Subsurface Characterization at Ground Failure Sites in Adapazari, Turkey

Ground failure in Adapazari, Turkey during the 1999 Kocaeli earthquake was severe. Hundreds of structures settled, slid, tilted, and collapsed due in part to liquefaction and ground softening. Ground failure was more severe adjacent to and under buildings. The soils that led to severe building damage were generally low plasticity silts. In this paper, the results of a comprehensive investigation of the soils of Adapazari, which included cone penetration test (CPT) profiles followed by borings with standard penetration tests (SPTs) and soil index tests, are presented. The effects of subsurface conditions on the occurrence of ground failure and its resulting effect on building performance are explored through representative case histories. CPT- and SPT-based liquefaction triggering procedures adequately identified soils that liquefied if the clay-size criterion of the Chinese criteria was disregarded. The CPT was able to identify thin seams of loose liquefiable silt, and the SPT (with retrieved samples) allowed for reliable evaluation of the liquefaction susceptibility of fine-grained soils. A well-documented database of in situ and index testing is now available for incorporating in future CPT- and SPT-based liquefaction triggering correlations.     

一种语句级细粒度情感倾向性分析算法研究

针对中文语句的细粒度情感倾向分析问题,构建一个细粒度情感词库。对所含词语进行权重值的计算,并结合中文语句的句式、情感词修饰方法等特点,提出一种基于词库权重、句式权重、修饰权重相结合的语句级细粒度情感倾向性分析算法。实验结果表明,该算法可以准确计算出评论语句的情感倾向值,为进一步研究语句级细粒度情感倾向分类提供了重要的参考依据。     

一种基于GPU加速的细粒度并行蚁群算法

为改善蚁群算法对大规模旅行商问题的求解性能,提出一种基于图形处理器(GPU)加速的细粒度并行蚁群算法.将并行蚁群算法求解过程转化为统一计算设备架构的线程块并行执行过程,使得蚁群算法在GPU中加速执行.实验结果表明,该算法能提高全局搜索能力,增大细粒度并行蚁群算法的蚂蚁规模,从而提高了算法的运算速度.     

Toward Fine-grained Image Retrieval with Adaptive Deep Learning for Cultural Heritage Image

Fine-grained image classification is a challenging research topic because of the high degree of similarity among categories and the high degree of dissimilarity for a specific category caused by different poses and scales. A cultural heritage image is one of the fine-grained images because each image has the same similarity in most cases. Using the classification technique, distinguishing cultural heritage architecture may be difficult. This study proposes a cultural heritage content retrieval method using adaptive deep learning for fine-grained image retrieval. The key contribution of this research was the creation of a retrieval model that could handle incremental streams of new categories while maintaining its past performance in old categories and not losing the old categorization of a cultural heritage image. The goal of the proposed method is to perform a retrieval task for classes. Incremental learning for new classes was conducted to reduce the re-training process. In this step, the original class is not necessary for re-training which we call an adaptive deep learning technique. Cultural heritage in the case of Thai archaeological site architecture was retrieved through machine learning and image processing. We analyze the experimental results of incremental learning for fine-grained images with images of Thai archaeological site architecture from world heritage provinces in Thailand, which have a similar architecture. Using a fine-grained image retrieval technique for this group of cultural heritage images in a database can solve the problem of a high degree of similarity among categories and a high degree of dissimilarity for a specific category. The proposed method for retrieving the correct image from a database can deliver an average accuracy of 85 percent. Adaptive deep learning for fine-grained image retrieval was used to retrieve cultural heritage content, and it outperformed state-of-the-art methods in fine-grained image retrieval.     

基于树核函数的英文句子情感分类研究

最近几年,由于在线客户评论信息飞快地增长。如何把这些信息分类为正向和负向情感是一个迫切需要解决的问题。提出了一种细粒度级别(句子级别)的情感分类方法,该方法在SVM分类器中使用了树核和复合核函数来进行句子级别情感的分类。实验结果表明在句子级别的情感分类中树核和复合核的方法比线性核具有更佳的性能。     

Electrokinetic Remediation of Cadmium-Contaminated Clay

Electrokinetic extraction has been demonstrated to be very effective in removing heavy metals from Georgia kaolinite. The relatively high removal efficiency depends on the extremely acidic soil environment generated by the electrokinetic process. However, the efficiency observed in Georgia kaolinite cannot be achieved in soils of high acid/base buffer capacity without enhancement. In this study, the effect of ethylenediaminetetraacetic acid (EDTA) to enhance electrokinetic extraction of cadmium from Milwhite kaolinite was examined. The influence of electro-osmotic flow direction on the migration of cadmium, EDTA, and their complexes were also investigated. It was observed that injection of EDTA from the cathode reservoir by a reverse electro-osmotic flow could mobilize the cadmium in the specimen effectively. A less significant mobilization of cadmium was observed when the electro-osmotic flow was directed toward the cathode. However, accumulation of cadmium near the anode was observed regardless of the electro-osmotic flow direction.     

Relationship between the Undrained Shear Strength, Water Content, and Mineralogical Properties of Fine-Grained Soils

The relationship between the undrained shear strength of fine-grained soils and the water content can be described with a nonlinear function in which the type of soil is determined by two parameters. It is well known that these parameters depend mainly on the mineral compositions of soils; these relationships, however, have not yet been investigated. The findings described in this paper define those mineralogical properties of soils which determine the values of both parameters. Experimentally obtained results suggest that the parameters primarily depend on the size of the clay minerals, their quantity in soil composition, and the interlayer water quantity in the expanding clay minerals. As this dependence is well defined, the parameters, and thus the undrained shear strength at different water content, can be defined from knowledge of these mineralogical soil properties.     

Appropriate Material Properties for Advective–Diffusive Solute Flux in Membrane Soil

A generalized advective–diffusive equation for describing electrolytic solute transport in fine-grained soil (clay) membranes is presented. Clarification is made between the current theory and the widely cited coupled-flow theory by Yeung and Mitchell. Results of recently published experimental data are evaluated to demonstrate that the effective diffusion coefficient associated with Fick’s first law is not an appropriate independent material property for solute transport considerations in membrane soil. Three independent and experimentally attainable material properties are identified, specifically: osmotic efficiency, membrane diffusion coefficient, and hydraulic conductivity. Simple physical experiments by which these properties may be measured are described.     

Modelling the compaction curve of fine-grained soils

A theoretical model for the compaction curve of fine-grained soils at various compaction efforts for the entire range of water content is presented in this study. The prediction method is based on the assumption that the compaction curve represents the state surface at the yield state in an unsaturated condition. Thus, for each applied compaction effort, the compaction curve relates to one yielding point on the saturated normal consolidation line (NCL). For a given soil, the model requires the NCL, S_rc, and one point from any compaction curve to predict the compaction curves for different compaction efforts. Moreover, the lines of equal suctions on the compaction curves can be determined if the SWCC, the wetting path, is known. The model introduced here provides additional theoretical understanding of the soil׳s volume change behavior of the compaction curve. The model was verified in two ways: first it was verified quantitatively, by experimental results, and second it was verified qualitatively, by examining the relationships from other models in the literature. The model was further applied to experimental data reported in the literature on previous static and dynamic compaction tests. The results show that the model fits the experimental data very well. Finally, a simple chart, based on this model and using only liquid limits, is presented to estimate γ_dmax and OMC quickly.     

A Generalized Relationship for Determination of Tensile Strength of Fine-Grained Soils from Shrinkage Characteristics

Tensile strength of fine-grained soils has been extensively investigated by earlier researchers and several methodologies have been evolved for its determination. However, either most of these methods are not valid/applicable for a wide range of moisture contents or they involve tedious sample/specimen preparation. In this context, the methodology of determining tensile strength by employing thin films, which is available in the literature, has been found to be quite handy and useful. It has been observed that a unique relationship exists among the tensile strength, moisture content, and shrinkage characteristics of fine-grained soils. This methodology is appreciable due to its applicability to a wide range of moisture contents, comparable ease of sample preparation and testing, and the obtained results lack generalization. Exhaustive tests were conducted on fine-grained soils of entirely different characteristics and generalized relationships have been proposed between the percentage linear shrinkage, tensile strength, and moisture content (defined as liquid to solid ratio). Based on a critical analysis of the results available in the literature, the efficiency of such relationships for determination of tensile strength of fine-grained soils has been demonstrated. In the authors’ opinion, such relationships would be quite useful for determining tensile strength of fine-grained soils from their linear shrinkage, which can easily be measured in a conventional geotechnical engineering laboratory.