A New Database Intrusion Detection Approach Based on Hybrid Meta-Heuristics

A new secured database management system architecture using intrusion detection systems (IDS) is proposed in this paper for organizations with no previous role mapping for users. A simple representation of Structured Query Language queries is proposed to easily permit the use of the worked clustering algorithm. A new clustering algorithm that uses a tube search with adaptive memory is applied to database log files to create users’ profiles. Then, queries issued for each user are checked against the related user profile using a classifier to determine whether or not each query is malicious. The IDS will stop query execution or report the threat to the responsible person if the query is malicious. A simple classifier based on the Euclidean distance is used and the issued query is transformed to the proposed simple representation using a classifier, where the Euclidean distance between the centers and the profile’s issued query is calculated. A synthetic data set is used for our experimental evaluations. Normal user access behavior in relation to the database is modelled using the data set. The false negative (FN) and false positive (FP) rates are used to compare our proposed algorithm with other methods. The experimental results indicate that our proposed method results in very small FN and FP rates.     

Mechanical performance of natural fiber-reinforced composites for the strengthening of masonry

The growing concerns regarding the environmental impact generated by the use of inorganic materials in different fields of application increased the interest towards products based on materials with low environmental impact. In recent years, researchers have turned their attention towards the development of materials obtained from renewable sources, easily recoverable or biodegradable at the end of use. In the field of civil structures, a few attempts have been done to replace the most common composites (e.g. carbon and glass fibers) by materials less harmful to the environment, as natural fibers.This work presents a comprehensive experimental research on the mechanical performance of natural fibers for the strengthening of masonry constructions. Flax, hemp, jute, sisal and coir fibers have been investigated both from physical and mechanical points of view. The fibers with better performance were tested together with three different matrices (two of organic nature) in order to produce composites. These experimental results represent a useful database for understanding the potentialities of natural fibers as strengthening systems.     

Applications of the Crystallographic Search and Analysis System CRYSTDAT in Materials Science

Numerical database systems have recently become available online. Their enhanced search capabilities and fast retrieval of data make them a valuable tool in research. In particular, CRYSTDAT which is a search and analysis system for NBS CRYSTAL DATA has proven to be powerful in the identification of crystalline materials. In conjunction with a single-crystal x-ray diffractometer, a qualitative as well as quantitative phase determination is easily performed. The use of CRYSTDAT will be illustrated in several examples.     

International Nuclear Safety Center Database on Thermophysical Properties of Reactor Materials

The International Nuclear Safety Center (INSC) database has been established at Argonne National Laboratory to provide easily accessible data and information necessary to perform nuclear safety analyses and to promote international collaboration through the exchange of nuclear safety information. The INSC database, located on the World Wide Web at http://www.insc.anl.gov, contains critically assessed recommendations for reactor-material properties for normal operating conditions, transients, and severe accidents. The initial focus of the database is on thermodynamic and transport properties of materials for water reactors. Materials that are being included in the database are fuel, absorbers, cladding, structural materials, coolants, and liquid mixtures of combinations of UO₂, ZrO₂, Zr, stainless steel, absorber materials, and concrete. For each property, the database includes (1) a summary of recommended equations with uncertainties; (2) a detailed data assessment giving the basis for the recommendations, comparisons with experimental data and previous recommendations, and uncertainties; (3) graphs showing recommendations, uncertainties, and comparisons with data and other equations; and (4) property values tabulated as a function of temperature.     

Modeling and measurements of atomic surface roughness

We present a geometrical model of atomic topography with which to obtain a quantitative assessment of surface roughness. A series of two- and three-dimensional atomic surface roughness equations with sufficiently realistic parameters is developed to permit quantitative comparison with scanning-tunneling microscope and atomic-force microscope (AFM) experimental results. The model is sufficiently simple that one can easily use it to interpret experimental data. Tables are provided with estimated values for two- and three-dimensional rms atomic surface roughness in pure metal crystals and ionic crystals based on the atomic surface roughness equations. We use these roughness equations to determine the roughness of cleaved muscovite mica [essentially, KAl(2)(OH)(2)Si(3)AlO(10)]; the calculated values for both two- and three-dimensional roughness are consistent with those obtained in our AFM measurements. In addition, we demonstrate both theoretically and experimentally that atomic surface roughness is never zero.     

Quantity versus impact of software engineering papers: a quantitative study

According to the data from the Scopus publication database, as analyzed in several recent studies, more than 70,000 papers have been published in the area of Software Engineering (SE) since late 1960’s. According to our recent work, 43% of those papers have received no citations at all. Since citations are the most commonly used metric for measuring research (academic) impact, these figures raise questions (doubts) about the (non-existing) impact of such a large set of papers. It is a reality that typical academic reward systems encourage researchers to publish more papers and do not place a major emphasis on research impact. To shed light on the issue of volume (quantity) versus citation-based impact of SE research papers, we conduct and report in this paper a quantitative bibliometrics assessment in four aspects: (1) quantity versus impact of different paper types (e.g., conference versus journal papers), (2) ratios of uncited (non-impactful) papers, (3) quantity versus impact of papers originating from different countries, and (4) quantity versus impact of papers by each of the top-10 authors (in terms of number of papers). To achieve the above objective, we conducted a quantitative exploratory bibliometrics assessment, comprised of four research questions, to assess quantity versus impact of SE papers with respect to the aspects discussed above. We extracted the data through a systematic, automated and repeatable process from the Scopus paper database, which we also used in two previous papers. Our results show that the distribution of SE publications has a major inequality in terms of impact overall, and also when categorized in terms of the above four aspects. The situation in the SE literature is similar to the other areas of science as studied by previous bibliometrics studies. Also, among our results is the fact that journal articles and conference papers have been cited 12.6 and 3.6 times on average, confirming the expectation that journal articles have more impact, in general, than conference papers. Also, papers originated from English-speaking countries have in general more visibility and impact (and consequently citations) when compared to papers originated from non-English-speaking countries. Our results have implications for improvement of academic reward systems, which nowadays mainly encourage researchers to publish more papers and usually neglect research impact. Also, our results can help researchers in non-English-speaking countries to consider improvements to increase their research impact of their upcoming papers.     

A colour image retrieval scheme based on Z-scanning technique

Abstract

This paper proposes a new colour image retrieval scheme using Z-scanning technique for content-based image retrieval (CBIR). In recent years, the CBIR is a popular research topic for image retrieval. This paper proposes a scheme which employs the Z-scanning technique to extract directional intensity features for measuring the similarity between query and database images. In the multiple channel images, each colour channel can be processed individually or combined into a grey channel Y. In order to extract the features by Z-scanning technique from all images, each channel of all images must be divided into several N×N blocks. In each block, F pairs of pixels are scanned by a ‘Z’ direction to obtain the texture features. Each colour channel can be obtained an M×M Z-scanning co-occurrence matrix (ZSCM) for storing the probability of each relationship of all closest blocks. At the similarity measure stage, the ZSCMs of query image and database images are compared to measure their similarity. The experimental results show that the proposed scheme is beneficial for image retrieval when the images include the same texture or object. On the other hand, the proposed scheme also can get better retrieval results and more efficiency than colour correlogram (CC) technique for colour texture images. Another technique uses motif co-occurrence matrix (MCM) as the feature in similarity measurement. The experimental results show the proposed ZSCM can get better retrieval results and higher recall and precision values than the CC and MCM techniques for public image databases.     

Evaluation of "shotgun" proteomics for identification of biological threat agents in complex environmental matrixes: experimental simulations

There is currently a great need for rapid detection and positive identification of biological threat agents, as well as microbial species in general, directly from complex environmental samples. This need is most urgent in the area of homeland security, but also extends into medical, environmental, and agricultural sciences. Mass-spectrometry-based analysis is one of the leading technologies in the field with a diversity of different methodologies for biothreat detection. Over the past few years, "shotgun"proteomics has become one method of choice for the rapid analysis of complex protein mixtures by mass spectrometry. Recently, it was demonstrated that this methodology is capable of distinguishing a target species against a large database of background species from a single-component sample or dual-component mixtures with relatively the same concentration. Here, we examine the potential of shotgun proteomics to analyze a target species in a background of four contaminant species. We tested the capability of a common commercial mass-spectrometry-based shotgun proteomics platform for the detection of the target species (Escherichia coli) at four different concentrations and four different time points of analysis. We also tested the effect of database size on positive identification of the four microbes used in this study by testing a small (13-species) database and a large (261-species) database. The results clearly indicated that this technology could easily identify the target species at 20% in the background mixture at a 60, 120, 180, or 240 min analysis time with the small database. The results also indicated that the target species could easily be identified at 20% or 6% but could not be identified at 0.6% or 0.06% in either a 240 min analysis or a 30 h analysis with the small database. The effects of the large database were severe on the target species where detection above the background at any concentration used in this study was impossible, though the three other microbes used in this study were clearly identified above the background when analyzed with the large database. This study points to the potential application of this technology for biological threat agent detection but highlights many areas of needed research before the technology will be useful in real world samples.     

Standardised double-shear test for determining bond of FRP to concrete and corresponding model development

Bond stress – slip characteristics play a major role in the behaviour of EBR FRP strengthened RC beams. These characteristics are normally determined by using experimental data from small-scale bond tests. However, the research community is yet to agree on a unified experimental set-up and testing procedure for these tests. The lack of standard tests leads to high variability in published results and hinders the development of reliable design models. The testing programme presented herein was part of an international Round Robin Test (iRRT) exercise, aimed at assessing the suitability of double shear tests to characterise the bond behaviour of FRP strengthening systems. A total of 20 tests were performed on different FRP plates. Recommendations on how to improve the iRRT methodology are given. Based on the results, an improved capacity model that accounts for concrete surface preparation is proposed and validated against an extensive database of published results. The outcome of the current research is expected to provide engineers with more confidence in designing safely strengthening applications whilst making the best use of the FRP materials.     

A Simple Prediction Method for the Surface Tension of Ionic Liquids as a Function of Temperature

In this study, a simple prediction method for the surface tension of ionic liquids (ILs) as a function of temperature is developed. Based on a database of experimental surface tension values collected from the literature, first a prediction scheme for the surface tension at a reference temperature of 298.15 K using only information on the density, molar mass, and anion type of the IL is suggested. By combination of this approach with the temperature dependence of the density, an extended prediction scheme describing the temperature dependence of the surface tension of ILs is recommended. The optimized prediction model for the surface tension allows for the prediction of about 3500 temperature-dependent experimental surface tension data of 226 different ILs with a standard deviation of about 7 %. In comparison with fluid-specific prediction methods found in the literature, the developed simple empirical prediction model requires only easily accessible parameters and can be applied for ILs with arbitrary cation and anion combinations. Thus, the proposed prediction method seems to be a valuable engineering tool for the quantitative estimation of the surface tension of ILs.     

Quantitative analysis using steady-state free precession nuclear magnetic resonance

The use of steady-state free precession nuclear magnetic resonance (NMR) for quantitative analysis in low magnetic field is investigated and shown to exhibit substantial advantages compared to more conventional NMR methods. With only minor additional requirements, the technique permits a considerable increase in signal-to-noise ratio for a given acquisition time. The experimental conditions needed for implementation and optimization of the acquisition parameters are explored and shown to be easily accessible with unsophisticated equipment. The applicability of the technique for quantitative analysis of samples with a range of relaxation rates is tested using various examples of practical interest. Highly reproducible results can be obtained much faster and without any special sample-dependent adjustments.     

Strong static magnetic field processing of metallic materials: A review

Metallic materials processing in an imposed strong static magnetic field (SSMF) has attracted widely attention in the last decade since a magnetic field of 10 T or higher becomes easily attainable. Fundamentals including magnetic energy, magnetic anisotropy and magnetic forces influence significantly the research and development of this technology by means of both scientific and engineering paths. The ability to control metallic materials processing depends crucially on the understanding of the fundamentals and subsequently the engineering of the strong magnetic field effects. This review provides a critical examination of different SSMF effects together with the fundamentals that can be used in liquid/solid metal controlling and the subsequent metallic materials preparation. These effects are discussed by integrating them into different technologies or experimental results and accompanied by theoretical considerations of the fundamentals. Comprehensive comparisons are then carried out for each series of SSMF effects. It is aiming to provide an overview of the recent progress in SSMF processing of metallic materials.     

Uncertainty Estimation for Performance Evaluation of a Confocal Microscope as Metrology Equipment

Both in industry and research, the quality control of micrometric manufactured parts is based on the measurement of parameters whose traceability is sometimes difficult to guarantee. In some of these parts, the confocal microscopy shows great aptitudes to characterize a measurand qualitatively and quantitatively. The confocal microscopy allows the acquisition of 2D and 3D images that are easily manipulated. Nowadays, this equipment is manufactured by many different brands, each of them claiming a resolution probably not in accord to their real performance. The Laser Center (Technical University of Madrid) has a confocal microscope to verify the dimensions of the micro mechanizing in their own research projects. The present study pretends to confirm that the magnitudes obtained are true and reliable. To achieve this, a methodology for confocal microscope calibration is proposed, as well as an experimental phase for dimensionally valuing the equipment by 4 different standard positions, with its seven magnifications and the six objective lenses that the equipment currently has, in the x–y and z axis. From the results the uncertainty will be estimated along with an effect analysis of the different magnifications in each of the objective lenses.     

Statistical models for protein validation using tandem mass spectral data and protein amino acid sequence databases

The purpose of this work is to develop and verify statistical models for protein identification using peptide identifications derived from the results of tandem mass spectral database searches. Recently we have presented a probabilistic model for peptide identification that uses hypergeometric distribution to approximate fragment ion matches of database peptide sequences to experimental tandem mass spectra. Here we apply statistical models to the database search results to validate protein identifications. For this we formulate the protein identification problem in terms of two independent models, two-hypothesis binomial and multinomial models, which use the hypergeometric probabilities and cross-correlation scores, respectively. Each database search result is assumed to be a probabilistic event. The Bernoulli event has two outcomes: a protein is either identified or not. The probability of identifying a protein at each Bernoulli event is determined from relative length of the protein in the database (the null hypothesis) or the hypergeometric probability scores of the protein's peptides (the alternative hypothesis). We then calculate the binomial probability that the protein will be observed a certain number of times (number of database matches to its peptides) given the size of the data set (number of spectra) and the probability of protein identification at each Bernoulli event. The ratio of the probabilities from these two hypotheses (maximum likelihood ratio) is used as a test statistic to discriminate between true and false identifications. The significance and confidence levels of protein identifications are calculated from the model distributions. The multinomial model combines the database search results and generates an observed frequency distribution of cross-correlation scores (grouped into bins) between experimental spectra and identified amino acid sequences. The frequency distribution is used to generate p-value probabilities of each score bin. The probabilities are then normalized with respect to score bins to generate normalized probabilities of all score bins. A protein identification probability is the multinomial probability of observing the given set of peptide scores. To reduce the effect of random matches, we employ a marginalized multinomial model for small values of cross-correlation scores. We demonstrate that the combination of the two independent methods provides a useful tool for protein identification from results of database search using tandem mass spectra. A receiver operating characteristic curve demonstrates the sensitivity and accuracy level of the approach. The shortcomings of the models are related to the cases when protein assignment is based on unusual peptide fragmentation patterns that dominate over the model encoded in the peptide identification process. We have implemented the approach in a program called PROT_PROBE.     

电子探针线分析定量化方法对比

电子探针(EPMA)线分析定量化方法包括数据库法、标准样品法、待测样品两点法.利用电子探针对电沉积Fe-Zn合金进行线分析及定量点分析,通过对比线分析定量化与定量点分析的结果,分析了定量化结果产生偏差的原因.结果表明:数据库法定量化操作简单比较容易掌握,且不受人为因素影响,该结果可供参考.标准样品法定量化适用于主量元素...     

博物馆体验研究的国内现状及趋势分析

目的 对国内外博物馆体验研究的文献进行计量可视化分析,以便客观真实地了解现阶段博物馆体验研究的重点和动态。方法 运用Citespace可视化分析工具对CNKI核心数据库中2000—2022年博物馆体验及Web of Science数据库中核心合集期刊进行量化分析和质化论述,内容包括发文时间、关键词聚类、发文刊物分布、国内外研究侧重点论述、研究共性及差异解读。结论 检索范围内国内外博物馆体验研究发文数量呈快速上升趋势,中文发文刊物主要分布在艺术设计领域,国外发文刊物集中在博物馆学研究领域;国内外研究热点都涉及新媒体技术、文化旅游发展、观众研究方面,但国内主要围绕新媒体技术在展示设计中的应用、观众体验的跟踪调查研究和文旅融合下的游客研究,国外研究主要侧重于数字媒体技术对博物馆休闲娱乐氛围的营造、博物馆中的集体学习体验、文化旅游中博物馆的真实性表达。     

Bond between FRP composites and concrete: Assessment of design procedures and analytical models

The use of fibre reinforced polymers (FRPs) to strengthen reinforced concrete (RC) structures has gained a wide popularity in the last decades. Although many experimental and analytical studies are available in literature, some issues are still under discussion in the research communities. Since the typical failure mode of FRP–concrete joints is reported to be debonding of the composite from the concrete substrate [1], the estimation of the bond strength between FRP and concrete substrate represents a key issue for the proper use of this technology. For this reason, several analytical models for the evaluation of the FRP–concrete bond strength and few models for the estimation of the effective bond length were proposed (some of them are included in design codes/recommendations/guidelines); however they were not assessed by means of an appropriate experimental database.This work shows an assessment of twenty analytical models for the evaluation of the FRP–concrete bond strength. The assessment is based on the analysis of a wide experimental database collected from the literature. The results are provided distinguishing between the test setup adopted (single or double shear test, bending test) and the material used (post impregnated sheets or pre impregnated laminates). The accuracy of each model was evaluated by means of a simplified statistical analysis. The influence of the test setup and basic material on the accuracy of the model used was analysed as well. Lastly, the accuracy of twelve available models in providing an estimation of the effective bond length was also assessed.     

基于压电阻抗技术监测混凝土强度发展的实验研究

本文基于压电阻抗（EMI）监测技术,对混凝土立方体标准试块的强度发展进行了监测。制作3种不同配合比的标准试块,将压电片粘贴于标准试块表面和埋置于体内,用精密阻抗分析仪HP4294A提取压电片在不同养护龄期时的电导纳信号,并测试相应标准试块的抗压强度。试验结果表明,随着混凝土养护龄期的增长,表面粘贴和体内埋置两种压电片的电导频谱均发生了变化,但是变化形式不同。对表面压电片,得到了其共振频率的变化量与标准试块抗压强度之间的定量对应关系;对内置压电片,通过引入指标δ建立了电导频谱与标准试块抗压强度的定量关系。本文工作表明采用EMI技术监测早龄期混凝土在硬化过程中强度发展是一种可行且可靠的无损检测方法。