The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software w...The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two state-of-the-art methods.展开更多
随着信息化技术的日益发展,建筑信息模型(building information modeling,BIM)技术已在建筑结构设计领域得到较为成熟的运用。对于一些结构复杂的建筑工程,在设计阶段解决结构和机电等专业的冲突,对于保障现场顺利施工至关重要。以新加...随着信息化技术的日益发展,建筑信息模型(building information modeling,BIM)技术已在建筑结构设计领域得到较为成熟的运用。对于一些结构复杂的建筑工程,在设计阶段解决结构和机电等专业的冲突,对于保障现场顺利施工至关重要。以新加坡裕廊区域线登加车辆段与综合基地J101项目的高架桥为研究对象,采用REVIT软件进行三维可视化桥梁结构建模、参数化设计,最终解决了桥面板主筋与抗剪钢筋、剪力键钢筋、预埋管道等的冲突问题以及完成了工程量的自动统计,为工程项目带来了较好的经济效益。研究表明:BIM技术具有可视化、协同化、参数化等优点,能够显著提高建筑结构设计的质量和效率;本文为同类工程提供了可复制的数字化解决方案,对推动建筑行业技术进步及智能化转型具有重要示范价值。展开更多
Software is an important part of automotive product development, and it is commonly known that software quality assurance consumes considerable effort in safety-critical embedded software development. Increasing the e...Software is an important part of automotive product development, and it is commonly known that software quality assurance consumes considerable effort in safety-critical embedded software development. Increasing the effectiveness and efficiency of this effort thus becomes more and more important. Identifying problematic code areas which are most likely to fail and therefore require most of the quality assurance attention is required. This article presents an exploratory study investigating whether the faults detected by static analysis tools combined with code complexity metrics can be used as software quality indicators and to build pre-release fault prediction models. The combination of code complexity metrics with static analysis fault density was used to predict the pre-release fault density with an accuracy of 78.3%. This combination was also used to separate high and low quality components with a classification accuracy of 79%.展开更多
The most common way to analyze economics data is to use statistics software and spreadsheets.The paper presents opportunities of modern Geographical Information System （GIS） for analysis of marketing, statistical, a...The most common way to analyze economics data is to use statistics software and spreadsheets.The paper presents opportunities of modern Geographical Information System （GIS） for analysis of marketing, statistical, and macroeconomic data. It considers existing tools and models and their applications in various sectors. The advantage is that the statistical data could be combined with geographic views, maps and also additional data derived from the GIS. As a result, a programming system is developed, using GIS for analysis of marketing, statistical, macroeconomic data, and risk assessment in real time and prevention. The system has been successfully implemented as web-based software application designed for use with a variety of hardware platforms （mobile devices, laptops, and desktop computers）. The software is mainly written in the programming language Python, which offers a better structure and supports for the development of large applications. Optimization of the analysis, visualization of macroeconomic, and statistical data by region for different business research are achieved. The system is designed with Geographical Information System for settlements in their respective countries and regions. Information system integration with external software packages for statistical calculations and analysis is implemented in order to share data analyzing, processing, and forecasting. Technologies and processes for loading data from different sources and tools for data analysis are developed. The successfully developed system allows implementation of qualitative data analysis.展开更多
Medical device clinical trial is a preliminary clinical human safety and effectiveness evaluation test. With the rapid development of science and technology, the research and development of medical devices is increasi...Medical device clinical trial is a preliminary clinical human safety and effectiveness evaluation test. With the rapid development of science and technology, the research and development of medical devices is increasing year by year, so it is particularly important to improve the clinical research level of medical devices. Medical statistics is one of the effective means to ensure scientific and reasonable clinical trial design and reliable test results. SAS software is important software for statistical analysis of clinical trials of medical equipment. Starting from the specific application of SAS software, this paper focuses on correctly understanding and selecting various results of SAS statistics, and provides some practical experience for those who learn to apply SAS, so as to make the clinical statistics of medical devices possible. The trial is more accurate and scientific.展开更多
文摘The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two state-of-the-art methods.
文摘随着信息化技术的日益发展,建筑信息模型(building information modeling,BIM)技术已在建筑结构设计领域得到较为成熟的运用。对于一些结构复杂的建筑工程,在设计阶段解决结构和机电等专业的冲突,对于保障现场顺利施工至关重要。以新加坡裕廊区域线登加车辆段与综合基地J101项目的高架桥为研究对象,采用REVIT软件进行三维可视化桥梁结构建模、参数化设计,最终解决了桥面板主筋与抗剪钢筋、剪力键钢筋、预埋管道等的冲突问题以及完成了工程量的自动统计,为工程项目带来了较好的经济效益。研究表明:BIM技术具有可视化、协同化、参数化等优点,能够显著提高建筑结构设计的质量和效率;本文为同类工程提供了可复制的数字化解决方案,对推动建筑行业技术进步及智能化转型具有重要示范价值。
文摘Software is an important part of automotive product development, and it is commonly known that software quality assurance consumes considerable effort in safety-critical embedded software development. Increasing the effectiveness and efficiency of this effort thus becomes more and more important. Identifying problematic code areas which are most likely to fail and therefore require most of the quality assurance attention is required. This article presents an exploratory study investigating whether the faults detected by static analysis tools combined with code complexity metrics can be used as software quality indicators and to build pre-release fault prediction models. The combination of code complexity metrics with static analysis fault density was used to predict the pre-release fault density with an accuracy of 78.3%. This combination was also used to separate high and low quality components with a classification accuracy of 79%.
文摘The most common way to analyze economics data is to use statistics software and spreadsheets.The paper presents opportunities of modern Geographical Information System （GIS） for analysis of marketing, statistical, and macroeconomic data. It considers existing tools and models and their applications in various sectors. The advantage is that the statistical data could be combined with geographic views, maps and also additional data derived from the GIS. As a result, a programming system is developed, using GIS for analysis of marketing, statistical, macroeconomic data, and risk assessment in real time and prevention. The system has been successfully implemented as web-based software application designed for use with a variety of hardware platforms （mobile devices, laptops, and desktop computers）. The software is mainly written in the programming language Python, which offers a better structure and supports for the development of large applications. Optimization of the analysis, visualization of macroeconomic, and statistical data by region for different business research are achieved. The system is designed with Geographical Information System for settlements in their respective countries and regions. Information system integration with external software packages for statistical calculations and analysis is implemented in order to share data analyzing, processing, and forecasting. Technologies and processes for loading data from different sources and tools for data analysis are developed. The successfully developed system allows implementation of qualitative data analysis.
文摘Medical device clinical trial is a preliminary clinical human safety and effectiveness evaluation test. With the rapid development of science and technology, the research and development of medical devices is increasing year by year, so it is particularly important to improve the clinical research level of medical devices. Medical statistics is one of the effective means to ensure scientific and reasonable clinical trial design and reliable test results. SAS software is important software for statistical analysis of clinical trials of medical equipment. Starting from the specific application of SAS software, this paper focuses on correctly understanding and selecting various results of SAS statistics, and provides some practical experience for those who learn to apply SAS, so as to make the clinical statistics of medical devices possible. The trial is more accurate and scientific.
