Ofloxacin ocular inserts: Design, Formulation and Evaluation

In developing a drug delivery strategy, issues of absorption, distribution, metabolism, and elimination must be considered. The eye presents unique opportunities and challenges when it comes to the delivery of pharmaceuticals. While absorption by this route is bungling, there are few side effects with conventional ocular dosage forms. Hence, ocular inserts were prepared with prolonged release of drug and minimum swelling within cul-de-sac using ofloxacinas a model drug; and hydroxy propyl methyl cellulose, methyl cellulose, poly vinyl pyrrolidone and poly vinyl alcohol as polymers. PEG-400 was incorporated as plasticizer. The main purpose of the study was to deliver the drug in zero order kinetics. Solvent casting technique was followed to prepare ofloxacin ocular films. Eight formulations were formulated and subjected to various physicochemical evaluations. Ocular inserts prepared were smooth and passed all the evaluation tests performed. Formulation OF2 shows a maximum cumulative percentage drug release of 91.27 % at the end of 24 hours. Ocuserts formulated also passed the test for sterility. They showed zero-order release of the drug in the in vitro and in vivo release studies. The drug in the films was found to be active against selected microorganisms as was proved by microbial efficacy studies. A high correlation coefficient was found between in vitro and in vivo release rate studies. Shelf-life of the product was found to be more than one year.The results of in vitro, in vivo, kinetic treatment (zero order and Korsemeyer s regression values) and rate constant k value suggest that OF2 was the best formulation among the formulations studied for formulating ofloxacin ocular insert

Laser range finder model for autonomous navigation of a robot in a maize field using a particle filter

Autonomous navigation of robots in an agricultural environment is a difficult task due to the inherent uncertainty in the environment. Many existing agricultural robots use computer vision and other sensors to supplement Global Positioning System (GPS) data when navigating. Vision based methods are sensitive to ambient lighting conditions. This is a major disadvantage in an outdoor environment. The current study presents a novel probabilistic sensor model for a 2D range finder (LIDAR) from first principles. Using this sensor model, a particle filter based navigation algorithm (PF) for autonomous navigation in a maize field was developed. The algorithm was tested in various field conditions with varying plant sizes, different row patterns and at several scanning frequencies. Results showed that the Root Mean Squared Error of the robot heading and lateral deviation were equal to 2.4 degrees and 0.04 m, respectively. It was concluded that the performance of the proposed navigation method is robust in a semi-structured agricultural environment

Laser range finder model for autonomous navigation of a robot in a maize field using a particle filter

Autonomous navigation of robots in an agricultural environment is a difficult task due to the inherent uncertainty in the environment. Many existing agricultural robots use computer vision and other sensors to supplement Global Positioning System (GPS) data when navigating. Vision based methods are sensitive to ambient lighting conditions. This is a major disadvantage in an outdoor environment. The current study presents a novel probabilistic sensor model for a 2D range finder (LIDAR) from first principles. Using this sensor model, a particle filter based navigation algorithm (PF) for autonomous navigation in a maize field was developed. The algorithm was tested in various field conditions with varying plant sizes, different row patterns and at several scanning frequencies. Results showed that the Root Mean Squared Error of the robot heading and lateral deviation were equal to 2.4 degrees and 0.04 m, respectively. It was concluded that the performance of the proposed navigation method is robust in a semi-structured agricultural environment

Content‐based image retrieval system via sparse representation

The aim of image retrieval systems is to automatically assess, retrieve and represent relative images‐based user demand. However, the accuracy and speed of image retrieval are still an interesting topic of many researches. In this study, a new method based on sparse representation and iterative discrete wavelet transform has been proposed. To evaluate the applicability of the proposed feature‐based sparse representation for image retrieval technique, the precision at percent recall and average normalised modified retrieval rank are used as quantitative metrics to compare different methods. The experimental results show that the proposed method provides better performance in comparison with other methods