126 research outputs found
Review of Aakash Singh Rathore, Plato’s Labyrinth: Sophistries, lies and conspiracies in Socratic dialogues
No full textAakash Rathore Singh’s book Plato’s Labyrinth: Sophistries, Lies and Conspiracies in Socratic Dialogues attempts to break ground substantially, as far as I can discern, in two areas—one, on textual interpretive method or hermeneutics and the other on the content of what Plato has to say regarding issues like tyranny, the polis and the role of the philosopher in the political community. The kind of division I have just made regarding the intent of the author might not sit very well with the author himself, however. The reason I say this is because what Aakash Singh Rathore is attempting to do is to say that, with Plato, the content and the method of explicating that content always go hand in hand and that it is futile to separate them
Performance Monitoring and Analyzer Tool for CG SCADA
No full textM.E. (Information Security)Supervisory Control and Data Acquisition (SCADA) is widely used to control and
keep track of equipment or a plant in industries like water and waste control,
telecommunications, energy, transport, and oil and gas refining. It gathers data from
the distant site, presents data to the operator through the Human machine interface
(HMI) and transmits control signals to the remote site. So it is critical to monitor and
analyze SCADA performance. To address this issue, we present performance
monitoring and analyzer tool used for CG SCADA (Crompton Greaves SCADA)
system which can monitor and analyze performance parameter such as CPU
utilization, memory usage and page fault rate from time to time on demand. This tool
is used to monitor and analyze the CG-SCADA in two different states viz. in real time
and on the basis of logged information. The real time analyzing is provided detailed
tabular display and line graph representation. The logged information analyzing is
done on filter condition as per user requirement and it provides the filtered
information in line graph representation. This tool achieves real time monitoring and
analyzing of SCADA performance parameter during the CG-SCADA operation. At
the same time, it also record monitoring data in database within specified intervals
and show recorded data on client HMI.CSED, Thapar University, Patial
A Global Analysis on Microgrids through the PESTEL Framework
No full textMicrogrids enable distribution of electricity with higher shares of variable renewables, higher power quality, greater reliability and higher efficiency. There are a large number of factors in addition to the technology, which affect their shift towards market competitiveness and widespread adoption. The PESTEL framework, covering Political, Economic, Social, Technical, Environmental and Legislative factors, is used to identify and describe the drivers and barriers for microgrid development at the global level. The framework enables a broader approach to describe potential for microgrid applications. The results aim to provide engineers, project developers and microgrid specialists with an overview of the prospects for microgrid deployment.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Energy Technolog
Approximation of unbounded functions with linear positive operators
No full textElectrical Engineering, Mathematics and Computer Scienc
Internet of Things and machine learning in agriculture: technological impacts and challenges De Gruyter frontiers in computational intelligence ;, v. 8./ edited by Vishal Jain, Jyotir Moy Chatterjee, Abhishek Kumar, Pramod Singh Rathore.
No full textIncludes bibliographical references and index.Agriculture is one of the most fundamental human activities. As the farming capacity has expanded, the usage of resources such as land, fertilizer, and water has grown exponentially, and environmental pressures from modern farming techniques have stressed natural landscapes. Still, by some estimates, worldwide food production needs to increase to keep up with global food demand. 'Machine Learning and the Internet of Things' can play a promising role in the Agricultural industry, and help to increase food production while respecting the environment. This book explains how these technologies can be applied, offering many case studies developed in the research world.Part I. 1. 2. 3. 4. 5. Part II. 6. 7. 8. 9. Part III. 10. 11. 12. 13. 14. 15. 16. 17. 18. Index. Parul Verma and Umesh Kumar -- Ashish Tripathi, Arun Kumar Singh, Khararee Narayan Singh, Krishna Kant Singh, Pushpa Choudhary, and Prem Chand Vashist -- Jyoti Batra Arora -- Nilesh Uke, Trupti Thite, and Supriya Saste -- Sivakumar Rajagopal, Sonai Rajan Thangaraj, J. Paul Mansingh, and B. Prabadevi -- Aarti and Amit Kumar -- K. Krishnaveni, E. Radhamani, and K. Preethi -- Jibin Varghese, J. Jeba Praba, and John J. George -- Nikunj Rajyaguru, Shubhendu Vyas, and Kunjan Vyas -- Suvarna Pawar and Pravin Futane -- J. H. Kamdar, M. D. Jasani, J. D. Jasani, J. Jeba Praba, and John J. George -- Sapna Nigam, Rajni Jain, Sudeep Marwaha, and Alka Arora -- Sandip Kumar Roy and Preeta Sharan -- Mahua Bose and Kalyani Mali -- Tan Pham Nhat and Son Vu Truong Dao -- Shubhendu Vyas, Nikunj Rajyaguru, and Kunjan Vyas -- Yash Joshi, Sachit Mishra, and R. S. Ponmagal -- Punam Bedi, Pushkar Gole, and Sumit Kumar Agarwal -- Frontmatter -- Preface -- Acknowledgments -- Contents -- List of contributors -- Machine Learning and Internet of Things in Agriculture -- Smart farming : Using IoT and machine learning techniques / Food security and farming through IoT and machine learning / An innovative combination for new agritechnological era / Recent advancements and challenges of artificial intelligence and IoT in agriculture / Technological impacts and challenges of advanced technologies in agriculture / Applications of Internet of Things in Agriculture -- IoT-based platform for smart farming - Kaa / Internet of things platform for smart farming / Internet of things platform for smart farming / Internet of things platform for smart farming / Applications of Machine Learning in Agriculture -- Kisan-e-Mitra : A tool for soil quality analyzer and recommender system / Artificial intelligence for plant disease detection : Past, present, and future / Wheat rust disease identification using deep learning / Image-based hibiscus plant disease detection using deep learning / Rainfall prediction by applying machine learning technique / Plant leaf disease classification based on feature selection and deep neural network / Using deep learning for image-based plant disease detection / Using deep learning for image-based plant disease detection / Using deep learning for image-based plant disease detection /1 online resource (xvi, 410 pages)
Error Analysis of TRMM, WFD and APHRODITE datasets using Triple Collocation
No full textThe use of global precipitation datasets such as TRMM, WFD etc. for data scarce regions is gaining popularity since they provide forcing input for hydrological models. They make up for the lack of ground based data or the poor quality of whatever is available in many parts of the world. Using these datasets would be perfect if they were free of errors. Unfortunately, this is not the case. The geo-spatial data obtained from satellites or reanalysis products are not direct measures of precipitation. They are derived from atmospheric parameters such as cloud depth, brightness temperature etc. (Huffman 2007). The conversion of these to precipitation is done using complex algorithms. Efforts are made to calibrate this data but still errors sneak in. Similarly the interpolated gauge data like APHRODITE also has errors because of the inability of interpolation techniques to capture the high spatio-temporal variability in Precipitation. Hence the error estimation of these datasets remains a big problem. Lack of ground based data ensures there is no reference to check these global datasets against. In this research, Triple collocation technique is applied to 3 datasets namely APHRODITE, TRMM and WFD for the river basins in Myanmar. The technique gives an estimate of the residual errors in the 3 datasets (with uncorrelated errors) without using any ground measurements or true values (R. A. Roebeling 2012). This is the first time tit has been used to estimate errors in Precipitation datasets on a daily scale. Though the errors are not absolute, the results give an insight into the relative quality of these datasets. The errors have been calculated in space and time. Hence both temporal and spatial error characteristics are analysed. The study period is from 1998-2001. The results obtained show that for TRMM and WFD, the errors are concentrated and of higher magnitude. For APHRODITE, the errors are more evenly distributed in space. All three datasets showed high errors in the central dry parts and the delta region. Overall, APHRODITE seems to show lowest error values in space. The temporal error characteristics were also different for the 3 datasets. WFD showed highest average and maximum errors. TRMM had some very high error peaks but was in general better than WFD. Looking at the maximum and Average errors, APHRODITE seems to be the best of the three. WFD also shows some error peaks at the onset and end of Monsoon season. This shows its inability to estimate the localized pre and post monsoon storms. The assumption of uncorrelated errors was also verified post analysis. Errors for 2 locations, Bago and Yangon were used to make scatter plots. No strong correlation is visible in the scatter plots reinforcing the assumption that the errors are uncorrelated. The research shows that it is possible to make qualitative and quantitative inferences about the errors in the global precipitation datasets in the absence of in-situ measurements. Based on this research, it is concluded that overall, APHRODITE is the best of the 3 datasets. The possibility of a merged dataset formed by combining these 3 based on the error patterns observed in this study should be explored further.Water ResourcesWater ManagementCivil Engineering and Geoscience
Transsellar transsphenoidal encephalocele: A series of four cases
No full textTranssellar transsphenoidal encephalocele is the least common type of
basal encephalocele. We present a series of four cases of transsellar
transsphenoidal encephalocele. Clinical findings, imaging reviews,
surgical repair techniques and postoperative morbidity are discussed
with the relevant literature. Non contrast CT scan head with 3D
reconstruction and magnetic resonance imaging should be done in all
patients of transsphenoidal encephalocele. Endocrine assessment is also
essential. Repair of a transsphenoidal encephalocele should be
coordinated between a team of neurosurgeons and ENT surgeon. Our
surgical outcome supports the transpalatal/ transnasal approach over
the transcranial approach
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