Construction Of Index Research Articles

Aiding secure data retrieval incorporated with parallelization technique in cloud

<p>Cloud data owners prefer to outsource data because of ease in maintenance. Data confidentiality of this outsourced sensitive data is a major task. The searchable encryption technique helps to carry out searches on encrypted data without decrypting it. In the data outsourcing environment, volume of data is increasing rapidly. Hence the time required to build the index and to carry out searches is also increasing exponentially. This makes it more difficult to build a system which is efficient, reliable and can cope up with growing data. In this paper, a parallelization technique to build the index on outsourced data is proposed. This technique minimizes the time required to construct the index. It also supports secure ranked retrieval using bucketization technique. The buckets are formed using Hadoop map reduce framework which achieves significant efficiency. The proposed method prune the keyword dataset, which helps in significant reduction in the size of index. Through extensive experiments using standard dataset, the performance of the system is validated. The experimental results show that the proposed system requires less time for index construction and hence improves retrieval efficiency.</p>

A flexible method of housing price index construction using repeat‐sales aggregates

AbstractThe major issue which we address in this article is the one‐size‐fits‐all nature of the typical city‐level housing price index. In this vein, we make two contributions. First, we develop a new algorithm to ensure feasible estimation of geographically granular repeat‐sales price indices in cases of low transactions counts. This facilitates the estimation of a balanced panel of 63,084 U.S. Census tract‐level indices (2010 definitions) at an annual frequency between 1989 and 2021, which we release alongside this article. Second, we use these indices to estimate city‐level price indices that are robust to heterogeneous submarket appreciation and nonrandom sampling, two issues that confound classic approaches. Different index targets require alternative weighting schemes, and these formulations can result in index differences that can widen over time horizons. However, in some cases, sample‐based indices are quite similar to more strictly defined index targets; for instance, in the early COVID‐19 period, standard sample‐based indices are actually quite similar to a unit‐representative house price index for large cities.

Index construction and application of digital transformation in the insurance industry: Evidence from China.

In the context of digitization, the insurance industry's value chain is undergoing significant shifts. However, the existing research on its comprehension and measurement remains relatively limited. This study constructs an index system for digital transformation in the insurance industry (DTII) on three components: digital infrastructure, digital platform, and digital applications. Utilizing data from 31 provinces in China, this study employs the entropy weight method, analytic hierarchy process method and minimum relative entropy method to measure the weights of indicators, empirically applying this index system. The results show that DTII in China experiences rapid advancement with an average annual growth rate of 20.46% from 2014 to 2020 and there exists strong regional convergence. In addition, the spatial agglomeration and spatial effects of DTII are mainly concentrated in the life insurance industry and the eastern region. This study provides an index system and empirical evidence for evaluating the DTII, providing policy insights for exploring the sustainable development path of the insurance industry in the digital era.

Multi-working condition performance assessment based on knowledge extraction of optimal operating states for continuous annealing processes

Performance assessment is a key to strip quality improvement and energy consumption reduction of Continuous Annealing Processes (CAP). However, existing methods focus on performing the assessment under a single working condition, and the assessment accuracy must be improved. This study proposes a new multi-working-condition performance assessment method based on the knowledge extraction of the optimal operating states for CAP. First, a mechanism–data fusion-based assessment index construction method is proposed for the key parameter selection. Second, a knowledge extraction strategy for the optimal operating states under multiple working conditions is proposed to construct a benchmark library. Third, a knowledge-enhanced assessment model is built to achieve qualitative performance evaluation and quantitative non-optimal traceability. The experiment based on the process data shows the effectiveness of assessing the operating performance, providing decision guidance for strip quality improvement and energy consumption reduction.

An empirical approach and practical framework for a decentralized Ethereum Ecosystem Index (EEI).

Stock market indices are pivotal tools for establishing market benchmarks, enabling investors to navigate risk and volatility while capitalizing on the stock market's prospects through index funds. For participants in decentralized finance (DeFi), the formulation of a token index emerges as a vital resource. Nevertheless, this endeavor is complex, encompassing challenges such as transaction fees and the variable availability of tokens, attributed to their brief history or limited liquidity. This research introduces an index tailored for the Ethereum ecosystem, the leading smart contract platform, and conducts a comparative analysis of capitalization-weighted (CW) and equal-weighted (EW) index performances. The article delineates exhaustive criteria for token eligibility, intending to serve as a comprehensive guide for fellow researchers. The results indicate a consistent superior performance of CW indices over EW indices in terms of return and risk metrics, with a 30-constituent CW index outshining its counterparts with varied constituent numbers. The recommended CW30 index demonstrates substantial advantages in comparison to established benchmarks, including prominent indices like DeFi Pulse Index (DPI) and CRypto IndeX (CRIX). Additionally, the article explores the practicality of implementing the CW30 in Layer 2 networks of the Ethereum Ecosystem, advocating for the Arbitrum infrastructure as the optimal choice for the decentralized crypto index protocol herein referred to as the Ethereum Ecosystem Index (EEI). The study's insights aspire to enrich the DeFi ecosystem, offering a nuanced understanding of network selection and a strategic framework for implementation. This research significantly enhances the existing literature on index construction and performance within the Ethereum ecosystem. To our knowledge, it represents a pioneering comprehensive analysis of an index that accurately mirrors the Ethereum market, advancing our comprehension of its intricacies and wider ramifications. Moreover, this study stands as one of the initial thorough examinations of index construction methodologies within the nascent asset class of crypto. The insights gleaned provide a pragmatic approach to index construction and introduce an index poised to serve as a benchmark for index products. In illuminating the unique facets of the Ethereum ecosystem, this research makes a substantial contribution to the current discourse on crypto, offering valuable perspectives for investors, market stakeholders, and the ongoing exploration of digital assets.

Measurement of China-ASEAN Financial Cooperation: Index Construction and Characteristic Analysis

Measurement of China-ASEAN Financial Cooperation: Index Construction and Characteristic Analysis

Text Mining and Index Construction: Insights into Digital Transformation in Banking Industry

Text Mining and Index Construction: Insights into Digital Transformation in Banking Industry

Construction of a Comprehensive Energy Price Index for Prefecture-level Cities: The Case of Shanxi Province

Construction of a Comprehensive Energy Price Index for Prefecture-level Cities: The Case of Shanxi Province

Construction of Financial Inclusion Index for Micro, Small, and Medium-Sized Enterprises (MSMEs) in Malaysia

This study intends to develop a new index for assessing the financial inclusion of the Micro, Small, and Medium-sized Enterprises (MSMEs) in Malaysia. The index includes two important dimensions, namely digital financial technology (fintech) and digital financial literacy, using survey data from selected MSMEs in Malaysia for 2023. A total of 177 firms are voluntarily participated in the study, which were recruited based on the purposive sampling technique’s non-probability. This study employed non-parametric approaches using a multidimensional measurement model with Principal Component Analysis (PCA) as a parametric way to assess the index of financial inclusion. The main findings revealed that fintech dimensions and digital financial literacy possess a relative relevance and a substantial association with the level of financial inclusion. The study indicates that a higher index value signifies greater financial inclusion for firms, but a lower index value denotes the opposite. The implication from this study suggest that Malaysian policymakers must formulate policies and strategies pertinent to financial inclusion for MSMEs. Furthermore, the accessibility of digital financial technology services and digital financial literacy must be enhanced to elevate the financial inclusivity of firms.

The Construction and Concept Validation of Indian Financial Market Composite Risk Index (IFM: CRI): A Vibrant Risk Indicator to Retail Investors

The financial market volatility has been a major interest to all the stakeholders of the market especially to the retail investors post 2020. In this backdrop, the study is focused on constructing a Composite Risk Index (CRI) for the Indian Financial Market and examining the various methods of weighting as well as types of volatility capture in the construction of the Financial Market Composite Risk Index. The study intends on giving its contribution on the methodological portion of the derivation of appropriate weights to each segment of financial market. The study is based on the daily price series from 1st January 2020 to 31st March 2023. The research develops nine (09) different Composite Risk Index based on the types of volatility capture [Standard Deviation (SD), Autoregressive Conditional Heteroskedastic (ARCH), Generalised Autoregressive Conditional Heteroskedastic (GARCH)] and method of deriving the weights [Principal Component Analysis (PCA), Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA)] of various sub markets [ Equity, Commodity and Forex] and its segments [Spot and Derivatives]. The inter and intra evaluation of nine CRI are carried out with the help of nonparametric statistical tool Kruskal Wallis Test, further the pairwise comparation is also preformed to analyze the homogeneity between the types of volatility capture and method of deriving the weights. The results reveal that, GARCH based DEA Composite Risk Index is better exhibiting the volatility of the Indian Financial Markets compared to their counterpart CRI and also having a high co-movement with India VIX.

Pobreza multidimensional no Brasil: evidências para as áreas rurais e urbanas

Abstract This paper studied the behavior of multidimensional and income poverty, as well as its determinants in Brazil, in addition to rural and urban areas, based on information from the 2019 National Continuous Household Sample Survey (PNADC). The Alkire-Foster methodology was used in the construction of a Multidimensional Poverty Index (MPI), in addition to the logit model to estimate the impacts of determinants related to household characteristics on poverty. The health and sanitation dimension was the one that contributed the most to the MPI, followed by the education and housing dimensions. Unidimensional poverty was greater than multidimensional and rural poverty was also greater. Among the determinants of poverty, being in households with non-white heads, younger, unmarried, unemployed, less educated and in the North and Northeast regions increased the chances of poverty. In addition, while female heads reduced the chances of multidimensional poverty, it increased the chances of the unidimensional one.

Construction of Cross-Border E-Commerce Compliance Talent Capability Index Based on Competency Model

Construction of Cross-Border E-Commerce Compliance Talent Capability Index Based on Competency Model

Construction of Entrepreneurship Coaching Index: Based on a Survey of Art Design Students in Higher Vocational Colleges in Guangdong, China

Construction of Entrepreneurship Coaching Index: Based on a Survey of Art Design Students in Higher Vocational Colleges in Guangdong, China

QUALITY ASSESSMENT IN HIGHER EDUCATION USING A COMPOSITE INDEX. EMPIRICAL EVIDENCE FOR CENTRAL AND EASTERN EU COUNTRIES

Post-secondary education requires a complex organisational structure of higher education institutions, staff and infrastructure. The construction of a comprehensive quality index is necessary to assess the quality of higher education and to improve the higher education system in a country. It is imperative that administrators remain informed about the current state of the system through regular and realistic assessments. Therefore, this study has constructed a composite index to assess the quality of higher education. The quality of higher education in Central and Eastern Europe is analysed using 13 indicators from 11 countries with higher education institutions. Extraction of factor coefficient score matrices was performed by downgrading these indicators using principal component analysis (PCA). Using PCA, two principal components were extracted for analysis and the PCA weighting method was used to determine the importance of each indicator by dual-indicator. Each institution's research activity and the internationalization of higher education were included in this method to determine the efforts made by these institutions. Through the study we observed the differences between the eleven countries in terms of higher education and the importance of each measurement dimension used. These findings can be used to compare the current situation in each country and to find directions for development.

Construction of Directional Volatility Index

Construction of Directional Volatility Index

Construction of a climate risk index under the media attention perspective and its empirical test for financial market volatility

Under the current economic situation, China’s economy is steadily moving from the stage of high-speed growth to that of high-quality development. while climate risks arising from global warming are receiving increasing media attention. Media attention has a profound impact on the perception and investment decisions of financial market participants. This paper constructs a climate risk index based on media attention and empirically investigates its relationship with stock volatility. It is found that the climate risk media index significantly affects stock volatility, which provides a theoretical basis for the regulation of financial asset price volatility. Through in-depth study of its influence mechanism, it can provide accurate decision support and risk management strategies for financial market stabilization.

Aeroengine Remaining Life Prediction Based on Advanced Health Index Construction and Gray Similarity Multiscale Matching

Aeroengine Remaining Life Prediction Based on Advanced Health Index Construction and Gray Similarity Multiscale Matching

КОМПОЗИТНЫЕ ИНДЕКСЫ ДЛЯ УПРАВЛЕНИЯ ЦИФРОВИЗАЦИЕЙ: МЕТОДЫ ФОРМИРОВАНИЯ

In the circumstances of digital transformation of the state and society, the indicative approach to analyzing and governing digitalization finds active usage. However, the characteristics of relevant data cause methodological problems, including statistical duplication. The article considers various methods for constructing composite digitalization indices based on secondary aggregation of principal components in order to overcome duplication. It is hypothesized that there is no single best method for secondary aggregation, and that the preference of methods depends on the indicative evaluation tasks being addressed. The lack of scientific consensus on the best aggregation method for calculating composite indices supports this proposition. Multiple widespread aggregation methods are also described. To consider the hypothesis, two potential secondary aggregation methods, alongside the option to eschew secondary aggregation, are studied. Their advantages are analyzed using common tasks of rating and analysing the strengths and weaknesses of facilities as an example. The data for analysis include principal components extracted from 21 digitalization indicators for years 2014 and 2016. Correlation analysis of their secondary aggregation’s results and country rating comparison show that different analysed methods are suitable for different tasks. This is due to the correspondence of the methods’ properties to the requirements imposed by the tasks being solved. The practical applicability of the discussed methodologies for analysing digitalization is demonstrated by the example of the Russian Federation. The study confirmed the need to consider the index construction methods’ characteristics to select the methods most appropriate to the tasks being solved. The obtained results can serve as the basis for developing a classification of requirements posed by indicative evaluation tasks, which will also contribute to systematization of aggregation methods, which has practical usefulness within the indicative approach.

The Index Construction and Empirical Research of the Development Environment of Science and Technology Enterprises

The Index Construction and Empirical Research of the Development Environment of Science and Technology Enterprises

Construction of Green City Index in Indonesian Metropolitan Districts/Cities

Urbanization in Indonesia resulted in population density in urban areas, which has the potential for economic growth, marked by increased population income followed by changes in consumption patterns that will cause environmental problems in urban areas. Seeing environmental issues that occur in urban areas, it is necessary to have a green city concept city planning as a sustainable city planning solution without damaging the environment. The measurement of green city achievement has yet to be carried out in Indonesia. This study aims to measure the Green City Index (GCI) in metropolitan districts/cities in Indonesia using Partial Least Squares-Structural Equation Modeling (PLS-SEM). It examines the GCI achievements in Indonesian metropolitan districts/cities. The GCI is formed by a socioeconomic dimension of two indicators and an environmental dimension of eleven indicators. Generally, the highest GCI achievements are in the Bogor District, with a score of 74.3 percent. Bangkalan District achieved the highest socioeconomic dimension index, and Bogor District completed the highest environmental dimension index. In addition, there is a significant and negative relationship between GCI and the Human Development Index (HDI) and economic growth. It is hoped that the government and the community can pay attention to the balance of the environment in their activities.