Big Data to Lead a New Era for “Internet+”: Current Status and Prospect

2017 ◽  
pp. 245-252
Author(s):  
Shan Lin ◽  
Dawei Zheng
Keyword(s):  
Big Data ◽  
Current Status ◽  
New Era

INTERPRETATION OF SINO-RUSSIAN CULTURE AND HUMANITIES COOPERATION IN THE NEW ERA

2020 ◽  
Vol 10 (3) ◽  
pp. 186-193
Author(s):  
REN YANYAN ◽  
Keyword(s):  
Current Status ◽  
Human Relations ◽  
New Era ◽  
Russian Culture ◽  
The People ◽  
Starting Point ◽  
Cooperative Partnership ◽  
Belt And Road ◽  
The Belt And Road

The friendship between nations lies in the mutual affinity of the people, and the people’s affinity lies in the communion of hearts. The cultural and humanities cooperation between China and Russia has a long history. In recent years, under the role of the“Belt and Road” initiative, the SCO, and the Sino-Russian Humanities Cooperation Committee, Sino-Russian culture and humanities cooperation has continued to deepen. Entering a new era, taking the opportunity to promote Sino-Russian relations into a “new era China-Russia comprehensive strategic cooperative partnership”, the development of human relations between the two countries has entered a new historical starting point, while also facing a series of problems and challenges. This article is based on the current status of Sino-Russian human relations in the new era, interprets the characteristics of Sino-Russian human relations in the new era, analyzes the problems and challenges of Sino-Russian human relations in the new era, and tries to propose solutions and solutions with a view to further developing Sino-Russian cultural and humanities relations in the new era. It is a useful reference, and provides a reference for future related research, and ultimately helps the Sino-Russian cultural and humanities relations in the new era to be stable and far-reaching.

Learning Analytics Considered Harmful

2012 ◽  
Vol 16 (3) ◽  
Author(s):  
Laurie P Dringus
Keyword(s):  
Big Data ◽  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Research Community ◽  
Current Status ◽  
Online Course ◽  
Full Potential

This essay is written to present a prospective stance on how learning analytics, as a core evaluative approach, must help instructors uncover the important trends and evidence of quality learner data in the online course. A critique is presented of strategic and tactical issues of learning analytics. The approach to the critique is taken through the lens of questioning the current status of applying learning analytics to online courses. The goal of the discussion is twofold: (1) to inform online learning practitioners (e.g., instructors and administrators) of the potential of learning analytics in online courses and (2) to broaden discussion in the research community about the advancement of learning analytics in online learning. In recognizing the full potential of formalizing big data in online coures, the community must address this issue also in the context of the potentially "harmful" application of learning analytics.

AusGeochem and Big Data Analytics in Low-Temperature Thermochronology

2021 ◽  
Author(s):  
Samuel Boone ◽  
Fabian Kohlmann ◽  
Moritz Theile ◽  
Wayne Noble ◽  
Barry Kohn ◽  
...  
Keyword(s):  
Big Data ◽  
Low Temperature ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Application Programming Interface ◽  
Large Datasets ◽  
Geochemical Data ◽  
Advisory Group ◽  
New Era ◽  
Analytical Instruments

<p>The AuScope Geochemistry Network (AGN) and partners Lithodat Pty Ltd are developing AusGeochem, a novel cloud-based platform for Australian-produced geochemistry data from around the globe. The open platform will allow laboratories to upload, archive, disseminate and publish their datasets, as well as perform statistical analyses and data synthesis within the context of large volumes of publicly funded geochemical data. As part of this endeavour, representatives from four Australian low-temperature thermochronology laboratories (University of Melbourne, University of Adelaide, Curtin University and University of Queensland) are advising the AGN and Lithodat on the development of low-temperature thermochronology (LTT)-specific data models for the relational AusGeochem database and its international counterpart, LithoSurfer. These schemas will facilitate the structured archiving of a wide variety of thermochronology data, enabling geoscientists to readily perform LTT Big Data analytics and gain new insights into the thermo-tectonic evolution of Earth’s crust.</p><p>Adopting established international data reporting best practices, the LTT expert advisory group has designed database schemas for the fission track and (U-Th-Sm)/He methods, as well as for thermal history modelling results and metadata. In addition to recording the parameters required for LTT analyses, the schemas include fields for reference material results and error reporting, allowing AusGeochem users to independently perform QA/QC on data archived in the database. Development of scripts for the automated upload of data directly from analytical instruments into AusGeochem using its open-source Application Programming Interface are currently under way.</p><p>The advent of a LTT relational database heralds the beginning of a new era of Big Data analytics in the field of low-temperature thermochronology. By methodically archiving detailed LTT (meta-)data in structured schemas, intractably large datasets comprising 1000s of analyses produced by numerous laboratories can be readily interrogated in new and powerful ways. These include rapid derivation of inter-data relationships, facilitating on-the-fly age computation, statistical analysis and data visualisation. With the detailed LTT data stored in relational schemas, measurements can then be re-calculated and re-modelled using user-defined constants and kinetic algorithms. This enables analyses determined using different parameters to be equated and compared across regional- to global scales.</p><p>The development of this novel tool heralds the beginning of a new era of structured Big Data in the field of low-temperature thermochronology, improving laboratories’ ability to manage and share their data in alignment with FAIR data principles while enabling analysts to readily interrogate intractably large datasets in new and powerful ways.</p>

FastPacket: Towards Pre-trained Packets Embedding based on FastText for next-generation NIDS

2021 ◽  
Author(s):  
Khloud Al Jallad
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Language Processing ◽  
Intrusion Detection Systems ◽  
Dynamic Feature ◽  
Statistical Features ◽  
Text Data ◽  
New Approach ◽  
New Era ◽  
Detection Systems

Abstract New Attacks are increasingly used by attackers every day but many of them are not detected by Intrusion Detection Systems as most IDS ignore raw packet information and only care about some basic statistical information extracted from PCAP files. Using networking programs to extract fixed statistical features from packets is good, but may not enough to detect nowadays challenges. We think that it is time to utilize big data and deep learning for automatic dynamic feature extraction from packets. It is time to get inspired by deep learning pre-trained models in computer vision and natural language processing, so security deep learning solutions will have its pre-trained models on big datasets to be used in future researches. In this paper, we proposed a new approach for embedding packets based on character-level embeddings, inspired by FastText success on text data. We called this approach FastPacket. Results are measured on subsets of CIC-IDS-2017 dataset, but we expect promising results on big data pre-trained models. We suggest building pre-trained FastPacket on MAWI big dataset and make it available to community, similar to FastText. To be able to outperform currently used NIDS, to start a new era of packet-level NIDS that can better detect complex attacks

The Rise of UAVs Signals a New Era in Geotechnics: Big Data in Geotechnics is Coming from Above

2016 ◽  
Vol 20 (5) ◽  
pp. 72-77
Author(s):  
Dimitrios Zekkos ◽  
William Greenwood ◽  
John Manousakis ◽  
Jerome Lynch
Keyword(s):  
Big Data ◽  
New Era

E-Commerce Security Research in Big Data Environment

2021 ◽  
pp. 1476-1490
Author(s):  
Mei Zhang ◽  
Huan Liu ◽  
Jinghua Wen
Keyword(s):  
Big Data ◽  
Electronic Commerce ◽  
Rapid Development ◽  
Security System ◽  
Information Storage ◽  
New Era ◽  
Security Research ◽  
Distributed Platform ◽  
Data Environment ◽  
Electronic Commerce Security

Rapid development of e-commerce and mobile communication opens a new era of big data. In this article, the authors put big data and e-commerce security together. They construct electronic commerce security system from these aspects: the creation of database, the security of information storage, the mining of information based on big data environment thoroughly. The second-generation product distributed platform- Apache Hadoop which is more popular and instant has been brought in. what's more, this article expounds the structure and working process. On the base of this platform, this article analyses the certainty and security of e-commerce transactions data developed on the condition of big data. It puts forward a construction view that people should guide and monitor the behavior of e-commerce, and improve the security system of electronic commerce on the base of data.

Fan-in WLP: Technology and Market Trends

2015 ◽  
Vol 2015 (1) ◽  
pp. 000067-000072 ◽  
Author(s):  
A. Ivankovic ◽  
T. Buisson ◽  
S. Kumar ◽  
A. Pizzagalli ◽  
J. Azemar ◽  
...  
Keyword(s):  
Flip Chip ◽  
Semiconductor Industry ◽  
Cost Benefit ◽  
Current Status ◽  
Wafer Level ◽  
New Era ◽  
Device Scaling ◽  
Depth Analysis ◽  
Application Diversification ◽  
The Cost

The semiconductor industry is facing a new era in which device scaling and cost reduction will not continue on the path they followed for the past few decades, with Moore's law in its foundation. Advanced nodes do not bring the desired cost benefit anymore and R&D expenses for new lithography solutions and devices in sub-10nm nodes are rising substantially. Subsequently, new market shifts are expected in due time, with “Internet of Things” (IoT) getting ready to take over pole market driver position from mobile. In these circumstances, where front-end-of-line (FEOL) scaling options remain uncertain and IoT promises application diversification, in order to answer market demands, the industry seeks further performance and functionality boosts in package level integration. Emerging packages such as fan-out wafer level packages, 2.5D/3D IC and related System-in-Package (SiP) solutions together with more conventional but upgraded flip chip BGAs aim to bridge the gap and revive the cost/performance curve. In such an environment, what is the importance of fan-in wafer level packages (FI WLP), the current status of the fan-in WLP industry and how will fan-in WLP market and technology evolve? This work aims to answer these questions by performing an in-depth analysis on fan-in WLP market dynamics and technology trends.

scholarly journals Privacy And Web 3.0: Implementing Trust and Learning from Social Networks

2018 ◽  
Vol 10 (4) ◽  
pp. 16
Author(s):  
George Bouchagiar
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Semantic Web ◽  
Web 2.0 ◽  
Personal Information ◽  
Personal Data ◽  
New Era ◽  
Web 3.0 ◽  
Data Portability ◽  
Privacy Risks

After having shifted from Web 1.0 to Web 2.0, scientists welcome the advent of Web 3.0, an environment where meaning is added to data. While in the Semantic Web people are no longer users, but part of the emerging applications, producers, subjects and beneficiaries of the Big Data, however, opaque processing of personal data poses tremendous risks and dangers for individuals. Given the new era of Big Data this paper studies firms’ purposes and practices to detect some emerging privacy risks. Moreover, theories that deal with social networks are examined to conclude that, even if people state that they value their privacy, however, they often disclose a huge volume of personal information. Taking into account that today’s European concept of privacy is conceptualized in negative terms this paper also proposes the implementation of trust and loyalty into the privacy concept through flexible fiduciary laws. Furthermore, data portability is discussed to detect its potential as a strategic feature, a key tool that will enhance trust. Finally, further scenarios and proposals are submitted, in our attempt to answer the question whether the European concept of privacy could be re-shaped for the benefit of individuals.

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