Journal articles: 'Keywords: development'

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Ueda, Shuichi. "The evolution and the development of “kansei” keywords." Library and Information Science 41 (November 25, 2000): 17–25. http://dx.doi.org/10.46895/lis.41.17.

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Hays, David L. "Keywords in American Landscape Design." Journal of Landscape Architecture 8, no. 1 (2013): 86–87. http://dx.doi.org/10.1080/18626033.2013.798938.

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Adams, Thomas, Syed Muslim Jameel, and Jamie Goggins. "Education for Sustainable Development: Mapping the SDGs to University Curricula." Sustainability 15, no. 10 (2023): 8340. http://dx.doi.org/10.3390/su15108340.

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Education for sustainable development (ESD) is a growing research field, particularly over the last decade. Measuring the level of ESD that is currently embedded in curricula is useful for planning the further implementation of sustainability-related teaching. The Sustainable Development Goals (SDGs) are a useful benchmark for sustainability topics and so this paper follows a methodology in which a keyword scanning tool was created to quantify the level of SDG coverage within a list of learning outcomes for a module. The aim of the research is to further develop this methodology and compare the results from the keyword tool with results from a survey of the academic staff who deliver the modules. SDG-related keyword lists were collected from multiple sources for a meta-analysis, examining the performance of various lists. These lists were then compiled into one list of over 12,000 SDG keywords and a team of reviewers conducted a critical analysis on the relevancy of the context in which the keywords were found when scanned. This process reduced the list to 222 “crucial keywords” and gave the keywords a relevancy label based on the STARS definitions, the sustainability tracking assessment and rating system. Finally, ChatGPT was also investigated as a method of enriching the critically analysed list with contextually relevant synonyms. A survey was carried out within the College of Science and Engineering at the University of Galway. It asked staff to rate the level of SDG coverage within their own modules, in their own opinion. This gave results which could be compared with the keyword scanning tool. The findings show success in improving the accuracy of the SDG keywords. ChatGPT added synonyms to the crucial keywords identified and this list was the most accurate out of all keyword lists used in the study. Using these keywords and the modules that staff rated in the survey, a correlation was found in the SDG trend.

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Gibson, Katherine, Rini Astuti, Michelle Carnegie, et al. "Community economies in Monsoon Asia: Keywords and key reflections." Asia Pacific Viewpoint 59, no. 1 (2018): 3–16. http://dx.doi.org/10.1111/apv.12186.

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Park, Jisoon, Gayoung Choo, Yoonmi Kim, and Sueun Ju. "Comparative Analysis of Content Characteristics of Creative Teaching Method Development Program Through Keyword Network Analysis: Based on Case of D University's Creative Teaching Method Development." Korean Association For Learner-Centered Curriculum And Instruction 23, no. 4 (2023): 903–20. http://dx.doi.org/10.22251/jlcci.2023.23.4.903.

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Objectives The purpose of this study was to investigate keywords from the main contents of the creative teaching method development program conducted at universities and analyze them through keyword network analysis to compare and explore their connection and interdisciplinary approach. The purposes of this study were to specify variables related to convergence competency, and to analyze the structural relationships among them. Methods For this purpose, the matrix between keywords was analyzed through the Krkwic program, and keyword network analysis was conducted with the NodeXL program. Results The results of this study are as follows. First, keywords related to online and non-face-to-face classes are emphasized in the creative teaching method development program of universities, and the use of various teaching methods and competency-oriented individualized approaches are prominent. Second, in the comparison by period, there was a difference in the main keywords of the creative teaching method development programs of universities, and in particular, after 2022, digital transformation and metaverse-based education were appeared. Third, there was a difference in the main keywords of creative teaching method development programs of universities by academic field. Humanities majors were ‘creative’ and ‘culture’, social science majors were ‘field’ and ‘problem-centered approaches’, education majors were various teaching methods and inovative curriculum, and natural sciences-engineering majors ‘experiments’ and ‘analysis’ were presented as the main keywords. Medicines majors emphasized a mixture of knowledge and practical applications, and arts and sports majors emphasized practical skills and feedback according to level. Conclusions It is judged that the results of this study can serve as the criteria and basic data for the development of competency-based curriculum, hi-flex class model, and convergence subjects in the course of developing teaching and learning methods in the future.

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Li, Yuyao. "A calculation method for the development trend of subject keywords." Journal of Computational Methods in Sciences and Engineering 20, no. 1 (2020): 301–12. http://dx.doi.org/10.3233/jcm-193789.

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Finelli, Cynthia J., Maura Borrego, and Golnoosh Rasoulifar. "Development of a taxonomy of keywords for engineering education research." European Journal of Engineering Education 41, no. 3 (2016): 231–51. http://dx.doi.org/10.1080/03043797.2016.1153045.

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Finelli, Cynthia J., Maura Borrego, and Golnoosh Rasoulifar. "Development of a taxonomy of keywords for engineering education research." Australasian Journal of Engineering Education 21, no. 1 (2016): 1–16. http://dx.doi.org/10.1080/22054952.2015.1133215.

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Finelli, Cynthia J., Maura Borrego, and Golnoosh Rasoulifar. "Development of a Taxonomy of Keywords for Engineering Education Research." Journal of Engineering Education 104, no. 4 (2015): 365–87. http://dx.doi.org/10.1002/jee.20101.

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Cori, Andrea. "Andrea Bernardi and Salvatore Monni (editors): The Co-operative Firm. Keywords." Development 62, no. 1-4 (2019): 205–6. http://dx.doi.org/10.1057/s41301-019-00217-0.

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Shim, Joon, and Hong-Chul Lee. "The Development of Automatic Ontology Generation System Using Extended Search Keywords." Journal of the Korea Academia-Industrial cooperation Society 10, no. 6 (2009): 1220–28. http://dx.doi.org/10.5762/kais.2009.10.6.1220.

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NAKAMURA, Kenji, Shigenori TANAKA, Yuki FUJIMOTO, and Akira TOYAMA. "DEVELOPMENT OF METHOD OF REAL-TIME KEYWORDS FOR COLLECTING TRAFFIC PHENOMENA." Journal of Japan Society of Civil Engineers, Ser. F3 (Civil Engineering Informatics) 72, no. 2 (2016): I_182—I_191. http://dx.doi.org/10.2208/jscejcei.72.i_182.

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Kim, Min-Chang. "Exploring the Keyword Network Analysis and Research Trends for Sustainable Development of Paralympic Research: Based on Changes in Classification." Applied Sciences 13, no. 5 (2023): 3050. http://dx.doi.org/10.3390/app13053050.

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This study aims to identify an overall keyword network by drawing on core keywords in Paralympic studies and analyzing the relationships. It also aims to provide information on the changes in Paralympic study trends through a time series analysis to understand change, according to the application of a new classification (evidence-based classification). This study made a bibliographic list of 1613 studies by collecting studies published between 2003 and 2022 using keyword network analysis (KNA). By refining to exclude unsuitable studies, 1404 studies and 6414 keywords were used for the analysis. As a result of analyzing entire Paralympic studies performed between 2003 and 2022, Paralympic studies were revealed to be on the rise. The entire Paralympic studies ascertained that the areas of study were mainstream and centered on the top three keywords: athlete; performance; and classification. Secondly, as a result of analyzing Paralympic study trends in a time series manner, based on 2017 when a new classification was applied, studies related to physical impairment centered on the top two keywords, athlete and performance, were mainstream in Section 1 (2003–2016). Olympic Games, performance, and wheelchairs formed detailed study areas. In the Paralympic studies in Section 2 (2017–2022), the relevant studies centered on the top two keywords, athletes and performance, were mainstream. Parasport, disability, and classification were ascertained to form detailed study areas. Through all this, the changed trend in the keyword Paralympics was confirmed. The results of this study are meaningful in that they can contribute to the expansion of the Paralympic areas of study and invigoration by exploring core keywords and providing relevant information based on the significant change point in time, including entire Paralympic study trends.

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Hong, Jae-Won, and Seung-Bae Park. "The Identification of Marketing Performance Using Text Mining of Airline Review Data." Mobile Information Systems 2019 (January 2, 2019): 1–8. http://dx.doi.org/10.1155/2019/1790429.

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We are aim firstly to extract major keywords using text mining method, secondly to identify prominent keyword from the keywords extracted from text mining analysis, and then to confirm differences in influences of the keywords which affect corporate performance. Results were as following. First, keywords have been found to show distinctive features. Since the keywords posted from the clients showed certain tendency, airlines accordingly need service management by identifying the service property through keyword analysis. Second, prominent keywords have been found out of the keyword extracted from text mining. Some of the keywords have significantly correlated with marketing performance, but others not. This implies that the company could uncover consumers’ needs through the prominent keywords and managing the properties related to the prominent keywords would help with improving corporate performance. Third, “recommend” should be treated distinctively with “satisfaction” in terms of service management through the keywords. Results suggest strategic implications to the practical business environment by analyzing keywords around the industry using text mining. We believe this work, which aims to establish common ground for understanding these analyses across multiple disciplinary perspectives, will encourage further research and development of service industry.

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Schröter, Melani, and Marie Veniard. "Contrastive analysis of keywords in discourses." International Journal of Language and Culture 3, no. 1 (2016): 1–33. http://dx.doi.org/10.1075/ijolc.3.1.01sch.

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This article suggests a theoretical and methodological framework for a systematic contrastive discourse analysis across languages and discourse communities through keywords. This constitutes a lexical approach to discourse analysis which is considered to be particularly fruitful for comparative analysis. We use a corpus-assisted methodology, presuming meaning to be constituted, revealed, and constrained by collocation environment. We compare the use of the keywords intégration/Integration in French and German public discourses about migration on the basis of newspaper corpora built from two French and German newspapers from 1998 to 2011. We look at the frequency of these keywords over the given time span, group collocates into thematic categories, and discuss indicators of discursive salience by comparing the development of collocation profiles over time in both corpora as well as the occurrence of neologisms and compounds based on intégration/Integration.

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G., Pushpa, and Mutyalamma G. "Contiguous Neighbour Exploration through Keywords." International Journal of Trend in Scientific Research and Development 2, no. 1 (2017): 1352–57. https://doi.org/10.31142/ijtsrd8235.

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Presently days there are numerous android applications that mean to discover articles fulfilling both spatial predicate and a predicate on their related writings. In this paper, for discovering closest accommodation a basic arrangement is presented which depends on IR2 tree 1 .IR2 tree incorporates couple of insufficiencies that influence its productivity 2 . To build the proficiency another technique called spatial reversed list 1 is presented that extends the standard modified record to address multidimensional data. This new SI file technique accompanies calculations which will answer closest neighbor questions with essential words progressively. As confirmed by trials, this anticipated system performs the IR2 tree in question time response essentially. Customary reflection inquiries, as change hunt and closest neighbor recovery, include singularly conditions on objects geometric properties. Instantly the best determination to such inquiries is predicated on the IR2 tree, which, as indicated amid this paper, highlights a couple of inadequacies that truly effect its power. Incited by this, we have a tendency to build up a substitution access procedure known as the deliberation reversed file that extends the standard altered list to address level learning, and accompanies calculations that may answer closest neighbor questions with pivotal words progressively. As confirmed by examinations, the anticipated procedures outgo the IR2 tree being referred to inert period extensively, ordinarily by a component of requests of greatness. G. Pushpa | G. Mutyalamma "Contiguous Neighbour Exploration through Keywords" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: https://www.ijtsrd.com/papers/ijtsrd8235.pdf

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Tang, Chong-Ti, Yan-Hai Wang, Wen-Feng Peng, Liang Tang, and Dong Chen. "ALVEOLAR ECHINOCOCCUS SPECIES FROM VULPES CORSAC IN HULUNBEIER, INNER MONGOLIA, CHINA, AND DIFFERENTIAL DEVELOPMENT OF THE METACESTODES IN EXPERIMENTAL RODENTS." Journal of parasitology 92, no. 4 (2006): 719–24. https://doi.org/10.1645/GE-3526.1.

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Adults of alveolar Echinococcus species with different uterine structures were collected from Vulpes corsac in the Hulunbeier Pasture of Northeastern China in 2001. They were Echinococcus multilocularis Leuckart, 1863 (type No. 3, similar to E. m. multilocularis), with vaselike uterus; Echinococcus cf. sibiricensis Rausch et Schiller, 1954 (type No. 1), with pyriform uterus; and Echinococcus sp. (type No. 2) with spherical uterus at segment top. The metacestode development in rodents also differed among those 3 parasites. In the case of E. multilocularis (type No. 3), many germinal cells grew on the inner surface of early cysts, most of which metastasized into host tissue to form brood vesicles or from the germinal cell layer on the inner surface of the vesicle wall. Cells also had an appearance of proliferating by means of alveolar buds from alveolar tissue that developed outward to form new alveolar foci. In Echinococcus cf. sibiricensis (type No. 1), the formation of alveolar vesicles was due to the metastasizing of germinal tissue into host tissue; protoscoleces grew in the center of alveolar vesicles. In type No. 2 (Echinococcus sp.), the formation of the alveolar vesicle was by multiplication of germinal cell layers on the inner surface of alveolar cysts; protoscoleces grew from the germinal cell layer and mesh in the vesicles. On the basis of uterine structure and on differences in development of metacestodes in experimental rodents, we propose that the 3 types of Echinococcus represent 3 independent species: E. multilocularis, Echinococcus sibiricensis, and Echinococcus sp. (type No. 2-as yet under study).

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Antopol’skii, A. B., V. N. Beloozerov, N. E. Kalenov, N. N. Shaburova, and M. M. Yakshin. "The Development of a Semantic Network of Keywords Based on Definitive Relationships." Scientific and Technical Information Processing 44, no. 4 (2017): 261–65. http://dx.doi.org/10.3103/s0147688217040062.

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Tsao, Yung Chung, Kevin Chihcheng Hsu, and Yin Te Tsai. "The Architecture for Solving the Cross-Domain Keywords During New Product Development." Advanced Materials Research 605-607 (December 2012): 497–500. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.497.

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The team-members for the new product development (NPD) are recruited from different departments in the enterprises. So the team-members in the design teams range from novices to experts in NPD. The juniors developer in the design project team lack more successful product-design experiences as their seniority and skills. Therefore, those developers always query and search their problems with the limited terminology via the information systems or websites. So the results of the querying and searching always are limited to the similar domain-knowledge. The new product development (NPD) involves multidisciplinary knowledge such as accumulated experiences of knowledge-workers, and different technical and legal documents. The information systems (IS) facilitating the NPD processes often include document-based knowledge management system (KMS), Product Data Management (PDM), Product Lifecycle Management (PLM) systems etc. With these different systems, novices at various stages of NPD processes often have problems to use the exact and suitable keywords to query the problems from those information systems. The study proposes a case-based reasoning to construct a hierarchical knowledge model to record knowledge-workers’ experiences and to store the information of experiences and the recommendation of experts. The aim of the study is that the proposed architecture can query the information scattered in different information systems by using their individual-domain terminology and retrieve the better fitted results of the querying.

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Fakhri, Mahendra, Sam'Un Jaja Raharja, Margo Purnomo, and Rivani Rivani. "The development of servant leadership research: A brief bibliometric review." Journal of Infrastructure, Policy and Development 8, no. 7 (2024): 3730. http://dx.doi.org/10.24294/jipd.v8i7.3730.

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This study presents a simple yet informative bibliometric analysis of servant leadership literature, aiming to provide a basic overview of its scholarly landscape and identify general trends. We conducted this analysis in September 2023. We focused solely on the Scopus database to understand the current state of servant leadership research. Despite extensive search efforts, we found no similar bibliometric analyses within the servant leadership domain during our study period. Therefore, our focus is to present a brief and straightforward analysis of current research in this field based on identification trends over time, connection between co-occurrence of author keywords, most and less discussed keyword, and areas of high and low concentration. Our findings show an increase in scholarly publications, reflecting a growing acknowledgment of servant leadership’s relevance in management practices. Interconnected keywords and themes such as leadership, transformational leadership, job satisfaction, work engagement, authentic leadership, ethical leadership, organizational citizenship behavior, trust, and leadership development emerge prominently. Additionally, less-discussed keywords such as accountability, core self-evaluations, educational leadership, stewardship, customer orientation, and psychological well-being provide alternative perspectives on these research results. While acknowledging limitations inherent in our bibliometric research, such as potential publication bias and language restrictions, our study offers valuable insights for scholars and practitioners interested in this area.

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Mulligan, Martin, Wendy Steele, Lauren Rickards, and Hartmut Fünfgeld. "Keywords in planning: what do we mean by ‘community resilience’?" International Planning Studies 21, no. 4 (2016): 348–61. http://dx.doi.org/10.1080/13563475.2016.1155974.

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Sindi, Emilia. "DEVELOPMENT OF E-SERVQUAL DIMENSIONS FOR BANKING." Praxis : Jurnal Sains, Teknologi, Masyarakat dan Jejaring 6, no. 2 (2024): 178–94. http://dx.doi.org/10.24167/praxis.v6i2.11630.

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E-SERVQUAL is a tool used to measure customer service quality. This research aims to conduct a literature review on the dimensions and indicators of service quality specifically used for digital banking services. The research method has 3 stages, namely : First, Planning contains the Explanation of Research Objectives, Second, Research Identification contains the Determination of Criteria and Selection of Research Articles, Third, Selection of Basic Studies contains Selection of research articles using predetermined criteria keywords. The keyword used is "e-SERVQUAL". There are 2 selection criteria, namely the exclusion criteria, which include : Research journals cannot be downloaded, Research journals are not full text, Research journals that use e-SERVQUAL are not in the banking sector and Inclusion criteria are, Research articles that answer research questions, Research articles identified using keywords. The results of this study are : e-SERVQUAL dimensions specifically for the quality of banking services are Efficiency, Reliability, Responsiveness, Personal needs, Site organization, Fulfilment, Security/trust, Ease of use and Privacy. Not all journals regarding banking e-SERVQUAL include indicators and dimensions. Of the 10 journals studied, only 3 journals produced a significant positive value between the e-SERVQUAL variable and e-Customer Satisfaction.

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Azhari, Septian Cahya, Ceceng Saepulmilah, and Tasya Meita. "Development of Literature Academic Anxiety From 2002-2021: A Bibliometric Analysis Approach." Indonesian Journal Education 1, no. 1 (2022): 1–10. http://dx.doi.org/10.56495/ije.v1i1.171.

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Bibliometric analysis is a statistical tool that is useful for visualizing developments in the field of science to be used as a tool in finding research gaps. This study aims to create a visualization map on the topic of academic anxiety research which includes the development of keywords and popular authors. The database in this study was obtained from dimensions.ai and took data from 2002 to 2021 which was then divided into two ten-year periods. The results of the bibliometric analysis from 2002-2011 contained 6 clusters and 66 keyword items and citation authors with 26 clusters and 59 items. Meanwhile, the results of the bibliometric analysis of the database from 2012-2021 contained 66 items and 8 clusters for popular keywords, while 21 items and 11 clusters for citation authors.

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Cahyani, Vika Puji, and Dewiyanti Fadly. "The Development of Ethnoscience in Chemistry Learning in Indonesia: A Bibliometric Analysis of Literacy and Cultural Relevance." Jurnal Studi Guru dan Pembelajaran 7, no. 3 (2024): 1201–11. https://doi.org/10.30605/jsgp.7.3.2024.4797.

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The main issue in this study is the lack of comprehensive understanding and mapping of the patterns and progress in ethnoscience research within the context of chemistry education in Indonesia. Investigating the patterns and advancements in ethnoscientific research in Indonesian chemistry education is the aim of this study. This study uses a bibliometric technique and is quantitative descriptive in nature. he stages include Selection of Topic and Research Objectives, Data Collection, Data Cleaning and Processing, Data Analysis, Data Visualisation, Interpretation and Discussion. Data collection was carried out by searching for journal articles indexed by Google Scholar through Publish or Perish (PoP) with the keyword ‘chemical ethnoscience’. Data from Publish or Perish (PoP) was filled in and completed in the author's keywords section manually using Mendeley desktop software then integrated into VOSviewer software for mapping. The results of the analysis of keyword mapping in Google Scholar indexed scientific articles from 2014-2024, it is known that in the last 10 years, there are 137 keywords that are interrelated. The top 7 keywords with the strongest links include: ethnoscience (40), chemical literacy (9), chemistry learning (6), chemistry (4), problem based learning (4), local wisdom (3), STEM (3). Recent keywords in chemistry education that are still rarely discussed in scientific articles are podcast-based ethnoscience, common knowledge construction, chemical bonding, CKCM learning model, Flipped Classroom, knowledge, references, implementation, culture, character values, ethnoscience-based chemistry, need analysis, independent curriculum, 4-D development.

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Octavially, Reynaldi Prama, Rosa Reska Riskiana, Kusuma Ayu Laksitowening, Dana Sulistyo Kusumo, Monterico Adrian, and Nungki Selviandro. "Test Case Analysis with Keyword-Driven Testing Approach on Angkasa Website Using Katalon Studio Tools." Ultimatics : Jurnal Teknik Informatika 13, no. 2 (2022): 134–41. http://dx.doi.org/10.31937/ti.v13i2.2391.

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Abstract— Testing a software is an important stage of a series of software development. Functional testing of each feature on the Angkasa website is intended to try out the function to match the required specifications. To achieve a functional test result, there are elements of features on the web page that require keywords. These keywords are used to perform actions or actions in running a web page, these keywords will help in making Test Cases for the testing process. Because it takes the right keywords to test on the web. To overcome this problem, this study analyzes the use of the Keyword Driven Testing approach for making Test Cases through the Katalon Studio tools. Keyword Driven Testing is one of the concepts in ISO/IEC/IEEE 29119, namely Keyword Driven Testing in The Test Design Process. The results of the analysis show that making Test Cases with Keyword Driven testing is easier to understand and is fully supported by the Katalon Studio tools. However, when creating test cases, not all keywords can be added automatically, so they need to be added manually.

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Baskici, Cigdem, and Yunus Gokmen. "Evaluating the Conceptual Development of Healthcare Leadership Literature with a Network Approach." European Conference on Management Leadership and Governance 20, no. 1 (2024): 29–35. http://dx.doi.org/10.34190/ecmlg.20.1.2939.

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Analysis of co-word networks can be used in discovering themes that reflect both the cognitive structure of the scientific field and the gap in the field, besides following the conceptual change in the scientific field. This study aims to reveal the development of the "healthcare leadership" literature, which started to attract more attention with the COVID-19 Pandemic. The authors searched for all articles written in English between 2020 and 2023 in Web of Science Core Collection and Scopus databases with the key phrases “healthcare leadership”, “healthcare leader”, “health care leadership” or “health care leader” as the query to search the following fields within a record: Title, Abstract, and Author Keywords. 134 articles in the Web of Science database and 585 articles in the Scopus database were reached. Duplicate articles (271) were first eliminated, then articles with one keyword (12) were excluded since one keyword is not appropriate for network analysis. Consequently, 1,360 unique keywords of 2,372 keywords from 436 articles were entered into the analysis scope. A network of whole years was constructed based on word frequency co-occurrence matrices with keywords from all years included, besides a network for each year. Descriptive statistics such as network density, connected components, and total number of ties were calculated for the whole network. Centrality measures were calculated for the network of whole years and each year. Network density and number of the connected components were found as 0.012 and 27 respectively. Leadership, COVID-19/Pandemic, healthcare, healthcare leadership, qualitative research, and nurse were the first six concepts with the highest degree centrality, betweenness centrality, and eigenvector centrality for the network of whole years. Thus, it was possible to see both the general view of the cognitive structure of the healthcare leadership literature and conceptual change in the literature over the years. The findings have the potential to provide important clues for trends and future research directions in this field.

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Arie Edytia, Muhammad Heru, Zulhadi Sahputra, and Mirza Mirza. "ARCHITECTURAL DESIGN KEYWORDS OF INCEPTION SPACE." Malaysian Journal of Sustainable Environment 6, no. 2 (2019): 61. http://dx.doi.org/10.24191/myse.v6i2.8689.

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This paper explains the idea of inception space from Inception (2010), a movie directed by Christopher Nolan, to explore the inception space potential in designing architectural space. Inception space is an architectural space design mechanism that translates the essential experience of space users as an effort to implant idea in the form of positive emotions. In other words, the architectural space is a medium of inception to a space user or a target (mark). The main purpose of inception space design is to affect the target (mark) by planting the idea ‘secretly’. The target is unaware of the intervention and considers the idea presented itself. This process becomes the beginning of an idea to grow in one's mind the beginning of mindset and behavior change. In other words, architects or planners can apply this mechanism to design and influence users so that the design success rate can be improved. The main design keywords as part of the inception process are perception, memory, scenario, layer, and labyrinth. The development of design methods of inception space can be explored and applied to different targets and contexts by applying these design keywords. For example, this design mechanism can be applied to people with dementia who experience memory and visuospatial deficit through wayfinding programming.

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Mandal, Dr. Rajat Rabindranath. "Waste Management for Sustainable Development." International Journal of Advance and Applied Research 6, no. 25 (2025): 139–43. https://doi.org/10.5281/zenodo.15294280.

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<strong>Abstract:</strong> The waste management consist of management of all resources and processes for proper and suitable handling of various waste materials, from waste maintenance of transport trucks with dumping facilities for environmental regulations and health codes. The performance of all those activities with suitable action required to manage various waste materials from its inception or starting to its ending or final disposal. This research paper focuses on the process of waste management and related activities for sustainable development.

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Kim, hyunjun, jinah Kim, and sangsoo Lee. "Blended Learning Research Trend Analysis before and after COVID-19 Through Language Network Analysis." Korean Association For Learner-Centered Curriculum And Instruction 22, no. 15 (2022): 711–30. http://dx.doi.org/10.22251/jlcci.2022.22.15.711.

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Objectives This study intends to suggest the development and follow-up research direction of blended learning research by analyzing the trends and representative research topics of each period of blended learning related papers. Methods Keywords were collected and refined for papers related to blended learning from 2011 to October 2021 in the journal database. The keywords included in the study before and after COVID-19 were analyzed for frequency and degree centrality, and the results were visualized. Results As a result of quantitative change trend analysis, it was confirmed that there is a rapid increase after COVID-19. As a result of keyword analysis, the frequency and importance of keywords related to experimental research verifying the effectiveness of blended learning itself were high in the research prior to COVID-19. In research after COVID-19, it was confirmed that the frequency and importance of keywords related to development research such as class model development in non-face-to-face class situations were high. ‘Effectiveness Verification’ and ‘Experimental Research’, ‘Instructional Model Development’ and ‘Development Research’, ‘Experimental Research’ and ‘Academic Achievement’, ‘COVID-19’ and ‘Non-face-to-face Class Situation’ was confirmed to have a high relevance. As a result of the centrality analysis, before COVID-19, research was being conducted centered on the keywords of ‘Effectiveness Verification’, ‘Experimental Research’, and ‘University’. After COVID-19, research has been focused on the keywords of ‘Development Research’, ‘Mixed Learning Environment’, and ‘University’. In addition, it was confirmed that the keywords were grouped into four themes. Conclusions Although blended learning related papers have achieved steady quantitative growth over the past 10 years, previous studies have a limitation in that the proportion of microscopic studies focused on effectiveness verification and instructional model and program development was high. For the balanced development of blended learning research, it seems necessary to understand blended learning from a more macroscopic point of view in future research and field application, and to approach systematically from the instructional design stage, which is the basis of class operation.

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Chu, sung-hee. "Analysis of Domestic Music Education Research Trends Using Text Mining: Focused on the Impact of the Fourth Industrial Revolution on Music Education." Korean Society of Music Education Technology 57 (October 16, 2023): 1–23. http://dx.doi.org/10.30832/jmes.2023.57.1.

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The purpose of this study is to understand the impact of the Fourth Industrial Revolution on music education by analyzing research trends in the field. To this end, we extracted research papers from the Research Information Sharing Service (RISS) using keywords such as 'Fourth Industrial Revolution,' 'Artificial Intelligence,' 'Big Data,' 'Virtual Reality,' 'Augmented Reality,' and 'Deep Learning.' After collecting the titles, abstracts, and keywords of these papers, we performed text-mining analyses, including keyword analysis, network centrality analysis, and LDA topic modeling. The results of this study are as follows: First, in the TF and TF-IDF analyses, 'Artificial Intelligence' and 'Music' were identified as the most influential keywords, and 'Program-Development' emerged as the most frequently co-occurring keyword combination. Second, the centrality analysis revealed that the keywords 'Music,' 'Education,' and 'Artificial Intelligence' had nearly equal importance. Third, the topics extracted through LDA topic modeling included subjects such as AI-based music education programs, content development, and the future direction of music education in relation to AI platform technologies.Further research is needed to explore the measures and effectiveness of practical applications that link various technologies of the Fourth Industrial Revolution with teaching and learning.

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Verma, Amit, and Pardeep Kaur. "Design an Algorithm for Software Development in Cbse Environment using Feed Forward Neural Network." IAES International Journal of Artificial Intelligence (IJ-AI) 4, no. 2 (2015): 53. http://dx.doi.org/10.11591/ijai.v4.i2.pp53-61.

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A In software development organizations, Component based Software engineering (CBSE) is emerging paradigm for software development and gained wide acceptance as it often results in increase quality of software product within development time and budget. In component reusability, main challenges are the right component identification from large repositories at right time. The major objective of this work is to provide efficient algorithm for storage and effective retrieval of components using neural network and parameters based on user choice through clustering. This research paper aims to propose an algorithm that provides error free and automatic process (for retrieval of the components) while reuse of the component. In this algorithm, keywords (or components) are extracted from software document, after by applying k mean clustering algorithm. Then weights assigned to those keywords based on their frequency and after assigning weights, ANN predicts whether correct weight is assigned to keywords (or components) or not, otherwise it back propagates in to initial step (re-assign the weights). In last, store those all keywords into Repositories for effective retrieval. Proposed algorithm is very effective in the error correction and detection with user base choice while choice of component for reusability for efficient retrieval is there. To check the results of our algorithm based on factors like accuracy, precision and recall compare with existing technique i.e. integrated classification scheme for retrieval of components based on keyword search and results are so encouraging.

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김미숙. "A historical review of the six keywords of the german elite sport development." Korean Journal of Sport Science 28, no. 3 (2017): 698–711. http://dx.doi.org/10.24985/kjss.2017.28.3.698.

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Coninx, Nele, Karel Kreijns, and Wim Jochems. "The use of keywords for delivering immediate performance feedback on teacher competence development." European Journal of Teacher Education 36, no. 2 (2013): 164–82. http://dx.doi.org/10.1080/02619768.2012.717613.

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Appanna, N. Jirnal, and Ashok Managanvi Dada. "Hazard Mitigation And Sustainable Community Development." Journal of Research & Development' 14, no. 20 (2022): 12–15. https://doi.org/10.5281/zenodo.7524712.

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Having a plan in place during times of crisis is increasingly seen as essential for resilient community development by many experts. It has been suggested that emergency management should also include environmental protection and city planning. The link between risk management and urban design is essential for building long-lasting communities that can weather any kind of emergency. It has been difficult to bring this theoretical link into practice. To address this issue and clarify the relationship between risk mitigation and neighborhood improvement, emergency management as a field has to undergo significant revision and growth. Furthermore, barriers to enforcing this link must be assessed and eliminated. There are real actions one may take to initiate this crucial process.

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Pan, Teng, Bing Liu, Yan Shuang Liu, and Yun Jie Li. "Design and Implementation of Keywords Extraction and Management System Based on Java Platform." Advanced Materials Research 765-767 (September 2013): 1596–99. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.1596.

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This essay discusses the design and implementation of a keywords extraction and management system based on java platform. By using development methodology of domain engineering, the essay focuses on key technology of keywords extraction system and outline some ideas of the software architecture, in which identify basic principles and requirements of the development of keywords extraction and management system. The system functions are implemented with Java language in Eclipse environment. The system is featured with expandability, reliability, suitability and friendly interface demonstrated in application test of engineering practice and plays positive practical value in keywords extraction and management in technical domain.

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Liwafa, Arizal, Bagong Suyanto, and Zuyyinna Choirunnisa. "Sustainable Competitive Advantage: A Literature Review and Future Research." RSF Conference Series: Business, Management and Social Sciences 3, no. 3 (2023): 428–39. http://dx.doi.org/10.31098/bmss.v3i3.707.

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Sustainable competitive advantage (SCA) is very important for companies in analyzing the quality of human resources and the company's environment that continues to change. Besides that, SCA is also able to provide short-term revenue increases and product advantages to customers. This research aims to map the topic of SCA in various scientific fields by visualizing it into a landscape map to see its development and novelty using bibliographic data. Thus, the novelty of research related to strategic management from previous studies can be known with certainty. This research is quantitative research with a descriptive approach. Documentation and literature studies in this study were obtained through the Scopus database with the keyword "sustainable competitive advantage". Bibliometric techniques were used for analysis and processed using Vosviewer software. The results of this study indicate that from 2017-2023, there are 205 articles related to the keywords used, the results of the Vosviewer analysis show 168 keywords that are connected to the keywords used, keywords that are widely used related to the keywords in this study are SCA, Sustainability, Sustainable Development, Innovation, while keywords that are rarely used are SME, Supply Chain, Competitive Strategy, these rarely used keywords can be used as a choice of future research topics.

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Tranbenkova, NA. "к экологиИ ECHINOCOCCUS MULTILOCULARIS (LEUCKART, 1863) И Е. GRANULOSUS (BATSCH, 1786) НА КАМЧАТСКОМ ПОЛУОСТРОВЕ". Meditsinskaia parazitologiia i parazitarnye bolezni, № 1 (7 червня 1992): 45–7. https://doi.org/10.5281/zenodo.15092307.

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Some aspects of dwelling of Echinococcus multilocularis and E. granulosus populations in the Kamchatka Peninsula were considered. Transformation of their natural foci to natural synanthropic due to enrichment of mammalian fauna, increased human density and rural development was noticed. Main quantitative characteristics of infectivity of the worm definitive and intermediate hosts are presented using literature and the author's own data. A correlation was noted between host density and their infectivity with Echinococcus.

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Rauf, AR, M. Marimin, P. Nurhayati, and S. Suprehatin. "Food Loss and Waste in Potato Supply Chains: A Systematic Literature Review and Framework Development Approach." IOP Conference Series: Earth and Environmental Science 1417, no. 1 (2024): 012023. https://doi.org/10.1088/1755-1315/1417/1/012023.

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Abstract The supply chain structure of the potato-based food industry in Indonesia is not yet optimal, characterized by problems with the continuity of processed potato production and limited supply of potatoes to certain varieties. Food Loss and Waste of potatoes tends to be high, while food loss and waste mapping along the potato supply chain in Indonesia are not yet available. This study aims to identify the research gap of food loss and waste in potato supply chain, to determine the future research position, and to develop the future research framework. Systematic literature review was conducted to identify the research gap. At first, bibliometric analysis was conducted using Harzing’s Publish or Perish and VOSviewer software to produce the network visualization of research keywords to identify the gaps. Secondly, the most frequent keywords were used as the basis to review the relevant previous studies to determine the future research position. “Sustainability” is the main keyword that appears which has a close relationship with “food supply chain”, “supply chain management”, and “food industry”, while “potato” is not the most frequent keyword. The gap identified is the absence of keywords related to “soft system dynamics”, “food loss”, “food waste”, “food loss and waste”, and “life cycle assessment” which could be a potential novelty. To connect the dots of previous studies and produce a novelty, the future research will be positioned around the topic of sustainable potato supply chain modelling to reduce food loss and waste.

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Toledo, Rubens C., Gretta L. A. F. Arce, João A. Carvalho, and Ivonete Ávila. "Experimental Development of Calcium Looping Carbon Capture Processes: An Overview of Opportunities and Challenges." Energies 16, no. 9 (2023): 3623. http://dx.doi.org/10.3390/en16093623.

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Global warming might be mitigated if emissions were interrupted through carbon capture technologies, as there is a significant amount of comprehensive studies on them. An outline of the main gaps and trends of a technology is critical for further development. In this context, this study provides an overview of calcium looping carbon capture processes that have proven their potential and commercial viability. A bibliometric analysis is conducted on both Scopus and Web of Science database by seeking the keywords “calcium looping”, “co2 capture”, and “fluidized bed” in titles, abstracts, and keywords. Word selection was based on a list of relevant papers on the topic. These items of data have been processed and analyzed based on the number of publications and citations by emphasizing recent publication evolution, journal influence, the use of specific keywords, and co-citation. Results reveal that the European Union (EU) leads the rankings on the topic, followed by Canada. Keyword choice might have affected the number of citations. Recent studies used limestone as a sorbent and a dual fluidized bed reactor with a calciner or resistance depending on its size. Most studies are focused on technology scale-up. Although scale-up seems to be a priority, multiple studies are designed to assess the effect of steam generation and SO2 on the process.

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Vandana, Priyanka Dungdung, and Priy Pursotam Ashutosh2 Dr. "Language Development in Preschool Children." 'Journal of Research & Development' 15, no. 1 (2023): 1–4. https://doi.org/10.5281/zenodo.7575618.

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A child's linguistic development follows the same pattern as their physical development. All parents should keep an eye on their children at this age since it has a profound impact on how their children learn. Parents should constantly work to maximize their children's potential since they have a major impact on their children's learning outcomes. Given its purpose, the capacity to communicate with others is at the heart of language. Language comprehension and spoken language are quite different in many ways. All kinds of communication, whether spoken, written, visually shown, or communicated via facial expressions and body language are considered languages. But spoken language is the most significant and extensively utilized method of communication since it is the most direct and effective. The purpose of this research is to provide a detailed account of the progression of scholastic literacy in very young children. The findings demonstrate that numerous competing hypotheses, including natavism, cognitivism and behaviourism, have raised serious doubts about how language evolved. The most remarkable thing for parents is hearing their young kid pronounce their first word, which is easier for children who have early linguistic abilities. The health, IQ, socioeconomic status, family connection, family size, peer interactions and personality of a child are only few of the aspects that influence their linguistic development.

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Böhme, Marcus H., André Gröger, and Tobias Stöhr. "Searching for a better life: Predicting international migration with online search keywords." Journal of Development Economics 142 (January 2020): 102347. http://dx.doi.org/10.1016/j.jdeveco.2019.04.002.

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Akerke, Akanova, Ospanova Nazira, Kukharenko Yevgeniya, and Abildinova Gulmira. "DEVELOPMENT OF THE ALGORITHM OF KEYWORD SEARCH IN THE KAZAKH LANGUAGE TEXT CORPUS." Eastern-European Journal of Enterprise Technologies 5, no. 2 (101) (2019): 26–32. https://doi.org/10.15587/1729-4061.2019.179036.

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The issue of semantic text analysis occupies a special place in computational linguistics. Researchers in this field have an increased interest in developing an algorithm that will improve the quality of text corpus processing and probabilistic determination of text content. The results of the study on the application of methods, approaches, algorithms for semantic text analysis in computational linguistics in international and Kazakhstan science led to the development of an algorithm of keyword search in a Kazakh text. The first step of the algorithm was to compile a reference dictionary of keywords for the Kazakh language text corpus. The solution to this problem was to apply the Porter (stemmer) algorithm for the Kazakh language text corpus. The implementation of the stemmer allowed highlighting unique word stems and getting a reference dictionary, which was subsequently indexed. The next step is to collect learning data from the text corpus. To calculate the degree of semantic proximity between words, each word is assigned a vector of the corresponding word forms of the reference dictionary, which results in a pair of a keyword and a vector. And the last step of the algorithm is neural network learning. During learning, the error backpropagation method is used, which allows a semantic analysis of the text corpus and obtaining a probabilistic number of words close to the expected number of keywords. This process automates the processing of text material by creating digital learning models of keywords. The algorithm is used to develop a neurocomputer system that will automatically check the text works of online learners. The uniqueness of the keyword search algorithm is the use of neural network learning for texts in the Kazakh language. In Kazakhstan, scientists in the field of computational linguistics conducted a number of studies based on morphological analysis, lemmatization and other approaches and implemented linguistic tools (mainly translation dictionaries). The scope of neural network learning for parsing of the Kazakh language remains an open issue in the Kazakhstan science. The developed algorithm involves solving one of the problems of effective semantic analysis of the text in the Kazakh language

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Grybauskas, Andrius, Vaida Pilinkienė, Mantas Lukauskas, Alina Stundžienė, and Jurgita Bruneckienė. "Nowcasting Unemployment Using Neural Networks and Multi-Dimensional Google Trends Data." Economies 11, no. 5 (2023): 130. http://dx.doi.org/10.3390/economies11050130.

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This article forms an attempt to expand the ability of online search queries to predict initial jobless claims in the United States and further explore the intricacies of Google Trends. In contrast to researchers who used only a small number of search queries or limited themselves to job agency explorations, we incorporated keywords from the following six dimensions of Google Trends searches: job search, benefits, and application; mental health; violence and abuse; leisure search; consumption and lifestyle; and disasters. We also propose the use of keyword optimization, dimension reduction techniques, and long-short memory neural networks to predict future initial claims changes. The findings suggest that including Google Trends keywords from other dimensions than job search leads to the improved forecasting of errors; however, the relationship between jobless claims and specific Google keywords is unstable in relation to time.

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Al-Sabi, M. N. S., P. M. Jensen, M. U. Christensen, and C. M. O. Kapel. "Morphological and molecular analyses of larval taeniid species in small mammals from contrasting habitats in Denmark." Journal of Helminthology 89 (June 7, 2015): 112–17. https://doi.org/10.1017/S0022149X13000680.

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Taeniid infections in intermediate hosts manifest themselves as extraintestinal larval stages which, in early development, lack species-specific characteristics. The inability to distinguish infections of zoonotic importance such as Echinococcus multilocularis from other taeniid infections that have mainly veterinary significance stimulated the development of species-specific molecular diagnostics. In this study, the prevalence of taeniid infections in potential intermediate hosts was evaluated using both morphological diagnosis and a newly described multiplex polymerase chain reaction (PCR) for species determination. Small mammals (N= 719) were trapped in three different types of habitats in north-east Zealand, Denmark. The sensitivity of the multiplex PCR (90.5%) exceeded that of morphological examination (57.9%) for identifying 95 taeniid infections. The use of the multiplex PCR resulted in higher prevalence rates due to improved detection of immature liver infections with Hydatigera taeniaeformis and Versteria mustelae, but did not affect the observed prevalence rates of peritoneal metacestodes of Taenia polyacantha. The prevalence of taeniid infections showed a significant difference according to habitat type, potentially identifying a ‘sylvatic’ transmission and an ‘urban’ transmission, with marked variation among different taeniid species. Versteria mustelae and T. polyacantha were more prevalent in rural forests, while infections with H. taeniaeformis were dominant in urban parks/forests and in residential and farm gardens. The multiplex PCR facilitated a better utilization of wildlife samples by yielding a higher number of definitive diagnoses of ambiguous taeniid infections in liver lesions, allowing for more accurate epidemiological data and, hence, a more accurate risk assessment.

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Wu, Hao, Degen Huang, and Xiaohui Lin. "Reinforcement Learning-Based Intent Classification of Chinese Questions About Respiratory Diseases." Applied Sciences 15, no. 7 (2025): 3983. https://doi.org/10.3390/app15073983.

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The intent classification of Chinese questions about respiratory diseases (CQRD) can not only promote the development of smart medical care, but also strengthen epidemic surveillance. The major core of the intent classification of CQRD is text representation. This paper studies how to utilize keywords to construct CQRD representation. Based on the characteristics of CQRD, we propose a keywords-based reinforcement learning model. In the reinforcement learning model based on keywords, we crafted a word frequency reward function to aid in generating the reward function and determining keyword categories. Simultaneously, to generate CQRD representations using keywords, we developed two models: keyword-driven LSTM (KD-LSTM) and keyword-driven GCN (KD-GCN). The KD-LSTM incorporates two methods: one based on word weights and the other based on category vectors. The KD-GCN employs keywords to construct a weight matrix for training. The method based on word weight achieves the best results on the CQRD_28000 dataset, which is 0.72% higher than the Bi-LSTM model. The method based on category vector outperforms the Bi-LSTM model in the CQRD_8000 dataset by 2.41%. The KD-GCN, although not attaining the optimal outcome, exhibited a superior performance of 3.12% compared to the GCN model. Both methods have significantly improved the classification results of minority classes.

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Kim, Ji Hyun, and Jung Hyun Na. "Analysis of media reports on digital textbooks using keyword networks and topic modeling." Korean Association For Learner-Centered Curriculum And Instruction 25, no. 7 (2025): 599–616. https://doi.org/10.22251/jlcci.2025.25.7.599.

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Objectives This study analyzed discourses related to digital textbooks in domestic media reports from 2007 to 2024. Methods To this end, data were collected from BIGKINDS, a domestic media report data provision platform, with keywords such as ‘digital textbook’ and ‘AI textbook’, and keyword frequency analysis, co-occurrence network analysis, and topic modeling were performed using the R program. Results Digital textbooks were linked to various issues in terms of policy, education, and technology, and keywords such as ‘education’, ‘digital’, ‘AI’, ‘school’, and ‘content’ appeared mainly in keyword frequency analysis. Topic modeling analysis derived 10 major topics such as digital infrastructure construction, AI-based learning innovation, resolving the education gap, digital content development, and policy support. Conclusions This study systematically analyzes media discourses on digital textbooks to suggest implications for future education policies and textbook development directions.

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Fan, Zhi Guo, and Wen Long Zheng. "The Analysis of Research Hotspot of Chinese Cultural and Creative Industry - Based on Co-Words Method." Advanced Materials Research 798-799 (September 2013): 924–29. http://dx.doi.org/10.4028/www.scientific.net/amr.798-799.924.

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Based on the journal resource from the cqvip database, taking "cultural and creative industry" as the keyword, the paper retrieved all the relevant "CSSCI" documents from 1989 to 2012. After getting the keywords co-occurrence matrix through BIBCOMB software, the paper focused on the keywords analysis which was obtained by the software UCINET and NETDRAW. Then it comes to the conclusion, which shows that development countermeasures, cultural area, cultural creativity and influential factors are the hotspots in present research.

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Padwiansyah, Muh Rizwal, Rr Sri Handari Wahyuningsih, and Siti Dyah Handayani. "Analyzing sustainable organizational development with VOSviewer: a bibliometric analysis." Multidisciplinary Reviews 6, no. 3 (2023): 2023023. http://dx.doi.org/10.31893/multirev.2023023.

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The purpose of this study is to determine and analyze the development of publications on sustainable organizational development using the SCOPUS database. This research uses a bibliometric analysis approach using VOSviewer software to build and visualize bibliometric networks. Researchers conducted screening with the keyword sustainable organizational development in the SCOPUS database in the 2018–2022-time span. The number of publications according to the keywords used was 1,916 documents. Then, filtering was carried out, and the results obtained were 394 publications. The development of publications on Sustainable Organizational Development within 5 years tends to continue to increase and reach its highest point in 2022. Based on the results of the analysis with VOSviewer, the results of network visualization of cooccurrence based on keywords are 55 items divided into 6 clusters marked with different colors. The results of this study show that research on sustainable organizational development contributes greatly to the scientific focus of management. This is then supported by the phenomenon that change is always faced by a company, so it requires steps and strategies so that the company can sustain these changes and adapt. The results of the analysis using VOSviewer software produce network visualization, overlay, and density, and it can be concluded that within five years, the development of publications or research on this topic has increased significantly.

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Park, Jin-Iee. "Analyzing the national kindergarten curriculum through text mining." korean Jouranl of Early Childhood Education 26, no. 2 (2024): 211–37. http://dx.doi.org/10.15409/riece.2024.26.2.9.

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This study aims to examine the changes in the national kindergarten curriculum text through text mining. Semantic network analysis using R was employed for this purpose, yielding the following results. Firstly, consistently High-centrality keywords from the 1st kindergarten curriculum of the 2019 revised Nuri Curriculum were ‘child’ and ‘curriculum,’ with ‘kindergarten,’ ‘operation,’ and ‘development’ also showing general centrality. Secondly, keywords reflecting differences in centrality emphasized in each curriculum period included ‘community,’ ‘play,’ ‘welfare,’ ‘construction,’ and ‘parents.’ The keyword ‘community’ showed High-Centrality in the 1st, 5th, and 6th kindergarten curricula and the 2007 revised kindergarten curriculum. The keywords ‘welfare’ and ‘construction’ displayed High-Centrality in the 3rd kindergarten curriculum. Additionally, the keyword ‘play’ showed High-Centrality in the 2019 revised Nuri Curriculum, and the keyword ‘parents’ showed High-Centrality in the 6th and 2007 revised kindergarten curricula. This study offers implications for future revisions of the early childhood curriculum as a theoretical reference.

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Zeng, Y., J. Zhang, and R. Niu. "Research Status and Development Trend of Remote Sensing in China Using Bibliometric Analysis." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W4 (June 26, 2015): 203–8. http://dx.doi.org/10.5194/isprsarchives-xl-7-w4-203-2015.

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Remote sensing was introduced into China in 1970s and then began to flourish. At present, China has developed into a big remote sensing country, and remote sensing is increasingly playing an important role in various fields of national economic construction and social development. Based on China Academic Journals Full-text Database and China Citation Database published by China National Knowledge Infrastructure, this paper analyzed academic characteristics of 963 highly cited papers published by 16 professional and academic journals in the field of surveying and mapping from January 2010 to December 2014 in China, which include hot topics, literature authors, research institutions, and fundations. At the same time, it studied a total of 51,149 keywords published by these 16 journals during the same period. Firstly by keyword selection, keyword normalization, keyword consistency and keyword incorporation, and then by analysis of high frequency keywords, the progress and prospect of China's remote sensing technology in data acquisition, data processing and applications during the past five years were further explored and revealed. It can be seen that: highly cited paper analysis and word frequency analysis is complementary on subject progress analysis; in data acquisition phase, research focus is new civilian remote sensing satellite systems and UAV remote sensing system; research focus of data processing and analysis is multi-source information extraction and classification, laser point cloud data processing, objectoriented high resolution image analysis, SAR data and hyper-spectral image processing, etc.; development trend of remote sensing data processing is quantitative, intelligent, automated, and real-time, and the breadth and depth of remote sensing application is gradually increased; parallel computing, cloud computing and geographic conditions monitoring and census are the new research focuses to be paid attention to.

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Journal articles on the topic 'Keywords: development'

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