Utilising semantic technologies for intelligent indexing and retrieval of digital images

The proliferation of digital media has led to a huge interest in classifying and indexing media objects for generic search and usage. In particular, we are witnessing a colossal growth in digital image repositories that are difficult to navigate using free-text search mechanisms, which often return inaccurate matches as they in principle rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this paper we present a semantically-enabled image annotation and retrieval engine that is designed to satisfy the requirements of the commercial image collections market in terms of both accuracy and efficiency of the retrieval process. Our search engine relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. We also show how our well-analysed and designed domain ontology contributes to the implicit expansion of user queries as well as the exploitation of lexical databases for explicit semantic-based query expansion.     

Graphic approach for the determination of the existence of sequences guaranteeing observability of switched linear systems

This paper deals with the design of sequences allowing the observability of the state of a switched linear system. The proposed method, based on a graph-theoretic approach, needs only the knowledge of the system’s structure. The necessary and sufficient conditions for the existence of at least one switching sequence guaranteeing the observability of a switched structured system are provided. Such conditions are particularly intuitive and they can be implemented with classic algorithms of the graph theory.     

Passivation and pitting corrosion of nanostructured Sn-Ni alloy in NaCl solutions

The passivation and pitting corrosion of tin-nickel alloy (34% Ni-66% Sn) in NaCl solution was studied using potentiodynamic, cyclic voltammetry and electrochemical impedance spectroscopy (EIS) techniques complemented by X-ray diffraction (XRD) and scanning electron microscopy (SEM). The effect of concentration of the chloride ion, the switching potential, scans rate and pH on the electrochemical behavior of Sn-Ni alloy is discussed. The data indicate that the corrosion rate and the pitting corrosion of Sn-Ni alloy increases by the increasing of chloride ion concentration. The observed corrosion resistance of electrodeposited Sn-Ni alloy is due to the formation of a thin passive film from tin and nickel oxides.     

Rheology of poly(n‐butyl methacrylate) and its composites with calcium carbonate

Poly(n‐butyl methacrylate) (PBMA) composites with calcium carbonate (CaCO₃) were prepared by in situ radical copolymerization of butyl methacrylate (BMA) and methacrylic acid (MA) with precipitated calcium carbonate. To compare the different rheological behaviors of the monomer mixtures with CaCO₃ and the composites, the steady and dynamic viscosities of BMA/MA/CaCO₃ and poly(BMA/MA/CaCO₃) were measured by means of steady and oscillatory shear flows. The viscosity of the mixture BMA/MA/CaCO₃ was found to increase evidently with the increasing of CaCO₃%. The influence of MA% on viscosity of BMA/MA/CaCO₃ was slight. During the in situ polymerization, the viscosity of the reacting system was measured to be enhanced by a factor of about 10⁴ from the monomer/CaCO₃ mixture to composites. The dependency of zero‐shear viscosity on molar mass of PBMA was also investigated. The relation between the zero‐shear viscosity and molar mass is η₀ = 10^?15 M_w^3.5. The evolution of the viscosity with the temperature for both PBMA and its composites was obtained and time–temperature superposition was used to build master curves for the dynamic moduli. The flow activation energies were found to be 115.0, 148.6, and 178.7 kJ/mol for PBMA, composite PBMA/CaCO₃ (90/10), and PBMA/MA/CaCO₃ (89/1/10), respectively. The viscosity of the composites containing less than 10% CaCO₃ was lower than that of pure PBMA with the same molar mass. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 88: 1376–1383, 2003     

Geological Engineering,Civil Engineering,Traffic and Transportation Engineering Electrical capacitance volume tomography for measurement soil water infiltration in vessel experiments简

Electrical capacitance volume tomography （ECVT） is a recently-developed technique for real-time, non-invasive 3D monitoring of processes involving materials with strong contrasts in dielectric permittivity. This work is first application of the method to visualization of water flow in soil. We describe the principles behind the method, and then demonstrate its use with a simple laboratory infiltration experiment. 32 ECVT sensors were installed on the sides of an empty PVC column. Water was poured into the column at a constant rate, and ECVT data were collected every second. The column was then packed with dry sand and again supplied with water at a constant rate with data collected every second. Data were analyzed to give bulk average water contents, which proved consistent with the water supply rates. Data were also analyzed to give 3D images （216 voxels） allowing visualization of the water distribution during the experiments. Result of this work shows that water infiltration into the soil, wall flow, progress of the unstable wetting front and the final water distribution are clearly visible.     

Effect of pH and zeta potential of Pickering stabilizing magnetite nanoparticles on the features of magnetized polystyrene microspheres

Styrene as a monomer was emulsified in water using several magnetite nanoparticles concentration and pH values. Emulsified styrene drops were used as templates for polymerization, in presence of water soluble free radical initiator, and formation of composite particles. Styrene template drops stabilization was verified by light as well as scanning electron microscopy imaging, which ensured the participation of the particles in building up a mechanical barrier to stop oil drops coalescence. Furthermore, the produced polystyrene composites were strongly attracted to an external magnet. The difference in particles size as a function of pH was elucidated using zeta potential measurements, which indicated dominance of pH on the hydrophilicity of the particles and consequently the extent of emulsification, which in turn affected the size of the obtained microspheres. Under some circumstances, capsules were formed instead of particles. Thereby, it can be concluded that the magnetic microspheres are optimally formed at pH 2.3 independently of the magnetite content used.     

Detection of Abnormal Activities from Various Signals Based on Statistical Analysis

We perceive big data with massive datasets of complex and variegated structures in the modern era. Such attributes formulate hindrances while analyzing and storing the data to generate apt aftermaths. Privacy and security are the colossal perturb in the domain space of extensive data analysis. In this paper, our foremost priority is the computing technologies that focus on big data, IoT (Internet of Things), Cloud Computing, Blockchain, and fog computing. Among these, Cloud Computing follows the role of providing on-demand services to their customers by optimizing the cost factor. AWS, Azure, Google Cloud are the major cloud providers today. Fog computing offers new insights into the extension of cloud computing systems by procuring services to the edges of the network. In collaboration with multiple technologies, the Internet of Things takes this into effect, which solves the labyrinth of dealing with advanced services considering its significance in varied application domains. The Blockchain is a dataset that entertains many applications ranging from the fields of crypto-currency to smart contracts. The prospect of this research paper is to present the critical analysis and review it under the umbrella of existing extensive data systems. In this paper, we attend to critics' reviews and address the existing threats to the security of extensive data systems. Moreover, we scrutinize the security attacks on computing systems based upon Cloud, Blockchain, IoT, and fog. This paper lucidly illustrates the different threat behaviour and their impacts on complementary computational technologies. The authors have mooted a precise analysis of cloud-based technologies and discussed their defense mechanism and the security issues of mobile healthcare.

     

Reference Range Estimation: Accounting for Measurement System Errors

Reference range is a statistic that is used in health related fields to represent the range of the most likely values for a variable of interest. Based on this range, individuals are classified as being healthy or unhealthy. In biostatistics, the reference range is calculated as the (1 ? α)% prediction interval, where this prediction interval is based on the estimated population variance from the data. Such estimation of population variance is not precise, because obtained test results do usually have errors associated with them. These errors are due to the imprecise test procedure or gauge used. In this paper, the total variability in the data is decomposed into two categories. The first is the patient‐to‐patient variability and the other is the variability due to the measurement system used. Estimation of the two kinds is performed through a gauge repeatability and reproducibility study, then the reference range is calculated, taking into account only the patient‐to‐patient variability. The revised reference range procedure is illustrated through a case study of vitamin B12 test results. A closed form formula is given to calculate the probability of a given test result being within the revised reference range. Copyright © 2015 John Wiley & Sons, Ltd.     

ARO: A new model free optimization algorithm for real time applications inspired by the asexual reproduction

This paper presents a new individual based optimization algorithm, which is inspired from asexual reproduction known as a remarkable biological phenomenon, called as asexual reproduction optimization (ARO). ARO can be essentially considered as an evolutionary based algorithm that mathematically models the budding mechanism of asexual reproduction. In ARO, a parent produces a bud through a reproduction operator; thereafter the parent and its bud compete to survive according to a performance index obtained from the underlying objective function of the optimization problem; this leads to the fitter individual. ARO adaptive search ability along with its strength and weakness points are fully described in the paper. Furthermore, the ARO convergence to the global optimum is mathematically analyzed. To approve the effectiveness of the ARO performance, it is tested with several benchmark functions frequently used in the area of optimization. Finally, the ARO performance is statistically compared with that of an improved genetic algorithm (GA). Results of simulation illustrate that ARO remarkably outperforms GA.     

Combining docking, scoring and molecular field analyses to probe influenza neuraminidase-ligand interactions

In this project, several docking conditions, scoring functions and corresponding protein-aligned molecular field analysis (CoMFA) models were evaluated for a diverse set of neuraminidase (NA) inhibitors. To this end, a group of inhibitors were docked into the active site of NA. The docked structures were utilized to construct a corresponding protein-aligned CoMFA models by employing probe-based (H+, OH, CH3) energy grids and genetic partial least squares (G/PLS) statistical analysis. A total of 16 different docking configurations were evaluated, of which some succeeded in producing self-consistent and predictive CoMFA models. However, the best model coincided with docking the ionized ligands into the hydrated form of the binding site via PLP1 scoring function (r2LOO=0.735, r2PRESS against 24 test compounds=0.828). The highest-ranking CoMFA models were employed to probe NA-ligand interactions. Further validation by comparison with a co-crystallized ligand-NA crystallographic structure was performed. This combination of docking/scoring/CoMFA modeling provided interesting insights into the binding of different NA inhibitors.