For homogeneous charge compression ignition (HCCI) combustion, the auto-ignition process is very sensitive to in-cylinder conditions, including in-cylinder temperature, in-cylinder components and concentrations. The...For homogeneous charge compression ignition (HCCI) combustion, the auto-ignition process is very sensitive to in-cylinder conditions, including in-cylinder temperature, in-cylinder components and concentrations. Therefore, accurate control is required for reliable and efficient HCCI combustion. This paper outlines a simplified gasoline-fueled HCCI engine model implemented in Simulink environment. The model is able to run in real-time and with fixed simulation steps with the aim of cycle-to-cycle control and hardware- in-the-loop simulation. With the aim of controlling the desired amount of the trapped exhaust gas recirculation (EGR) from the previous cycle, the phase of the intake and exhaust valves and the respective profiles are designed to vary in this model. The model is able to anticipate the auto-ignition timing and the in-cylinder pressure and temperature. The validation has been conducted using a comparison of the experimental results on Ricardo Hydro engine published in a research by Tianjin University and a JAGUAR V6 HCCI test engine at the University of Birmingham. The comparison shows the typical HCCI combustion and a fair agreement between the simulation and experimental results.展开更多
Software product lines have recently been presented as one of the best promis-ing improvements for the efficient software development. Different research works contribute supportive parameters and negotiations regardi...Software product lines have recently been presented as one of the best promis-ing improvements for the efficient software development. Different research works contribute supportive parameters and negotiations regarding the prob-lems of producing a perfect software scheme. Traditional approaches or recy-cling software are not effective to solve the problems concerning software competence. Since fast developments with software engineering in the past few years, studies show that some approaches are getting extensive attention in both industries and universities. This method is categorized as the software product line improvement;that supports reusing of software in big organizations. Different industries are adopting product lines to enhance efficiency and reduce operational expenses by way of emerging product developments. This research paper is formed to offer in-depth study regarding the software engineering issues such as complexity, conformity, changeability, invisibility, time constraints, budget constraints, and security. We have conducted various research surveys by visiting different professional software development organizations and took feedback from the professional software engineers to analyze the real-time problems that they are facing during the development process of software systems. Survey results proved that complexity is a most occurring issue that most software developers face while developing software applications. Moreover, invisibility is the problem that rarely happens according to the survey.展开更多
Model transformation is one of the prominent features and the rising research area of Model Driven Engineering (MDE). MDE promotes models to primary artifacts that drive the whole development process. This paper prese...Model transformation is one of the prominent features and the rising research area of Model Driven Engineering (MDE). MDE promotes models to primary artifacts that drive the whole development process. This paper presents the model transformation approach for textual model oriented programs Umple (UML Programming Language) to generate android applications (apps). The proposed approach improved the generation of android source code by using Drools transformation rules and introducing new concern in model driven mobile engineering. The major objective of proposed transformation approach intends to address consistency between source and target model and also intends to handle productivity issues in model driven software development. The main results of model transformation approach are Java class for model layer, XML file for view layer and android activity class for controller layer. Results show that proposed approach achieves high consistency between source and target model and also improves model transformation productivity.展开更多
This article presents an innovative approach to automatic rule discovery for data transformation tasks leveraging XGBoost,a machine learning algorithm renowned for its efficiency and performance.The framework proposed...This article presents an innovative approach to automatic rule discovery for data transformation tasks leveraging XGBoost,a machine learning algorithm renowned for its efficiency and performance.The framework proposed herein utilizes the fusion of diversified feature formats,specifically,metadata,textual,and pattern features.The goal is to enhance the system’s ability to discern and generalize transformation rules fromsource to destination formats in varied contexts.Firstly,the article delves into the methodology for extracting these distinct features from raw data and the pre-processing steps undertaken to prepare the data for the model.Subsequent sections expound on the mechanism of feature optimization using Recursive Feature Elimination(RFE)with linear regression,aiming to retain the most contributive features and eliminate redundant or less significant ones.The core of the research revolves around the deployment of the XGBoostmodel for training,using the prepared and optimized feature sets.The article presents a detailed overview of the mathematical model and algorithmic steps behind this procedure.Finally,the process of rule discovery(prediction phase)by the trained XGBoost model is explained,underscoring its role in real-time,automated data transformations.By employingmachine learning and particularly,the XGBoost model in the context of Business Rule Engine(BRE)data transformation,the article underscores a paradigm shift towardsmore scalable,efficient,and less human-dependent data transformation systems.This research opens doors for further exploration into automated rule discovery systems and their applications in various sectors.展开更多
In recent years, with the rapid development of sensing technology and deployment of various Internet of Everything devices, it becomes a crucial and practical challenge to enable real-time search queries for objects, ...In recent years, with the rapid development of sensing technology and deployment of various Internet of Everything devices, it becomes a crucial and practical challenge to enable real-time search queries for objects, data, and services in the Internet of Everything. Moreover, such efficient query processing techniques can provide strong facilitate the research on Internet of Everything security issues. By looking into the unique characteristics in the IoE application environment, such as high heterogeneity, high dynamics, and distributed, we develop a novel search engine model, and build a dynamic prediction model of the IoE sensor time series to meet the real-time requirements for the Internet of Everything search environment. We validated the accuracy and effectiveness of the dynamic prediction model using a public sensor dataset from Intel Lab.展开更多
A hardware-in-the-loop simulating platform is developed to avoid designing defects caused by the complicated logical structure and multiple-functional buildup of the dectronic control unit(ECU)in modem diesel engine...A hardware-in-the-loop simulating platform is developed to avoid designing defects caused by the complicated logical structure and multiple-functional buildup of the dectronic control unit(ECU)in modem diesel engines, and to diminish potential damages on components or human exposure to dangers in R&D en- deavor. This plat-form consists of a computer installed with software Matlab/Simulink/RTW and dSPACE/ ControlDesk; a diesel engine ECU, and a dSPACE autobox which runs a real-time diesel engine model. A typical model of diesel engine with turbocharger and intercooler is presented. Based on this model our research is carried out with a real ECU to test its software control strategies. Results show that by using the diesel engine model downloaded inside, the hardware-in-the-loop platform can simulate diesel engine's working conditions and generate all kinds of sensor signals which ECU needs on a real-time basis. So the ECU control strategies can be validated and relevant parameters roughly calibrated.展开更多
为准确模拟桥址随机车流荷载,提出基于可变元胞与跟驰理论的元胞自动机(cellular automata,CA)模型。首先,重新定义元胞构成,提出以车辆为核心的动态可变元胞,并将精确的轴间距和轴重信息融入车辆元胞,实现车辆荷载的精确模拟;然后,引...为准确模拟桥址随机车流荷载,提出基于可变元胞与跟驰理论的元胞自动机(cellular automata,CA)模型。首先,重新定义元胞构成,提出以车辆为核心的动态可变元胞,并将精确的轴间距和轴重信息融入车辆元胞,实现车辆荷载的精确模拟;然后,引入跟驰理论,提出基于跟驰理论的状态演化规则,推导每辆车的专有加速度,实现车辆微观交互的模拟;最后,提出基于实测动态称重系统(weigh in motion,WIM)数据的发车规则,依据WIM数据,重构任意时段的实际车队,并建立基于车头时距的发车规则,重现车辆通过WIM时的运动状态。基于所提出的发车规则和动态演化规则,实现车辆从进入道路到驶离道路全过程时空位置的准确模拟,结合融入精确轴载的车辆元胞,实现随机车流荷载的模拟。基于实测WIM数据验证所提模型的可行性和先进性。结果表明:可变元胞可以精确模拟车辆荷载;提出的状态演化规则可以根据不同车辆的运动状态计算得到每辆车的专属加速度,准确模拟每辆车在自由行驶和跟驰行驶时的不同运动状态;新发车规则可以重构任意时段的实测车队,结合新状态演化规则,可以实现桥址任意时段随机车流的模拟。结合精细化车辆荷载模拟和合理的车流模拟,可实现桥址随机车流荷载模拟。展开更多
文摘For homogeneous charge compression ignition (HCCI) combustion, the auto-ignition process is very sensitive to in-cylinder conditions, including in-cylinder temperature, in-cylinder components and concentrations. Therefore, accurate control is required for reliable and efficient HCCI combustion. This paper outlines a simplified gasoline-fueled HCCI engine model implemented in Simulink environment. The model is able to run in real-time and with fixed simulation steps with the aim of cycle-to-cycle control and hardware- in-the-loop simulation. With the aim of controlling the desired amount of the trapped exhaust gas recirculation (EGR) from the previous cycle, the phase of the intake and exhaust valves and the respective profiles are designed to vary in this model. The model is able to anticipate the auto-ignition timing and the in-cylinder pressure and temperature. The validation has been conducted using a comparison of the experimental results on Ricardo Hydro engine published in a research by Tianjin University and a JAGUAR V6 HCCI test engine at the University of Birmingham. The comparison shows the typical HCCI combustion and a fair agreement between the simulation and experimental results.
文摘Software product lines have recently been presented as one of the best promis-ing improvements for the efficient software development. Different research works contribute supportive parameters and negotiations regarding the prob-lems of producing a perfect software scheme. Traditional approaches or recy-cling software are not effective to solve the problems concerning software competence. Since fast developments with software engineering in the past few years, studies show that some approaches are getting extensive attention in both industries and universities. This method is categorized as the software product line improvement;that supports reusing of software in big organizations. Different industries are adopting product lines to enhance efficiency and reduce operational expenses by way of emerging product developments. This research paper is formed to offer in-depth study regarding the software engineering issues such as complexity, conformity, changeability, invisibility, time constraints, budget constraints, and security. We have conducted various research surveys by visiting different professional software development organizations and took feedback from the professional software engineers to analyze the real-time problems that they are facing during the development process of software systems. Survey results proved that complexity is a most occurring issue that most software developers face while developing software applications. Moreover, invisibility is the problem that rarely happens according to the survey.
文摘Model transformation is one of the prominent features and the rising research area of Model Driven Engineering (MDE). MDE promotes models to primary artifacts that drive the whole development process. This paper presents the model transformation approach for textual model oriented programs Umple (UML Programming Language) to generate android applications (apps). The proposed approach improved the generation of android source code by using Drools transformation rules and introducing new concern in model driven mobile engineering. The major objective of proposed transformation approach intends to address consistency between source and target model and also intends to handle productivity issues in model driven software development. The main results of model transformation approach are Java class for model layer, XML file for view layer and android activity class for controller layer. Results show that proposed approach achieves high consistency between source and target model and also improves model transformation productivity.
文摘This article presents an innovative approach to automatic rule discovery for data transformation tasks leveraging XGBoost,a machine learning algorithm renowned for its efficiency and performance.The framework proposed herein utilizes the fusion of diversified feature formats,specifically,metadata,textual,and pattern features.The goal is to enhance the system’s ability to discern and generalize transformation rules fromsource to destination formats in varied contexts.Firstly,the article delves into the methodology for extracting these distinct features from raw data and the pre-processing steps undertaken to prepare the data for the model.Subsequent sections expound on the mechanism of feature optimization using Recursive Feature Elimination(RFE)with linear regression,aiming to retain the most contributive features and eliminate redundant or less significant ones.The core of the research revolves around the deployment of the XGBoostmodel for training,using the prepared and optimized feature sets.The article presents a detailed overview of the mathematical model and algorithmic steps behind this procedure.Finally,the process of rule discovery(prediction phase)by the trained XGBoost model is explained,underscoring its role in real-time,automated data transformations.By employingmachine learning and particularly,the XGBoost model in the context of Business Rule Engine(BRE)data transformation,the article underscores a paradigm shift towardsmore scalable,efficient,and less human-dependent data transformation systems.This research opens doors for further exploration into automated rule discovery systems and their applications in various sectors.
基金supported by the National Natural Science Foundation of China under NO.61572153, NO. 61702220, NO. 61702223, and NO. U1636215the National Key research and Development Plan (Grant No. 2018YFB0803504)
文摘In recent years, with the rapid development of sensing technology and deployment of various Internet of Everything devices, it becomes a crucial and practical challenge to enable real-time search queries for objects, data, and services in the Internet of Everything. Moreover, such efficient query processing techniques can provide strong facilitate the research on Internet of Everything security issues. By looking into the unique characteristics in the IoE application environment, such as high heterogeneity, high dynamics, and distributed, we develop a novel search engine model, and build a dynamic prediction model of the IoE sensor time series to meet the real-time requirements for the Internet of Everything search environment. We validated the accuracy and effectiveness of the dynamic prediction model using a public sensor dataset from Intel Lab.
基金Sponsored by the Ministerial Level Advanced Research(10660060220)
文摘A hardware-in-the-loop simulating platform is developed to avoid designing defects caused by the complicated logical structure and multiple-functional buildup of the dectronic control unit(ECU)in modem diesel engines, and to diminish potential damages on components or human exposure to dangers in R&D en- deavor. This plat-form consists of a computer installed with software Matlab/Simulink/RTW and dSPACE/ ControlDesk; a diesel engine ECU, and a dSPACE autobox which runs a real-time diesel engine model. A typical model of diesel engine with turbocharger and intercooler is presented. Based on this model our research is carried out with a real ECU to test its software control strategies. Results show that by using the diesel engine model downloaded inside, the hardware-in-the-loop platform can simulate diesel engine's working conditions and generate all kinds of sensor signals which ECU needs on a real-time basis. So the ECU control strategies can be validated and relevant parameters roughly calibrated.
文摘为准确模拟桥址随机车流荷载,提出基于可变元胞与跟驰理论的元胞自动机(cellular automata,CA)模型。首先,重新定义元胞构成,提出以车辆为核心的动态可变元胞,并将精确的轴间距和轴重信息融入车辆元胞,实现车辆荷载的精确模拟;然后,引入跟驰理论,提出基于跟驰理论的状态演化规则,推导每辆车的专有加速度,实现车辆微观交互的模拟;最后,提出基于实测动态称重系统(weigh in motion,WIM)数据的发车规则,依据WIM数据,重构任意时段的实际车队,并建立基于车头时距的发车规则,重现车辆通过WIM时的运动状态。基于所提出的发车规则和动态演化规则,实现车辆从进入道路到驶离道路全过程时空位置的准确模拟,结合融入精确轴载的车辆元胞,实现随机车流荷载的模拟。基于实测WIM数据验证所提模型的可行性和先进性。结果表明:可变元胞可以精确模拟车辆荷载;提出的状态演化规则可以根据不同车辆的运动状态计算得到每辆车的专属加速度,准确模拟每辆车在自由行驶和跟驰行驶时的不同运动状态;新发车规则可以重构任意时段的实测车队,结合新状态演化规则,可以实现桥址任意时段随机车流的模拟。结合精细化车辆荷载模拟和合理的车流模拟,可实现桥址随机车流荷载模拟。