data provenance refers to the historical record of the derivation of the data, allowing the reproduction of experiments, interpretation of results and identification of problems through the analysis of the processes t...
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ISBN:
(纸本)1891706411
data provenance refers to the historical record of the derivation of the data, allowing the reproduction of experiments, interpretation of results and identification of problems through the analysis of the processes that originated the data. data provenance contributes to the evaluation of experiments. This paper presents a framework for data provenance using the W3C provenance data model, called PROV-DM. Such framework aims at contributing to, and facilitating, the collection, storage and retrieval of provenance data through a modeling and storage layer based on PROV-DM, yet is compatible with other representations of PROV such as PROV-O. To demonstrate the utilization of the framework, it was used in an IoT application that performs the gas classification to identify diseases.
In order to improve the ability of defect detection and effective testing of multimedia application software, the technology of defect data generation of multimedia application software for group users is proposed. Th...
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In recent years, more than thirty bridge accidents have occurred in China, but only few accidents were tracked and most accident investigation reports were not open to the public. The Yangmingtan Bridge collapse accid...
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In recent years, more than thirty bridge accidents have occurred in China, but only few accidents were tracked and most accident investigation reports were not open to the public. The Yangmingtan Bridge collapse accident occurred on 24 August, 2012 in Harbin City, which caused three fatalities and five injuries. This accident has evoked wide concern from the public and media, but no official report provided any conclusion on the cause of the accident until now, while no related research was ever undertaken either. NVivo is a qualitative data analysis package which helps researchers to organize and analyze complex non numerical or unstructured data. Because of the lack of data in the official report, this research collected both texts and multimedia information from the web, newspaper and videos to identify potential root causes of the accident. This research first organized all information with the aid of NVivo 8.0 software. Then Rasmussen's accident causation model was adopted for use as the frame nodes for the case study. Based on the software, this research analyzed the system wide failures and actions involved in the accident and identified the multi-levels of failure modes which included government, regulatory agency, company, management, staff, and the physical accident sequence. (C) 2015 Elsevier Ltd. All rights reserved.
Developers often refactor code to improve the maintainability and comprehension of the software. There are many studies on refactoring activities in traditional software systems. However, refactoring in data-intensive...
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ISBN:
(纸本)9781665437868
Developers often refactor code to improve the maintainability and comprehension of the software. There are many studies on refactoring activities in traditional software systems. However, refactoring in data-intensive systems is not well explored. Understanding the refactoring practices of developers is important to develop efficient tool *** conducted a longitudinal study of refactoring activities in data access classes using 12 data-intensive subject systems. We investigated the prevalence and evolution of refactorings and the association of refactorings with data access smells. We also conducted a manual analysis of over 378 samples of data access refactoring instances to identify the functionalities of the code that are targeted by such refactorings. Our results show that (1) data access refactorings are prevalent and different in type. Rename variable is the most prevalent data access refactoring. (2) The prevalence and type of refactorings vary as systems evolve in time. (3) Most data access refactorings target codes that implement data fetching and insertion. (4) data access refactorings do not generally touch SQL queries. Overall, the results show that data access refactorings focus on improving the code quality but not the underlying data access operations. Hence, more work is needed from the research community on providing awareness and support to practitioners on the benefits of addressing data access smells with refactorings.
Satellite data transmission scheduling is assigning limited ground resources for satellite data requests reasonably in the condition of many satellites and ground stations with considering many constraints. Its purpos...
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ISBN:
(纸本)9781479953769
Satellite data transmission scheduling is assigning limited ground resources for satellite data requests reasonably in the condition of many satellites and ground stations with considering many constraints. Its purpose is improving the efficient usage of ground resources. In this paper, we focus on the building of satellite data transmission scheduling and algorithm. We describe the constraints of satellite data transmission scheduling formally and analyze the process of satellites data transmission. We put forward conflict degrees of data transmission after analyzing the data transmission time windows. And we give one strategy to resolve the conflicts. We build models of satellite data transmission after giving the resolve the problem based on its characteristic. Owing to the shortcoming of GA, we connect Tabu Search Algorithm(TSA) with Genetic Algorithms (GA), we call the combination TSGA. We get the scene of scheduling by the software of STK. We build several evaluation indexes of two kinds of algorithms. The results show that TSGA algorithm outperforms GA.
Ordinary Least squares (OLS) are the most widely used due to tradition and their optimal properties to estimate the parameters of linear and nonlinear regression models. Nevertheless, in the presence of outliers in th...
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ISBN:
(纸本)9781665426329
Ordinary Least squares (OLS) are the most widely used due to tradition and their optimal properties to estimate the parameters of linear and nonlinear regression models. Nevertheless, in the presence of outliers in the data, estimates of OLS become inefficient, and even a single unusual point can have a significant impact on the estimation of parameters. In the presence of outliers is the use of robust estimators rather than the method of OLS. They are finding a suitable nonlinear transformation to reduce anomalies, including non-additivity, heteroscedasticity, and non-normality in multiple nonlinear regression. It might be beneficial to transform the response variable or predictor variable, or both together to present the equation in a simple, functional form that is linear in the transformed variables. To illustrate the superior transformation function, we compare the squared correlation coefficient (coefficient of determination), Breusch-Pagan test, and Shapiro-Wilk test between the transformation functions.
Handling large data sets is becoming quite a challenge in the field of bioinformatics. Bioinformatics softwares such as plink are not designed to scale automatically to multiple computing nodes and to process rapidly ...
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ISBN:
(纸本)9781450342247
Handling large data sets is becoming quite a challenge in the field of bioinformatics. Bioinformatics softwares such as plink are not designed to scale automatically to multiple computing nodes and to process rapidly very large datasets, on demand.
Machine learning (ML) techniques are used to make the software development process more efficient and effective. Many ML approaches have also been proposed to automate Requirements engineering (RE) activities such as ...
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ISBN:
(纸本)9781665418980
Machine learning (ML) techniques are used to make the software development process more efficient and effective. Many ML approaches have also been proposed to automate Requirements engineering (RE) activities such as ambiguity detection, traceability analysis and to address complex RE challenges. The overall goal of this research is to explore the state of the art of application of ML in RE and to determine the effectiveness of ML in improving the RE process and artefacts. Following the Evidence-Based softwareengineering approach, we performed a mapping study of the empirical studies on ML techniques and approaches used in RE published between 2010 and April 2020. data were extracted from the selected papers about the ML techniques, problems, and challenges of using ML, identification of the used datasets, and the evaluation metrics employed to assess the ML techniques. We analyzed 65 relevant papers in this mapping study. Our analysis shows that ML is an effective tool for automating RE analysis tasks, overcoming complexity, and reducing cost and time. We also present the gaps in the ML for RE literature and suggest areas that need further research.
A novel 3D shape preserving data reduction technique for managing the amount of data acquired by laser scanning is presented that overcomes the shortcomings of existing filter-based methods. The technique is based on ...
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ISBN:
(纸本)9781605603360
A novel 3D shape preserving data reduction technique for managing the amount of data acquired by laser scanning is presented that overcomes the shortcomings of existing filter-based methods. The technique is based on a discrete Gaussian image of the scanned points which is obtained by estimating surface normals and projecting them into a Gaussian sphere. The discrete Gaussian image is then used to partition the points into cells. In each cell, a reference point and its neighbours are used to determine the cell representative point and all other points are removed. The performance of the proposed method is illustrated using a range of point clouds scanned from typical engineering surfaces.
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