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Chandrakant R. Kokare,Shital C. Patil,Amol A. Tagalpallewar 한국약제학회 2019 Journal of Pharmaceutical Investigation Vol.49 No.5
Piperine is a poorly water-soluble drug and its bioavailability is a great barrier for this drug. The objective of current work was to formulate and investigate a self-microemulsifying drug delivery system (SMEDDS) of piperine as well as modification of liquid SMEDDS into the solid SMEDDS. Solubility study of piperine was performed in various excipients. Optimum composition of the microemulsion region was identified by using the pseudo-ternary phase diagram. Liquid SMEDDS formulation was optimized by Box–Behnken statistical design. The optimized liquid SMEDDS formulation showed particle size 22.12 ± 0.88 nm, PDI 0.185 ± 0.03 and transmittance 99.48 ± 0.32%. A methyl thiazolyl tetrazolium (MTT) assay was performed to determine in vitro anticancer efficacy of piperine using KB cell lines. The piperine loaded self-microemulsifying nanoparticles significantly inhibited the growth of carcinoma cells by targeting mitochondria and produced caspases-3 activity. Whereas, this mechanism showed significant role in inhibition of cancer signaling stage. The MTT assay confirmed 98.7% cytotoxicity in cancerous cells. Moreover, PXRD analysis showed the transformation of the crystalline structure of piperine to the amorphous (dissolved) state. In vitro release and ex vivo permeation of liquid and solid-SMEDDS has shown faster drug release as compared to the pure drug. The developed formulation was stable under stability conditions after 3 months of storage. Thus, the studies revealed that SMEDDS has a promising strategy for a poorly water-soluble drug, which benefits to enhance the solubility, dissolution also an anti-proliferative performance of piperine in the oral squamous carcinoma.
Hartley Transform Based Fingerprint Matching
Bharkad, Sangita,Kokare, Manesh Korea Information Processing Society 2012 Journal of information processing systems Vol.8 No.1
The Hartley transform based feature extraction method is proposed for fingerprint matching. Hartley transform is applied on a smaller region that has been cropped around the core point. The performance of this proposed method is evaluated based on the standard database of Bologna University and the database of the FVC2002. We used the city block distance to compute the similarity between the test fingerprint and database fingerprint image. The results obtained are compared with the discrete wavelet transform (DWT) based method. The experimental results show that, the proposed method reduces the false acceptance rate (FAR) from 21.48% to 16.74 % based on the database of Bologna University and from 31.29% to 28.69% based on the FVC2002 database.
Iris Recognition Using Ridgelets
Birgale, Lenina,Kokare, Manesh Korea Information Processing Society 2012 Journal of information processing systems Vol.8 No.3
Image feature extraction is one of the basic works for biometric analysis. This paper presents the novel concept of application of ridgelets for iris recognition systems. Ridgelet transforms are the combination of Radon transforms and Wavelet transforms. They are suitable for extracting the abundantly present textural data that is in an iris. The technique proposed here uses the ridgelets to form an iris signature and to represent the iris. This paper contributes towards creating an improved iris recognition system. There is a reduction in the feature vector size, which is 1X4 in size. The False Acceptance Rate (FAR) and False Rejection Rate (FRR) were also reduced and the accuracy increased. The proposed method also avoids the iris normalization process that is traditionally used in iris recognition systems. Experimental results indicate that the proposed method achieves an accuracy of 99.82%, 0.1309% FAR, and 0.0434% FRR.
Fingerprint Matching Based on Dimension Reduced DCT Feature Vectors
Bharkad, Sangita,Kokare, Manesh Korea Information Processing Society 2017 Journal of information processing systems Vol.13 No.4
In this work a Discrete Cosine Transform (DCT)-based feature dimensionality reduced approach for fingerprint matching is proposed. The DCT is applied on a small region around the core point of fingerprint image. The performance of our proposed method is evaluated on a small database of Bologna University and two large databases of FVC2000. A dimensionally reduced feature vector is formed using only approximately 19%, 7%, and 6% DCT coefficients for the three databases from Bologna University and FVC2000, respectively. We compared the results of our proposed method with the discrete wavelet transform (DWT) method, the rotated wavelet filters (RWFs) method, and a combination of DWT+RWF and DWT+(HL+LH) subbands of RWF. The proposed method reduces the false acceptance rate from approximately 18% to 4% on DB1 (Database of Bologna University), approximately 29% to 16% on DB2 (FVC2000), and approximately 26% to 17% on DB3 (FVC2000) over the DWT based feature extraction method.
Interactive Semantic Image Retrieval
Patil, Pushpa B.,Kokare, Manesh B. Korea Information Processing Society 2013 Journal of information processing systems Vol.9 No.3
The big challenge in current content-based image retrieval systems is to reduce the semantic gap between the low level-features and high-level concepts. In this paper, we have proposed a novel framework for efficient image retrieval to improve the retrieval results significantly as a means to addressing this problem. In our proposed method, we first extracted a strong set of image features by using the dual-tree rotated complex wavelet filters (DT-RCWF) and dual tree-complex wavelet transform (DT-CWT) jointly, which obtains features in 12 different directions. Second, we presented a relevance feedback (RF) framework for efficient image retrieval by employing a support vector machine (SVM), which learns the semantic relationship among images using the knowledge, based on the user interaction. Extensive experiments show that there is a significant improvement in retrieval performance with the proposed method using SVMRF compared with the retrieval performance without RF. The proposed method improves retrieval performance from 78.5% to 92.29% on the texture database in terms of retrieval accuracy and from 57.20% to 94.2% on the Corel image database, in terms of precision in a much lower number of iterations.
Fingerprint Matching Based on Dimension Reduced DCT Feature Vectors
( Sangita Bharkad ),( Manesh Kokare ) 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.4
In this work a Discrete Cosine Transform (DCT)-based feature dimensionality reduced approach for fingerprint matching is proposed. The DCT is applied on a small region around the core point of fingerprint image. The performance of our proposed method is evaluated on a small database of Bologna University and two large databases of FVC2000. A dimensionally reduced feature vector is formed using only approximately 19%, 7%, and 6% DCT coefficients for the three databases from Bologna University and FVC2000, respectively. We compared the results of our proposed method with the discrete wavelet transform (DWT) method, the rotated wavelet filters (RWFs) method, and a combination of DWT+RWF and DWT+(HL+LH) subbands of RWF. The proposed method reduces the false acceptance rate from approximately 18% to 4% on DB1 (Database of Bologna University), approximately 29% to 16% on DB2 (FVC2000), and approximately 26% to 17% on DB3 (FVC2000) over the DWT based feature extraction method.
Mohammed, A.F.,kokare, N.D.,Sangshetti, J.N.,Shinde, D.B. Korean Chemical Society 2007 대한화학회지 Vol.51 No.5
Sulphanilic Acid 촉매를 사용한 벤조인 또는 벤질, 초산암모늄 그리고 방향족 알데히드의 축합반응을 통한 간단하고 높은 수율의 2,4,5-Triarylimidazoles의 One-pot 합성에 대한 보고 값싼 가격의 촉매,높은 수율 그리고 짧은 반응 시간은 제시된 방법의 장점이다. A simple and high yielding one-pot method for synthesis of 2,4,5-triarylimidazoles from condensation of benzoin or benzil, ammonium acetate and aromatic aldehydes using sulphanilic acid catalyst is described. The lower priced catalyst, higher yields and shorter reaction time are the advantages of the presented method.
Interactive Semantic Image Retrieval
( Pushpa B. Patil ),( Manesh B. Kokare ) 한국정보처리학회 2013 Journal of information processing systems Vol.9 No.3
The big challenge in current content-based image retrieval systems is to reduce the semantic gap between the low level-features and high-level concepts. In this paper, we have proposed a novel framework for efficient image retrieval to improve the retrieval results significantly as a means to addressing this problem. In our proposed method, we first extracted a strong set of image features by using the dual-tree rotated complex wavelet filters (DT-RCWF) and dual tree-complex wavelet transform (DT-CWT) jointly, which obtains features in 12 different directions. Second, we presented a relevance feedback (RF) framework for efficient image retrieval by employing a support vector machine (SVM), which learns the semantic relationship among images using the knowledge, based on the user interaction. Extensive experiments show that there is a significant improvement in retrieval performance with the proposed method using SVMRF compared with the retrieval performance without RF. The proposed method improves retrieval performance from 78.5% to 92.29% on the texture database in terms of retrieval accuracy and from 57.20% to 94.2% on the Corel image database, in terms of precision in a much lower number of iterations.