Bibliografías temáticas / Marketing research Data processing

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Literatura académica sobre el tema "Marketing research Data processing"

Autor: Grafiati
Publicado: 27 de julio de 2024
Última modificación: 31 de julio de 2025

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Artículos de revistas sobre el tema "Marketing research Data processing"

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Ganebnykh, E. V., N. K. Savelieva, A. A. Sozinova, O. V. Fokina, and I. G. Altsybeeva. "Machine learning methods (tokenization) in marketing research." Vestnik Universiteta, no. 4 (June 17, 2024): 61–72. http://dx.doi.org/10.26425/1816-4277-2024-4-61-72.

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Field research is of particular interest in marketing because it often generates unique statistics. Closed-ended questions during data collection simplify data processing, but at the same time significantly limit the research subject depth. Open-ended questions provide a deeper understanding of respondents’ opinions, but processing responses in the form of natural language (qualitative data) is difficult and time-consuming, as it is usually done manually. Modern machine learning techniques, particularly tokenization, can be used to automate such data processing. The purpose of the study is to
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Li, Xinlin, and Xiuhui Dong. "Research on Intelligent Marketing Scheme Based on Fuzzy Mathematics Theory and Vehicular Networking Data." Journal of Computer Science and Artificial Intelligence 3, no. 1 (2025): 48–52. https://doi.org/10.54097/r9vmy462.

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With the rapid development of information technology, the Internet of vehicles has produced massive data, which has brought new opportunities for the intelligent marketing of the automobile industry. However, there is ambiguity and uncertainty in these data, which brings challenges to effective use. This paper introduces the theory of fuzzy mathematics into the processing of car networking data, aiming to construct an innovative intelligent marketing program. Through the collection of Telematics data, analysis and processing based on fuzzy mathematics, it can realize accurate market positionin
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Eshbayev, Oybek, and Laylo Yakhshiboeva. "Harnessing Big Data Processing in Computer Networks for Digital Marketing Entrepreneurship." Financial Technology and Innovation 3, no. 2 (2023): 30–36. http://dx.doi.org/10.54216/fintech-i.030204.

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This research investigates the integration of big data processing in computer networks for digital marketing entrepreneurship to optimize marketing strategies and drive business growth. By analyzing current digital marketing practices, we identify key challenges faced by entrepreneurs. Through examining successful case studies, we showcase the effectiveness of big data processing in marketing campaigns. A practical framework is developed to guide startups and small businesses in integrating big data processing into their marketing strategies, considering factors like customer behavior analysis
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Bhagya, Shree M., V. Pavana K, K. Khushbu, N. R. Deepak, and Sahu Rajesh. "Real-time Predicting Analytics for Financial Marketing Trends Using Big Data." Journal of Network Security and Data Mining 8, no. 2 (2025): 9–17. https://doi.org/10.5281/zenodo.15117499.

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<em>The growing availability of the extensive, including the Internet of Things (IoT), social media platforms, and search engines, has presented B2B (business-to-business) industrial marketing organizations with significant opportunities to use analytical methods for crafting programmatic marketing strategies in online display advertising. However, the tasks of cleansing, processing, and analyzing these large datasets come with considerable challenges, especially in the context of real-time decision-making and its broader implications. Despite these opportunities, research exploring these inte
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LARKA, Ludmila. "MARKETING RESEARCH AS AN INFORMATION BASIS FOR THE DIAGNOSTICS OF THE MARKETING ACTIVITY OF THE ENTERPRISE." Herald of Khmelnytskyi National University. Economic sciences 314, no. 1 (2023): 80–84. http://dx.doi.org/10.31891/2307-5740-2023-314-1-10.

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The article examines the correspondence of marketing research to the information needs of marketing diagnostics of the enterprise. The purpose of the article is to substantiate the expediency of a wider application of marketing research as an information basis for diagnosing the marketing activity of an enterprise in modern economic conditions. It was determined that the application of marketing research ensures the search, processing, accumulation and updating of information through the use of special methods of its processing for the purpose of making management decisions. The possibility of
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Dilfuza, Kuzikulova, and Rozikov Ravshan. "Leveraging Big Data Processing in Computer Networks for Effective Digital Marketing Strategies." Financial Technology and Innovation 3, no. 2 (2023): 23–29. http://dx.doi.org/10.54216/fintech-i.030203.

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In the rapidly evolving digital landscape, businesses are increasingly turning to digital marketing strategies to engage their target audiences effectively. The abundance of data generated through online interactions presents both opportunities and challenges in leveraging it for marketing purposes. This research investigates the potential of integrating big data processing in computer networks to optimize digital marketing strategies and enhance customer targeting. By exploring the current state of digital marketing practices and the role of computer networks in data processing, this study ai
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الدرولى, علاء الدين محمد سالم. "استخدام تقنيات الذكاء الاصطناعي في تحليل البيانات التسويقية". International Science and Technology Journal 35, № 1 (2024): 1–12. https://doi.org/10.62341/amsd1715.

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Big data has become a major resource for companies seeking competitive advantage. Using artificial intelligence (AI) techniques to analyze marketing data is an innovative approach to improving marketing strategies and increasing effectiveness. This research focuses on reviewing how artificial intelligence can be applied to analyze marketing data and extract valuable insights to improve customer experience and enhance financial performance[1]. The process begins with collecting data from various sources such as social media, websites, email, sales records, and mobile applications. The data is t
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Wu, Xudong. "Research on Cigarette Market Capacity Forecasting Based on Data Mining Methods." Transactions on Economics, Business and Management Research 11 (November 5, 2024): 519–27. https://doi.org/10.62051/28e4gx03.

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With the tobacco industry gradually stepping into the modern cigarette marketing mode of data and informationization, cigarette precision marketing will become the industry's new way of refined marketing management. Among them, precise placement is one of the important contents of cigarette precision marketing. Precision placement is based on the segmentation, quantification, and combination of brand, customer, market, and time, aiming at precisely supplying the brand to the corresponding market segments, and realizing the goal of “finding the market for the brand, finding the brand for the ma
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Oursatyev, Oleksii A. "Data Research in Industrial Data Mining Projects in the Big Data Generation Era." Control Systems and Computers, no. 3 (303) (2023): 33–53. http://dx.doi.org/10.15407/csc.2023.03.033.

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Introduction. The review material is based mainly on business intelligence (BI) solutions designed for tasks with corporate data. But all the main aspects of working with data discussed in the work are also used on data processing platforms (Data Science Platform). Many BI vendors have expanded the capabilities of their systems to perform more advanced analytics, including Data Science. They added the phrase “Data Science” to their marketing research, and the term “advanced analytics” lost some popularity in relation to corporate data. The Data Science Platform provides a comprehensive set of
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Zhou, Dan. "Tourism destination marketing strategy driven by big data." Journal of Computational Methods in Sciences and Engineering 24, no. 4-5 (2024): 2593–609. http://dx.doi.org/10.3233/jcm-247486.

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In this study, the marketing strategy of tourism destination driven by big data is deeply discussed. Firstly, the application of big data in the tourism industry and the current strategy of tourism destination marketing are analyzed, and then the research methods are designed through factor analysis and big data analysis theory. After processing and factor analysis of the collected data, the influence of big data on tourism destination marketing strategy is analyzed, and the possible optimization path is explored. At the same time, the problems and challenges encountered in this process are al
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Tesis sobre el tema "Marketing research Data processing"

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Soutar, Garron. "Target marketing : the geographical information systems approach." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53611.

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Thesis (MA)--Stellenbosch University, 2003.<br>ENGLISH ABSTRACT: Geodemographics has been used extensively as a decision-support tool in both the business sector and the market survey environment in the United States, the United Kingdom and numerous other countries. This has however not been the case in South Africa, partly because of the expense involved in capturing current and complete customer information. As an alternative to capturing all the required customer information, geodemographics has frequently made use of government census data to supplement the organisation-specific data
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Yanamandram, Venkata Krishna Kumar. "Retention of dissatisfied business-to-business services customers." Thesis, The University of Sydney, 2008. https://hdl.handle.net/2123/28954.

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The strategic importance of customer retention and the costs associated with customer switching behaviour have resulted in researchers devoting considerable attention to investigating the switching and/or staying behaviour of customers. However, relatively little attention has been devoted to investigating (1) the important deterrents to discontinuing the relationship in a single model in the business-to-business (B-to-B) service sector, and (2) the mediating factors under the condition of dissatisfaction in the B-to-B services sector. The fastest growth in services marketing today is in
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Ip, Lai Cheng. "Mining on social network community for marketing." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3950661.

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FORLEO, GIANROBERTO. "Digital AgriFood – Conversazioni online e Big Data per lo sviluppo della comunicazione strategica e progettuale del sistema produttivo marchigiano. Abstract." Doctoral thesis, Urbino, 2023. https://hdl.handle.net/11576/2710331.

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Shi, H. (Henglin). "A GQM-based open research data technology evalution method in open research context." Master's thesis, University of Oulu, 2016. http://urn.fi/URN:NBN:fi:oulu-201605221853.

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Open Research Data is gaining popularity nowadays, and various research units and individuals are interested to join this trend. However, due to variety of Open Research Data technologies, they have found it is difficult to select proper ones for their specific requirements. Thus, a method for evaluating of Open Research Data related technologies is developed in this study for researchers to select proper ones. Firstly, the theoretical knowledge of research data sharing and reusing barriers is resulted from a structured literature review. As a result, from the 19 primary studies, 96 instances
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Bilimoria, Cyrus M. "Use of computers and the Internet to facilitate export of prefabricated housing from Canada." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/mq64106.pdf.

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Lynch, Kevin John. "Data manipulation in collaborative research systems." Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184923.

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This dissertation addresses data manipulation in collaborative research systems, including what data should be stored, the operations to be performed on that data, and a programming interface to effect this manipulation. Collaborative research systems are discussed, and requirements for next-generation systems are specified, incorporating a range of emerging technologies including multimedia storage and presentation, expert systems, and object-oriented database management systems. A detailed description of a generic query processor constructed specifically for one collaborative research system
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Venkataraman, Suzanne Marie. "CAD graphics utilization in the design and marketing phases of textile/apparel product development." Thesis, Virginia Tech, 1992. http://hdl.handle.net/10919/41538.

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The purpose of this research was to identify the expertise of CAD graphics operators/managers in the design and marketing phases of textile/apparel product development. Additionally, the purposes were to determine the effect of CAD graphics on product development in the textile/apparel industry, and to identify future needs and uses of CAD graphics in the industry. A questionnaire was sent to 117 CAD graphics operators/managers. The results from the questionnaire were obtained through frequency and percentage distributions. The major findings of this study concluded that textile design and
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Joshua, Edwin (Edwin Ratnaraj) Carleton University Dissertation Management Studies. "An examination of product knowledge and information search in consumer information processing." Ottawa, 1992.

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Herzberg, Nico, and Mathias Weske. "Enriching raw events to enable process intelligence : research challenges." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6401/.

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Business processes are performed within a company’s daily business. Thereby, valuable data about the process execution is produced. The quantity and quality of this data is very dependent on the process execution environment that reaches from predominantly manual to fullautomated. Process improvement is one essential cornerstone of business process management to ensure companies’ competitiveness and relies on information about the process execution. Especially in manual process environments data directly related to the process execution is rather sparse and incomplete. In this paper, we presen
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Libros sobre el tema "Marketing research Data processing"

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Advertising, Research Foundation Key Issues Workshop (1988 New York N. Y. ). New insights into single source data: The promise and the reality, merging sales and media data, computerizing data, computerizing data bases : transcript proceedings : an ARF Key Issues Workshop, the New York Hilton, July 14, 1988. Advertising Research Foundation, 1988.

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Schellinck, Douglas Anton. Marketing research: A computer assisted approach. Dryden Press, 1987.

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Stoffels, Jörg. Der elektronische Minimarkttest. Deutscher Universitäts-Verlag, 1989.

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Seminar on the Impact of New User-Oriented Computer Facilities on Market Research (1988 Copenhagen, Denmark). Seminar on the Impact of New User-Oriented Computer Facilities on Market Research, Copenhagen (Denmark), 19th-22nd October, 1988. ESOMAR, 1988.

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PONG-YUEN. Marketing Research with R and Python. World Scientific Publishing Co Pte Ltd, 2023.

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K, Thomas Richard. Desktop marketing: Lessons from America's best. American Demographic Books, 1991.

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Clarke, Darral G. Marketing analysis and decision making: Text and cases with Lotus 1-2-3. Scientific Pr., 1987.

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Steiger, Andreas. Computergestützte Aktivierungsmessung in der Marketingforschung: Entwicklung eines Computerprogramms zur Erfassung elektrodermaler Daten und zur marketingorientierten Auswertung unter besonderer Berücksichtigung von Werbespots. P. Lang, 1988.

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Rushmore, Stephen. Hotel market analysis and valuation: International issues and software applications. Appraisal Institute, 2012.

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1962-, O'Neill John W., and Rushmore Stephen 1974-, eds. Hotel market analysis and valuation: International issues and software applications. Appraisal Institute, 2012.

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Capítulos de libros sobre el tema "Marketing research Data processing"

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Wilson, Alan I. "Secondary data, customer databases and big data analytics." In Marketing Research. Macmillan Education UK, 2019. http://dx.doi.org/10.1057/978-1-352-00112-9_3.

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Wilson, Alan I. "Analysing quantitative data." In Marketing Research. Macmillan Education UK, 2019. http://dx.doi.org/10.1057/978-1-352-00112-9_10.

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Wilson, Alan I. "Collecting Qualitative Data." In Marketing Research. Macmillan Education UK, 2019. http://dx.doi.org/10.1057/978-1-352-00112-9_5.

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Wilson, Alan I. "Collecting quantitative data." In Marketing Research. Macmillan Education UK, 2019. http://dx.doi.org/10.1057/978-1-352-00112-9_6.

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Wilson, Alan I. "Analysing qualitative data." In Marketing Research. Macmillan Education UK, 2019. http://dx.doi.org/10.1057/978-1-352-00112-9_9.

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West, Chris. "Electronic Data Collection." In Marketing Research. Macmillan Education UK, 1999. http://dx.doi.org/10.1007/978-1-349-14681-9_11.

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Wilson, Alan I. "Collecting observation data and social media listening." In Marketing Research. Macmillan Education UK, 2019. http://dx.doi.org/10.1057/978-1-352-00112-9_4.

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Baker, Michael J. "Data interpretation." In Research for Marketing. Macmillan Education UK, 1991. http://dx.doi.org/10.1007/978-1-349-21230-9_9.

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Kumar, V. "Secondary Data." In International Marketing Research. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-54650-1_5.

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Kumar, V. "Primary Data Research." In International Marketing Research. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-54650-1_7.

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Actas de conferencias sobre el tema "Marketing research Data processing"

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Ao, Dongyang, Zhenhao Xu, and Changlun Wang. "FeatureSeries: An explainable neural network for financial marketing." In 2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP). IEEE, 2024. https://doi.org/10.1109/icsidp62679.2024.10868327.

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Lu, Zhao, and Qiu Yuming. "Social Media Data Analysis in Film Marketing Strategy Optimization System Research." In 2024 IEEE 2nd International Conference on Electrical, Automation and Computer Engineering (ICEACE). IEEE, 2024. https://doi.org/10.1109/iceace63551.2024.10898443.

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Xu, Qian, and Xiaolian Li. "Research on Brand Marketing Data Mining Model Based on Feature Extraction Algorithm." In 2024 International Conference on Telecommunications and Power Electronics (TELEPE). IEEE, 2024. http://dx.doi.org/10.1109/telepe64216.2024.00083.

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Zhou, Chenyang, Sang-Bum Son, Chenming Zhu, and Xinyuan Zhu. "Research on the Application of Big Data Analysis in Green Marketing Strategies." In 2024 3rd International Conference on Artificial Intelligence and Computer Information Technology (AICIT). IEEE, 2024. http://dx.doi.org/10.1109/aicit62434.2024.10730039.

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Wang, Yimin, Lei Zhao, Ziyue Yang, et al. "Research on Data Protection of Electric Power Marketing Based on Differential Privacy." In 2024 5th International Conference on Machine Learning and Computer Application (ICMLCA). IEEE, 2024. http://dx.doi.org/10.1109/icmlca63499.2024.10753791.

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Batraga, Anda, Jelena Salkovska, Katrina Kellerte, and Liene Kaibe. "pportunities and limitations for using big data in the marketing industry." In 24th International Scientific Conference. “Economic Science for Rural Development 2023”. Latvia University of Life Sciences and Technologies. Faculty of Economics and Social Development, 2023. http://dx.doi.org/10.22616/esrd.2023.57.033.

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The use of big data in marketing in Latvia is a relatively new and unexplored field, therefore the most important information about the possibilities of using big data in marketing and the limitations related to it has not been collected so far. In order for company management and marketing specialists to be able to manage the risks arising from the use of big data and the implementation of privacy policies, it is necessary to identify them, assess the main causes and analyse the impact of risks on consumer behavior. Despite the rapid development of technology, many companies avoid the use of
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He, Qiong. "Research on the Advantage Strategy of Social Network Big Data in Marketing." In CIPAE 2021: 2021 2nd International Conference on Computers, Information Processing and Advanced Education. ACM, 2021. http://dx.doi.org/10.1145/3456887.3457106.

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Li, Jianwei, and Xi Chen. "Research on On-line Marketing Model of Agricultural Products Based on Data Mining Algorithm." In IPEC2022: 2022 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers. ACM, 2022. http://dx.doi.org/10.1145/3544109.3544346.

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Jie, Liu. "Research on Information Strategy of Social Media Short Video Marketing Co-creation Based on Data Mining." In ICIIP 2023: 2023 8th International Conference on Intelligent Information Processing. ACM, 2023. http://dx.doi.org/10.1145/3635175.3635180.

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Zhukova, M. "PLATFORMS FOR PROCESSING STREAMING DATA AND THEIR APPLICATION IN JSC «RUSSIAN RAILWAYS»." In Digital transformation in the economy of the transport complex. INFRA-M Academic Publishing LLC., 2025. https://doi.org/10.12737/conferencearticle_67893107a23a05.54689001.

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The article examines the key aspects of big data processing platforms, highlighting their importance in the modern world of business and research. Discusses key technologies and tools such as Hadoop, Apache Spark, Apache Kafka, as well as machine learning methods and analysis algorithms that allow extracting valuable information from huge volumes of data. Particular attention is paid to the application of Big Data in various industries, including marketing, trend forecasting and price optimization. Issues and challenges associated with big data processing are also addressed, including financia
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Informes sobre el tema "Marketing research Data processing"

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Ambiel, Suzanne. The Case for Confidential Computing: Delivering Business Value Through Protected, Confidential Data Processing. The Linux Foundation, 2024. https://doi.org/10.70828/iynl6589.

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As the collection, storage, and analysis of data becomes increasingly important across industries, businesses are looking for solutions that keep data secure and processes compliant with regulations. Confidential computing is one of these solutions, involving the use of a trusted execution environment that runs on shared infrastructure but processes data away from unauthorized users. This use case report interviewed members of the confidential computing community on the ways they have implemented the technology and what they believe its future holds. The report looks at the use of confidential
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti
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Cheng, Yi-Wen, and Christian L. Sargent. Data-reduction and analysis procedures used in NIST's thermomechanical processing research. National Institute of Standards and Technology, 1990. http://dx.doi.org/10.6028/nist.ir.3950.

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Volkova, Nataliia P., Nina O. Rizun, and Maryna V. Nehrey. Data science: opportunities to transform education. [б. в.], 2019. http://dx.doi.org/10.31812/123456789/3241.

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The article concerns the issue of data science tools implementation, including the text mining and natural language processing algorithms for increasing the value of high education for development modern and technologically flexible society. Data science is the field of study that involves tools, algorithms, and knowledge of math and statistics to discover knowledge from the raw data. Data science is developing fast and penetrating all spheres of life. More people understand the importance of the science of data and the need for implementation in everyday life. Data science is used in business
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Finkelstain, Israel, Steven Buccola, and Ziv Bar-Shira. Pooling and Pricing Schemes for Marketing Agricultural Products. United States Department of Agriculture, 1993. http://dx.doi.org/10.32747/1993.7568099.bard.

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In recent years there has been a growing concern over the performance of Israel and U.S. agricultural marketing organizations. In Israel, poor performance of some marketing institutions has led to radical reforms. Examples are the two leading export industries - citrus and flowers. In the U.S., growth of local market power is eliminating competitive row product prices which served as the basis for farmer cooperative payment plans. This research studies, theoretically, several aspects of the above problem and develops empirical methods to assess their relative importance. The theoretical part d
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Pasupuleti, Murali Krishna. AI-Driven Marketing Innovations: Personalization and Ethics in the Digital Era. National Education Services, 2025. https://doi.org/10.62311/nesx/rr625.

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Abstract: This article explores the transformative impact of artificial intelligence (AI) on digital marketing, focusing on strategies for delivering personalized content and ensuring ethical advertising. By leveraging AI, marketers can now analyze consumer behavior with precision, enabling targeted content, automated ad placement, and real-time adjustments that enhance user engagement and conversions. The Article examines foundational AI techniques, such as recommendation engines, predictive analytics, and natural language processing, which drive personalization at scale. Additionally, it add
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Birkemeier, William, Kent Hathaway, Michael Forte, Katherine Brodie, Patrick Dickhudt, and Annika O'Dea. Field Research Facility long-term data. Engineer Research and Development Center (U.S.), 2025. https://doi.org/10.21079/11681/49713.

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The U.S. Army Corps of Engineers has been collecting long-term coastal process data at the Engineer Research and Development Center, Field Research Facility in Duck, NC since 1974. These data include meteorological, oceanographic, topographic, and bathymetric data. Oceanographic and meteorologic data are collected and processed as real-time data and follow Qartod (https://ioos.noaa.gov/project/qartod/) real-time data quality control standards. Dune lidar data including both DEMs and hydrodynamic data are collected and processed in real. These data are stored and publicly served in netCDF forma
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Weijters, Bert. Analyzing Experimental Data in Structural Equation Models. Instats Inc., 2023. http://dx.doi.org/10.61700/zclk0a8vgkfaa706.

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This two-day workshop, 'Analyzing Experimental Data using Structural Equation Modeling', led by Bert Weijters from Ghent University, provides a comprehensive understanding of SEM and its applications in research, with a focus on using Mplus software for SEM analysis. Ideal for PhD students, professors, and professional researchers in Psychology, Education, Management, and Marketing, the seminar offers practical experience in data analysis and an official Instats certificate of completion, with ECTS Equivalent points for European students.
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Coleman, Sean, and John A. Barth. Processing and Analysis of National Oceanic and Atmospheric Administration US West Coast 2022 and 2023 Fisheries Survey Data: Exploring a Robust Data Processing Modus Operandi with Various Collection Methods. Oregon State University, 2024. http://dx.doi.org/10.5399/osu/1175.

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The National Oceanic and Atmospheric Administration‘s (NOAA) Northwest Fisheries Science Center’s (NWFSC) Fishery Resource Analysis and Monitoring Division (FRAM) performs multiple fisheries surveys aboard NOAA research vessels and chartered commercial fishery vessels along the US west coast stretching from San Diego, California, to the Strait of Juan de Fuca off northern Washington. In partnership with Fisheries and Oceans Canada, the Hake survey is extended north along the Canadian West Coast, to Haida Gwaii, British Columbia. Data from these surveys inform the implementation of the Magnuson
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Duchesne, M. J., S. G. Kang, and U. Jang. 2017 Korea-Canada-U.S.A. Beaufort Sea (offshore Yukon and Northwest Territories) research program: processing of 2-D seismic data collected during expedition ARA08C. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2019. http://dx.doi.org/10.4095/313533.

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