Bibliografías temáticas / MARKET RESEARCH TECHNIQUES

Literatura académica sobre el tema "MARKET RESEARCH TECHNIQUES"

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Publicado: 11 de septiembre de 2023

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Artículos de revistas sobre el tema "MARKET RESEARCH TECHNIQUES"

Birn, Robin J. "Market research techniques in publishing". Learned Publishing 2, n.º 3 (1 de enero de 1989): 125–28. http://dx.doi.org/10.1002/leap/20047.

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Wilton, Vivien y Keith Greenhoff. "Integration of sensory techniques into market research". Food Quality and Preference 1, n.º 1 (enero de 1988): 33–35. http://dx.doi.org/10.1016/0950-3293(88)90006-7.

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Wilson, Suzanne G. "Market Research Techniques-A Synopsis for CE Providers". Journal of Continuing Education in Nursing 23, n.º 4 (julio de 1992): 182–83. http://dx.doi.org/10.3928/0022-0124-19920701-11.

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Dzikevičius, Audrius y Svetlana Šaranda. "SMOOTHING TECHNIQUES FOR MARKET FLUCTUATION SIGNALS". Business: Theory and Practice 12, n.º 1 (10 de marzo de 2011): 63–74. http://dx.doi.org/10.3846/btp.2011.07.

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The financial crisis of 2008–2009 caused lots of discussions between Academia and as a result researches on financial crisis and bubble prediction possibilities appeared. Academia shows its growing interest in the issue during the last decade. The majority of researches made are based on different forms of forecast used. Some of previous studies claim that the trend of the stock market can be forecasted using moving average method. After the finance market crashed, a need to forecast further possible bubbles arises. As the economics of the Baltic States is very sensitive to such bubbles it is very important to forecast preliminary the trends of the finance markets ant to plan the right actions in order to temper such bubble influence on the national economics. Although economic theory is opposite to the technical analysis theory which is the main tool for traders in stock markets it is used widely. This paper examines whether a proper technical analysis rule such as Exponential Moving Average (EMA) has a predictive power on stock markets in the Baltic States. The method is applied to OMX Baltic Benchmark Index and industrial indexes as they are more or less sensitive to the main index fluctuations. The results were compared using systematic error (mean square error, the mean absolute deviation, mean forecast error, the mean absolute percentage error) and tracking signal evaluation, CAPM method and appropriate period of EMA finding for each market forecast. A graphical analysis was used in order to determine whether EMA can forecast the main trends of the stock market fluctuations. The conclusions made during the research suggest new research issues and new hypotheses for its further testing.

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Boddy, Clive R. "Projective techniques in Taiwan and Asia‐Pacific market research". Qualitative Market Research: An International Journal 10, n.º 1 (23 de enero de 2007): 48–62. http://dx.doi.org/10.1108/13522750710720396.

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Chopra, Ritika y Gagan Deep Sharma. "Application of Artificial Intelligence in Stock Market Forecasting: A Critique, Review, and Research Agenda". Journal of Risk and Financial Management 14, n.º 11 (4 de noviembre de 2021): 526. http://dx.doi.org/10.3390/jrfm14110526.

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The stock market is characterized by extreme fluctuations, non-linearity, and shifts in internal and external environmental variables. Artificial intelligence (AI) techniques can detect such non-linearity, resulting in much-improved forecast results. This paper reviews 148 studies utilizing neural and hybrid-neuro techniques to predict stock markets, categorized based on 43 auto-coded themes obtained using NVivo 12 software. We group the surveyed articles based on two major categories, namely, study characteristics and model characteristics, where ‘study characteristics’ are further categorized as the stock market covered, input data, and nature of the study; and ‘model characteristics’ are classified as data pre-processing, artificial intelligence technique, training algorithm, and performance measure. Our findings highlight that AI techniques can be used successfully to study and analyze stock market activity. We conclude by establishing a research agenda for potential financial market analysts, artificial intelligence, and soft computing scholarship.

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Abbasi, Behjat y Mohammad Hamed Khan Mohammadi. "Effect of strategic management accounting techniques on market share changes in firms in Tehran Stock Exchange market". Problems and Perspectives in Management 14, n.º 3 (15 de septiembre de 2016): 325–31. http://dx.doi.org/10.21511/ppm.14(3-si).2016.04.

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Increasing market share is one of the main challenges of organizations nowadays, in order to guarantee profitability and survival of the organization. Market share index in an indicator of success/failure. The aim of the present study is to investigate the effect of strategic management accounting techniques effect on market share changes in Tehran stock market companies. This is a descriptive research in which information are in collected via secondary data and inspecting financial statements. The purpose is to investigate the relationship between variables of the study and then find their correlation. Results of the study suggested that market added value, net present value, profitability index and investment return rate are among those accounting strategic techniques that have significant effect on markets market share, but economical added valued doesn’t have a significant effect on markets share changes. Keywords: market added value (MAV), economic value added, net present value, profitability index, investment return rate, market share changes. JEL Classification: G14, G30, M31, M41

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Patel, Jay, Siddhanth Jain y U. M. Prakash. "Multivariate Index Relationship Exploration Using Advanced Machine Learning Techniques". International Journal for Research in Applied Science and Engineering Technology 11, n.º 4 (30 de abril de 2023): 3775–85. http://dx.doi.org/10.22214/ijraset.2023.51011.

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Abstract: Stock market forecasts have always attracted the attention of many analysts and researchers. Popular theory suggests that stock markets are inherently straightforward, and trying to predict them is a trivial matter. It is a difficult problem in itself. The market behaves like a voting machine in the short term, but in the long term it behaves like a pair of scales. Therefore, there is room to predict market movements over a longer period of time. Applying machine learning techniques and other algorithms to stock price analysis and forecasting is a promising area. This white paper begins with a brief overview of the stock market and a taxonomy of stock market forecasting methods. We then highlight some research findings on resource analysis and forecasting. We discuss technical, fundamental, short- term and long-term approaches to equity analysis. Finally, we present some challenges and research opportunities in this area.

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Shah, Dev, Haruna Isah y Farhana Zulkernine. "Stock Market Analysis: A Review and Taxonomy of Prediction Techniques". International Journal of Financial Studies 7, n.º 2 (27 de mayo de 2019): 26. http://dx.doi.org/10.3390/ijfs7020026.

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Stock market prediction has always caught the attention of many analysts and researchers. Popular theories suggest that stock markets are essentially a random walk and it is a fool’s game to try and predict them. Predicting stock prices is a challenging problem in itself because of the number of variables which are involved. In the short term, the market behaves like a voting machine but in the longer term, it acts like a weighing machine and hence there is scope for predicting the market movements for a longer timeframe. Application of machine learning techniques and other algorithms for stock price analysis and forecasting is an area that shows great promise. In this paper, we first provide a concise review of stock markets and taxonomy of stock market prediction methods. We then focus on some of the research achievements in stock analysis and prediction. We discuss technical, fundamental, short- and long-term approaches used for stock analysis. Finally, we present some challenges and research opportunities in this field.

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Wilson, Suzanne G. "Brief: Market Research Techniques-A Synopsis for Continuing Education Providers". Journal of Continuing Education in Nursing 21, n.º 5 (septiembre de 1990): 224–26. http://dx.doi.org/10.3928/0022-0124-19900901-11.

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Tesis sobre el tema "MARKET RESEARCH TECHNIQUES"

SHARMA, MANISH. "EMOTIONAL INTELLIGENCE DRIVEN QUALITATIVE MARKET RESEARCH TECHNIQUES: AN EXPLORATORY STUDY". Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18686.

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Intelligence is what differentiates human from other living organisms on this planet. Intelligence has been defined in various ways at different times by different disciplines. Intelligence is what makes us think and do things which others cannot. Intelligence evolved over the decades, although it has been that was around always, but the definition changed with time and types emerged. Emotional intelligence (EI) must have been in humans forever but was not being talked about so much until 25 years ago. It has gained much popularity in the last 25 years. After a few years of Emotional Intelligence, another kind of intelligence became popular, and that was customer intelligence. It is being gathered in many ways, and one of the very involved ways is to use qualitative market research techniques. A recent intelligence is about machines and is called Artificial Intelligence. The purpose of this study is to assess the importance of emotional intelligence in qualitative market research techniques (customer Intelligence) and artificial intelligence is used to detect the emotions from the facial images. Another purpose is to automate the measurement of Emotional Intelligence by finding the essential features and missing data out of emotional intelligence measurement test. In the pursuit to detect images from the face, feature extraction was done using Principal Component Analysis (PCA). This experiment aims to recognise emotions from a given set of pictures. The problem is a classification problem and comes under supervised learning. Since each image has many features, feature extraction techniques were required to reduce the feature set. This research applies PCA for transforming the dimensions of the data. PCA helps in converting the data and improves the efficiency and effectiveness of the classifier. If the number of features of the data is large, it takes more time for computation, and more memory is required to store and process the data. The understanding of the results is also hampered because of failure to visualise the data. As some of the features are not relevant, so feature selection was made using the Fisher Discriminant Ratio, and the classification was done using Support Vector Machine (SVM). The application of forward feature selection was used to reduce the number of features. The suggested model reads a set of images, converts them to a two-dimensional array, followed by the application of PCA. The resultant data is subjected to forward feature selection. This resulted in reducing the dimensionality of the data to a large extent. High values of accuracy, specificity and sensitivity conclude that the proposed machine learning model can help to identify emotions. The accuracy, specificity and sensitivity are encouraging. The average accuracy is 0.80; specificity is .97 and sensitivity is 0.75. This helps to conclude that this model can detect emotions on facial images by 80% accuracy and will be specific 97% times and sensitive 75% times. This study helps in the measurement of EI by finding the most important features of the TMMS test of EI using Machine Learning techniques. It is intended to carry out similar experiments in the future for the remaining tests used for measuring EI, and hence to develop a better model for understanding, classifying and predicting EI. In order to measure EI, issues like the handling of noise and regression need to be addressed. This study suggests a framework to do the same. Regression analysis is used to find the relation between the dependent and the independent variables. Neural Network has been used to carry out the regression to find missing data of emotional intelligence measurement test. The study created a framework to classify the faces based on emotions. It was concluded that artificial intelligence could help in increased emotional intelligence and gather customer intelligence. In a nutshell, it can be said that Emotional Intelligence plays a role in qualitative market research techniques, as reported. So there are a significant relationship in Emotional Intelligence and qualitative market research techniques. It is also concluded that missing data while measuring EI can be predicted using regression techniques. It is also concluded that features of the existing EI test can be ranked according to their importance to get the most important features. The emotions on faces can be detected using machine learning, and that can help in study consumer behaviour as behaviour comprises of emotions, thus increasing the impact of qualitative market research techniques. The first chapter of the thesis gives an introduction and classification of emotional intelligence and qualitative market research. The chapter also charts out the scope of the study, parts of the study under its orientation and most importantly, the significance of the study. The second chapter discusses the literature published in this area with details of 21 tests of emotional intelligence. It is followed by the third chapter, which discusses the research objectives, hypothesis and the conceptual framework of the study. The fourth chapter gives details of the survey, including sampling, sample size & variables and pre-processing of data. The fifth chapter explains the experiment, observation and analysis of data. Conclusion and contribution are given in the Sixth chapter, and recommendations are made in the Seventh chapter. Some implications are explained in chapter 8 th and limitation, and future scope of the study is given in the last (Ninth) chapter.

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Orlichová, Zuzana. "The emerging market of cosmetics for men - What are the adoption barriers?" Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-85276.

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The aim of this study is to describe adoption barriers emerging on the cosmetics for men market through market research and consumer behaviour exploration. The relationship men have with the cosmetics is not easy to understand, so the purpose of this study is to explore on what is based their relationship to cosmetics market - why some are ready to use cosmetics while other reject. Regarding market of cosmetics for men, there are the barriers that prevent in adoption of cosmetics. The thesis would reveal what influence the social decision making, and would go deeper into what influence men; and what the relationships with products, brands, services, and environment they have. The conclusion will be the interpretation of the adoption barriers on cosmetics for men market.

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Miguelote, Vera Regina da Silva. "A indústria do conhecimento, o médico e a indústria farmacêutica: uma coprodução de técnicos e técnicas de poder". Universidade do Estado do Rio de Janeiro, 2008. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=5284.

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Este estudo abordou o contexto de uma engrenagem macropolítica, na qual o poder dominante (representado pela indústria farmacêutica) se articula à indústria do conhecimento, condicionando construção e divulgação de conhecimento biomédico à mesma lógica da produção e distribuição capitalista de mercadorias. A indústria farmacêutica tem investido em projetos de pesquisas clínicas, com o objetivo de legitimar, cientificamente, seus produtos. A investigação deste papel financiador de ensaios clínicos baseou-se nos depoimentos de quatro médicos, professores de Medicina, coparticipantes de projetos da indústria farmacêutica. Os resultados evidenciaram que os protocolos das pesquisas são elaborados pela própria indústria, sem participação do médico colaborador; o acesso à íntegra dos dados coletados é de exclusividade dos coordenadores centrais da pesquisa; e, os resultados dos ensaios, apresentados através de resumos, são previamente submetidos a critérios de seleção de dados. Com o objetivo de articular saber médico a expectativas de mercado, o poder dominante se exerce através de técnicas de poder (estratégias de marketing), atribuindo aos médicos o papel de técnicos de poder, a serviço de seus interesses. Essa relativização de valores clama por uma crítica revisão ética.
This study is an approach to the macro-political engine where the dominant power (represented by the pharmaceutical industry) articulates with the knowledge industry promoting the construction and transmission of a biomedical knowledge with the same logic production and distribution of capitalist commodities. The pharmaceutical companies have been investing in clinical research projects with the intention to scientifically legitimate its products. The investigation of the financial role of these clinical trials was based on the interviews with four physicians who are also medicine professors engaged in these pharmaceutical projects. The results showed that the research protocols are elaborated by the pharmaceutical industry without the participation of the engaged doctors; the whole access to the research data is only available to the main research supervisors and the results are submitted to previous data selection. The dominant power of the pharmaceutical industry is exercised through market power techniques. It establishes a technical power position to the physicians enrolled in the research who are also in service of the industries interests. This relativistic approach concerning health values claims for a critical and ethical revision.

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Tsai, Yi-Ting y 蔡依庭. "Application of Data Mining Techniques to Film Market Research". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/16605744340914078907.

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碩士
國立政治大學
統計研究所
98
Considering the current film market, the publication cost of a film is steadily increased. Meanwhile, customers have complicated requirements, and the trend of concentrated film consumption is gradually clear. For the perspective of both film companies and film broadcasting business, clear market segmentation after understanding customers’ needs and interpretation of customer behaviors to design different products and marketing combination for different markets are of great urgency for the general film industry. In view of this, the study aims to using four Decision Trees(C&RT, QUEST, CHAID, C5.0), Logistic Regression, and Artificial Neural Network to construct the model by applying Data Mining technology. Since Decision Tree-CHAID is excellent in the forecast accuracy, precision, and recall rate as compared to other models for response variables of going to the movies and going to foreign movies or Taiwan movies, the CHAID is adopted in this research for both response variables. The CHAID is more excellent for the response variable of going to the movies than the other, so use it as the main result. Through using Decision Tree-CHAID, this study identified thirteen factors that have greater impact on going to the movies. Based on the analysis results, this study induced the characteristics of three customer groups-the highest contribution customers, regular contribution customers and low contribution customers. Three different contribution groups shows significant differences at age, education, entertainment expenditure, living area, internet surfing, collecting information from internet, watch foreign movies, watch foreign drama, speak English, watch on-lines movies, affluent, and seize the day. This study mainly based on the characteristics of the three different groups, and group characteristic of going to foreign movies or Taiwan movies as auxiliary, to provide the marketing portfolio strategy recommendations.

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Chiu, Jen-Fu y 邱仁甫. "The Research of Data Mining Techniques Applied to Market Segmentation New Product Development of Mobile Phone Service". Thesis, 2006. http://ndltd.ncl.edu.tw/handle/13042910443148426133.

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碩士
國防管理學院
資源管理研究所
94
Since the service of Mobile Number Portability, MNP was adopted in 2005, it makes user to change the telecommunication system industry with keeping original mobile phone number. Therefore every telecommunication system industry is eager to promote the MNP service to raise the market share.However the products that telecommunication system industry promoted have similar function and in the so highly competitive environment how to provide the new product or service which is satisfied with customers and Market demand? It is just the main management field that they are devoted to. Every telecommunication system industry has the large database at present. According to the different Marketing target and using data mining technique, they can find undiscovered consumption action or some specially and tendency of Market Segmentation. It is very beneficial on scheduling and implementing Marketing Strategy. The research focuses on Market Segmentation for mobile phone users in Taiwan and through making use of Cluster Analysis technique, we excavates different-extent user’s distinctions and understand the demand difference of user’s feature and service. In addition according to so insightful opinions and suggestions which user provided and making use of Association Rule technique, we introduce the knowledge from user to New Product Development’s process. Furthermore we apply this method to develop potential customers and determine potential using distinctions. Through this information, it gives us different Marketing Mix.

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Petty, Silvia. "Neurofyziologické metody a techniky v marketingovém výzkumu v České republice". Master's thesis, 2016. http://www.nusl.cz/ntk/nusl-351897.

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Improvements of neuroscience tools and their wider availability complements previously used qualitative and quantitative research methods and techniques with neurophysiological methods and techniques to help us find out what respondents really think. In the Czech Republic, these methods are relatively new. Agencies focusing on market research have started using these methods in 2010 and currently are in the process of establishing neurological and neurophysiological techniques in the portfolio of offered services. There are not many studies on the techniques in the academic world, there is no guide for sociologists and students of sociology and this paper therefore aims to present neurological and neurophysiological research methods and techniques, to define their place in research methods, to highlight their advantages, disadvantages and limitations as a tool for marketing (eventually sociological) research in comparison with traditional methods and techniques, to map the current situation of their use in the Czech Republic, to reflect on the ethical issue of using the methods and their future.

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Zois, Christos. "Applying text mining techniques to forecast the stock market fluctuations of large it companies with twitter data: descriptive and predictive approaches to enhance the research of stock market predictions with textual and semantic data". Master's thesis, 2019. http://hdl.handle.net/10362/92164.

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Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies Management
This research project applies advanced text mining techniques as a method to predict stock market fluctuations by merging published tweets and daily stock market prices for a set of American Information Technology companies. This project executes a systematical approach to investigate and further analyze, by using mainly R code, two main objectives: i) which are the descriptive criteria, patterns, and variables, which are correlated with the stock fluctuation and ii) does the single usage of tweets indicate moderate signal to predict with high accuracy the stock market fluctuations. The main supposition and expected output of the research work is to deliver findings about the twitter text significance and predictability power to indicate the importance of social media content in terms of stock market fluctuations by using descriptive and predictive data mining approaches, as natural language processing, topic modelling, sentiment analysis and binary classification with neural networks.

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Ndebele, Tom. "Economic non-market valuation techniques : theory and application to ecosystems and ecosystem services : a case study of the restoration and preservation of Pekapeka Swamp : an application of the contingent valuation method in measuring the economic value of restoring and preserving ecosytem services in an impaired wetland : a thesis submitted in partial fulfillment of the requirements for the degree of Master of Philosophy in Economics at Massey University, Palmerston North, New Zealand". 2009. http://hdl.handle.net/10179/1287.

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This thesis explores the theoretical basis of non-market valuation techniques; discusses in detail, the Contingent Valuation Method (CVM) and the Travel Cost Method (TCM); highlights the advantages and disadvantages of various non-market valuation techniques and their suitability under different conditions; and identifies the Contingent Valuation Method as the most appropriate non-market valuation technique to apply to Pekapeka Swamp, the case study site. The overall objective of the study is to apply the most appropriate non-market valuation technique to estimate the total economic value (TEV) of the restoration and preservation of Pekapeka Swamp and to test Hawke’s Bay Regional Council’s (HBRC) restoration programme for the Pekapeka Swamp using economic efficiency criteria. An appropriate contingent valuation mail survey questionnaire was designed to elicit responses to the dichotomous choice (DC) and open-ended valuation questions, and to collect socio-economic data and information on households’ attitude towards the environment. Responses to the survey questionnaire were analysed (using ordinary least squares regression for the open ended question, and logistic regression, for the DC question) to identify the factors that influence households’ willingness to pay (WTP) for the restoration and preservation of the Pekapeka Swamp and to estimate TEV. A number of functional forms of the logit and open-ended WTP models were fitted from which WTP functions were estimated. Households were asked a DC question followed by an open-ended question regarding the value they placed on the restoration and preservation of Pekapeka Swamp. Out of an initial mail-out of 958 questionnaires, an overall response rate of 46.13% was achieved after two follow-ups. Results from the final usable sample of 231, after removing protests and inconsistent responses, indicate that households in the Hawke’s Bay region would pay, on average, between NZ$30.00 and NZ$76.89 per annum for five years. Unit value ranges between NZ$17,898 and NZ$45,866 per hectare per year; and net present values for the restoration and preservation programme for Pekapeka Swamp based on our ‘best estimates’ range between NZ$5.05 million and NZ$18.20 million depending on the model and discount rate used.

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Libros sobre el tema "MARKET RESEARCH TECHNIQUES"

Robin, Birn, Hague Paul N y Vangelder Phyllis, eds. The handbook of international market research techniques. 2^a ed. London: Kogan Page, 2000.

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John, Snyder, ed. Forecasting and market analysis techniques: A practical approach. Westport, Conn: Quorum Books, 1994.

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1972-, Williams Navin y York Sue 1968-, eds. The handbook of mobile market research: Tools and techniques for market researchers. Chichester, West Sussex, United Kingdom: John Wiley and Sons, Inc., 2014.

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Priya, Preeti. Market selection decision scorecard: Integrating multivariate techniques and AHP. Anand: Institute of Rural Management, Anand, 2010.

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G, Pol Louis y Thomas Richard K. 1944-, eds. Healthcare market research: Tools and techniques for analyzing and understanding today's healthcare environment. [Burr Ridge, IL]: Irwin, 1997.

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A, Morrison Margaret, ed. Using qualitative research in advertising: strategies, techniques, and applications. Thousand Oaks, Calif: Sage, 2002.

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The handbook of online and social media research: Tools and techniques for market researchers. New York: Wiley, 2010.

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Poynter, Ray. The handbook of online and social media research: Tools and techniques for market researchers. New York: Wiley, 2010.

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McAllister, Isabel. The use of modular building techniques for social housing in the UK: A market research report. Watford: Published by Construction Research Communications Ltd by permission of Building Research Establishment Ltd, 2000.

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Matthew, Housden y Institute of Marketing, eds. Marketing research for managers. 2^a ed. Oxford: Butterworth Heinemann, 1996.

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Capítulos de libros sobre el tema "MARKET RESEARCH TECHNIQUES"

Gordon, Wendy, Roy Langmaid y Christopher Mills. "Projective and Enabling Techniques". En Qualitative Market Research, 89–126. London: Routledge, 2022. http://dx.doi.org/10.4324/9781315245553-8.

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Feld, Karl G. y William K. Stone. "Improving Honeywell's Market Research: Combining Online Surveys, Traditional Interviewing Techniques and Web-based Reporting". En Market Research Best Practice, 195–212. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119208815.ch9.

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Shameem, S. S. S. y Sonal Sachin Deshmukh. "Progress in Machine Learning Techniques for Stock Market Movement Forecast". En Advances in Computer Science Research, 69–77. Dordrecht: Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-136-4_9.

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Gaul, Wolfgang. "Market Research Support by Data Analysis Techniques: Theoretical Developments vs. Practical Applications". En Operations Research Proceedings, 338. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73778-7_84.

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Sreekumar, Ajithkumar, Prabhasa Kalkur y Mohammed Moiz. "Practical Market Indicators for Algorithmic Stock Market Trading: Machine Learning Techniques and Grid Strategy". En Emerging Research in Computing, Information, Communication and Applications, 121–32. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6001-5_10.

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Spagnoli, Valentina y Claudio Piferi. "Regeneration of historic centers in Mediterranean cities: the case study of the Venice district in Livorno". En Ninth International Symposium “Monitoring of Mediterranean Coastal Areas: Problems and Measurement Techniques”, 343–53. Florence: Firenze University Press, 2022. http://dx.doi.org/10.36253/979-12-215-0030-1.32.

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The article talks about an experience of design research, aimed at the regeneration of a portion of the waterfront of the city of Livorno, which is now fragmented and in a state of decay and strongly characterized by the presence of the contemporary fish market building. The research proposes a new spatial arrangement through the re-functionalization of the building and the design of all the access systems to the area, driveways, pedestrian and cycle paths, which can allow its proper use by citizens and tourists. The area is transformed from a transit place into a place of rest and meeting.

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Sabioni, Rachel Campos, Joanna Daaboul y Julien Le Duigou. "Optimization of Reconfigurable Manufacturing Systems Configuration: A Literature Review". En Lecture Notes in Mechanical Engineering, 426–35. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70566-4_67.

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AbstractReconfigurable Manufacturing Systems (RMS) have gained importance in the current context of increasing high variety demand, Mass Customization (MC) and market instability, due to their ability of being quickly modified to adjust their production capacity to attain sudden fluctuations in market demands as well as to accommodate operations of new products. RMS can be configured at system and machine levels. Many papers have described the RMS configuration as combinatorial optimization problems and proposed several techniques to optimize them in terms of different responses of interest. This paper presents a literature review that seeks to understand how RMS configuration has been addressed in terms of configuration level, optimization problem modelling and techniques applied to solve it. This work aims to assist researchers working on RMS configuration to identify trends and new research opportunities.

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Usai, Maria Pina. "Tuna: underwater natural and cultural heritage. The Tunèa case study, a project for the re- connection between coastal community and marine ecosystem". En Ninth International Symposium “Monitoring of Mediterranean Coastal Areas: Problems and Measurement Techniques”, 887–95. Florence: Firenze University Press, 2022. http://dx.doi.org/10.36253/979-12-215-0030-1.84.

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Understanding the intersection between marine nature and culture is a basis for sustainable coastal development. In this frame the Carloforte tonnara, one of the last fixed Thunnus thynnus trap in the Mediterranean, represent a significant case study. Since until about thirty years ago the life of local community was closely linked to the fishing activities, but the evolution of the fish market at a global scale has radically interrupted it. In 2021 the author of this contribution created Tunèa1, an arts-based research in action project, aimed to re-create the lost relationship in new forms.

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Vuppalapati, Chandrasekar. "Commodity Markets: Machine Learning Techniques". En International Series in Operations Research & Management Science, 219–327. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77485-1_4.

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"Combining Research Techniques Into Research Strategies". En The Market Research Toolbox: A Concise Guide for Beginners, 323–31. 2455 Teller Road, Thousand Oaks California 91320: SAGE Publications, Inc, 2016. http://dx.doi.org/10.4135/9781483398228.n15.

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Actas de conferencias sobre el tema "MARKET RESEARCH TECHNIQUES"

Tena-Monferrer, Sandra, Juan Carlos Fandos-Roig, María Pilar Monte-Collado, Montserrat Boronat-Navarro, Beatriz Forés-Julián y Alba Puig-Denia. "USING ROLE-PLAYING TECHNIQUES IN AN UNDERGRADUATE MARKET RESEARCH CLASSROOM". En International Conference on Education and New Learning Technologies. IATED, 2017. http://dx.doi.org/10.21125/edulearn.2017.2009.

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Wen, Ching-chih y Chieh-chih Wen. "The Use of Modern Online Techniques and Mechanisms in Market Research". En 2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06). IEEE, 2006. http://dx.doi.org/10.1109/cimca.2006.214.

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Yadav, Rakesh y Mannu. "Mathematical modeling on crop pricing based on market price and demand". En THE FOURTH SCIENTIFIC CONFERENCE FOR ELECTRICAL ENGINEERING TECHNIQUES RESEARCH (EETR2022). AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0164307.

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Singh, Bhupinder y Santosh Kumar Henge. "The threshold effect of forecasting parameters on Saudi Financial Market due to volatile dynamics". En THE FOURTH SCIENTIFIC CONFERENCE FOR ELECTRICAL ENGINEERING TECHNIQUES RESEARCH (EETR2022). AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0163493.

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Devi, M. Uma, P. Akilandeswari y M. Eliazer. "Stock Market Ontology-Based Knowledge Management for Forecasting Stock Trading". En International Research Conference on IOT, Cloud and Data Science. Switzerland: Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-02laqd.

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Today’s markets are rather matured and arbitrage opportunities remain for a very short time. The main objective of the paper is to devise a stock market ontology-based novel trading strategy employing machine learning to obtain maximum stock return with the highest stock ratio. The paper aims to create a dynamic portfolio to obtain high returns. In this work, the impact of the applied machine learning techniques on the Chinese market was studied. The problem of investing a particular total amount in a large universe of stocks is considered. The Chinese stocks traded on Shanghai Stock Exchange and Shenzhen Stock Exchange are chosen to be the entire universe. The inputs that are considered are fundamental data and company-specific technical indicators unlike the macroscopic factors considered in the existing systems. In the stock market document repository, ontological constructs with Word Sense Disambiguation (WSD) algorithm improve the conceptual relationships and reduce the ambiguities in Ontological construction. The machine learning techniques Kernel Regression and Recurrent Neural Networks are used to start the analysis. The predicted values of stock prices from the Artificial Neural Network provided quite accurate results with an accuracy level of 97.55%. In this study, the number of nodes will be selected based on Variance-Bias plots by tracking the error on the in-sample data set and the validation data set.

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Fetterhoff, Otto y William J. O'Brien. "Planning to Get Work: An Evaluation of Market Forecasting Techniques for Use by Large Design and Construction Firms". En Construction Research Congress 2005. Reston, VA: American Society of Civil Engineers, 2005. http://dx.doi.org/10.1061/40754(183)54.

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Savciuc, Oxana. "Neuromarketing and ethical aspects in conducting market research". En International Scientific Conference “30 Years of Economic Reforms in the Republic of Moldova: Economic Progress via Innovation and Competitiveness”. Academy of Economic Studies of Moldova, 2022. http://dx.doi.org/10.53486/9789975155618.18.

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Designing marketing research tools capable of generating as much accurate and real information as possible, helps to substantiate marketing decisions. Starting from this practical need for research in marketing, in the contemporary information society new directions of action and development appear, springing both from the evolution and from development of marketing and from the development of information technology, the evolution of imaging and scanning techniques of the human brain. The ethical nature of the neuromarketing approach is one of the biggest and most sensitive challenges of its application in the field of market research. Since its inception, neuromarketing has been a controversial field, raising many ethical issues for researchers. This reaction is due to the research methodology, which is considered, by some authors, to have a high potential for intrusion into the subject's mind.

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Morris, Lloyd, Homero Murzi, Hernan Espejo, Olga Jamin Salazar De Morris y Juan Luis Arias Vargas. "Big Data Analysis in Vehicular Market Forecasts for Business Management". En 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002299.

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Information in various markets constitutes the primary basis for making the right decisions in a modern and globalized world. Therefore, opportunities grow based on the availability of data and how the data is structured to obtain information that supports decision-making processes, Ogrean (2018) and Neubert (2018), and even more so when business dynamics revolve around satisfying the demand for the products or services offered, Jacobs and Chase (2009). This article proposes the analysis of the new vehicle market, through operational research techniques, addressing the behavior of vehicle sales for medium and long-term projections for business management. The analysis is developed through Markov Chains and time series analysis techniques, so a complementary approach is used to obtain predictions in future scenarios such as analysis in sales levels related to market shares. Choi et al (2018), indicate that one of the important applications of Big Data in business management is in the field of demand forecasts, becoming one of the common alternatives in prediction for data series over time. The data is taken from Statistics of the National Association of Sustainable Mobility, from 2016 to 2019 for new vehicles in the Colombian market, Andemos (2021). Merkuryeba (2019) proposes procedures between techniques that allow a comprehensive approach to forecasts and where the methods complement each other, it is through the use of the methodology in Markov chain models (Kiral and Uzun 2017), plus the methodology of the time series analysis (Stevenson et al 2015), which with a complementary approach, can reach a more detailed and comprehensive level of analysis for the statement about the future of the variable of interest: vehicle market sales for business management.The results showed that Markov chains were very useful in long-term analysis for sales forecasting and their analysis by market segmentation, for this the sales level is ranked according to the technique of Pareto. Another important contribution to the Markov chain in business management corresponds to the analysis disaggregated by sales rankings, for example in ranking 1 (first 5 brands), was obtained an expectation of value defined at 67.1% of the total sales level, also an internal analysis of this percentage ranking was carried out. Complementarily, for the alternative of times series analysis; we start from the analysis of the demand, where a seasonal behavior of vehicle sales is detected. Rockwell and Davis (2016) and Stevenson et al (2015), establish a procedure for estimating and eliminating seasonal components by using the seasonal index. Additionally, Weller and Crone (2012) and Lau et al (2018), recommend two common alternatives to measure forecast error and making decisions to selected the technique more adequate for business management: mean absolute deviation (MAD) and mean absolute percentage error (MAPE), finally, the result of the three techniques developed: moving average, exponential smoothing, and weighted moving average, the simple exponential smoothing, optimized through MAPE minimization is the selected technique, with which short and medium-term forecasts are defined.This study contributes directly to decision-making in the context of the marketing of new vehicles, as well as in academic settings in relation to research processes in data series under the configuration of big data. In this sense, it was demonstrate that the behavior of sales, segmented by market levels according to the participating brands, can be transformed into estimates of future behavior that establishes an orienting mapping of business objectives with respect to the possible level of participation in quotas of market. Finally, the methodological scheme under an epistemological perspective supported by technical decisions, represent an academic contribution of great relevance for business management, where is recommended to use the time series techniques for short and medium-term forecasts, while Markov chains for the prediction and analysis of the sales structure in medium to long term forecasts.

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Venkatesan, Srinjay, S. Sanjay Kumar y Geo Shaji Kutty. "Stock Market Portfolio Prediction Using Machine Learning". En International Research Conference on IOT, Cloud and Data Science. Switzerland: Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-nyoo2h.

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A Stock refers to a share of ownership in a particular company. An investor owns 1 percent of the company if they purchase one part of its ownership divided into 100 parts, each equal to one share. Stock exchanges are run by an automated matching system driven by order demand. Stock prices are defined as “at any particular time, how many buyers and sellers available for the same stock in the market. If the number of buyers is more than sellers, then stock price becomes high” and vice-versa. The stock market depends on many factors like open price, close price, high and low price. Many researchers have tried to predict the stock prices using various ML (machine learning) techniques such as ARIMA model, linear regression, RNN, etc. Because of the uncertainty in stock market, simple models cannot yield any genuine results. The limitations with models like ARIMA, TSLM have been traced in this paper. This paper builds a web application using a library named Streamlit and integrate the stock prediction model. The main objective of this paper is to build a LSTM (Long-Short Term Memory) based RNN (Recurrent Neural Network) model using opening prices in order to get one of the most accurate stock rates.

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Bitetto, Alessandro, Stefano Filomeni y Michele Modina. "Can unlisted firms benefit from market information? A data-driven approach". En CARMA 2022 - 4th International Conference on Advanced Research Methods and Analytics. valencia: Universitat Politècnica de València, 2022. http://dx.doi.org/10.4995/carma2022.2022.15045.

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We employ a sample of 10,136 Italian micro-, small-, and mid-sized enterprises (MSMEs) that borrow from 113 cooperative banks to examine whether market pricing of public firms adds additional information to accounting measures in predicting default of private firms. Specifically, we first match the asset prices of listed firms following a data-driven clustering by means of Neural Networks Autoencoder so to evaluate the firm-wise probability of default (PD) of MSMEs. Then, we adopt three statistical techniques, namely linear models, multivariate adaptive regression spline, and random forest to assess the performance of the models and to explain the relevance of each predictor. Our results provide novel evidence that market information represents a crucial indicator in predicting corporate default of unlisted firms. Indeed, we show a significant improvement of the model performance, both on class-specific (F1-score for defaulted class) and overall metrics (AUC) when using market information in credit risk assessment, in addition to accounting information. Moreover, by taking advantage of global and local variable importance technique we prove that the increase in performance is effectively attributable to market information, highlighting its relevant effect in predicting corporate default.

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Informes sobre el tema "MARKET RESEARCH TECHNIQUES"

Bano, Masooda. Low-Fee Private-Tuition Providers in Developing Countries: An Under-Appreciated and Under- Studied Market—Supply-Side Dynamics in Pakistan. Research on Improving Systems of Education (RISE), agosto de 2022. http://dx.doi.org/10.35489/bsg-rise-wp_2022/107.

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Although low-income parents’ dependence on low-fee private schools has been actively documented in the past decade, existing research and policy discussions have failed to recognise their heavy reliance on low-fee tuition providers in order to ensure that their children complete the primary cycle. By mapping a vibrant supply of low-fee tuition providers in two neighbourhoods in the twin cities of Rawalpindi and Islamabad in Pakistan, this paper argues for understanding the supply-side dynamics of this segment of the education market with the aim of designing better-informed policies, making better use of public spending on supporting private-sector players to reach the poor. Contrary to what is assumed in studies of the private tuition market, the low-fee tuition providers offering services in the Pakistani urban neighbourhoods are not teachers in government schools trying to make extra money by offering afternoon tutorial to children from their schools. Working from their homes, the tutors featured in this paper are mostly women who often have no formal teacher training but are imaginative in their use of a diverse set of teaching techniques to ensure that children from low-income households who cannot get support for education at home cope with their daily homework assignments and pass the annual exams to transition to the next grade. These tutors were motivated to offer tuition by a combination of factors ranging from the need to earn a living, a desire to stay productively engaged, and for some a commitment to help poor children. Arguing that parents expect them to take full responsibility for their children’s educational attainment, these providers view the poor quality of education in schools, the weak maternal involvement in children’s education, and changing cultural norms, whereby children no longer respect authority, as being key to explaining the prevailing low educational levels. The paper presents evidence that the private tuition providers, who may be viewed as education entrepreneurs, have the potential to be used by the state and development agencies to provide better quality education to children from low-income families.

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Yang, Yu y Hen-Geul Yeh. Electrical Vehicle Charging Infrastructure Design and Operations. Mineta Transportation Institute, julio de 2023. http://dx.doi.org/10.31979/mti.2023.2240.

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California aims to achieve five million zero-emission vehicles (ZEVs) on the road by 2030 and 250,000 electrical vehicle (EV) charging stations by 2025. To reduce barriers in this process, the research team developed a simulation-based system for EV charging infrastructure design and operations. The increasing power demand due to the growing EV market requires advanced charging infrastructures and operating strategies. This study will deliver two modules in charging station design and operations, including a vehicle charging schedule and an infrastructure planning module for the solar-powered charging station. The objectives are to increase customers’ satisfaction, reduce the power grid burden, and maximize the profitability of charging stations using state-of-the-art global optimization techniques, machine-learning-based solar power prediction, and model predictive control (MPC). The proposed research has broad societal impacts and significant intellectual merits. First, it meets the demand for green transportation by increasing the number of EV users and reducing the transportation sector’s impacts on climate change. Second, an optimal scheduling tool enables fast charging of EVs and thus improves the mobility of passengers. Third, the designed planning tools enable an optimal design of charging stations equipped with a solar panel and battery energy storage system (BESS) to benefit nationwide transportation system development.

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Vingre, Anete, Peter Kolarz y Billy Bryan. On your marks, get set, fund! Rapid responses to the Covid-19 pandemic. Fteval - Austrian Platform for Research and Technology Policy Evaluation, abril de 2022. http://dx.doi.org/10.22163/fteval.2022.538.

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This paper presents findings from an analysis of seven multidisciplinary national research funders’ responses to COVID-19. We posit that while some parts of research and innovation funding responses to COVID-19 were ‘pandemic responses’ in the conventional biomedical sense, other parts were thematically far broader and are better termed ‘societal emergency’ funding. This type of funding activity was unprecedented for many funders. Yet, it may signal a new/additional mission for research funders, which may be required to tackle future societal emergencies, medical or otherwise. Urgency (i.e., the need to deploy funding quickly) is a key distinguishing theme in these funding activities. This paper explores the different techniques that funders used to substantially speed up their application and assessment processes to ensure research on COVID-19 could commence as quickly as possible. Funders used a range of approaches, both before application submission (call design, application lengths and formats) and after (review and decision-making processes). Our research highlights a series of trade-offs, at the heart of which are concerns around simultaneously ensuring the required speed as well as the quality of funding-decisions. We extract some recommendations for what a generic ‘societal emergency’ funding toolkit might include to optimally manage these tensions in case national research funders are called upon again to respond to future crises.

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Mai Phuong, Nguyen, Hanna North, Duong Minh Tuan y Nguyen Manh Cuong. Assessment of women’s benefits and constraints in participating in agroforestry exemplar landscapes. World Agroforestry, 2021. http://dx.doi.org/10.5716/wp21015.pdf.

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Participating in the exemplar landscapes of the Developing and Promoting Market-Based Agroforestry and Forest Rehabilitation Options for Northwest Vietnam project has had positive impacts on ethnic women, such as increasing their networks and decision-making and public speaking skills. However, the rate of female farmers accessing and using project extension material or participating in project nurseries and applying agroforestry techniques was limited. This requires understanding of the real needs and interests grounded in the socio-cultural contexts of the ethnic groups living in the Northern Mountain Region in Viet Nam, who have unique social and cultural norms and values. The case studies show that agricultural activities are highly gendered: men and women play specific roles and have different, particular constraints and interests. Women are highly constrained by gender norms, access to resources, decision-making power and a prevailing positive-feedback loop of time poverty, especially in the Hmong community. A holistic, timesaving approach to addressing women’s daily activities could reduce the effects of time poverty and increase project participation. As women were highly willing to share project information, the project’s impacts would be more successful with increased participation by women through utilizing informal channels of communication and knowledge dissemination. Extension material designed for ethnic women should have less text and more visuals. Access to information is a critical constraint that perpetuates the norm that men are decision-makers, thereby, enhancing their perceived ownership, whereas women have limited access to information and so leave final decisions to men, especially in Hmong families. Older Hmong women have a Vietnamese (Kinh) language barrier, which further prevents them from accessing the project’s material. Further research into an adaptive framework that can be applied in a variety of contexts is recommended. This framework should prioritize time-saving activities for women and include material highlighting key considerations to maintain accountability among the project’s support staff.

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Bilous, Vladyslav V., Volodymyr V. Proshkin y Oksana S. Lytvyn. Development of AR-applications as a promising area of research for students. [б. в.], noviembre de 2020. http://dx.doi.org/10.31812/123456789/4409.

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The article substantiates the importance of using augmented reality in the educational process, in particular, in the study of natural and mathematical disciplines. The essence of AR (augmented reality), characteristics of AR hardware and software, directions and advantages of using AR in the educational process are outlined. It has proven that AR is a unique tool that allows educators to teach the new digital generation in a readable, comprehensible, memorable and memorable format, which is the basis for developing a strong interest in learning. Presented the results of the international study on the quality of education PISA (Programme for International Student Assessment) which stimulated the development of the problem of using AR in mathematics teaching. Within the limits of realization of research work of students of the Borys Grinchenko Kyiv University the AR-application on mathematics is developed. To create it used tools: Android Studio, SDK, ARCore, QR Generator, Math pattern. A number of markers of mathematical objects have been developed that correspond to the school mathematics course (topic: “Polyhedra and Functions, their properties and graphs”). The developed AR tools were introduced into the process of teaching students of the specialty “Mathematics”. Prospects of research in development of a technique of training of separate mathematics themes with use of AR have been defined.

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Weller, Joel I., Derek M. Bickhart, Micha Ron, Eyal Seroussi, George Liu y George R. Wiggans. Determination of actual polymorphisms responsible for economic trait variation in dairy cattle. United States Department of Agriculture, enero de 2015. http://dx.doi.org/10.32747/2015.7600017.bard.

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The project’s general objectives were to determine specific polymorphisms at the DNA level responsible for observed quantitative trait loci (QTLs) and to estimate their effects, frequencies, and selection potential in the Holstein dairy cattle breed. The specific objectives were to (1) localize the causative polymorphisms to small chromosomal segments based on analysis of 52 U.S. Holstein bulls each with at least 100 sons with high-reliability genetic evaluations using the a posteriori granddaughter design; (2) sequence the complete genomes of at least 40 of those bulls to 20 coverage; (3) determine causative polymorphisms based on concordance between the bulls’ genotypes for specific polymorphisms and their status for a QTL; (4) validate putative quantitative trait variants by genotyping a sample of Israeli Holstein cows; and (5) perform gene expression analysis using statistical methodologies, including determination of signatures of selection, based on somatic cells of cows that are homozygous for contrasting quantitative trait variants; and (6) analyze genes with putative quantitative trait variants using data mining techniques. Current methods for genomic evaluation are based on population-wide linkage disequilibrium between markers and actual alleles that affect traits of interest. Those methods have approximately doubled the rate of genetic gain for most traits in the U.S. Holstein population. With determination of causative polymorphisms, increasing the accuracy of genomic evaluations should be possible by including those genotypes as fixed effects in the analysis models. Determination of causative polymorphisms should also yield useful information on gene function and genetic architecture of complex traits. Concordance between QTL genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 30 trait-by-chromosomal segment effects that are segregating in the U.S. Holstein population; a probability of <10²⁰ was used to accept the null hypothesis that no segregating gene within the chromosomal segment was affecting the trait. Genotypes for 83 grandsires and 17,217 sons were determined by either complete sequence or imputation for 3,148,506 polymorphisms across the entire genome. Variant sites were identified from previous studies (such as the 1000 Bull Genomes Project) and from DNA sequencing of bulls unique to this project, which is one of the largest marker variant surveys conducted for the Holstein breed of cattle. Effects for stature on chromosome 11, daughter pregnancy rate on chromosome 18, and protein percentage on chromosome 20 met 3 criteria: (1) complete or nearly complete concordance, (2) nominal significance of the polymorphism effect after correction for all other polymorphisms, and (3) marker coefficient of determination >40% of total multiple-regression coefficient of determination for the 30 polymorphisms with highest concordance. The missense polymorphism Phe279Tyr in GHR at 31,909,478 base pairs on chromosome 20 was confirmed as the causative mutation for fat and protein concentration. For effect on fat percentage, 12 additional missensepolymorphisms on chromosome 14 were found that had nearly complete concordance with the suggested causative polymorphism (missense mutation Ala232Glu in DGAT1). The markers used in routine U.S. genomic evaluations were increased from 60,000 to 80,000 by adding markers for known QTLs and markers detected in BARD and other research projects. Objectives 1 and 2 were completely accomplished, and objective 3 was partially accomplished. Because no new clear-cut causative polymorphisms were discovered, objectives 4 through 6 were not completed.

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Taylor. L51755 Development and Testing of an Advanced Technology Vibration Transmission. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), julio de 1996. http://dx.doi.org/10.55274/r0010124.

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Fiber optic sensors have been under development in industrial and government laboratories around the world for over a decade. The commercial market for fiber sensors for measuring parameters such as temperature, displacement, and liquid level is now estimated to exceed $100 M/year. Aside from the commercial interest, the U. S. Department of Defense has vigorously pursued the development of fiber gyroscopes and hydrophones. In spite of the high level of research and development activity, however, until recently fiber sensors had not been successfully applied in high-temperature engine environments. The goal of this effort is to develop and test high-temperature fiber optic sensors and show that they are suitable for monitoring vibration and other instabilities in gas turbine engines. The underlying technology developed during the course of PRCI projects PR- 219-9120 and PR-219-9225 during 1991-94 serves as the foundation for PR-240-9416. Transducers with the fiber optic Fabry-Perot interferometer (FFPI) configuration have been adapted for use in the turbomachinery environment.To ensure the survival of the FFPI sensors at high temperatures, two techniques for coating the fibers with metal have been developed: electroplating and vacuum deposition. Coated sensors have subsequently been embedded in aluminum and brass alloys. Experiments on a small Sargent Welch turbine engine have shown the high sensitivity of embedded FFPI strain sensors to vibration in rolling bearings. Data have been collected in both the time and frequency domain. A new accelerometer design in which a metal-coated fiber containing the FFPI element is soldered directly to a diaphragm in a stainless steel housing shows response similar to a piezoelectric accelerometer in shaker table tests. The high sensitivity of the FFPI accelerometer has been demonstrated in field tests in a Solar Centaur turbine engine, and the design has survived temperatures greater than 500�C in a test oven. A magnetometer with a physical configuration similar to that of the accelerometer has been used to measure the distance from the sensor head to a rotating shaft made of ferromagnetic material. This device, which functions as a proximity probe, has been used to monitor shaft rotation rate (keyphasor application) and as a shaft thrust position sensor. These results indicate the potential for performing critical measurements in turbine engines with FFPI sensors. They can measure acceleration, distance (proximity), strain (as it relates to bearing defect diagnosis), and gas pressure, and can operate at higher temperatures than conventional transducers.

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Dinovitzer, Aaron. PR-214-153739-WEB ERW Fatigue Life Integrity Management Improvement - Phase III. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), agosto de 2019. http://dx.doi.org/10.55274/r0011614.

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Tuesday, September 17, 2019 11:00 a.m ET PRESENTER: Aaron Dinovitzer, MA Sc., MBA, PEng, BMT Canada HOST: Mark Piazza, Colonial Pipeline Company MODERATOR: John Lynk, PRCI CLICK THE BUY/DOWNLOAD BUTTON TO ACCESS THE WEBINAR REGISTRATION LINK Join the PRCI Integrity and Inspection Technical Committee as they present research results that set out to evaluate the level of conservatism inherent to current state-of-practice procedures using full-scale fatigue testing. Learning outcomes/benefits of attending: - Understand the sources of conservatism, and how to improve the accuracy of, fatigue life estimation techniques for ERW or EFW pipes containing manufacturing process induced crack-like features. - Learn about an improved estimation method of remaining pipe fatigue life estimates that better agree with actual operational experience. This can reduce conservatism in engineering fatigue life estimates over currently used techniques. - Since fatigue life estimates are used to identify inspection intervals and assessing the life of features in a pipeline system, reducing unnecessary conservatism will avoid the cost of unnecessary inspections, pressure tests and repairs before fatigue life is expended. Who should attend? - Pipeline integrity and risk personnel, engineers and management Recommended pre-reading: PR-214-153739-R01 ERW Fatigue Life Integrity Management Improvement - Phase III Register anyway to automatically receive a link to the webinar recording to view on-demand at your convenience. After registering, you will receive a confirmation email containing information about joining the webinar.

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Morkun, Volodymyr S., Сергій Олексійович Семеріков, Svitlana M. Hryshchenko y Kateryna I. Slovak. System of competencies for mining engineers. Видавництво “CSITA”, 2016. http://dx.doi.org/10.31812/0564/719.

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Topicality of the material, highlighted in this article is stipulated by the need to ensure effectiveness of educational process while preparing mining engineers. System of competencies for future mining engineers, taken as basis for high school sectoral standard for Mining 6.050301 update is theoretically substantiated and developed. Sources of state-of-the-art foreign educational system and technologies as well as scientific research results of local teachers have been analyzed, enabling development of new sectoral standard. Switching to new high school competencies-based sectoral standards is the necessary step in high education reforming in Ukraine, while the application of competencies-based approach to high school sectoral standards development facilitates tuning of education towards labour market’s requirements and demands, further development of educational techniques and educational system as a whole. Objective of the article: to project system of competencies and to define components of environmental competencies for mining engineers. Methods: – theoretical: analysis, generalization, systematization of legislative framework, educational standards, Internet - sources in order to distinguish theoretical basis of research, develop system of competencies for future mining engineers. – Empirical – improvement of system of competencies for future mining engineers. Scientific novelty is represented with structured system, consisting of 49 competencies, comprising the core of new sectoral standard for mining engineers preparation; Practical importance of the outcomes is related to developments: separate constituents of high school draft sectoral standard for Mining engineers bachelors’ preparation 6.050301 Mining (system of social & personal, general scientific, tool-based, general professional and special professional competencies. Research outcomes can be used while developing educational qualification profile and training program for Mining bachelors 6.050301 education field, in course of geoinformational technologies review by ecology, land survey and geography bachelors.

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Yatsymirska, Mariya. MODERN MEDIA TEXT: POLITICAL NARRATIVES, MEANINGS AND SENSES, EMOTIONAL MARKERS. Ivan Franko National University of Lviv, febrero de 2022. http://dx.doi.org/10.30970/vjo.2022.51.11411.

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The article examines modern media texts in the field of political journalism; the role of information narratives and emotional markers in media doctrine is clarified; verbal expression of rational meanings in the articles of famous Ukrainian analysts is shown. Popular theories of emotions in the process of cognition are considered, their relationship with the author’s personality, reader psychology and gonzo journalism is shown. Since the media text, in contrast to the text, is a product of social communication, the main narrative is information with the intention of influencing public opinion. Media text implies the presence of the author as a creator of meanings. In addition, media texts have universal features: word, sound, visuality (stills, photos, videos). They are traditionally divided into radio, TV, newspaper and Internet texts. The concepts of multimedia and hypertext are related to online texts. Web combinations, especially in political journalism, have intensified the interactive branching of nonlinear texts that cannot be published in traditional media. The Internet as a medium has created the conditions for the exchange of ideas in the most emotional way. Hence Gonzo’s interest in journalism, which expresses impressions of certain events in words and epithets, regardless of their stylistic affiliation. There are many such examples on social media in connection with the events surrounding the Wagnerians, the Poroshenko case, Russia’s new aggression against Ukraine, and others. Thus, the study of new features of media text in the context of modern political narratives and emotional markers is important in media research. The article focuses review of etymology, origin and features of using lexemes “cмисл (meaning)” and “сенс (sense)” in linguistic practice of Ukrainians results in the development of meanings and functional stylistic coloring in the usage of these units. Lexemes “cмисл (meaning)” and “сенс (sense)” are used as synonyms, but there are specific fields of meanings where they cannot be interchanged: lexeme “сенс (sense)” should be used when it comes to reasonable grounds for something, lexeme “cмисл (meaning)” should be used when it comes to notion, concept, understanding. Modern political texts are most prominent in genres such as interviews with politicians, political commentaries, analytical articles by media experts and journalists, political reviews, political portraits, political talk shows, and conversations about recent events, accompanied by effective emotional narratives. Etymologically, the concept of “narrative” is associated with the Latin adjective “gnarus” – expert. Speakers, philosophers, and literary critics considered narrative an “example of the human mind.” In modern media texts it is not only “story”, “explanation”, “message techniques”, “chronological reproduction of events”, but first of all the semantic load and what subjective meanings the author voices; it is a process of logical presentation of arguments (narration). The highly professional narrator uses narration as a “method of organizing discourse” around facts and impressions, impresses with his political erudition, extraordinary intelligence and creativity. Some of the above theses are reflected in the following illustrations from the Ukrainian media: “Culture outside politics” – a pro-Russian narrative…” (MP Gabibullayeva); “The next will be Russia – in the post-Soviet space is the Arab Spring…” (journalist Vitaly Portnikov); “In Russia, only the collapse of Ukraine will be perceived as success” (Pavel Klimkin); “Our army is fighting, hiding from the leadership” (Yuri Butusov).

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