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Diversity of Saurian fauna in the Buldhana district, Maharashtra, India
Prasanna S. Joshi,Vasudha T. Tantarpale 국립중앙과학관 2016 Journal of Asia-Pacific Biodiversity Vol.9 No.3
The present report provides knowledge about the diversity of Saurian fauna in the Buldhana district of the Indian state of Maharashtra as a model geographic area to promote conservation management. The presented study is based on the field work carried out in the study sites during February 2014 to January 2015. The study revealed the presence of 14 Saurian species belonging to 5 families dominated by Gekkonidae (43.05%), Scincidae (29.15%), Agamidae (21.35%), Varanidae (6.1%), and Chamaeleonidae (0.35%). The relative dominance of species varied with differentmonths, apparently indicating that the Buldhana district has a healthy environmental and demographic setup that accommodates rich Saurian diversity.
Prasanna Vadhanan 대한치과마취과학회 2020 Journal of Dental Anesthesia and Pain Medicine Vol.20 No.5
Various anesthetic techniques have been utilized for maxillo-mandibular fixation. We report the case of a patient with bilateral condylar and zygomatic arch fractures who had severe pulmonary dysfunction. The patient was administered bilateral image-guided Gasserian ganglion block through the foramen ovale to achieve surgical anesthesia. The technical details, advantages, and disadvantages of this rather unusual technique are discussed. The procedure could be a feasible technique when performed meticulously in cases where other approaches are deemed difficult.
Multi Label Deep Learning classification approach for False Data Injection Attacks in Smart Grid
( Prasanna Srinivasan. V ),( Balasubadra. K ),( Saravanan. K ),( Arjun. V. S ),( Malarkodi. S ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.6
The smart grid replaces the traditional power structure with information inventiveness that contributes to a new physical structure. In such a field, malicious information injection can potentially lead to extreme results. Incorrect, FDI attacks will never be identified by typical residual techniques for false data identification. Most of the work on the detection of FDI attacks is based on the linearized power system model DC and does not detect attacks from the AC model. Also, the overwhelming majority of current FDIA recognition approaches focus on FDIA, whilst significant injection location data cannot be achieved. Building on the continuous developments in deep learning, we propose a Deep Learning based Locational Detection technique to continuously recognize the specific areas of FDIA. In the development area solver gap happiness is a False Data Detector (FDD) that incorporates a Convolutional Neural Network (CNN). The FDD is established enough to catch the fake information. As a multi-label classifier, the following CNN is utilized to evaluate the irregularity and cooccurrence dependency of power flow calculations due to the possible attacks. There are no earlier statistical assumptions in the architecture proposed, as they are "model-free." It is also "cost-accommodating" since it does not alter the current FDD framework and it is only several microseconds on a household computer during the identification procedure. We have shown that ANN-MLP, SVM-RBF, and CNN can conduct locational detection under different noise and attack circumstances through broad experience in IEEE 14, 30, 57, and 118 bus systems. Moreover, the multi-name classification method used successfully improves the precision of the present identification.
Dense Granule Protein-7 (GRA-7) of Toxoplasma gondii inhibits viral replication in vitro and in vivo
Prasanna Weeratunga,틸리나,김태환,이현철,김재훈,이병훈,이은서,Kiramage Chathuranga,W. A. Gayan Chathuranga,양철수,마진열,이종수 한국미생물학회 2017 The journal of microbiology Vol.55 No.11
Dense granule protein-7 (GRA-7) is an excretory protein of Toxoplasma gondii. It is a potential serodiagnostic marker and vaccine candidate for toxoplasmosis. Previous reports demonstrated that GRA-7 induces innate immune responses in macrophages by interacting with TRAF6 via the MyD88- dependent pathway. In the present study, we evaluated the antiviral activity and induction of an antiviral state by GRA-7 both in vitro and in vivo. It was observed that GRA-7 markedly reduced the replication of vesicular stomatitis virus (VSVGFP), influenza A virus (PR8-GFP), coxsackievirus (H3- GFP), herpes simplex virus (HSV-GFP), and adenovirus-GFP in epithelial (HEK293T/HeLa) and immune (RAW264.7) cells. These antiviral activities of GRA-7 were attributed to the induction of type I interferon (IFN) signaling, resulting in the secretion of IFNs and pro-inflammatory cytokines. Additionally, in BALB/c mice, intranasal administration of GRA-7 prevented lethal infection by influenza A virus (H1N1) and exhibited prophylactic effects against respiratory syncytial virus (RSV-GFP). Collectively, these results suggested that GRA-7 exhibits immunostimulatory and broad spectrum antiviral activities via type I IFN signaling. Thus, GRA-7 can be potentially used as a vaccine adjuvant or as a candidate drug with prophylactic potential against viruses.
A 32 ㎚ NPN SOI HBT with Programmable Power Gain and 839 ㎓V f<SUB>t</SUB>BV<SUB>CEO</SUB> Product
Prasanna Kumar Misra,S. Qureshi 대한전자공학회 2014 Journal of semiconductor technology and science Vol.14 No.6
The performance of npn SiGe HBT on thin film SOI is investigated at 32 ㎚ technology node by applying body bias. An n-well is created underneath thin BOX to isolate the body biased SOI HBT from SOI CMOS. The results show that the HBT voltage gain and power gain can be programmed by applying body bias to the n-well. This HBT can be used in variable gain amplifiers that are widely used in the receiver chain of RF systems. The HBT is compatible with 32 ㎚ FDSOI technology having 10 ㎚ film thickness and 30 ㎚ BOX thickness. As the breakdown voltage increases by applying the body bias, the SOI HBT with 3 V VCE has very high ftBVCEO product (839 ㎓V). The self heating performance of the proposed SOI HBT is studied. The high voltage gain and power gain (60 ㏈) of this HBT will be useful in designing analog/RF systems which cannot be achieved using 32 ㎚ SOI CMOS (usually voltage gain is in the range of 10-20 ㏈).
Cryptography Based Dynamic Multi-Keyword Ranked Search Using ECC/B+TRE
Prasanna B T,C B Akki 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.11
Today, Cloud computing is becoming a household technology. In cloud, a shared pool of computing resources can be accessed on demand through internet and web applications. Since outsourced data is in third party premises i.e. cloud, accountability of user data is paramount. To preserve privacy and security of user data in cloud, many cryptographic techniques have been proposed by many scientists. One among them is searchable encryption. Searchable encryption allows secure search over encrypted data. In our system, a noble approach has been made using the Elliptic Curve Cryptography (ECC), a cryptographic techniques to reduce the overall computation overhead. Dynamic B+ tree data structure is used to perform multi-keyword search over the encrypted data. To retrieve appropriate data files, ranking will be done based on relevance score. Finally, we compare the effectiveness and efficiency of our proposed scheme with our previous work on CRSA/B+ tree through extensive experimental evaluation using Microsoft azure platform.
Development of daily gridded rainfall dataset over the Ganga, Brahmaputra and Meghna river basins
Prasanna, Venkatraman,Subere, Juvy,Das, Dwijendra K.,Govindarajan, Srinivasan,Yasunari, Tetsuzo John Wiley Sons, Ltd 2014 Meteorological applications Vol.21 No.2
<P><B>Abstract</B></P><P>The India Meteorological Department (IMD) gridded rainfall dataset, the 47 Bangladesh gauge rainfall observations and the Tropical Rainfall Measuring Mission (TRMM) 3B42V6 satellite data are used in the present analysis. The nearest neighbour interpolation scheme is used, wherein the interpolated values are computed from a weighted sum of observations. The Bangladesh daily gauge measured rainfall is interpolated into regular grids of 0.5° × 0.5° resolution every day from January 1988 to December 2007 and appended with the daily gridded dataset of the IMD over the Indian region. A similar resolution dataset of 0.5° × 0.5° for the TRMM‐3B42V6 data from January 1998 to December 2007 is created from the original data of 0.25° × 0.25° resolution. To produce a merged rainfall product, all the gridded datasets are merged. The merging of datasets is done in such a way as to include the highest rainfall at each grid point from the three products. Based on the three available sets of daily observations (IMD dataset (1° × 1°), TRMM‐3B42 (0.25° × 0.25°) and 46 daily station observations over Bangladesh), a dataset of 0.5° × 0.5° resolution on a daily scale is generated. The focus of this study is to compare the TRMM‐3B42V6 rainfall data over the Ganga, Brahmaputra and Meghna (GBM) domain with observed point gauge data, and assess the possibility of using them for application in real time flood forecasting as well as to serve as a comparison tool for the baseline simulation of high resolution atmospheric models aimed at flood forecasting and climate change projections. Copyright © 2012 Royal Meteorological Society</P>