Training a Feed-forward Neural Network with Artificial Bee Colony Based Backpropagation Method

Back-propagation algorithm is one of the most widely used and popular techniques to optimize the feed forward neural network training. Nature inspired meta-heuristic algorithms also provide derivative-free solution to optimize complex problem. Artificial bee colony algorithm is a nature inspired meta-heuristic algorithm, mimicking the foraging or food source searching behaviour of bees in a bee colony and this algorithm is implemented in several applications for an improved optimized outcome. The proposed method in this paper includes an improved artificial bee colony algorithm based back-propagation neural network training method for fast and improved convergence rate of the hybrid neural network learning method. The result is analysed with the genetic algorithm based back-propagation method, and it is another hybridized procedure of its kind. Analysis is performed over standard data sets, reflecting the light of efficiency of proposed method in terms of convergence speed and rate.Comment: 14 Pages, 11 figure

Smart Knowledge Transfer using Google-like Search

To address the issue of rising software maintenance cost due to program comprehension challenges, we propose SMARTKT (Smart Knowledge Transfer), a search framework, which extracts and integrates knowledge related to various aspects of an application in form of a semantic graph. This graph supports syntax and semantic queries and converts the process of program comprehension into a {\em google-like} search problem.Comment: 3 pages, 2 figures, accepted in the NDLI-UNESCO International Symposium on Knowledge Engineering for Digital Library Design 2019 (KEDL) as an extended abstract and poste

Multi-objective optimization of mechanical properties of chemically treated bio-based composites using response surface methodology

Eco-friendly surface treatment of natural fibers using sodium acetate (CH3COONa) affects the mechanical properties of the developed composites in many ways. In present study, geometrically different kenaf fiber mats (bidirectional (BC), unidirectional (UD) and randomly oriented (RO) were treated at different concentration (10, 15 and 20 percentage w/w) of sodium acetate aqueous solution for varying time (24, 48 and 72 hr.) at room temperature. PLA (Poly-Lactic Acid) was used for the fabrication of treated fiber reinforced bio-degradable composites. The influence of above parameters on mechanical properties were studied. Response surface methodology (RSM) module face centered central composite design was employed for the development of regression models. The relationship between chemical treatment parameters and mechanical responses were predicted by quadratic model. In this study, predicted model was developed for two numerical factors (chemical concentration (CC) and treatment time (TT)) and one categorical factor (type of mat (TOM)). Tensile strength (TS), flexural strength (FS) and impact strength (IS) are considered as response variables. The statistical analysis showed that chemical concentration, treatment time and kenaf mat type have individually and interactively influenced the response of experiments. Chemical concentration was found to be the most influencing factor among all for the changes in mechanical properties. Optimization of input variables was done based on predicted model within bounded reason of responses

EFFECT OF PURITY LEVEL OF CO2 SHIELDING ON METAL ACTIVE GAS WELDED JOINT QUALITY

The investigation deals with the study of the effect of the purity level of carbon dioxide shielding gas on the metal active gas weld quality. Studied 99.78 %, 99.95 %, and 99.97 % purity levels of carbon dioxide shielding gas. Factors considered were related to shielding gas purity, moisture, Sulphur, and oxygen content. Welded samples were subjected to ultrasonic testing to assess weld quality. With the reduction in purity level below 99.9 %, it was observed that the weld defect percentage increased in both lab trials and mass manufacturing jobs. The defects recorded were 5% higher when jobs were welded using carbon dioxide supplied from a gas cylinder than that supplied from liquid cryogenic bullets; this established that a higher purity level could be maintained in cryogenic storage and transport of shielding gases. This states helpful references to manufacturing industries for selecting the purity level of shielding gas, with the objective of rework reduction

An Improved Gauss-Newtons Method based Back-propagation Algorithm for Fast Convergence

The present work deals with an improved back-propagation algorithm based on Gauss-Newton numerical optimization method for fast convergence. The steepest descent method is used for the back-propagation. The algorithm is tested using various datasets and compared with the steepest descent back-propagation algorithm. In the system, optimization is carried out using multilayer neural network. The efficacy of the proposed method is observed during the training period as it converges quickly for the dataset used in test. The requirement of memory for computing the steps of algorithm is also analyzed.Comment: 7 pages, 6 figures,2 tables, Published with International Journal of Computer Applications (IJCA

SLE in Pregnancy

Systemic lupus erythematosus is specially a disease of young women in their child bearing age. It has been found that SLE disease activity can repair in pregnancy even though patient is in complete remission state before the pregnancy. Besides this, pregnancy complications are higher in SLE patients. Another important issue is the use of drugs to control SLE because some of these drugs are potentially terotogenic. Fetal outcome is also a challenging issue. Therefore, multidisciplinary approach has key role in the management of Lupus pregnancy.Key words: Systemic lupus erythematosus (SLE); Lupus pregnancy; Lupus flare; Anti-phospholipid Antibody Syndrome;Neonatal Lupus Syndrome; Congenital heart block.DOI: 10.3329/bsmmuj.v3i1.5517BSMMU J 2010; 3(1): 54-5