The use of natural (Pinus pinaster) resin in the production of printing ink and the printability effect

Alkyd resins are generally used in the production of printing inks. All industries look for alternative raw materials in the production of ink with the growing inclination toward using natural products. Resins forming the vehicle of the ink to be obtained from natural resources will provide benefits for the environment, nature, and living creatures. The aim of the study was to promote the use of natural resin in the ink system. Natural Pinus pinaster resin was added into vegetable and mineral oil-based solvents in pure form with alkyd resin in different amounts and ink varnishes of different combinations were prepared. Then, printing inks were produced from these varnishes in pure and hybrid form. Following the assessment of the rheological properties of the inks prepared, printing tests were conducted to assess the printing quality parameters. Ideal mixing ratios of the natural resins in the ink were determined for printability. The environmental importance and advantages of the use of natural resins were discussed. Recommendations were given in line with the results to encourage widespread use of natural resins in near future.     

Electrochemical mass transfer between an impinging jet and a rotating disk in a confined system

This paper presents the mass transfer results from an impinging liquid jet to a rotating disk. The mass transfer coefficients were measured using the electrochemical limiting diffusion current technique (ELDCT). Rotational Reynolds number (Re_r) in the range of 3.4 × 10⁴–1.2 × 10⁵, jet Reynolds number (Re_j) 1.7 × 10⁴–5.3 × 10⁴ and non-dimensional jet-to-disk spacing (H/d) 2–8 were taken into consideration as parameters. It was found that the jet impingement resulted in a substantial enhancement in the mass transfer compared to the case of the rotating disk without jet.     

Cellular neural network with trapezoidal activation function

This paper presents a cellular neural network (CNN) scheme employing a new non‐linear activation function, called trapezoidal activation function (TAF). The new CNN structure can classify linearly non‐separable data points and realize Boolean operations (including eXclusive OR) by using only a single‐layer CNN. In order to simplify the stability analysis, a feedback matrix W is defined as a function of the feedback template A and 2D equations are converted to 1D equations. The stability conditions of CNN with TAF are investigated and a sufficient condition for the existence of a unique equilibrium and global asymptotic stability is derived. By processing several examples of synthetic images, the analytically derived stability condition is also confirmed. Copyright © 2005 John Wiley & Sons, Ltd.     

Locational analysis for regionalization of Turkish Red Crescent blood services

After a series of earthquakes in 1999, Turkish Red Crescent (TRC) has engaged in a restructuring for all of its activities, including the blood services. Our study on the blood management system had been started as part of this initiative to restructure the blood services and improve both their effectiveness and efficiency. In the current system of TRC, not much consideration has been given to how the locational decisions affect the performance of blood centers, stations and mobile units. In recent years, however, there has been much discussion regarding the regionalization of the blood management system in Turkey. In this study, we develop several mathematical models to solve the location–allocation decision problems in regionalization of blood services. We report our computational results, obtained by using real data, for TRC blood services.     

A new deep intuitionistic fuzzy time series forecasting method based on long short-term memory

The Journal of Supercomputing - In recent years, deep artificial neural networks can have better forecasting performance than many other artificial neural networks. The long short-term memory...     

Prediction of software vulnerability based deep symbiotic genetic algorithms: Phenotyping of dominant-features

The detection of software vulnerabilities is considered a vital problem in the software security area for a long time. Nowadays, it is challenging to manage software security due to its increased complexity and diversity. So, vulnerability detection applications play a significant part in software development and maintenance. The ability of the forecasting techniques in vulnerability detection is still weak. Thus, one of the efficient defining features methods that have been used to determine the software vulnerabilities is the metaheuristic optimization methods. This paper proposes a novel software vulnerability prediction model based on using a deep learning method and SYMbiotic Genetic algorithm. We are first to apply Diploid Genetic algorithms with deep learning networks on software vulnerability prediction to the best of our knowledge. In this proposed method, a deep SYMbiotic-based genetic algorithm model (DNN-SYMbiotic GAs) is used by learning the phenotyping of dominant-features for software vulnerability prediction problems. The proposed method aimed at increasing the detection abilities of vulnerability patterns with vulnerable components in the software. Comprehensive experiments are conducted on several benchmark datasets; these datasets are taken from Drupal, Moodle, and PHPMyAdmin projects. The obtained results revealed that the proposed method (DNN-SYMbiotic GAs) enhanced vulnerability prediction, which reflects improving software quality prediction.

     

Corrosion inhibition of stainless steel by polyaniline,poly(2-chloroaniline), and poly(aniline-co-2-chloroaniline) in HCl

Polyaniline (PANi), poly(2-chloroaniline) (PClANi), and poly(aniline-co-2-chloroaniline) (co-PClANi) films were synthesized by electrochemical deposition on 304-stainless steel (SS) from an acetonitrile solution. The structural properties of these polymer films were characterized by spectroscopic (FTIR and UV–vis) and electrochemical (cyclic voltammetry) methods. Open circuit potential–time (E_ocp–time) curves, potentiodynamic polarization, and electrochemical impedance (EIS) measurements showed that these films have significant protective performance against corrosion of SS in 0.5 M HCl solution. It was found that co-PClANi film has acted as a passivator as well as barrier for cathodic reduction reaction in a similar manner as PANi film. However, PClANi film has behaved only as barrier for corrosion protection of SS in 0.5 M HCl.