scholarly journals Continuous Release of Data Streams under both Centralized and Local Differential Privacy

2021 ◽  
Author(s):  
Tianhao Wang ◽  
Joann Qiongna Chen ◽  
Zhikun Zhang ◽  
Dong Su ◽  
Yueqiang Cheng ◽  
...  
Keyword(s):  
Data Streams ◽  
Differential Privacy ◽  
Continuous Release

Effect of coating method on release of Glimepiride from porosity osmotic pump tablets (POPTs)

2020 ◽  
pp. 37-45
Keyword(s):  
In Vitro Release ◽  
Osmotic Pump ◽  
Release Time ◽  
Once Daily ◽  
Coating Solution ◽  
Continuous Release ◽  
Red Color ◽  
Coating Method ◽  
Osmotic Agent

In this study, once-daily porosity osmotic pump tablets (POPTs) of Glimepiride were prepared using HPMC K100M (61%), osmotic agent (30% NaCl) coated using two different coating techniques spraying and dipping methods. The coating solution composed of ethyl cellulose (7.5%) w\w in ethanol (90%), castor oil (2%) as water-insoluble plasticizer and Gingo red color (0.5% w\w). In both techniques, the coating level was adjusted to give a 10% increase in the weight of the tablets. The effect of the coating by dipping technique with an increase in the weight of tablet (10 %, 20% & 50%) was also investigated to see the effect coating level on the percentage of drug release from POPTs. The results of the in vitro release of Glimepiride from tablets coated by the spraying method showed longer release time (24 hrs) than those coated with dipping method. On the other hand, increasing the coating level by dipping method retarded the release of the drug from tablets. However, the same retardation effect on release as shown with the spraying technique was only obtained by increasing the coating level with a 50% increase in the weight of the tablet. Thus, coating by spraying is more efficient to prepare POPTs to give a continuous release of Glimepiride from once daily table with the lowest increase in the total weight of the tablet.

Improved Macro-clusters generation using Top-k shared Micro-clusters in Data Streams

2017 ◽  
Vol 7 (10) ◽  
pp. 52
Author(s):  
LAKSHMI PRANEETHA
Keyword(s):  
Real Time ◽  
Data Streams ◽  
Bloom Filter ◽  
Scientific Applications ◽  
Pruning Algorithm ◽  
Density Data ◽  
Data Points ◽  
Short Time ◽  
Information Streams

Now-a-days data streams or information streams are gigantic and quick changing. The usage of information streams can fluctuate from basic logical, scientific applications to vital business and money related ones. The useful information is abstracted from the stream and represented in the form of micro-clusters in the online phase. In offline phase micro-clusters are merged to form the macro clusters. DBSTREAM technique captures the density between micro-clusters by means of a shared density graph in the online phase. The density data in this graph is then used in reclustering for improving the formation of clusters but DBSTREAM takes more time in handling the corrupted data points In this paper an early pruning algorithm is used before pre-processing of information and a bloom filter is used for recognizing the corrupted information. Our experiments on real time datasets shows that using this approach improves the efficiency of macro-clusters by 90% and increases the generation of more number of micro-clusters within in a short time.

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