This paper proposes a spam detection technique, at the packet level (layer 3), based on classification of e-mail contents. Our proposal targets spam control implementations on middleboxes. E-mails are first pre-classified (pre-detected) for spam on a per-packet basis, without the need for reassembly. This, in turn, allows fast e-mail class estimation (spam detection) at receiving e-mail servers to support more effective spam handling on both inbound and outbound (relayed) e-mails. In this paper, the naïve Bayes classification technique is adapted to support both pre-classification and fast e-mail class estimation, on a per-packet basis. We focus on evaluating the accuracy of spam detection at layer 3, considering the constraints on processing byte-streams over the network, including packet re-ordering, fragmentation, overlapped bytes, and different packet sizes. Results show that the proposed layer-3 classification technique gives less than 0.5% false positive, which approximately equals the performance attained at layer 7. This shows that classifying e-mails at the packet level could differentiate non-spam from spam with high confidence for a viable spam control implementation on middleboxes. 相似文献
A microarray machine offers the capacity to measure the expression levels of thousands of genes simultaneously. It is used
to collect information from tissue and cell samples regarding gene expression differences that could be useful for cancer
classification. However, the urgent problems in the use of gene expression data are the availability of a huge number of genes
relative to the small number of available samples, and the fact that many of the genes are not relevant to the classification.
It has been shown that selecting a small subset of genes can lead to improved accuracy in the classification. Hence, this
paper proposes a solution to the problems by using a multiobjective strategy in a genetic algorithm. This approach was tried
on two benchmark gene expression data sets. It obtained encouraging results on those data sets as compared with an approach
that used a single-objective strategy in a genetic algorithm.
This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January
31–February 2, 2008 相似文献
Gene expression technology, namely microarrays, offers the ability to measure the expression levels of thousands of genes
simultaneously in biological organisms. Microarray data are expected to be of significant help in the development of an efficient
cancer diagnosis and classification platform. A major problem in these data is that the number of genes greatly exceeds the
number of tissue samples. These data also have noisy genes. It has been shown in literature reviews that selecting a small
subset of informative genes can lead to improved classification accuracy. Therefore, this paper aims to select a small subset
of informative genes that are most relevant for cancer classification. To achieve this aim, an approach using two hybrid methods
has been proposed. This approach is assessed and evaluated on two well-known microarray data sets, showing competitive results.
This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January
31–February 2, 2008 相似文献
Neural Computing and Applications - A lot of different methods are being opted for improving the educational standards through monitoring of the classrooms. The developed world uses Smart... 相似文献
Underwater optical communication (UOC) has attracted considerable interest in the continuous expansion of human activities in marine/ocean environments. The water-durable and self-powered photoelectrodes that act as a battery-free light receiver in UOC are particularly crucial, as they may directly face complex underwater conditions. Emerging photoelectrochemical (PEC)-type photodetectors are appealing owing to their intrinsic aqueous operation characteristics with versatile tunability of photoresponses. Herein, a self-powered PEC photodetector employing n-type gallium nitride (GaN) nanowires as a photoelectrode, which is decorated with an iridium oxide (IrOx) layer to optimize charge transfer dynamics at the GaN/electrolyte interface, is reported. Strikingly, the constructed n-GaN/IrOx photoelectrode breaks the responsivity-bandwidth trade-off limit by simultaneously improving the response speed and responsivity, delivering an ultrafast response speed with response/recovery times of only 2 µs/4 µs while achieving a high responsivity of 110.1 mA W−1. Importantly, the device exhibits a large bandwidth with 3 dB cutoff frequency exceeding 100 kHz in UOC tests, which is one of the highest values among self-powered photodetectors employed in optical communication system. 相似文献
Artificial Life and Robotics - Although the design of the reward function in reinforcement learning is important, it is difficult to design a system that can adapt to a variety of environments and... 相似文献
The edge computing model offers an ultimate platform to support scientific and real-time workflow-based applications over the edge of the network. However, scientific workflow scheduling and execution still facing challenges such as response time management and latency time. This leads to deal with the acquisition delay of servers, deployed at the edge of a network and reduces the overall completion time of workflow. Previous studies show that existing scheduling methods consider the static performance of the server and ignore the impact of resource acquisition delay when scheduling workflow tasks. Our proposed method presented a meta-heuristic algorithm to schedule the scientific workflow and minimize the overall completion time by properly managing the acquisition and transmission delays. We carry out extensive experiments and evaluations based on commercial clouds and various scientific workflow templates. The proposed method has approximately 7.7% better performance than the baseline algorithms, particularly in overall deadline constraint that gives a success rate.
Journal of Signal Processing Systems - Segmentation of thigh tissues (muscle, fat, inter-muscular adipose tissue (IMAT), bone, and bone marrow) from magnetic resonance imaging (MRI) scans is useful... 相似文献
The Journal of Supercomputing - Power consumption is likely to remain a significant concern for exascale performance in the foreseeable future. In addition, graphics processing units (GPUs) have... 相似文献
Neural Computing and Applications - In the present study, a novel application of backpropagated neurocomputing heuristics (BNCH) is presented for epidemic virus model that portrays the Stuxnet... 相似文献