A knowledge based component/service repository to enhance analysts’ domain knowledge for requirements analysis

Knowledge of the business domain (e.g., insurance claim, human resources) is crucial to analysts’ ability to conduct good requirements analysis (RA). However, current practices afford little assistance to analysts in acquiring domain knowledge. We argue that traditional reuse repositories could be augmented by adding rich faceted information on component/services and artifacts such as business-process templates to help analysts acquire domain knowledge during RA. In this paper, we present the design of a Knowledge Based Component Repository (KBCR) for facilitating RA. Then, we report on the design and development of a KBCR prototype. We illustrate its application in a system that is populated with components and process templates for the auto insurance claim domain. An empirical study was conducted to assess its effectiveness in improving RA. Results showed that KBCR enhanced analysts’ business domain knowledge and helped them better prepare for RA. Our key research contribution is to offer analysts a rich repository (i.e., KBCR) containing domain knowledge that they could utilize to acquire domain knowledge that is crucial for carrying out RA. While repositories of reusable components have been employed for some time, no one has used such repositories to help analysts acquire domain knowledge in order improve the RA of the system.     

Synthesis, characterization and magnetic properties of NiS1+x nanocrystals from [bis(salicylidene)nickel(II)] as new precursor

[Bis(salicylidene)nickel(II)] was used as a precursor to prepare nickel sulfides nanoparticles of average size 20 nm by a chemical process in oleylamine. The products were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM), X-ray photoelectron spectroscopy (XPS), ultraviolet-visible spectroscopy (UV-vis) and photoluminescence (PL) spectroscopy. Magnetization measurement indicates that both of the α-NiS and Ni₃S₄ nanoparticles show pramagnetism due to the size effect.     

Protein encapsulated in electrospun nanofibrous scaffolds for tissue engineering applications

The main purpose of tissue engineering is the preparation of fibrous scaffolds with similar structural and biochemical cues to the extracellular matrix in order to provide a substrate to support the cells. Controlled release of bioactive agents such as growth factors from the fibrous scaffolds improves cell behavior on the scaffolds and accelerates tissue regeneration. In this study, nanofibrous scaffolds were fabricated from biocompatible and biodegradable poly(lactic‐co‐glycolic acid) through the electrospinning technique. Nanofibers with a core–sheath structure encapsulating bovine serum albumin (BSA) as a model protein for hydrophilic bioactive agents were prepared through emulsion electrospinning. The morphology of the nanofibers was evaluated by field‐emission scanning electron microscopy and the core–sheath structure of the emulsion electrospun nanofibers was observed by transmission electron microscopy. The results of the mechanical properties and X‐ray diffraction are reported. The scaffolds demonstrated a sustained release profile of BSA. Biocompatibility of the scaffolds was evaluated using the MTT (3(4,5‐ dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide) assay for NIH‐3T3 fibroblast cells. The results indicated desirable biocompatibility of the scaffolds with the capability of encapsulation and controlled release of the protein, which can serve as tissue engineering scaffolds. © 2013 Society of Chemical Industry     

An extended compromise ratio method for fuzzy group multi-attribute decision making with SWOT analysis

The technique for order preference by similarity to ideal solution (TOPSIS) is a well-known multi-attribute decision making (MADM) method that is used to identify the most attractive alternative solution among a finite set of alternatives based on the simultaneous minimization of the distance from an ideal solution (IS) and the maximization of the distance from the nadir solution (NS). We propose an alternative compromise ratio method (CRM) using an efficient and powerful distance measure for solving the group MADM problems. In the proposed CRM, similar to TOPSIS, the chosen alternative should be simultaneously as close as possible to the IS and as far away as possible from the NS. The conventional MADM problems require well-defined and precise data; however, the values associated with the parameters in the real-world are often imprecise, vague, uncertain or incomplete. Fuzzy sets provide a powerful tool for dealing with the ambiguous data. We capture the decision makers’ (DMs’) judgments with linguistic variables and represent their importance weights with fuzzy sets. The fuzzy group MADM (FGMADM) method proposed in this study improves the usability of the CRM. We integrate the FGMADM method into a strengths, weaknesses, opportunities and threats (SWOT) analysis framework to show the applicability of the proposed method in a solar panel manufacturing firm in Canada.     

Controlled release of prednisolone acetate from molecularly imprinted hydrogel contact lenses

The aim of this work was to study the influence of methacrylic acid (MAA) as a comonomer and the application of a molecular imprinting technique on the loading and release properties of weakly crosslinked 2‐hydroxyethyl methacrylate (HEMA) hydrogels, with a view toward their use as reloadable soft contact lenses for the administration of prednisolone acetate (PA). The hydrogels were prepared with HEMA (95.90–98.30 mol %) as a backbone monomer, ethylene glycol dimethacrylate (140 mM) as a crosslinker, and MAA (0, 50, 100, or 200 mM) as a functional monomer. Different PA/MAA molar ratios (0, 1 : 8, 1 : 6, and 1 : 4) in the feed composition of the hydrogels were also applied to study the influence of the molecular imprinting technique on their binding properties. The hydrogels (0.4 mm thick) were synthesized by thermal polymerization at 60°C for 24 h in a polypropylene mold. The hydrogels were then characterized by the determination of their swelling and binding properties in water. Their loading and release properties were also studied in 0.9% NaCl and artificial lachrymal fluid. Increasing the MAA content of the hydrogel and applying the molecular imprinting technique led to an increase in the loading capacity of the hydrogel. The optimized imprinted hydrogel showed the highest affinity for PA and the greatest ability to control the release process, sustaining it for 48 h. The results obtained clearly indicate that the incorporation of MAA as a comonomer increased the PA loading capacity of hydrogel. Our data showed that the molecular imprinting technique also had a significant effect on the loading and release properties of the hydrogels. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Refractive index determination in fuel cells using high-resolution laser heterodyne interferometer

In this paper, we present an interferometry method for refractive index determination in membranes of fuel cells. This technique is based on the use of an improved laser heterodyne interferometer. The photocurrents of the avalanche photodiodes, resulting from reflected beams of the optical head, are led to the signal conditioner and digital signal processing sections. The optical path difference between the target and reference paths is fixed, and as a result, the phase shift is calculated in terms of the refractive index shift. In addition, nonlinearity of this system is analyzed and modeled with different neural networks and adaptive filter algorithms. For neural networks, the radial basis function (RBF), the multi-layer perceptron (MLP), and the stacked generalization method are simulated. In adaptive filter algorithms, the least mean square (LMS), the normalized least mean square (NLMS), the recursive least squares (RLS), and the affine projection algorithm (APA) are applied. The simulation results indicate that the RLS method is faster and contains minimum mean square error (MSE) compared to the other approaches. Also, comparison between two main approaches shows that the nonlinearity of refractive index determination can be effectively modeled with adaptive filter algorithms.     

Influence of drying and extraction methods on yield and chemical composition of the essential oil of Satureja hortensis

The aerial parts of Satureja hortensis, cultivated in Iran (Research Station of Alborz, Karaj), were collected at the full-flowering stage and dried by three different drying methods (sun-drying, shade-drying and oven-drying at 45 °C). The essential oils of every treatment were obtained by hydro-distillation of the aerial parts. In addition, the essential oil of shade-dried sample was obtained by two other distillation methods (water- and steam-distillation and direct steam-distillation). The oils were analyzed by capillary GC and GC–MS. Statistical analysis showed no significant difference between oil yield (w/w) of the oven-dried sample (1.06%) compared to shade-dried (0.94%) and sun-dried (0.87%). The oil content of the shade-dried sample, obtained by hydro-distillation, was higher (0.94%) than that of the steam-distilled (0.27%). Twenty-three components were identified in the oil of S. hortensis in the different drying methods, including carvacrol (46.0–48.1%) and γ-terpinene (37.7–39.4%) as main components. Seventeen compounds were characterized in the oils of different distillation methods, including carvacrol (12.3–46%) and γ-terpinene (37.7–70.4%). Although the drying methods had no significant effect on oil composition of S. hortensis, the distillation changed the percentage of main components sharply (significant at 1%). The steam-distillation method produced the lowest amount of carvacrol and highest amount of γ-terpinene. The results showed that extraction by hydro-distillation gave the best results for S. hortensis, based on oil yield and carvacrol percentage.     

Synthesis and characterization of paclitaxel-imprinted nanoparticles for recognition and controlled release of an anticancer drug

Imprinted nanoparticles as drug delivery carriers have been considered because owing to their cross-linked network, they act as the drug reservoir for controlled release. In this study, selective MIPs nanoparticles of paclitaxel (PTX) were successfully developed for application in the biological molecular recognition and in the design of new anticancer drug delivery systems. The MIPs nanoparticles prepared by miniemulsion polymerization technique using methacrylic acid (MAA) and methyl methacrylate as non-covalent functional monomer, ethylene glycol dimethacrylate and trimethylolpropane trimethacrylate (TRIM) as cross-linker agent, azobisisobutyronitrile as initiator, and hexadecane as hydrophobic agent. In order to prepare of MIP nanoparticles, the synthesis conditions and effective parameters, such as: cross-linker agent, different molar ratios of template–functional monomer–cross-linker agent, were investigated. In addition, the effect of different molar ratios of template and monomers on polymers binding and morphology were characterized. Structure and thermal properties of MIPs were confirmed by FT-IR spectroscopy and thermogravimetric analysis. Imprinted nanoparticles showed significant drug loading and encapsulation efficiency, 17.8 and 100 %, respectively. The particle size of MIP nanoparticles varies between 187 and 726 nm, according the SEM images and laser light scattering data. The imprinted nanoparticles showed satisfactory affinity (84 %) to PTX with a binding of 12 times higher than non-imprinted nanoparticles in biological samples when MAA and TRIM were used as functional and cross-linker monomer, respectively. Results from release experiments of MIPs showed a very slow and controlled release of PTX which would be helpful for sustained drug delivery.     

Thermal sensor allocation for 3DICs using three dimensional thermal sensors

Stacking active layers leads to increased power density and overall higher temperatures in a three dimensional integrated circuit (3DIC). Thermal sensors are therefore crucial for run-time thermal management of 3DICs. A thermal sensor allocation method customized for 3DICs that utilizes ring oscillator based 3D sensors is introduced in this paper. A new 3D thermal map modeling method that facilitates efficient and very fast analyses is embodied in this thermal sensor distribution algorithm. Our results indicate that for a 4-layer stacked 3DIC, consisting of two layers of quad-core processors and one layer of L2 cache and one layer of main memory, less than 3.58% in maximum sensor reading error can be accomplished with a 53× speedup in the thermal evaluation time and thermal sensor distribution algorithm implementation.