Application of water cumulative charges as a water spouts for intensive flame extinguishing

Shape cumulative charge is a set of explosive components that uses directional energy accumulation. The water cumulative charges are filled with water, which forms a water-directed beam that has the ability to effectively counteract the intense flame that is induced by gaseous flammable gas or liquid from the damaged gas duct and extinguishes it. Study contains description of the experimentally constructed cumulative charge as well as the analysis of results of experiments carried out in real conditions. Based on the facts gained from the experiments we can conclude that the cumulative water charge has a significant potential and possibilities to extinguish an intense flame.Web of Science68326426

Controlling a mobile robot with a biological brain

The intelligent controlling mechanism of a typical mobile robot is usually a computer system. Some recent research is ongoing in which biological neurons are being cultured and trained to act as the brain of an interactive real world robot�thereby either completely replacing, or operating in a cooperative fashion with, a computer system. Studying such hybrid systems can provide distinct insights into the operation of biological neural structures, and therefore, such research has immediate medical implications as well as enormous potential in robotics. The main aim of the research is to assess the computational and learning capacity of dissociated cultured neuronal networks. A hybrid system incorporating closed-loop control of a mobile robot by a dissociated culture of neurons has been created. The system is flexible and allows for closed-loop operation, either with hardware robot or its software simulation. The paper provides an overview of the problem area, gives an idea of the breadth of present ongoing research, establises a new system architecture and, as an example, reports on the results of conducted experiments with real-life robots

Predicting software faults in large space systems using machine learning techniques

Recently, the use of machine learning (ML) algorithms has proven to be of great practical value in solving a variety of engineering problems including the prediction of failure, fault, and defect-proneness as the space system software becomes complex. One of the most active areas of recent research in ML has been the use of ensemble classifiers. How ML techniques (or classifiers) could be used to predict software faults in space systems, including many aerospace systems is shown, and further use ensemble individual classifiers by having them vote for the most popular class to improve system software fault-proneness prediction. Benchmarking results on four NASA public datasets show the Naive Bayes classifier as more robust software fault prediction while most ensembles with a decision tree classifier as one of its components achieve higher accuracy rates

Verification of the efficacy of the special water shaped charge prototype

On the basis of an analysis of terrorist attacks carried out worldwide, where in recent years a preference for the use of bulk explosives placed in vehicles prevails, effective protection against these malicious explosive-containing systems that have a single goal - to cause death and significant material damage in a large radius is dealt. These improvised explosive devices are, in pyrotechnical terms, ranked as one of the most effective weapons, with a highly destructive character of explosive effect. A special water shaped charge that is able to destructively disassemble a bomb without initiation has been developed as an effective invasive means of eliminating similarly designed terrorist explosives hidden in cars, a condition which allows for considerable variation in location.Web of Science65536636

High dynamic range color image enhancement using fuzzy logic and bacterial foraging

High dynamic range images contain both the underexposed and the overexposed regions. The enhancement of the underexposed and the overexposed regions is the main concern of this paper. Two new transformation functions are proposed to modify the fuzzy membership values of under and the overexposed regions of an image respectively.For the overexposed regions, a rectangular hyperbolic function is used while for the underexposed regions, an S-function is applied. The shape and range of these functions can be controlled by the parameters involved, which are optimized using the bacterial foraging optimization algorithm so as to obtain the enhanced image. The hue, saturation, and intensity (HSV) color space is employed for the purpose of enhancement, where the hue component is preserved to keep the original color composition intact. This approach is applicable to a degraded image of mixed type. On comparison, the proposed transforms yield better results than the existing transformation functions17 for both the underexposed and the overexposed regions

Digital Watermarking Security

As creative works (e.g. books, films, music, photographs) become increasingly available in digital formats in a highly connected world, it also becomes increasingly difficult to secure intellectual property rights. Digital watermarking is one potential technology to aid intellectual property owners in controlling and tracking the use of their works. Surveys the state of digital watermarking research and examines the attacks that the technology faces and how it fares against them. Digital watermarking is an inherently difficult design problem subject to many constraints. The technology currently faces an uphill battle to be secure against relatively simple attacks

Automatic selection of initial points for exploratory vessel tracing in fluoroscopic images

Automatic extraction of vessel centerlines has been an essential process in most of the image guided diagnosis and therapy applications. Among a considerable number of methods, direct exploratory tracing method is known to be an efficient solution for reliable extraction of vessel features from two-dimensional fluoroscopic images. The first step of most automatic exploratory tracing algorithms is collecting a number of candidate initial seed points and their initial tracing directions. To detect reliable initial points, a validation step is required to filter out the false candidates and avoid unnecessary tracing. Staring from reliable initial points, the algorithm efficiently extracts the centerline points along the initial direction until certain pre-defined criteria are satisfied. However, most of these algorithms suffer from incomplete results due to inappropriate selection of the initial seed points. The conventional seed point selection algorithms either rely merely on signal-to-noise ratio analysis, which results in a large number of false traces, or impose a set of strict geometrical validation rules that lead to more false negatives and require more computation time. This paper presents a new method for efficient selection of initial points for exploratory tracing algorithms. The proposed method improves the performance upon existing methods by employing a combination of geometrical and intensity-based approaches

Chemical Characterisation of Bulk and Melt-spun Ribbons of NiMnIn alloy using Inductively Coupled Plasma Optical Emission Spectrometry

Method development for the analysis of NiMnIn, a new magnetocaloric effect (MCE) material using inductively coupled plasma optical emission spectrometry (ICPOES) is discussed. Spectral interference of Ni and Mn on the analysis of In were studied. The process of method validation was carried out using various analytical techniques like conventional wet chemical techniques and instrumental techniques such as atomic absorption spectrometry. All the techniques show a close agreement in values, thus this method could be applied for regular analysis of NiMnIn alloys. A comparative chemical analysis of bulk and melt-spun ribbons of this alloy is also discussed.Defence Science Journal, 2011, 61(3), pp.270-274, DOI:http://dx.doi.org/10.14429/dsj.61.39

Radar Cross-section Measurement Techniques

Radar cross-section (RCS) is an important study parameter for defence applications specially dealing with airborne weapon system. The RCS parameter guides the detection range for a target and is therefore studied to understand the effectiveness of a weapon system. It is not only important to understand the RCS characteristics of a target but also to look into the diagnostic mode of study where factors contributing to a particular RCS values are studied. This further opens up subject like RCS suppression and stealth. The paper discusses the RCS principle, control, and need of measurements. Classification of RCS in terms of popular usage is explained with detailed theory of RF imaging and inverse synthetic aperture radar (ISAR). The various types of RCS measurement ranges are explained with brief discussion on outdoor RCS measurement range. The RCS calibration plays a critical role in referencing the measurement to absolute values and has been described.The RCS facility at Reseach Centre Imarat, Hyderabad, is explained with some details of different activities that are carried out including RAM evaluation, scale model testing, and diagnostic imaging.Defence Science Journal, 2010, 60(2), pp.204-212, DOI:http://dx.doi.org/10.14429/dsj.60.34

Content-based Image Retrieval by Information Theoretic Measure

Content-based image retrieval focuses on intuitive and efficient methods for retrieving images from databases based on the content of the images. A new entropy function that serves as a measure of information content in an image termed as 'an information theoretic measure' is devised in this paper. Among the various query paradigms, 'query by example' (QBE) is adopted to set a query image for retrieval from a large image database. In this paper, colour and texture features are extracted using the new entropy function and the dominant colour is considered as a visual feature for a particular set of images. Thus colour and texture features constitute the two-dimensional feature vector for indexing the images. The low dimensionality of the feature vector speeds up the atomic query. Indices in a large database system help retrieve the images relevant to the query image without looking at every image in the database. The entropy values of colour and texture and the dominant colour are considered for measuring the similarity. The utility of the proposed image retrieval system based on the information theoretic measures is demonstrated on a benchmark dataset.Defence Science Journal, 2011, 61(5), pp.415-430, DOI:http://dx.doi.org/10.14429/dsj.61.117