Layered Approach Using Conditional Random Fields for Intrusion Detection

Intrusion detection faces a number of challenges; an intrusion detection system must reliably detect malicious activities in a network and must perform efficiently to cope with the large amount of network traffic. In this paper, we address these two issues of Accuracy and Efficiency using Conditional Random Fields and Layered Approach. We demonstrate that high attack detection accuracy can be achieved by using Conditional Random Fields and high efficiency by implementing the Layered Approach. Experimental results on the benchmark KDD '99 intrusion data set show that our proposed system based on Layered Conditional Random Fields outperforms other well-known methods such as the decision trees and the naive Bayes. The improvement in attack detection accuracy is very high, particularly, for the U2R attacks (34.8 percent improvement) and the R2L attacks (34.5 percent improvement). Statistical Tests also demonstrate higher confidence in detection accuracy for our method. Finally, we show that our system is robust and is able to handle noisy data without compromising performance.     

Design and analysis of SSSC-based supplementary damping controller

Power-system stability improvement by a static synchronous series compensator (SSSC)-based damping controller is thoroughly investigated in this paper. The design problem of the proposed controller is formulated as an optimization problem, and real coded genetic algorithm (RCGA) is employed to search for the optimal controller parameters. Both local and remote signals with associated time delays are considered in the present study and a comparison has been made between the two signals. The performances of the proposed controllers are evaluated under different disturbances for both single-machine infinite-bus power system and multi-machine power system. Simulation results are presented and compared with a recently published modern heuristic optimization technique under various disturbances to show the effectiveness and robustness of the proposed approach.     

On a new class of analytic functions associated with conic domain

The aim of this paper is to generalize the conic domain defined by Kanas and Wisniowska, and define the class of functions which map the open unit disk E onto this generalized conic domain. A brief comparison between these conic domains is the main motivation of this paper. A correction is made in selecting the range interval of order of conic domain.     

Short-term and long-term memory analysis of learning using 2D and 3D educational contents

ABSTRACT

The effect of 2D and 3D educational content learning on memory has been studied using electroencephalography (EEG) brain signal. A hypothesis is set that the 3D materials are better than the 2D materials for learning and memory recall. To test the hypothesis, we proposed a classification system that will predict true or false recall for short-term memory (STM) and long-term memory (LTM) after learning by either 2D or 3D educational contents. For this purpose, EEG brain signals are recorded during learning and testing; the signals are then analysed in the time domain using different types of features in various frequency bands. The features are then fed into a support vector machine (SVM)-based classifier. The experimental results indicate that the learning and memory recall using 2D and 3D contents do not have significant differences for both the STM and the LTM.     

Spiral-shaped inertial stem cell device for high-throughput enrichment of iPSC-derived neural stem cells

Stem cell enrichment plays a critical role in both research and clinical applications. The typical method for stem cell enrichment may use invasive processes and takes a long period of time. Spiral-shaped microfluidic devices, which combine lift and Dean drag forces to direct cells of different sizes into separate trajectories, can be used to noninvasively process samples at a rate of milliliters per minute. This paper presents a simple 2-loop spiral-shaped inertial microfluidic devices with the aid of sheath flow to enrich neural stem cells (NSCs), derived from induced pluripotent stem cells. NSCs and spontaneously differentiated non-neural cells were mixed and flowed through the spiral-shaped devices. Samples collected at the outlets were analyzed for purity and recovery. It was found that the device focused the NSCs into a narrow trajectory, which could then be collected in two out of the eight outlets. The device was tested at different flow rates and found that the most highly enriched fractions (2.1×) with NSCs recovery 93% were achieved at the flow rate (3 ml/min). Next, we extended our investigation from 2-loop design to 10-loop design to eliminate the use of sheath flow. NSCs were enriched to 2.5×, but only 38% of the NSCs were recovered from the most enriched fractions. Spiral-shaped microfluidic devices are capable of rapid, label-free enrichment of target stem cells, and have great potential in point-of-care tissue preparation.     

Conflict-preserving abstraction of discrete event systems using annotated automata

This paper proposes to enhance compositional verification of the nonblocking property of discrete event systems by introducing annotated automata. Annotations store nondeterministic branching information, which would otherwise be stored in extra states and transitions. This succinct representation makes it easier to simplify automata and enables new efficient means of abstraction, reducing the size of automata to be composed and thus the size of the synchronous product state space encountered in verification. The abstractions proposed are of polynomial complexity, and they have been successfully applied to model check the nonblocking property of the same set of large-scale industrial examples as used in related work.     

Bandwidth requirements for accurate detection of direct path in multipath environment

The accurate detection of the direct path in a dense multipath environment is critical in time-based and angle-of-arrival-based location estimation techniques. It is generally assumed that an infinitely large bandwidth is helpful in the accurate detection of the direct path and high-range resolution. It is experimentally demonstrated that, for a wideband system, a bandwidth of up to 4 GHz, centred on 12.5 GHz, is sufficient for accurate detection of direct path in a typical indoor scattering environment. Additionally, the bandwidth gain, incremental range accuracy with bandwidth, is an effective indicator of the bandwidth requirements for accurate detection of the direct path.     

Statistical evaluation of water tree lengths in XLPE cables at different temperatures

Accelerated aging of two types of commercially produced medium voltage XLPE insulated cables was carried out under the combined stresses of three types consisting of ionic aqueous species, elevated electrical stress and temperature cycling. After 1000 h of aging, the water tree parameters were evaluated. Results show that external ionic species exert profound impact on the generation of bow tie and vented water trees, while impurities inherently present in the cable components also contribute significantly. Temperature cycling increases the bow tie trees by an order of magnitude, while morphology of insulation influences the level of water tree degradation. The water tree population and their lengths were subjected to Weibull and log-normal models of statistical distributions and the data were found to fit better on the log-normal model. For a better statistical inference, a computer based Monte Carlo simulation was devised and used to precisely discriminate the two models. Simulation results further confirm that both types of water trees fit better on the log-normal model. The most likely mechanism for water tree degradation is fatigue based and hence mechanistic by nature.     

Joint physical and link layer error control analysis for nanonetworks in the Terahertz band

Nanonetworks consist of nano-sized communicating devices which are able to perform simple tasks at the nanoscale. The limited capabilities of individual nanomachines and the Terahertz (THz) band channel behavior lead to error-prone wireless links. In this paper, a cross-layer analysis of error-control strategies for nanonetworks in the THz band is presented. A mathematical framework is developed and used to analyze the tradeoffs between Bit Error Rate, Packet Error Rate, energy consumption and latency, for five different error-control strategies, namely, Automatic Repeat reQuest (ARQ), Forward Error Correction (FEC), two types of Error Prevention Codes (EPC) and a hybrid EPC. The cross-layer effects between the physical and the link layers as well as the impact of the nanomachine capabilities in both layers are taken into account. At the physical layer, nanomachines are considered to communicate by following a time-spread on-off keying modulation based on the transmission of femtosecond-long pulses. At the link layer, nanomachines are considered to access the channel in an uncoordinated fashion, by leveraging the possibility to interleave pulse-based transmissions from different nodes. Throughout the analysis, accurate path loss, noise and multi-user interference models, validated by means of electromagnetic simulation, are utilized. In addition, the energy consumption and latency introduced by a hardware implementation of each error control technique, as well as, the additional constraints imposed by the use of energy-harvesting mechanisms to power the nanomachines, are taken into account. The results show that, despite their simplicity, EPCs outperform traditional ARQ and FEC schemes, in terms of error correcting capabilities, which results in further energy savings and reduced latency.