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In recent years, big data analysis is gaining immense credence in the fields of academics and business. Businesses such as management and marketing have demonstrated a strong inclination and interest in data analytics. However, many businesses are unable to utilize data even if they have access to it. The main reason for that is the…

SME big data maturity models will be reviewed in this study to identify systematic publications related to the subject. For SMEs to remain competitive, digitalization is essential. Due to limited resources, SMEs need to be more proactive in digitalization. Still, the benefits, such as operational efficiency, cost reduction, quality improvement, and innovative culture, make digitalization…

Blockchain technology has been successfully applied in many fields for immutable and secure data storage. However, for applications with on-chain big data, blockchain scalability remains to be a main concern. In this paper, we propose a novel scalable storage scheme, called HistoChain, for a consortium blockchain network to manage blockchain data. We use a current…

Social networks have become a valuable platform for tracking and analyzing Internet users’ feelings. This analysis provides crucial information for decision-making in various areas, such as politics and marketing. In addition to this challenge and our interest in the field of big data and sentiment analysis in social networks, we have dedicated this work to…

IoT platforms play an important role on modern measurement systems because they allow the ingestion and processing of huge amounts of data (big data). Given the increasing use of these platforms, it is important to characterize their performance and robustness in real application scenarios. The paper analyzes the ThingSpeak platform by measuring the latencies associated…

The world is witnessing unprecedented advancements in ICT (Information & Communication Technology) related fields. These advancements are further boosted with the emergence of big data. It goes without saying that big data requires two major operations: storage and processing. The latter is usually provided through High-Performance Computing (HPC) which is delivered through two main venues:…

This paper presents the results of the research conducted with the help of cognitive cybernetics about the “mass” factor from the theory of totalitarianism. According to the expert system model, “big data” analysis sought to discover knowledge for assessing the future status of digital social connectivity. Originally developed models and methods of cognitive and computer…

The paper addresses speeding up meetings in a networked environment during rescue works in a transport emergency. Several groups of representatives of various services and observers participate in those meetings. The number of wrong decisions tends to increase because remote participants cannot understand each other quickly. First, the meetings must be efficiently held to avoid…

Big data is a vast data set that was used in many areas. Online applications are subject to theft of confidential information because opponents can exploit software errors to access private data, and because curious or malicious officials can capture and lose data. CryptDB is a functional system that provides security and confidentiality through a…

Bearings are the key components of many rotating machines, in which serious failure or even major breakdown may occur due to their abnormal operation and defects. Thus, accurate fault diagnoses of bearing elements are essential for proactive predictive maintenance. However, the using of multiple sensors with high sampling rate reveal considerable shortages in the analysis…

News companies have a need to automate and make the process of writing about popular and new events more effective. Current technologies involve robotic programs that fill in values in templates and website listeners that notify editors when changes are made so that the editor can read up on the source change on the actual…

With the development of big data, artificial intelligence and deep learning, various social information networks are becoming exponentially intelligent. Of all the various social networks, YouTube is so popular that it is called the YouTube era. Not only video viewers, but also actual video producers, influencer youtubers, are increasing, allowing individuals as well as operators…

Recently, wireless sensor network (WSN) gets more concern due to the robustness in the latest communication technology iteration such as big data, IoT and 5G. Such daily usage of these technologies includes smart home, smart farming, smart traffic control etc. Moreover, WSN becomes the best preference for mobile objects in data accumulating in a wild…

With the unprecedented wave of Big Data, the importance of information visualization is catching greater momentum. Understanding the underlying relationships between constituent objects is becoming a common task in every branch of science, and visualization of such relationships is a critical part of data analysis. While the techniques for the visualization of binary relationships are…

The era of big data has witnessed the explosion of tensor datasets, and large scale Probabilistic Tensor Factorization (PTF) analysis is important to accommodate such increasing trend of data. Sparsity, and Cold-Start are some of the inherent problems of recommender systems in the era of big data. This paper proposes a novel Sentiment-Based Probabilistic Tensor…

Cloud computing is a power platform to deal with big data. Among several software frameworks used for the construction of cloud computing systems, Apache Hadoop, which is an open-source software, becomes a popular one. Hadoop supports for distributed data storage and the process of large data sets on computer clusters based on a MapReduce parallel…

A company’s ability to find the most profitable technology is based on a precise forecast of achievement potential. Technology Management (TM) uses forecasting models to analyse future potentials, e.g. the Gartner Hype Cycle, Arthur D. Little’s technology lifecycle or McKinsey’s S-curve model. All these methods are useful for qualitative analysis in the planning of strategic…

Network security implements various strategies for the identification and prevention of security breaches. Network intrusion detection is a critical component of network management for security, quality of service and other purposes. These systems allow early detection of network intrusion and malicious activities; so that the Network Security infrastructure can react to mitigate these threats. Various…

Infrastructure Asset Management was first adopted in 1980s for challenges faced by the utilities, road and rail transport systems, mining, process and manufacturing industries in asset life cycle value optimization. International standards ISO 55000 and PAS 55 were subsequently developed to provide a basis for a structured methodology in the development of Asset Management System.…

In the aim to manage and retrieve the organizational knowledge, in the last years numerous proposals of models and tools for knowledge management and knowledge representation have arisen. However, most of them store knowledge in a non-structured or semi-structured way, hindering the semantic and automatic processing of this knowledge. In this paper we present a…

The implemented programs in the MapReduce processing model are focused in the analysis of large volume of data in a distributed and parallel architecture. This architecture is automatically managed by the framework, so the developer could be focused in the program functionality regardless of infrastructure failures or resource allocation. However, the infrastructure state can cause…

It has become difficult to handle traditional networks because of extensive network developments and an increase in the number of network users, and also because of new technologies like cloud computing and big data. Traditional networks are experiencing an increase in VM load and in the time taken for processing tasks. Hence, it has become…

The digital factory is a concept signing a new era for industry, the so-called Industry 4.0, in which ordinary production systems like manufacturing plants, machineries and utilities are being equipped with diagnostic and sensitive instrumentation to be connected to digital shared networks. This data-sharing, trough the big data management techniques, is a fully integrated base…