PiSHi: click the images and I tell if you are a human

This paper introduces pictorial intelligent system for human identification (PiSHi), an image-based captcha which uses three human cognitive abilities to distinguish humans from machines. The first is the human ability to easily recognise the image’s upright orientation. The second is the human brain’s ability in recognising a picture’s content when it is only partially visible. And the third is the human ability in unconscious decision making when encountering pictorial challenges. This work models such complicated human patterns in problem solving for the first time. In order to extract these behavioural patterns and save them in a pattern database, we have implemented our own captcha and performed a series of experiments. PiSHi’s interface presents the user with a set of distorted pictures and asks her to click on the upright orientation of all the pictures in any preferred order. Next, it captures the user’s interaction patterns, compares them with the ones saved in the pattern database, and grants her a corresponding credit. Based on this credit, the user either passes or fails the test, and participates in updating the picture database. Our experiments indicate that human users can solve our proposed captcha effectively—with an accuracy of 99.44 %. Besides, our proposed system is secure against several types of attacks including random guessing and reverse image search engines. The results offer the possibility of utilising the identified human behavioural models in practical captchas.     

Phase Separation and Spatial Morphology in Sodium Silicate Glasses by AFM,Light Scattering and NMR

The morphological and structural properties of sodium silicate (Na₂O–SiO₂) glasses were analyzed using atomic force microscopy (AFM) and light scattering following thermal treatments. AFM observations indicated that the glass surface microstructure evolves during the phase separation mechanisms from continuous interpenetrating phases in the spinodal decomposition process to separated droplets embedded in a continuous matrix for the nucleation/growth one. Raman mapping gave evidence of a phase separation through the nucleation/growth process with formation of silica‐rich clusters characterized by higher polymerization degree as separate droplets. The variations in inhomogeneities versus temperature investigated by Brillouin are exponential for spinodal decomposition and linear in the case of nucleation/growth mechanism. Nuclear magnetic resonance spectroscopy was used to investigate the spatial distribution of the various Q_n species present in thermally treated glasses and allows determining fractal dimension between two and three.     

Accurate analysis of spectral regrowth of nonlinear power amplifier driven by cyclostationary modulated signals

In this paper we present an exact analytical expression to calculate the spectral regrowth at the output of a nonlinear power amplifier (PA) using the higher order cumulants and Poisson summation formula. This PA is driven by the filtered digitally modulated signals. To improve the accuracy of the calculations, the cyclosationarity of the input signal is considered. Moreover, closed-form expressions for the 1-dB compression and saturation points are extracted as a function of the PA model parameters, higher order statistics of the input signal, and the transfer function of the pulse shaping filter. In addition, an analytical expression for the adjacent channel power (ACP) and a closed-form expression of the ACP ratio are derived. This is followed by investigation of the effect of the PA nonlinearity on the performance of receiver. Simulation studies are carried out to verify the accuracy of the derived expressions. Excellent agreement between the analytical and simulation results is achieved.     

An integrated supervised learning solution for monitoring process mean vector

When an out-of-control condition is detected by a control chart, a search begins to identify and eliminate the source(s) of the signal. Identification of the time when a process first changed is an important step in root cause analysis which helps a process engineer to eliminate the source(s) of assignable cause effectively. The time when a change takes place in the process is referred to as the change point. In multivariate environment, since there is more than one variable involved, then root cause analysis is relatively harder compared to the case of univariate because it is not clear exactly which variable has contributed to the out-of-control condition and in what direction its mean has shifted. Hence, a procedure that identifies the change point, performs diagnostic analysis, and specifies the direction of the shift in the mean of the contributing variable(s) all simultaneously could help to conduct root cause analysis effectively. Although different multivariate methods exist in the literature that allow to either estimate change point in the process mean vector or identify the contributing variables leading to the out-of-control condition, but in this research, an integrated supervised learning solution is proposed, which helps to (1) detect of an out-of-control condition, (2) identify the change point leading to shift in the mean vector, (3) specify the variable(s) contributing to the out-of-condition, and (4) identify the direction of the shift in the mean of each contributing variable simultaneously. A real case study is used to evaluate and compare the performance of the proposed integrated approach to existing methods in the literature.     

Natural Vibrations of Open-Variable Thickness Circular Cylindrical Shells in High Temperature Field

The feasibility of using the transfer matrix method (TMM) to analyze open-variable thickness circular cylindrical shells exposed to a high-temperature field is explored theoretically. In the approach to the problem, the thermal degradation (TG) of thermoelastic characteristics of the material is considered. Natural frequencies and mode shapes for the cylindrical shells are investigated in detail by combining the vibration theory with the TMM. The governing equations of vibration for this system are expressed by the matrix differential equations, and the coefficient matrices are derived. After the relationship between the transfer matrix and the coefficient matrix is established, the fourth-order Runge-Kutta method is used numerically to solve the matrix equation. Once the transfer matrix of single component has been obtained, the product of each component matrix can compose the matrix of the entire structure. The frequency equations and mode shape are formulated in terms of the elements of the structural matrices. Finite-element numerical simulation has validated the present formulas of natural frequencies. Numerical illustrations, supplying pertinent information on the implications of the TG, are presented for various curvatures, aspect ratios, boundary conditions, and thickness ratios, and the pertinent conclusions are outlined.     

Thermocatalytic decomposition of methane using activated carbon: Studying the influence of process parameters using factorial design

The thermocatalytic decomposition of methane over activated carbon (AC) is proposed as a potential alternative for the production of hydrogen. The experiments were divided into two parts; the first part was conducted using thermogravimetric analyzer (TGA) while the second part was conducted in a bench-scale unit. For the first part, the research objective is to study the main and interaction effects of decomposition temperature (800-950 °C) and methane partial pressure (0.03-0.63 atm) on the initial specific rate of carbon formation by using statistical method. The experiments were carried out as a general full factorial design consisting of 20 experiments. Quadratic model was developed for initial specific rate of carbon formation in term of temperature and methane partial pressure using response surface methodology. The model’s results show that not only the effects of the main parameters are important, but also the interaction effects between them are significant. For the second part, the main effects of decomposition temperature (775-850 °C) and AC weight (20-120 g) on the initial rate of methane decomposition by using the analysis of variance (ANOVA) were investigated. The results showed that AC weight has higher mean effects than decomposition temperature on the initial rate of methane decomposition.     

Preparation and properties of probiotic concentrated yoghurt (labneh) fortified with conjugated linoleic acid

Milk of high conjugated linoleic acid (CLA) level (1.25 g per 100 g milk fat) was produced by inclusion of fish oil and rousted soy bean in the ration of Holstein cows as compared to 0.55 g per 100 g milk fat in the milk of animals receiving control diet. Milk of normal (control) and high CLA content (treatment) was spray‐dried. Labneh was made from 20 g L^?1 reconstituted milk using 3 mL per 100 mL yoghurt starter and 2 mL per 100 mL of probiotic cultures of Lactobacillus casei or Lactobacillus acidophilus. The control (C) and high CLA (T) labneh were analysed chemically and microbiologically, and their viscosities were determined during cold storage for 15 days. The fat content of labneh of high CLA was less than that of the control, but the total solids (TS) were unaffected by the CLA level. Labneh made with Lb. acidophilus had lower TS and higher acidity, exopolysaccharides and acetaldehyde contents and viscosity than that made with the use of Lb. casei. Labneh from the different treatments retained high counts of the added probiotic (>10⁸ cfu g^?1) throughout the storage period. The storage period had significant effects on all parameters determined.     

Combined cross-linking treatments of bovine serum albumin gel beadlets for controlled-delivery of caffeine

Combined cross-linking agents (CCLA) of microbial transglutaminase (MTgase) and ribose were applied during production of bovine serum albumin gels via incubation and heating treatment, respectively. CCLA produced stronger gels with lower protein solubility in disruptive solvents (1% sodium dodecyl sulphate plus 1% β-mercaptoethanol) as compared to BSA gels (BSA/Control) or gels produced using single cross-linking agents (SCLA) of MTGase or ribose. The gels were then converted into dried beadlets containing caffeine following a freeze-drying process. In-vitro controlled-release of caffeine and swelling ratio studies of the beadlets in artificial saliva or simulated gastric fluid indicated that CCLA beadlets had the slowest release of caffeine and the lowest swelling ratio as compared to other beadlets. Scanning electron microscopy (SEM) data suggested that the improved release and the lower swelling ratio were mainly due to the denser network formed within the CCLA beadlets that had restricted the diffusion of caffeine and hampered the enzymatic breakdown of the matrix. The additional protein cross-linkings formed as a result of MTgase incubation and ribose-induced Maillard reaction could provide a delay action in releasing caffeine that potentially extend the duration of the action of the drug during ingestion.