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The Internet of Things (IoT) is at a face paced growth in the advanced Industrial Revolution (IR) 4.0 in the modern digital world. Considering the current network security challenges and sophistication of attacks in the heavily computerized and interconnected systems, such as an IoT ecosystem, the need for an innovative, robust, intelligent and adaptive malware…

With the advent of Big Data, we are witnessing a rapid and varied production of huge amounts of sequential data that can have multiple dimensions, we speak of data streams. The characteristics of these data streams make their processing and storage very difficult and at the same time reduce the possibilities of querying them a…

Efficient real-time clustering is a relevant topic in big data streams. Data stream clustering needs necessarily a short time execution frame with bounded memory utilizing a one-scan process. Because of the massive volumes and dynamics of data streams, parallel clustering solutions are urgent. This paper presents a new approach for this trend, with advantages to…

Data mined from social media can be used in a variety of methods. The goal of this paper is to explore some of the various methods of mining data from social media and the different areas of its applications. From the analysis of other studies, it was clear that methods such as text analysis, classification,…

In 1980, an application was developed to track, manage and store documents in electronic format. Scan technology has enabled organizations to digitize papers for easier document storage and tracking. Document management tools have since developed by introducing new functionalities, related to security, users services, workflow and audit. Our research is part of the context of…

Computer vision offers several strategies that permit computers to comprehend the substance of inputted data to extract the relevant highlights features. That gives the possibility to develop several successful recognition systems like face identification. One of the enormous difficulties these days is the way to have a prompt identification face in a multi-client identification system.…

This research describes new traffic congestion analysis method “Traffic Congestion Triangle” based on more than one month real traffic big data analysis in India. The location of the research is one of typical economical growing cities Ahmedabad in Gujarat state of India. The traffic congestion becomes more serious issues in most developing countries and the…

This research sought to measure some socio-political indicators using millions of opinionated messages from social network sourced big data. Thus, and using an enhanced mixed method for sentiment analysis and a fusion model algorithm to infer topics from short text, this study attempted to demonstrate the value of computational approaches in measuring some phenomena in…

Due to high failure rates many students end up spending unnecessary years struggling to qualify and subsequently accumulate unnecessary debt. In this paper, our principal contribution is to provide an expert system that statistically predicts the success of a first year student in an undergraduate Science programme given only academic merit in their subject matter.…

The technology of Big Data got the capability to process large amounts of data, manage them effectively and make retrieval whenever it is required. Decision making in any organisation is a challenging task since decisions need to be made based on the accessibility of data and its status, this becomes more challenging especially in large…

Recurrent Neural Networks has been widely used by researchers in the domain of weather prediction. Weather Prediction is forecasting the atmosphere for the future. In this proposed paper, Deep LSTM networks has been implemented which is the variant of RNNs having additional memory block and gates making them capable of remembering long term dependencies. Fifteen…

In Big Data, several solution providers offer distributions to handle this large amount of data. Given the variety of these solutions, we are working to provide universal meta-modeling for all layers of a Big Data system in order to address the issue of interoperability and portability between these solutions. As part of our continuous efforts…

Big data can be considered to be at the forefront of the present and future research activities. The volume of data needing to be processed is growing dramatically in both velocity and variety. In response, many big data technologies have emerged to tackle the challenges of collecting, processing and storing such large-scale datasets. High-performance computing…

Cloud Computing is considered nowadays an attractive solution to serve the Big Data storage, processing, and analytics needs. Given the high complexity of Big Data workflows and their contingent requirements, a single cloud provider might not be able alone to satisfy these needs. A multitude of cloud providers that offer myriad of cloud services and…

This application developing for the project OCEMA comes as result of architecture building in Android, then the development of a professional modeling in Talend Open Studio for Big Data, which enabled the integration of data from many data sources. One of its uses is the quick identification of people found in areas affected by natural…

Day by day, data grows exponentially large using advanced technology and it requires effective analytical techniques to analyze the unknown and useful facts, patterns, associations and new trends which will provide new way for giving treatment to diseases and to provide good quality healthcare at low cost for everyone. This paper describes uncover valuable insights,…

These last years, the amount of data generated by information systems has exploded. It is not only the quantities of information that are now estimated in Exabyte, but also the variety of these data which is more and more structurally heterogeneous and the velocity of generation of these data which can be compared in many…

Big Data Analytics (BDA) is important to utilize data from hospital systems to reduce healthcare costs. BDA enable queries of large volumes of patient data in an interactively dynamic way for healthcare. The study objective was high performance establishment of interactive BDA platform of hospital system. A Hadoop/MapReduce framework was established at University of Victoria…

Conformal Prediction is a recently developed framework for reliable confident predictions. In this work we discuss its possible application to big data coming from different, possibly heterogeneous data sources. On example of anomaly detection problem, we study the question of saving validity of Conformal Prediction in this case. We show that the straight forward averaging…

The wide acceptance of the semantic web language RDF for ontologies creation in various application fields has led to the emergence of numerous RDF data processing solutions, the so-called triplestores, for the storage of RDF data and its querying using the RDF query language SPARQL. Such solutions are however developed under various perspectives and on…

In an intelligent transportation system (ITS), time is a big challenge since processing a huge amount of data in a short time is very difficult, especially when the processed data is heterogeneous, consisting of a mixture of emergency data, normal data, and noise. In an ITS, an ambulance is one of the priority vehicles, and…

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis.…

This paper provides an overview of Intelligence, Surveillance, and Reconnaissance (ISR) data with respect on NATO standards and recommendations; further presents methods, tools, and experiences in ISR data processing in military operations. The steps of the Intelligence cycle and disciplines Business Intelligence (BI), Data Warehousing, Data Mining, and Big Data are presented in the introduction.…

With such a big volume of data growing tremendously every day, and the storage of important volume of data becoming increasingly more flexible, NoSQL(Not only SQL or Non-Relational ) database are designed to store a large amount of information and are growing for big data systems in web analytics. It an approach does not require…

Visualization plays a crucial role in the exploratory analysis of Big Data. The direct visualization of Big Data is a challenging task and difficult to analyze. Dimensionality Reduction techniques extract the features in the context of visualization. Due to the unsupervised and non-parametric nature, most of the dimensionality reduction techniques are not evaluated quantitatively and…