Refinery wastewater most often contains hydrocarbons, spent catalyst and acid as well as soluble bases used as raw materials and treatment reagents. Most of these pollutants, which often include toxic, hazardous and priority pollutants, accounts for between 0.5-15% weight of the process wastewater [Bhatnaga and Minocha, 2009; Girish and Murty, 2013]. The need to comply with environmental regulations require that such pollutants be removed to an acceptable level

A face recognition system for automatic door access control has been developed in this work with a view to providing a relatively more robust and foolproof access control which can provide better security and reduce human errors inherent in other conventional methods. The system was designed with machine learning and artificial intelligence to capture faces, train faces with machine mode, and run trained faces to grant access to the user. The system uses the RaspberryPi module, camera module, servo motor and the GSM module which were all incorporated into the fabricated building to make up the prototype developed to provide access control by means of facial biometrics. In order to grant access to registered users, various photos of the users were taken in different positions and expressions with proper illumination. The user’s face is been captured by the camera module and saved in the database with the help of Raspberry Pi Module. Good lighting condition and other favorable conditions helps the camera module to recognize faces and sends signal to the Raspberry Pi which processes these images and opens the door with the help of the servo motor. The developed prototype was used to train fifty (50) users. It granted access to all fifty (50) users when there was proper illumination and pose but five (5) and nine (9) users respectively were denied access due to challenges of poor illumination and pose variation.

The need to drastically reduce the delay faced by patients before they receive treatment in the University Clinic and the need to reduce the occurrence of medical mistakes due to patient’s misidentification led to this work which aimed at developing a hospital biometric data management system.Java was the programming language of choice and Netbeans was the Integrated Development Environment (IDE) used to design the Graphical User Interphase (GUI) and write codes. For the backend database, MySQL was used for demonstration purposes. The analytical diagrams were drawn using VioletUMLEdit. The Griaule Fingerprint Software Development Kit (SDK) was used to implement the fingerprint capture, enrollment, identification and verification features of the software.The tests and results obtained showed that with this hospital management system, the time taken to retrieve patient’s record has been reduced from several minutes to less than five seconds thereby eliminating the delay experienced by patients during search of their records. The problem of medical mistakes due to patient’s misidentification was also addressed by the biometric feature of the management system.

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