Automatic Extraction of Vertebral Endplates from Scoliotic Radiographs Using Customized Filter

Anitha H.,Karunakar A. K.,Dinesh K. V. N. 대한의용생체공학회 2014 Biomedical Engineering Letters (BMEL) Vol.4 No.2

Purpose The scoliosis diagnosing system needs radio-graphicinformation in terms of spinal curvature estimated usingCobb’s definition. The evaluation process and treatmentanalysis depends on the reliability and reproducibility of thespine curvature in the frontal view. Methods Manual identification of end vertebrae and otheranatomical features required for the estimation of spinalcurvature causes variability and unreliability at higher rate. This paper proposes an automated system to extract therequired anatomical features using customized filter. Thecustomized filter used in this paper is a combination ofanisotropic, sigmoid and differential filter. Combination ofthese filters automatically extracts the anatomical features interms of required vertebral endplates. Automatic identificationof these endplates eliminates the human intervention involvedin the quantification of Cobb angle. Results and Conclusions Analysis of the results revealssignificant difference between the observer variabilitybetween manual, computer assisted and computerized imageunderstanding system in terms of inter and intra crosscorrelation coefficient ratio (ICCR).

Empirical Investigations to Plant Leaf Disease Detection Based on Convolutional Neural Network

K. Anitha,M.Srinivasa Rao International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.6

Plant leaf diseases and destructive insects are major challenges that affect the agriculture production of the country. Accurate and fast prediction of leaf diseases in crops could help to build-up a suitable treatment technique while considerably reducing the economic and crop losses. In this paper, Convolutional Neural Network based model is proposed to detect leaf diseases of a plant in an efficient manner. Convolutional Neural Network (CNN) is the key technique in Deep learning mainly used for object identification. This model includes an image classifier which is built using machine learning concepts. Tensor Flow runs in the backend and Python programming is used in this model. Previous methods are based on various image processing techniques which are implemented in MATLAB. These methods lack the flexibility of providing good level of accuracy. The proposed system can effectively identify different types of diseases with its ability to deal with complex scenarios from a plant's area. Predictor model is used to precise the disease and showcase the accurate problem which helps in enhancing the noble employment of the farmers. Experimental results indicate that an accuracy of around 93% can be achieved using this model on a prepared Data Set.

NPFAM: Non-Proliferation Fuzzy ARTMAP for Image Classification in Content Based Image Retrieval

( Anitha K ),( Chilambuchelvan A ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.7

A Content-based Image Retrieval (CBIR) system employs visual features rather than manual annotation of images. The selection of optimal features used in classification of images plays a key role in its performance. Category proliferation problem has a huge impact on performance of systems using Fuzzy Artmap (FAM) classifier. The proposed CBIR system uses a modified version of FAM called Non-Proliferation Fuzzy Artmap (NPFAM). This is developed by introducing significant changes in the learning process and the modified algorithm is evaluated by extensive experiments. Results have proved that NPFAM classifier generates a more compact rule set and performs better than FAM classifier. Accordingly, the CBIR system with NPFAM classifier yields good retrieval.

Convolutional Neural Network Based Plant Leaf Disease Detection

K. Anitha,M.Srinivasa Rao International Journal of Computer ScienceNetwork S 2024 International journal of computer science and netw Vol.24 No.4

Plant leaf diseases and destructive insects are major challenges that affect the agriculture production of the country. Accurate and fast prediction of leaf diseases in crops could help to build-up a suitable treatment technique while considerably reducing the economic and crop losses. In this paper, Convolutional Neural Network based model is proposed to detect leaf diseases of a plant in an efficient manner. Convolutional Neural Network (CNN) is the key technique in Deep learning mainly used for object identification. This model includes an image classifier which is built using machine learning concepts. Tensor Flow runs in the backend and Python programming is used in this model. Previous methods are based on various image processing techniques which are implemented in MATLAB. These methods lack the flexibility of providing good level of accuracy. The proposed system can effectively identify different types of diseases with its ability to deal with complex scenarios from a plant's area. Predictor model is used to precise the disease and showcase the accurate problem which helps in enhancing the noble employment of the farmers. Experimental results indicate that an accuracy of around 93% can be achieved using this model on a prepared Data Set.

Antidiabetic, lipid lowering and antioxidant potentiating effect of Canavalia species in high fat diet-streptozotocin induced model

K. Anitha,S. Mohana Lakshmi,S. V. Satyanarayana 경희대학교 융합한의과학연구소 2020 Oriental Pharmacy and Experimental Medicine Vol.20 No.4

The leguminous plants Canavalia ensiformis (CE) and Canavalia gladiata (CG) though not eaten frequently but possess some desirable potential but widely used for lowering the glucose level in folkloric medicine. The current research aims for the fractionation of total triterpenoids (TT) and total flavonoid (TF) of ethanolic seed extract of Canavalia species shows significant hypoglycemic, hypolipidemic effect in High-fat diet +Streptozotocin induced rats and to explore the mechanism. Two fractions of Canavalia ensiformis (CE) total triterpenoids (CETT), total flavonoids (CETF) and two fractions of Canavalia gladiata (CG) total triterpenoids (CGTT), total flavonoids (CGTF) were subjected to Phytopharmacognostic study. Glibenclamide (5 mg/kg) was used as a standard drug. The body weight of control group increased significantly from 206 ± 0.98 to 240 ± 0.97 after STZ treated at 21st day diabetic rats showed significant decrease in body weight from 220 ± 0.78 to 168 ± 0.34. HbA1C level was raised in diabetic group 12.2% meanwhile treated groups summarized deceased levels. Elevated level of blood glucose > 386 mg/dl was considered as severe diabetic and further Diabetic induced rats, when treated with these four fractions of extracts, decreased the blood glucose level and serum levels of TC, TG, LDL has also lowered in treated rats than in diabetic rats and increased levels of HDL. The antioxidant indexes SOD, GSH showed decreased levels and LPx, NO levels elevated in diabetic group were also evaluated Histopathological effect of Pancreas of CETT, CETF, CGTT, CGTF has been studied The results obtained from this study showed significant hypoglycemic, hypolipidemic and antioxidant potential.

Study of electrical conductivity and photoelectric response of liquid phase exfoliated graphene thin film prepared via spray pyrolysis route

Vasanthi V.,Logu T.,Ramakrishnan V.,Anitha K.,Sethuraman K. 한국탄소학회 2020 Carbon Letters Vol.30 No.4

Facile process for the fabrication of multi-layer graphene thin flm (MLGF) is reported here. Multi-layer graphene dispersion prepared by liquid-phase exfoliation of graphite was sprayed on a glass substrate by spray pyrolysis method. The structural, optical and electrical properties of the deposited MLGF are investigated. The sheets of graphene are deposited uniformly on the substrate and distribution of small graphene sheets with size of 300–500 nm can be observed in SEM image. AFM and micro-Raman results ensured that the spray-coated graphene thin flm is composed of multi-layer graphene sheets. Spray coated graphene thin flm showed signifcant optical transparency of 57% in the visible region (400–550 nm). MLGF pos�sessed the electrical conductivity in the order of 744 S/m with surface resistivity of 3.54 k Ω/sq. The prepared liquid-phase exfoliated graphene thin flm showed superior photoelectric response. The results of this study provided a framework for fabricating an optimized MLGF using a spray pyrolysis route for optoelectronics devices.

Synchronous radiation-induced enterovesical and enterocervical fistulas in carcinoma of the uterine cervix

Anitha Mandava,Veeraiah Koppula,Meghana Kandati,K. V. V. N. Raju 대한방사선종양학회 2023 Radiation Oncology Journal Vol.41 No.4

Radiation-induced fistulas (RIF) are uncommon therapeutic complications of radiotherapy in patients treated for carcinoma of the uterine cervix. Synchronous occurrence of enterocervical and enterovesical fistulas secondary to radiation is extremely rare and previously unreported in the literature. We report a case of synchronous enterovesical and enterocervical fistulas in a patient with carcinoma of the cervix treated using chemotherapy and radiation along with a brief overview of etiopathogenesis of RIF.

Impact of Foreign Direct Investment on Power Sector: An Empirical Study With Refrence to India

K. Maran,R. Anitha 동아시아경상학회 2015 The East Asian Journal of Business Economics Vol.3 No.1

In the later quarter of the twentieth century, the need for foreign capital is realized among the various countries of the world. Developing countries especially developed multi-pronged strategies to attract foreign capital into the country. One such strategy is the adoption of liberalization policy. Almost all the developing countries started opening their economy, out of the compulsion, to achieve faster rate of economic growth and development. Even a communist country like China adopted liberalization policy as a strategy for accelerated economic growth during 1979. India also joined the race by 1991, when the government announced the policy of liberalization. The importance of FDI extends beyond the financial capital that flows into the country. The huge size of the market in this sector and high returns on investment are two important factors in boosting FDI inflows to power sector. 100 percent FDI is allowed under automatic route in almost all the sub sectors of power sector except the atomic energy. Major foreign investment is made in this sector during 2000 to 2009 is Mauritius with an investment of US$ 4490.96 i.e., 4.24 percent of the total FDI inflows into the country during the period. The estimation of future FDI flow shows a marginal decline in the year 2010. Then from 2011 to 2015 onwards upward trend of FDI was observed.

An Improved Design and Performance Enhancement of Y-Source DC-DC Boost Combined Phase Shifted Full Bridge Converter for Electric Vehicle Battery Charging Applications

Anitha P.,Kumar K. Karthik,Kamaraja A. S. 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.4

In the conventional scheme of power converters for electric vehicle battery charging applications from Solar Photo Voltaic System (SPV), the boost converter is preferred at the front end followed by a full-bridge converter with a discrete switches design. The effect of circuit parasites considerably contributes to power losses and degrades performance. An attempt is made on the entire scheme by integrating the Y-Source Boost Converter (YSBC) with the Phase Shifted Full Bridge Converter (PSFBC) to perform better with the high-power density and minimum effects of circuit parasites. The total system were digitally controlled incorporating the effective MPPT with boost solutions for solar conversion and Zero Voltage Switching (ZVS) on the full-bridge conversion through full protection features. The thermal design of the system were carried out to achieve effective power density. The system voltage conversion boosted from SPV voltage of 20VDC to 60VDC to charge a battery bank of 48 V with a typical system specification of (300–350) W was targeted with a switching frequency of 12.5 kHz at the boost stage and 100 kHz at the full-bridge stage for optimum performance. The solar efficiency of the system is improved using the Incremental Conductance (IC) MPPT methodology.

Synergistic Metal–Metal Oxide Nanoparticles Supported Electrocatalytic Graphene for Improved Photoelectrochemical Glucose Oxidation

Devadoss, Anitha,Sudhagar, P.,Das, Santanu,Lee, Sang Yun,Terashima, C.,Nakata, K.,Fujishima, A.,Choi, Wonbong,Kang, Yong Soo,Paik, Ungyu American Chemical Society 2014 ACS APPLIED MATERIALS & INTERFACES Vol.6 No.7

<P>We report the fabrication of graphene–WO<SUB>3</SUB>–Au hybrid membranes and evaluate their photocatalytic activity towards glucose oxidase mediated enzymatic glucose oxidation. The dual-functionality of gold nanoparticles in the reinforcement of visible light activity of graphene–WO<SUB>3</SUB> membranes and improving the catalytic activity of immobilized enzymes for unique photoelectrochemical sensing application is demonstrated. This work provides new insights into the fabrication of light-sensitive hybrid materials and facilitates their application in future.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/aamick/2014/aamick.2014.6.issue-7/am4058925/production/images/medium/am-2013-058925_0011.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/am4058925'>ACS Electronic Supporting Info</A></P>