Dynamic Multi Keyword Ranked Search Using Greedy Best First Search

Today, due to the enormous growth of data technology in cloud computing, the data owners are stimulated to outsource their data in data management to reduce cost and for the convenient. Data confidentiality, in general, can be obtained by encrypting the data before it is outsourced. The client stores the encrypted data to the cloud using Searchable encryption schemes and applies keyword search techniques over cipher text domain. But the main problem in outsourcing is the lack of security and privacy for the sensitive data. So, to overcome this, for privacy requirement, the sensitive data can be encrypted before it is outsourced. Various methods were proposed to preserve the privacy and to provide security to the cloud data which are encrypted. Here in this paper, we proposed a tree-based search method over the encrypted datain the cloud that supports dynamic operation and multi-keyword ranked search. Clearly, the commonly used “inverse document frequency (IDF) term frequency (TF)” model and the vector space method are joined in the query generation and index creation to give multi-keyword ranked search. To get high search efficiency, a tree-type index structure, “Greedy Best-first Search” algorithm is proposed based on the tree- index.

A Comparison of Different Reconstruction Modes and Adaptive Evaluation Systems for Community Recovery Following the Wenchuan Earthquake

Living environment reconstruction in Wenchuan earthquake disaster-hit areas received substantial attention internationally, so it is imperative to examine out the methods employed, to evaluate community reconstruction and recovery performances. However, the existing evaluation systems for post-disaster reconstruction practices are mostly generalized models, and thus, the actual differences among various reconstruction modes and local characteristics are given insufficient attention. After 10 years of reconstruction and recovery, Dujiangyan, Beichuan, and Wenchuan have exhibited distinct differences and characteristics because of two different reconstruction modes: “paired assistance” and “self-construction”. Based on a thorough review of the literature and expert judgments, this article focuses on the introduction of evaluation factors comprising the opinions and requirements of disaster victims. Adopting the “four-step method” to select the evaluation factors through conceptual consolidation, analytical structuring, indicator identification, and index creation, this article summarizes the homogeneities and heterogeneities of the three different areas. The results reveal that people in different areas under the influences of different reconstruction modes and local characteristics will emphasize different evaluation factors and demonstrate different levels of concern for the same factor. This article analyzes the three areas and establishes an adaptable evaluation index system to provide scientific guidance to community recovery evaluations in different areas after major disasters.

A novel method for parallel indexing of real time geospatial big data generated by IoT devices

IoT produces a huge amount of big data as it comprises billions of devices that are interconnected with each other through internet. Today’s majority of the big data part is about geospatial data and every year it increases rapidly. In order to process such massive real time geospatial big data, we must have scalable, efficient indexing method. R Tree and its variants have emerged as most efficient, widely accepted and have adopted indexing method for the management and processing of geospatial data. Current literature on parallel construction of R Tree indexes of geospatial data has disadvantages, that all the methods considered only two dimensional geospatial data and all are based on MapReduce framework. As the number of dimension increases, complexity of index creation is also increases along with this MapReduce framework has lots of disadvantages such as, it works only on static data, consumes a lot of disk space and time, which leads to high latency and fault tolerance of the entire system. In order to overcome these issues, a novel method for parallel construction of R Tree and its variants, use of the Apache Spark (in-memory and on-disk computation) based on the IoT Zetta platform is proposed. The main purpose of using Apache Spark is to index real time geospatial data for continuously updating the position of aircraft in real time while indexing it in R tree and its variants, so that spatial range query can fetch real time results and Apache Spark is much faster as compared to MapReduce framework. The extensive experimental results show that our parallel generated R tree and its variants retains similar properties as of sequential generated R tree and its variants with the excellent scalability and reducing a significant amount of time for the construction of index, index updating & executing spatial range query over geospatial data by exploiting the latest parallelism framework.

Index Self-tuning with Agent-based Databases


 
 
 The use of software agents as Database Management System components lead to database systems that may be configured and extended to support new requirements. We focus here with the self-tuning feature, which demands a somewhat intelligent behavior that agents could add to traditional DBMS modules. We propose in this paper an agent-based database architecture to deal with automatic index creation. Implementation issues are also discussed, for a built-in agents and DBMS integration architecture.
 
 

Current System of National Bibliographic Resources of the Sakha Republic (Yakutia)

The current state of the national bibliography in the Republic of Sakha (Yakutia), worked out in 2000—2017, is analysed. The main types of national bibliographic indexes — current and retrospective — are considered. The author describes the existing system of national bibliographic resources, its methodological, organizational and technological development. It is noted that currently there are determined the bibliographing centers of the Republic — the main participants in the creation of national bibliographic indexes. The author reveals the specific features of the development of the modern national bibliography of Yakutia in the main areas: state (current national) bibliographic control of the legal deposit copy of documents of the Republic of Sakha (Yakutia); development of the retrospective national bibliographic repertoires. The emphasis is made on the activities of the National Library of the Republic of Sakha (Yakutia), which processes all national and regional documents published in the Republic and beyond its borders. The current organizational structure is analysed, considering seventeen-year experience of formation of the system of national bibliography, creation of the National Bibliographing Agency and resumption of issue of State Bibliography Indexes. There are described the materials of the long-term plan for creation of system of retrospective national bibliography of the Republic of Sakha (Yakutia) for the period up to 2020, which regulates the development and defines the main organizational activities for its formation, as well as contains information about specific projects. There are characterized the key National Retrospective Indexes: “Bibliography of the Bibliography of Yakutia (1838—2000)”, “Yakut Book (1917—1957)”, “Union Catalogue of the Yakut Books (1812—1917)”, “Books in the Languages of the Indigenous Minorities of the Sakha Republic (Yakutia)”, “Book Culture of the Evens”, “Book Culture of the Evenks”. The results of development and the features of the modern system of national bibliographic resources of the Republic of Sakha (Yakutia) are presented.