14 research outputs found
Revisão cientométrica das pesquisas de enfermagem sobre gestão da dor
Objetivo: analizar artículos de investigación sobre dolor y temas de enfermería, utilizando metodologías bibliométricas y cienciométricas. Método: se analizaron los artículos en la base de datos Web of Science que contenían dolor y enfermero y dolor y enfermería, usando métodos cienciométricos, a través de técnicas de visualización de datos y análisis avanzado de textos. Resultado: entre los 107.559 artículos de investigación encontrados en el campo de la enfermería, 3.976 de ellos fueron escritos con base en las palabras clave dolor y enfermería, y fueron considerados en conformidad con el ámbito de aplicación de este estudio. Los análisis preliminares indicaron que las publicaciones han aumentado a través de los años, con pequeñas fluctuaciones. Los títulos, las palabras clave y los resúmenes se analizaron mediante análisis de texto para revelar agrupaciones de palabras clave y estructuras de temas. Los estudios sobre oncología y dolor en el campo de la enfermería tienen una frecuencia relativamente más alta. Conclusión: los resultados de los análisis revelaron las características de la literatura actual en una amplia gama de áreas, teniendo en cuenta dimensiones específicas. Por lo tanto, los resultados presentados en este estudio pueden respaldar investigaciones actuales y futuras en este campo, proporcionando información sobre redes, tendencias y contenidos de la literatura en cuestión.Objetivos: analisar artigos científicos sobre dor e enfermagem, utilizando metodologias bibliométricas e cienciométricas. Método: artigos do banco de dados Web of Science que continham dor e enfermeiro e dor e enfermagem foram analisados utilizando métodos cientométricos, através de técnicas de visualização de dados e análise avançada de textos. Resultado: dos 107.559 artigos científicos encontrados na área de enfermagem, 3.976 deles foram escritos com base nas palavras-chave dor e enfermagem, e foram considerados em consonância com o âmbito de aplicação deste estudo. As análises preliminares indicaram que as publicações têm aumentado ao longo dos anos, com pequenas flutuações. Títulos, palavras-chave e resumos foram analisados através de análise de texto para revelar agrupamentos de palavras-chave e estruturas de temas. Estudos sobre oncologia e dor no campo da enfermagem têm uma frequência relativamente maior. Conclusão: os resultados das análises revelaram as características da literatura atual em uma ampla gama de áreas, considerando-se dimensões específicas. Portanto, os resultados podem respaldar pesquisas atuais e futuras neste campo, proporcionando informações sobre redes, tendências e conteúdos da literatura em questão.Objective: to analyse research articles on pain and nursing issues using bibliometric and scientometric methodologies. Method: articles in the Web of Science database containing pain and nurse and pain and nursing were analyzed using scientometric methods through data visualization techniques and advanced text analytics. Result: among the 107,559 research articles found in the field of nursing, 3,976 of them were written based on the keywords pain and nursing, and were considered in conformity with the scope of this study. Preliminary analyses indicated that the publications have increased through the years with minor fluctuations. Titles, keywords, and abstracts were analyzed through text analytics to reveal keyword clusters and topic structures. Studies on oncology and pain in the field of nursing have a relatively higher frequency. Conclusion: the results of the analyses revealed the characteristics of the current literature in a broad range of areas by considering the particular dimensions. Therefore, the findings may support present and future research in this field by shedding light on the networks, trends, and contents in the related literature
Electronic Device Selection in Industrial Products and Machinery Industry: Comparative Analysis with Ocra and Maut Method
The diversity and abundance of product alternatives lead to vagueness on decisions related to procurement, production, and R & D management processes along with other decisions taken within the company and render purchasing, production and R&D decision processes, much more effortful. As choosing appropriate and effective decisions within purchasing, production, R&D, and all other departments are of great importance in today’s competitive business environment, firms are strongly encouraged to concentrate on their decision processes. Within the scope of this study, the purchase decisions of electronic device alternatives are being analysed in industrial products and machinery industry with OCRA method. The importance levels of evaluation criteria for the purchase are obtained out of 100 points. These importance levels are then being used in OCRA method in an attempt to evaluate various electronic device alternatives. In order to scrutinize the results, it can be said that the same data set is compatible with MAUT, which is another multi-criteria decision making method. Information regarding the evaluation criteria as well as alternatives of electronic device has been gathered through focus group study that includes marketing and purchasing managers. The results provide useful information for the sector
The application of data mining techniques in manipulated financial statement classification: The case of turkey
Predicting financially false statements to detect frauds in companies has an increasing trend in recent studies. The manipulations in financial statements can be discovered by auditors when related financial records and indicators are analyzed in depth together with the experience of auditors in order to create knowledge to develop a decision support system to classify firms. Auditors may annotate the firms’ statements as “correct” or “incorrect” to add their experience, and then these annotations with related indicators can be used for the learning process to generate a model. Once the model is learned and tested for validation, it can be used for new firms to predict their class values. In this research, we attempted to reveal this benefit in the framework of Turkish firms. In this regard, the study aims at classifying financially correct and false statements of Turkish firms listed on Borsa İstanbul, using their particular financial ratios as indicators of a success or a manipulation. The dataset was selected from a particular period after the crisis (2009 to 2013). Commonly used three classification methods in data mining were employed for the classification: decision tree, logistic regression, and artificial neural network, respectively. According to the results, although all three methods are performed well, the latter had the best performance, and it outperforms other two classical methods. The common ground of the selected methods is that they pointed out the Z-score as the first distinctive indicator for classifying financial statements under consideration
A framework for the selection of the right nuclear power plant
Civil nuclear reactors are used for the production of electrical energy. In the nuclear industry vendors propose several nuclear reactor designs with a size from 35–45 MWe up to 1600–1700 MWe. The choice of the right design is a multidimensional problem since a utility has to include not only financial factors as levelised cost of electricity (LCOE) and internal rate of return (IRR), but also the so called “external factors” like the required spinning reserve, the impact on local industry and the social acceptability. Therefore it is necessary to balance advantages and disadvantages of each design during the entire life cycle of the plant, usually 40–60 years. In the scientific literature there are several techniques for solving this multidimensional problem. Unfortunately it does not seem possible to apply these methodologies as they are, since the problem is too complex and it is difficult to provide consistent and trustworthy expert judgments. This paper fills the gap, proposing a two-step framework to choosing the best nuclear reactor at the pre-feasibility study phase. The paper shows in detail how to use the methodology, comparing the choice of a small-medium reactor (SMR) with a large reactor (LR), characterised, according to the International Atomic Energy Agency (2006), by an electrical output respectively lower and higher than 700 MWe
Fuzzy multi-criteria decision making for carbon dioxide geological storage in Turkey
The problem of choosing the best location for CO2 storage is a crucial and challenging multi-criteria decision problem for some companies. This study compares the performance of three fuzzy-based multi-criteria decision making (MCDM) methods, including Fuzzy TOPSIS, Fuzzy ELECTRE I and Fuzzy VIKOR for solving the carbon dioxide geological storage location selection problem in Turkey. The results show that MCDM approach is a useful tool for decision makers in the selection of potential sites for CO2 geological storage
Scientometric overview of nursing research on pain management
ABSTRACT Objective: to analyse research articles on pain and nursing issues using bibliometric and scientometric methodologies. Method: articles in the Web of Science database containing pain and nurse and pain and nursing were analyzed using scientometric methods through data visualization techniques and advanced text analytics. Result: among the 107,559 research articles found in the field of nursing, 3,976 of them were written based on the keywords pain and nursing, and were considered in conformity with the scope of this study. Preliminary analyses indicated that the publications have increased through the years with minor fluctuations. Titles, keywords, and abstracts were analyzed through text analytics to reveal keyword clusters and topic structures. Studies on oncology and pain in the field of nursing have a relatively higher frequency. Conclusion: the results of the analyses revealed the characteristics of the current literature in a broad range of areas by considering the particular dimensions. Therefore, the findings may support present and future research in this field by shedding light on the networks, trends, and contents in the related literature
Career decision making in the maritime industry: research of merchant marine officers using Fuzzy AHP and Fuzzy TOPSIS methods
Individual career planning plays a key role in achieving success, goals, and ideals in professional life. However, managing to accomplish such favorable results depends on the correct decisions of graduates to choose
suitable job opportunities. Oceangoing watchkeeping officers, who are responsible for the management and
administration of vessels at sea, have several job options which are differentiated by vessel type, such as; bulk
carriers, chemical tankers, general cargo ships, and container ships, etc. This study aims to discuss the criteria
that Turkish oceangoing watchkeeping officers take into consideration and the values they attribute to such
criteria regarding their vessel type preference. The aim is to provide instructions to oceangoing watchkeeping
officer candidates and academicians who are interested in these issues and related parties of maritime industry.
Attribution values of the criteria are determined by means of Fuzzy Analytic Hierarchy Process (AHP) and the
most preferred alternative vessel type is revealed through Fuzzy TOPSIS methodology. According to the study
results, the most important factors are; revenue, perception of occupational health and safety, and labor work
density. The most preferred ship type among alternatives is the oil tanker
Integration of fuzzy analytic hierarchy process and multi-objective fuzzy goal programming for selection problems: An application on roadheader selection
In this study a general methodology employing fuzzy analytic hierarchy process and fuzzy goal programming is developed for selection problems. The proposed methodology has two main sub-phases. In the first phase, fuzzy triangular numbers are used in order to represent the comparisons among decision criteria. Then lower and upper bounds as well as mid-values of priorities belonging to each decision criteria are computed. In the second phase these values and fuzzy triangular numbers are entered into the goal programming model and the model is solved to give the final priorities of decision criteria. Then the weighted sum of ratings for each selection alternative are found where the weights are final priorities from goal programming model. The proposed methodology is presented on a real life roadheader selection problem from mining industry. The results revealed that the methodology is easily applicable and provides satisfactory results