Massively parallel acceleration of a document-similarity classifier to detect web attacks

This paper describes our approach to adapting a text document similarity classifier based on the Term Frequency Inverse Document Frequency (TFIDF) metric to two massively multi-core hardware platforms. The TFIDF classifier is used to detect web attacks in HTTP data. In our parallel hardware approaches, we design streaming, real time classifiers by simplifying the sequential algorithm and manipulating the classifier’s model to allow decision information to be represented compactly. Parallel implementations on the Tilera 64-core System on Chip and the Xilinx Virtex 5-LX FPGA are presented. For the Tilera, we employ a reduced state machine to recognize dictionary terms without requiring explicit tokenization, and achieve throughput of 37 MB/s at a slightly reduced accuracy. For the FPGA, we have developed a set of software tools to help automate the process of converting training data to synthesizable hardware and to provide a means of trading off between accuracy and resource utilization. The Xilinx Virtex 5-LX implementation requires 0.2% of the memory used by the original algorithm. At 166 MB/s (80X the software) the hardware implementation is able to achieve Gigabit network throughput at the same accuracy as the original algorithm.     

Two heads better than one: pattern discovery in time-evolving multi-aspect data

Data stream values are often associated with multiple aspects. For example each value observed at a given time-stamp from environmental sensors may have an associated type (e.g., temperature, humidity, etc.) as well as location. Time-stamp, type and location are the three aspects, which can be modeled using a tensor (high-order array). However, the time aspect is special, with a natural ordering, and with successive time-ticks having usually correlated values. Standard multiway analysis ignores this structure. To capture it, we propose 2 Heads Tensor Analysis (2-heads), which provides a qualitatively different treatment on time. Unlike most existing approaches that use a PCA-like summarization scheme for all aspects, 2-heads treats the time aspect carefully. 2-heads combines the power of classic multilinear analysis with wavelets, leading to a powerful mining tool. Furthermore, 2-heads has several other advantages as well: (a) it can be computed incrementally in a streaming fashion, (b) it has a provable error guarantee and, (c) it achieves significant compression ratio against competitors. Finally, we show experiments on real datasets, and we illustrate how 2-heads reveals interesting trends in the data. This is an extended abstract of an article published in the Data Mining and Knowledge Discovery journal.     

Reduction mammaplasty improves symptoms of macromastia

The condition macromastia has not been defined and characterized precisely by the medical community. Whether the patient with hypertrophic breasts is a candidate for or can be helped by reduction mammaplasty is unclear to both the medical and the lay community. A prospective study of 39 women undergoing reduction mammaplasty surgery was initiated to answer these questions. Patients rated the severity of their somatic pain symptoms and discomfort before reduction mammaplasty and again after complete recovery. The severity of their symptoms and complaints was numerically graded and analyzed. These data were compared with similar data obtained from 40 "small-breasted" women of similar age. Headache, neck pain, back pain, shoulder pain, and bra strap groove pain were present in 60 to 92 percent of patients, and 97 percent of patients had at least three of these pain symptoms preoperatively. All the patients had reduction of their pain symptomatology postoperative, and 25 percent of the study patients had total elimination of pain symptoms by reduction mammaplasty. The postoperative incidence and severity of pain symptoms and discomfort complaints were statistically equivalent to or less than the levels in the control group.     

Cytomorphometric markers for uterine cancer in intermediate cells

Precise microphotometric assessment of intermediate cells from patients with normal cervical cytology and from patients with dysplasia or carcinoma in situ shows the existence of small but consistent differences. Marker features for the presence of premalignant and malignant disease can be extracted from the cell images of "normal"-appearing intermediate cells. The marker features and their diagnostic classification potential are described.     

随机算法异步并行化的效率分析

随机算法的执行时间具有不确定性,这种不确定性为随机算法的异步并行提供了良好的基础,已有许多计算实验表明了随机算法的异步并行可以达到线性甚至超线性的加速.对于求解SAT问题的随机算法RDP,研究了异步并行效率与运行时间分布和处理器数目之间的关系.应用一种单峰分布──分段线性分布模型来模拟随机算法的运行时间分布.理论分析和计算结果均表明:当处理器数目k较小和单峰位于分布的前部时,随机算法的异步并行具有近线性加速.     

Effect of Fiber Length on Carbon Nanotube-Induced Fibrogenesis

Given their extremely small size and light weight, carbon nanotubes (CNTs) can be readily inhaled by human lungs resulting in increased rates of pulmonary disorders, particularly fibrosis. Although the fibrogenic potential of CNTs is well established, there is a lack of consensus regarding the contribution of physicochemical attributes of CNTs on the underlying fibrotic outcome. We designed an experimentally validated in vitro fibroblast culture model aimed at investigating the effect of fiber length on single-walled CNT (SWCNT)-induced pulmonary fibrosis. The fibrogenic response to short and long SWCNTs was assessed via oxidative stress generation, collagen expression and transforming growth factor-beta (TGF-β) production as potential fibrosis biomarkers. Long SWCNTs were significantly more potent than short SWCNTs in terms of reactive oxygen species (ROS) response, collagen production and TGF-β release. Furthermore, our finding on the length-dependent in vitro fibrogenic response was validated by the in vivo lung fibrosis outcome, thus supporting the predictive value of the in vitro model. Our results also demonstrated the key role of ROS in SWCNT-induced collagen expression and TGF-β activation, indicating the potential mechanisms of length-dependent SWCNT-induced fibrosis. Together, our study provides new evidence for the role of fiber length in SWCNT-induced lung fibrosis and offers a rapid cell-based assay for fibrogenicity testing of nanomaterials with the ability to predict pulmonary fibrogenic response in vivo.     

Correcting evaluation bias of relational classifiers with network cross validation

Recently, a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and identically distributed (i.i.d.). These methods specifically exploit the statistical dependencies among instances in order to improve classification accuracy. However, there has been little focus on how these same dependencies affect our ability to draw accurate conclusions about the performance of the models. More specifically, the complex link structure and attribute dependencies in relational data violate the assumptions of many conventional statistical tests and make it difficult to use these tests to assess the models in an unbiased manner. In this work, we examine the task of within-network classification and the question of whether two algorithms will learn models that will result in significantly different levels of performance. We show that the commonly used form of evaluation (paired t-test on overlapping network samples) can result in an unacceptable level of Type I error. Furthermore, we show that Type I error increases as (1) the correlation among instances increases and (2) the size of the evaluation set increases (i.e., the proportion of labeled nodes in the network decreases). We propose a method for network cross-validation that combined with paired t-tests produces more acceptable levels of Type I error while still providing reasonable levels of statistical power (i.e., 1−Type II error).     

Compatibility of the Support System Consisting of Yielding Elements and Shotcrete Lining in Highly Faulted Grounds

The design procedure is made for a mine shaft where permanent underground facilities are interconnected. The highly faulted grounds were identified using empirical and semi-empirical theories. Furthermore, the behavior types are presented. This paper presents excavation and support methods in such ground conditions and the calculations results show that the installation of the yielding elements have an effect on support elements and prevent shotcrete damage during the curing stage. Different numerical analyses carried out showed that, with the yielding elements installed, the total displacements increase but the final axial force reduces, and therefore, the characteristic compressive strength of shotcrete is not exceeded. The calculation results of ground loads and displacements on the designed support system are presented with a 3D numerical geo-mechanical model adopted for highly faulted ground surrounding deeper complex underground structures.     

Torrefied biomass‐polypropylene composites

Torrefied almond shells and wood chips were incorporated into polypropylene as fillers to produce torrefied biomass‐polymer composites. The composites were prepared by extrusion and injection molding. Response surface methodology was used to examine the effects of filler concentration, filler size, and lignin factor (relative lignin to cellulose concentration) on the material properties of the composites. The heat distortion temperatures, thermal properties, and tensile properties of the composites were characterized by thermomechanical analysis, differential scanning calorimetry, and tensile tests, respectively. The torrefied biomass composites had heat distortion temperatures of 8–24°C higher than that of neat polypropylene. This was due to the torrefied biomass restricting mobility of polypropylene chains, leading to higher temperatures for deformation. The incorporation of torrefied biomass generally resulted in an increase in glass transition temperature, but did not affect melting temperature. Also, the composites had lower tensile strength and elongation at break values than those of neat polypropylene, indicating weak adhesion between torrefied biomass and polypropylene. However, scanning electron microscopy results did indicate some adhesion between torrefied biomass and polypropylene. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41582.