Poisson Process and Its Application to the Storm Water Overflows

The homogenous Poisson process is often used to describe the event arrivals. Such Poisson process has been applied in various areas. This study focuses on the arrival pattern of storm water overflows. A set of overflow data was obtained from the storm water pipeline of a municipality. The aim is to verify the overflow arrival pattern and check whether the Poisson process can be applied. The adopted method is the analysis over the inter-arrival times. The exponential distribution test is conducted on the annual data set as well as the entire data set. The results show that all data sets follow the exponential distribution. With the verification of Poisson process, specific examples are also given to show how the Poisson process properties can be used in the management of storm water pipeline management. For other data that are featured with various heterogeneities, the homogenous Poisson process might not be able to be verified and used. Under such circumstances, non-homogenous survival model can be used to simulate the arrival process.

Arrival Analysis of Dry Weather Sanitary Sewer Overflows

This study investigates arrivals of sanitary sewer overflows collected from a municipality. The data set consists of recorded overflows from 2011 to 2014 during dry weather. Reliability analysis is conducted upon each data set. The Weibull distribution is adopted to evaluate the data sets. The results show that the arrival of dry weather SSOs cannot be simply modeled with a Poisson process that is featured with a constant arrival rate. For annual data set, 2-parameter Weibull generally has an acceptable fitting (except 2014 data). The shape parameters are close to 1 or a little greater than 1, indicating relatively constant arrival rate or slightly increased rate. For the entire data set, the 3-parameter Weibull distribution is able to fit the data well. The shape parameter is also greater than 1. Therefore, an increased SSO arrival rate is noticed for this data set. There are needs to make more efforts in maintaining the sewer system.

一种结合代码片段和混合主题模型的软件数据聚类方法

使用主题模型进行文档聚类是众多文本挖掘任务中一种常见的做法。许多研究针对软件问答网站的数据,利用主题模型进行聚类来分析不同领域在社区的发展情况。然而,这些软件相关数据往往包含代码片段且文本长度分布不均,使用传统单一的主题模型对文本数据建模,易得到不稳定的聚类结果。文中提出了一种结合代码片段和混合主题模型的聚类方法,并使用Stack Overflow作为数据源,构造了在该平台上被提问数量排名前60的Python第三方库数据集,经过建模,该数据集最终划分为以下6个不同的领域:网络安全、数据分析、人工智能、文本处理、软件开发和系统终端。实验结果表明,在自动评估和人工评估的指标上,使用代码片段结合文本进行主题建模,在聚类结果划分的质量上表现良好,而联合多个模型进行实验,一定程度上提高了聚类结果的稳定性和准确性。

Optimized parameters of downhole all-metal PDM based on genetic algorithm

Currently,deep drilling operates under extreme conditions of high temperature and high pressure,demanding more from subterranean power motors.The all-metal positive displacement motor,known for its robust performance,is a critical choice for such drilling.The dimensions of the PDM are crucial for its performance output.To enhance this,optimization of the motor's profile using a genetic algorithm has been undertaken.The design process begins with the computation of the initial stator and rotor curves based on the equations for a screw cycloid.These curves are then refined using the least squares method for a precise fit.Following this,the PDM's mathematical model is optimized,and motor friction is assessed.The genetic algorithm process involves encoding variations and managing crossovers to optimize objective functions,including the isometric radius coefficient,eccentricity distance parameter,overflow area,and maximum slip speed.This optimization yields the ideal profile parameters that enhance the motor's output.Comparative analyses of the initial and optimized output characteristics were conducted,focusing on the effects of the isometric radius coefficient and overflow area on the motor's performance.Results indicate that the optimized motor's overflow area increased by 6.9%,while its rotational speed reduced by 6.58%.The torque,as tested by Infocus,saw substantial improvements of38.8%.This optimization provides a theoretical foundation for improving the output characteristics of allmetal PDMs and supports the ongoing development and research of PDM technology.

Flood Overflows Jinshan Temple (Chinese Painting)

The Chinese painting Flood Ouerflows Jinshan Temple draws its subject from a beautiful and well-known legend,The white Snake.In the tale Jinshan was an islet in the Yangtze River of yesteryear.Inorder to aave her husband kept in a temple at the top of the isle.Bai Niangzi.incarnation of the whitesnake.bravely fought Monk Fahat.She borrowed the Yangtze River’s water to overcome Jinshan Templeand force Fahai to release her husband.

基于问答语义匹配的知识社区新问题专家推荐方法

传统的知识社区专家推荐方法采用文本相似度匹配机理,并基于问题或专家描述来构建专家特征.这些方法没有利用问题与答案的语义匹配关系,因此难以充分挖掘专家回答问题的能力特征,影响推荐性能.提出一种基于综合历史和当前问答语义匹配的知识社区新问题的专家推荐方法(History-Now Semantics Expert RECommendation model,HNS-EREC).首先,采用反馈评价和负采样技术来处理数据集中的两类不平衡现象;其次,基于问答语义来提取专家回答问题能力特征;最后,提出一种基于问答语义匹配的History-Now联合专家推荐模型,该模型能够实现面向专家的历史问答和当前问答的语义联合学习.实验结果表明,相对于其他方法,本文所提出的HNS-EREC方法在新问题专家推荐方面具有显著的优势.

Water hammer protection for diversion systems in front of pumps in long-distance water supply projects

For a water supply system with long-distance diversion pipelines, in addition to the water hammer problems that occur beyond pumps, the safety of the water diversion pipeline in front of pumps also deserves attention. In this study, a water hammer protection scheme combined with an overflow surge tank and a regulating valve was developed. A mathematical model of the overflow surge tank was developed, and an analytical formula for the height of the overflow surge tank was derived. Furthermore, a practical water supply project was used to evaluate the feasibility of the combined protection scheme and analyze the sensitivity of valve regulation rules. The results showed that the combined protection scheme effectively reduced the height of the surge tank, lessened the difficulties related to construction, and reduced the necessary financial investment for the project. The two-stage closing rule articulated as fast first and then slow could minimize the overflow volume of the surge tank when the power failure occurred, while the two-stage opening rule articulated as slow first and then fast could be more conducive to the safety of the water supply system when the pump started up.

An Integrated Load Balancing Scheme Based on SDN ASR Algorithm

At present,the flow table of the SDN switch is stored in the costly Ternary Content Addressable Memory(TCAM)cache.Due to the cost problem,the number of flow tables that the SDN switch can store is extremely limited,which is far less than the number of traffic,so it is prone to overflow problem,and leads to network paralysis.That has become a bottleneck in restricting the processing capacity of the data center,and will become a weak point focused by attackers.In this paper,we propose an algorithm for the Alarm Switch Remove(ASR)that fully loads the flow table space in SDN,and further put forward an integrated load balancing scheme in SDN.Finally,we use Mininet to verify that the scheme can ease the SDN switch flow table overflow problem and increase network throughput.

面向专家示例的Stack Overflow本体构造和推理研究

Stack Overflow是一个计算机领域的IT技术问答网站,为了获取问答网站中的专家示例并将其应用于API挖掘中。首先采用Scrapy爬虫框架技术获取Stack Overflow问答网站中的结构化数据,并存储在关系模式中;再使用本体建模工具Protégé构建本体,然后使用D2RQ工具实现对关系数据库的知识抽取,将关系模式转换为三元组形式的本体模型;同时,提出了一个面向专家示例的子本体抽取算法,用于从原本体中抽取出专家示例推理相关的子本体,并提出了若干条专家示例推理规则,能推导出专家所编写的代码示例。实验结果证明,从Stack Overflow本体模型中抽取的专家示例能提高API调用序列挖掘的准确率。

Detection of Buffer Overflow Attacks with Memoization-based Rule Set

Different abnormalities are commonly encountered in computer network systems.These types of abnormalities can lead to critical data losses or unauthorized access in the systems.Buffer overflow anomaly is a prominent issue among these abnormalities,posing a serious threat to network security.The primary objective of this study is to identify the potential risks of buffer overflow that can be caused by functions frequently used in the PHP programming language and to provide solutions to minimize these risks.Static code analyzers are used to detect security vulnerabilities,among which SonarQube stands out with its extensive library,flexible customization options,and reliability in the industry.In this context,a customized rule set aimed at automatically detecting buffer overflows has been developed on the SonarQube platform.The memoization optimization technique used while creating the customized rule set enhances the speed and efficiency of the code analysis process.As a result,the code analysis process is not repeatedly run for code snippets that have been analyzed before,significantly reducing processing time and resource utilization.In this study,a memoization-based rule set was utilized to detect critical security vulnerabilities that could lead to buffer overflow in source codes written in the PHP programming language.Thus,the analysis process is not repeatedly run for code snippets that have been analyzed before,leading to a significant reduction in processing time and resource utilization.In a case study conducted to assess the effectiveness of this method,a significant decrease in the source code analysis time was observed.

Overflowing phenomenon during ultrasonic treatment in Al-Si alloys

At the late stage of solidification with ultrasonic treatment （UST） in Al-Si alloys, a part of semisolid overflows and climbs along the probe. The interesting phenomenon and its influence on the solidification microstructure were investigated in order to better study the mechanism of UST. It is considered that the overflowing phenomenon occurs due to the changes of vibration and flow in the remaining semisolid. Because the overflowed portion comes from the region with intense UST effect and vibrates with the probe during solidification, great modification of primary and euteetic Si （about 10 pm in length） and refinement of primary a（Al） （about 70 μm in size） are observed in this portion.

Stack Overflow上机器学习相关问题的大规模实证研究

为了调查机器学习相关主题分布和发展趋势,从在线问答网站Stack Overflow上,利用过滤标签,从4 178多万帖子中提取出60 028个与机器学习相关的问题帖.通过分析问题帖,统计各个机器学习平台的讨论量,发现Scikit-learn、TensorFlow、Keras是前3位频繁被讨论的机器学习平台,占总讨论量的58%.为了进一步分析机器学习相关讨论主题,进行潜在狄利克雷分布(LDA)主题模型训练,提出自适应LDA中的主题数渐进搜索方法,采用主题一致性系数评估输出结果,获得主题最佳数量,从而发现9个讨论主题,分属3个类别:代码相关、模型相关、理论相关.基于主题中问题帖的浏览数、评论数,分析不同主题的流行度和回答困难程度.

台山核电厂淡水水源工程水库溢流坝消能试验研究

以台山核电厂淡水水源工程为例,通过水力模型试验研究,推荐溢流坝采用宽尾墩+坝面削角阶梯+底流消力池的联合消能方案。试验结果表明,该方案消能效果较显著、工程量小,优化了溢流坝工程布置和体型。

基于数据挖掘的专业可信回答者个性化推荐——以Stack Overflow问答社区为例

针对问答社区中问题不能得到及时、有效解答的现状,文章以Stack Overflow问答社区为例,首先介绍了问答社区数据的采集与预处理情况;然后,通过挖掘学习者信息,得到专业可信回答者、高信誉回答者和徽章回答者三种潜在回答者;最后,实施了三种回答者推荐并对比了推荐性能。实验结果表明,与高信誉回答者推荐和徽章回答者推荐相比,考虑回答质量和专业相关性的专业可信回答者推荐具有更高的准确率和召回率,其推荐性能更优。实施基于数据挖掘的专业可信回答者个性化推荐,能有效缓解问答社区的信息过载问题,有助于建设更高效的网络学习社区环境。

Method of integer overflow detection to avoid buffer overflow

A simplified integer overflow detection method based on path relaxation is described for avoiding buffer overflow triggered by integer overflow. When the integer overflow refers to the size of the buffer allocated dynamically, this kind of integer overflow is most likely to trigger buffer overflow. Based on this discovery, through lightly static program analysis, the solution traces the key variables referring to the size of a buffer allocated dynamically and it maintains the upper bound and lower bound of these variables. After the constraint information of these traced variables is inserted into the original program, this method tests the program with test cases through path relaxation, which means that it not only reports the errors revealed by the current runtime value of traced variables contained in the test case, but it also examines the errors possibly occurring under the same execution path with all the possible values of the traced variables. The effectiveness of this method is demonstrated in a case study. Compared with the traditional buffer overflow detection methods, this method reduces the burden of detection and improves efficiency.

Lossless Mapping from Semi-Structured Data to Structured Data

Most semi-structured data are of certain structure regularity. Having beenstored as structured data in relational database (RDB), they can be effectively managed by databasemanagement system (DBMS). Some semi-structured data are difficult to transform due to theirirregular structures. We design an efficient algorithm and data structure for ensuring losslesstransformation. We bring forward an approach of schema extraction through data mining, in whichdifferent kinds of elements are transformed respectively and lossless mapping from semi-structureddata to structured data can be achieved.

基于Stack Overflow的数据库相关主题分析

数据库管理系统虽是一种较为成熟的软件系统,但开发人员在应用数据库系统进行数据管理以及数据分析时还是会遇到各种问题,因此会在Stack Overflow之类的问答论坛上寻求解决方法。文中获取了Stack Overflow上94473条与数据库相关的问题,应用LDA主题模型将这些问题归为25个主题,结果显示开发者的问题可归为"表""SQL""SELECT"等主题。通过研究与数据库相关的不同主题的流行度和困难程度发现,"SQL"主题相关的问题较为流行。除此以外,文中还分别研究了3种不同的数据库,即MySQL,Oracle和MongoDB,分析了与不同数据库系统相关的问题的主题分布。文中的研究成果有助于了解数据库开发者所面临的挑战,从而为数据库系统版本更新、数据库课程教学内容的设置,甚至是数据库领域的研究问题提供参考。

Stack Overflow的缺陷代码特征分析与相似缺陷检测

目前在软件代码缺陷审查以及缺陷预测中,研究人员对源代码进行分析研究却忽略了代码的缺陷信息.本文通过对缺陷信息进行分析,发现缺陷信息对于相似缺陷的检测有着重要的参考价值.基于这一思想,本文分析软件缺陷社区Stack Overflow中关于缺陷代码的信息,提出一种基于缺陷代码特征分析的相似缺陷检测方法.该方法首先对缺陷报告进行LDA主题分析并将缺陷报告分类到不同的主题(类别)中,统计得到高频缺陷类别;其次对于高频缺陷类别的缺陷代码提取特征;最后根据缺陷代码特征构建相似缺陷检测模型.为了验证相似缺陷检测模型的有效性,针对数据操作缺陷数据构建诊断模型并对该模型进行实证,实验结果表明该方法对检测其他代码中相似缺陷有较好的效果.

基于CBOW-LDA主题模型的Stack Overflow编程网站热点主题发现研究

Stack Overflow是一个热门的国外编程问答网站,通过对该网站编程提问帖的问题文本进行文本语义挖掘,能获析用户关注的编程热点。由于研究对象所代表的短文本信息具有高维性及分布不均的特点,易导致主题获取不明晰。文中提出一种基于LDA(Latent Dirichlet Allocation)主题模型的CBOW-LDA建模方法,该方法对目标语料进行相似词聚类后再完成主题建模,能有效降低文本输入维度,使主题分布更明确。采集Stack Overflow网站上2010-2015年的问题帖数据集POST,并对其进行实验,同等主题数下采用文本建模中衡量模型性能的评价指标困惑度(Perplexity)来度量算法在不同数据集容量维度下的性能。结果表明,与现有的基于词频权重的词量化主题建模TFLDA方法相比,CBOW-LDA方法的困惑度更低,在实验语料下的困惑度降低约4.87%,证明了所提算法的性能更好。采用CBOW-LDA方法对Stack Overflow进行热点挖掘,同时使用TF-LDA方法进行对比实验,建立手工标注的标准评测集对两种方法获取的热门主题和热搜词汇进行查全率、查准率及F1值的判定,结果证实CBOW-LDA表现更佳,其热点挖掘效果较好。由实验结果可知,Java为该编程网站提问帖中最热门的主题,而C和Javascript则为该网站用户提问中被提及得最频繁的词汇。

CodeSearcher:基于自然语言功能描述的代码查询

在项目开发过程中,开发者需要为实现某一功能而编写代码;在不确定如何使用特定编程语言来实现当前待开发功能时,其往往会在文档或网络资源中进行代码查询。因此,代码查询的有效性会直接影响软件开发的效率。目前,已有相当数量的工具可以用来辅助开发者进行代码查询,但这些工具普遍存在输入形式复杂或者匹配精确度低等问题。文中提出的CodeSearcher是一种基于自然语言功能描述的代码查询方法。CodeSearcher将软件开发垂直领域的问答网站Stack OverFlow的问答记录转换为〈自然语言描述,代码片段〉数据对,使用神经网络模型将“自然语言描述”和“代码片段”映射到相同的向量空间并进行匹配,从而能够支持开发者使用待开发功能的自然语言描述来查询相应代码。CodeSearcher不同于一般的代码查询系统,一方面,它只需要代码本身而不依赖于代码的注释或说明,因此可以支持更多代码查询的场景;另一方面,它拓展了代码查询的流程,使其不再局限于一次性的查询反馈流程,而是在这中间加入了代码询答的流程,利用返回代码片段之间的差异性元素帮助开发者挑选目标代码,使得开发者不需要详细阅读所有返回的代码片段。实验结果表明,CodeSearcher相较于基准有着更好的效果。