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A sensitivity analysis of millimeter wave characteristics of siC IMPATT diodes

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Journal of semiconductors 2017年第6期38卷 58-65页

作者： s K swain J Pradhan G N Dash s r pattanaik school of Physics sambalpur University Sambalpur Odisha 767019 India College of Engineering Bhubaneswar Bhubaneswar Odisha 751024 India National Institute of science and Technology Berhampur Odisha 761008 India

Ionization rate coefficients and saturation drift velocities for electrons and holes are the vital material parameters in determining the performance of an IMPATT diode.We have performed a sensitivity analysis of the millimeter wave characteristics of 4H-siC and 6H-siC IMPATT diodes with reference to the above mentioned material data and an operating frequency of 220 GHz.The effect of a small variation in the ionization rate and drift velocity on the device characteristics like break down voltage,efficiency,noise measure and power output has been presented here.

关键词： IMPATT siC ionization rate saturation drift velocity, millimeter wave

Ensemble of Handcrafted and Deep Learning Model for Histopathological Image Classification

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Computers, Materials & Continua 2022年第11期73卷 4393-4406页

作者： Vasumathi Devi Majety N.sharmili Chinmaya ranjan pattanaik ELaxmi Lydia subhi r.M.Zeebaree sarmad Nozad Mahmood Ali s.Abosinnee Ahmed Alkhayyat Department of Computer science Engineering Vignan’s Nirula Institute of Technology and Science for WomenGuntur522005India Department of Computer science Engineering Gayatri Vidya Parishad College of Engineering for WomenVisakhapatnam530048India Department of Computer science and Engineering Ajay Binay Institute of Technology CuttackOdisha750314India Department of Computer science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Energy Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq Computer Technology Engineering College of Engineering TechnologyAl-Kitab UniversityIraq Computer Technical Engineering Department College of Technical EngineeringThe Islamic UniversityNajaf54001Iraq College of Technical Engineering The Islamic UniversityNajafIraq

Histopathology is the investigation of tissues to identify the symptom of abnormality.The histopathological procedure comprises gathering samples of cells/tissues,setting them on the microscopic slides,and staining them.The investigation of the histopathological image is a problematic and laborious process that necessitates the expert’s knowledge.At the same time,deep learning(DL)techniques are able to derive features,extract data,and learn advanced abstract data representation.With this view,this paper presents an ensemble of handcrafted with deep learning enabled histopathological image classification(EHCDL-HIC)model.The proposed EHCDLHIC technique initially performs Weiner filtering based noise removal technique.Once the images get smoothened,an ensemble of deep features and local binary pattern(LBP)features are extracted.For the classification process,the bidirectional gated recurrent unit(BGrU)model can be employed.At the final stage,the bacterial foraging optimization(BFO)algorithm is utilized for optimal hyperparameter tuning process which leads to improved classification performance,shows the novelty of the work.For validating the enhanced execution of the proposed EHCDL-HIC method,a set of simulations is performed.The experimentation outcomes highlighted the betterment of the EHCDL-HIC approach over the existing techniques with maximum accuracy of 94.78%.Therefore,the EHCDL-HIC model can be applied as an effective approach for histopathological image classification.

关键词： Histopathological image classification machine learning deep learning handcrafted features bacterial foraging optimization

VLsI scaling methods and low power CMOs buffer circuit

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Journal of semiconductors 2013年第9期34卷 92-99页

作者： Vijay Kumar sharma Manisha pattanaik Department of Information Technology ABV-Indian Institute of Information Technology & Management

Device scaling is an important part of the very large scale integration （VLsI） design to boost up the success path of VLsI industry, which results in denser and faster integration of the devices. As technology node moves towards the very deep submicron region, leakage current and circuit reliability become the key issues. Both are increasing with the new technology generation and affecting the performance of the overall logic circuit. The VLsI designers must keep the balance in power dissipation and the circuit＇s performance with scaling of the devices. In this paper, different scaling methods are studied first. These scaling methods are used to identify the effects of those scaling methods on the power dissipation and propagation delay of the CMOs buffer circuit. For mitigating the power dissipation in scaled devices, we have proposed a reliable leakage reduction low power transmission gate （LPTG） approach and tested it on complementary metal oxide semiconductor （CMOs） buffer circuit. All simulation results are taken on HsPICE tool with Berkeley predictive technology model （BPTM） BsIM4 bulk CMOs files. The LPTG CMOs buffer reduces 95.16% power dissipation with 84.20% improvement in figure of merit at 32 nm technology node. Various process, voltage and temperature variations are analyzed for proving the robustness of the proposed approach. Leakage current uncertainty decreases from 0.91 to 0.43 in the CMOs buffer circuit that causes large circuit reliability.

关键词： LPTG buffer power dissipation propagation delay scaling nanoscale CMOs figure of merit

A geospatial investigation of interlinkage between basement fault architecture and coastal aquifer hydrogeochemistry

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Geoscience Frontiers 2020年第4期11卷 1431-1440页

作者： P.P.Das P.P.Mohapatra s.Goswami M.Mishra J.K.pattanaik ACOAsT Amity University HarayanaGurugramIndia Department of Geology North Odisha UniversityOdishaIndia Department of Earth sciences Sambalpur UniversitySamabalpurOdishaIndia Khallikote University BerhampurOdishaIndia Centre for Geography and Geology Central University of PunjabBhatindaIndia

The Mahanadi delta,deposited on a series of horst and graben basement structures,is considered an extension of the East Lambert rift of Antarctica.Current study is based on the hydrogeochemical assessment of this deltaic aquifer system and geospatial analysis thereof,to appreciate the basement structure influence on groundwater chemistry.Major ion chemistry of subsurface waters portrays a distinct saline contamination across the terrain and varied regimes of water types,specifically with respect to southern and northern parts of this aquifer system.Findings of the study indicate a general near surface saline horizon and significant fragmentation of the hydrostatic units.This,in turn,implies noteworthy influence of formational water to salinity regimes and basin structural changes for the escape of these waters to surroundings.A plot of recent low intensity earthquakes displays proximity of epicenters to the faults as well as striking similarity to the trend of terrestrial faults indicating multiple reactivations of the faults.To further corroborate the above findings,spatial pattern analysis of individual hydrochemical variables is carried out which reveals specific clusters of sources(groundwater mixing)and sinks(groundwater dispersion) in proximity to basement fault dispositions.While the faults can be disregarded as conduits or barriers owing to their great depth,the overlying sedimentary mass,particularly,the horizons with significant clayey content have been distorted due to post rift subsidence and fault reactivations.A proximity analysis of ionic clusters points towards a greater influence of longitudinal faults to that of the transverse ones on groundwater mixing or dispersion.

关键词： Hydrogeochemistry Mahanadi Geospatial salinity Cluster analysis

A research progress review on regional extreme events

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Advances in Climate Change research 2018年第3期9卷 161-169页

作者： rEN Fu-Min Blair TrEWIN Manola BrUNET pattanaik DUsHMANTA Andreas WALTEr Omar BADDOUr Maya KOrBEr state Key Laboratory of severe Weather Chinese Academy of Meteorological Sciences Beijing 100081 China Bureau of Meteorology Melbourne VIC 3001 Australia Centre for Climate Change Department of Geography University Rovira i Virgili Tarragona 43007 Spain Climatic research Unit School of Environmental Sciences University of East Anglia Norwich NR4 7TJ UK India Meteorological Department New Delhi 110003 India German Meteorological service (DWD) Offenbach 63067 Germany World Meteorological Organization Geneva 1211 Switzerland

An extreme （weather and climate） event does not only mean that an extreme occurs at a location, but more generally it can impact a certainarea and last a certain period of time, which is defined as a regional extreme event （rEE） with a certain impacted area and duration. The conceptof rEE has been defined to allow mainly objective assessment of the events without a pre-determined boundary and duration. This paper reviewsthe studies on rEEs published during the past 20 years, especially recent years. Mainly in view of methodology, these studies can be divided intothree types studies focusing on spatial simultaneity, studies focusing on temporal persistence, and studies identifying rEEs. The methodsidentifying rEEs include two kinds, e.g., type-I methods stressing rEE＇s temporal persistence within a relatively certain area and type-IImethods focusing on catching a complete rEE. Identification methods proposed in this paper could provide valuable information for variouspurposes, such as real-time monitoring, estimating long-term changes, mechanism diagnosis, forecasting study and even attribution analysis.research on rEEs is important for objectively defining extreme weather and climate events, which depends on the spatial and temporal scales ofinterest. such an objective definition will support ongoing climate monitoring and improve the assessment of how regional extreme events havechanged over time.

关键词： Extreme (weather and climate) events regional extreme events research progress review

Monthly Forecast of Indian southwest Monsoon rainfall Based on NCEP’s Coupled Forecast system

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Atmospheric and Climate sciences 2012年第4期2卷 479-491页

作者： Dushmanta r. pattanaik Biswajit Mukhopadhyay Arun Kumar Climate Prediction Center National Centres for Environmental Prediction (NCEP)/National Oceanic and Atmospheric Administration (NOAA) Camp Springs USA India Meteorological Department (IMD) New Delhi India

The monthly forecast of Indian monsoon rainfall during June to september is investigated by using the hindcast data sets of the National Centre for Environmental Prediction (NCEP)’s operational coupled model (known as the Climate Forecast system) for 25 years from 1981 to 2005 with 15 ensemble members each. The ensemble mean monthly rainfall over land region of India from CFs with one month lead forecast is underestimated during June to september. With respect to the inter-annual variability of monthly rainfall it is seen that the only significant correlation coefficients (CCs) are found to be for June forecast with May initial condition and september rainfall with August initial conditions. The CFs has got lowest skill for the month of August followed by that of July. Considering the lower skill of monthly forecast based on the ensemble mean, all 15 ensemble members are used separately for the preparation of probability forecast and different probability scores like Brier score (Bs), Brier skill score (Bss), Accuracy, Probability of Detection (POD), False Alarm ratio (FAr), Threat score (Ts) and Heidke skill score (Hss) for all the three categories of forecasts (above normal, below normal and normal) have been calculated. In terms of the Bs and Bss the skill of the monthly probability forecast in all the three categories are better than the climatology forecasts with positive Bss values except in case of normal forecast of June and July. The “Ts”, “Hss” and other scores also provide useful probability forecast in case of CFs except the normal category of July forecast. Thus, it is seen that the monthly probability forecast based on NCEP CFs coupled model during the southwest monsoon season is very encouraging and is found to be very useful.

关键词： Indian Monsoon Coupled Model Monthly Forecast Probability Forecast Brier skill score Threat score Heidke skill score

The Medicinal Flora of sambalpur District,Orissa,India

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云南植物研究 2010年第6期32卷 554-560页

作者： Chiranjibi pattanaik C.sudhakar reddy P.Manikya reddy salim Ali Centre for Ornithology & Natural History Forestry and Ecology Division National Remote Sensing Center Department of Botany Osmania University

This paper describes an analysis of the plants of sambalpur district of Orissa,India which have been used medicinally by local people. The families having medicinal values are analysed using Moerman's method of regression analysis. There were 136 plant families recorded from the study area. The analysis of families showed that the Euphorbiaceae family being used most ethnomedicinally by the local people in sambalpur district of Orissa,whereas Poaceae is used least one. This type of study determines the degree of importance of plant families in the medicinal flora of the region.

关键词： Medicinal flora Orissa regression analysis sambalpur district

recent advances in seasonal and multi-annual tropical cyclone forecasting

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Tropical Cyclone research and review 2023年第3期12卷 182-199页

作者： Yuhei Takaya Louis-Philippe Caron Eric Blake Francois Bonnardot Nicolas Bruneau Joanne Camp Johnny Chan Paul Gregory Jhordanne J.Jones Namyoung Kang Philip J.Klotzbach Yuriy Kuleshov Marie-Dominique Leroux Julia F.Lockwood Hiroyuki Murakami Akio Nishimura Dushmanta r.pattanaik Tom J.Philp Yohan ruprich-robert ralf Toumi Frederic Vitart seonghee Won ruifen Zhan Meteorological research Institute Japan Meteorological AgencyIbarakiJapan Ouranos MontrealCanada National Hurricane Center National Oceanic and Atmospheric AdministrationMiamiUSA Meteo-France Direction Interregionale pour l'Ocean IndienSaint-Denisde La ReunionFrance reask LondonUK Bureau of Meteorology VictoriaAustralia City University of Hong Kong Hong KongChina Asia-Pacific Typhoon Collaborative research Center ShanghaiChina shanghai Typhoon Institute China Meteorological AdministrationShanghaiChina Department of Earth Atmosphericand Planetary SciencesPurdue UniversityWest LafayetteUSA University Corporation for Atmospheric research BoulderUSA Department of Geography Kyungpook National UniversityDaeguRepublic of Korea Department of Atmospheric science Colorado State UniversityFort CollinsUSA royal Melbourne Institute of Technology(rMIT)University MelbourneAustralia Met Office Hadley Centre ExeterUK National Oceanographic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory PrincetonUSA Japan Meteorological Agency TokyoJapan India Meteorological Department New DelhiIndia Maximum Information LondonUK Barcelona supercomputing Center BarcelonaSpain Department of Physics Imperial College LondonLondonUK European Centre for Medium-range Weather Forecasts(ECMWF) ReadingUK Korea Meteorological Administration JejuRepublic of Korea Department of Atmospheric and Oceanic sciences&Institute of Atmospheric sciences Fudan UniversityShanghaiChina

seasonal tropical cyclone(TC)forecasting has evolved substantially since its commencement in the early 1980s.However,present operational seasonal TC forecasting services still do not meet the requirements of society and stakeholders:current operational products are mainly basin-scale information,while more detailed sub-basin scale information such as potential risks of TC landfall is anticipated for decision making.To fill this gap and make the TC science and services move forward,this paper reviews recent research and development in seasonal tropical cyclone(TC)forecasting.In particular,this paper features new research topics on seasonal TC predictability in neutral conditions of El Ni˜no–southern Oscillation(ENsO),emerging forecasting techniques of seasonal TC activity including Machine Learning/Artificial Intelligence,and multi-annual TC predictions.We also review the skill of forecast systems at predicting landfalling statistics for certain regions of the North Atlantic,Western North Pacific and south Indian oceans and discuss the gap that remains between current products and potential user's expectations.New knowledge and advanced forecasting techniques are expected to further enhance the capability of seasonal TC forecasting and lead to more actionable and fit-for-purpose products.

关键词： Tropical cyclones seasonal forecasting Climate services

The Choice to Go Organic: Evidence from small Us Farms

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Agricultural sciences 2019年第12期10卷 1566-1580页

作者： Xuanli Liu Nalini pattanaik Mack Nelson Mohammed Ibrahim Agricultural research station Fort Valley State University Fort Valley USA Department of Business and Economics Fort Valley State University Fort Valley USA

This research examined small farmers’ operational choice in converting to organic farming in the southern region of the United states. A logistic model fitted to survey data from responses of 456 produce growers found the key determinants of the conversion choices of farmers and offered quantitative impacts of the major influential factors retained in the fitted model. Among them, barriers to the conversion were linked to farmer’s age, risk aversion, years of farming, and the lack of education as well as low yield of organic farming;nevertheless, the model also revealed the existence of stimuli reflecting on access to farmers markets, peer exemplars, and operational scale. The confluence of variables retained partially explained a slow but steady conversion to organic farming in the United states. Besides the broad implication for policy making in the agricultural sector, this study found that organic farming was closely tied to small farms and organic farming could be a back road to the future of small Us farms.

关键词： Organics Barriers Produce Organic Farming small Farms