KH Coder

This study conducted a quantitative analysis by text mining using KH Coder on the effects of TT English classes with JTE and ALTs in junior high school on the causes of improvement/decrease in motivation to learn English among high school students (121 students). The analysis of co-occurrence networks showing the causes of motivation increase/decrease and the timing of their occurrence revealed the characteristic causes for each period. While there were common causes of increased and decreased motivation at each occurrence, the causes affecting each occurrence were different. As for the cause of increased motivation to learn, it became clear that even in TT English classes, which aim to "teach using English," there is a strong awareness of "tests" and "entrance examinations" as career paths in the background. This tendency became more pronounced as the students' grades increased, from the second year of junior high school to the third year of junior high school. In other words, the results indicate that the cause of high school entrance examinations is a significant factor in learners' motivation. As for the cause of low motivation to learn, "I do not understand (English)" was found to be associated with the cause in all the periods. Given the content in the free statements, this is likely due to insufficient understanding of the TT English classes and the difficulty of learning due to the increased complexity of the content. In other words, the sense of alienation in TT English classes for learners who are not good at English is considered a significant factor. This result was revealed by Watanabe (2021), Which complements the results of Watanabe (2021), who found that English teachers' instruction in English did not affect motivation. Considering these results, we believe that this is a result of the adverse effects of "English-based instruction" in TT English classes; it can be said that we need to reconsider how to proceed with TT English classes in the future.

La aplicación de métodos automatizados en cualquier investigación ha facilitado el trasvase de metodologías de una disciplina a otra, permitiendo realizar análisis cuantitativos a textos con estructura o semiestructurados. El objeto de este trabajo es aplicar a un dataset en lenguaje natural -castellano del siglo XVIII- métodos de análisis de la disciplina de documentación. Pretende establecer una metodología automática de análisis cuantitativo y cualitativo de textos, que permita enriquecer en el futuro las conclusiones procedentes del análisis histórico tradicional. Este estudio construye los procedimientos necesarios para poder aplicar análisis de frecuencia, extracción y clasificación de palabras y la construcción de clústeres y redes neuronales con un dataset preexistente, de características muy singulares. Permite validar diferentes utilidades de herramientas y automatizar parte del trabajo de los historiadores, para la edición de los corpus documentales de los claustros unive...

The advance of digitalization in industry is making possible that connected products and processes help people, industrial plants and equipment to be more productive and efficient, and the results for operative processes should impact throughout the economy and the environment.Connected products and processes generate data that is being seen as a key source of competitive advantage, and the management and processing of that data is generating new challenges in the industrial environment.The article to be presented looks into the framework of the adoption of Artificial Intelligence and Machine Learning and its integration with IIoT or IoT under industry 4.0, or smart manufacturing framework. This work is focused on the discussion around Artificial Intelligence/Machine Learning and IIoT/IoT as driver for Industrial Process optimization.The paper explore some related articles that were find relevant to start the discussion, and includes a bibliometric analysis of the key topics around ...

La aplicación de métodos automatizados en cualquier investigación ha facilitado el trasvase de metodologías de una disciplina a otra, permitiendo realizar análisis cuantitativos a textos con estructura o semiestructurados. El objeto de este trabajo es aplicar a un dataset en lenguaje natural -castellano del siglo XVIII- métodos de análisis de la disciplina de documentación. Pretende establecer una metodología automática de análisis cuantitativo y cualitativo de textos, que permita enriquecer en el futuro las conclusiones procedentes del análisis histórico tradicional. Este estudio construye los procedimientos necesarios para poder aplicar análisis de frecuencia, extracción y clasificación de palabras y la construcción de clústeres y redes neuronales con un dataset preexistente, de características muy singulares. Permite validar diferentes utilidades de herramientas y automatizar parte del trabajo de los historiadores, para la edición de los corpus documentales de los claustros unive...

The application of modern information technologies in the oil and gas sector is constantly developing, which facilitates the acceleration of exploration and detection of oil, the increase in oil production and reduction in risks relates to health, human safety, and the environment. The Internet of things in the oil and gas sector, like in all sectors of industry, has great prospects from an economic point of view. The article is devoted to the study of the current state and avenues of solving key problems of effective and reliable functioning of the oil and gas industry as a cyber-physical system using the Internet of things in the Azerbaijani oil company SOCAR. The main technological processes and existing opportunities for the application of information technologies in the oil and gas complex are analyzed. New approaches are proposed to solve the problems in the oil and gas complex as cyber-physical system based on the smart sensors, the Internet of things, wireless networks and cloud technologies. The implementation of the proposed model is aimed at increasing the effectiveness, resource storage, exploration reliability and durability of the oil and gas complex.

Requests to Scopus:
TITLE-ABS-KEY ( digital AND collaboration ) AND PUBYEAR > 2014 AND ( LIMIT-TO ( DOCTYPE , "ar" ) OR LIMIT-TO ( DOCTYPE , "cp" ) ) — 4,029 document results

Publication sources are largely related to — computers, information, communications, intelligent systems, digital libraries and education;
from keywords we can build the collaboration chain: humans — management — decision making by digital storage — education and teaching — big data — digital technologies — digital libraries — social networking — artificial intelligence

United States — documents/citations/total link strength; 4558/1059 = 4,3; 31835/1059 = 30,06;
Russian Federation — 82/60 = 1,36; 1055/80 = 17,58; — low citation and link strength

Universities in Canada, the USA and Europe dominate the list. The presence of two Arab universities and the Schlumberger service company is noteworthy. OnePetro
Query for collaboration digital, published between 2015 and 2019 has returned 741 results.

This paper aims to examine the progress of Industry 4.0 studies worldwide from 2012 to present. The study investigates how these studies progress using text mining and science mapping analysis method and the results are interpreted. Text mining, also referred to as text data mining, roughly equivalent to text analytics, is the process of deriving high-quality information from text. High-quality information is typically derived through the devising of patterns and trends through means such as statistical pattern learning. Using firstly text mining ,after secondly scientific mapping methods and the obtained results are interpreted. Text mining with bibliometric analysis method enables a statistical analysis of various data about scientific publications including their country, author(s), cooperation among authors, citations, references, institutions, publication date, and puts forward the general aspect of a certain discipline in the light of obtained statistical results. In other words, the purpose of scientific mapping is to demonstrate structural and dynamic aspects of a scientific research. This study introduces how many indusrty 4.0 related papers were published between the period 2012-2018 regarding SCOPUS data base and their distributions are established with respect to the scope of journals and keywords using scientific mapping analysis with Science Mapping Analysis Software Tool (SciMAT). This package program provides a comprehensive data sorting and opportunity to succeed single-handed distinctive analyis methods for scientific mapping. Moreover, VOSviewer program is also used to put forward citation patterns among authors. Thus, differences between subjects that may have an impact on the revolution of studies concentrated on the concept of industry 4.0 on SCOPUS data base, can be examined. Abstract This paper aims to examine the progress of Industry 4.0 studies worldwide from 2012 to present. The study investigates how these studies progress using text mining and science mapping analysis method and the results are interpreted. Text mining, also referred to as text data mining, roughly equivalent to text analytics, is the process of deriving high-quality information from text. High-quality information is typically derived through the devising of patterns and trends through means such as statistical pattern learning. Using firstly text mining ,after secondly scientific mapping methods and the obtained results are interpreted. Text mining with bibliometric analysis method enables a statistical analysis of various data about scientific publications including their country, author(s), cooperation among authors, citations, references, institutions, publication date, and puts forward the general aspect of a certain discipline in the light of obtained statistical results. In other words, the purpose of scientific mapping is to demonstrate structural and dynamic aspects of a scientific research. This study introduces how many indusrty 4.0 related papers were published between the period 2012-2018 regarding SCOPUS data base and their distributions are established with respect to the scope of journals and keywords using scientific mapping analysis with Science Mapping Analysis Software Tool (SciMAT). This package program provides a comprehensive data sorting and opportunity to succeed single-handed distinctive analyis methods for scientific mapping. Moreover, VOSviewer program is also used to put forward citation patterns among authors. Thus, differences between subjects that may have an impact on the revolution of studies concentrated on the concept of industry 4.0 on SCOPUS data base, can be examined.

Objective: to obtain key phrases from OnePetro on "Digital Transformation" topic (petroleum context) and compare them with key phrases from Scopus (more general context). In Scopus, we try to limit context by technical topics, see Scopus query in the text below.  The purpose of such comparison is to find nonordinary items in general context which could be useful for petroleum context.

Emotional remark: I was deeply impressed when text mining of titles and abstracts from Scopus prompted the phrase "cyber-physical systems data analytics"  (Table 2) and then in dimensions.ai the query '"cyber-physical systems" AND analytic' suggested 31 publications in 2010 and 2030 in 2018!

Results: 

- "Cyber-physical systems data analytics" could be an  attractive emergence  topic for petroleum domain based on experience in other industries. Emphasis on analytics for cyber-physical systems.
- The concept of "platform" are important for both petroleum and common domains, in petroleum domain the  "IOT" term  is more frequent but  "analysis" is less frequent. The concept "cyber-physical systems data analytics" could incorporate both "IOT" and  "analysis".
- KH Coder 3 gives the most attractive results by extracting key phrases from titles and abstracts compare to VOSviewer and authors and KW+

References:

KH Coder (by HIGUCHI Koichi) is a free software for quantitative content analysis or text mining. It is also utilized for computational linguistics. https://khcoder.net/en/

Van Eck, N.J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. *Scientometrics*, *84*(2), 523-538.

—The application of modern information technologies in the oil and gas sector is constantly developing, which facilitates the acceleration of exploration and detection of oil, the increase in oil production and reduction in risks relates to health, human safety, and the environment. The Internet of things in the oil and gas sector, like in all sectors of industry, has great prospects from an economic point of view. The article is devoted to the study of the current state and avenues of solving key problems of effective and reliable functioning of the oil and gas industry as a cyber-physical system using the Internet of things in the Azerbaijani oil company SOCAR. The main technological processes and existing opportunities for the application of information technologies in the oil and gas complex are analyzed. New approaches are proposed to solve the problems in the oil and gas complex as cyber-physical system based on the smart sensors, the Internet of things, wireless networks and cloud technologies. The implementation of the proposed model is aimed at increasing the effectiveness, resource storage, exploration reliability and durability of the oil and gas complex.