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Roy, Uttam Kumar
- An Elucidation of the Major Symptoms Treated by Self-medication of Pain Relieving and H1 Antihistaminic Drugs in Bangladesh
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Authors
Affiliations
1 Department of Pharmacy, State University of Bangladesh, Dhanmondi, Dhaka-1205, BD
2 Department of Pharmacy, Northern University of Bangladesh, Dhaka-1215, BD
1 Department of Pharmacy, State University of Bangladesh, Dhanmondi, Dhaka-1205, BD
2 Department of Pharmacy, Northern University of Bangladesh, Dhaka-1215, BD
Source
Indian Journal of Drugs and Diseases, Vol 1, No 6 (2012), Pagination: 161-167Abstract
As we move towards a culture of increased self-management of minor illness, the demonstrated need for improved pharmacovigilance of non-prescribed medicines must be addressed. Hence, the objectives of this paper are to present data on the self-reported use of prescribed and over-the-counter pain relieving agents and H1-antihistaminic drugs among general people and to examine factors associated with the use of prescribed drugs, over-the-counter painkillers and cough, cold and allergy treatments. Aspirin was significantly more self medicated for headache and Diclofenac for pain than other symptoms. Paracetamol, Pizotifen, Tramadol, Chlorphenamine and Promethazine were significantly more used in fever, migraine, fever, cold and cough respectively rather than other symptoms. Loratadine, Desloratadine and Cetirizine were significantly more used in allergy rather than other symptoms. The medicines having higher popularity i.e. acquaintance rate showed higher self-medication rate. The statistics presented here can be a useful probe for law enforcers and public health campaigns.Keywords
Self-medication, Pain Relieving, H1 Antihistaminic DrugsFull Text
References
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- Modified PSOLA-Genetic Algorithm Based Approach for Voice Re-Construction
Abstract Views :273 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science & Engineering, Jaypee University of Engineering & Technology, Guna, Madhya Pradesh, IN
2 Department of Information Technology, Jadavpur University, Kolkata, West Bengal, IN
1 Department of Computer Science & Engineering, Jaypee University of Engineering & Technology, Guna, Madhya Pradesh, IN
2 Department of Information Technology, Jadavpur University, Kolkata, West Bengal, IN
Source
Journal of Network and Information Security, Vol 2, No 1 (2014), Pagination: 14-21Abstract
The process by which we try to reconstruct or regenerate a voice sample from a source sample or try to modify a source voice to a desirable voice, is called synthetic voice generation or artificial voice or voice conversion. The basic and conventional remedies to overcome this issue are based on training and applying conversion functions which generally require a suitable amount of pre-stored training data from both the source and the target speaker. The paper deals with a very crucial issue of achieving the required prosody, timber and some other unique voice templates by considerably reducing the dependence on the sample training dataset of voice. We needed to find out a way by which we can have templates of the "to be achieved voice" which are nearly same parametrically. This is achieved by assigning a marker to the target voice sample for training. A proper estimation of the transformation function can be made possible only by the above mentioned data. We can get the process done by pre-existing methods. In a nutshell, what we proposed is a system by which even in the scarce availability of training dataset, we can reach to a considerable amount of closeness of the target voice. Even though there is a disadvantage that to have higher precision and closer resemblance, we need to have clear idea of the system of spelling that a language uses.Keywords
Artificial Voice, Prosody, Timber, Source Voice, Target Voice, Formant Structure.
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