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Open access

Július Czap, Peter Šugerek, Stanislav Jendrol’ and Juraj Valiska

Abstract

Let G be a plane graph. Two edges are facially adjacent in G if they are consecutive edges on the boundary walk of a face of G. Given nonnegative integers r, s, and t, a facial [r, s, t]-coloring of a plane graph G = (V,E) is a mapping f : VE → {1, . . ., k} such that |f(v 1) − f(v 2)| ≥ r for every two adjacent vertices v 1 and v 2, |f(e 1) − f(e 2)| ≥ s for every two facially adjacent edges e 1 and e 2, and |f(v) − f(e)| ≥ t for all pairs of incident vertices v and edges e. The facial [r, s, t]-chromatic number ̄ χr,s,t(G) of G is defined to be the minimum k such that G admits a facial [r, s, t]-coloring with colors 1, . . ., k. In this paper we show that ̄ χr,s,t(G) ≤ 3r + 3s + t + 1 for every plane graph G. For some triplets [r, s, t] and for some families of plane graphs this bound is improved. Special attention is devoted to the cases when the parameters r, s, and t are small.

Open access

Monika Rosicka

Abstract

For a given graph G = (V;E) and permutation π : VV the prism πG of G is defined as follows: VG) = V (G) ∪ V (G′), where G′ is a copy of G, and E(πG) = E(G) ∪ E(G′) ∪M π, where M π = {uv′ : uV (G); v = π (u)} and v′ denotes the copy of v in G′.

We study and compare the properties of convex and weakly convex dominating sets in prism graphs. In particular, we characterize prism γcon-fixers and -doublers. We also show that the differences γwcon(G) – γwcon(πG) and γwcon (πG) – 2γwcon (G) can be arbitrarily large, and that the convex domination number of πG cannot be bounded in terms of γcon (G).

Open access

George Tambouratzis and Marina Vassiliou

Abstract

The present article describes a novel phrasing model which can be used for segmenting sentences of unconstrained text into syntactically-defined phrases. This model is based on the notion of attraction and repulsion forces between adjacent words. Each of these forces is weighed appropriately by system parameters, the values of which are optimised via particle swarm optimisation. This approach is designed to be language-independent and is tested here for different languages.

The phrasing model’s performance is assessed per se, by calculating the segmentation accuracy against a golden segmentation. Operational testing also involves integrating the model to a phrase-based Machine Translation (MT) system and measuring the translation quality when the phrasing model is used to segment input text into phrases. Experiments show that the performance of this approach is comparable to other leading segmentation methods and that it exceeds that of baseline systems.

Open access

Yang Cao, R. Samidurai and R. Sriraman

Abstract

This paper studies the global asymptotic stability and dissipativity problem for a class of neutral type stochastic Markovian Jump Static Neural Networks (NTSMJSNNs) with time-varying delays. By constructing an appropriate Lyapunov-Krasovskii Functional (LKF) with some augmented delay-dependent terms and by using integral inequalities to bound the derivative of the integral terms, some new sufficient conditions have been obtained, which ensure that the global asymptotic stability in the mean square. The results obtained in this paper are expressed in terms of Strict Linear Matrix Inequalities (LMIs), whose feasible solutions can be verified by effective MATLAB LMI control toolbox. Finally, examples and simulations are given to show the validity and advantages of the proposed results.

Open access

Amnah Nasim, Laura Burattini, Muhammad Faisal Fateh and Aneela Zameer

Abstract

Cases where the derivative of a boundary value problem does not exist or is constantly changing, traditional derivative can easily get stuck in the local optima or does not factually represent a constantly changing solution. Hence the need for evolutionary algorithms becomes evident. However, evolutionary algorithms are compute-intensive since they scan the entire solution space for an optimal solution. Larger populations and smaller step sizes allow for improved quality solution but results in an increase in the complexity of the optimization process. In this research a population-distributed implementation for differential evolution algorithm is presented for solving systems of 2nd-order, 2-point boundary value problems (BVPs). In this technique, the system is formulated as an optimization problem by the direct minimization of the overall individual residual error subject to the given constraint boundary conditions and is then solved using differential evolution in the sense that each of the derivatives is replaced by an appropriate difference quotient approximation. Four benchmark BVPs are solved using the proposed parallel framework for differential evolution to observe the speedup in the execution time. Meanwhile, the statistical analysis is provided to discover the effect of parametric changes such as an increase in population individuals and nodes representing features on the quality and behavior of the solutions found by differential evolution. The numerical results demonstrate that the algorithm is quite accurate and efficient for solving 2nd-order, 2-point BVPs.

Open access

Md Wasiur Rahman, Fatema Tuz Zohra and Marina L. Gavrilova

Abstract

Computational intelligence firmly made its way into the areas of consumer applications, banking, education, social networks, and security. Among all the applications, biometric systems play a significant role in ensuring an uncompromised and secure access to resources and facilities. This article presents a first multimodal biometric system that combines KINECT gait modality with KINECT face modality utilizing the rank level and the score level fusion. For the KINECT gait modality, a new approach is proposed based on the skeletal information processing. The gait cycle is calculated using three consecutive local minima computed for the distance between left and right ankles. The feature distance vectors are calculated for each person’s gait cycle, which allows extracting the biometric features such as the mean and the variance of the feature distance vector. For Kinect face recognition, a novel method based on HOG features has been developed. Then, K-nearest neighbors feature matching algorithm is applied as feature classification for both gait and face biometrics. Two fusion algorithms are implemented. The combination of Borda count and logistic regression approaches are used in the rank level fusion. The weighted sum method is used for score level fusion. The recognition accuracy obtained for multi-modal biometric recognition system tested on KINECT Gait and KINECT Eurocom Face datasets is 93.33% for Borda count rank level fusion, 96.67% for logistic regression rank-level fusion and 96.6% for score level fusion.

Open access

Simone A. Ludwig

Abstract

An intrusion detection system (IDS) is an important feature to employ in order to protect a system against network attacks. An IDS monitors the activity within a network of connected computers as to analyze the activity of intrusive patterns. In the event of an ‘attack’, the system has to respond appropriately. Different machine learning techniques have been applied in the past. These techniques fall either into the clustering or the classification category. In this paper, the classification method is used whereby a neural network ensemble method is employed to classify the different types of attacks. The neural network ensemble method consists of an autoencoder, a deep belief neural network, a deep neural network, and an extreme learning machine. The data used for the investigation is the NSL-KDD data set. In particular, the detection rate and false alarm rate among other measures (confusion matrix, classification accuracy, and AUC) of the implemented neural network ensemble are evaluated.

Open access

Marapureddy Murali Krishna Rao

Abstract

In this paper, we introduce the notion of a Г-field as a generalization of field, study them properties of a Г -field and prove that M is a Г-field if and only if M is an integral, simple and commutative Г-ring.

Open access

Andrzej G. Chmielewski and Marcin Sudlitz

Abstract

Large quantity of sewage sludge originating from wastewater treatment plants is becoming a growing problem from environmental and human health points of view. One of the ways to use sewage sludge is agricultural purpose due to its nutrients and organic matter content, but the condition is that it should be deprived of pathogenic bacteria and parasite egg contamination. Application of ionizing radiation to hygienize sewage sludge can make it appropriate for agricultural use. The process does not require addition of chemicals to sludge; it is environmentally friendly and effective in removal of biological threats. In the past, successful attempts of sewage sludge treatment using ionizing radiation were made. Pilot plants and commercial ones proved that pathogens can be easily removed from sewage sludge by ionizing radiation. The concept of ‘zero energy’ biogas plant is based on the construction of a complex system consisting of biogas plant and electron accelerator in the biofertilizer manufacturing line. Digestate originating from the methane fermentation of sewage sludge is irradiated to remove all pathogens using electron beam from an accelerator powered by electric energy obtained from burning biogas in a cogenerator. The product is a high-quality, biologically safe fertilizer.