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      • First in situ estimations of small phytoplankton carbon and nitrogen uptake rates in the Kara, Laptev, and East Siberian seas

        Bhavya, P. Sadanandan,Lee, Jang Han,Lee, Ho Won,Kang, Jae Joong,Lee, Jae Hyung,Lee, Dabin,An, So Hyun,Stockwell, Dean A.,Whitledge, Terry E.,Lee, Sang Heon Copernicus GmbH 2018 Biogeosciences Vol.15 No.18

        <P><p><strong>Abstract.</strong> Carbon and nitrogen uptake rates by small phytoplankton (0.7-5<span class='thinspace'></span><span class='inline-formula'>µ</span>m) in the Kara, Laptev, and East Siberian seas in the Arctic Ocean were quantified using in situ isotope labeling experiments; this research, which was novel and part of the NABOS (Nansen and Amundsen Basins Observational System) program, took place from 21 August to 22 September 2013. The depth-integrated carbon (C), nitrate (<span class='inline-formula'><math xmlns='http://www.w3.org/1998/Math/MathML' id='M2' display='inline' overflow='scroll' dspmath='mathml'><mrow class='chem'><msubsup><mi mathvariant='normal'>NO</mi><mn mathvariant='normal'>3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg='http://www.w3.org/2000/svg' width='25pt' height='16pt' class='svg-formula' dspmath='mathimg' md5hash='4c315b3ea451cf26923ad12993612b33'><svg:image xmlns:xlink='http://www.w3.org/1999/xlink' xlink:href='bg-15-5503-2018-ie00001.svg' width='25pt' height='16pt' src='bg-15-5503-2018-ie00001.png'/></svg:svg></span></span>), and ammonium (<span class='inline-formula'><math xmlns='http://www.w3.org/1998/Math/MathML' id='M3' display='inline' overflow='scroll' dspmath='mathml'><mrow class='chem'><msubsup><mi mathvariant='normal'>NH</mi><mn mathvariant='normal'>4</mn><mo>+</mo></msubsup></mrow></math><span><svg:svg xmlns:svg='http://www.w3.org/2000/svg' width='24pt' height='15pt' class='svg-formula' dspmath='mathimg' md5hash='f83a9f1907f38a5589c34b239e10518b'><svg:image xmlns:xlink='http://www.w3.org/1999/xlink' xlink:href='bg-15-5503-2018-ie00002.svg' width='24pt' height='15pt' src='bg-15-5503-2018-ie00002.png'/></svg:svg></span></span>) uptake rates by small phytoplankton ranged from 0.54 to 15.96<span class='thinspace'></span>mg<span class='thinspace'></span>C<span class='thinspace'></span>m<span class='inline-formula'><sup>−2</sup></span><span class='thinspace'></span>h<span class='inline-formula'><sup>−1</sup></span>, 0.05 to 1.02<span class='thinspace'></span>mg<span class='thinspace'></span>C<span class='thinspace'></span>m<span class='inline-formula'><sup>−2</sup></span><span class='thinspace'></span>h<span class='inline-formula'><sup>−1</sup></span>, and 0.11 to 3.73<span class='thinspace'></span>mg<span class='thinspace'></span>N<span class='thinspace'></span>m<span class='inline-formula'><sup>−2</sup></span><span class='thinspace'></span>h<span class='inline-formula'><sup>−1</sup></span>, respectively. The contributions of small phytoplankton towards the total C, <span class='inline-formula'><math xmlns='http://www.w3.org/1998/Math/MathML' id='M10' display='inline' overflow='scroll' dspmath='mathml'><mrow class='chem'><msubsup><mi mathvariant='normal'>NO</mi><mn mathvariant='normal'>3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg='http://www.w3.org/2000/svg' width='25pt' height='16pt' class='svg-formula' dspmath='mathimg' md5hash='dd23f13eb24280cbe650be4567ce8571'><svg:image xmlns:xlink='http://www.w3.org/1999/xlink' xlink:href='bg-15-5503-2018-ie00003.svg' width='25pt' height='16pt' src='bg-15-5503-2018-ie00003.png'/></svg:svg></span></span>, and <span class='inline-formula'><math xmlns='http://www.w3.org/1998/Math/MathML' id='M11' display='inline' overflow='scroll' dspmath='mathml'><mrow class='chem'><msubsup><mi mathvariant='normal'>NH</mi><mn mathvariant='normal'>4</mn><mo>+</mo></msubsup></mrow></math><span><svg:svg xmlns:svg='http://www.w3.org/2000/svg' width='24pt' height='15pt' class='svg-formula' dspmath='mathimg' md5hash='8cff18dc7544e09830abea500d71300b'><svg:image xmlns:xlink='http://www.w3.org/1999/xlink' xlink:href='bg-15-5503-2018-ie00004.svg' width='24pt' height='15pt' src='bg-15-5503-2018-ie00004.png'/></svg:svg></span></span> varied from 25<span class='thinspace'></span>% to 89<span class='thinspace'></span>%, 31<span class='thinspace'></span>% to 89<span class='thinspace'></span

      • KCI등재후보

        Understanding anterior communicating artery aneurysms: A bibliometric analysis of top 100 most cited articles

        Bhavya Pahwa,Sarvesh Goyal,Bipin Chaurasia 대한뇌혈관외과학회 2022 Journal of Cerebrovascular and Endovascular Neuros Vol.24 No.4

        Bibliometric analysis is of paramount importance in assessing the research impact wherein studies are ranked on the basis of citations received. It also brings out the excellent contribution of authors and journals in adding evidence for future research. This study aimed at evaluating the top 100 most cited articles on anterior communicating artery (ACoA) Aneurysms. Scopus database was searched using title specific search for the aneurysm of ACoA and top 100 most cited articles along with their authors, author IDs, affiliated institutions, countries and funding bodies were identified. Search yielded 841 articles and top 100 articles were identified to include in this analysis which secured 5615 citations. Citations per year was also calculated to minimize the risk of bias. Maximum citations by any article were 242. The United States was the major contributor to the number of articles while Kessler Institute for Rehabilitation became the highest contributing institution. DeLuca J proved to be a pioneer in this specialized area as he penned 6 studies being first author in 4 of them, making him the most frequent author. National Institutes of Health and the U.S. Department of Health and Human Services were the main funding bodies. Subcategory analysis revealed, 50% studies provided evidence for the treatment and the surgical outcome of the aneurysm. Studies like these can aid in better neurological and neurosurgical management in decision making of ACoA aneurysm.

      • SCIESCOPUS

        Electrochemical Impedance Spectroscopy (EIS) Performance Analysis and Challenges in Fuel Cell Applications

        Padha, Bhavya,Verma, Sonali,Mahajan, Prerna,Arya, Sandeep The Korean Electrochemical Society 2022 Journal of electrochemical science and technology Vol.13 No.2

        Electrochemical impedance spectroscopy (EIS) is a unique non-destructive technique employed to analyze various devices in different energy storage applications. It characterizes materials and interfaces for their properties in heterogeneous systems employing equivalent circuits as models. So far, it has been used to analyze the performance of various photovoltaic cells, fuel cells, batteries, and other energy storage devices, through equivalent circuit designing. This review highlights the diverse applications of EIS in fuel cells and specific parameters affecting its performance. A particular emphasis has been laid on the challenges faced by this technique and their possible solutions.

      • SCIESCOPUS

        Process Parameter Optimization via RSM of a PEM based Water Electrolysis Cell for the Production of Green Hydrogen

        P Bhavya Teja Reddy,Hiralal Pramanik The Korean Electrochemical Society 2024 Journal of electrochemical science and technology Vol.15 No.3

        In the present work, the operating parameters were optimized using Box Behnken Design (BBD) in response surface methodology (RSM) to maximize the hydrogen production rate (R<sub>1</sub>) and hydrogen production rate per unit watt consumed (R<sub>2</sub>) of a proton exchange membrane electrolysis cell (PEMEC), a third response (R<sub>3</sub>) which was the sum of the scaled values of R<sub>1</sub> and R<sub>2</sub> were selected to be maximized so that both hydrogen production rate and hydrogen production rate per unit watt consumed could be maximized. The major parameters which were influencing the experiment for enhancing the output responses were oxygen electrode/anode electrocatalyst loading (A), current supplied (B) and water inlet temperature (C). The commercial proton exchange membrane Nafion<sup>®</sup> was used as the electrolyte. The acetylene black carbon (C<sub>AB</sub>) supported IrO<sub>2</sub> was used as the electrocatalyst for preparing oxygen electrode/anode whereas commercial Pt (40 wt%)/C<sub>HSA</sub> was used as the H<sub>2</sub> electrode/cathode electrocatalyst. The quadratic model was developed to predict the output/ responses and their proximity to the experimental output values. The developed model was found to be significant as the P values for both the responses were < 0.0001 and F values were greater than 1. The optimum condition for both the responses were O<sub>2</sub> electrode/anode electrocatalyst loading of 1.78 mg/cm<sup>2</sup>, supplied current of 0.33 A and water inlet temperature of 54℃. The predicted values for hydrogen production rate (R<sub>1</sub>) and hydrogen production rate per unit watt consumed (R<sub>2</sub>) were 2.921 mL/min and 2.562 mL/(min·W), respectively obtained from the quadratic model. The error % between the predicted response values and experimental values were 1.47% and 3.08% for R<sub>1</sub> and R<sub>2</sub>, respectively. This model predicted the optimum conditions reasonably in good agreement with the experimental conditions for the enhancement of the output responses of the developed PEM based electrolyser.

      • KCI등재

        A Review on Marine N2 Fixation: Mechanism, Evolution of Methodologies, Rates, and Future Concerns

        P. S. Bhavya,이상헌,민준오,김민섭,장효근,김관우,강재중,이재형,이다빈,조나은,김명준,김예진,이준범,이창화,배현지,유혜주,박상훈,윤미선 한국해양과학기술원 2019 Ocean science journal Vol.54 No.4

        Investigations on marine N2 fixation have gained momentum since 1960s with eventual establishments of relevant methodologies to identify species involved and quantify the rates. The evolution of various methodologies to understand N2 fixation and to estimate its rates were underpinned by the constant efforts of pioneers in the ocean biogeochemical research field. Those efforts succeeded in introducing various methodologies that include experimental (15N2 bubble method and acetylene reduction method), geochemical (N* and P* method), mathematical modelling, and remote sensing techniques. However, the construction of an accurate N budget is still under progress due to inseparable issues associated with each method and difficulties in conducting the experiments onboard on a larger scale. Nevertheless, the contributions by each of the methodologies are significant and helped in forming basic ideas about N2 fixation activities on a global scale. It is not only important to recognize the contributions made by the formation of various methodologies by marine research pioneers, but also vital to summarize what we have achieved in the marine N2 fixation research area so far. Hence, this review is an attempt to brief on the various milestones achieved in research on the N2 fixation mechanism, species involved, evolution of methodologies to estimate N2 fixation rates, species identification, budgets, and future concerns.

      • KCI등재

        A Review on the Macromolecular Compositions of Phytoplankton and the Implications for Aquatic Biogeochemistry

        P. S. Bhavya,김보경,조나은,김관우,강재중,이재형,이다빈,이장한,주희태,안소현,김예원,민준오,강민구,윤미선,강창근,이상헌 한국해양과학기술원 2019 Ocean science journal Vol.54 No.1

        Biochemical composition of phytoplankton is a key indicator of the physiological and nutritional status of phytoplankton. A balanced biochemical pattern represents a healthy and productive metabolism in the autotrophic levels which can facilitate proper functioning of higher level organisms. The estimation of biochemical compositions was initiated in the early 1970’s. However, there has been a significant set of modifications in the extraction method and improvements in the sampling and analysis techniques since then. Similarly, the extent of biochemical measurements from various aquatic ecosystems around the globe has also increased. Recently, biochemical patterns are being used as a tool to track the changes in the physiological status of phytoplankton as a response to climate change. Such investigations are also forming part of research works on marine food webs and the nutritional status of ecosystems. This article is a brief review of research works carried out so far in an attempt to understand the biochemical compositions of phytoplankton in the global oceans and the implications with regard to changing environmental conditions.

      • Development 2.0: Principles and Warnings for Leveraging Advances in Information Communication Technologies for Improved Development Efforts

        Kang, Christina Soyeon,Lal, Bhavya ScienceTechnology Policy Institute 2010 STI Policy Review Vol.1 No.3

        Advances in Information Communication Technologies (ICT) have demonstrated tremendous potential for solving development challenges and improving development processes, culminating in the new Development 2.0. Many development practitioners have embraced ICT (particularly on Web 2.0 and mobile phone technologies and applications), which have become hot topics in both the development community and the policy community as they engage in development practice and dialogue. Despite this excitement, there lacks among the policy community a robust understanding of the powers and pitfalls of ICT in development, executed actions to back the excited chatter, and dissemination of this understanding to practitioners and policymakers alike. We conducted a literature review, interviewed experts, and engaged in discussion with leaders in international development and science and technology policy to provide an operational framework base in which to view ICT in development. This framework regards ICT as tools that support more effective and efficient community development actions and appropriate consideration of general guidelines, which enable better engagement across and within sectors and individuals. Flexibility and accountability are critical requirements pervading throughout the various actions and guidelines, which promote transparent, partnership-based, and sustainable development. We highlight the strengths and weaknesses of ICT to focus on the cautions to keep ICT access and distribution in context, understand the various levels of technologies and services, and dig below the surface as excitement about ICT increases and threatens to become a short-term solution. We offer ideas for specific programs that policymakers can implement to contribute to a more efficient and effective development process to ultimately support global human development, but stress the endless possibilities that can be explored with creativity and flexibility beyond what is proposed here.

      • KCI등재

        Using artificial intelligence to detect human errors in nuclear power plants: A case in operation and maintenance

        Gursel Ezgi,Reddy Bhavya,Khojandi Anahita,Madadi Mahboubeh,Coble Jamie Baalis,Agarwal Vivek,Yadav Vaibhav,Boring Ronald L. 한국원자력학회 2023 Nuclear Engineering and Technology Vol.55 No.2

        Human error (HE) is an important concern in safety-critical systems such as nuclear power plants (NPPs). HE has played a role in many accidents and outage incidents in NPPs. Despite the increased automation in NPPs, HE remains unavoidable. Hence, the need for HE detection is as important as HE prevention efforts. In NPPs, HE is rather rare. Hence, anomaly detection, a widely used machine learning technique for detecting rare anomalous instances, can be repurposed to detect potential HE. In this study, we develop an unsupervised anomaly detection technique based on generative adversarial networks (GANs) to detect anomalies in manually collected surveillance data in NPPs. More specifically, our GAN is trained to detect mismatches between automatically recorded sensor data and manually collected surveillance data, and hence, identify anomalous instances that can be attributed to HE. We test our GAN on both a real-world dataset and an external dataset obtained from a testbed, and we benchmark our results against state-of-the-art unsupervised anomaly detection algorithms, including one-class support vector machine and isolation forest. Our results show that the proposed GAN provides improved anomaly detection performance. Our study is promising for the future development of artificial intelligence based HE detection systems.

      • SSA를 이용한 최적화된 YOLOv8 기반의 원격탐사 객체 탐지

        서정한(Seo jeong han),바비아 말호트라(Bhavya Malhotra),무누수리 요겐드라 라오(Munusuri Yogendra Rao),이진우(Kim dan bi),김단비(Lee jin woo),권오설(Kwon Oh Seol) 한국방송·미디어공학회 2024 한국방송미디어공학회 학술발표대회 논문집 Vol.2024 No.11

        본 논문에서는 다람쥐의 이동과 먹이 찾기 전략을 모방한 Squirrel Search Algorithm(SSA)를 이용해 YOLOv8의 하이퍼파라미터(학습률, 배치 크기, 에포크 수)를 최적화하는 방법을 제안한다. SSA는 초기 다람쥐 군집을 무작위로 설정한 후, 반복적인 위치 업데이트를 통해 모델의 성능을 극대화할 수 있는 하이퍼파라미터 최적의 조합을 탐색한다. 최적화 과정에서는 mAP(mean average precision)를 중심으로 적합도 함수를 설정해 최적의 해를 도출하였다. 이는 제한된 자원으로 YOLOv8 모델의 성능을 극대화할 수 있는 효율적인 방법을 제시하며, 다양한 원격 탐지 응용 분야에서의 객체 탐지 성능을 향상할 수 있다.

      • Feature Selection and Hyper-Parameter Tuning for Optimizing Decision Tree Algorithm on Heart Disease Classification

        Tsehay Admassu Assegie,Sushma S.J,Bhavya B.G,Padmashree S International Journal of Computer ScienceNetwork S 2024 International journal of computer science and netw Vol.24 No.2

        In recent years, there are extensive researches on the applications of machine learning to the automation and decision support for medical experts during disease detection. However, the performance of machine learning still needs improvement so that machine learning model produces result that is more accurate and reliable for disease detection. Selecting the hyper-parameter that could produce the possible maximum classification accuracy on medical dataset is the most challenging task in developing decision support systems with machine learning algorithms for medical dataset classification. Moreover, selecting the features that best characterizes a disease is another challenge in developing machine-learning model with better classification accuracy. In this study, we have proposed an optimized decision tree model for heart disease classification by using heart disease dataset collected from kaggle data repository. The proposed model is evaluated and experimental test reveals that the performance of decision tree improves when an optimal number of features are used for training. Overall, the accuracy of the proposed decision tree model is 98.2% for heart disease classification.

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