Row and column matrices in multiple correspondence analysis with ordered categorical and dichotomous variables

In multiple correspondence analysis, whenever the number of variables exceeds the number of observations, row matrix should be used, but if the number of variables is less than the number of observations column matrix is the suitable procedure to follow. One of the following matrices (rows, columns) leads to loss of information that can be found by the other method, therefore, this paper developed a proposal to overcome this problem, which is: to find a shortcut method allowing the use of the results of one matrix to obtain the results of the other matrix. Taking advantage of all information available, the phenomenon was studied. Some of these results are: Eigenvectors, factor loadings and factor scores based on ordered categorical and dichotomous data. This method is illustrated by using a real data set. Results were obtained by using Minitab program. As a result, it is possible to shortcut transformation between the results of row and column matrices depending on factor loadings and factor scores of the row and column matrices

Numerical modelling of mass transfer for solvent-carbon dioxide system at supercritical (miscible) conditions

A numerical procedure of mathematical model for mass transfer between a droplet of organic solvent and a compressed antisolvent is presented for conditions such that the two phases are fully miscible. The model is applicable to the supercritical antisolvent (SAS) method of particle formation. In this process, solute particles precipitate from an organic solution when sprayed into a compressed antisolvent continuum. Effects of operating temperature and pressure on droplet behavior were examined. The CO2 critical locus and the conditions for which the densities of solvent and carbon dioxide are equal are identified. Calculations were performed using Peng-Robinson equation of state. The model equations were put into the form that allowed the application of the Matlab standard solver pdepe. Calculations with toluene, ethanol, acetone (solvents) and carbon dioxide (antisolvent) demonstrated that droplets swell upon interdiffusion when the solvent is denser than the antisolvent and shrink when the antisolvent is denser. Diffusion modeling results might be used for data interpretation or experiments planning of the more complex real SAS process

Threshold Verification Technique for Network Intrusion Detection System

Internet has played a vital role in this modern world, the possibilities and opportunities offered are limitless. Despite all the hype, Internet services are liable to intrusion attack that could tamper the confidentiality and integrity of important information. An attack started with gathering the information of the attack target, this gathering of information activity can be done as either fast or slow attack. The defensive measure network administrator can take to overcome this liability is by introducing Intrusion Detection Systems (IDSs) in their network. IDS have the capabilities to analyze the network traffic and recognize incoming and on-going intrusion. Unfortunately the combination of both modules in real time network traffic slowed down the detection process. In real time network, early detection of fast attack can prevent any further attack and reduce the unauthorized access on the targeted machine. The suitable set of feature selection and the correct threshold value, add an extra advantage for IDS to detect anomalies in the network. Therefore this paper discusses a new technique for selecting static threshold value from a minimum standard features in detecting fast attack from the victim perspective. In order to increase the confidence of the threshold value the result is verified using Statistical Process Control (SPC). The implementation of this approach shows that the threshold selected is suitable for identifying the fast attack in real time.Comment: 8 Pages, International Journal of Computer Science and Information Securit

Comparison between bayesian structural equation models with ordered categorical data

In this paper, ordered categorical variables are used to compare between linear and nonlinear Bayesian structural equation models, Gibbs Sampling method is applied for estimation and model comparison. Statistical inferences, which involve estimation of parameters and their standard deviations, and residuals analyses for testing the posited model, are discussed. The proposed procedure is illustrated by a simulation data obtained from R program. Data results are obtained from WinBUGS program

Bayesian Analysis of Multiple Group Nonlinear Structural Equation Models with Ordered Categorical and Dichotomous Variables: A Survey

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Advanced Trace Pattern For Computer Intrusion Discovery

The number of crime committed based on the malware intrusion is never ending as the number of malware variants is growing tremendously and the usage of internet is expanding globally. Malicious codes easily obtained and use as one of weapon to gain their objective illegally. Hence, in this research, diverse logs from different OSI layer are explored to identify the traces left on the attacker and victim logs in order to establish worm trace pattern to defending against the attack and help revealing true attacker or victim. For the purpose of this paper, it focused on malware intrusion and traditional worm namely sasser worm variants. The concept of trace pattern is created by fusing the attacker's and victim's perspective. Therefore, the objective of this paper is to propose a general worm trace pattern for attacker's, victim's and multi-step (attacker/victim)'s by combining both perspectives. These three proposed worm trace patterns can be extended into research areas in alert correlation and computer forensic investigation.Comment: IEEE Publication Format, https://sites.google.com/site/journalofcomputing