8,114 research outputs found
Bibliographics for the 983 eprints in the live archives of E-LIS : trends and status report up to 7th July 2004, based on author-self-archiving metadata
No full textThe priority for ideas and philosophy related to "Network Theory" have been traced back and documented by Braun(2004),and credit goes to Karinthy(1929).The IT has empowered to realise it, as the most practical phenomena and it is no more a humour. The OAI (Open Archives Initiatives)and ACIS (Academic Contributor Information System)are progressive in the direction ,which may lead to realise the "Collective Genius" at global level. Focus of present study is on Author-Self-Archiving (A-S-A)Metadata of the 983 Eprints in the Live Archives of the E-LIS (EPrints of Library and Information Science),which were approved till 7th July 2004.The A-S-A Metadata was used for librametric analysis. Self-explanatory bibliographics are illustrated.The highlights include: Conference papers (34%); highest approval, June 2004 (28%); published archives (76%);not refereed (52%); not in public domain (60%); highest self-archiving-author (De Robbio, Antonella).The Nos. of EPrints having single JITA domain specifications were: Theoretical and general aspects of libraries and information(27); Information use and sociology of information(80);Users,literacy and reading(13);Libraries as physical collections(30);Publishing and legal issues(57);Management(13);Industry, profession and education(36);Information sources, supports, channels(113) ; Information treatment for information services, Information functions and techniques (101); Technical services libraries, archives and museums(25); Housing technologies(1); Information technology and library technology(92); and Inter-domainery (395) i.e. having specifications of two or more than two JITA classes
sj-docx-1-ppj-10.1177_17504589231180737 – Supplemental material for Comparative evaluation of isoflurane and desflurane for postoperative cognitive decline in elderly patients: A prospective observational pilot study
No full textSupplemental material, sj-docx-1-ppj-10.1177_17504589231180737 for Comparative evaluation of isoflurane and desflurane for postoperative cognitive decline in elderly patients: A prospective observational pilot study by Damarla Haritha, Soumya Sarkar, Souvik Maitra, Seema Kashyap, Rohit Verma, Sujata Satapathy, Lokesh Kashyap, Akhil Kant Singh, Lata Singh, Bikash Ranjan Ray, Rahul Kumar Anand, Shailendra Kumar and Puneet Khanna in Journal of Perioperative Practice</p
A Unified Shell model for Buoyancy-Driven Turbulence
No full textWe construct a unified shell model for stably stratified and convective turbulence. Shell model simulation of stably stratified flow in turbulent regime exhibit Bolgiano-Obukhbov (BO) scaling in which the kinetic energy spectrum varies as . However, simulation of convective turbulence shows Kolmogorov's spectrum. These results are consistent with the direct numerical simulations of Kumar {\em et al.} [Phys. Rev. E {\bf 90}, 023016 (2014)]. We also observe a dual scaling ( and ) for a limited range of parameters in stably stratified flow
Investigating cloud-cloud collisions and hub-filament systems: pathways to massive star formation
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Architecture and security issues in fog computing applications Advances in computer and electrical engineering (ACEE) book series./ [edited by] Sam Goundar, S. Bharath Bhushan, Praveen Kumar Rayani.
No full textIncludes bibliographical references and index.As the progression of the internet continues, society is finding easier, quicker ways of simplifying their needs with the use of technology. With the growth of lightweight devices, such as smart phones and wearable devices, highly configured hardware is in heightened demand in order to process the large amounts of raw data that are acquired. Connecting these devices to fog computing can reduce bandwidth and latency for data transmission when associated with centralized cloud solutions and uses machine learning algorithms to handle large amounts of raw data. The risks that accompany this advancing technology, however, have yet to be explored. Architecture and Security Issues in Fog Computing Applications is a pivotal reference source that provides vital research on the architectural complications of fog processing and focuses on security and privacy issues in intelligent fog applications. While highlighting topics such as machine learning, cyber-physical systems, and security applications, this publication explores the architecture of intelligent fog applications enabled with machine learning. This book is ideally designed for IT specialists, software developers, security analysts, software engineers, academicians, students, and researchers seeking current research on network security and wireless systems.1. Fog resource allocation through machine learning algorithm / Gowri A. S., Shanthi Bala P. -- 2. A novel resource management framework for fog computing by using machine learning algorithm / Shanthi Thangam Manukumar, Vijayalakshmi Muthuswamy -- 3. [Retracted] Security issues in fog computing for Internet of Things / D.N. Kartheek, Bharath Bhushan -- 4. Analysis of identity-based cryptography in Internet of Things (IoT) / Aravind Karrothu, Jasmine Norman -- 5. Cloud security architecture based on fully homomorphic encryption / Vaishali Ravindra Thakare, K. John Singh -- 6. Object detection in fog computing using machine learning algorithms / Peyakunta Bhargavi, Singaraju Jyothi -- 7. Distributed intelligence platform to the edge computing / Xalphonse Inbaraj -- 8. Internet of Things and fog computing applications in intelligent transportation systems / Korupalli V. Rajesh Kumar, K. Dinesh Kumar, Ravi Kumar Poluru, Syed Muzamil Basha, M. Praveen Kumar Reddy -- 9. Agribot / Ravi Kumar Poluru, M. Praveen Kumar Reddy, Rajesh Kaluri, Kuruva Lakshmanna, G. Thippa Reddy -- 10. Towards efficient resource management in fog computing : a survey and future directions / M. Sudhakara, K. Dinesh Kumar, Ravi Kumar Poluru, R. Lokesh Kumar, S. Bharath Bhushan.1 online resource (205 pages)
Story of the Story-Teller: A Conversation with Ramendra Kumar
No full textRamendra Kumar (Ramen) is an award-winning writer, storyteller and inspirational speaker with 42 books to his name. Ramen’s writings have been published by many of the leading publishers in the county and translated into 30 languages. They have found a place in several textbooks and anthologies. He has written across all genres ranging from picture books to adult fiction, satire, poetry, travelogues, biographies and on issues related to parenting and relationships. He has been invited to literary festivals held in Denmark, Greece, Sharjah, Sri Lanka as well Indian events including the prestigious Jaipur Litfest to conduct storytelling sessions and creative writing workshops. He has also been empanelled by Pearson India Education Services as well as several schools to conduct workshops. He was nominated as a Jury Member for the Best Children’s Author Category of The Times of India’s ‘Women AutHer’ Awards 2020. Many of his stories have been showcased by popular audio streaming, apps both within and outside the country, such as Spotify, Gaatha, Talking Stories Radio – London et al.
An Engineer & an MBA, Ramen was serving as the General Manager (Corporate Communications), SAIL, Rourkela Steel Plant, when he took Voluntary Retirement to pursue his passion, in August 2020. To know more about the writer, you can visit his website www.ramendra.in & his page on Wikipedia. Dr. Sagar Kumar Sharma interviews the author and unfolds the pages of his life.
 
Anomaly-Based DNN Model for Intrusion Detection in IoT and Model Explanation: Explainable Artificial Intelligence
No full textIoT has gained immense popularity recently with advancements in technologies and big data. IoT network is dynamically increasing with the addition of devices, and the big data is generated within the network, making the network vulnerable to attacks. Thus, network security is essential, and an intrusion detection system is needed. In this paper, we proposed a deep learning-based model for detecting intrusions or attacks in IoT networks. We constructed a DNN model, applied a filter method for feature reduction, and tuned the model with different parameters. We also compared the performance of DNN with other machine learning techniques in terms of accuracy, and the proposed DNN model with weight decay of 0.0001 and dropout rate of 0.01 achieved an accuracy of 0.993, and the reduced loss on the NSL-KDD dataset having five classes. DL models are a black box and hard to understand, so we explained the model predictions using LIME.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.Cyber Securit
Engineering of redox-triggered polymeric lipid hybrid nanocarriers for selective drug delivery to cancer cells
No full textTunable redox-sensitive polymeric-lipid hybrid nanocarriers (RS-PLHNCs) were fabricated using homogenization and nanoprecipitation methods. These nanocarriers were composed of novel redox-cholesterol with disulfide linkages and synthesized by conjugating cholesterol with dithiodipropionic acid via esterification. Berberine (BBR) was loaded into the fabricated nanocarriers to investigate the selective uptake of BBR by cancer cells as well as its release and enhanced cytotoxicity. The optimized BBR nanocarriers BBR NP-17 and -18 exhibited a spherical shape and uniform distribution, with a particle size of 124.7 +/- 1.2 nm and 185.2 +/- 1.6 nm and a zeta potential of -5.9 +/- 2.5 mV and -20.3 +/- 1.1 mV, respectively. These NCs released >80% BBR in a simulated intracellular tumor microenvironment (TME), while only 30%-45% was released under normal physiological conditions. The accelerated drug release in the TME was due to disulfide bond cleavage and ester bond hydrolysis in the presence of GSH and acidic pH, whereas under normal conditions, the NCs remained stable/undissociated. Cellular uptake studies confirmed enhanced BBR uptake in GSH-rich cancer cells (H1975) compared with normal cells (BEAS-2B and HEK293A). Following uptake, compared with the free form of the drug, the optimized nanocarriers displayed significant selective cytotoxicity and apoptosis in cancer cells by notably downregulating anti-oxidant (NFE2L2, HO-1, NQO1, and TXRND1) and anti-apoptotic (MCL-1) genes while upregulating pro-apoptotic genes (PUMA and NOXA). This resulted in increased oxidative stress, thereby inducing selective apoptosis in the GSH-rich lung cancer cells. These results suggest that the synthesized novel NCs hold great potential for specifically delivering drugs to cancer cells (with a reduced environment) while sparing normal cells, thus ensuring safe and efficient cancer therapy.The authors thank the full financial support by intramural funding (DPR) received from National Institute of Science Education and Research (NISER), Department of Atomic Energy (DAE), Government of India (GoI). B.S.L., R.C., and S.K.M., would like to acknowledge NISER, DAE, GoI for the research fellowship. The authors would also like to acknowledge the support provided by TEM imaging facility, Centre for Interdisciplinary Sciences (CIS), NISER, for their assistance in TEM imaging and Dr Tathagata Mukherjee, Somlata Khamaru, and Kshyama Subhadarsini Tung, School of Biological Sciences (SBS), NISER, during FACS analysis. The authors also acknowledge Dr Amit Jaiswal, IIT-Mandi, India, for helping with the HEK293A cell line for in vitro cell based studies. The authors are thankful to acknowledge Dr Soumendra Rana, IITBhubaneswar, India, for mass characterization
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