scholarly journals Improving Incident Response in Big Data Ecosystems by Using Blockchain Technologies

2020 ◽  
Vol 10 (2) ◽  
pp. 724 ◽  
Author(s):  
Julio Moreno ◽  
Manuel A. Serrano ◽  
Eduardo B. Fernandez ◽  
Eduardo Fernández-Medina
Keyword(s):  
Big Data ◽  
Research Work ◽  
Daily Activities ◽  
Incident Response ◽  
Reference Architecture ◽  
Normal Functioning ◽  
Design And Implementation ◽  
Analysis Design ◽  
Data Ecosystem

Big data ecosystems are increasingly important for the daily activities of any type of company. They are decisive elements in the organization, so any malfunction of this environment can have a great impact on the normal functioning of the company; security is therefore a crucial aspect of this type of ecosystem. When approaching security in big data as an issue, it must be considered not only during the creation and implementation of the big data ecosystem, but also throughout its entire lifecycle, including operation, and especially when managing and responding to incidents that occur. To this end, this paper proposes an incident response process supported by a private blockchain network that allows the recording of the different events and incidents that occur in the big data ecosystem. The use of blockchain enables the security of the stored data to be improved, increasing its immutability and traceability. In addition, the stored records can help manage incidents and anticipate them, thereby minimizing the costs of investigating their causes; that facilitates forensic readiness. This proposal integrates with previous research work, seeking to improve the security of big data by creating a process of secure analysis, design, and implementation, supported by a security reference architecture that serves as a guide in defining the different elements of this type of ecosystem. Moreover, this paper presents a case study in which the proposal is being implemented by using big data and blockchain technologies, such as Apache Spark or Hyperledger Fabric.

scholarly journals Analysis, design, and creation of a learning program in Big Data at the higher education level: Case study Instituto Tecnológico Superior de Rioverde, SLP

2021 ◽  
pp. 9-13
Author(s):  
Omar Mendoza-González ◽  
Mónica Amador-García ◽  
Yurivia Torres-Meraz ◽  
Fabiola García-Padrón
Keyword(s):  
Big Data ◽  
Basic Knowledge ◽  
Computer Engineering ◽  
Learning Program ◽  
Learning Programs ◽  
Solid Foundation ◽  
The Subject ◽  
Analysis Design ◽  
Job Context

In this paper results of a quantitative and qualitative study are shown to identify interest and acceptance level of Big Data in university students. The creation of a learning program is proposed that will allow students to obtain the necessary knowledge to form a solid foundation regarding Big Data, as well as the necessary tools to start working with this technology. A survey has been carried out of students who study the Educational Programs of Computer Engineering and Engineering in Computer Systems at ITSRV, the results show that 41% of the respondent’s report having zero knowledge of Big Data, 51.28% mention that it is important to learn about the subject by development professional and the most suitable way, according to the answers, is through a workshop or a certification. Of the eight most used Big Data tools, Hadoop and Spark were the ones identified by the respondents, due to this, and the literature reviewed, it is important that spaces and Big Data learning programs are generated in higher level institutions that allow Students obtain the necessary basic knowledge and identify applications of Big Data in the professional and job context.

scholarly journals Decision-Making Enhancement in a Big Data Environment: Application of the K-Means Algorithm to Mixed Data

2019 ◽  
Vol 9 (4) ◽  
pp. 293-302
Author(s):  
Oded Koren ◽  
Carina Antonia Hallin ◽  
Nir Perel ◽  
Dror Bendet
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Mixed Data ◽  
Systems Research ◽  
Information Systems Research ◽  
Effective Decision ◽  
Data Ecosystem ◽  
Effective Decision Making ◽  
Business Requirements

Abstract Big data research has become an important discipline in information systems research. However, the flood of data being generated on the Internet is increasingly unstructured and non-numeric in the form of images and texts. Thus, research indicates that there is an increasing need to develop more efficient algorithms for treating mixed data in big data for effective decision making. In this paper, we apply the classical K-means algorithm to both numeric and categorical attributes in big data platforms. We first present an algorithm that handles the problem of mixed data. We then use big data platforms to implement the algorithm, demonstrating its functionalities by applying the algorithm in a detailed case study. This provides us with a solid basis for performing more targeted profiling for decision making and research using big data. Consequently, the decision makers will be able to treat mixed data, numerical and categorical data, to explain and predict phenomena in the big data ecosystem. Our research includes a detailed end-to-end case study that presents an implementation of the suggested procedure. This demonstrates its capabilities and the advantages that allow it to improve the decision-making process by targeting organizations’ business requirements to a specific cluster[s]/profiles[s] based on the enhancement outcomes.

scholarly journals Military Applications of Natural Language Processing and Software

2011 ◽  
pp. 301-321
Author(s):  
J. A. Rodger ◽  
P. C. Pendharkar
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Interactive Technology ◽  
Health Protection ◽  
Design And Implementation ◽  
Military Applications ◽  
Clinical Surveillance ◽  
Analysis Design

The case study describes the process of planning, analysis, design and implementation of an integrated voice interactive device (VID) for the Navy. The goal of this research is to enhance Force Health Protection and to improve medical readiness by applying voice interactive technology to environmental and clinical surveillance activities aboard U.S. Navy ships.

A Case Study of Business Service Realization

2008 ◽  
pp. 315-374
Author(s):  
Bill Karakostas ◽  
Yannis Zorgios
Keyword(s):  
Web Services ◽  
Business Models ◽  
Business Service ◽  
Business Services ◽  
Design And Implementation ◽  
Service Identification ◽  
Service Execution ◽  
Service Oriented ◽  
Analysis Design

Having discussed a method for service realization in Chapter VII, the service methodology that was first outlined in the Introduction of this book is now complete. We have covered the following, so far: • Service concepts and fundamentals (Chapter II). • Service identification from business models and modeling, using the IDEF0/ IDEF1X notations (Chapter VII). • Service realization using the MDA transformation of business services to executable Web services (Chapter V). • Environments for service execution and management (Chapter IX). This chapter demonstrates how the above aforementioned concepts and methods can be applied to the analysis design and implementation of real business services. The business domain that we have chosen, accounts.payable/accounts.receivable (A/R-A/P), is pervasive, but by no means trivial. In this chapter, we approach this traditional accounting domain from a fresh, service-oriented perspective, by following the steps of the approach presented in the previous chapters, to show how services can be realized. We finally implement the modeled services using the CLMS service engineering platform that was first introduced in Chapter IX.

Development of Reference Architecture Based on Big Data Ecosystem

2014 ◽  
Vol 11 (6) ◽  
pp. 511-522
Author(s):  
Suwook Ha ◽  
Seungyun Lee ◽  
Kangchan Lee
Keyword(s):  
Big Data ◽  
Reference Architecture ◽  
Data Ecosystem

scholarly journals Assessing a Methodological Proposal for the Design, Creation and Evaluation of Learning Objects Oriented to Educators with Diverse Educational and Technological Competencies

2016 ◽  
Author(s):  
Jorge J. Maldonado ◽  
Jorge L. Bermeo ◽  
Guillermo Pacheco
Keyword(s):  
Learning Objects ◽  
Design And Implementation ◽  
Design Methodologies ◽  
Basic Understanding ◽  
Design Activities ◽  
Technological Competencies ◽  
Analysis Design ◽  
Evaluation Of Learning

This paper describes a methodological proposal for the design, creation and evaluation of Learning Objects (LOs). This study arises from the compilation and analysis of several LO design methodologies currently used in Ibero-America. This proposal, which has been named DICREVOA, defines five different phases: analysis, design (instructional and multimedia), implementation (LO and metadata), evaluation (from the perspective of both the producer and the consumer of the LO), and publishing. The methodology focuses not only on the teaching inexperienced, but also on those having a basic understanding of the technological and educational aspects related to LO design; therefore, the study emphasizes LO design activities centered around the Kolb cycle and the use of the ExeLearning tool in order to implement the LO core. Additionally, DICREVOA was used in a case study, which demonstrates how it provides a feasible mechanism for LO design and implementation within different contexts. Finally, DICREVOA, the case study to which it was applied, and the results obtained are presented.

HIPEREMESIS GRAVIDARUM PADA IBU HAMIL DI KLINIK BIDAN SUPRIYATI SRIBIT BERBAH SLEMAN

2019 ◽  
Vol 14 (1) ◽  
pp. 51
Author(s):  
Pramukti Dian Setianingrum ◽  
Farah Irmania Tsani
Keyword(s):  
Blood Pressure ◽  
Pregnant Women ◽  
Hyperemesis Gravidarum ◽  
Unwanted Pregnancy ◽  
The Body ◽  
Nausea And Vomiting ◽  
Daily Activities ◽  
World Health ◽  
The World

Backgroud: The World Health Organization (WHO) explained that the number of Hyperemesis Gravidarum cases reached 12.5% of the total number of pregnancies in the world and the results of the Demographic Survey conducted in 2007, stated that 26% of women with live births experienced complications. The results of the observations conducted at the Midwife Supriyati Clinic found that pregnant women with hyperemesis gravidarum, with a comparison of 10 pregnant women who examined their contents there were about 4 pregnant women who complained of excessive nausea and vomiting. Objective: to determine the hyperemesis Gravidarum of pregnant mother in clinic. Methods: This study used Qualitative research methods by using a case study approach (Case Study.) Result: The description of excessive nausea of vomiting in women with Hipermemsis Gravidarum is continuous nausea and vomiting more than 10 times in one day, no appetite or vomiting when fed, the body feels weak, blood pressure decreases until the body weight decreases and interferes with daily activities days The factors that influence the occurrence of Hyperemesis Gravidarum are Hormonal, Diet, Unwanted Pregnancy, and psychology, primigravida does not affect the occurrence of Hyperemesis Gravidarum. Conclusion: Mothers who experience Hyperemesis Gravidarum feel nausea vomiting continuously more than 10 times in one day, no appetite or vomiting when fed, the body feels weak, blood pressure decreases until the weight decreases and interferes with daily activities, it is because there are several factors, namely, hormonal actors, diet, unwanted pregnancy, and psychology.

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