An Optimized Multiple Fuzzy Membership Functions based Image Contrast Enhancement Technique

( Pushpa Mamoria ),( Deepa Raj ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.3

Image enhancement is an emerging method for analyzing the images clearer for interpretation and analysis in the spatial domain. The goal of image enhancement is to serve an input image so that the resultant image is more suited to the particular application. In this paper, a novel method is proposed based on Mamdani fuzzy inference system (FIS) using multiple fuzzy membership functions. It is observed that the shape of membership function while converting the input image into the fuzzy domain is the essential important selection. Then, a set of fuzzy If-Then rule base in fuzzy domain gives the best result in image contrast enhancement. Based on a different combination of membership function shapes, a best predictive solution can be determined which can be suitable for different types of the input image as per application requirements. Our result analysis shows that the quality attributes such as PSNR, Index of Fuzziness (IOF) parameters give different performances with a selection of numbers and different sized membership function in the fuzzy domain. To get more insight, an optimization algorithm is proposed to identify the best combination of the fuzzy membership function for best image contrast enhancement.

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.

Co-culture with NK-92MI cells enhanced the anti-cancer effect of bee venom on NSCLC cells by inactivation of NF-jB

Pushpa Saranya Kollipara,김정현,원도희,이상민,성하정,장현석,이강태,이강식,박미희,송민종,송호섭,홍진태 대한약학회 2014 Archives of Pharmacal Research Vol.37 No.3

In the present study we experimented on amultimodal therapeutic approach, such as combining chemotherapyagent (Bee venom) with cellular (NK-92MI)immunotherapy. Previously bee venom has been found toshow anti-cancer effect in various cancer cell lines. In lungcancer cells bee venom showed an IC50 value of 3 lg/ml inboth cell lines. The co-culture of NK-92MI cell lines withlung cancer cells also show a decrease in viability upto50 % at 48 h time point. Hence we used bee venom treatedNK-92MI cells to co-culture with NSCLC cells and foundthat there is a further decrease in cell viability upto 70 and75 % in A549 and NCI-H460 cell lines respectively. Wefurther investigated the expression of various apoptotic andanti-apoptotic proteins and found that Bax, cleaved caspase-3 and -8 were increasing where as Bcl-2 and cIAP-2was decreasing. The expression of various death receptorproteins like DR3, DR6 and Fas was also increasing. Concomitantly the expression of various death receptorligands (TNFalpha, Apo3L and FasL) was also increasing of NK-92MI cells after co-culture. Further the DNAbinding activity and luciferase activity of NF-jB was alsoinhibited after co-culture with bee venom treated NK-92MIcell lines. The knock down of death receptors with si-RNAhas reversed the decrease in cell viability and NF-jBactivity after co-culture with bee venom treated NK-92MIcells. Thus this new approach can enhance the anti-cancereffect of bee venom at a much lower concentration.

Binarized Spiking Neural Networks Optimized with Color Harmony Algorithm for Liver Cancer Classification

Pushpa Balakrishnan,B. Baskaran,S. Vivekanan,P. Gokul 대한전자공학회 2023 IEIE Transactions on Smart Processing & Computing Vol.12 No.6

Binarized spiking neural networks optimized with a color harmony algorithm for liver cancer classification (BSNN-CHA-LCC) are proposed to classify liver cancer as normal and abnormal. Initially, fusion of an MRI dataset and CT-scan datasets of a liver cancer dataset were taken, and the input images were given to CWF-based preprocessing for removing noise and increasing the quality of input computed tomography (CT) and magnetic resonance imaging (MRI). The preprocessed images of CT and MRI are given to improve the non-sub sampled Shearlet transform (INSST) method-based feature extraction for extracting features. The extracted features were given BSNN to classify liver cancer as normal and abnormal. The proposed method was implemented, and the efficiency of the proposed BSNN-CHA-LCC method was evaluated under performance metrics, such as precision, sensitivity, F-scores, specificity, accuracy, error rate, and computational time. The proposed technique achieved23.03%, 11.56%, and 21.22% higher accuracy and 36.12%, 15.23%, and 27.11% lower error rates than the existing models, such as hybrid-feature analysis depending on machine-learning for liver cancer categorization utilizing fused images (MLP-LCC), Deep learning-based classification of liver cancer histopathology images utilizing only global labels (mask-RCNN-LCC), and deep learning based liver cancer identification utilizing watershed transform and Gaussian mixture method (DNN-GMM-LCC), respectively.

Load Frequency Control of Hybrid Power System Incorporating Vehicle‑to‑Grid Technology Considering AC Transmission Links

Pushpa Gaur,Nirmala Soren,Debashish Bhowmik 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.1

In modern power system, the participation of Vehicle-to-grid (V2G) in contributing to ancillary services like frequency regulation is probable to increase due to their fast charging/discharging capabilities. Renewable energy sources (RES) also play an important role in meeting the power demand and indirectly, minimizing the utilization of fossil fuels by the conventional power plants, but their behavior is very intermittent in nature which may cause frequency fuctuations. V2G technology can be used for meeting the imbalance in demand and generation. In view of these points, this paper proposes a load frequency control scheme with the participation of RES and V2G which can enhance the system dynamics under load fuctuations. For this, a multi-source system is designed with a solar-thermal power plant (STPP) and a thermal unit in Area-1, gas and thermal unit along with an electric vehicle (EV) feet in Area-2, and two thermal units and an EV feet in Area-3. The application of wind driven optimized two degree of freedom proportional–integral–derivative controller as secondary controller has been attempted in this work. The impact of addition of STPP and EVs into the system is verifed in terms of reduction of magnitude and numbers of oscillations of the system responses.

In-silico elucidation of phytoconstituents against 1LPB protein and anti-dyslipidaemic activity of Psoralea corylifolia Linn leaf extract

Pushpa A. Karale,Shashikant C. Dhawale,Mahesh A. Karale 경희대학교 융합한의과학연구소 2023 Oriental Pharmacy and Experimental Medicine Vol.23 No.4

Psoralea corylifolia L. has been used in traditional Chinese and Ayurvedic medicine systems for management of various diseases. The various phytochemical constituents work in orchestric manner to treat diverse illnesses. Current pharmacotherapies shown beneficiary role in treatment of dyslipidaemia but facing life threatening side effects. The usage of herbs increased worldwide and paves the way for development of pharmaceuticals for hyperlipidemia treatment. The main objective of present work was to investigate anti-hyperlipidemic activity and in-silico pancreatic lipase inhibitory potential of Psoralea corylifolia L. (PC) leaf extract. The existence of several phytoconstituents was confirmed by the chromatographic research and mainly includes the flavonoids and furanocoumarins. All studied phytoconstituents were found to have superior binding affinity than standard orlistat (− 7.1 kcal/mol), with docking score ranges from − 10.6 to − 7.3 kcal/mol. At 200 mg/ kg/day the ethanolic leaf extract demonstrated highest lipid lowering action. Ethanolic leaf extract of Psoralea corylifolia revealed evidential antihyperlipidemic potential in a concentration dependent manner (P < 0.01). The serum lipid profile (LDL, VLDL, TG, TC) dropped firmly and HDL elevated in hyperlipidemic rats treated with plant extract compared with the hyperlipidemic group rats (P < 0.01). The hepatic TC and TG abruptly increased in hyperlipidemic rats and significantly reduced in hyperlipidemic rats administered with EPC compared with the control group (P < 0.01). The hyperlipidemic rats treated with atorvastatin and PC at different doses shown evidentiary increase in secretion of TC and TG compared with the hyperlipidemic group rats. The study results proposed that EPC leaf extract demonstrated noteworthy antihyperlipidemic action. The findings of docking study recommend utilization of the best ligands experimentally to develop novel anti-obesity agents. Psoralea corylifolia L. has been used in traditional Chinese and Ayurvedic medicine systems for management of various diseases. The various phytochemical constituents work in orchestric manner to treat diverse illnesses. Current pharmacotherapies shown beneficiary role in treatment of dyslipidaemia but facing life threatening side effects. The usage of herbs increased worldwide and paves the way for development of pharmaceuticals for hyperlipidemia treatment. The main objective of present work was to investigate anti-hyperlipidemic activity and in-silico pancreatic lipase inhibitory potential of Psoralea corylifolia L. (PC) leaf extract. The existence of several phytoconstituents was confirmed by the chromatographic research and mainly includes the flavonoids and furanocoumarins. All studied phytoconstituents were found to have superior binding affinity than standard orlistat (− 7.1 kcal/mol), with docking score ranges from − 10.6 to − 7.3 kcal/mol. At 200 mg/ kg/day the ethanolic leaf extract demonstrated highest lipid lowering action. Ethanolic leaf extract of Psoralea corylifolia revealed evidential antihyperlipidemic potential in a concentration dependent manner (P < 0.01). The serum lipid profile (LDL, VLDL, TG, TC) dropped firmly and HDL elevated in hyperlipidemic rats treated with plant extract compared with the hyperlipidemic group rats (P < 0.01). The hepatic TC and TG abruptly increased in hyperlipidemic rats and significantly reduced in hyperlipidemic rats administered with EPC compared with the control group (P < 0.01). The hyperlipidemic rats treated with atorvastatin and PC at different doses shown evidentiary increase in secretion of TC and TG compared with the hyperlipidemic group rats. The study results proposed that EPC leaf extract demonstrated noteworthy antihyperlipidemic action. The findings of docking study recommend utilization of the best ligands experimentally to develop novel anti-obesity agents. Keywords Psoralea

Numerical study of double-diffusive convection in a vertical annular enclosure with a baffle

Pushpa, B V,Prasanna, B M R,Younghae, Do,Sankar, M. Institute of Physics Publishing Ltd 2017 Journal of Physics: Conference Series Vol.908 No.-

Concentration Building System for Children with Attention Deficit Hyperactivity Disorder

Pushpa Kotipalli,Murali Krishna Doma 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.11

Children with Attention deficit hyperactivity disorder (ADHD) experience lack of concentration. In learning process, the concentration power of the students with ADHD should be increased first. Concentration building systems for them are not available in market. This paper proposes a concentration building system for children with ADHD. It consists of three modules-Bird chirping module, Fish tank module and Alphabet learning module. At first the child is encouraged to press switch corresponding to bird chirping module; it soothes his hyperactive mind. This creates interest in pressing the switch related to next module, that is, fish tank module. Tthe movement of different types of fishes makes the child to stare deeply into the screen and can learn counting them. This activity based learning further improves his concentration power. The third one, Alphabet learning module can be further used to enhance his alphabet learning skills. Individual modules are developed using the microcontrollers MSP430G2553 and PIC16F877A. The proposed system improves the concentration power of the child which in turn improves his cognitive skills.

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.

The Non-Motor Symptom Profile of Progressive Supranuclear Palsy

Sudhakar Pushpa Chaithra,Shweta Prasad,Vikram Venkappayya Holla,Albert Stezin,Nitish Kamble,Ravi Yadav,Pramod Kumar Pal 대한파킨슨병및이상운동질환학회 2020 Journal Of Movement Disorders Vol.13 No.2

ObjectiveaaNon-motor symptoms (NMSs) significantly contribute to increased morbidity and poor quality of life in patients withparkinsonian disorders. This study aims to explore the profile of NMSs in patients with progressive supranuclear palsy (PSP) usingthe validated Non-Motor Symptom Scale (NMSS). MethodsaaSeventy-six patients with PSP were evaluated in this study. Motor symptoms and NMSs were evaluated using the PSPRating Scale (PSPRS), Unified Parkinson’s Disease Rating Scale-III, Montreal Cognitive Assessment, Hamilton Depression (HAMD)and Anxiety Rating Scales, Parkinson’s Disease Sleep Scale (PDSS) and NMSS. NMS severity and prevalence were also comparedbetween patients with PSP-Richardson syndrome (PSP-RS) and those with PSP-parkinsonism. ResultsaaAll subjects in this cohort reported at least 2 NMSs. The most prevalent NMSs in patients with PSP were in the domainsof sleep/fatigue, mood/cognition, and sexual function. The least prevalent NMSs were in the domains of cardiovascular includingfalls, and perceptual problems/hallucinations. Significant correlations were observed between the NMSS scores and HAM-D,PDSS, PSPRS scores and PSPRS sub-scores. The severity of NMSs was unrelated to the duration of illness. Patients with PSP-RSreported a higher severity of drooling, altered smell/taste, depression and altered interest in sex and a higher prevalence of sexualdysfunction. ConclusionaaNMSs are commonly observed in patients with PSP, and the domains of sleep, mood and sexual function aremost commonly affected. These symptoms contribute significantly to disease morbidity, and clinicians should pay adequate attentionto identifying and addressing these symptoms.