Efficient Handwritten Digit Classification using User-defined Classification Algorithm

In automatic numeral digit recognition system, feature selection is most important factor for achieving high recognition performance. To achieve this, the present paper proposed system for isolated handwritten numeral recognition using number of contours, skeleton features, Number of watersheds, and ratio between the numbers of foreground pixels in upper half part and lower half-part of the numerical digit image. Based on these features the present paper designed user-defined classification algorithm for handwritten digit recognition. To find the effectiveness of the proposed features, these features are given as an input for standard classification algorithms like k–nearest neighbor classifier, Support Vector Machines and other classification algorithms and evaluate the results.  The experimental result proves that the proposed features are well suited for handwritten digit recognition for both user and standard classification algorithms. The novelty of the proposed method is size invariant

Comparative Analysis of common Edge Detection Algorithms using Pre-processing Technique

Edge detection is the process of segmenting an image by detecting discontinuities in brightness. So far, several standard segmentation methods have been widely used for edge detection. However, due to inherent quality of images, these methods prove ineffective if they are applied without any preprocessing. In this paper, an image preprocessing approach has been adopted in order to get certain parameters that are useful to perform better edge detection with the standard edge detection methods. The proposed preprocessing approach involves median filtering to reduce the noise in image and then Edge Detection technique is carried out. And atlast Standard edge detection methods can be applied to the resultant preprocessing image and its Simulation results are show that our preprocessed approach when used with a standard edge detection method enhances its performance

Analgesic activity of Alpinia galanga extract in mice models and TNF-alpha receptor computational docking analysis on its leads with pharmacokinetics prediction

Background: Alpinia galanga is an ayurvedic herb recognized and used across many traditional medicine systems for its analgesic and anti-inflammatory activity. The present study scientifically validates the potential anti nociceptive action of ethanolic extract of Alpinia galanga by chemical, neurogenic and inflammatory nociception model in mice followed by identification of potential lead compound by computational analysis.Methods: The assessment of anti nociceptive action is evaluated by Acetic acid induced abdominal constrictions and Formalin assay on ethonolic extract of Alpinia galanga, followed by 20 compounds with known chemical structure of Alpinia galanga is subjected to computational analysis to predict possible lead compound with desirable pharmacokinetic and drug like features.Results: The percentage inhibition rate of Aspirin (100mg/kg) was 82.15% compared to Alpinia galanga (100mg/kg) 19.63%, (200mg/kg) 33.02% and (400mg/kg) 57.13% by acetic acid induced abdominal constrictions antinociceptive mice model. Alpinia galanga 400mg/kg (71.70%) had comparable percentage inhibition of nociception to standard group indomethacin (88.71%) in formalin induced nociceptive mice model. Among 20 compounds screened for pharmacokinetic and drug like features, Galanal B had the binding free energy -56.664 when compared to control compound 2AZ5-56.000.Conclusions: The Alpinia galanga extract had significant anti nociceptive activity and followed by computational analysis of 20 compounds with known chemical structure predicted Galanal B as lead compound with best insilico pharmacokinetic and drug like features

Beneficiation of iron ore fines by conventional flotation, flotation column and dual extraction column – A pilot scale study

Goa state in India is endowed with large deposits of low-grade iron ores, geologically formed from lower Dharwar super group of Archaean rocks. Petrological studies have revealed that silica and alumina are the main gangue minerals where alumina exists as fine clay and adherent material interspersed in the ore body and in some cases both silica and alumina interlocked with iron ore particles. Efficiency of conventional flotation, column flotation and dual extraction column for separation of gangue was studied on a pilot scale at Greater Ferromet Beneficiation Plant of M/s. Sociedade De Fomento Industrial Ltd., Goa. Reverse flotation process was adopted wherein gangue minerals silica and alumina were floated using cationic amine collector. Sodium hydroxide and starch were used to regulate the slurry pH and to depress iron ore, respectively. Various iron ore samples drawn from different mines and their mixtures were subjected to the test work. Results of pilot scale tests clearly indicate the superiority of flotation column vis-a-vis conventional cells and dual extraction column. Iron ore concentrate assaying 67 % Fe and 2 % Si02 and AI203 with a recovery of 85 - 90 % could be obtained by single stage flotation column operation

Statistical characterization of thermal inversions observed over Tirupati using sodar and microbarograph

289-296A monostatic acoustic sounder (sodar) has been developed for the study of dynamical behaviour of the atmospheric boundary layer (ABL) phenomena over Tirupati. The infrasonic pressure variations have been recorded near sodar site using a microbarograph. A systematic study is made on ABL phenomena (over inland region) using sodar and microbarograph. Ground-based inversions and elevated layers have been observed to be predominantly the nighttime phenomena. Statistical analysis of ground-based inversions, elevated inversions, wave motions and rising inversions is made along with the variations in their heights of occurrences. Simultaneous observations of ABL using sodar and microbarograph are made. Some of the case studies are presented

Investigation of gravity waves in the atmospheric boundary layer using sodar and microbarograph

247-259Presence of irregularities and irregular motions in the atmospheric boundary layer (ABL) have been detected and studied by a variety of techniques, including sodars and microbarographs. The infrasonic pressure variations have been recorded at Tirupati using a microbarograph. Wave motions associated with temperature inversions in ABL are studied using an acoustic sounder and a microbarograph. Two-year investigation of waves and wave perturbations in low-level inversions in the atmosphere over Tirupati valley region are reported. A detailed study on wave motions in terms of diurnal variation, seasonal variation, occurrence percentage and amplitude of the wave motion associated with different structures in ABL is made. Simultaneous study of the nature of waves in the atmosphere is made using echosonde and microbarograph data. Gravity waves are mostly observed in this region during winter and premonsoon seasons due to temperature inversions and thunderstorms. In order to characterize the wave nature and to study the effect of their motions occurring mostly at nighttime stable conditions, cross-correlation and power spectral density technique have been applied