Gridding and Segmentation Method for DNA Microarray Images

This article mainly explores meshing and segmentation techniques for microarray image analysis. The term "grid" refers to dividing an image into subgrids of dots and then dividing them into point detection. Most of the existing methods depend on input parameters such as the number of rows / columns, the number of points in each row / column, the size of the subarrays, etc. This article proposes a fully automatic mesh generation algorithm. This can remove any initialized parameter without any manual intervention. In the segmentation step, clustering algorithms are used because they do not consider the size and shape of the spots, do not depend on the initial state of the pixels, and do not require post-processing. In this article, a new method is proposed to estimate the initial parameters (centroid and number of clusters) required by any clustering algorithm. Qualitative and quantitative analysis shows that the algorithm can perform grid processing on microarray images well, and improves the performance of the clustering algorithm

Performance evaluation of a manually operated paddy drum seeder - a cost saving technology for paddy cultivation

 A study was conducted at farmer field to evaluate performance of mechanized paddy cultivation (T1), mechanized paddy cultivation with incorporation of Dhaincha before direct sowing of paddy seed (T2) and the traditional farmer practice (T3).  Consecutive three years of data were obtained for analysis and different crop growth parameters were measured like panicle length, number of tillers, grain yield etc. for each treatment.  It was found that the average grain yield for three years in different treatments T1 and T2 was enhanced by 10% and 14% respectively when compared with farmer practice.  Average cost of cultivation was reduced by 25% in treatment T2 where green manuring crop (Dhaincha) was grown and incorporated in soil with indigenous plough before paddy seeding.  Study also revealed that due to mechanized cultivation practices, the crop was ready to harvest eight to ten days early than farmer’s practices.  The experiment well proved to raise the socio-economic status of the farmers by changing their strategy towards mechanized organic paddy cultivation.   Keywords: drum seeder, mechanization, green manuring crop, growth parameters

Converting a paper proforma template to a user friendly electronic database to collect traumatic brain injury data

A structured reporting system which is based on a uniform template will permit uniform data collection and future statistics and will facilitate and validate independent or comparative audit of performance and quality of care. The successful establishment of a multi-center registry depends on the development of a concise data entry form, data entry system and data analysis to continuously maintain the registry. In the first phase we introduced the paper data collection form, in second phase this data form was converted to an electronic interface. In this second phase of the study the paper proforma which was developed in the first phase was converted into an electronic database by using the FileMaker Pro 13 Advanced®. The FileMaker Pro 13 Advanced® is capable to store the data, provides user friendly interface to enter data and can be converted the standalone runtime program to install in any other computer system. The next step is to explore the possibility whether it would be feasible to use this as a multi-center traumatic brain injury registry

Developing a traumatic brain injury registry: lessons learned from difficulties

Aim: The aim of present article is to share our experiences and lessons learned from a pilot study which was conducted to collect data to serve as a model in establishing a multi-center registry on traumatic brain injury patients.Methods: The present study was conducted from December 2013 to June 2014 in the Department of Neurosurgery and Department of Accident and Emergency Medicine. All patients with the diagnosis of traumatic brain injury (as per the criteria laid by International Classification of Disease injury codes ICD 10) were enrolled in the study. Variables were identified as per the international norms and the data points were selected which included demographic details, pre-hospital characteristics, clinical details in emergency room, injury details, course during hospital stay, treatment and disposition. The data were categorized into master data, data related to pre-hospital events including pre-hospital care, data related to emergency room care offered in the emergency department, data related to hospital stay and patient course, outcome and follow up.Results: A total of 231 patients were admitted with the diagnosis of traumatic brain injury. There were 79.1% male and 20.5% female patients. Mean age was 37.19 years (SD±17.02 years, range 4-87 years). Mean hospital stay was 3.66 days (SD±4.46 days, range-1-21 days). Data were collected daily for all the admitted patients on previous day fulfilling the inclusion criteria. The Proforma was easy to comprehend and it was easy to fill.Conclusion: We found that a well-designed Proforma based under supervision data collection in a relatively low volume trauma center. We found that a well-designed Proforma based under supervision data collection in a relatively low volume trauma center and at regular intervals can be cost-effective which can be managed by personnel with basic training

Aerosol spectral optical depths and size characteristics at a coastal industriallocation in India - effect of synoptic and mesoscale weather

The aerosol spectral optical depths at ten discrete channels in the visible and near IR bands, obtained from a ground-based passive multi-wavelength solar radiometer at a coastal industrial location, Visakhapatnam, on the east coast of India, are used to study the response of the aerosol optical properties and size distributions to the changes in atmospheric humidity, wind speed and direction. It is observed that during high humidity conditions, the spectral optical depths show about 30% higher growth factors, and the size distributions show the generation of a typical new mode around 0.4 microns. The surface wind speed and direction also indicate the formation of new particles when the humid marine air mass interacts with the industrial air mass. This is interpreted in terms of new particle formation and subsequent particle growth by condensation and self-coagulation. The results obtained on the surface-size segregated aerosol mass distribution from a co-located Quartz Crystal Microbalance during different humidity conditions also show a large mass increase in the sub-micron size range with an increase in atmospheric humidity, indicating new particle formation at the sub-micron size range

Prediction of Effective Mobile Wireless Network Data Profiling Using Data Mining Approaches

Abstract Mobile network analysis has a huge potential that provide insight into the relational dynamics of individuals. Machine learning and data mining techniques provide the behavior patterns of the mobile network data. The data transfer during all the days has produced good results in transfer of data starting from Day 1 to Day 22. Hierarch ical clustering of the datasets for all the 1634 data examples in the mobile t raffic dataset. Co mplete linkage dendrogram has been produced between 0 and 4.64. Two clusters have been produced from the present wireless mobile t raffic datasets