Accuracy Improvement of Attitude Determination Systems Using EKF-Based Error Prediction Filter and PI Controller

Accurate attitude and heading reference system (AHRS) play an essential role in navigation applications and human body tracking systems. Using low-cost microelectromechanical system (MEMS) inertial sensors and having accurate orientation estimation, simultaneously, needs optimum orientation methods and algorithms. The error of attitude estimation may lead to imprecise navigation and motion capture results. This paper proposed a novel intermittent calibration technique for MEMS-based AHRS using error prediction and compensation filter. The method, inspired from the recognition of gyroscope’s error and by a proportional integral (PI) controller, can be regulated to increase the accuracy of the prediction. The experimentation of this study for the AHRS algorithm, aided by the proposed prediction filter, was tested with real low-cost MEMS sensors consists of accelerometer, gyroscope, and magnetometer. Eventually, the error compensation was performed by post-processing the measurements of static and dynamic tests. The experimental results present about 35% accuracy improvement in attitude estimation and demonstrate the explicit performance of proposed method.

Continuous Telugu Speech Recognition On T-LPC and DNN Techniques

This paper deals with the basic application speech recognition. There are many languages in the world but one of the regional language is Telugu. Recognition of this language helps in many applications for 8 crores of people stay in AP and Telangana states. Recognition is done by recording the speech signals and database creation. Pre-processing is done by 2 stage DNN (seep neural networks) where denoising, framing is done. The preprocessed signal features are extracted using TLPC(teager energy operator linear prediction filter). The features extracted are classified using DNN which generates adequate results. The results are obtained for continuous speech of Telugu language

PROSPECTIVE BIOLOGICAL ACTIVE COMPOUNDS AMONG 7-SUBSTITUTED OF 3-BENZYL-8-PROPYLXANTHINES FOR TREATMENT OF METABOLIC SYNDROME PATHOLOGIES

Aim – the search for biologically active compounds with diuretic and hypoglycemic action among 7-substituted of 3-benzyl-8-propylxanthines, which can be used for the treatment of pathologies of “metabolic syndrome”. Materials and methods. 30 new chemical compounds among derivatives of 7-substituted of 3-benzyl-8-propylxanthines by PASS prediction filter were chosen for diuretic and hypoglycemic activity researches. Diuretic, hypoglycemic activity and for the most active compounds – the acute toxicity were studied in vivo. The molecular docking, which is based on EADock DSS mechanism of the modulation displayed the interaction between some of functional groups inside discovered xanthine ligands and known receptors and enzymes presented in Ligand-protein Database of Swiss Institute of Bioinformatics. Results. It has been shown that synthesized compounds displayed strong diuretic and medium hypoglycemic activities. The molecular docking modulation (SwissDock) of interaction of xanthine derivatives hits with proposed receptors and enzymes revealed prospective of using 7-substituted of 3-benzyl-8-propylxanthines as potential drugs for treatment of metabolic syndrome pathologies. Conclusion. The diuretic activity of the new 23 compounds of 7-substituted of 3-benzyl-8-propylxanthines and hypoglycemic activity of the new 7 derivatives of 7-substituted of 3-benzyl-8-propylxanthines was studied. Results of performed investigation illustrate that 7-substituted of 3-benzyl-8-propylxanthines demonstrate biological activity comparable to standard drugs. We also proposed probable molecular targets for the most active compounds by molecular docking method. It was shown that derivatives of 7-substituted of 3-benzyl-8-propylxanthines can be used for metabolic syndrome disorders prevention.