Application of GA-Optimized ANNs to Predict the Water Content,CO2 and H2S Absorption Capacity of Diethanolamine (DEA) in Khangiran Gas Sweetening Plant

Theoretical Foundations of Chemical Engineering - In this work, with the aim of accurate prediction of water content, H2S and CO2 absorption capacity of diethanolamine (DEA) solvent in Khangiran...     

A new method for detecting various variants of GoF design patterns using conceptual signatures

Software design patterns are well-known solutions for solving commonly occurring problems in software design. Detecting design patterns used in the code can help to understand the structure and behavior of the software, evaluate the quality of the software, and trace important design decisions. To develop and maintain a software system, we need sufficient knowledge of design decisions and software implementation processes. However, the acquisition of knowledge related to design patterns used in complex software systems is a challenging, time-consuming, and costly task. Therefore, using a suitable method to detect the design patterns used in the code reduces software development and maintenance costs. In this paper, we proposed a new method based on conceptual signatures to improve the accuracy of design pattern detection. So we used the conceptual signatures based on the purpose of patterns to detect the patterns’ instances that conform to the standard structure of patterns, and cover more instances of patterns’ variants and implementation versions of the patterns and improve the accuracy of pattern detection. The proposed method is a specific process in two main phases. In the first phase, the conceptual signature and detection formula for each pattern is determined manually. Then in the second phase, each pattern in the code is detected in a semi-automatic process using the conceptual signature and pattern detection formula. To implement the proposed method, we focused on GoF design patterns and their variants. We evaluated the accuracy of our proposed method on five open-source projects, namely, Junit v3.7, JHotDraw v5.1, QuickUML 2001, JRefactory v2.6.24, and MapperXML v1.9.7. Also, we performed our experiments on a set of source codes containing the instances of GoF design patterns’ variants for a comprehensive and fair evaluation. The evaluation results indicate that the proposed method has improved the accuracy of design pattern detection in the code.

     

Green synthesis of silver nanoparticles using flower extract of Malva sylvestris and investigation of their antibacterial activity

High‐quality colloidal silver nanoparticles (AgNP) were synthesised via a green approach by using hydroalcoholic extracts of Malva sylvestris. Silver nitrate was used as a substrate ion while the plant extract successfully played the role of reducing and stabilising agents. The synthesised nanoparticles were carefully characterised by using transmission electron microscopy, atomic‐force microscopy, energy dispersive X‐ray spectroscopy, Fourier transform infrared spectroscopy and UV–vis spectroscopy. The maximum absorption wavelengths of the colloidal solutions synthesised using 70 and 96% ethanol and 100% methanol, as extraction solvents, were 430, 485 and 504 nm, respectively. Interestingly, the size distribution of nanoparticles depended on the used solvent. The best particle size distribution belonged to the nanoparticles synthesised by 70% ethanol extract, which was 20–40 nm. The antibacterial activity of the synthesised nanoparticles was studied on Escherichia coli, Staphylococcus aureus and Streptococcus pyogenes using disk diffusion, minimum inhibitory concentrations and minimum bactericidal concentrations assays. The best antibacterial activity obtained for the AgNPs produced by using 96% ethanolic extract.Inspec keywords: silver, nanoparticles, nanofabrication, antibacterial activity, colloids, particle size, transmission electron microscopy, atomic force microscopy, X‐ray chemical analysis, Fourier transform spectra, infrared spectra, ultraviolet spectra, visible spectra, microorganisms, nanomedicine, biomedical materialsOther keywords: Green synthesis, flower extract, Malva sylvestris, antibacterial activity, high‐quality colloidal silver nanoparticles, hydroalcoholic extracts, plant extract, reducing agents, stabilising agents, transmission electron microscopy, atomic‐force microscopy, energy dispersive X‐ray spectroscopy, Fourier transform infrared spectroscopy, UV– vis spectroscopy, colloidal solutions, particle size distribution, Escherichia coli, Staphylococcus aureus, Streptococcus pyogenes, disk diffusion, minimum inhibitory concentrations, minimum bactericidal concentrations assays, ethanolic extract, size 430 nm, size 485 nm, size 504 nm, size 20 nm to 40 nm, Ag     

Real world representation of a road network for route planning in GIS

This paper addresses a methodology to properly represent a road network in the geographic information system (GIS) for network analysis. Over the years, the real world has become too complex to model properly within a given information system, such as GIS. Ideally, when the real world is represented as accurately as possible, a GIS can answer a question in its virtual world that coincides with the exact answer in the real world. However, existing methods related to impedance modeling for each segment of a road network in a route planning analysis that includes only a distance or time variable do not give proper results. Hence, this study investigates how a road network can represent the real world in a GIS and offer route planning tools. To address this, first, additional realistic variables are taken into account. These include weather, sight-seeing information, road type, and so on. Second, to combine these variables, an impedance model (IM) using the analytical hierarchical process (AHP) method is proposed. Finally, all of the models are implemented and verified with a sensitivity analysis. The models were successfully implemented in this work. All of the paths of the route planning analysis were successfully matched with the drivers’ paths that would normally be chosen in reality. It is anticipated that the use of other techniques such as analytical network process (ANP) in addition to AHP would be useful to overcome the aforementioned problem.     

A hybrid recommendation technique based on product category attributes

Recommender systems are powerful tools that allow companies to present personalized offers to their customers and defined as a system which recommends an appropriate product or service after learning the customers’ preferences and desires. Extracting users’ preferences through their buying behavior and history of purchased products is the most important element of such systems. Due to users’ unlimited and unpredictable desires, identifying their preferences is very complicated process. In most researches, less attention has been paid to user’s preferences varieties in different product categories. This may decrease quality of recommended items. In this paper, we introduced a technique of recommendation in the context of online retail store which extracts user preferences in each product category separately and provides more personalized recommendations through employing product taxonomy, attributes of product categories, web usage mining and combination of two well-known filtering methods: collaborative and content-based filtering. Experimental results show that proposed technique improves quality, as compared to similar approaches.     

A novel method for voice conversion based on non-parallel corpus

This article puts forward a new algorithm for voice conversion which not only removes the necessity of parallel corpus in the training phase but also resolves the issue of insufficiency of the target speaker’s corpus. The proposed approach is based on one of the new voice conversion models utilizing classical LPC analysis-synthesis model combined with GMM. Through this algorithm, the conversion functions among vowels and demi-syllables are derived. We assumed that these functions are rather the same for different speakers if their genders, accents, and languages are alike. Therefore, we will be able to produce the demi-syllables with just having access to few sentences from the target speaker and forming the GMM for one of his/her vowels. The results from the appraisal of the proposed method for voice conversion clarifies that this method has the ability to efficiently realize the speech features of the target speaker. It can also provide results comparable to the ones obtained through the parallel-corpus-based approaches.     

Nano levels detection of beryllium by a novel beryllium PVC-based membrane sensor based on 2,3,5,6,8,9-hexahydro-1,4,7,10-benzotetra oxacyclododecine-12-carbaldehyde-12-(2,4-dinitrophenyl)hy

A novel poly(vinyl chloride)-based 2,3,5,6,8,9-hexahydro-1,4,7,10-benzotetra oxacyclododecine-12-carbaldehyde-12-(2,4-dinitrophenyl)hy (PBC) with sodium tetraphenyl borate (NaTPB) as an anion excluder, benzyl acetate (BA), acetophenon (AP) and o-nitrophenyloctyl ether (NPOE) as plasticizing solvent mediators was prepared and investigated as a beryllium selective sensor. The best performance was observed with the membrane having the PVC–NaTPB–NPOE–PBC composition 30%:3%:62%:5%, which worked well over a very wide concentration range (1.0×10⁻⁷ M to 1.0×10⁻¹ M). The sensor exhibits a Nernstian slope of 29.9 mV per decade of Be²⁺ activity. The detection limit of the sensor is 7.0×10⁻⁸ M (630 ppt). The proposed electrode shows excellent discriminating ability toward Be²⁺ ion with regard to alkali, alkaline earth, transition and heavy metal ions. It was successfully applied to the determination of beryllium in a mineral sample.     

Synthesis of nano-structured La0.8Ba0.2MnO3 perovskite via a mechano-thermal route

In this study, barium-doped lanthanum manganite, La_0.8Ba_0.2MnO₃, was synthesized via a mechano-thermal route employing high energy ball milling and subsequent heat treatment. The structural evolution, morphology and thermal behaviour of the powders were evaluated using XRD, FESEM, and DTA/TGA, respectively. DTA/TGA results showed that the calcination temperature of the carbonates significantly decreased by increasing the milling time. The results revealed that single phase perovskite was formed at 900 °C in a milled sample for 2 h and this temperature decreased to 600 °C by increasing the milling time to 30 h. The mean crystallite size also decreased from 32 to 20 nm by increasing the milling time from 2 to 30 h. The reaction sequence of La_0.8Ba_0.2MnO₃ formation via the mechano-thermal route is proposed using XRD and DTA/TGA results. FESEM micrographs showed that the mean particle size of the perovskite phase is increased slightly from 30 to 40 nm by increasing the heat treatment temperature from 600 to 900 °C.     

Improvement of time alignment of the speech signals to be used in voice conversion

One of the main applications of time alignment is parallel corpus based voice conversion. In the literature, various methods such as dynamic time warping (DTW) and hidden Markov model have been suggested for time alignment of two speech signals. In this paper, we introduce some modifications to DTW in order to decrease the time alignment error. These modifications are refinement, which is done by exerting a threshold, normalization, and comparisons between the preceding and the following frames to make sound correspondence between two different parallel corpus-based speakers’ speeches. Evaluation of this approach which has been done on some corpus sentences indicates a significant improvement of time alignment. At least about 4% and in some cases 15% decrease of error in comparison with DTW has been achieved.     

Photoluminescence emission of nanoporous anodic aluminum oxide films prepared in phosphoric acid

The photoluminescence emission of nanoporous anodic aluminum oxide films formed in phosphoric acid is studied in order to explore their defect-based subband electronic structure. Different excitation wavelengths are used to identify most of the details of the subband states. The films are produced under different anodizing conditions to optimize their emission in the visible range. Scanning electron microscopy investigations confirm pore formation in the produced layers. Gaussian analysis of the emission data indicates that subband states change with anodizing parameters, and various point defects can be formed both in the bulk and on the surface of these nanoporous layers during anodizing.