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نتیجه جستجو - COMPETING MODELS

تعداد مقالات یافته شده: 5
ردیف عنوان نوع
1 On a partial least squares regression model for asymmetric data with a chemical application in mining
مدل رگرسیون حداقل مربعات جزئی برای داده های نامتقارن با کاربرد شیمیایی در معدن-2019
In chemometrical applications, covariates in regression models are often correlated, causing a collinearity problem that can be solved by partial least squares (PLS) regression. In addition, high dimensionality in the space of covariates is also a problem with more parameters than cases, a phenomenon usually found in chemical spectral data that can also be solved by PLS regression. The Birnbaum-Saunders distribution has theoretical justifications for modeling chemical data. In this paper, a new methodology based on PLS regression models is proposed considering a reparameterized Birnbaum-Saunders (RBS) distribution for the response, which is useful for describing asymmetric data frequently found in chemical phenomena. We estimate the RBS-PLS model parameters using the maximum likelihood method. A bootstrap approach is employed to obtain the optimal number of PLS components. Quantile residuals and Cook and Mahalanobis type distances are utilized for detecting possible anomalies in the modeling. We conduct perturbation studies to assess the performance of these diagnostic tools. The proposed methodology is applied to real-world kaolinite data and compared to other competing models. This provides a useful illustration of chemical analysis in the mining industry
Keywords: Bootstrapping | Cook and Mahalanobis distances | Diagnostic analysis | GLM | Likelihood method | NIR spectral data | PCA | R software | Statistical residuals
مقاله انگلیسی
2 Using deep learning to evaluate peaks in chromatographic data
استفاده از یادگیری عمیق برای ارزیابی قله ها در داده های کروماتوگرافی-2019
Analysis of untargeted gas-chromatographic data is time consuming. With the earlier introduction of the PARAFAC2 (PARAllel FACtor analysis 2) based PARADISe (PARAFAC2 based Deconvolution and Identification System) approach in 2017, this task was made considerably more time-efficient. However, there are still a number of manual steps in the analysis which require data analytical expertise. One of these is the need to define whether or not each PARAFAC2 resolved component represents a peak suitable for integration. As the peaks may change in both shape and location on the elution time-axis, this presents a problem which cannot be readily solved by applying a linear classifier, such as PLS-DA (Partial Least Squares regression for Discriminant Analysis). As part of our ongoing efforts to further automate analysis of Gas Chromatography with Mass Spectrometry (GC-MS), we therefore explore a convolutional neural network classifier, capable of handling these shifts and variations in shape. The theory of convolutional neural networks and application on vector samples is briefly explained, and the performance is tested against a PLS-DA classifier, a shallow artificial neural network and a locally weighted regression model. The models are built on a training set with PARAFAC2 resolved components from eight different aroma related GC-MS runs with a total of over 70,000 elution profile samples, and validated using another, independent, GC-MS dataset. Based on Receiver Operating Characteristic curves (ROC) and manual analysis of the misclassified cases, it is shown that the convolutional network consistently outperforms the competing models, yielding an Area Under the Curve (AUC) value of 0.95 for peak classification. Examples are given illustrating that this new approach provides convincing means to automatically assess and evaluate modelled elution profiles of chromatographic data and thereby remove this laborious manual step.
Keywords: Deep learning | PARAFAC2 | Expert system | Automation
مقاله انگلیسی
3 Understanding the role of technology in service innovation: Comparison of three theoretical perspectives
درک نقش فناوری در نوآوری خدمات: مقایسه سه دیدگاه تئوریکی-2018
Although prior studies have stressed the importance of technology in service innovation, debates on the roles of technology continue to surface. This study aims to investigate the role of technology in service innovation based on a service innovation framework. After identifying four innovation orientations, we propose three competing models having different roles of technology (direct, indirect, and moderating). Using data from 193 service firms, we determine which model best explains the role of technology. Results show that technology plays multiple roles in service innovation. Our study helps managers effectively coordinate their technology infusion into service innovation to improve firm performance.
keywords: Service innovation| Technology| Strategic innovation orientation| Resource-advantage theory| Technology-push perspective| Complementarity theory
مقاله انگلیسی
4 Adoption of Internet of Things in India: A test of competing models using a structured equation modeling approach
تصویب اینترنت اشیاء در هند: تست مدل های رقابت با استفاده از رویکرد مدل سازی معادلات ساختاری-2017
Internet of Things based applications for smart homes, wearable health devices, and smart cities are in the evo lutionary stage in India. Adoption of Internet of Things is still limited to a few application areas. In developing countries, the usefulness of IOTs adoption is recognized as a key factor for economic and social development of a country by both academicians and practitioners as well. Currently, there are still very few studies that explore the adoption of Internet of Things from a multiple theory perspective, namely, The Theory of Reasoned Action (TRA), The Theory of Planned Behaviour (TPB) and The Technology Acceptance Model (TAM). This research aims to satisfy a clear gap in the main field of research by proposing a Structured Equation Model (SEM) approach to test three competing models in the context of Internet of Things in India. With respect to previous literature, this research sets the stage for extensive research in a broad domain of application areas for the Internet of Things, like healthcare, elderly well- being and support, smart cities and smart supply chains etc.
Keywords: Internet of Things | Healthcare | Smart cities | Smart supply-chain management | Indian market | Multiple-theory based approach
مقاله انگلیسی
5 رهبری انتقالی در کارگروه خدمات مصرف کننده: مدل های رقابتی رضایت شغلی، تعهد تغییر و تضاد مشارکتی
سال انتشار: 2014 - تعداد صفحات فایل pdf انگلیسی: 18 - تعداد صفحات فایل doc فارسی: 27
این مقاله درباره اثرات رهبری انتقالی بر حل (مدیریت) تضاد مشارکتی از طریق ارزیابی مدل های مرتبط جایگزین مربوط به متعادل سازی نقش رضایت شغلی و تعهد تغییر بحث می کند. نمونه هایی از اطلاعات مربوط به کارکنان بخش خدمات مشتریان در کشور تایوان مورد ارزیابی واقع شده است. براساس تکنیک نمونه بوت استرپینگ ، یک مطالعه تجربی برای دستیابی به بهترین مدل تطبق انجام شده است. روند تحلیل مدل سلسه مراتبی تو در تو استفاده شده است که روش های متعادل سازی بوت استرپ، PRODCLIN2 و مقایسه مدل سازی معادلات ساختاری (SEM) را در بر می گیرد. این تحلیل پیشنهاد می دهد که رهبری که یکپارچگی (تعهد به تغییر) را ترویج می دهد و الهام و انگیزه (رضایت شغلی) را فراهم می کند، به روشی مناسب می تواند ابزارهایی را برای حل تضاد های مشارکتی و همکاری فراهم کند.
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