big data


Challenges in 5G: how to empower SON with big data for enabling 5G
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While an al dente character of 5G is yet to emerge, network densification, miscellany of node types, split of control and data plane, network virtualization, heavy and localized cache, infrastructure sharing, concurrent operation at multiple frequency bands, simultaneous use

Social-network-sourced big data analytics
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Very large datasets, also known as big data , originate from many domains, including healthcare, energy, weather, business, and social networks. Deriving knowledge is more difficult than ever when we must do it by intricately processing big data . Organizations relyExtending the current Internet and providing connection, communication, and internetworking between devices and physical objects, or things, is a growing trend thats often referred to as the Internet of Things (IoT). Integrating real-world data into the Web, withBig data enables new directions for scientific research once limited by the volume of available data . For example, many natural language and speech-related problems are ill suited for mathematically precise algorith- mic solutions. To better address this problem, statistical machine-learning

Representational learning with extreme learning machine for big data
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Restricted Boltzmann Machines (RBM) and auto encoders, learns to represent features in a dataset meaningfully and used as the basic building blocks to create deep networks. This paper introduces Extreme Learning Machine based Auto Encoder (ELM-AE), which learns

Mobile cloud sensing, big data , and 5G networks make an intelligent and smart world
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Through time, we have seen mobile phones transform into multifaceted devices, adapted to meet and exceed our everyday needs. These needs range from something as personal as a health care manager to something as purely analytical as an environment monitor. In effect

Big data analysis with signal processing on graphs
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Analysis and processing of very large datasets, or Big Data , poses a significant challenge. Massive datasets are collected and studied in numerous domains, from engineering sciences to social networks, biomolecular research, commerce and security. Extracting

Bootstrapping smart cities through a self-sustainable model based on big data flows
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We have a clear idea today about the necessity and usefulness of making cities smarter, about the potential market size, about trials and tests. However, it seems that business around Smart Cities has difficulties of taking off and thus runs short of projected potentials

Ubiquitous analytics: Interacting with big data anywhere, anytime
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UBILYTICS We refer to the use of mul- tiple networked devices in our local environment to enable deep and dynamic analysis of massive, hetero geneous, and multiscale data anytime, anywhere as ubiquitous analytics, or ubilytics. This approach not only liberates analysts from the confines

Big data opportunities and challenges: Discussions from data analytics perspectives
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Big Data as a term has been among the biggest trends of the last three years, leading to an upsurge of research, as well as industry and government applications. Data is deemed a powerful raw material that can impact multidisciplinary research endeavors as well asNOWADAYS, the hot topics on novel information technology include cloud computing, social networking, mobile Internet, and big data . The major goal of cloud computing is to share resources, which consist of infrastructure, platform, software, and business process. When

Big Data –Opportunities and Challenges Panel Position Paper
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I. INTRODUCTION Recent technological advances and novel applications, such as sensors, cyber-physical systems, smart mobile devices, cloud systems, data analytics, and social networks, are making possible to capture, process, and share huge amounts of data referred

From big data to big service
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Big service brings together both virtual (such as cloud services) and physical (such as public transportation) services; by aggregating these services from various domains it produces composite service solutions to meet customer requirements. Big service is customer focused

Storage challenge: Where will all that big data go
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This means that existing technologies led by the vener- able hard drive will have to step up. In fact, there are new advances that could significantly increase hard drives storage capacity. Cloud storage will provide ways for many organizations to handle increasing amounts

Big Data -solutions for RDBMS problems-A survey
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Now a days increases shared data very fast due to social networking and mobile phone. In olden days the data is less and able to handle most popular RDBMS concepts, but recently it is difficult to handle this much of huge data through old RDBMS tools. To overcome this

Second-generation big data systems
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› New systems like Apache Spark (http://spark. apache. org) leverage memory to store and call up intermediate results; when intermediate objects must be persisted, flash technology seems likely to supersede hard-disk storage, and flash-as-memory (or data -object stores)

Big data analytics-enabled supply chain transformation: A literature review
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Despite the rising potential of big data , a few studies have been conducted to examine it in the supply chain field. This article gives an overview of big data use in this field and underlines its potential role in the supply chain transformation by leading a systematicKord Davis played with technology from an early age, and he loved learning its underlying principles and mecha- nisms. He chose to study philosophy be- cause it gave him the best of both worlds: rigorous analysis and uncovering the way things work. Now, with a philos- ophy degree

Privacy of big data in the internet of things era
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Over the last few years, we have seen a plethora of Internet of Things (IoT) solutions, products and services, making their way into the industrys market-place. All such solution will capture a large amount of data pertaining to the environment, as well as their users. The

Crowdsourcing, big data and homeland security
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In the aftermath of the Boston Marathon bombing, the FBI twice appealed to the public for help. The first time the appeal was for all photos and videos that the public had of the Boston Marathon environment. The second time the appeal was to help identify the two suspects