Analysis of Signalling Time of Community Model

Bhattacharya, Boudhayan; Saha, Banani

doi:10.5815/ijmsc.2015.02.02

Cited by 3 publications

(3 citation statements)

References 21 publications

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“…The approach varies depending on the context. A composite technopole index is made up of weight ratios given by the experts and specific indices that were examined in (Aliyev and Shahverdiyeva 2017;Bhattacharya and Saha, 2015). To measure technopole performance, the potential socio-economic indicators of technopole development are used alongside a correlation-regression analysis.…”

Section: Figure 1 -The Grp Of the East Kazakhstan Region In 2016-2018mentioning

confidence: 99%

The Effectiveness of Innovative Infrastructure: The Case of Kazakhstan

Bayadilova¹,

Nassyrkhanov

Tlessova

et al. 2020

QIP Journal

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Purpose: The development of an innovative economy is constrained by the problems of science funding, modernization of scientific institutions and innovative training of specialists. This article focuses on the problem of evaluating the effectiveness of the innovation infrastructure of the Republic of Kazakhstan using a systematized set of performance indicators.Methodology/Approach: Approaches to assessing innovation infrastructure have been analysed. Based on the analysis, correlation and regression assessment model has been developed.Findings: A forecast has been made for innovative infrastructure development based on the obtained performance indicators. This forecast is of high practical significance, as it allows predicting the outcomes of innovation.Research Limitation/implication: In the light of globalization, it is extremely urgent to develop an innovative economy along with regional innovation systems. If combined, these systems can accelerate the innovation processes in the regions, ensure competitiveness and expedite the socio-economic development. The formation of an innovative economy should be in line with the productive forces and production relations.Originality/Value of the paper: Through categorization, this study establishes a set of underlying indicators, which are used to measure the performance of the innovation infrastructure. A model of correlation and regression analysis is built, which allows evaluating the effectiveness of the innovation infrastructure of Kazakhstan.

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Section: Figure 1 -The Grp Of the East Kazakhstan Region In 2016-2018mentioning

confidence: 99%

The Effectiveness of Innovative Infrastructure: The Case of Kazakhstan

Bayadilova¹,

Nassyrkhanov

Tlessova

et al. 2020

QIP Journal

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“…To form composit indexsuggested for comparative evaluation of activity of technoparks, the weight ratios given by experts to selected indexes have been studied accordingly [14,15]. Then the final score for each index and technopark is calculated.…”

Section: In Scientific Innovative Technoparksmentioning

confidence: 99%

Application of Mathematical Methods and Models in Product - Service Manufacturing Processes in Scientific Innovative Technoparks

Aliyev¹,

Shahverdiyeva²

2018

IJMSC

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The article focuses on the application of mathematical methods and models in product -service manufacturing processes in scientific innovative technoparks. The necessity of applying economic-mathematical models and methods in the activity of innovative structures is substantiated. A system of indicators and criteria for assessing the performance and effective management of technoparks has been developed. Based on this system, an information model of the technopark was proposed. A mathematical model of the general management of technoparks is proposed. An econometric model for the innovative product-service manufacturing has been developed. The technique of comparative evaluation of innovative technology parks based on a system of composite indicators and a composite index is proposed. As a result of the experimental implementation of these methods and models, the activity of technoparks. prepared. In this direction "The Strategic Roadmap for National Economy and the main sectors of economy" was prepared also in Azerbaijan by the end of 2016 [1]. 12 strategic roadmaps approved for national economy and 11 sectors of economy in general are prepared. These roadmaps are increasing the competitiveness, inclusiveness and social welfare of the economy.Strategic roadmaps include strategy of economic development and action plan for 2016-2020 years, longterm vision for the period up to 2025 and target vision for the post-2025 period. Targeted vision of the SRM (strategic roadmap) for the post-2025 period will provide wide opportunities, expansion of access to quality education, the basis of transition to efficiency and innovation-based economy. The competitive labor force being the main driven force of the economy, regulation of labor market, application of high technologies, including smart machines and systems is the transition of economy from the efficiency-based model to the innovation-based model.The impact of innovative technologies on the development of new emerging economic fields, automated knowledge creation process, "internet control", remote control technologies, artificial intelligence and robotization, adaptation of management to the requirements of advanced technologies (bio, nano, information, communication, industry, finance, etc.) will be implemented.On the national economy perspective within the framework of SRM to ensure macroeconomic stability on the basis of effective management, to improve the structure of the economy, to increase employment, to provide balanced regional development, improve the business environment and strengthen the participation of the private sector is planned. The main objective of SRM on development of telecommunication and information technologies, which is one of the 11 sectors of SRM, is the effective functioning of the public sector in the country, improving the level of socio-economic life of the population, development and improvement of ICT infrastructure for health, education, finance, and digitization of the economy in general, increasing the potential of ICT industry o...

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“…A well-provided method for calculating signaling time of the community model via late signaling cost for the data fusion using the Dynamic Transformation Model (DTM) by [4] has been the link between two processes in signaling and time axes indexes; the signaling time was estimated based on the data transmission time and processing delay based on the two immediate filter levels via designed algorithm.…”

Section: Related Workmentioning

confidence: 99%

Bayesian Approach: An Alternative to Periodogram and Time Axes Estimation for Known and Unknown White Noise

Olawale¹

2018

IJMSC

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This study describes the Bayesian approach as an alternative approach for estimating time axes parameters and the periodogram (power spectrum) associated with sinusoidal model when the white noise (sigma) is known or unknown. The conventional method of estimating the time axes parameters and the periodogram has been via the Schuster method that relies solely on Maximum Likelihood Estimation (MLE). The Bayesian alternative approach proposed in this work, on the other hand, adopted the Maximum a Posteriori (MAP) via the Markov Chain Monte Carlo (MCMC) in order to checkmate the problem of re-parameterization and overparameterization associated with MLE in the conventional practice. The rates of heartbeat variability at exactly an hour and two hours after birth of one thousand eight hundred (1800) newly born babies in a state hospital were recorded and subjected to both the Bayesian approach and Schuster approach for inferences. The periodogram estimates, exactly an hour and two hours of after birth, were estimated to be 0.7395 and 0.7549, respectively -and it was deduced that rates of heartbeat (frequency) variability moderated and stabilized the pulse among the babies after two hours of birth. In addition, MAP mean estimates of the parameters approximately equals to the true mean of estimates when round up to curb the problem of re-parameterization and over-parameterization that do affect Schuster method via MLE.Index Terms: Bayesian, Maximum A Posteriori (MAP), Markov Chain Monte Carlo (MCMC), Maximum Likelihood Estimation (MLE), and Periodograms.

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Analysis of Signalling Time of Community Model

Cited by 3 publications

References 21 publications

The Effectiveness of Innovative Infrastructure: The Case of Kazakhstan

The Effectiveness of Innovative Infrastructure: The Case of Kazakhstan

Application of Mathematical Methods and Models in Product - Service Manufacturing Processes in Scientific Innovative Technoparks

Bayesian Approach: An Alternative to Periodogram and Time Axes Estimation for Known and Unknown White Noise

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