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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.

Open access

Dorin Sarafoleanu and Raluca Enache

Abstract

Whiplash syndrome is a quite common pathology and can be defined as a neck injury produced by a sudden acceleration-deceleration, the consequence of which is a sudden forward and backward movement of the head and neck. The main production mechanism is a sudden acceleration-deceleration process that has as a consequence the sudden extension/flexion of the neck. Starting from the many structures involved, the whiplash syndrome is an interdisciplinary challenge (ENT specialist, neurologist, orthopedist, ophthalmologist, psychologist) and can be described by multiple signs and symptoms.

Whiplash syndrome is a complex pathology both through the mechanism of production and symptoms, and through the forensic implications that it has. The interdisciplinary medical collaboration, the implementation of stricter rules on wearing the seat belt and the development by car manufacturers of chairs and head restraints that protect the head and neck of passengers, would be the preventive step in the occurrence and especially the chronicization of these lesions.

Open access

Gašper Rak, Marko Hočevar and Franci Steinman

Abstract

The complexity of flow conditions at junctions amplifies significantly with supercritical flow. It is a pronounced three-dimensional two-phased flow phenomenon, where standing waves with non-stationary water surface are formed. To analyse the hydrodynamic conditions at an asymmetric right-angled junction with incoming supercritical flows at Froude numbers between 2 and 12, an experimental approach was used. For a phenomenological determination of the relations between the integral parameters of incoming flows and the characteristics of standing waves at the junction area, water surface topographies for 168 scenarios at the junction were measured using non-intrusive measurement techniques. The new, phenomenologically derived equations allow for determination of location, height and extent of the main standing waves at the junction. Research results give important information on the processes and their magnitude for engineering applications.