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The Big data analytics gives new chances to the enterprises to enhance their management and manufacturing levels. A solution with case study is proposed to accomplish deep-level quality management based on big data analytics. First, the implementation of big data analytics based on industrial process data is illustrated with case study illustration. Through the analysis and feature extraction of off-line...
Current procedure in travel demand estimation models is to separately deal with attraction, production and trip distribution, where the latter typically assumes inverse distance proportionality. We show that this procedure leads to errors in the demand estimation, particularly when dealing with very specific zones and heterogeneous travel behavior. We argue that this traditional procedure is rooted...
This paper explores scalable implementation strategies for carrying out lazy schema evolution in NoSQL data stores. For decades, schema evolution has been an evergreen in database research. Yet new challenges arise in the context of cloud-hosted data backends: With all database reads and writes charged by the provider, migrating the entire data instance eagerly into a new schema can be prohibitively...
Information and communication technologies have crucial role with many researches improving existing electrical grid. With the emergence of the internet of things and the growing availability of connected devices such as smart meters and other sensors, we are facing huge amount of data about energy consumption, energy production and so on. In this context, smart grid data management and analytics...
Increasing efficiency of fatigue testing complex technical systems (for example, aircraft engine) is possible with its technical and economic assessment on base of relationship with the economic effect from the system operation. The amount of data is received during the engine life cycle. It should be properly processed to build the lifecycle model. Big Data concept can be suggested as an effective...
In recent years economic an social activity fields is based on data. Oil and gas industry leaders understand the value of big data and are interested in digital oil industry becoming a reality. Here is big data is analysed as a key component in based decision making in oil and gas industry during exploration, drilling and production. In oil and gas industry architectural model is offered for integration...
Based on unified data expression model of agricultural data lacking with the common management data, and inconsistent problems of agricultural data in the process of the management and use, the establishing method of the agricultural data integration model based on ontology is presented in this paper. First, the common management data structure of agricultural production institutions is analyzed,...
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...
The structures of product design, process development, manufacturing, sales, product utilization, after sale service and product retirement are becoming more and more complex due to the underlying reasons of newly introduced rules as well as constraints of the respective stakeholders. On the other hand, these complexities are also appending up the organizational assets. The configuration of the state...
In this paper, we managed to identify a typical thermal process of an ultra supercritical unit on the basis of DSC data obtained from a power plant rather than doing experiments. With screened reliable data and data processing, this system identification was performed by applying Particle Swarm Optimization(PSO) to establish mathematical model. As a result, the model-predicted data showed an excellent...
Algorithm trading techniques are adopted by institutional and individual investors with the expectation of making profit. Not only the algorithms are getting more complex, but also the data on which algorithms are running is becoming bigger, and various data are exploited to make more accurate prediction. Next generation of algorithm trading will be big data driven. This paper presents the big data...
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