Sustainability for the Holistic Ecosystem : Regulation Guide Designing for the Prevalent Technology Development of China Emerging Communications: Big Data, IoT, 5G etc.

2018 ◽  
Author(s):  
Dr. Fu-Cheng Chao
Keyword(s):  
Big Data ◽  
Technology Development

Challenges and Cloud Computing Environments Towards Big Data

2014 ◽  
pp. 203-208
Author(s):  
Kiran Kumar S V N Madupu
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Technology Development ◽  
Computing Environments ◽  
Modern Technologies

Big Data has terrific influence on scientific discoveries and also value development. This paper presents approaches in data mining and modern technologies in Big Data. Difficulties of data mining as well as data mining with big data are discussed. Some technology development of data mining as well as data mining with big data are additionally presented.

Prospects for Cooperation Between Russia and the Republic of Korea in the Fields of Big Data, Network and Artificial Intelligence for the Development of the Digital Economy

2021 ◽  
Vol 65 (8) ◽  
pp. 51-60
Author(s):  
Yujeong Kim
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Large Scale ◽  
Technology Development ◽  
Technological Development ◽  
Digital Economy ◽  
Republic Of Korea ◽  
Data Network ◽  
Leading Position ◽  
The Government

Today, each country has interest in digital economy and has established and implemented policies aimed at digital technology development and digital transformation for the transition to the digital economy. In particular, interest in digital technologies such as big data, 5G, and artificial intelligence, which are recognized as important factors in the digital economy, has been increasing recently, and it is a time when the role of the government for technological development and international cooperation becomes important. In addition to the overall digital economic policy, the Russian and Korean governments are also trying to improve their international competitiveness and take a leading position in the new economic order by establishing related technical and industrial policies. Moreover, Republic of Korea often refers to data, network and artificial intelligence as D∙N∙A, and has established policies in each of these areas in 2019. Russia is also establishing and implementing policies in the same field in 2019. Therefore, it is timely to find ways to expand cooperation between Russia and Republic of Korea. In particular, the years of 2020and 2021marks the 30th anniversary of diplomatic relations between the two countries, and not only large-scale events and exchange programs have prepared, but the relationship is deepening as part of the continued foreign policy of both countries – Russia’s Eastern Policy and New Northern Policy of Republic of Korea. Therefore, this paper compares and analyzes the policies of the two countries in big data, 5G, and artificial intelligence to seek long-term sustainable cooperation in the digital economy.

scholarly journals FORECASTING OF BLOCKCHAIN TECHNOLOGY DEVELOPMENT IN ECONOMY: ACCOUNTING POINT OF VIEW

2019 ◽  
pp. 37-44
Author(s):  
L. Shkulipa
Keyword(s):  
Big Data ◽  
New Technologies ◽  
Technology Development ◽  
Local Economy ◽  
Point Of View ◽  
Negative Effects ◽  
Blockchain Technology ◽  
Hype Cycle ◽  
Predictive Assessment ◽  
Further Development

In the article the importance of blockchain technology in the economy and predicting its development from the accounting point of view was investigated. The methods used in the study are based on the analysis of literature related to disclosure issues and a description of existing blockchain claims on the world stage. On the basis of this, a predictive assessment of the considered results for the further development of blockchain technology in the economy, its impact on accounting and the profession of accountant was made. The findings include the positive and negative effects of blockchain technology on the medical and banking sectors, information technology, the financial sector, and accounting. The blockchain in the hype cycle was considered as a phenomenon that all new technologies undergo before stable existing or disappearing. Based on the consideration of the most famous blockchain projects with the combination of Big Data, the estimation of the development technologies of Blockchain and Big Data in finance was discussed. This study suggests to consider blockchain technology as (1) a new way of sending and processing invoices, documents, contracts, and payments, reducing errors, costs and transaction time; (2) a path to financial equality through affordability; (3) investments in the local economy so that developing countries can grow significantly; (4) updating the currency market and the international monetary and financial transaction system; (5) a major breakthrough in the economy together with the Big Data technology.

scholarly journals Taming Disruption? Pervasive Data Analytics, Uncertainty and Policy Intervention in Disruptive Technology and its Geographic Spread

2019 ◽  
Vol 8 (1) ◽  
pp. 34 ◽  
Author(s):  
Roger Brackin ◽  
Michael Jackson ◽  
Andrew Leyshon ◽  
Jeremy Morley
Keyword(s):  
Big Data ◽  
Technology Development ◽  
Specific Aspect ◽  
Disruptive Technology ◽  
Policy Intervention ◽  
Disruptive Effect ◽  
Geographical Spread ◽  
Political Implications ◽  
Technology Transition ◽  
Historic Data

The topic of technology development and its disruptive effects has been the subject of much debate over the last 20 years with numerous theories at both macro and micro scales offering potential models of technology progression and disruption. This paper focuses on how theories of technology progression may be integrated and considers whether suitable indicators of this progression and any subsequent disruptive effects might be derived, based on the use of big data analytic techniques. Given the magnitude of the economic, social, and political implications of many disruptive technologies, the ability to quantify disruptive change at the earliest possible stage could deliver major returns by reducing uncertainty, assisting public policy intervention, and managing the technology transition through disruption into deployment. However, determining when this stage has been reached is problematic because small random effects in the timing, direction of development, the availability of essential supportive technologies or “platform” technologies, market response or government policy can all result in failure of a technology, its form of adoption or optimality of implementation. This paper reviews key models of technology evolution and their disruptive effect including the geographical spread of disruption. The paper then describes a use case and an experiment in disruption prediction, looking at the geographical spread of disruption using internet derived historic data. The experiment, although limited to one specific aspect of the integrated model outlined in the paper, provides an initial example of the type of analysis envisaged. This example offers a glimpse into the potential indicators and how they might be used to measure disruption hinting at what might be possible using big data approaches.

From remote sensing to bioeconomy: how big data can improve automatic map generation

2020 ◽  
Author(s):  
Jonathan Rizzi ◽  
Ingvild Nystuen ◽  
Misganu Debella-Gilo ◽  
Nils Egil Søvde
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Big Data ◽  
Climate Adaptation ◽  
Technology Development ◽  
Production Systems ◽  
Learning Algorithm ◽  
Efficient Production ◽  
Research Activity ◽  
Social Mission

<p>Recent years are experiencing an exponential increase of remote sensing datasets coming from different sources (satellites, airplanes, UAVs) at different resolutions (up to few cm) based on different sensors (single bands sensors, hyperspectral cameras, LIDAR, …). At the same time, IT developments are allowing for the storage of very large datasets (up to Petabytes) and their efficient processing (through HPC, distributed computing, use of GPUs). This allowed for the development and diffusion of many libraries and packages implementing machine learning algorithm in a very efficient way. It has become therefor possible to use machine learning (including deep learning methods such as convolutional neural networks) to spatial datasets with the aim of increase the level of automaticity of the creation of new maps or the update of existing maps. </p><p>Within this context, the Norwegian Institute of Bioeconomy Research (NIBIO), has started a project to test and apply big data methods and tools to support research activity transversally across its divisions.  NIBIO is a research-based knowledge institution that utilizes its expertise and professional breadth for the development of the bioeconomy in Norway. Its social mission entails a national responsibility in the bioeconomy sector, focusing on several societal challenges including: i) Climate (emission reductions, carbon uptake and climate adaptation); ii) Sustainability (environment, resource management and production within nature and society's tolerance limits); iii) Transformation (circular economy, resource efficient production systems, innovation and technology development); iv) food; and v) economy.</p><p>The presentation will show obtained results focus on land cover mapping using different methods and different dataset, include satellite images and airborne hyperspectral images. Further, the presentation will focus related on the criticalities related to automatic mapping from remote sensing dataset and importance of the availability of large training datasets.</p>

scholarly journals Government Management Innovation in the Age of Big Data

2016 ◽  
Vol 7 (2) ◽  
pp. 47
Author(s):  
Que Tianshu
Keyword(s):  
Big Data ◽  
Digital Divide ◽  
Policy Making ◽  
Technology Development ◽  
Population Subdivision ◽  
Management Innovation ◽  
Information Transparency ◽  
Government Administration ◽  
Government Management

“Big data” is a word to be increasingly mentioned, which is used to describe the coming of information explosion. It also defines the related technology development and innovation. Big data triggers a great revolution. This seems to herald the inescapable process of quantization for all professions including academia, business or government. The trend of big data obviously outdated the conventional means of government administration, hence making its innovation the theme of this age. The innovation faces both opportunities and challenges. Opportunities are that it promotes information transparency and policy making based on population subdivision. For challenges, it may increase the risk of “data dictatorship”, privacy, once being abused, may also lead to preemptive punishment; it is also possible to deepen “the digital divide”. Based on pioneering research, this paper puts forward a new mode of government administrative innovation.

scholarly journals AKUNTAN DALAM INDUSTRI 4.0: STUDI KASUS KANTOR JASA AKUNTAN (KJA) DI WILAYAH KEPULAUAN RIAU

2020 ◽  
Vol 11 (2) ◽  
pp. 100-109
Author(s):  
Alfonsa Dian Sumarna
Keyword(s):  
Information Technology ◽  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
Data Analytics ◽  
Technology Development ◽  
Leadership Skills ◽  
Computer Software ◽  
Data Entry ◽  
Information Technology Development

Abstract Using robotics and data analytics (big data) can over take clerical job (data entry, bookkeeping, compliance work). Accounting profession underestimate to technologies. Competence such as data analysis, information technology development, and leadership skills must be adapted to face 4.0. Our research found that Kantor Jasa Akuntan in Kepulauan Riau Province using 80% accounting professional labor (accounting bachelor). This research confirmed about IoT (Internet of Things) that 60% of KJA use 70-100% of total hours of work using computer (software) and internet compare with manual working. KJA need accounting professional who able to work with software such as accounting software, statistic, Ms Office, Zahir, and SAP. This research also found the main softskill needed is critical thingking ability. Acording to the survey, software are not affecting accounting employment yet. Keywords: Industry 4.0; Accounting Professional; Software; Internet of Things Abstrak Penggunaan robotics dan data analytics (big data) dapat mengambil alih pekerjaan dasar yang dilakukan oleh akuntan (mencatat transaksi, mengolah transaksi, dan memilah transaksi). Profesi akuntan merasa dirugikan terkait dampak teknologi terhadap pekerjaan akuntan. Kompetensi yang penting bagi profesi akuntan dalam menghadapi 4.0 misalnya data analysis, information technology development, dan leadership skills harus dapat dikembangkan. Penelitian ini menunjukkan bahwa Kantor Jasa Akuntan di Wilayah Provinsi Kepulauan Riau masih tetap mempertahankan menggunakan tenaga profesional akuntan sebesar 80% merupakan Sarjana Akuntansi. Selain itu penelitian ini juga mengkonfirmasi penggunaan IoT (Internet of Things) yaitu sebesar 60% KJA menggunakan 70-100% total waktu menyelesaikan pekerjaan menggunakan komputer (software) dan internet dibandingkan dengan pengerjaan manual. KJA membutuhkan akuntan profesional yang menguasai software akuntansi, statistika, MsOffice, Zahir dan SAP. Selain menguasai software dalam menghadapi 4.0, penelitian ini menunjukkan bahwa softskill utama yang diperlukan adalah memiliki kemampuan berpikir kritis dan analitis. Kata Kunci: Industri 4.0; Akuntan Profesional; software; Internet of Things

scholarly journals Taming Disruption? Pervasive Data Analytics, Uncertainty, and Policy Intervention in Disruptive Technology and Its Geographic Spread

2018 ◽  
Author(s):  
Roger C. Brackin ◽  
Michael J. Jackson ◽  
Andrew Leyshon ◽  
Jeremy G. Morley
Keyword(s):  
Big Data ◽  
Technology Development ◽  
Analytical Techniques ◽  
Disruptive Technology ◽  
Policy Intervention ◽  
Disruptive Effect ◽  
Potential Models ◽  
Disruptive Technologies ◽  
Political Implications ◽  
Technology Transition

The topic of technology development and its disruptive effects has been the subject of much debate over the last 20 years with numerous theories at both macro and micro scale offering potential models of technology progression and disruption. This paper focuses on how the potential theories of technology progression can be integrated and considers whether suitable indicators of this progression and any subsequent disruptive effects (particularly considering these geographically) might be derived, based on the use of big data analytic techniques. Given the magnitude of the economic, social and political implications of many disruptive technologies, the ability to quantify disruptive change at the earliest possible stage could deliver major returns by reducing uncertainty, assisting public policy intervention and managing the technology transition through disruption into deployment. However, determining when this stage has been reached is problematic because small random effects in the timing, direction of development, the availability of essential supportive technologies or “platform” technologies, market response or government policy can all result in failure of a technology, its form of adoption or optimality of implementation. This paper reviews some of the key models of technology evolution and their disruptive effect including, in particular, the geographical spread of disruption. It suggests a methodology for utilising the recent explosion of open and web-discoverable data to determine a methodology to achieve this earlier determination and considers the potential exploitation of big data modelling and predictive analytical techniques to achieve this goal.

scholarly journals From Big Data to Deep Learning: A Leap Towards Strong AI or ‘Intelligentia Obscura’?

2018 ◽  
Vol 2 (3) ◽  
pp. 16 ◽  
Author(s):  
Stefan Strauß
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Deep Learning ◽  
Technology Development ◽  
Well Being ◽  
Societal Implications ◽  
Algorithmic Accountability ◽  
Novel Approaches ◽  
Basic Concepts ◽  
Made In

Astonishing progress is being made in the field of artificial intelligence (AI) and particularly in machine learning (ML). Novel approaches of deep learning are promising to even boost the idea of AI equipped with capabilities of self-improvement. But what are the wider societal implications of this development and to what extent are classical AI concepts still relevant? This paper discusses these issues including an overview on basic concepts and notions of AI in relation to big data. Particular focus lies on the roles, societal consequences and risks of machine and deep learning. The paper argues that the growing relevance of AI in society bears serious risks of deep automation bias reinforced by insufficient machine learning quality, lacking algorithmic accountability and mutual risks of misinterpretation up to incrementally aggravating conflicts in decision-making between humans and machines. To reduce these risks and avoid the emergence of an intelligentia obscura requires overcoming ideological myths of AI and revitalising a culture of responsible, ethical technology development and usage. This includes the need for a broader discussion about the risks of increasing automation and useful governance approaches to stimulate AI development with respect to individual and societal well-being.

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