scholarly journals Reframing E-Government Development Indices with Respect to New Trends in ICT

2015 ◽  
Vol 15 (4) ◽  
pp. 383-412 ◽  
Author(s):  
Renáta Máchová ◽  
Martin Lněnička
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Rank Correlation ◽  
Important Indicator ◽  
The Public ◽  
Telecommunication Infrastructure ◽  
Kendall Rank Correlation ◽  
New Framework ◽  
Government Development

Abstract E-government readiness is an important indicator of the quality of a country’s technological and telecommunication infrastructure and the ability of its citizens, businesses and governments to adopt, use and benefit from modern technologies. To measure and compare selected countries, a lot of benchmarking and ranking indices have been introduced since the beginning of the century. With the increasing importance of trends such as cloud computing, open (big) data, participation tools or social media, new indicators and approaches need to be introduced in the measuring of the e-government development, and the existing indices should to be updated, redefined and restructured. Therefore, this article explores the structure of the existing e-government development indices to show the main indicators and trends. Then, it proposes and implements a new framework to evaluate e-government development using these new trends in ICT. It also examines and compares a basic background on the e-government development, benefits and risks of cloud computing, open (big) data and participation tools in the public sector. Based on the newly proposed framework, the e-government development index is calculated for each EU Member State to clearly identify the indicators to have an influence on the e-government development. In the last part, these results are compared to the already existing indices to validate the conformity of the rank methods using Kendall rank correlation coefficient.

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

Reinforcement Learning for Cloud Computing Digital Library

2014 ◽  
Vol 571-572 ◽  
pp. 105-108
Author(s):  
Lin Xu
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Reinforcement Learning ◽  
Digital Library ◽  
Learning Algorithms ◽  
Experimental Results ◽  
Current Status ◽  
Self Learning ◽  
New Framework

This paper proposes a new framework of combining reinforcement learning with cloud computing digital library. Unified self-learning algorithms, which includes reinforcement learning, artificial intelligence and etc, have led to many essential advances. Given the current status of highly-available models, analysts urgently desire the deployment of write-ahead logging. In this paper we examine how DNS can be applied to the investigation of superblocks, and introduce the reinforcement learning to improve the quality of current cloud computing digital library. The experimental results show that the method works more efficiency.

scholarly journals The Construction and Thinking of Cloud Computing and Big Data Technology in Smart Campus

2019 ◽  
Vol 3 (2) ◽  
pp. 152
Author(s):  
Xianglan Wu
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Storage ◽  
Information Technologies ◽  
Rapid Development ◽  
Smart Campus ◽  
Huge Data ◽  
New Information ◽  
Big Data Technology

<p>In today's society, the rise of the Internet and rapid development make every day produce a huge amount of data. Therefore, the traditional data processing mode and data storage can not be fully analyzed and mined these data. More and more new information technologies (such as cloud computing, virtualization and big data, etc.) have emerged and been applied, the network has turned from informationization to intelligence, and campus construction has ushered in the stage of smart campus construction.The construction of intelligent campus refers to big data and cloud computing technology, which improves the informatization service quality of colleges and universities by integrating, storing and mining huge data.</p>

Big Data IoT Analytics for Smart Cities With Cloud Computing Technique

2021 ◽  
pp. 104-126
Author(s):  
Chellaswamy C. ◽  
Sathiyamoorthi V.
Keyword(s):  
Big Data ◽  
Smart Cities ◽  
Computing Technique ◽  
Strong Connectivity ◽  
The Public ◽  
Environmental Footprints ◽  
5G Network ◽  
Information And Communication ◽  
Data Analytic

Currently, cities are being reconstructed to smart cities that use an information and communication technology (ICT) framework alongside the internet of things (IoT) technology to increase efficiency and also share information with the public, helping to improve the quality of government services citizens' welfare. This large, diverse set of information called big data is obtained by ICT and IoT technologies from smart cities. This information does not have any meaning of its own but a high potential to make use of smart city services. Therefore, the information collected is mined and processed through use of big data analytic techniques. The environmental footprints in smart cities can be monitored and controlled with the help of ICT. Big data analytic techniques help enhance the functionalities of smart cities and the 4G and 5G network provides strong connectivity for professional devices.

IoT Based Agriculture as a Cloud and Big Data Service

2020 ◽  
pp. 1499-1521
Author(s):  
Sukhpal Singh Gill ◽  
Inderveer Chana ◽  
Rajkumar Buyya
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Cloud Services ◽  
Cloud Environment ◽  
Big Data Technologies ◽  
Sensor Networking ◽  
New Applications

Cloud computing has transpired as a new model for managing and delivering applications as services efficiently. Convergence of cloud computing with technologies such as wireless sensor networking, Internet of Things (IoT) and Big Data analytics offers new applications' of cloud services. This paper proposes a cloud-based autonomic information system for delivering Agriculture-as-a-Service (AaaS) through the use of cloud and big data technologies. The proposed system gathers information from various users through preconfigured devices and IoT sensors and processes it in cloud using big data analytics and provides the required information to users automatically. The performance of the proposed system has been evaluated in Cloud environment and experimental results show that the proposed system offers better service and the Quality of Service (QoS) is also better in terms of QoS parameters.

scholarly journals Impact of E-government Development on the Level of Corruption: Measuring the Effects of Related Indices in Time and Dimensions

2018 ◽  
Vol 18 (2) ◽  
pp. 99-121 ◽  
Author(s):  
Renáta Máchová ◽  
Jolana Volejníková ◽  
Martin Lněnička
Keyword(s):  
Empirical Relationship ◽  
The Public ◽  
Telecommunication Infrastructure ◽  
Ict Adoption ◽  
Ict Development ◽  
Ict Infrastructure ◽  
The Impact ◽  
The Relationship ◽  
Stimulation Of ◽  
Government Development

Abstract E-government is recognized as a tool for improving transparency and openness in the public sector and for combatting corruption. Understanding the relationship between e-government development and the level of corruption would allow for a more effective leveraging of related projects in anti-corruption efforts. This paper examines the impact of e-government development on the level of corruption in the context of economic perspective. In contrast to previous studies, this empirical relationship is measured across sub-indices (dimensions) of related indices between 2002 and 2016. The results show that higher levels of e-government development are related to lower levels of corruption. The three most important dimensions found are the environment sub-index, which assesses the extent to which a country’s market conditions and regulatory framework support entrepreneurship, innovation, and ICT development; the usage sub-index, which assesses the level of ICT adoption by a society’s main stakeholders; and the telecommunication infrastructure sub-index measuring a country’s ICT infrastructure capacity. Following these findings, certain ways of influencing of the level of corruption by a stimulation of concrete e-government development dimensions can be drawn. This is important especially in the time of a financial crisis and its consequences, which are also discussed in this paper.

scholarly journals Qualitative Characteristics of the Educational Process Organized by the University Departments for Economics Students (Regional Aspect)

2020 ◽  
pp. 100-106
Author(s):  
O. S. Koshevoy ◽  
◽  
N. V. Nekrylova ◽  
Keyword(s):  
Undergraduate Students ◽  
Research Work ◽  
Rank Correlation ◽  
Educational Process ◽  
University Departments ◽  
Regional Aspect ◽  
Kendall Rank Correlation ◽  
The University ◽  
Qualitative Characteristics

The assessment of the qualitative characteristics of the organization of the educational process by the departments of a regional university, in particular, Penza State University (PSU), for undergraduate students of economics is given. The following materials and scientific research methods are applied: questionnaire survey, ranking method, calculation of the Kendall rank correlation W test and the nonparametric Kruskal–Wallis H test. The departments involved in teaching undergraduate students of economics of PSU were assessed according to the level of their activity in organizing research work of students, the professionalism of teachers and methodological support of classes, the demand for the electronic LMS of the university. It is noted that the quality of the educational process at the university is determined by the personal and professional characteristics of the teachers of the departments and the level of organizational and methodological support of classroom studies. Moreover, the gender, place of residence and status of the students’ parents affect the results of assessing the quality of education from the standpoint of students.

Cloud Computing

2015 ◽  
Vol 5 (3) ◽  
pp. 32-43 ◽  
Author(s):  
Yulin Yao
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Big Data ◽  
Current Literature ◽  
Emerging Technologies ◽  
Future Directions ◽  
Development Review ◽  
The Past ◽  
New Framework

This paper provides an overview of Cloud Computing between Year 2009 and Year 2015. It presents the past and current literature and practices for Cloud Computing. Literatrue review is undertaken to identify key areas relevant to current Cloud Computing development. Review on frameworks for Cloud computing has also been presented to illustrate the good use of structured and valid framework approaches. Topics of discussion demonstrate that Cloud computing can provide added values not only to businesses but also Higher Education. Future directions and conclusion have been presented and acknowledged, including the development of a new framework. Cloud Computing is concluded to provide better services and integrations with other emerging technologies such as Big Data.

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