Big Data Technology for Scientific Applications

Suciu, George; Anwar, Muneeb; Rogojanu, Ioana; Pasat, Adrian; Stanoiu, Alina

doi:10.1109/rolcg.2018.8572023

Cited by 8 publications

(4 citation statements)

References 10 publications

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“…Looking holistically at the research question and at the current technological trends, the availability of large amounts of heterogeneous data and of significant computation capabilities intuitively points to techniques based on Big Data analytics [20]. Such an approach is already in use for scientific applications [21]. While the direct adoption of Big Data analytics can probably result complex and expensive to answer the research question object of the paper, it's combination with MCDA [22] provides an interesting approach to prioritise association rules and identified patterns.…”

Section: A Comparative Studymentioning

confidence: 99%

Is the World Becoming a Better or a Worse Place? A Data-Driven Analysis

Pileggi

2019

Sustainability

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Is the World becoming a better or a worse place to live? In this paper, we propose a tool that can help to answer the question by combining a number of global indicators belonging to multiple categories. The proliferation of statistical data about various aspects of the World performance may suggest that it should be "easy" to evaluate the overall success of human enterprise on this planet. Moreover, it also points out the intrinsic importance in the selection of indicators. However, people have different values, biases, and preferences about the importance of various indicators, making it almost impossible to find an objective answer to this question. To address the variety and the heterogeneity of available indicators and world views, we present the analysis of global World performance as a multi-criteria decision problem, making sure that the assessment method remains as transparent as possible. By dynamically selecting a set of indicators of interest, defining the weights that we attach to various indicators and specifying the desired trends associated with each indicator, we make the assessment adaptive to individual values. We also try to deal with the inherent bias that may exist in the set of indicators that are chosen. As a study case, from various data sets that are openly available online, we have selected several that are most relevant and easy to interpret in the context of the question in the title of the paper. We demonstrate how the choice of personal preferences, or weights, can strongly change the result. Our method also provides analysis of the weights space, showing how results for particular value sets compare to the average and extreme (optimistic and pessimistic) combinations of weights that may be chosen by users.

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Section: A Comparative Studymentioning

confidence: 99%

Is the World Becoming a Better or a Worse Place? A Data-Driven Analysis

Pileggi

2019

Sustainability

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“…The unreliability is frequently caused by consumer privacy protection behavior [19]. Meanwhile, Big Data storage is also a challenge for traditional manufacturing companies [47]. Data Company owning the skill to safeguard consumer privacy will get more trust of consumers and they will provide their personal information to the Data Company.…”

Section: Importance Of Data Company In Book Supply Chainmentioning

confidence: 99%

Decision‐Making and Coordination of a Three‐Stage Book Supply Chain considering Big Data Information Cost

Liu

2019

Mathematical Problems in Engineering

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In the Big Data era, Big Data Information (BDI) has been used in the book supply industry. Data Company as an important BDI supplier should be included in a book supply chain. Thus, to explore the investment decision-making problems of BDI and its effects on the coordination and pricing rules of book supply chain, a three-stage book supply chain with one book publisher, one retailer, and one Data Company was chosen. Meanwhile, four benefit models about BDI investment were proposed and analyzed in the environments of symmetry information and asymmetric information. A revenue sharing contract was used to achieve book supply chain coordination. Findings: whether the book publisher and the retailer were suitable to invest in BDI, it was influenced by the cost improvement coefficient. With the ascent of the cost improvement coefficient, benefits of supply chain members will reduce, and, in different investment models, their prices show different change trends with the cost improvement coefficient.

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“…In [11], the authors have presented a low-powered design of IoT by using Pysense sensor shield, Waspmote, and Raspberry Pi. The authors in [12] used Pycom/Pytrack to collect data and send them to the cloud for big data analysis. Again, the authors in [13] have Pycom LoPy module to collect data from multiple sensors and send data to The Things Network (TTN), which are retrieved by Node-Red to display the data in a dashboard.…”

Section: Related Workmentioning

confidence: 99%

Remote Condition Monitoring: A Prototype Based on Pycom Development Board FiPy and Pysense

Voisin-Grall

Malaolu

Zhu

et al. 2019

2019 UK/ China Emerging Technologies (UCET)

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Internet of Things (IoT) is not new in the market; however, they are becoming more dominant in various operations and applications. These pervasive infrastructures can collect different data in a given environment such as temperature, pressure, light sensitivity, and so on to enable remote condition monitoring. Subsequently, these collected data can be used for many purposes depending on the user's requirement. Currently, there are colossal interests from researchers to know how to use these infrastructures to collect and send data over different protocols to the cloud for efficient remote handling from anywhere in the world. In this paper, we design and implement an infrastructure based on Pycom development board FiPy and sensor shield Pysense to collect and send data to the remote cloud over Wi-Fi and Long Range (LoRa) protocols. The intelligible set up is beneficial for observing and managing data in the cloud.

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Big Data Technology for Scientific Applications

Cited by 8 publications

References 10 publications

Is the World Becoming a Better or a Worse Place? A Data-Driven Analysis

Is the World Becoming a Better or a Worse Place? A Data-Driven Analysis

Decision‐Making and Coordination of a Three‐Stage Book Supply Chain considering Big Data Information Cost

Remote Condition Monitoring: A Prototype Based on Pycom Development Board FiPy and Pysense

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