Using Genetic Algorithm as Test Data Generator for Stored PL/SQL Program Units

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.

基于MQTT协议的轻量化文本信息分发技术研究

随着卫星通信网络的发展,基于卫星通信网络实现手机、平板电脑等移动通信设备之间的通信成为研究的热点。由于其采用无线电波进行信号传输,且需要经过多个中继站进行信号的转发和处理,导致存在网络延时大、丢包率高以及信道狭窄等问题。针对文本信息在卫星通信网络下的分发过程存在效率低下、可靠性不高的问题,设计一种基于MQTT(Message Queuing Telemetry Transport)协议的轻量化文本信息分发技术。该技术使用MQTT协议作为消息传输协议,在文本信息分发前对MQTT协议进行主题设计、发布订阅机制设计、设备连接设计以及设备心跳设计,确保设备之间的连通性;在文本信息的分发过程中,设计数据校验加密算法、文本信息轻量化处理方法和离线消息存储机制,保证文本信息分发的安全性、可靠性。实验结果表明:相较于传统的基于JSON数据的文本信息分发技术,该技术在提高文本信息分发效率的同时,可确保信息分发的安全性、完整性和稳定性。

具有高价值密度的农业物联网数据区块链压缩存储方案

针对现有区块链物联网体系主要采用链上存储摘要链下保留原始数据的存储方式中链上无法直接获得真实数据的问题,该研究提出了一种具有高价值密度的农业物联网数据区块链压缩存储方案。首先,边缘服务器将收集的同一批数据聚合到同一批事务中;其次,设计离群值可处理的自适应有损压缩方法,在满足用户保真度要求的前提下降低数据冗余;最后,压缩数据上链,实现区块链上物联网数据的高价值密度存储。与现有方案相比,该方案能提高链上存储真实物联网数据的效率。试验结果表明,在使用自适应压缩方法压缩数据时,针对不同的数据集会自适应选取k值,在满足用户重建精度的前提下,获得良好压缩效果,减少链上存储空间,提高了数据价值密度;相对于风速之类频率较高的数据,温湿度、二氧化碳等变化频率较低的数据可以获得较高的压缩比;当假设正常数据压缩比为10:1时,该方案可节省约85%的链上存储空间,相应的价值密度提高了约85%。该研究可为农产品溯源过程中的物联网数据高效存储提供解决方案,为实现分布式农业物联网数据压缩存储提供技术支持。

时序数据库关键技术综述

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.

Big Data Analytics in Healthcare——A Systematic Literature Review and Roadmap for Practical Implementation

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.

基于高密度计算的多核处理器电力芯片低功耗设计系统

多核处理器电力芯片是目前多种系统的重要组成部分,设计低功耗电力芯片,能够更好地保证系统正常运行。目前设计的电力芯片低功耗系统运行速度较慢,功耗难以达到用户要求,为此该文应用高密度计算设计了一种多核处理器电力芯片低功耗系统。兼容系统多核处理器与层次化AHB总线,探索处理器电力芯片的整体结构,集中处理存储数据信息,不断调整系统算法参数,通过高密度分析引入矩阵进行数据解析,确保运行过程的安全性。在分析处理器调度性能的基础上,利用高密度处理对数据进行层次化处理,避免数据冗余造成的系统运行故障。实验结果表明,引入所设计系统后电力芯片功耗减少了60%,加速比达到3.992,可以有效提高电力芯片运行性能。

存储式交通气象传感器数据采集系统

针对交通气象监测等领域对数据采集系统数据安全性与低成本的要求,设计一种基于存储式的气象数据采集系统,系统利用RS485自动收发电路采集前端气象传感器输出的气象监测区域采集时间、能见度、风速、风向、降水、气压、温度、相对湿度等数据信号;以STM32F103主控芯片进行数据处理,通过FatFS文件系统移植、SPI通信实现数据存储,提升对低信号区域气象灾害的监测和预警能力。试验结果表明,此系统能实时采集、解析、存储气象传感器数据,具有数据存储量大、兼容性强、成本低、稳定性高的优势,便于对交通气象传感器进行长期采集、存储、分析。

连锁门店数据驱动运营发展策略

近年来,随着社会新零售模式的发展,连锁门店经营新模式向智能技术、多渠道销售和外卖服务方向转型,传统的管理方法不易处理经营管理中的新问题,而数据可视化技术可以有效地分析大量数据,并从中提取有效信息。文章就连锁门店运营管理分析,目的在于探索当前新零售背景下,连锁企业门店经营发展策略及新模式选择,结合企业具体经营方式,寻找连锁门店数据化运营发展的方法。

电子商务数据分析在网店运营中的应用研究

随着互联网的快速发展,电子商务已成为一种不可替代的商业模式。在电商领域,数据分析不仅可帮助企业更好地了解市场需求和消费者行为,还可优化产品和服务,提高营销效果。本研究主要探讨电子商务数据分析在网店运营中的应用。通过对商务数据分析的意义、作用的分析,对比常见的商务数据分析工具,明确商务数据分析的方法与步骤,通过案例列举电子商务数据分析在网店运营的作用,并总结其中的难点以及网店运营中电子商务数据分析报告的撰写步骤与技巧。

Modeling the Physical Parameters of Solenoids for MEMS Applications

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.

Storing and Searching Metadata for Digital Broadcasting on Set-Top Box Environments

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.

基于FPGA的MEMS水听器数据采集系统

MEMS水听器工作时需要将探测到的信息有效保存以作后续处理。为解决此问题,以FPGA为控制核心,设计了一套数据采集装置。将多路数据混合编帧后写入SD卡,完成最多8路模拟信号以及3路数字信号的保存。采集工作结束后,通过USB 2.0接口将保存的数据高速传输至上位机。经验证,该系统在水下工作稳定,多通道同步采样率均为10 k Hz,存储容量32 G,可连续采集数据56 h,上位机通信最大速率为40 MByte/s,满足实际应用需求。系统内置电源模块为水听器和采集装置供电,摆脱了线缆的干扰和束缚,便携性得到大幅提升,为后续水听器应用于恶劣环境奠定基础。

Proposed Caching Scheme for Optimizing Trade-off between Freshness and Energy Consumption in Name Data Networking Based IoT

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.

奶茶门店的空间格局与影响因素分析——以喜茶、蜜雪冰城为例

消费需求的转变引发奶茶门店数量在城市的迅速增加,以喜茶和蜜雪冰城的门店兴趣点数据作为研究对象,采用Arcgis中的空间分析方法探讨奶茶门店的空间格局,为当代城市持续重构的奶茶商业景观和消费文化提供一个微观视角。研究表明:(1)喜茶和蜜雪冰城门店空间分布数量、方向和距离特征存在差异;(2)喜茶和蜜雪冰城的高密度区域呈不同拓展形态和地域范围;(3)蜜雪冰城的空间集聚特征更为显著,高高聚类值和高低聚类值都分布于二三线城市,而喜茶的高高聚类值和高低聚类值都位于一线或新一线城市。喜茶和蜜雪冰城都呈现出多种扩散模式混合并存的格局,门店空间分布态势受品牌经营定位、地域文化情节和经济水平的影响。

面向不可变存储环境的近似成员查询二级索引

键值存储系统得益于优异的写入性能被广泛应用于各种Web应用。主流的键值存储系统多利用布隆过滤器优化非主键查询性能,而该方法存在查询效率受数据段数量影响和误判引发的多余数据段访问可能性等不足。为了进一步优化键值系统分析处理的查询能力,针对一次写多次读的数据访问特征,提出了新型二级索引。通过构建全局索引,避免了多过滤器探测引发的查询延迟提高。此外,提出了预探测递归驱逐策略,优化了索引构建效率。与传统方法相比,该索引处理存在数据项查询时能够返回完全正确的数据段编号序列。进一步,该索引基于逻辑链的范围查询方案实现了范围查询。实验结果验证了索引结构的有效性。与基线结构相比,该索引的查询性能提升了约10~50倍。

大数据背景下生鲜电商O2O社区店的商业模式研究

随着我国经济迅猛发展,人们的生活需求和消费水平不断提升,作为基础消费品的生鲜商品有了更广阔的市场和更灵活多样的销售模式。本文基于大数据背景对国内生鲜电商O2O社区店的商业模式进行分析,进而对我国生鲜电商“到家经济”提出合理建议,在推动生鲜电商行业发展的同时,还能为新时期各地民生进步提供基础保障。

基于“互联网+”思路的地质大数据平台建设研究

近年来,随着数字经济的快速发展,地质产业的数字化转型迫在眉睫,地质数据的价值化发挥亟待激发,地质大数据平台的研究对数字经济背景下地质产业的发展意义重大。针对现阶段地质大数据平台建设过程中出现的数据存储分散、集成难度大,数据涉及范围广、标准难统一,数据专业性强、处理难度大等问题,通过借鉴“互联网+”实践中以平台模式聚合多边市场的思路,提出了一种基于“互联网+”思路的地质大数据平台建设方案,以云环境为基础支撑,客户端为工具,云资讯为媒介,云商店为平台,通过聚合多边市场,打造共赢生态圈,创新平台运营机制和盈利模式。基于此思路开展了平台的总体架构设计,阐述了研究过程中涉及到的关键技术,构建了包含微内核客户端、云商店、云资讯、云支撑平台在内的平台系统,构成了共赢生态圈支撑体系。研究成果为数字经济背景下进行地质大数据平台建设,开展“互联网+地质”融合研究提供了有益探索与实践。

基于大数据的电力通信网络状态感知分析

在分布式电源接入和可再生能源的大量应用下,其渗透率逐渐提高,此时电网的规模、设备状态等各项指数会大幅增长。如果仍依靠传统的模型和技术来判断电力通信网络的状态,则难以全面、精准地掌握具体信息。文中提出了一种新型感知电力通信网络状态的方法,其借助大数据技术,可深层次阐述电力通信网络组成和通信业务的特点,并分析了基于大数据的电力通信网络状态感知模型,对于全面展示电力通信网络的态势变化和功能变化有着积极的作用。

基于数据挖掘的张星平治疗肝不藏魂型不寐用药规律研究

目的基于中医传承计算平台分析张星平教授治疗肝不藏魂型不寐的处方用药规律。方法收集2021年6月-2022年6月因“不寐病”于新疆医科大学附属中医医院名中医工作室张星平教授门诊就诊患者的医案处方,建立张星平教授治疗肝不藏魂型不寐门诊医案数据库,使用中医传承计算平台3.0及SPSS Statistics 23.0软件,采用关联规则、聚类分析及因子分析方法,对张教授治疗肝不藏魂型不寐处方药物的使用频次、性味归经、功效进行统计,获得基于关联规则和聚类分析的高频药物组合、高频用药因子及基于聚类分析的中药核心药物组合。结果共纳入门诊医案305例、处方305首,涉及中药136味,其中使用频次前10位中药依次为炙甘草、醋北柴胡、陈皮、白芍、当归、茯苓、麸炒白术、法半夏、煅牡蛎、黄连,频次均超过220次;药性以寒、温、平为主,药味以苦最多,归经以脾经、肝经、心经常见;功效以理气、补虚、清热、安神类为主;基于关联规则得到高频药物组合178组,出现频次居前3位的药物组合依次为醋北柴胡-当归、醋北柴胡-炙甘草、醋北柴胡-茯苓;基于聚类分析获得4个核心药物组合;因子分析显示,305首处方中10个高频药物公因子累计贡献率达66.49%。结论肝不藏魂型不寐主要病位在肝,治疗主要从肝、脾、肺、心四脏入手,治疗上补泻同施、虚实兼顾,以疏肝解郁、安魂为主,健脾安意、安肺定魄、宁心安神为辅。所提取的核心药物与张教授经验方养肝安魂汤高度吻合。

基于SATA的嵌入式高速大容量数据存储系统设计

在高清晰油气管道检测等应用场合,需要快速存储大量数据,使用传统的传输总线和Flash存储器已经难以满足要求,为了解决这个问题,本文介绍了一种应用于嵌入式系统中、基于SATA接口的高速大容量数据存储系统的设计。本设计基于高速SATA接口技术,以高速DSP为微控制器,以大容量电子盘为存储介质。本设计的存储速度可以达到32Mbit/s,存储容量高达120GByte,很好地解决了嵌入式检测系统中大量数据的快速存储问题。