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Michael Wagner and Christin Henzen
In Earth System Sciences (ESS), spatial data are increasingly used for impact research and decision-making. To support the stakeholders? decision, the quality of the spatial data and its assurance play a major role. We present concepts and a workflow to ...
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Santisook Limpeeticharoenchot,Nagul Cooharojananone,Thira Chanvanakul,Nuengwong Tuaycharoen,Kanokwan Atchariyachanvanich
Pág. pp. 87 - 106
A Big Data maturity model (BDMM) is one of the key tools for Big Data assessment and monitoring, and a guideline for maximizing the usage and opportunity of Big Data in organizations. The development of a BDMM for SMEs is a new concept and is challenging...
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Fitri Retrialisca,Umi Chotijah
Pág. 70 - 78
Background: Big data technology has been used in several sectors in Indonesia. Adoption of big technology provides great potential for research, especially achievement in the implementation of big data in manufacturing companies. The Data Warehousing Ins...
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Zaher Ali Al-Sai, Mohd Heikal Husin, Sharifah Mashita Syed-Mohamad, Rosni Abdullah, Raed Abu Zitar, Laith Abualigah and Amir H. Gandomi
Big Data and analytics have become essential factors in managing the COVID-19 pandemic. As no company can escape the effects of the pandemic, mature Big Data and analytics practices are essential for successful decision-making insights and keeping pace w...
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Karol Król and Dariusz Zdonek
This paper aims to review, characterize and comparatively analyze selected organizations? analytics maturity models. Eleven various organizations? analytics maturity models (AMMs) were characterized. The models? characteristics were developed based on an...
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Angela Mattia
The issue of interest in this study is two-fold. First the evolution of Nolans Stage Model is presented. Next, the study discusses adapting Nolans stage theory into a framework that is an adaptable data management measurement tool. An exploratory measure...
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Bozena Gajdzik
The aim of the article is to present the author?s concept of steel market enterprises? maturity for functioning in Industry 4.0. The model is based on the assessment of key technologies or pillars of the new industrial concept. The proposed assessment in...
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Allan Mazimwe, Imed Hammouda and Anthony Gidudu
The success of disaster management efforts demands meaningful integration of data that is geographically dispersed and owned by stakeholders in various sectors. However, the difficulty in finding, accessing and reusing interoperable vocabularies to organ...
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Michiko Miyamoto
Purpose:Using a conceptual framework of Sledgianowski and Luftman (2001), this paper empirically investigates how Japanese SMEs view their Strategy Alignment Maturity, Short-term Linkage, and Organizational Performance. The author examines a theoretical ...
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John C. Gardner, Carl B. McGowan Jr
In this paper, we demonstrate how to collect the data and compute the actual value of Black-Scholes Option Pricing Model call option prices for Coca-Cola and PepsiCo.The data for the current stock price and option price are taken from Yahoo Finance and t...
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Roman Zoun, Kay Schallert, David Broneske, Ivayla Trifonova, Xiao Chen, Robert Heyer, Dirk Benndorf and Gunter Saake
Mass spectrometers enable identifying proteins in biological samples leading to biomarkers for biological process parameters and diseases. However, bioinformatic evaluation of the mass spectrometer data needs a standardized workflow and system that store...
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Marçal Mora-Cantallops, Salvador Sánchez-Alonso, Elena García-Barriocanal and Miguel-Angel Sicilia
Traceability is considered a key requirement for trustworthy artificial intelligence (AI), related to the need to maintain a complete account of the provenance of data, processes, and artifacts involved in the production of an AI model. Traceability in A...
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Saud Sultan Al Rashdi,Smitha Sunil Kumaran Nair
Higher education institutions generate big data, yet they are not exploited toobtain usable information. Making sense of data within organizations becomes the key factorfor success in maintaining sustainability within the market and gaining competitivead...
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Min Li, Xuejing Wu, Yulei Zhu, Najeeb Ullah and Youhong Song
The frequency of heat events is likely to increase due to global climate change, posing an increasing risk to wheat production. To optimize crop management strategies for coping with future climates, it is crucial to quantify the high-temperature occurre...
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Mohan Lal, Sunita Munda, Twahira Begum and Sudin Kumar Pandey
Kaempferia galanga is an endangered plant whose recognition as a flavoring agent and perfumery ingredient has increased its demand greatly. Therefore, the present investigation aimed at the identification of high-rhizome-yielding varieties of K. galanga....
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Philipp Satlawa and Robert B. Fisher
Timely information about the need to thin forests is vital in forest management to maintain a healthy forest while maximizing income. Currently, very-high-spatial-resolution remote sensing data can provide crucial assistance to experts when evaluating th...
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Fa Zhao, Guijun Yang, Hao Yang, Huiling Long, Weimeng Xu, Yaohui Zhu, Yang Meng, Shaoyu Han and Miao Liu
Accurate determination of crop phenology is key to field management and decision making. The existing research on phenology based on remote sensing data is mainly phenology monitoring, which cannot realize the prediction of phenology. In this paper, we p...
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Sungil Kim, Byungki Jung, Dongyun Han and Choonjoo Lee
The smartphone is a must-have mobile device for the military forces to accomplish critical missions and protect critical infrastructures. This paper explores the applicability of a technology prediction methodology to manage technological obsolescence wh...
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Johane H. Bracamonte, Sarah K. Saunders, John S. Wilson, Uyen T. Truong and Joao S. Soares
Inverse modeling approaches in cardiovascular medicine are a collection of methodologies that can provide non-invasive patient-specific estimations of tissue properties, mechanical loads, and other mechanics-based risk factors using medical imaging as in...
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Jianguo Zheng, Yilin Wang, Shihan Li and Hancong Chen
Accurate stock market prediction models can provide investors with convenient tools to make better data-based decisions and judgments. Moreover, retail investors and institutional investors could reduce their investment risk by selecting the optimal stoc...
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