Improvement in Intrusion Detection With Advances in Sensor Fusion

Various intrusion detection systems (IDSs) reported in the literature have shown distinct preferences for detecting a certain class of attack with improved accuracy, while performing moderately on the other classes. In view of the enormous computing power available in the present-day processors, deploying multiple IDSs in the same network to obtain best-of-breed solutions has been attempted earlier. The paper presented here addresses the problem of optimizing the performance of IDSs using sensor fusion with multiple sensors. The trade-off between the detection rate and false alarms with multiple sensors is highlighted. It is illustrated that the performance of the detector is better when the fusion threshold is determined according to the Chebyshev inequality. In the proposed data-dependent decision ( DD) fusion method, the performance optimization of ndividual IDSs is first addressed. A neural network supervised learner has been designed to determine the weights of individual IDSs depending on their reliability in detecting a certain attack. The final stage of this DD fusion architecture is a sensor fusion unit which does the weighted aggregation in order to make an appropriate decision. This paper theoretically models the fusion of IDSs for the purpose of demonstrating the improvement in performance, supplemented with the empirical evaluation.

Effect of antiserum to luteinizing hormone (LHAS) on the physiology of the epididymis and accessory glands in the albino rat

Rabbit antiserum specific to ovine luteinizing hormone free of contaminating antibodies to nonspecific proteins and FSH was administered to adult, intact rats at a dose of 0.1 and 0.2 ml/day for five days. LHAS had no effect on the weights of the epididymis but decreased their secretory activity to castrate level. Administration of 0.2 ml of LHAS or castration resulted in a marked and comparable reduction in the weights and secretory activity of the accessory glands. LHAS, even at a lower dose (0.1 ml/day), caused a significant reduction in the content of sialic acid in the vas deferons and Cowper's glands. These results are discussed in relation to the factors that regulate the functions of the epididymis and accessory glands.

Effect of rabbit antiserum to ovine LH on reproductive organs in male hamsters and guinea-pigs

Administration of rabbit antiserum to ovine luteinizing hormone to immature hamsters and guinea-pigs resulted in a significant decrease in the weights of testes, seminal vesicle and ventral prostate. The author wishes to thank Prof. N.R. Moudgal for his interest and Family Planning Foundation for financial assistance.

Transport of retinol in the duck plasma

Retinol-binding protein and prealbumin were isolated from duck plasma by chromatography on DEAE-cellulose-and DEAE-Sephadex A-50, gel filtration on Sephadex G- 100 and preparative Polyacrylamide gel electrophoresis. The molecular weights of the retinolbinding protein-prealbumin complex, prealbumin and retinol-binding protein were found to be 75,000, 55,0000 and 20,000, respectively. On sodium dodecyl sulphate Polyacrylamide gel electrophoresis, prealbumin dissociated into identical subunits exhibiting a molecular weight of 13,500. Retinol-binding protein exhibited microheterogeneity on electrophoresis, whereas prealbumin moved as a single band unlike the multiple bands observed in chicken and rat.The ultraviolet and fluorescence spectra of the two proteins were similar to those isolated from other species. No carbohydrate moiety was detected in either retinol-binding protein or prealbumin. Duck retinol-binding protein and prealbumin showed cross-reactivity with their counterparts in chicken but differed immunologically from those of goat and man. Retinolbinding protein and prealbumin could be dissociated at low ionic strength, in 2M urea, by CMsephadex chromatography or on preparative electrophoresis. Although the transport of retinol in duck plasma is mediated by carrier proteins as in other species, it is distinguished by the absence of microheterogeneity in prealbumin and of an apo-retinol-binding protein form that could be transported in the plasma.

The purification and properties of peroxidase in Mycobacterium tuberculosis H37Rv and its possible role in the mechanism of action of isonicotinic acid hydrazide

Peroxidase from Mycobacterium tuberculosis H37Rv was purified to homogeneity. The homogeneous protein exhibits catalase and Y (Youatt's)-enzyme activities in addition to peroxidase activity. Further confirmation that the three activities are due to a single enzyme was accomplished by other criteria, such as differential thermal inactivation, sensitivity to different inhibitors, and co-purification. The Y enzyme (peroxidase) was separated from NADase (NAD+ glycohydrolase) inhibitor by gel filtration on Sephadex G-200. The molecular weights of peroxidase and NADase inhibitor, as determined by gel filtration, are 240000 and 98000 respectively. The Y enzyme shows two Km values for both isoniazid (isonicotinic acid hydrazide) and NAD at low and high concentrations. Analysis of the data by Hill plots revealed that the enzyme has one binding site at lower substrate concentrations and more than one at higher substrate concentration. The enzyme contains 6g-atoms of iron/mol. Highly purified preparations of peroxidases from different sources catalyse the Y-enzyme reaction, suggesting that the nature of the reaction may be a peroxidatic oxidation of isoniazid. Moreover, the Y-enzyme reaction is enhanced by O2. Isoniazid-resistant mutants do not exhibit Y-enzyme, peroxidase or catalase activities, and do not take up isoniazid. The Y-enzyme reaction is therefore implicated in the uptake of the drug.

Climate change impact assessment: Uncertainty modeling with imprecise probability

Hydrologic impacts of climate change are usually assessed by downscaling the General Circulation Model (GCM) output of large-scale climate variables to local-scale hydrologic variables. Such an assessment is characterized by uncertainty resulting from the ensembles of projections generated with multiple GCMs, which is known as intermodel or GCM uncertainty. Ensemble averaging with the assignment of weights to GCMs based on model evaluation is one of the methods to address such uncertainty and is used in the present study for regional-scale impact assessment. GCM outputs of large-scale climate variables are downscaled to subdivisional-scale monsoon rainfall. Weights are assigned to the GCMs on the basis of model performance and model convergence, which are evaluated with the Cumulative Distribution Functions (CDFs) generated from the downscaled GCM output (for both 20th Century [20C3M] and future scenarios) and observed data. Ensemble averaging approach, with the assignment of weights to GCMs, is characterized by the uncertainty caused by partial ignorance, which stems from nonavailability of the outputs of some of the GCMs for a few scenarios (in Intergovernmental Panel on Climate Change [IPCC] data distribution center for Assessment Report 4 [AR4]). This uncertainty is modeled with imprecise probability, i.e., the probability being represented as an interval gray number. Furthermore, the CDF generated with one GCM is entirely different from that with another and therefore the use of multiple GCMs results in a band of CDFs. Representing this band of CDFs with a single valued weighted mean CDF may be misleading. Such a band of CDFs can only be represented with an envelope that contains all the CDFs generated with a number of GCMs. Imprecise CDF represents such an envelope, which not only contains the CDFs generated with all the available GCMs but also to an extent accounts for the uncertainty resulting from the missing GCM output. This concept of imprecise probability is also validated in the present study. The imprecise CDFs of monsoon rainfall are derived for three 30-year time slices, 2020s, 2050s and 2080s, with A1B, A2 and B1 scenarios. The model is demonstrated with the prediction of monsoon rainfall in Orissa meteorological subdivision, which shows a possible decreasing trend in the future.

Characterization of vitamin A transport system from goat plasma

Retinol-binding protein and its complex with prealbumin were isolated from goat serum by chromatography on DEAE-Sephadex A-50, gel filtration and immuno-affinity chromatography on antigoat-serum albumin-Sepharose 4B. The homogeneous prealbumin-retinol-binding protein complex had a molecular weight of 75 000. Both on electrophoresis and in the presence of 2 M urea, the complex dissociated into retinol-binding protein and prealbumin. The molecular weight, electrophoretic behaviour, ultraviolet and fluorescence spectra of goat retinol-binding protein were similar to those isolated from other sources. On sodium dodecyl sulphate gel electrophoresis, goat prealbumin (molecular weight ≈ 55 000) exhibited two bands corresponding to molecular weights 26 000 and 13 000. This suggests that either goat prealbumin consists of two non-identical sub-units or perhaps complete dissociation might not have occurred. Goat prealbumin was able to bind Image -thyroxine and retinol-binding protein.

Dynamic viscosity of ternary mixtures of dichlorodifluoromethane (R-12), chlorodifluoromethane (R-22), and dichlorotetrafluoroethane (R-114) vapors

The viscosities of ternary mixtures of R-12, R-22, and R-114 vapors were determined at ambient temperature and pressure within +-1% by using an oscillating disk viscometer. The empirical viscosity obtained by Wllke's equation compares very well with the experimental results obtained with this vlscometer. In the case of this ternary vapor mixture, as long as the molar fraction ratio of R-12 to R-114 Is maintained at approximately 2"' (=Inverse ratio of thelr molecular weights) the viscosity of the ternary mixture at ambient temperature and pressure remalns constant irrespective of the percentage of R-22 present in the mixture.

An optimal dynamic inversion-based neuro-adaptive approach for treatment of chronic myelogenous leukemia

Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an innovative technique is presented to design an automatic drug administration strategy for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used to design the controller (medication dosage). First, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat the nominal model patients (patients who can be described by the mathematical model used here with the nominal parameter values) effectively. However, since the system parameters for a realistic model patient can be different from that of the nominal model patients, simulation studies for such patients indicate that the nominal controller is either inefficient or, worse, ineffective; i.e. the trajectory of the number of cancer cells either shows non-satisfactory transient behavior or it grows in an unstable manner. Hence, to make the drug dosage history more realistic and patient-specific, a model-following neuro-adaptive controller is augmented to the nominal controller. In this adaptive approach, a neural network trained online facilitates a new adaptive controller. The training process of the neural network is based on Lyapunov stability theory, which guarantees both stability of the cancer cell dynamics as well as boundedness of the network weights. From simulation studies, this adaptive control design approach is found to be very effective to treat the CML disease for realistic patients. Sufficient generality is retained in the mathematical developments so that the technique can be applied to other similar nonlinear control design problems as well.

On a Special Co-cycle Basis of Graphs

In this paper we consider the problems of computing a minimum co-cycle basis and a minimum weakly fundamental co-cycle basis of a directed graph G. A co-cycle in G corresponds to a vertex partition (S,V ∖ S) and a { − 1,0,1} edge incidence vector is associated with each co-cycle. The vector space over ℚ generated by these vectors is the co-cycle space of G. Alternately, the co-cycle space is the orthogonal complement of the cycle space of G. The minimum co-cycle basis problem asks for a set of co-cycles that span the co-cycle space of G and whose sum of weights is minimum. Weakly fundamental co-cycle bases are a special class of co-cycle bases, these form a natural superclass of strictly fundamental co-cycle bases and it is known that computing a minimum weight strictly fundamental co-cycle basis is NP-hard. We show that the co-cycle basis corresponding to the cuts of a Gomory-Hu tree of the underlying undirected graph of G is a minimum co-cycle basis of G and it is also weakly fundamental.

Nonlinear structural dynamical system identification using adaptive particle filters

The problem of identifying parameters of nonlinear vibrating systems using spatially incomplete, noisy, time-domain measurements is considered. The problem is formulated within the framework of dynamic state estimation formalisms that employ particle filters. The parameters of the system, which are to be identified, are treated as a set of random variables with finite number of discrete states. The study develops a procedure that combines a bank of self-learning particle filters with a global iteration strategy to estimate the probability distribution of the system parameters to be identified. Individual particle filters are based on the sequential importance sampling filter algorithm that is readily available in the existing literature. The paper develops the requisite recursive formulary for evaluating the evolution of weights associated with system parameter states. The correctness of the formulations developed is demonstrated first by applying the proposed procedure to a few linear vibrating systems for which an alternative solution using adaptive Kalman filter method is possible. Subsequently, illustrative examples on three nonlinear vibrating systems, using synthetic vibration data, are presented to reveal the correct functioning of the method. (c) 2007 Elsevier Ltd. All rights reserved.

New approximation algorithms for minimum cycle bases of graphs

We consider the problem of computing an approximate minimum cycle basis of an undirected edge-weighted graph G with m edges and n vertices; the extension to directed graphs is also discussed. In this problem, a {0,1} incidence vector is associated with each cycle and the vector space over F-2 generated by these vectors is the cycle space of G. A set of cycles is called a cycle basis of G if it forms a basis for its cycle space. A cycle basis where the sum of the weights of the cycles is minimum is called a minimum cycle basis of G. Cycle bases of low weight are useful in a number of contexts, e.g. the analysis of electrical networks, structural engineering, chemistry, and surface reconstruction. We present two new algorithms to compute an approximate minimum cycle basis. For any integer k >= 1, we give (2k - 1)-approximation algorithms with expected running time 0(kmn(1+2/k) + mn((1+1/k)(omega-1))) and deterministic running time 0(n(3+2/k)), respectively. Here omega is the best exponent of matrix multiplication. It is presently known that omega < 2.376. Both algorithms are o(m(omega)) for dense graphs. This is the first time that any algorithm which computes sparse cycle bases with a guarantee drops below the Theta(m(omega)) bound. We also present a 2-approximation algorithm with O(m(omega) root n log n) expected running time, a linear time 2-approximation algorithm for planar graphs and an O(n(3)) time 2.42-approximation algorithm for the complete Euclidean graph in the plane.

On the maximal rate of non-square STBCs from complex orthogonal designs

A Linear Processing Complex Orthogonal Design (LPCOD) is a p x n matrix epsilon, (p >= n) in k complex indeterminates x(1), x(2),..., x(k) such that (i) the entries of epsilon are complex linear combinations of 0, +/- x(i), i = 1,..., k and their conjugates, (ii) epsilon(H)epsilon = D, where epsilon(H) is the Hermitian (conjugate transpose) of epsilon and D is a diagonal matrix with the (i, i)-th diagonal element of the form l(1)((i))vertical bar x(1)vertical bar(2) + l(2)((i))vertical bar x(2)vertical bar(2)+...+ l(k)((i))vertical bar x(k)vertical bar(2) where l(j)((i)), i = 1, 2,..., n, j = 1, 2,...,k are strictly positive real numbers and the condition l(1)((i)) = l(2)((i)) = ... = l(k)((i)), called the equal-weights condition, holds for all values of i. For square designs it is known. that whenever a LPCOD exists without the equal-weights condition satisfied then there exists another LPCOD with identical parameters with l(1)((i)) = l(2)((i)) = ... = l(k)((i)) = 1. This implies that the maximum possible rate for square LPCODs without the equal-weights condition is the same as that or square LPCODs with equal-weights condition. In this paper, this result is extended to a subclass of non-square LPCODs. It is shown that, a set of sufficient conditions is identified such that whenever a non-square (p > n) LPCOD satisfies these sufficient conditions and do not satisfy the equal-weights condition, then there exists another LPCOD with the same parameters n, k and p in the same complex indeterminates with l(1)((i)) = l(2)((i)) = ... = l(k)((i)) = 1.

A network representation of protein structures: Implications for protein stability

This study views each protein structure as a network of noncovalent connections between amino acid side chains. Each amino acid in a protein structure is a node, and the strength of the noncovalent interactions between two amino acids is evaluated for edge determination. The protein structure graphs (PSGs) for 232 proteins have been constructed as a function of the cutoff of the amino acid interaction strength at a few carefully chosen values. Analysis of such PSGs constructed on the basis of edge weights has shown the following: 1), The PSGs exhibit a complex topological network behavior, which is dependent on the interaction cutoff chosen for PSG construction. 2), A transition is observed at a critical interaction cutoff, in all the proteins, as monitored by the size of the largest cluster (giant component) in the graph. Amazingly, this transition occurs within a narrow range of interaction cutoff for all the proteins, irrespective of the size or the fold topology. And 3), the amino acid preferences to be highly connected (hub frequency) have been evaluated as a function of the interaction cutoff. We observe that the aromatic residues along with arginine, histidine, and methionine act as strong hubs at high interaction cutoffs, whereas the hydrophobic leucine and isoleucine residues get added to these hubs at low interaction cutoffs, forming weak hubs. The hubs identified are found to play a role in bringing together different secondary structural elements in the tertiary structure of the proteins. They are also found to contribute to the additional stability of the thermophilic proteins when compared to their mesophilic counterparts and hence could be crucial for the folding and stability of the unique three-dimensional structure of proteins. Based on these results, we also predict a few residues in the thermophilic and mesophilic proteins that can be mutated to alter their thermal stability.

BER-optimized linear parallel interference cancellers for multicarrier DS-CDMA systems

In this paper, we consider the design and bit-error performance analysis of linear parallel interference cancellers (LPIC) for multicarrier (MC) direct-sequence code division multiple access (DS-CDMA) systems. We propose an LPIC scheme where we estimate and cancel the multiple access interference (MAT) based on the soft decision outputs on individual subcarriers, and the interference cancelled outputs on different subcarriers are combined to form the final decision statistic. We scale the MAI estimate on individual subcarriers by a weight before cancellation. In order to choose these weights optimally, we derive exact closed-form expressions for the bit-error rate (BER) at the output of different stages of the LPIC, which we minimize to obtain the optimum weights for the different stages. In addition, using an alternate approach involving the characteristic function of the decision variable, we derive BER expressions for the weighted LPIC scheme, matched filter (MF) detector, decorrelating detector, and minimum mean square error (MMSE) detector for the considered multicarrier DS-CDMA system. We show that the proposed BER-optimized weighted LPIC scheme performs better than the MF detector and the conventional LPIC scheme (where the weights are taken to be unity), and close to the decorrelating and MMSE detectors.