基于NB分类器重访概率预测的Web缓存替换策略

Web缓存是用来解决网络访问延迟和网络拥塞问题，缓存替换策略直接影响缓存的命中率。为此，提出一种朴素贝叶斯（NB）分类器重访概率预测的Web缓存替换策略；根据用户之前访问日志，通过分区操作提取多项特征来表示每次访问的对象，并构建特征数据集；训练NB分类器，用来确定缓存中对象被再次访问的概率，为对象分配权重；结合LRU策略来合理删除一些对象。仿真结果表明，提出的策略在保证较高命中率的同时有效降低了执行时间。     

Determining Stability Constants Using the AKUFVE Technique

ABSTRACT

The AKUFVE techniques were developed by Rydberg and co-workers in the 1960s. The main aim was to be able to perform a series of liquid-liquid extraction data varying one or more parameters and at the same time achieve very pure phases. As such, this technique was later used for short-lived isotope studies in the SISAK system, but also as a standalone unit for a large number of thermodynamic studies of extraction systems both for fundamental understanding as well as more applied investigations. In this paper, the apparatus with modifications made over the decades is described. In addition, studies with stability constant determinations for the zirconium-water-acetylacetone system as well as lanthanide extraction using bromodecanoic acid are exemplified to demonstrate the potential use of the technique. The results shown clearly demonstrate the versatility and ability of the AKUFVE system.     

浊点萃取在锕系和镧系元素分离分析中的应用

浊点萃取（cloud point extraction, CPE）是一种安全环保同时兼具高富集系数和低成本的萃取方法，在分析化学中已经被广泛应用于金属离子分析等领域。锕系和镧系金属元素存在环境复杂，自身浓度相对较低，对其进行分离和分析一直是放射化学研究者所关注的问题。经过条件优化，CPE能够有选择性地分离和富集锕系和镧系金属元素。通过与多种技术联用，CPE能实现锕系和镧系元素的高灵敏度分析。本文在介绍浊点萃取机理的基础上，着重描述了不同萃取体系中各类萃取剂（β-二酮类、膦氧类、含氮类、含硫类）对于锕系和镧系元素的萃取效果，全面总结了其中使用的不同联用技术，同时简述了通过构筑超分子识别位点，修饰配体，使用不同表面活性剂及掩蔽剂等改良现有浊点萃取体系的尝试。最后，对浊点萃取在放射化学领域的应用进行了总结和展望。     

Querying on large and complex databases by content: Challenges on variety and veracity regarding real applications

The amount and variety of digital data currently being generated, stored and analyzed, including images, videos, and time series, have brought challenges to data administrators, analysts and developers, who struggle to comply with the expectations of both data owners and end users. The majority of the applications demand searching complex data by taking advantage of queries that analyze different aspects of the data, and need the answers in a timely manner. Content-based similarity retrieval techniques are well-suited to handle large databases, because they enable performing queries and analyses using features automatically extracted from the data, without users’ intervention. In this paper, we review and discuss the challenges posed to the database and related communities in order to provide techniques and tools that can meet the variety and veracity characteristics of big and complex data, while also considering the aspects of semantical preservation and completeness of the data. Examples and results obtained over a two-decade-long experience with real applications are presented and discussed.     

Reformate-enriched gasoline-ethanol blends: Volatility criteria and azeotrope formation

Four hydrocarbon-base gasolines (BG) were formulated from the local refinery streams; isomerate, reformate, and light naphtha. The formulations were enriched in reformate. Each of these BG formulations was blended with 10 vol% of anhydrous ethanol. From ASTM-D86 distillation data, eight distillation curves were constructed and the trend line equations of these distillation curves were developed. Also, the area under each distillation curve (AUDC) was calculated through calculus definite integration technique. Subsequently, the area due to azeotrope formation (ADAF) for each BG-ethanol blend was estimated. In this paper, the influence of increasing reformate proportions on the created positive azeotrope, was studied. Also the influence of increasing reformate proportions on vapor pressure, Temperature for the vapor-liquid ratio of 20, T50 and octane number was studied. The results show that the R² values of the distillation curve equations prove the reliability of the fits. Also, increasing reformate proportion in the fuel blend improves the octane number while increasing reformate proportion decreases the volatility of the fuel formulation.     

Extraction equilibrium conditions of beryllium and aluminium from a beryl ore for optimal industrial beryllium compound production

This study examines the extraction of beryllium and aluminium from a Nigerian beryl ore using Cyanex®272 in kerosene from an aqueous sulphate pregnant solution. Parameters such as extractant concentration and equilibrium pH that dictates the extraction yield were studied. Under the following conditions: temperature 27?±?2°C, phase ratio 1?1, about 45.50 and 46.76% of beryllium and aluminium were extracted by 0.15?mol?L^?1 Cyanex®272 concentration within 30?min. However, the extraction yield of beryllium and aluminium was increased to 91.68% and 97.89% at equilibrium pH of 3 and 4, respectively, for beryllium and aluminium at 27?±?2°C. A 0.05?mol?L^?1 H₂SO₄ solution was found to be adequate for the stripping of about 99.00% Be and 95.40% Al from the loaded organic phase. The pure solutions containing metal ions were accordingly beneficiated to obtain beryllium and aluminium compounds of industrial values.     

Simple Wet Rendering Method for Extraction of Prime Quality Oil from Skipjack Tuna Eyeballs

Oil from skipjack tuna (ST) eyeballs is extracted by the wet rendering method at 121 °C for different holding times (5–60 min) using an autoclave. Yield increases as heating time increases up to 20 min (p < 0.05); no further increase is obtained with a longer heating time (p > 0.05). Conversely, acid value and total polar compounds increase. However, peroxide value (PV), thiobarbituric acid reactive substances, and anisidine value (AnV) decrease up to 30 min. No changes in unsaponifiable matter (UM) or conjugated diene (CD) are attained, regardless of heating time. Polar components (PC) increase with heating time (p < 0.05). All oil samples have a high polyunsaturated fatty acids (PUFA) content (40.46–41.00%), with monounsaturated fatty acids (MUFA) and saturated fatty acids (SFA) in the range of 20.94–21.26% and 37.77–38.45%, respectively. PUFA content is reduced slightly with a heating time of 60 min. Docosahexaenoic acid (DHA) (C22:6, n3) is the dominant fatty acid in all samples (31.67–32.24%). Based on FTIR spectra, heating for longer time results in lower intensity at wavenumbers of 3015 and 1740 cm^?1. Thus, light yellow oil from ST eyeballs prepared by a green process for an appropriate time can serve as an excellent source of DHA and other PUFA. Practical Applications: Tuna oil is known to be a rich source of DHA and PUFA with health benefits. However, precooked tuna heads, generally used as raw material, yield oils with a very dark color and offensive odor, which require several refinery processes. To reduce the number of steps in the refinery process, tuna eyeballs which are separated from tuna heads can render higher quality fish oil. Moreover, the wet rendering process, a green process without toxic substances, can be used without causing environmental problems.     

基于机器视觉的玻璃缺陷检测

随着科学技术的进步,高端显示屏产品对平板玻璃的质量要求越来越高,玻璃的表面缺陷检测技术也因此备受关注。传统的人眼检测方法工作量大且准确率低,已经无法满足生产实际要求。研究了一种基于机器视觉的玻璃质量检测系统,采用先进的CCD成像技术和背光式照明获取图像,用MATLAB图像处理工具箱对采集到的图像进行灰度值化、滤波降噪和阈值分割处理,实现对缺陷区域的特征提取和识别。最后用BP神经网络对玻璃表面的三种缺陷进行分类,该神经网络识别的平均误差率为9.84%,表明此检测方法具有一定的应用价值。