Hierarchical TCP network traffic classification with adaptive optimisation

Nowadays, with the increasing deployment of modern packet-switching networks, traffic classification is playing an important role in network administration. To identify what kinds of traffic transmitting across networks can improve network management in various ways, such as traffic shaping, differential services, enhanced security, etc. By applying different policies to different kinds of traffic, Quality of Service (QoS) can be achieved and the granularity can be as fine as flow-level. Since illegal traffic can be identified and filtered, network security can be enhanced by employing advanced traffic classification. There are various traditional techniques for traffic classification. However, some of them cannot handle traffic generated by applications using non-registered ports or forged ports, some of them cannot deal with encrypted traffic and some techniques require too much computational resources. The newly proposed technique by other researchers, which uses statistical methods, gives an alternative approach. It requires less resources, does not rely on ports and can deal with encrypted traffic. Nevertheless, the performance of the classification using statistical methods can be further improved. In this thesis, we are aiming for optimising network traffic classification based on the statistical approach. Because of the popularity of the TCP protocol, and the difficulties for classification introduced by TCP traffic controls, our work is focusing on classifying network traffic based on TCP protocol. An architecture has been proposed for improving the classification performance, in terms of accuracy and response time. Experiments have been taken and results have been evaluated for proving the improved performance of the proposed optimised classifier. In our work, network packets are reassembled into TCP flows. Then, the statistical characteristics of flows are extracted. Finally the classes of input flows can be determined by comparing them with the profiled samples. Instead of using only one algorithm for classifying all traffic flows, our proposed system employs a series of binary classifiers, which use optimised algorithms to detect different traffic classes separately. There is a decision making mechanism for dealing with controversial results from the binary classifiers. Machining learning algorithms including k-nearest neighbour, decision trees and artificial neural networks have been taken into consideration together with a kind of non-parametric statistical algorithm — Kolmogorov-Smirnov test. Besides algorithms, some parameters are also optimised locally, such as detection windows, acceptance thresholds. This hierarchical architecture gives traffic classifier more flexibility, higher accuracy and less response time

Case based reasoning approach for transaction outcomes prediction on currency markets

This paper presents a case based reasoning approach for making profit in the foreign exchange (forex) market with controlled risk using k nearest neighbour (kNN) and improving on the results with neural networks (NNs) and a combination of both. Although many professionals have proven that exchange rates can be forecast using neural networks for example, poor trading strategies and unpredictable market fluctuation can inevitably still result in substantial loss. As a result, the method proposed in this paper will focus on predicting the outcome of potential trades with fixed stop loss (ST) and take profit (TP) positions1, in terms of a win or loss. With the help of the Monte Carlo method, randomly generated trades together with different traditional technical indicators are fed into the models, resulting in a win or lose output. This is clearly a case based reasoning approach, in terms of searching similar past trade setups for selecting successful trades. There are several advantages over classical forecasting associated with such an approach, and the technique presented in this paper brings a novel perspective to problem of exchange trades predictability. The strategies implemented have not been empirically investigated with such wide a range of time granularities as is done in this paper, in any to the authors known academic literature. The profitability of this approach is back-tested at the end of this paper and highly encouraging results are reported

第1059回千葉医学会例会・第2回呼吸器内科例会(第16回呼吸器内科同門会)

Additional file 4. Diseases prevention and control provided and medical services availabilities in different villages and camps

Scatter diagram of the measurements of M1 (left) and m1 (right) of <i>Prosiphneus</i> and “<i>Pliosiphneus</i>” <i>lyratus</i>.

<p>a, <i>Prosiphneus</i> cf. <i>P</i>. <i>eriksoni</i>, Zanda, Tibet; b, <i>P</i>. <i>qiui</i>, Amuwusu, Nei Mongol; c, <i>P</i>. <i>haoi</i>, Qin’an, Gansu; d, <i>P</i>. <i>licenti</i>, Qin’an, Gansu; e, <i>P</i>. <i>tianzuensis</i>, Tianzhu, Gansu; f, <i>Prosiphneus</i> cf. <i>P</i>. <i>eriksoni</i>, Kunlun Pass, Qinghai; g, <i>P</i>. <i>licenti</i>, Qingyang, Gansu; h, <i>P</i>. <i>murinus</i>, Yushe, Shanxi; i, “<i>Pliosiphneus</i>” <i>lyratus</i>, Yushe; j, <i>Prosiphneus</i> cf. <i>P</i>. <i>eriksoni</i>, Bilike, Nei Mongol; k, <i>P</i>. <i>eriksoni</i>, Ertemte, Nei Mongol.</p

Geographic distribution of the main localities of the fossil and extant zokors.

<p>Green line–extant (referred from website of IUCN, <a href="http://www.iucnredlist.org/details/14116/0" target="_blank">http://www.iucnredlist.org/details/14116/0</a>, /14118/0, /14119/0, /14120/0, /14121/0, and /14122/0, accessed on Dec. 11^th, 2014); yellow shadow and black circles–fossils (based on Zheng, 1994). Red arrow shows a potential dispersal way of the <i>Prosipheus</i> from its center of origin in north China and Mongolian Plateau to the Zanda Basin of southwestern Tibetan Plateau, possibly via the Hol Xil-Qiangtang hinterland in northern Tibet.</p

Molars of <i>Prosiphneus eriksoni</i> from loc. ZD1001, Zanda, Tibet.

<p>A. right M1, V 18032.2; B. right M2, V 18032.3; C. right M2, V 18032.6; D. right M2, V 18032.7; E. left M3, V 18032.10; F. left M3, V 18032.11; G. left m1, V 18032.13; H, left m1, V 18032.14; I, left m1, V 18032.15; J. right m1, V 18032.17; K. left m2, V 18032.19; L. left m2, V 18032.20; M. left m3, V 18032.25. A1-M1, occlusal view; A2-F2, labial view, G2-M2, lingual view, showing the dentine tracts.</p

Species ranges and cladistic phylogeny among the <i>Prosiphneus</i> in the Neogene China.

<p>Most of the species ranges are approximate. The first lower molars are scaled to their approximate relative size and the Fig also shows the m1 evolutionary trends of <i>Prosiphneus</i> especially on the heightening of the crown and lateral dentine tracts.</p

Comparison of the dentine tract measurements of M1 (right) and m1 (left) of <i>Prosiphneus</i>.

<p>1, <i>P</i>. <i>qiui</i>, Amuwusu; 2, <i>P</i>. <i>haoi</i>, Qin’an; 3, <i>P</i>. <i>licenti</i>, Qingyang; 4, <i>P</i>. <i>murinus</i>, Yushe; 5, <i>P</i>. <i>tianzuensis</i>, Tianzhu; 6and 8 <i>P</i>. <i>eriksoni</i>, 6, Ertemte; 8, Zanda; 7and 9, <i>Prosiphneus</i> cf. <i>P</i>. <i>eriksoni</i>: 7, Bilike; 9, Kunlun Pass. 1–6, data cited from Zheng et al. (2004: Tables <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144993#pone.0144993.t001" target="_blank">1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144993#pone.0144993.t002" target="_blank">2</a>); 7, remeasured and 8, 9 measured by authors.</p

Near-infrared and Mid-infrared Light Emission of Boron-doped Crystalline Silicon

The bottleneck in achieving fully integrated silicon photonics lies in silicon-based light-emitting devices that are compatible with standard CMOS technology. Dislocation loops by implanting boron into silicon and annealing represents an enticing strategy to transform highly inefficient silicon into a luminescent material. However, the emission at telecommunication wavelength suffers from the strong thermal quenching effect, resulting in low efficiency at room temperature. Here, we applied a new deep cooling process to address this issue. Interestingly, we find that electrons and holes recombine through defects emitting two photons, one in near infrared (NIR, 1.3~1.6 {\mu}m) and the other in mid-infrared band (MIR, around 3.5 {\mu}m). The PL intensity at NIR increases by three folds when the temperature increases from 77 K to 300K. Furthermore, the NIR light emission of reverse biased silicon diodes was significantly enhanced compared to forward bias, emitting the maximum output power of 42 nW at 60 mA. The results offer new opportunities for the development of IR light sources in integrated circuits

Mechanism of the Anomalous Dependence between Spin–Orbit Coupling and Dimensionality in Lead Halide Perovskites

The spin–orbit coupling (SOC) effect of lead (Pb) atoms is a consequential attribute of the unique optoelectronic and defect properties of lead halide perovskites (LHPs). It has been found that the SOC effect varies significantly as the structural dimensionality changes with an anomalous dependence; i.e., while the SOC strength monotonically decreases as structural dimensionality decreases from three-dimensional (3D) to two-dimensional (2D) and then to one-dimensional (1D), the zero-dimensional (0D) SOC strength is greater than the 1D SOC strength. The underlying mechanism of such a SOC dimensionality dependence anomaly remains elusive. In this work, we show that Pb 6p energy splitting increases from 3D to 2D and to 1D LHPs due to the increased degree of distortion, leading to a reduced SOC strength. However, the degree of distortion decreases for the 1D to 0D transformation, resulting in reverse SOC enhancement. The mechanism described in this work can be employed to regulate the SOC effect in the design of perovskite materials