Abstract: The invention relates to the field of air purification, sterilization, disinfection, sanitization, removal of particulate matter and harmful gases. A UV light source(102), which is preferably positioned parallel to the flow of air ensuring continuous disinfection of the airstream due to increased residence time, and a filter (106) that is preferably positioned surrounding/around the UV source. In an embodiment, the invention is disclosing a self-cleaning ability that is achieved by using electrostatic fields. In another embodiment, a small, compact self-cleaning purifier/device can be used to sanitize small, enclosed spaces like cars, cabins, etc.

Abstract: An apparatus, and method for air purification and airborne microbial deactivation is described. In one embodiment, liquid is being used as a medium to attach air pollutants and deactivate microbes in the air. In one embodiment a negative charge is imparted for the formation of dense electric fields and negative ions using negative ion generators, corona discharge or plasma and using liquid as capturing media and disinfecting source; The air purification is done through a batch or a continuous process.

Abstract: The process includes receiving a data set comprising a plurality of rows and a plurality of columns, and applying a first rule based decisioning to the data set to generate a first layer of metadata that comprises at least one of a key, a type indicator, a categorical indicator, and/or a continuous indicator. The first layer of metadata may be descriptive of the data set. The processor may further apply a second rule based decisioning to the first layer to generate a second layer that includes at least one of the key, the type indicator, the categorical indicator, or the continuous indicator. The second layer may be descriptive of the first layer. The process may also include generating an output file from at least one of the first layer or the second layer.

Abstract: The process includes receiving a data set comprising a plurality of rows and a plurality of columns, and applying a first rule based decisioning to the data set to generate a first layer of metadata that comprises at least one of a key, a type indicator, a categorical indicator, and/or a continuous indicator. The first layer of metadata may be descriptive of the data set. The processor may further apply a second rule based decisioning to the first layer to generate a second layer that includes at least one of the key, the type indicator, the categorical indicator, or the continuous indicator. The second layer may be descriptive of the first layer. The process may also include generating an output file from at least one of the first layer or the second layer.

Abstract: The process includes receiving a data set comprising a plurality of rows and a plurality of columns, and applying a first rule based decisioning to the data set to generate a first layer of metadata that comprises at least one of a key, a type indicator, a categorical indicator, and/or a continuous indicator. The first layer of metadata may be descriptive of the data set. The processor may further apply a second rule based decisioning to the first layer to generate a second layer that includes at least one of the key, the type indicator, the categorical indicator, or the continuous indicator. The second layer may be descriptive of the first layer. The process may also include generating an output file from at least one of the first layer or the second layer.

Abstract: The process includes receiving a data set comprising a plurality of rows and a plurality of columns, and applying a first rule based decisioning to the data set to generate a first layer of metadata that comprises at least one of a key, a type indicator, a categorical indicator, and/or a continuous indicator. The first layer of metadata may be descriptive of the data set. The processor may further apply a second rule based decisioning to the first layer to generate a second layer that includes at least one of the key, the type indicator, the categorical indicator, or the continuous indicator. The second layer may be descriptive of the first layer. The process may also include generating an output file from at least one of the first layer or the second layer.