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2. IoT-Based Water Quality Analysis and Purification System

Author

Singh, Ashutosh, Ranjan, Akihil, Nikhil, Singh, Manish Kumar, Nagaraja, Veda S., Raghunandan, S., Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Shetty, N. R., editor, Patnaik, L. M., editor, Nagaraj, H. C., editor, Hamsavath, Prasad N., editor, and Nalini, N., editor

Published
2022
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15. List of Contributors

Author

Abdiev, Bakhtiyar, primary, Agvaantseren, Bayarjargal, additional, Ale, Som, additional, Ali, Hussain, additional, Allen, Priscilla, additional, Almashev, Chagat, additional, Amato, George, additional, Amgalanbaatar, Sukh, additional, Amirov, Zayiniddin, additional, Anarbaev, Maksat, additional, Arenas, Rafael, additional, Aromov, Bakhtyor, additional, Bürki, Roland, additional, Bayrakçısmith, Rana, additional, Beale, Nick, additional, Bhatnagar, Yash Veer, additional, Bijoor, Ajay, additional, Blidchenko, Ekaterina Yu., additional, Blomqvist, Leif, additional, Boixader, Jordi, additional, Botezatu, Ioana, additional, Breitenmoser, Urs, additional, Breitenmoser-Würsten, Christine, additional, Buzdar, Hafeez, additional, Bykova, Elena, additional, Caragiulo, Anthony, additional, Castner, Jennifer, additional, Chundawat, Raghunandan S., additional, Colorado, Apela, additional, Criffield, Marc, additional, Dadul, Jigmet, additional, Dashzeveg, Unurzul, additional, Davaa, Galbadrakh, additional, Davletbakov, Askar, additional, Ud Din, Jaffar, additional, Dorjgurkhem, Batbold, additional, Driscoll, Carlos A., additional, Duisekeyev, Bakytbek, additional, Esipov, Alexander, additional, Farrington, John D., additional, Fernández, Leonardo, additional, Fisher, Kim, additional, Fominykh, Irina, additional, Fox, Joseph L., additional, García-Tardío, Maribel, additional, Garrote, Germán, additional, Ghoshal, Abhishek, additional, Gibbs, James P., additional, Gilbert, Martin, additional, Harris, Richard B., additional, Heiner, Michael, additional, Hemmingmoore, Heather, additional, Hernandez-Blanco, Jose A., additional, Hillard, Darla, additional, Hotham, Paul, additional, Howard, Pippa, additional, Hunter, Don, additional, Hussain, Shafqat, additional, Istomov, Sergei, additional, Jackson, Rodney M., additional, Jiménez-Peréz, Ignacio Ignacio, additional, Johansson, Örjan, additional, Kachel, Shannon, additional, Karimov, Khalil, additional, Karnaukhov, Alexander, additional, Kiesecker, Joseph, additional, Khan, Ahmad, additional, Khan, Ashiq Ahmad, additional, Khanduri, Shakti Kant, additional, Khatiwada, Ambika, additional, Khuukhenduu, Tungalagtuya, additional, Kitchener, Andrew C., additional, Kochorov, Chyngyz, additional, Koontz, Fred W., additional, Korablev, Miroslav, additional, Kozlova, Svetlana, additional, Kubanychbekov, Zairbek, additional, Kunkel, Kyran, additional, Kuksin, Alexander, additional, Kushlin, Andrey, additional, Lal, Panna, additional, Lama, Wendy Brewer, additional, Lanz, Tabea, additional, Laporte, Bruno, additional, Li, Juan, additional, Lind, Thomas, additional, Liu, Yanlin, additional, Loginov, Oleg, additional, Loginova, Irina, additional, López, Guillermo, additional, López-Parra, Marcos, additional, Lovari, Sandro, additional, Lu, Zhi, additional, Lumpkin, Susan, additional, Maheshwari, Aishwarya, additional, Majumder, Bipasha, additional, Mallon, David, additional, Malykh, Sergei, additional, Mathur, Vinod Bihari, additional, McCarthy, Kyle, additional, McCarthy, Thomas, additional, Michel, Stefan, additional, Mijiddorj, Tserenadmid, additional, Miquelle, Dale G., additional, Mishra, Charudutt, additional, Mock, John, additional, Modaqiq, Abdul Wali, additional, Mohammad, Ghulam, additional, Moheb, Zalmai, additional, Mostafawi, Sayed Naqibullah, additional, Munkhtsog, Bariushaa, additional, Murali, Ranjini, additional, Naidenko, Sergey V., additional, Namgail, Tsewang, additional, Nasir, Syed Mahmood, additional, Nawaz, Muhammad Ali, additional, Noras, Sibylle, additional, Nyul, Helen, additional, Oakleaf, James, additional, Onorato, Dave, additional, Ostrowski, Stéphane, additional, Padmanabhan, Sujatha, additional, Paley, Richard, additional, Paltsyn, Mikhail, additional, Pandey, Megh Bahadur, additional, Poyarkov, Andrey, additional, Prins, Herbert H.T., additional, Protas, Yelizaveta, additional, Purevjav, Lkhagvajav, additional, Quammen, Betsy Gaines, additional, Raghunath, Rangaswamy, additional, Reading, Richard P., additional, Redpath, Stephen R., additional, Rey, Teresa del, additional, Riordan, Philip, additional, Robinson, Hugh S., additional, Rosen, Tatjana, additional, Rozhnov, Viatcheslav V., additional, Rozhnov, Vyacheslav, additional, Ruiz, Gema, additional, Rullman, Jennifer Snell, additional, Rutherford, Brad, additional, Ryskulova, Nargiza, additional, Saidov, Abdusattor, additional, Saidov, Nurali, additional, Samanchina, Jarkyn, additional, Sanderson, Eric W., additional, Sathyakumar, Sambandam, additional, Seidensticker, John, additional, Seth, Anand, additional, Shah, Karan B., additional, Shah, Safdar Ali, additional, Sharma, Koustubh, additional, Sharma, Rishi Kumar, additional, Shehzad, Wasim, additional, Shi, Kun, additional, Simón, Miguel A., additional, Simms, Anthony, additional, Sliwa, Alexander, additional, Sonam, Karma, additional, Sorokin, Pavel A., additional, Spitsyn, Sergei, additional, Suryawanshi, Kulbhushansingh R., additional, Tetzloff, Jay, additional, Tharchen, Lhendup, additional, Thinley, Tanzin, additional, Thomas, Patrick R., additional, Tichomirow, Boris, additional, Timbadia, Radhika, additional, Trivedi, Pranav, additional, uulu, Kuban Jumabai, additional, Varma, Keshav, additional, von Meibom, Stephanie, additional, Wangchuk, Sonam, additional, Wangchuk, Tshewang R., additional, Weckworth, Byron, additional, Weddle, Mike, additional, Wegge, Per, additional, Whitten, Tony, additional, Wong, Wai-Ming, additional, Xiao, Lingyun, additional, Yachmennikova, Anna A., additional, Yunden, Bayarjargal, additional, Yin, Hang, additional, Yamaguchi, Nobuyuki, additional, Yunusov, Nodirjon, additional, Zahler, Peter, additional, Zakharenka, Andrew, additional, Zhao, Xiang, additional, Zhongtian, Zhang, additional, and Zvychainaya, Elena, additional

Published
2016
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17. GeneLab Phase 2: Integrated Search Data Federation of Space Biology Experimental Data

Author

Tran, P. B, Berrios, D. C, Gurram, M. M, Hashim, J. C. M, Raghunandan, S, Lin, S. Y, Le, T. Q, Heher, D. M, Thai, H. T, Welch, J. D, Caldwell, S. M, Stotzky, O. G, and Skidmore, M. G

Subjects
Life Sciences (General)
Abstract

The GeneLab project is a science initiative to maximize the scientific return of omics data collected from spaceflight and from ground simulations of microgravity and radiation experiments, supported by a data system for a public bioinformatics repository and collaborative analysis tools for these data. The mission of GeneLab is to maximize the utilization of the valuable biological research resources aboard the ISS by collecting genomic, transcriptomic, proteomic and metabolomic (so-called omics) data to enable the exploration of the molecular network responses of terrestrial biology to space environments using a systems biology approach. All GeneLab data are made available to a worldwide network of researchers through its open-access data system. GeneLab is currently being developed by NASA to support Open Science biomedical research in order to enable the human exploration of space and improve life on earth. Open access to Phase 1 of the GeneLab Data Systems (GLDS) was implemented in April 2015. Download volumes have grown steadily, mirroring the growth in curated space biology research data sets (61 as of June 2016), now exceeding 10 TB/month, with over 10,000 file downloads since the start of Phase 1. For the period April 2015 to May 2016, most frequently downloaded were data from studies of Mus musculus (39) followed closely by Arabidopsis thaliana (30), with the remaining downloads roughly equally split across 12 other organisms (each 10 of total downloads). GLDS Phase 2 is focusing on interoperability, supporting data federation, including integrated search capabilities, of GLDS-housed data sets with external data sources, such as gene expression data from NIHNCBIs Gene Expression Omnibus (GEO), proteomic data from EBIs PRIDE system, and metagenomic data from Argonne National Laboratory's MG-RAST. GEO and MG-RAST employ specifications for investigation metadata that are different from those used by the GLDS and PRIDE (e.g., ISA-Tab). The GLDS Phase 2 system will implement a Google-like, full-text search engine using a Service-Oriented Architecture by utilizing publicly available RESTful web services Application Programming Interfaces (e.g., GEO Entrez Programming Utilities) and a Common Metadata Model (CMM) in order to accommodate the different metadata formats between the heterogeneous bioinformatics databases. GLDS Phase 2 completion with fully implemented capabilities will be made available to the general public in September 2017.

Published
2016

18. Implementation of Beam Steering using Phased Array Antennas

Author

Nitish Hs, Jestin John Mathew, Raghunandan S, and Jayavrinda

Subjects
Optics, Computer science, business.industry, Phased array, Beam steering, Astrophysics::Instrumentation and Methods for Astrophysics, Physics::Accelerator Physics, business, Computer Science::Information Theory
Abstract

Beam steering is a phenomenon of varying the direction of the main lobe in the radiation pattern, so in radar systems it can be achieved by changing the relative phases of the antenna being implemented.But,some of the setbacks of implementing beam steering in mechanical antennas like microstrip antenna is that the directivity and, gain is low,and interference is very high.Whereas,in our project we have implemented beam steering using phased array antennas which has produced better results.So,an phased array antenna is electronically scanned antenna ,which produces a beam of radio waves that can be steered to different points based on our requirements by keeping the antenna stationary.Also,these type of antennas require less maintenance as compared to mechanical antennas

Published
2020
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19. Contributors

Author

Abdiev, Bakhtiyar, Agvaantseren, Bayarjargal, Akmatova, Kuluipa, Alamshev, Chagat, Alamshoev, Qurbonidin, Ale, Som, Alexander, Justine Shanti, Ali, Hussain, Allen, Priscilla, Amgalanbaatar, Sukh, Arenas-Rojas, Rafael, Aromov, Bakhtyor, Asykulov, Tolkunbek, Atzeni, Luciano, Augugliaro, Claudio, Ayusheev, Vladimir (Norbu), Azhunova, Maria, Baidavletov, Yerlik, Bayrakcismith, Rana, Bespalov, Maxim, Bhatia, Saloni, Bhatnagar, Yash Veer, Bijoor, Ajay, Blidchenko, Ekaterina Yu., Blomqvist, Leif, Boixader, Jordi, Borchers, David, Breitenmoser, Urs, Breitenmoser-Würsten, Christine, Bürki, Roland, Bykova, Elena, Cancellare, Imogene, Caragiulo, Anthony, Castner, Jennifer, Chelteuv, Slava, Chistopolova, Maria, Chundawat, Raghunandan S., Colorado, Apela, Criffield, Marc, Dadul, Jigmet, Dashzeveg, Unurzul, Davaa, Galbadrakh, Davletbakov, Askar, del Rey, Teresa, Dendhup, Tashi, Din, Jaffar Ud, Dorjgurkhem, Batbold, Driscoll, Carlos A., Duisekeyev, Bakytbek, Durbach, Ian, Dzhanyspaev, Altynbek, Erdenetsogt, Buyanbadrakh, Esipov, Alexander, Farrington, John D., Faryabi, Sorosh Poya, Fernández, Leonardo, Ferretti, Francesco, Fisher, Kim, Fominykh, Irina, Fox, Joseph L., García-Tardío, Maribel, Garmaev, Rinchin, Garrote, Germán, Ghoshal, Abhishek, Gilbert, Martin, Grachev, Alexey, Grachev, Yuriy, Gritsina, Mariya, Hacker, Charlotte, Hameed, Shoaib, Harris, Richard B., Heiner, Michael, Hemmingmoore, Heather, Hernandez-Blanco, José Antonio, Hillard, Darla, Hotham, Paul, Howard, Pippa, Hunter, Ben, Hunter, Don, Hussain, Shafqat, Ivashkina, Lyubov, Jackson, Rodney M., Janecka, Jan E., Jiménez, Ignacio, Johansson, Örjan, Jumabayuulu, Kubanychbek, Kachel, Shannon, Karimov, Khalil, Karnaukhov, Alexander, Khan, Ashiq Ahmad, Khan, Babar, Khanal, Gopal, Khanduri, Shakti Kant, Khatiwada, Ambika, Kholmatov, Ismoil, Khurelbataar, Erdembileg, Khuukhenduu, Tungalagtuya, Kiesecker, Joseph, Kitchener, Andrew C., Kochorov, Chyngyz, Kodi, Abinand Reddy, Koontz, Fred W., Korablev, Miroslav, Koshkin, Maxim, Kubanychbekov, Zairbek, Kuksin, Alexander, Kulenbekov, Rakhim, Kunkel, Kyran, Kushlin, Andrey, Lal, Panna, Lama, Wendy Brewer, Lanz, Tabea, Laporte, Bruno, Li, Juan, Liang, Xuchang, Lind, Thomas, Liu, Yanlin, Liu, Yixuan, Loginova, Olga, López, Guillermo, López-Parra, Marcos, Lovari, Sandro, Lu, Zhi, Lumpkin, Susan, Lyons, Anna, Lyu, Zhuoluo, MacKenzie, Darryl, Maheshwari, Aishwarya, Majumder, Bipasha, Malikov, Denis, Mallon, David, Malykh, Sergei, Mathur, V.B., McCann, Colleen, McCarthy, Kyle, McCarthy, Tom, Michel, Stefan, Mijiddorj, Tserenadmid Nadia, Miquelle, Dale G., Mishra, Charudutt, Mock, John, Modaqiq, Abdul Wali, Mohammad, Ghulam, Moheb, Zalmai, Moshier, Andrea, Munkhtsog, Bariushaa, Munkhtsog, Bayaraa, Murali, Ranjini, Musaev, Almaz, Naidenko, Sergey V., Namgail, Tsewang, Nasir, Syed Mahmood, Nawaz, Muhammad Ali, Nichols, James, Niraj, Shekhar Kumar, Noras, Sibylle, Novikova, Tatjana, Nygren, Emma, Nyul, Helen, Oakleaf, James, Onrato, Dave, Osmanova, Almagul, Ostrowski, Stéphane, Padmanabhan, Sujatha, Pal, Ranjana, Paley, Richard, Paltsyn, Mikhail, Pandey, Megh Bahadur, Poyarkov, Andrey, Prins, Herbert H.T., Protas, Yelizaveta, Quammen, Betsy, Raghunath, R., Rasheed, Tahir, Raymbekov, Zhaparkul, Reading, Richard P., Redpath, Stephen R., Riordan, Philip, Rosen, Tatjana, Rozhnov, Viatcheslav V., Ruiz, Gema, Rullman, Jennifer Snell, Rutherford, Brad, Ryskulova, Nargiza, Saidov, Abdusattor, Saidov, Nurali, Samanchina, Jarkyn, Samelius, Gustaf, Sanderson, Eric W., Sanjer, Amruddin, Saparbayev, Saltore, Sathyakumar, S., Schwartz, Karin R., Seidensticker, John, Seth, Anand, Shah, Karan B., Shah, Safdar Ali, Shaidoev, Sayfidin, Sharma, Koustubh, Sharma, Rishi Kumar, Shi, Kun, Simms, Anthony, Simón, Miguel A., Slight, Ted Waleij, Sliwa, Alexander, Sonam, Karma, Sorokin, Pavel A., Spitsyn, Sergei, Suresh, Shruti, Suryawanshi, Kulbhushansingh Ramesh, Sutherland, Chris, Tallian, Aimee, Tetzloff, Jay, Thakali, Shailendra, Thinley, Tanzin, Thomas, Patrick R., Tichomirow, Boris, Timbadia, Radhika, Trivedi, Pranav, Uluu, Kuban Jumabay, Varma, Keshav, Victurine, Ray, Wang, Jun, Wangchuk, Sonam, Wangchuk, Tshewang R., Weckworth, Byron, Weddle, Mike, Wegge, Per, Whitten, Tony, Wong, Wai-Ming, Xiao, Lingyun, Xueyang, Li, Yachmennikova, Anna A., Yamaguchi, Nobuyuki, Yin, Hang, Young, Juliette, Yunusov, Nodirjon, Zahler, Peter, Zakharenka, Andrew, Zhao, Xiang, Zhi, Lu, and Zhongtian, Zhang

Published
2024
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21. Analysis of GAA Junction Less NS FET Towards Analog and RF Applications at 30 nm Regime

Author

Asisa Kumar Panigrahy, Sudheer Hanumanthakari, Shridhar B. Devamane, Shruti Bhargava Choubey, M. Prasad, D. Somasundaram, N. Kumareshan, N. Arun Vignesh, Gnanasaravanan Subramaniam, Durga Prakash M, and Raghunandan Swain

Subjects
CMOS inverter, dielectrics, high-k, gate-all-around, quantum effects, transient analysis, Chemical technology, TP1-1185, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

This research focuses on a quantum model created using an entirely novel nanosheet FET. The standard model describes the performance of a Gate-all-around (GAA) Junction-less (JL) nanosheet device with a gate dielectric of SiO2 and HfO2, each having a thickness of 1 nm. The performance of both the classical and quantum models of the GAA nanosheet device is evaluated using the visual TCAD tool, which measures the ION, IOFF, ION/ IOFF, threshold voltage, DIBL, gain parameters (gm, gd, Av), gate capacitance, and cut-off frequency (fT). The device is suited for applications needing rapid switching since it has a low gate capacitance of the order of 10–18, according to the simulation results. A transconductance (gm) value of 21 µS and an impressive cut-off frequency of 9.03 GHz are displayed during device analysis. A detailed investigation has also been done into the P-type device response for the same device. Finally, the proposed GAA nanosheet device is used in the inverter model. The NSFET-based inverter, although having higher gate capacitance, has the shortest propagation latency.

Published
2024
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22. Spacer Dielectric Analysis of Multi-Channel Nanosheet FET for Nanoscale Applications

Author

Asisa Kumar Panigrahy, Veera Venkata Sai Amudalapalli, Depuru Shobha Rani, Muralidhar Nayak Bhukya, Hima Bindu Valiveti, Vakkalakula Bharath Sreenivasulu, and Raghunandan Swain

Subjects
CMOS inverter, DIBL, dielectric material, gate-all-round (GAA), power consumption, nanosheet (NS) FET, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

This work investigates the effect of single and dual-k spacer materials consisting of different dielectric constants (k) in optimized nano-channel gate-stack nanosheet (NS-FET) employing hafnium oxide and silicon dioxide as gate insulator to improve its sub-threshold performance. The effect of the external low-k spacer modification in the dual-k spacer has been shown by adjusting the inner high-k spacer. The drain-induced barrier lowering (DIBL) in this modification with dual-k spacer is 14 mV/V, a significant improvement above single spacer NS-FET. The Visual TCAD 3D Cogenda tool is used to examine the performance of the developed NS-FET with air, single, dual-k, and hybrid spacers. The CADENCE platform is used to perform circuit aspects. Additionally, a comparison of the device architecture’s performance study with respect to DC characteristics is made. DC parameters of the proposed device are established: $I_{ON}$ to $I_{OFF}$ ratio of approximately $10^{5}$ , DIBL of approximately 14 mV/V, sub-threshold swing (SS) of approximately 62 mV/dec, and low threshold voltage (Vth) of 0.38 V. The analysis on power consumption for advanced NS-FET is also analyzed with single-k and dual-k spacers. The performance of single-k and dual-k spacer dielectric variation for CMOS inverter is also shown. Furthermore, low power consumption by this NS-FET ensures improved device performance suitable for nanoscale semiconductor industries.

Published
2024
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23. A Faster and Robust Artificial Neural Network Based Image Encryption Technique With Improved SSIM

Author

Asisa Kumar Panigrahy, Shima Ramesh Maniyath, Mithileysh Sathiyanarayanan, Mohan Dholvan, T. Ramaswamy, Sudheer Hanumanthakari, N. Arun Vignesh, S. Kanithan, and Raghunandan Swain

Subjects
Artificial neural network, encryption, image security, SSIM, NPCR, UACI, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

A robust image encryption process is still one of the most challenging tasks in image security owing to massive degree and sensitivity nature of information in the form of pixels. The hurdles include greater computational difficulty, information loss during encryption, universality, applicability of the approach, and less scalability. Many image encryption methods existing in literature merely encrypt a portion of the data. Therefore, we propose a robust, dynamic, and sophisticated technique to enhance the encryption process to make it difficult for an attacker to gain unauthorized access to the pixel data. The proposed system uses a novel analytical research methodology through dynamically harnessing the potential of neural network that offers better forward and backward secrecy, dynamic control, and automatic management unlike any existing system. The encryption procedure comprises of two levels, first level is confusion- permutation of input image and second level is diffusion by Bit XOR operation for secure transmission and storage of images. Finally, the encrypted image is used as a target for training the Artificial Neural Network (ANN) model. ANN trained values are used for final level of encryption to develop a Neural Network (NN)-based cryptosystem, where the crypto analyst or the cracker need to know the number of adaptive iterations and the final weights for the encryption and decryption systems to crack the system which offers higher degree of resiliency towards potential threats. Results and security analysis show that our algorithm has good encryption effect, ability of resisting exhaustive attack, statistical attack, and differential attack. The system performance after implementing the proposed method is compared with existing methods present in literature with respect to processing time and Structural Similarity Index Measure (SSIM). Our proposed method offers significant reduction in encryption time and is approximately 10-15% faster than others with SSIM of 0.002165, close to zero after encryption. It also successfully balances the image quality with higher image security and lower computational complexity.

Published
2024
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25. 3D Annotation Tool Using LiDAR

Author

Shrinidhi Kulkarni, Raghunandan S, and Manjunath Chandrashekaraiah

Subjects
Data collection, business.industry, Computer science, Point cloud, Python (programming language), Data structure, computer.software_genre, Visualization, Lidar, RGB color model, Computer vision, Plug-in, Artificial intelligence, business, computer, computer.programming_language
Abstract

Data collection has become one of the most important aspects of daily life. In visualization of data, the number of points determines the clarity of data one can show. One such resource is a point cloud which is a data structure that represents a collection of huge amounts of multidimensional points and is used to store three-dimensional data. LiDAR is an active optical sensing device that provides extremely accurate x, y and z coordinates of the object it is reflected from. It transmits laser beams to a specific object and reflects its movements back to the receiver and analyzes the time span and measures the distance. The information obtained is used to construct a 3D point cloud of reflected obstacles. Also, by adding color information to the point cloud, we can be converted it from 3D to 4D. They are very dense and may be difficult to analyze since the point clouds can store massive amount of data. Handling such amount of data can be difficult and consumes a considerable amount of time for its visualization. We have designed a 3D Annotation Tool which is an application designed to annotate objects in a point cloud scene. We have annotated the objects by drawing 3D bounding boxes around them. The tool we have designed is capable of visualizing point cloud and RGB images together. It makes accessing and understanding of data easy for the observer. We have used PyQt package to design the GUI interface of the tool. PyQt is a Python binding of the cross-platform GUI toolkit Qt, implemented as a Python plugin. It provides features such as loading of point cloud and RGB images, rotation of RGB image, movement in point cloud and many more features.

Published
2019
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26. Size matters: Scale mismatch between space use patterns of tigers and protected area size in a Tropical Dry Forest

Author

Pradeep Kumar Malik, Koustubh Sharma, Abi Tamim Vanak, Neel Gogate, and Raghunandan S. Chundawat

Subjects
0106 biological sciences, Tropical and subtropical dry broadleaf forests, education.field_of_study, Ecology, Tiger, 010604 marine biology & hydrobiology, Home range, Population, Small population size, 010603 evolutionary biology, 01 natural sciences, Geography, Animal ecology, Local extinction, education, Protected area, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation
Abstract

India harbours the largest wild tiger population in the world and Tropical Dry Forest areas constitute the largest habitat for them. Recent extinctions, however, from two high profile tiger reserves, highlight the vulnerability of tiger in this habitat. Our examination of historic range areas for tigers shows that populations are disappearing at a faster rate in Tropical Dry Forest (64% sites suffering local extinction in 100 years) than in any other suitable habitat in India. Focusing on data from the Tropical Dry Forest of Panna Tiger Reserve in central India, we examine the spatial ecology of the tiger population prior to its local extinction. We analyse home range sizes, overlaps and shifts, as well as the range expansion and contraction of radio-collared tigers between 1996 and 2005. In this reserve, the average annual home range sizes for both males (n = 2) and females (n = 4) were three to four times larger than those reported so far from other tropical habitats in India — male: mean 179.3 ± 11.8 km2 (95% Fixed kernel; n = 7); female: mean 46.6 ± 3.7 km2; (95% Fixed kernel; n = 16). Adult female home ranges were exclusive and overlapped little with neighbouring female ranges (3 ± 1.46%, n = 6). Male home ranges were not exclusive: resident floater males shared space with territorial males and mated with resident females. Home ranges of all breeding radio-collared tigers extended beyond the protected area boundary and were exposed to edge effects that exist at the periphery and outside. With such spatial use patterns, security and management measures provided within the boundary are unlikely to be very successful in protecting the population. Protected Areas in Tropical Dry Forest across India are relatively small (366.92 ± 422.12 km2 SD) and historical trends point towards a scale-mismatch that exists between the size of Protected Areas and the space use requirements of tigers. This scale mismatch adds to the vulnerability of existing small populations and perhaps explains why tiger populations in Tropical Dry Forest have disappeared at a faster rate than in any other tiger habitat of the sub-continent.

Published
2016
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27. The Impact of Covid-19 on Selected Securities Traded on NSE India: An Empirical Analysis.

Author

Nair, Raghunandan S., Alur, Diya, and Devakumar, Christopher

Subjects
SECURITIES trading, COVID-19, GRANGER causality test, CAPITAL market
Abstract

This paper carries out a brief study of the impact of Covid-19 on seven indices of the Indian economy. For the analysis, risk, covariance, and Capital Market Line (CML) formulas have been applied to the same set of stocks belonging to two different time periods, i.e., pre- and post-Covid. Using these formulas and two tools, namely, the Granger Causality Test and the Augmented Dickey-Fuller Model (ADF), the impact of Covid-19 on the stocks has been analyzed. After a thorough analysis, it is concluded that the impact of the pandemic has been drastic on the selected stocks and the performance of the stocks has been highly fluctuating post Covid-19. [ABSTRACT FROM AUTHOR]

Published
2021

30. List of Contributors

Author

Bakhtiyar Abdiev, Bayarjargal Agvaantseren, Som Ale, Hussain Ali, Priscilla Allen, Chagat Almashev, George Amato, Sukh Amgalanbaatar, Zayiniddin Amirov, Maksat Anarbaev, Rafael Arenas, Bakhtyor Aromov, Roland Bürki, Rana Bayrakçısmith, Nick Beale, Yash Veer Bhatnagar, Ajay Bijoor, Ekaterina Yu. Blidchenko, Leif Blomqvist, Jordi Boixader, Ioana Botezatu, Urs Breitenmoser, Christine Breitenmoser-Würsten, Hafeez Buzdar, Elena Bykova, Anthony Caragiulo, Jennifer Castner, Raghunandan S. Chundawat, Apela Colorado, Marc Criffield, Jigmet Dadul, Unurzul Dashzeveg, Galbadrakh Davaa, Askar Davletbakov, Jaffar Ud Din, Batbold Dorjgurkhem, Carlos A. Driscoll, Bakytbek Duisekeyev, Alexander Esipov, John D. Farrington, Leonardo Fernández, Kim Fisher, Irina Fominykh, Joseph L. Fox, Maribel García-Tardío, Germán Garrote, Abhishek Ghoshal, James P. Gibbs, Martin Gilbert, Richard B. Harris, Michael Heiner, Heather Hemmingmoore, Jose A. Hernandez-Blanco, Darla Hillard, Paul Hotham, Pippa Howard, Don Hunter, Shafqat Hussain, Sergei Istomov, Rodney M. Jackson, Ignacio Ignacio Jiménez-Peréz, Örjan Johansson, Shannon Kachel, Khalil Karimov, Alexander Karnaukhov, Joseph Kiesecker, Ahmad Khan, Ashiq Ahmad Khan, Shakti Kant Khanduri, Ambika Khatiwada, Tungalagtuya Khuukhenduu, Andrew C. Kitchener, Chyngyz Kochorov, Fred W. Koontz, Miroslav Korablev, Svetlana Kozlova, Zairbek Kubanychbekov, Kyran Kunkel, Alexander Kuksin, Andrey Kushlin, Panna Lal, Wendy Brewer Lama, Tabea Lanz, Bruno Laporte, Juan Li, Thomas Lind, Yanlin Liu, Oleg Loginov, Irina Loginova, Guillermo López, Marcos López-Parra, Sandro Lovari, Zhi Lu, Susan Lumpkin, Aishwarya Maheshwari, Bipasha Majumder, David Mallon, Sergei Malykh, Vinod Bihari Mathur, Kyle McCarthy, Thomas McCarthy, Stefan Michel, Tserenadmid Mijiddorj, Dale G. Miquelle, Charudutt Mishra, John Mock, Abdul Wali Modaqiq, Ghulam Mohammad, Zalmai Moheb, Sayed Naqibullah Mostafawi, Bariushaa Munkhtsog, Ranjini Murali, Sergey V. Naidenko, Tsewang Namgail, Syed Mahmood Nasir, Muhammad Ali Nawaz, Sibylle Noras, Helen Nyul, James Oakleaf, Dave Onorato, Stéphane Ostrowski, Sujatha Padmanabhan, Richard Paley, Mikhail Paltsyn, Megh Bahadur Pandey, Andrey Poyarkov, Herbert H.T. Prins, Yelizaveta Protas, Lkhagvajav Purevjav, Betsy Gaines Quammen, Rangaswamy Raghunath, Richard P. Reading, Stephen R. Redpath, Teresa del Rey, Philip Riordan, Hugh S. Robinson, Tatjana Rosen, Viatcheslav V. Rozhnov, Vyacheslav Rozhnov, Gema Ruiz, Jennifer Snell Rullman, Brad Rutherford, Nargiza Ryskulova, Abdusattor Saidov, Nurali Saidov, Jarkyn Samanchina, Eric W. Sanderson, Sambandam Sathyakumar, John Seidensticker, Anand Seth, Karan B. Shah, Safdar Ali Shah, Koustubh Sharma, Rishi Kumar Sharma, Wasim Shehzad, Kun Shi, Miguel A. Simón, Anthony Simms, Alexander Sliwa, Karma Sonam, Pavel A. Sorokin, Sergei Spitsyn, Kulbhushansingh R. Suryawanshi, Jay Tetzloff, Lhendup Tharchen, Tanzin Thinley, Patrick R. Thomas, Boris Tichomirow, Radhika Timbadia, Pranav Trivedi, Kuban Jumabai uulu, Keshav Varma, Stephanie von Meibom, Sonam Wangchuk, Tshewang R. Wangchuk, Byron Weckworth, Mike Weddle, Per Wegge, Tony Whitten, Wai-Ming Wong, Lingyun Xiao, Anna A. Yachmennikova, Bayarjargal Yunden, Hang Yin, Nobuyuki Yamaguchi, Nodirjon Yunusov, Peter Zahler, Andrew Zakharenka, Xiang Zhao, Zhang Zhongtian, and Elena Zvychainaya

Published
2016
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31. Corrections to 'A Faster and Robust Artificial Neural Network Based Image Encryption Technique With Improved SSIM'

Author

Asisa Kumar Panigrahy, Shima Ramesh Maniyath, Mithileysh Sathiyanarayanan, Mohan Dholvan, T. Ramaswamy, Sudheer Hanumanthakari, N. Arun Vignesh, S. Kanithan, and Raghunandan Swain

Subjects
Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Presents corrections to the paper, Corrections to “A Faster and Robust Artificial Neural Network Based Image Encryption Technique With Improved SSIM”.

Published
2024
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32. Science deficiency in conservation practice: the monitoring of tiger populations in India

Author

John Seidenstricker, A. J. T. Johnsingh, James D. Nichols, Eric Dinerstein, James L. Smith, K. Ullas Karanth, Valmik Thapar, Raghunandan S. Chundawat, and Charles McDougal

Subjects
Estimation, Sociology of scientific knowledge, Ecology, Tiger, business.industry, Computer science, media_common.quotation_subject, Environmental resource management, Wildlife, Sampling (statistics), Context (language use), Census, business, Sophistication, Nature and Landscape Conservation, media_common
Abstract

Conservation practices are supposed to get refined by advancing scientific knowledge. We study this phenomenon in the context of monitoring tiger populations in India, by evaluating the ‘pugmark census method’ employed by wildlife managers for three decades. We use an analytical framework of modern animal population sampling to test the efficacy of the pugmark censuses using scientific data on tigers and our field observations. We identify three critical goals for monitoring tiger populations, in order of increasing sophistication: (1) distribution mapping, (2) tracking relative abundance, (3) estimation of absolute abundance. We demonstrate that the present census-based paradigm does not work because it ignores the first two simpler goals, and targets, but fails to achieve, the most difficult third goal. We point out the utility and ready availability of alternative monitoring paradigms that deal with the central problems of spatial sampling and observability. We propose an alternative sampling-based approach that can be tailored to meet practical needs of tiger monitoring at different levels of refinement.

Published
2003
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33. Status of the snow leopard Panthera uncia in Northwest India

Author

Raghunandan S. Chundawat, Pallav K. Das, Joseph L. Fox, and Satya P. Sinha

Subjects
Capra ibex, biology, Pseudois nayaur, Ecology, Range (biology), Panthera uncia, Endangered species, Leopard, fictional_universe, fictional_universe.character_species, biology.organism_classification, Geography, Snow leopard, Environmental protection, biology.animal, Panthera, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation
Abstract

A nine-month survey of snow leopard Panthera uncia status was carried out in selected regions of India's three northwestern Himalayan states. Evidence of snow leopard presence was most abundant in central Ladakh, decreased southward toward the crest of the Himalaya, and was least on the southern side of the main Himalaya, where evidence of common leopard Panthera pardus was also found near the timberline. Prey populations, primarily blue sheep Pseudois nayaur and Asiatic ibex Capra ibex , were also more plentiful in the areas surveyed to the north of the main Himalaya. Perhaps 400 snow leopard occur throughout northwest India. Several national parks in India's Himalaya probably include small numbers of snow leopard, but the stronghold of this species in India is apparently the trans-Himalayan ranges in Ladakh where new parks and reserves are being established, some in association with a ‘snow leopard recovery programme’ of the state of Jammu and Kashmir and a ‘Project Snow Leopard’ of the central Indian government. Because of the generally low density of snow leopard, conservation measures must also be considered within the large areas of its range lying outside parks and reserves.

Published
1991
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34. The mountain ungulates of Ladakh, India

Author

Raghunandan S. Chundawat, Chering Nurbu, and Joseph L. Fox

Subjects
education.field_of_study, Capra ibex, biology, Pseudois nayaur, Ecology, Population, Endangered species, Equus kiang, Tibetan gazelle, biology.organism_classification, Geography, Threatened species, education, Ecology, Evolution, Behavior and Systematics, Procapra, Nature and Landscape Conservation
Abstract

Eight species of wild ungulates occur in India's high-elevation steppe and mountain regions of Ladakh, with six listed as endangered and protected in India's or other international conservation laws. Two species are still quite common, with perhaps 11 000 blue sheep Pseudois nayaur and 6000 Asiatic ibex Capra ibex sibirica present today in Ladakh. Tibetan argali Ovis ammon hodgsoni, severely persecuted in the recent past, are now restricted to a few small populations totalling about 200 individuals in central and eastern Ladakh. The Ladakh urial Ovis vignei vignei, with current estimates of about 1000 in Ladakh, has apparently increased in recent years but is still threatened because its relatively accessible range is highly susceptible to human encroachment. Less than 50 Tibetan gazelle Procapra picticaudata remain in isolated pockets along the high eastern plains and about 200 Tibetan antelope Pantholops hodgsoni are usually present in Ladakh only during summer, wintering in China. The Tibetan wild ass or kiang Equus kiang has apparently recently increased in number, possibly approaching 1500 individuals in central and eastern Ladakh. A population of about 20 wild yak Bos grunniens is reported still to occur in one location along the eastern border with China. Following substantial sport hunting in the early part of this century and large reductions in some populations during border wars from the 1950s to the 1970s, conservation of these species has recently been enhanced by efforts of both the stage government of Jammu and Kashmir and India's central government, with the planning and initial designation of reserves in the establishment of a system of protected areas in Ladakh.

Published
1991
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36. Laser-scanning projection lithography for wafer-level packaging

Author

Klosner, M., Zemel, M., Raghunandan, S., and Jain, K.

Subjects
Technology application, Semiconductor wafers -- Technology application, X-ray lithography -- Testing -- Methods -- Technology application
Abstract

Seamless high-speed scanning of 300mm wafers with a 1X laser-projection exposure tool results in throughput up to 150wph in wafer-bumping applications. To meet the patterning needs of wafer-level packaging (WLP), […]

Published
2004

49. Estimation of tiger densities in the tropical dry forests of Panna, Central India, using photographic capture–recapture sampling.

Author

K. Ullas Karanth, Raghunandan S. Chundawat, James D. Nichols, and N. Samba Kumar

Subjects
*TIGERS, *ANIMAL populations, *FORESTS & forestry, *HABITATS
Abstract

Tropical dry-deciduous forests comprise more than 45% of the tiger (Panthera tigris) habitat in India. However, in the absence of rigorously derived estimates of ecological densities of tigers in dry forests, critical baseline data for managing tiger populations are lacking. In this study tiger densities were estimated using photographic capture–recapture sampling in the dry forests of Panna Tiger Reserve in Central India. Over a 45-day survey period, 60 camera trap sites were sampled in a well-protected part of the 542-km2 reserve during 2002. A total sampling effort of 914 camera-trap-days yielded photo-captures of 11 individual tigers over 15 sampling occasions that effectively covered a 418-km2 area. The closed capture–recapture model Mh, which incorporates individual heterogeneity in capture probabilities, fitted these photographic capture history data well. The estimated capture probability/sample, $\hat{p} = 0.04$, resulted in an estimated tiger population size and standard error ( $\hat{N}(S\hat{E}\hat{N}$)) of 29 (9.65), and a density ( $\hat{D}(S\hat{E}\hat{D}$)) of 6.94 (3.23) tigers/100 km2. The estimated tiger density matched predictions based on prey abundance. Our results suggest that, if managed appropriately, the available dry forest habitat in India has the potential to support a population size of about 9000 wild tigers. [ABSTRACT FROM AUTHOR]

Published
2004
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50. Science deficiency in conservation practice: the monitoring of tiger populations in India.

Author

K. Ullas Karanth, James D. Nichols, John Seidenstricker, Eric Dinerstein, James L. David Smith, Charles McDougal, A. J. T. Johnsingh, Raghunandan S. Chundawat, and Valmik Thapar

Subjects
TIGERS, SCIENTIFIC knowledge, WILDLIFE conservation, ANIMAL populations
Abstract

Conservation practices are supposed to get refined by advancing scientific knowledge. We study this phenomenon in the context of monitoring tiger populations in India, by evaluating the ‘pugmark census method’ employed by wildlife managers for three decades. We use an analytical framework of modern animal population sampling to test the efficacy of the pugmark censuses using scientific data on tigers and our field observations. We identify three critical goals for monitoring tiger populations, in order of increasing sophistication: (1) distribution mapping, (2) tracking relative abundance, (3) estimation of absolute abundance. We demonstrate that the present census-based paradigm does not work because it ignores the first two simpler goals, and targets, but fails to achieve, the most difficult third goal. We point out the utility and ready availability of alternative monitoring paradigms that deal with the central problems of spatial sampling and observability. We propose an alternative sampling-based approach that can be tailored to meet practical needs of tiger monitoring at different levels of refinement. [ABSTRACT FROM AUTHOR]

Published
2003
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