Control strategy and methods for continuous direct compression processes

We presented a control strategy for tablet manufacturing processes based on continuous direct compression.The work was conducted by the experts of pharmaceutical companies,machine suppliers,academia,and regulatory authority in Japan.Among different items in the process,the component ratio and blended powder content were selected as the items requiring the control method specific to continuous manufacturing different from the conventional batch manufacturing.The control and management of the Loss in Weight(LIW)feeder were deemed the most important,and the Residence Time Distribution(RTD)model were regarded effective for setting the control range and for controlling of the LIW feeder.Based on these ideas,the concept of process control using RTD was summarized.

Rough set-based rule generation and Apriori-based rule generation from table data sets II: SQL-based environment for rule generation and decision support

This study follows the previous study entitled‘Rough set-based rule generation and Apriori-based rule generation from table data sets:A survey and a combination’,and this is the second study on‘Rough set-based rule generation and Apriori-based rule generation from table data sets’.The theoretical aspects are described in the previous study,and here the aspects of application,an SQL-based environment for rule generation and decision support,are described.At first,the implementation of rule generator defined in the previous study is explained,then the application of the obtained rules to decision support is considered.Especially,the following two issues are focused on,(i)Rule generator from table data sets with uncertainty in SQL,(ii)The manipulation in decision support below:(ii-a)In the case that an obtained rule matches the condition,(ii-b)In the case that any obtained rule does not match the condition.The authors connect such cases with decision support and realised an effective decision support environment in SQL.

Rough set-based rule generation and Apriori-based rule generation from table data sets: a survey and a combination

The authors have been coping with new computational methodologies such as rough sets,information incompleteness,data mining,granular computing,etc.,and developed some software tools on association rules as well as new mathematical frameworks.They simply term this research Rough sets Non-deterministic Information Analysis(RNIA).They followed several novel types of research,especially Pawlak’s rough sets,Lipski’s incomplete information databases,Or?owska’s non-deterministic information systems,Agrawal’s Apriori algorithm.These are outstanding researches related to information incompleteness,data mining,and rule generation.They have been trying to combine such novel researches,and they have been trying to realise more intelligent rule generator handling data sets with information incompleteness.This study surveys the authors’research highlights on rule generators,and considers a combination of them.

Rule induction based on rough sets from information tables having continuous domains

Information tables having continuous domains are handled by neighborhood rough sets.Two approximations in complete information tables are extended to handle incomplete information.Consequently,four approximations are obtained:certain and possible lower ones and certain and possible upper ones without computational complexity.These extended approximations create the same results as the ones from possible world semantics by using possible indiscernibility relations.Therefore,the extension is justified.In complete information tables two types of single rules that an object supports are obtained:consistent and inconsistent ones.The single rule has low applicability.To increase applicability,a series of single rules are brought into one combined rule with an interval value.In incomplete information tables four kinds of single rules are obtained.From them,four kinds of combined rules are obtained:certain and consistent,possible and consistent,certain and inconsistent,and possible inconsistent ones.A combined rule has higher applicability than the single rules from which it is assembled.

Guest Editorial: Rough Sets and Data Mining

A rough set,first described by Polish computer scientist Zdzis?aw Pawlak,is a formal approximation of a crisp set,and it is now known as a new mathematical tool to process vague concepts.They are used for machine learning,knowledge discovery,feature selection,etc.,and are applied to artificial intelligence,medical informatics,civil engineering,Kansei engineering,decision science,business administration,and so on.Especially,research on data mining using rough sets is widely spreading,and the obtained association rules are applied to the characterisation of data and decision support.

Simultaneous removal of dissolved organic matter and bromide from drinking water source by anion exchange resins for controlling disinfection by-products

Anion exchange resins （AERs） with different properties were evaluated for their ability to remove dissolved organic matter （DOM） and bromide, and to reduce disinfection by-product （DBP） formation potentials of water collected from a eutrophic surface water source in Japan. DOM and bromide were simultaneously removed by all selected AERs in batch adsorption experiments. A polyacrylic magnetic ion exchange resin （MIEX） showed faster dissolved organic carbon （DOC） removal than other AERs because it had the smallest resin bead size. Aromatic DOM fractions with molecular weight larger than 1600 Da and fluorescent organic fractions of fulvic acid- and humic acid-like compounds were efficiently removed by all AERs. Polystyrene AERs were more effective in bromide removal than polyacrylic AERs. This result implied that the properties of AERs, i.e. material and resin size, influenced not only DOM removal but also bromide removal efficiency, MIEX showed significant chlorinated DBP removal because it had the highest DOC removal within 30 rain, whereas polystyrene AERs efficiently removed brominated DBPs, especially brominated trihalomethane species. The results suggested that, depending on source water DOM and bromide concentration, selecting a suitable AER is a key factor in effective control of chlorinated and brominated DBPs in drinking water.

Effects of Freestream Turbulence on Bypass Transition of Separated Boundary Layer on Low-Pressure Turbine Airfoils

This paper presents experimental studies on bypass transition of separated boundary layer on low-pressure turbine airfoils,focusing on the effects of freestream turbulence on the transition process.Hot-wire probe measurements are performed on the suction side of an airfoil in the low-pressure linear turbine cascade at several Reynolds number conditions.Freestream turbulence is enhanced by use of turbulence grid located upstream of the cascade.The results of this experimental study show that the location of boundary layer separation does not strongly de-pend on the freestream turbulence level.However,as the freestream turbulence level increases,the size of separa-tion bubble becomes small and the location of turbulent transition moves upstream.The size of separation bubble becomes small as the Reynolds number increases.At low freestream turbulence intensity,the velocity fluctuation due to Kelvin-Helmholtz instability is observed clearly in the shear layer of the separation bubble.At high frees-tream turbulence intensity,the streak structures appear upstream of the separation location,indicating bypass transition of attached boundary layer occurs at high Reynolds number.