scholarly journals Genomic big data hitting the storage bottleneck

2018 ◽  
Vol 24 ◽  
pp. e910 ◽  
Author(s):  
Louis Papageorgiou ◽  
Picasi Eleni ◽  
Sofia Raftopoulou ◽  
Meropi Mantaiou ◽  
Vasileios Megalooikonomou ◽  
...  
Keyword(s):  
Big Data ◽  
Technological Development ◽  
Daily Basis ◽  
Storage Space ◽  
Permanent Loss ◽  
High Storage Capacity ◽  
Data Volume ◽  
Extensive Information ◽  
Analyse Data ◽  
The One

During the last decades, there is a vast data explosion in bioinformatics. Big data centres are trying to face this data crisis, reaching high storage capacity levels. Although several scientific giants examine how to handle the enormous pile of information in their cupboards, the problem remains unsolved. On a daily basis, there is a massive quantity of permanent loss of extensive information due to infrastructure and storage space problems.  The motivation for sequencing has fallen behind. Sometimes, the time that is spent to solve storage space problems is longer than the one dedicated to collect and analyse data. To bring sequencing to the foreground, scientists have to slide over such obstacles and find alternative ways to approach the issue of data volume. Scientific community experiences the data crisis era, where, out of the box solutions may ease the typical research workflow, until technological development meets the needs of Bioinformatics. 

scholarly journals Semitensor Product Compressive Sensing for Big Data Transmission in Wireless Sensor Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Haipeng Peng ◽  
Ye Tian ◽  
Jürgen Kurths
Keyword(s):  
Big Data ◽  
Compressive Sensing ◽  
Data Transmission ◽  
Matrix Multiplication ◽  
Wireless Sensor ◽  
Storage Space ◽  
Secret Key ◽  
Encrypt Data ◽  
The Matrix ◽  
Data Volume

Big data transmission in wireless sensor network (WSN) consumes energy while the node in WSN is energy-limited, and the data transmitted needs to be encrypted resulting from the ease of being eavesdropped in WSN links. Compressive sensing (CS) can encrypt data and reduce the data volume to solve these two problems. However, the nodes in WSNs are not only energy-limited, but also storage and calculation resource-constrained. The traditional CS uses the measurement matrix as the secret key, which consumes a huge storage space. Moreover, the calculation cost of the traditional CS is large. In this paper, semitensor product compressive sensing (STP-CS) is proposed, which reduces the size of the secret key to save the storage space by breaking through the dimension match restriction of the matrix multiplication and decreases the calculation amount to save the calculation resource. Simulation results show that STP-CS encryption can achieve better performances of saving storage and calculation resources compared with the traditional CS encryption.

Designing Analytical Approaches for Interactive Competitive Intelligence

2013 ◽  
Vol 4 (2) ◽  
pp. 34-45 ◽  
Author(s):  
Michael Prilop ◽  
Liina Tonisson ◽  
Lutz Maicher
Keyword(s):  
Big Data ◽  
State Of The Art ◽  
The Other ◽  
Competitive Intelligence ◽  
Interaction Theory ◽  
Competitive Strategies ◽  
Data Volume ◽  
Service Oriented ◽  
The One ◽  
Analytical Approaches

Since Porter’s work on competitive strategies in the 1980s, the concept of competitive intelligence has become part of the management mainstream. Currently, two big shifts are challenging the state of the art. On the one hand there is the rise of the ubiquitous servicification in all industries which makes the existing methods for product-oriented industries outdated. On the other hand there is the rise of big data (volume, velocity, variety). Both shifts are driving the development towards interactive competitive intelligence systems. The authors introduced a framework for interactive competitive intelligence systems which overcome the sequential water-fall processes which are current CI practice. In the introduced framework they combine the concept of Key Intelligence Topics (KIT) with the concept of (boundary) objects from interaction theory. The authors demonstrated with examples within their “IP Industry Base” how interactive CI for service-oriented sectors can be implemented. The resulting vector-based representations of the companies’ service profiles allow the user to visualize, compare, retrieve and analyse companies in a constructive and scalable way.

THE USE OF CRITICAL THINKING AGAINST FAKE NEWS

2020 ◽  
Author(s):  
Alexandra-Niculina Babii
Keyword(s):  
Critical Thinking ◽  
Critical Discourse Analysis ◽  
Daily Basis ◽  
Informal Logic ◽  
Critical Discourse ◽  
Fake News ◽  
Digital Era ◽  
The Social ◽  
Legal Sanctions ◽  
The One

The digital era has determined a very easy creation and propagation of fake news. As a consequence, it has become harder for people to fight this malicious phenomenon. However, the only weapon that can have results in this informational war is critical thinking. But who should use it? The creators of fake news that do this for different reasons? The social platforms that allow the circulation of fake news with ease? Mass media which does not always verify with much attention and rigour the information they spread? The Governments that should apply legal sanctions? Or the consumer that receives all the fake news, him being the final target? Even if critical thinking would be useful for every actor on fake news’ stage, the one who needs it the most is the consumer. This comes together with the big responsibility placed on his shoulders. Even if others are creating and spreading disinformation, the consumer must be aware and be careful with the information he encounters on a daily basis. He should use his reasoning and he should not believe everything just because it is on the Internet. How can he do that? Critical thinking seems to be a quite difficult tool to use, especially for non-specialized individuals. This paper’s aim is to propose a simplified model of critical thinking that can contribute to detecting fake news with the help of people’s self judgement. The model is based on theories from Informal Logic considering the structure of arguments and on Critical Discourse Analysis theories concerning the patterns found in the content of the information.

How Phillips saw the light

2020 ◽  
Vol 36 (8) ◽  
pp. 29-31
Keyword(s):  
Design Methodology ◽  
Reading Time ◽  
Daily Basis ◽  
Business World ◽  
Content Type ◽  
Freak Show ◽  
The World ◽  
Pertinent Information ◽  
The One ◽  
Practical Implications

Purpose Reviews the latest management developments across the globe and pinpoints practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings The problem with developing a reputation of being something of an oracle in the business world is that all of a sudden, everyone expects you to pull off the trick of interpreting the future on a daily basis. Like a freak show circus act or one-hit wonder pop singer, people expect you to perform when they see you, and they expect you to perform the thing that made you famous, even if it is the one thing in the world you don’t want to do. And when you fail to deliver on these heightened expectations, you are dismissed as a one trick pony, however good that trick is in the first place. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

scholarly journals Is There a Predisposition towards the Use of New Technologies within the Traffic Field of Emerging Countries? The Case of the Dominican Republic

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1208
Author(s):  
Francisco Alonso ◽  
Mireia Faus ◽  
Cristina Esteban ◽  
Sergio A. Useche
Keyword(s):  
Dominican Republic ◽  
Road Safety ◽  
New Technologies ◽  
Technological Development ◽  
Personal Data ◽  
Emerging Countries ◽  
Level Of Knowledge ◽  
One Year ◽  
The One ◽  
And Control

Technological devices are becoming more and more integrated in the management and control of traffic in big cities. The population perceives the benefits provided by these systems, and, therefore, citizens usually have a favorable opinion of them. However, emerging countries, which have fewer available infrastructures, could present a certain lack of trust. The objective of this work is to detect the level of knowledge and predisposition towards the use of new technologies in the transportation field of the Dominican Republic. For this study, the National Survey on Mobility was administered to a sample of Dominican citizens, proportional to the ONE census and to sex, age and province. The knowledge of ITS topics, as well as the use of mobile applications for mobility, are scarce; however, there was a significant increase that can be observed in only one year. Moreover, technology is, in general, positively assessed for what concerns the improvement of the traffic field, even though there is a lack of predisposition to provide one’s personal data, which is necessary for these devices. The process of technological development in the country must be backed up by laws that protect the citizens’ privacy. Thus, technologies that can improve road safety, mobility and sustainability can be implemented in the country.

scholarly journals Investigation of an Electrostatic Discharge Protective Biodegradable Packaging Foam in the Logistic Chain

2014 ◽  
Vol 5 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Ákos Mojzes ◽  
Barnabás Tóth ◽  
Péter Csavajda
Keyword(s):  
Electrostatic Discharge ◽  
Technological Development ◽  
Environmental Parameters ◽  
Thermoplastic Starch ◽  
Vital Role ◽  
Packaging Materials ◽  
Negative Effects ◽  
Packaging System ◽  
Product Packaging ◽  
The One

Abstract Since the beginning of the 20th century, logistics has undergone a huge technological development, which has, however, resulted in many negative effects as well. The industry, particularly in the packaging industry has been a massive waste producer, although recently it has forced the use of new materials and it started to focus on environmentally friendly technologies. During the transportation of finished and semi-finished Electrostatic Discharge (ESD) sensitive products, the product packaging system has a vital role. These kind of packaging materials must be suitable to both logistic (protection against mechanical and environmental stresses) and special ESD protection requirements. During the transportation of printed-circuit electronic products, ESD defense is then of primary significance. However there is a huge disadvantage for the use of various shield bags. Namely, this kind of associated packaging is particularly pollutant, it causes a lot of inconvenience in the form of waste. In order to rule out these materials from the packaging system, new innovative solutions have to be found. The investigated TPS (thermoplastic starch biodegradable foam) is subjected to a validation, a long process to certify that this material unites properties of two types of packaging materials at the same time. On the one hand, this packaging foam has to meet the requirements product defense. On the other hand, the material must be anti-static under the logistic stress effects. In case it is found suitable, it can be an alternative of the conventional materials. In this article, we investigate the ESD characteristic of TPS foam. As this material sensitive for environmental parameters during transportation, we make the relevant Surface Resistance (Rs) tests on different temperature and humidity conditions. Based on result, the decision of the application can be done, as an ESD packaging material.

scholarly journals Challenges of Big Data analysis

2014 ◽  
Vol 1 (2) ◽  
pp. 293-314 ◽  
Author(s):  
Jianqing Fan ◽  
Fang Han ◽  
Han Liu
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Measurement Errors ◽  
Modern Society ◽  
Big Data Analysis ◽  
Small Scale ◽  
Paradigm Change ◽  
Statistical Inferences ◽  
The One ◽  
And Storage

Abstract Big Data bring new opportunities to modern society and challenges to data scientists. On the one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This paper gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-confidence set and point out that exogenous assumptions in most statistical methods for Big Data cannot be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions.

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.

Analysis of time series using Big Data algorithms

2021 ◽  
pp. 118-124
Author(s):  
А.И. Сотников
Keyword(s):  
Time Series ◽  
Big Data ◽  
Daily Basis ◽  
Processing Methods ◽  
Traditional Technologies ◽  
New Processing ◽  
Analysis Of Time Series

То, с какой скоростью человечество накапливает информацию ежедневно, и непредсказуемость завтрашнего дня показывают, что для прогнозирования временных рядов больших данных уже не хватает традиционных технологий и необходимы новые методы обработки. В связи с этим встает вопрос, какие методы возможно использовать в настоящее время для получения достоверного прогнозирования временных рядов больших данных? The speed at which humanity is accumulating information on a daily basis and the unpredictability of tomorrow show that traditional technologies are no longer enough for forecasting big data time series and new processing methods are needed. In this regard, the question arises, what methods can be used at present to obtain reliable forecasting of time series of big data?

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