TEC and Instrumental Bias Estimation of GAGAN Station Using Kalman Filter and SCORE Algorithm

The standalone Global Positioning System (GPS) does not meet the higher accuracy requirements needed for approach and landing phase of an aircraft. To meet the Category-I Precision Approach (CAT-I PA) requirements of civil aviation, satellite based augmentation system (SBAS) has been planned by various countries including USA, Europe, Japan and India. The Indian SBAS is named as GPS Aided Geo Augmented Navigation (GAGAN). The GAGAN network consists of several dual frequency GPS receivers located at various airports around the Indian subcontinent. The ionospheric delay, which is a function of the total electron content (TEC), is one of the main sources of error affecting GPS/SBAS accuracy. A dual frequency GPS receiver can be used to estimate the TEC. However, line-of-sight TEC derived from dual frequency GPS data is corrupted by the instrumental biases of the GPS receiver and satellites. The estimation of receiver instrumental bias is particularly important for obtaining accurate estimates of ionospheric delay. In this paper, two prominent techniques based on Kalman filter and Self-Calibration Of pseudo Range Error (SCORE) algorithm are used for estimation of instrumental biases. The estimated instrumental bias and TEC results for the GPS Aided Geo Augmented Navigation (GAGAN) station at Hyderabad (78.47°E, 17.45°N), India are presented.

Blockchain-based Bank-to-Personal Credit Decisions

With the continuous integration of Internet technology and people's lives,blockchain technology provides more possibilities for the development of the banking industry.Blockchain is a distributed database.It has the characteristics of non-tampering,openness,transparency,decentralization,and good anonymity.It can well solve the shortcomings of the current personal credit evaluation system,thus proposing corresponding strategies for banks.Firstly,this paper proposes the challenges and difficulties in building a personal credit data sharing system based on blockchain,designs a personal credit data sharing model based on blockchain technology,and proposes a personal credit evaluation mechanism based on blockchain,including three parts:credit mechanism,credit index,and weighted scoring algorithm.Finally,through the linear regression model,corresponding credit strategies are proposed for banks.

In silico Prediction and Analysis of Potential Off-Targets and Off-Target Mutation Detection in StERF3-Gene Edited Potato Plants

The imperative aspect of the CRISPR/Cas9 system is a short stretch of 20 nucleotides of gRNA that control the overall specificity.Due to the small size,the chance of its multiple occurrences in the genome increases;however,a few mismatches are tolerated by the Cas9 endonuclease activity.An accurate and careful in silico-based off-target prediction while target selection is preferred to address the issue.These predictions are based on a comprehensive set of selectable parameters.Therefore,we investigated the possible off-target prediction and their screening in StERF3 gene-edited potato plants while developing StERF3-loss-of-function mutants using CRISPR/Cas9 approach.The 201 off-targets for the selected targets of the StERF3 gene were predicted,and 79 werefiltered as potential off-targets.Of these 79,twenty-five off-targets showed scores with defined cut-off values<0.5 and were analyzed in Sterf3-edited potato plants compared to wild-type plants.No off-targeting was found to have occurred in edited plants.