Fraudulent Firm Classification: A Case Study of an External Audit

This paper is a case study of visiting an external audit company to explore the usefulness of machine learning algorithms for improving the quality of an audit work. Annual data of 777 firms from 14 different sectors are collected. The Particle Swarm Optimization (PSO) algorithm is used as a feature selection method. Ten different state-of-the-art classification models are compared in terms of their accuracy, error rate, sensitivity, specificity, F measures, Mathew’s Correlation Coefficient (MCC), Type-I error, Type-II error, and Area Under the Curve (AUC) using Multi-Criteria Decision-Making methods like Simple Additive Weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The results of Bayes Net and J48 demonstrate an accuracy of 93% for suspicious firm classification. With the appearance of tremendous growth of financial fraud cases, machine learning will play a big part in improving the quality of an audit field work in the future.     

Ontology based E-learning framework: A personalized,adaptive and context aware model

Multimedia Tools and Applications - Enhancing the degree of learner productivity, one of the major challenges in E-Learning systems, may be catered through effective personalization, adaptivity and...     

Study on micro-patterning process of vertically aligned carbon nanotubes (VACNTs)

Vertically aligned carbon nanotubes (VACNTs) have drawn significant attention by the researchers because of their nanometric size and favorable material properties. Patterning of CNT forests in the micrometric domain is very important for their application in the area of microelectromechanical system (MEMS). For the first time this paper reports, detailed experimental investigation on a post growth μ-patterning process of VACNT forests. The micromechanical bending (M2B) process was locally applied at the targeted area in order to change the alignment of VACNT forests. Interestingly, the VACNT forest was transformed from typical black body absorber to reflective mirror as the M2B process was applied. Several parameters were identified that govern the resultant patterns such as rotational spindle speed, lateral bending speed, step size, tool morphology, and total depth of bend. Optimization of the parameters was carried out experimentally to obtain the best surface roughness and integrity of the microstructure. A minimum average surface roughness of Ra = 15 nm was achieved with 2000 rpm spindle speed, 1 mm/min bending speed and 1 µm step size.     

Relationship between physicochemical and functional properties of amaranth (Amaranthus hypochondriacus) protein isolates

Protein isolates from six amaranth lines/cultivars (APIs) were evaluated to study their physicochemical (hunter colour, protein content and zeta potential), structural (thermal and conformational) and functional (emulsification, foaming, water and fat absorption) properties. APIs had protein content, whiteness index and gel temperature in range of 79.4–85.4%, 41.17–54.26 and 87.8–91.8 °C, respectively. The Fourier‐transform infrared spectra of APIs revealed α‐helix, β‐sheets and random coil conformations in the secondary structure. APIs with higher relative proportion of β‐sheets had higher Differential Scanning Calorimeter denaturation temperature and gel temperature. Minimum protein solubility (PS) was observed at pH 5.0, indicating isoelectric point (pI) of amaranth proteins. The PS, emulsifying activity index (EAI), emulsifying stability index (ESI), foaming capacity (FC) and foam stability (FS) of APIs at neutral pH were related to their zeta potential (ζ). The emulsifying and foaming properties were also determined at different pHs (between 2.0 and 9.0). The EAI‐pH profile of APIs confirmed close relationship between the emulsifying ability and PS.     

MOLECULAR APPROACH TO MATERIAL DETACHMENT MECHANISM DURING CHEMICAL MECHANICAL PLANARIZATION

Mechanistic numerical analysis and molecular dynamics (MD) simulation are employed to understand the material detachment mechanism associated with chemical mechanical polishing. We investigate the mechanics of scratch intersection mechanism to obtain a characteristic length scale and compare the theoretical predictions with previous experimental observations on ductile copper discs at the micro-scale. First, an analytical model is developed based on mechanics of materials approach. The analytical model includes the effects of strain hardening during material removal as well as the geometry of indenter tip. In the next step, molecular simulations of the scratch intersection are performed at the atomistic scale. The embedded atom method (EAM) is utilized as the force field for workpiece material and a simplified tool-workpiece interaction is assumed to simulate material removal through scratch intersection mechanism. Both models are utilized to predict a characteristic length of material detachment related to material removal during scratch intersection. The predictions from two approaches are compared with experimental observations in order to draw correlations between experiment and simulation. The insights obtained from this work may assist in understanding the mechanism for chemical mechanical planarization (CMP), and even be applied to other different machining and polishing events.     

Poly(ethylene oxide)‐g‐gellan polysaccharide nanocarriers for controlled gastrointestinal delivery of simvastatin

Herein, a novel gellan polysaccharide‐based amphiphilic copolymer was synthesized for the development of simvastatin‐loaded micellar nanoparticles. The nanoparticles were explored for their controlled drug release and improved pharmacodynamic potentials. The copolymer was characterized by Fourier transform infrared spectroscopy (FTIR) and elemental analysis. The onset of copolymer micellization was detected by fluorescence spectroscopy. Simvastatin was loaded into micellar particles by solvent evaporation method and the particles were then characterized by microscopic and light scattering techniques. The physical state of drug was studied by X‐ray diffraction analysis. Pharmacodynamic assessment of the micellar preparations was done on rabbit models. The copolymer formed micellar nanoparticles in water. Critical micellar concentration was 9.12mg/l. The micellar particles (426.8–912.6nm) entrapped a maximum of 18.86% drug. Higher negative zeta potential indicated physical stability of micellar systems. A simple diffusion mechanism was operative in the event of comparatively faster drug release in pH6.8 phosphate buffer solution. No significant drug‐copolymer interaction was traced by FTIR spectroscopy. The amorphization of drug into micellar particles reduced LDL‐cholesterol level by ～45% in hyperlipidemic rabbits and this was about 2.5 times higher than pure drug dispersion. Copolymer micellar nanoparticles of simvastatin could control cholesterol level in hyperlipidemic rabbits and thus had potential in drug delivery applications. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42399.