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RISS 인기검색어
- 검색키워드
- 저자 : K. Swapna (검색결과 5 건)
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Price Forecasting on a Large Scale Data Set using Time Series and Neural Network Models
Preetha K G,K R Remesh Babu,Sangeetha U,Rinta Susan Thomas,Saigopika,Shalon Walter,Swapna Thomas 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.12
Environment, price, regulation, and other factors influence the price of agricultural products, which is a social signal of product supply and demand. The price of many agricultural products fluctuates greatly due to the asymmetry between production and marketing details. Horticultural goods are particularly price sensitive because they cannot be stored for long periods of time. It is very important and helpful to forecast the price of horticultural products which is crucial in designing a cropping plan. The proposed method guides the farmers in agricultural product production and harvesting plans. Farmers can benefit from long-term forecasting since it helps them plan their planting and harvesting schedules. Customers can also profit from daily average price estimates for the short term. This paper study the time series models such as ARIMA, SARIMA, and neural network models such as BPN, LSTM and are used for wheat cost prediction in India. A large scale available data set is collected and tested. The results shows that since ARIMA and SARIMA models are well suited for small-scale, continuous, and periodic data, the BPN and LSTM provide more accurate and faster results for predicting well weekly and monthly trends of price fluctuation.
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Diabetes detection using deep learning algorithms
Swapna G.,Vinayakumar R.,Soman K.P. 한국통신학회 2018 ICT Express Vol.4 No.4
Diabetes is a metabolic disease affecting a multitude of people worldwide. Its incidence rates are increasing alarmingly every year. If untreated, diabetes-related complications in many vital organs of the body may turn fatal. Early detection of diabetes is very important for timely treatment which can stop the disease progressing to such complications. RR-interval signals known as heart rate variability (HRV) signals (derived from electrocardiogram (ECG) signals) can be effectively used for the non-invasive detection of diabetes. This research paper presents a methodology for classification of diabetic and normal HRV signals using deep learning architectures. We employ long short-term memory (LSTM), convolutional neural network (CNN) and its combinations for extracting complex temporal dynamic features of the input HRV data. These features are passed into support vector machine (SVM) for classification. We have obtained the performance improvement of 0.03% and 0.06% in CNN and CNN-LSTM architecture respectively compared to our earlier work without using SVM. The classification system proposed can help the clinicians to diagnose diabetes using ECG signals with a very high accuracy of 95.7%.
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Swapna S. Khadanga,Ashaq Ahmad Dar,Neha Jaiswal,Prasad K. Dash,Shanmuganathan Jayakumar 국립중앙과학관 2023 Journal of Asia-Pacific Biodiversity Vol.16 No.3
Tropical mountain forests in Eastern Ghats provide a unique opportunity to relate environmental driversto plant community structure along elevation gradient. We aimed to investigate the tree diversity,composition and stand structure along elevation gradient and drivers facilitating species distributionacross Mahendragiri Hill Forest (MHF) in Eastern Ghats of Odisha, India. Altogether 120 plots of 0.05 hawere established and stems 10 cm diameter at breast height were measured. We compared speciescomposition and stand structure among elevation zones. Ordination analysis was used to quantify howcommunity structure was related to topographic, climatic and onsite conditions. In total 189 speciesrepresenting 131 genera and 51 families were recorded ranging from 64 (MHF6) to 106 species (MHF4). Fabaceae representing 23 species, followed by Phyllanthaceae was dominant families. Maximum treedensity and basal area were enumerated in high elevation MHF6 and least disturbed MHF5, respectively. Canonical Correspondence Analysis (CCA) interpreted 58.59% of variation and depicted the role ofelevation followed by disturbance and precipitation in species distribution patterns. Variance parti tioning analysis shows that topography and disturbance strongly partitioned the dissemination of treespecies. Variations in species diversity reflects a direct coupling or interaction of several factors together,making it a complex phenomenon.
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Design, Synthesis and Biological Evaluation of Novel Analogs of Bortezomib
Rao, R. Janaki Rama,Rao, A.K.S. Bhujanga,Swapna, K.,Rani, B. Baby,Kumar, S. Prasanna,Awantika, S.,Murthy, Y.L.N. Korean Chemical Society 2011 대한화학회지 Vol.55 No.5
Novel analogs of bortezomib were designed, synthesized and in vitro biological evaluation was carried out using human tumor cell lines A549 and PC3. Docking studies of these analogs of bortezomib was discussed. According to biological investigations, the inhibitors 4, 6, and 8 were found to be more potent than reference drug candidate bortezomib. A549 cell line showed significant sensitivity towards 4, 6, and 8 with $IC_{50}$ values 14.03, 18.5, and 12.4 nM, respectively, and PC3 cell line showed IC50 values 26.1, 37.0, and 21.2 nM, respectively. The $IC_{50}$ values of bortezomib in these cell lines are 27.3 nM and 42.0 nM.
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V. V. Sathibabu Uddandrao,Brahmanaidu Parim,P. R. Nivedha,K. Swapna,P. Rameshreddy,S. Vadivukkarasi,Mustapha Shabana Begum,Saravanan Ganapathy 경희대학교 융합한의과학연구소 2019 Oriental Pharmacy and Experimental Medicine Vol.19 No.3
Pomegranate (Punica granatum Linn), has been widely used in India’s ancient Ayurveda system of traditional medicine which is commonly portrayed as a constituent in remedies. The present study was aimed to investigate the anticancer activity of the aqueous extract of P. granatum fruits (PGET) against ehrlich-ascites-carcinoma (EAC)-bearing Swiss albino mice. The PGET were administered to EAC bearing mice at the doses of 100, 200 and 400 mg/kg body weight (BW) intraperitonially for 14 successive days and 24 h of last dose and 18 h of fasting, the mice were sacrifced and the anticancer efect of PGET was appraised by evaluating tumor volume, viable, nonviable tumor cell count, tumor weight, hematological, biochemical parameters and histopathological changes of EAC mice. PGET showed momentous decrease in tumor volume, viable cell count, tumor weight and elevated the life span of EAC bearing mice. Hematological profle such as RBC, hemoglobin and lymphocyte count reverted to normal level in PGET treated mice. The extract at 400 mg/kg BW showed a noteworthy reduction in the level of lipid peroxidation and considerably increased the levels of antioxidant enzymes in the liver and observed signifcant restoration of histopathological changes in experimental animals. Hence, the current study revealed that the PGET was efcient in inhibiting the tumor growth in ascitic models and that is comparable to 5-Fluorouracil. The anticancer properties of P. granatum could be due to the presence of the various phytoconstituents in it.
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