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Title: Web-Based Expert System for Civil Service Regulations: RCSES |
Abstract: Internet and expert systems have offered new ways of sharing and distributing knowledge, but there is a lack of researches in the area of web based expert systems. This paper introduces a development of a web-based expert system for the regulations of civil service in the Kingdom of Saudi Arabia named as RCSE... |
Title: A Binary Control Chart to Detect Small Jumps |
Abstract: The classic N p chart gives a signal if the number of successes in a sequence of inde- pendent binary variables exceeds a control limit. Motivated by engineering applications in industrial image processing and, to some extent, financial statistics, we study a simple modification of this chart, which uses only... |
Title: Sequentially Updated Residuals and Detection of Stationary Errors in Polynomial Regression Models |
Abstract: The question whether a time series behaves as a random walk or as a station- ary process is an important and delicate problem, particularly arising in financial statistics, econometrics, and engineering. This paper studies the problem to detect sequentially that the error terms in a polynomial regression mode... |
Title: Cheating for Problem Solving: A Genetic Algorithm with Social Interactions |
Abstract: We propose a variation of the standard genetic algorithm that incorporates social interaction between the individuals in the population. Our goal is to understand the evolutionary role of social systems and its possible application as a non-genetic new step in evolutionary algorithms. In biological population... |
Title: A New Method to Extract Dorsal Hand Vein Pattern using Quadratic Inference Function |
Abstract: Among all biometric, dorsal hand vein pattern is attracting the attention of researchers, of late. Extensive research is being carried out on various techniques in the hope of finding an efficient one which can be applied on dorsal hand vein pattern to improve its accuracy and matching time. One of the crucia... |
Title: A Topological derivative based image segmentation for sign language recognition system using isotropic filter |
Abstract: The need of sign language is increasing radically especially to hearing impaired community. Only few research groups try to automatically recognize sign language from video, colored gloves and etc. Their approach requires a valid segmentation of the data that is used for training and of the data that is used ... |
Title: A New Image Steganography Based On First Component Alteration Technique |
Abstract: In this paper, A new image steganography scheme is proposed which is a kind of spatial domain technique. In order to hide secret data in cover-image, the first component alteration technique is used. Techniques used so far focuses only on the two or four bits of a pixel in a image (at the most five bits at th... |
Title: ICD 10 Based Medical Expert System Using Fuzzy Temporal Logic |
Abstract: Medical diagnosis process involves many levels and considerable amount of time and money are invariably spent for the first level of diagnosis usually made by the physician for all the patients every time. Hence there is a need for a computer based system which not only asks relevant questions to the patients... |
Title: An Improved Image Mining Technique For Brain Tumour Classification Using Efficient Classifier |
Abstract: An improved image mining technique for brain tumor classification using pruned association rule with MARI algorithm is presented in this paper. The method proposed makes use of association rule mining technique to classify the CT scan brain images into three categories namely normal, benign and malign. It com... |
Title: Reversible jump Markov chain Monte Carlo and multi-model samplers |
Abstract: To appear in the second edition of the MCMC handbook, S. P. Brooks, A. Gelman, G. Jones and X.-L. Meng (eds), Chapman & Hall. |
Title: Likelihood-free Markov chain Monte Carlo |
Abstract: To appear to MCMC handbook, S. P. Brooks, A. Gelman, G. Jones and X.-L. Meng (eds), Chapman & Hall. |
Title: An alternative marginal likelihood estimator for phylogenetic models |
Abstract: Bayesian phylogenetic methods are generating noticeable enthusiasm in the field of molecular systematics. Many phylogenetic models are often at stake and different approaches are used to compare them within a Bayesian framework. The Bayes factor, defined as the ratio of the marginal likelihoods of two competi... |
Title: Cooperative Automated Worm Response and Detection Immune Algorithm |
Abstract: The role of T-cells within the immune system is to confirm and assess anomalous situations and then either respond to or tolerate the source of the effect. To illustrate how these mechanisms can be harnessed to solve real-world problems, we present the blueprint of a T-cell inspired algorithm for computer sec... |
Title: Computer Simulation Study of the Levy Flight Process |
Abstract: Random walk simulation of the Levy flight shows a linear relation between the mean square displacement <r2> and time. We have analyzed different aspects of this linearity. It is shown that the restriction of jump length to a maximum value (lm) affects the diffusion coefficient, even though it remains constant... |
Title: Comparing Simulation Output Accuracy of Discrete Event and Agent Based Models: A Quantitive Approach |
Abstract: In our research we investigate the output accuracy of discrete event simulation models and agent based simulation models when studying human centric complex systems. In this paper we focus on human reactive behaviour as it is possible in both modelling approaches to implement human reactive behaviour in the m... |
Title: Improved estimators for dispersion models with dispersion covariates |
Abstract: In this paper we discuss improved estimators for the regression and the dispersion parameters in an extended class of dispersion models (J\orgensen, 1996). This class extends the regular dispersion models by letting the dispersion parameter vary throughout the observations, and contains the dispersion models ... |
Title: Skewness of maximum likelihood estimators in dispersion models |
Abstract: We introduce the dispersion models with a regression structure to extend the generalized linear models, the exponential family nonlinear models (Cordeiro and Paula, 1989) and the proper dispersion models (J\orgensen, 1997a). We provide a matrix expression for the skewness of the maximum likelihood estimators ... |
Title: DCA for Bot Detection |
Abstract: Ensuring the security of computers is a non-trivial task, with many techniques used by malicious users to compromise these systems. In recent years a new threat has emerged in the form of networks of hijacked zombie machines used to perform complex distributed attacks such as denial of service and to obtain s... |
Title: Biological Inspiration for Artificial Immune Systems |
Abstract: Artificial immune systems (AISs) to date have generally been inspired by naive biological metaphors. This has limited the effectiveness of these systems. In this position paper two ways in which AISs could be made more biologically realistic are discussed. We propose that AISs should draw their inspiration fr... |
Title: Syllable Analysis to Build a Dictation System in Telugu language |
Abstract: In recent decades, Speech interactive systems gained increasing importance. To develop Dictation System like Dragon for Indian languages it is most important to adapt the system to a speaker with minimum training. In this paper we focus on the importance of creating speech database at syllable units and ident... |
Title: Speech Recognition by Machine, A Review |
Abstract: This paper presents a brief survey on Automatic Speech Recognition and discusses the major themes and advances made in the past 60 years of research, so as to provide a technological perspective and an appreciation of the fundamental progress that has been accomplished in this important area of speech communi... |
Title: Application of a Fuzzy Programming Technique to Production Planning in the Textile Industry |
Abstract: Many engineering optimization problems can be considered as linear programming problems where all or some of the parameters involved are linguistic in nature. These can only be quantified using fuzzy sets. The aim of this paper is to solve a fuzzy linear programming problem in which the parameters involved ar... |
Title: The Application of Mamdani Fuzzy Model for Auto Zoom Function of a Digital Camera |
Abstract: Mamdani Fuzzy Model is an important technique in Computational Intelligence (CI) study. This paper presents an implementation of a supervised learning method based on membership function training in the context of Mamdani fuzzy models. Specifically, auto zoom function of a digital camera is modelled using Mam... |
Title: Statistical tests for whether a given set of independent, identically distributed draws does not come from a specified probability density |
Abstract: We discuss several tests for whether a given set of independent and identically distributed (i.i.d.) draws does not come from a specified probability density function. The most commonly used are Kolmogorov-Smirnov tests, particularly Kuiper's variant, which focus on discrepancies between the cumulative distri... |
Title: A Little More, a Lot Better: Improving Path Quality by a Simple Path Merging Algorithm |
Abstract: Sampling-based motion planners are an effective means for generating collision-free motion paths. However, the quality of these motion paths (with respect to quality measures such as path length, clearance, smoothness or energy) is often notoriously low, especially in high-dimensional configuration spaces. We... |
Title: Dendritic Cells for Real-Time Anomaly Detection |
Abstract: Dendritic Cells (DCs) are innate immune system cells which have the power to activate or suppress the immune system. The behaviour of human of human DCs is abstracted to form an algorithm suitable for anomaly detection. We test this algorithm on the real-time problem of port scan detection. Our results show a... |
Title: Dendritic Cells for Anomaly Detection |
Abstract: Artificial immune systems, more specifically the negative selection algorithm, have previously been applied to intrusion detection. The aim of this research is to develop an intrusion detection system based on a novel concept in immunology, the Danger Theory. Dendritic Cells (DCs) are antigen presenting cells... |
Title: An Explicit Nonlinear Mapping for Manifold Learning |
Abstract: Manifold learning is a hot research topic in the field of computer science and has many applications in the real world. A main drawback of manifold learning methods is, however, that there is no explicit mappings from the input data manifold to the output embedding. This prohibits the application of manifold ... |
Title: Sparsity-accuracy trade-off in MKL |
Abstract: We empirically investigate the best trade-off between sparse and uniformly-weighted multiple kernel learning (MKL) using the elastic-net regularization on real and simulated datasets. We find that the best trade-off parameter depends not only on the sparsity of the true kernel-weight spectrum but also on the ... |
Title: Analytical shape determination of fiber-like objects with Virtual Image Correlation |
Abstract: This paper reports a method allowing for the determination of the shape of deformed fiber-like objects. Compared to existing methods, it provides analytical results including the local slope and curvature which are of first importance, for instance, in beam mechanics. The presented VIC (Virtual Image Correlat... |
Title: Detecting Botnets Through Log Correlation |
Abstract: Botnets, which consist of thousands of compromised machines, can cause significant threats to other systems by launching Distributed Denial of Service (SSoS) attacks, keylogging, and backdoors. In response to these threats, new effective techniques are needed to detect the presence of botnets. In this paper, ... |
Title: Relaxation Penalties and Priors for Plausible Modeling of Nonidentified Bias Sources |
Abstract: In designed experiments and surveys, known laws or design feat ures provide checks on the most relevant aspects of a model and identify the target parameters. In contrast, in most observational studies in the health and social sciences, the primary study data do not identify and may not even bound target para... |
Title: Longitudinal Data with Follow-up Truncated by Death: Match the Analysis Method to Research Aims |
Abstract: Diverse analysis approaches have been proposed to distinguish data missing due to death from nonresponse, and to summarize trajectories of longitudinal data truncated by death. We demonstrate how these analysis approaches arise from factorizations of the distribution of longitudinal data and survival informat... |
Title: Kernel machines with two layers and multiple kernel learning |
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