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This paper argues that there has not been enough discussion in the field of applications of Gaussian Process for the fast moving consumer goods industry. Yet, this technique can be important as it e.g., can provide automatic feature relevance determination and the posterior mean can unlock insights on the data. Significant challenges are the large size and high dimensionality of commercial data at...
With the rapid development of cloud computing, the Internet of things, big data has become one of the hot spots of society, but also a major focus of applied research, made many service sectors to become data-driven organizations, which exploit the value of big data resources to gain competitive advantage. The meteorological department and the Internet online monitoring collected a large number of...
In this paper, a big-data-driven based intelligent prognostics strategy is proposed to deal with industrial big data generated in the process of intelligent manufacturing, which is an inevitable trend in the industry 4.0 environment. The developed scheme demonstrated the important issues for the intelligent prognostics methodology, including pre-processing methods for industrial big data, association...
In the past few years, there has been significant developments in how machine learning can be used in various industries and research. This paper discusses the potential of utilizing machine learning technologies in healthcare and outlines various industry initiatives using machine learning initiatives in the healthcare sector.
Cyber Physical Systems(CPS) have achieved attention, research and applications from the governments, academic circles, industry circles of domestic and foreign, so, CPS have become an important content of China's two modernizations' deeply integration in future. Using Petri net model to describe CPS information security risk evaluation process. Colligating Petri net model analysis results and CPS...
Big Data has rapidly boomed into a hot topic that attracts attention from governments, academia, and industry around the world. Furthermore, the rapid development of Internet, Internet of Things, and Machine To Machine Communication has led to an extensive growth of data whether in industry or business area. This paper provided discussion about the definition, the characteristics of Big Data and important...
In the era of big data, the emerging big data technologies has brought about revolutionary changes to our lives and many fields, made many service sectors to become data-driven organizations, which exploit the value of big data resources to gain competitive advantage. Big data gradually permeates into every industry and business functions, and meteorological institute is no exception. Currently, meteorological...
Mobile Internet technology is more and more into people's lives. Big Data for the commercial, economic, service, and other areas has brought the earth-shaking change. Over the next 10 years will be a Big Data to lead the age of wisdom, both opportunities and challenges. The data in a certain sense has become a new economic asset class. How to use Big Data to create more value will be a new task faced...
Industry 4.0 can make a factory smart by applying intelligent information processing approaches, communication systems, future-oriented techniques, and more. However, the high complexity, automation, and flexibility of an intelligent factory bring new challenges to reliability and safety. Industrial big data generated by multisource sensors, intercommunication within the system and external-related...
Exponential growth in data volume originating from Internet of Things sources and information services drives the industry to develop new models and distributed tools to handle big data. In order to achieve strategic advantages, effective use of these tools and integrating results to their business processes are critical for enterprises. While there is an abundance of tools available in the market,...
Support vector machines (SVMs) are widely-used for classification in machine learning and data mining tasks. However, they traditionally have been applied to small to medium datasets. Recent need to scale up with data size has attracted research attention to develop new methods and implementation for SVM to perform tasks at scale. Distributed SVMs are relatively new and studied recently, but the distributed...
The digital transformation enables new business models and enhanced business processes by utilizing available data for analytics, prediction, and decision support. We give an overview of the enabling developments for the digital transformation, the areas of application, and concrete use case examples. We summarize our findings in a framework for the digital transformation and discuss the potential...
Data Science is an emerging field of science, which requires a multi-disciplinary approach and should be built with a strong link to emerging Big Data and data driven technologies, and consequently needs re-thinking and re-design of both traditional educational models and existing courses. The education and training of Data Scientists currently lacks a commonly accepted, harmonized instructional model...
Logistic regression (LR) for classification is the workhorse in industry, where a set of predefined classes is required. The model, however, fails to work in the case where the class labels are not known in advance, a problem we term label-drift classification. Label-drift classification problem naturally occurs in many applications, especially in the context of streaming settings where the incoming...
With the continuous development of smart grid and energy Internet, modern power system is gradually evolved into the one with funnel large amounts of data and calculation of large information systems, which shows the applicability and feasibility of the analysis technology of data mining. This paper puts forward a big data modeling method for the reactive power optimization based on the theory of...
The abundant aspects of big data and it's technology are increasing due to new methods of fetching data and diverse needs. Meteorological data is also the source of big data in terms of volume, variety, veracity and velocity, and it includes structured, unstructured and hybrid forms. This paper aims to apply Hadoop architecture and MapReduce algorithm into meteorological big data. It also describes...
In recent years, the rapid development of Internet, Internet of Things, mobile application and Cloud Computing have led to the explosive growth of data in almost every business and industry area. Today, the big data technology and concepts have been gradually applied to the traditional industry from the Internet industry, big data has become an important driving force for economic reform and development...
Companies and organizations are acutely admitting the discernment that business itself can be the driving force in developing new innovations and competitive strategies so that the critical and sustainable factor is whether they have it or not and that is one of the substantial factors in of the entity existence. In this research, concerning the enormously appearing and evaporating industries can...
We live in the Era of Big Data in which data sizes massively larger than previously seen, and increasing access to this data, are transforming people's lives in major ways. Two of the main drivers of this era are the proven capability to extract more value from more data; and the exponential growth of available data enabled in large part to mobile devices and the sensor instrumentation of the world...
Large amounts of heterogeneous education data have emerged in MOOC, which are provided by various educational organizations and universities. In this paper, we present an overview of state-of-art research framework and techniques used in the field of analytics over education big data. Finally, the conclusion is given.
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