PL/SQL is the most common language for ORACLE database application. It allows the developer to create stored program units (Procedures, Functions, and Packages) to improve software reusability and hide the complexity ...PL/SQL is the most common language for ORACLE database application. It allows the developer to create stored program units (Procedures, Functions, and Packages) to improve software reusability and hide the complexity of the execution of a specific operation behind a name. Also, it acts as an interface between SQL database and DEVELOPER. Therefore, it is important to test these modules that consist of procedures and functions. In this paper, a new genetic algorithm (GA), as search technique, is used in order to find the required test data according to branch criteria to test stored PL/SQL program units. The experimental results show that this was not fully achieved, such that the test target in some branches is not reached and the coverage percentage is 98%. A problem rises when target branch is depending on data retrieved from tables;in this case, GA is not able to generate test cases for this branch.展开更多
The advent of healthcare information management systems(HIMSs)continues to produce large volumes of healthcare data for patient care and compliance and regulatory requirements at a global scale.Analysis of this big da...The advent of healthcare information management systems(HIMSs)continues to produce large volumes of healthcare data for patient care and compliance and regulatory requirements at a global scale.Analysis of this big data allows for boundless potential outcomes for discovering knowledge.Big data analytics(BDA)in healthcare can,for instance,help determine causes of diseases,generate effective diagnoses,enhance Qo S guarantees by increasing efficiency of the healthcare delivery and effectiveness and viability of treatments,generate accurate predictions of readmissions,enhance clinical care,and pinpoint opportunities for cost savings.However,BDA implementations in any domain are generally complicated and resource-intensive with a high failure rate and no roadmap or success strategies to guide the practitioners.In this paper,we present a comprehensive roadmap to derive insights from BDA in the healthcare(patient care)domain,based on the results of a systematic literature review.We initially determine big data characteristics for healthcare and then review BDA applications to healthcare in academic research focusing particularly on No SQL databases.We also identify the limitations and challenges of these applications and justify the potential of No SQL databases to address these challenges and further enhance BDA healthcare research.We then propose and describe a state-of-the-art BDA architecture called Med-BDA for healthcare domain which solves all current BDA challenges and is based on the latest zeta big data paradigm.We also present success strategies to ensure the working of Med-BDA along with outlining the major benefits of BDA applications to healthcare.Finally,we compare our work with other related literature reviews across twelve hallmark features to justify the novelty and importance of our work.The aforementioned contributions of our work are collectively unique and clearly present a roadmap for clinical administrators,practitioners and professionals to successfully implement BDA initiatives in their organizations.展开更多
Radio frequency identification(RFID) enabled retail store management needs workflow optimization to facilitate real-time decision making. In this paper, complex event processing(CEP) based RFID-enabled retail store ma...Radio frequency identification(RFID) enabled retail store management needs workflow optimization to facilitate real-time decision making. In this paper, complex event processing(CEP) based RFID-enabled retail store management is studied, particularly focusing on automated shelf replenishment decisions. We define different types of event queries to describe retailer store workflow action over the RFID data streams on multiple tagging levels(e.g., item level and container level). Non-deterministic finite automata(NFA)based evaluation models are used to detect event patterns. To manage pattern match results in the process of event detection, optimization algorithm is applied in the event model to share event detection results. A simulated RFID-enabled retail store is used to verify the effectiveness of the method, experiment results show that the algorithm is effective and could optimize retail store management workflow.展开更多
储粮害虫是影响粮食安全的重要因素,深入研究储粮害虫事件的发展过程及其因果关系极为关键。通过量化分析储粮害虫事件之间的因果强度,能够更加准确地评估潜在风险,帮助相关工作人员制定防控措施,减少不必要的损失。为解决储粮害虫领域...储粮害虫是影响粮食安全的重要因素,深入研究储粮害虫事件的发展过程及其因果关系极为关键。通过量化分析储粮害虫事件之间的因果强度,能够更加准确地评估潜在风险,帮助相关工作人员制定防控措施,减少不必要的损失。为解决储粮害虫领域数据中存在的数据偏差而造成模型过分依赖数据集中的表面特征,在应对泛化数据时效果不佳的问题,该研究提出一种反事实数据增强的因果强度计算方法,旨在准确量化事件之间的因果强度。设计了一个反事实数据增强的因果强度计算框架(counterfactual data augmentation-event causal strength,CDA-ECS),通过利用大语言模型(large language model,LLM)生成反事实实例,对原始数据进行扩展,将去偏的因果知识整合进预训练语言模型中,帮助其更深入地理解和学习句子的因果关系,提高模型的泛化能力。在公共数据集和领域数据集上的试验表明,所提方法能够训练出更加稳健的模型,在领域泛化数据的推理任务上准确率提高了2.4个百分点,能有效应用于储粮害虫事件的因果强度计算。在储粮害虫领域,反事实数据增强方法的引入为解决数据偏差提供了一种新的视角,增强后数据的多样性和复杂性使得模型能够更加深入地理解害虫行为与环境因素之间的复杂联系,进一步帮助实现储粮害虫事件的风险分析。该研究证明了反事实数据增强方法的可行性和有效性,为实现储粮害虫事件的因果强度计算提供了一定的参考。展开更多
Over the last few years, the Internet of Things (IoT) has become an omnipresent term. The IoT expands the existing common concepts, anytime and anyplace to the connectivity for anything. The proliferation in IoT offer...Over the last few years, the Internet of Things (IoT) has become an omnipresent term. The IoT expands the existing common concepts, anytime and anyplace to the connectivity for anything. The proliferation in IoT offers opportunities but may also bear risks. A hitherto neglected aspect is the possible increase in power consumption as smart devices in IoT applications are expected to be reachable by other devices at all times. This implies that the device is consuming electrical energy even when it is not in use for its primary function. Many researchers’ communities have started addressing storage ability like cache memory of smart devices using the concept called—Named Data Networking (NDN) to achieve better energy efficient communication model. In NDN, memory or buffer overflow is the common challenge especially when internal memory of node exceeds its limit and data with highest degree of freshness may not be accommodated and entire scenarios behaves like a traditional network. In such case, Data Caching is not performed by intermediate nodes to guarantee highest degree of freshness. On the periodical updates sent from data producers, it is exceedingly demanded that data consumers must get up to date information at cost of lease energy. Consequently, there is challenge in maintaining tradeoff between freshness energy consumption during Publisher-Subscriber interaction. In our work, we proposed the architecture to overcome cache strategy issue by Smart Caching Algorithm for improvement in memory management and data freshness. The smart caching strategy updates the data at precise interval by keeping garbage data into consideration. It is also observed from experiment that data redundancy can be easily obtained by ignoring/dropping data packets for the information which is not of interest by other participating nodes in network, ultimately leading to optimizing tradeoff between freshness and energy required.展开更多
随着工业物联网(industrial Internet of things,IIoT)的不断发展,越来越多的设备和传感器开始连接到网络中,产生了大量的时间序列数据(简称“时序数据”),时序数据爆炸式的增长给数据库管理系统带来了新的挑战:持续高吞吐量数据摄取、...随着工业物联网(industrial Internet of things,IIoT)的不断发展,越来越多的设备和传感器开始连接到网络中,产生了大量的时间序列数据(简称“时序数据”),时序数据爆炸式的增长给数据库管理系统带来了新的挑战:持续高吞吐量数据摄取、低延迟多维度数据查询、高性能时间序列索引以及低成本数据存储.近年来时序数据库技术已经成为一个研究热点,一些学者对时序数据库技术进行了深入的研究,同时出现了一些专门用于管理时序数据的时序数据库,并且已经被应用在多个领域,成为工业物联网中不可缺少的关键组成.现有的时序数据库相关综述侧重于时序数据库的功能和性能比较,以及在特定领域中对时序数据库的选择建议,缺少对时序数据库持久化存储、查询、计算和索引等关键技术的研究,同时这些综述工作出现的时间较早,缺少对现代时序数据库关键技术的研究.对学术界时序数据存储研究和工业界时序数据库进行了全面的调查和研究,凝练了时序数据库的4类关键技术:1)时间序列索引优化技术;2)内存数据组织技术;3)高吞吐量数据摄取和低延迟数据查询技术;4)海量历史数据低成本存储技术.同时分析总结了时序数据库评测基准.最后,展望了时序数据库关键技术在未来的发展方向.展开更多
Digital broadcasting is a novel paradigm for the next generation broadcasting. Its goal is to provide not only better quality of pictures but also a variety of services that is impossible in traditional airwaves broad...Digital broadcasting is a novel paradigm for the next generation broadcasting. Its goal is to provide not only better quality of pictures but also a variety of services that is impossible in traditional airwaves broadcasting. One of the important factors for this new broadcasting environment is the interoperability among broadcasting applications since the environment is distributed. Therefore the broadcasting metadata becomes increasingly important and one of the metadata standards for a digital broadcasting is TV-Anytime metadata. TV-Anytime metadata is defined using XML schema, so its instances are XML data. In order to fulfill interoperability, a standard query language is also required and XQuery is a natural choice. There are some researches for dealing with broadcasting metadata. In our previous study, we have proposed the method for efficiently managing the broadcasting metadata in a service provider. However, the environment of a Set-Top Box for digital broadcasting is limited such as low-cost and low-setting. Therefore there are some considerations to apply general approaches for managing the metadata into the Set-Top Box. This paper proposes a method for efficiently managing the broadcasting metadata based on the Set-Top Box and a prototype of metadata management system for evaluating our method. Our system consists of a storage engine to store the metadata and an XQuery engine to search the stored metadata and uses special index for storing and searching. Our two engines are designed independently with hardware platform therefore these engines can be used in any low-cost applications to manage broadcasting metadata.展开更多
The paper is devoted to study of the electrical parameters of the motion parts of the MEMS such as solenoids. The analytical background is given in order to describe the influence of the electrical field components on...The paper is devoted to study of the electrical parameters of the motion parts of the MEMS such as solenoids. The analytical background is given in order to describe the influence of the electrical field components on the forces, which are result of interaction of the electromagnetic (EM) field components with the parts of motion devices of MEMS. The given analytical formulas open the ability to calculate the self-inductance of the microsolenoids of the different kind, as well as the stored energy of such motion devices, that could be used for the modeling and optimization of parameters of running devices of MEMS such as actuators, sensors etc.展开更多
物联网作为国内外新兴的热门技术,正在深刻地影响着人们的生产生活,它在带来诸多好处的同时也给信息存储领域带来挑战.物联网信息存储中心需要根据其数据特性结合分布式实时数据库信息存储管理的优点,设计与之相适应的数据存储方案,而...物联网作为国内外新兴的热门技术,正在深刻地影响着人们的生产生活,它在带来诸多好处的同时也给信息存储领域带来挑战.物联网信息存储中心需要根据其数据特性结合分布式实时数据库信息存储管理的优点,设计与之相适应的数据存储方案,而数据分配策略作为数据存储方案的关键技术是研究的重点.根据物联网传感器信息的海量性、时空相关性、访问失衡性和连续变化性,需要一种基于时域的数据分配模型与之相适应,以此设计出基于自适应时域负载反馈的动态数据分配策略(adaptive time domain data allocation,ATDA).策略根据数据特征,将静态数据分配问题归约成简单线性规划问题,同时采用自适应时域对负载信息进行反馈,最后设置动态负载门限函数实现数据的动态分配.实验表明,该策略与同类Random、Bubba算法相比,在系统短时域负载均衡(LBST)、系统数据迁移量(DM)方面具有更好的性能.展开更多
文摘PL/SQL is the most common language for ORACLE database application. It allows the developer to create stored program units (Procedures, Functions, and Packages) to improve software reusability and hide the complexity of the execution of a specific operation behind a name. Also, it acts as an interface between SQL database and DEVELOPER. Therefore, it is important to test these modules that consist of procedures and functions. In this paper, a new genetic algorithm (GA), as search technique, is used in order to find the required test data according to branch criteria to test stored PL/SQL program units. The experimental results show that this was not fully achieved, such that the test target in some branches is not reached and the coverage percentage is 98%. A problem rises when target branch is depending on data retrieved from tables;in this case, GA is not able to generate test cases for this branch.
基金supported by two research grants provided by the Karachi Institute of Economics and Technology(KIET)the Big Data Analytics Laboratory at the Insitute of Business Administration(IBAKarachi)。
文摘The advent of healthcare information management systems(HIMSs)continues to produce large volumes of healthcare data for patient care and compliance and regulatory requirements at a global scale.Analysis of this big data allows for boundless potential outcomes for discovering knowledge.Big data analytics(BDA)in healthcare can,for instance,help determine causes of diseases,generate effective diagnoses,enhance Qo S guarantees by increasing efficiency of the healthcare delivery and effectiveness and viability of treatments,generate accurate predictions of readmissions,enhance clinical care,and pinpoint opportunities for cost savings.However,BDA implementations in any domain are generally complicated and resource-intensive with a high failure rate and no roadmap or success strategies to guide the practitioners.In this paper,we present a comprehensive roadmap to derive insights from BDA in the healthcare(patient care)domain,based on the results of a systematic literature review.We initially determine big data characteristics for healthcare and then review BDA applications to healthcare in academic research focusing particularly on No SQL databases.We also identify the limitations and challenges of these applications and justify the potential of No SQL databases to address these challenges and further enhance BDA healthcare research.We then propose and describe a state-of-the-art BDA architecture called Med-BDA for healthcare domain which solves all current BDA challenges and is based on the latest zeta big data paradigm.We also present success strategies to ensure the working of Med-BDA along with outlining the major benefits of BDA applications to healthcare.Finally,we compare our work with other related literature reviews across twelve hallmark features to justify the novelty and importance of our work.The aforementioned contributions of our work are collectively unique and clearly present a roadmap for clinical administrators,practitioners and professionals to successfully implement BDA initiatives in their organizations.
基金supported by National Social Science Fund (No. 16CTQ013)the Application Fundamental Research Foundation of Sichuan Province, China (No. 2017JY0011)the Key Project of Sichuan Provincial Department of Education, China (No. 2017GZ0333)
文摘Radio frequency identification(RFID) enabled retail store management needs workflow optimization to facilitate real-time decision making. In this paper, complex event processing(CEP) based RFID-enabled retail store management is studied, particularly focusing on automated shelf replenishment decisions. We define different types of event queries to describe retailer store workflow action over the RFID data streams on multiple tagging levels(e.g., item level and container level). Non-deterministic finite automata(NFA)based evaluation models are used to detect event patterns. To manage pattern match results in the process of event detection, optimization algorithm is applied in the event model to share event detection results. A simulated RFID-enabled retail store is used to verify the effectiveness of the method, experiment results show that the algorithm is effective and could optimize retail store management workflow.
文摘储粮害虫是影响粮食安全的重要因素,深入研究储粮害虫事件的发展过程及其因果关系极为关键。通过量化分析储粮害虫事件之间的因果强度,能够更加准确地评估潜在风险,帮助相关工作人员制定防控措施,减少不必要的损失。为解决储粮害虫领域数据中存在的数据偏差而造成模型过分依赖数据集中的表面特征,在应对泛化数据时效果不佳的问题,该研究提出一种反事实数据增强的因果强度计算方法,旨在准确量化事件之间的因果强度。设计了一个反事实数据增强的因果强度计算框架(counterfactual data augmentation-event causal strength,CDA-ECS),通过利用大语言模型(large language model,LLM)生成反事实实例,对原始数据进行扩展,将去偏的因果知识整合进预训练语言模型中,帮助其更深入地理解和学习句子的因果关系,提高模型的泛化能力。在公共数据集和领域数据集上的试验表明,所提方法能够训练出更加稳健的模型,在领域泛化数据的推理任务上准确率提高了2.4个百分点,能有效应用于储粮害虫事件的因果强度计算。在储粮害虫领域,反事实数据增强方法的引入为解决数据偏差提供了一种新的视角,增强后数据的多样性和复杂性使得模型能够更加深入地理解害虫行为与环境因素之间的复杂联系,进一步帮助实现储粮害虫事件的风险分析。该研究证明了反事实数据增强方法的可行性和有效性,为实现储粮害虫事件的因果强度计算提供了一定的参考。
文摘Over the last few years, the Internet of Things (IoT) has become an omnipresent term. The IoT expands the existing common concepts, anytime and anyplace to the connectivity for anything. The proliferation in IoT offers opportunities but may also bear risks. A hitherto neglected aspect is the possible increase in power consumption as smart devices in IoT applications are expected to be reachable by other devices at all times. This implies that the device is consuming electrical energy even when it is not in use for its primary function. Many researchers’ communities have started addressing storage ability like cache memory of smart devices using the concept called—Named Data Networking (NDN) to achieve better energy efficient communication model. In NDN, memory or buffer overflow is the common challenge especially when internal memory of node exceeds its limit and data with highest degree of freshness may not be accommodated and entire scenarios behaves like a traditional network. In such case, Data Caching is not performed by intermediate nodes to guarantee highest degree of freshness. On the periodical updates sent from data producers, it is exceedingly demanded that data consumers must get up to date information at cost of lease energy. Consequently, there is challenge in maintaining tradeoff between freshness energy consumption during Publisher-Subscriber interaction. In our work, we proposed the architecture to overcome cache strategy issue by Smart Caching Algorithm for improvement in memory management and data freshness. The smart caching strategy updates the data at precise interval by keeping garbage data into consideration. It is also observed from experiment that data redundancy can be easily obtained by ignoring/dropping data packets for the information which is not of interest by other participating nodes in network, ultimately leading to optimizing tradeoff between freshness and energy required.
文摘随着工业物联网(industrial Internet of things,IIoT)的不断发展,越来越多的设备和传感器开始连接到网络中,产生了大量的时间序列数据(简称“时序数据”),时序数据爆炸式的增长给数据库管理系统带来了新的挑战:持续高吞吐量数据摄取、低延迟多维度数据查询、高性能时间序列索引以及低成本数据存储.近年来时序数据库技术已经成为一个研究热点,一些学者对时序数据库技术进行了深入的研究,同时出现了一些专门用于管理时序数据的时序数据库,并且已经被应用在多个领域,成为工业物联网中不可缺少的关键组成.现有的时序数据库相关综述侧重于时序数据库的功能和性能比较,以及在特定领域中对时序数据库的选择建议,缺少对时序数据库持久化存储、查询、计算和索引等关键技术的研究,同时这些综述工作出现的时间较早,缺少对现代时序数据库关键技术的研究.对学术界时序数据存储研究和工业界时序数据库进行了全面的调查和研究,凝练了时序数据库的4类关键技术:1)时间序列索引优化技术;2)内存数据组织技术;3)高吞吐量数据摄取和低延迟数据查询技术;4)海量历史数据低成本存储技术.同时分析总结了时序数据库评测基准.最后,展望了时序数据库关键技术在未来的发展方向.
文摘Digital broadcasting is a novel paradigm for the next generation broadcasting. Its goal is to provide not only better quality of pictures but also a variety of services that is impossible in traditional airwaves broadcasting. One of the important factors for this new broadcasting environment is the interoperability among broadcasting applications since the environment is distributed. Therefore the broadcasting metadata becomes increasingly important and one of the metadata standards for a digital broadcasting is TV-Anytime metadata. TV-Anytime metadata is defined using XML schema, so its instances are XML data. In order to fulfill interoperability, a standard query language is also required and XQuery is a natural choice. There are some researches for dealing with broadcasting metadata. In our previous study, we have proposed the method for efficiently managing the broadcasting metadata in a service provider. However, the environment of a Set-Top Box for digital broadcasting is limited such as low-cost and low-setting. Therefore there are some considerations to apply general approaches for managing the metadata into the Set-Top Box. This paper proposes a method for efficiently managing the broadcasting metadata based on the Set-Top Box and a prototype of metadata management system for evaluating our method. Our system consists of a storage engine to store the metadata and an XQuery engine to search the stored metadata and uses special index for storing and searching. Our two engines are designed independently with hardware platform therefore these engines can be used in any low-cost applications to manage broadcasting metadata.
文摘The paper is devoted to study of the electrical parameters of the motion parts of the MEMS such as solenoids. The analytical background is given in order to describe the influence of the electrical field components on the forces, which are result of interaction of the electromagnetic (EM) field components with the parts of motion devices of MEMS. The given analytical formulas open the ability to calculate the self-inductance of the microsolenoids of the different kind, as well as the stored energy of such motion devices, that could be used for the modeling and optimization of parameters of running devices of MEMS such as actuators, sensors etc.
文摘物联网作为国内外新兴的热门技术,正在深刻地影响着人们的生产生活,它在带来诸多好处的同时也给信息存储领域带来挑战.物联网信息存储中心需要根据其数据特性结合分布式实时数据库信息存储管理的优点,设计与之相适应的数据存储方案,而数据分配策略作为数据存储方案的关键技术是研究的重点.根据物联网传感器信息的海量性、时空相关性、访问失衡性和连续变化性,需要一种基于时域的数据分配模型与之相适应,以此设计出基于自适应时域负载反馈的动态数据分配策略(adaptive time domain data allocation,ATDA).策略根据数据特征,将静态数据分配问题归约成简单线性规划问题,同时采用自适应时域对负载信息进行反馈,最后设置动态负载门限函数实现数据的动态分配.实验表明,该策略与同类Random、Bubba算法相比,在系统短时域负载均衡(LBST)、系统数据迁移量(DM)方面具有更好的性能.
