Institution
Jaypee Institute of Information Technology
Education•Noida, Uttar Pradesh, India•
About: Jaypee Institute of Information Technology is a education organization based out in Noida, Uttar Pradesh, India. It is known for research contribution in the topics: Computer science & Cluster analysis. The organization has 2136 authors who have published 3435 publications receiving 31458 citations. The organization is also known as: JIIT Noida.
Papers published on a yearly basis
Papers
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TL;DR: This paper addresses the data processing techniques such as data denoising, data outlier detection, missing data imputation and data aggregation, and elaborates on the necessity of data fusion and various data fusion methods such as direct fusion, associated feature extraction, and identity declaration data fusion.
Abstract: In the recent era of the Internet of Things, the dominant role of sensors and the Internet provides a solution to a wide variety of real-life problems. Such applications include smart city, smart healthcare systems, smart building, smart transport and smart environment. However, the real-time IoT sensor data include several challenges, such as a deluge of unclean sensor data and a high resource-consumption cost. As such, this paper addresses how to process IoT sensor data, fusion with other data sources, and analyses to produce knowledgeable insight into hidden data patterns for rapid decision-making. This paper addresses the data processing techniques such as data denoising, data outlier detection, missing data imputation and data aggregation. Further, it elaborates on the necessity of data fusion and various data fusion methods such as direct fusion, associated feature extraction, and identity declaration data fusion. This paper also aims to address data analysis integration with emerging technologies, such as cloud computing, fog computing and edge computing, towards various challenges in IoT sensor network and sensor data analysis. In summary, this paper is the first of its kind to present a complete overview of IoT sensor data processing, fusion and analysis techniques.
117 citations
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TL;DR: In this article, the authors obtained an anisotropic ana-log of the Durgapal and Fuloria (Gen Relativ Gravit 17:671, 1985) perfect fluid solution.
Abstract: In the present paper we obtain an anisotropic ana- log of the Durgapal and Fuloria (Gen Relativ Gravit 17:671, 1985) perfect fluid solution. The methodology consists of contraction of the anisotropic factorwith the help of both metric potentials e ν and e λ . Here we consider e λ the same as Durgapal and Fuloria (Gen Relativ Gravit 17:671, 1985) did, whereas e ν is as given by Lake (Phys Rev D 67:104015, 2003). The field equations are solved by the change of depen- dent variable method. The solutions set mathematically thus obtained are compared with the physical properties of some of the compact stars, strange star as well as white dwarf. It is observed that all the expected physical features are available related to the stellar fluid distribution, which clearly indicates the validity of the model.
114 citations
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TL;DR: A novel two-dimensional (2D) histogram-based segmentation method to improve the efficiency of multi-level image thresholding segmentation and results affirm that the proposed method outperforms the other 2D histograms-based image thresholded segmentation methods on majority of performance parameters.
112 citations
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TL;DR: A surface plasmon resonance (SPR) based fiber optic sensor with bi layers of metal-ZnO is proposed and theoretically studied in this paper, where the top ZnO layer is shown to protect the metallic layer from oxidation and to enhance the sensitivity of the SPR sensor.
Abstract: A surface plasmon resonance (SPR) based fiber optic sensor with bi layers of metal–ZnO is proposed and theoretically studied. Three metals: gold (Au), silver (Ag) and copper (Cu) have been exercised in the study. The top ZnO layer is shown to protect the metallic layer from oxidation and to enhance the sensitivity of the SPR sensor. Besides, increase in thickness of Au/Ag/Cu layer increases the sensitivity of SPR sensor for all thicknesses of ZnO layers. For a fixed thickness of ZnO layer, the sensitivity of sensor is larger for Au layer than that of Ag/Cu layer. Sensitivity also increases with increase in ZnO layer thickness for all thicknesses of Au/Ag/Cu layers. The SPR sensor based on bi layers of 40 nm Au–15 nm ZnO demonstrates the maximum sensitivity of 3161 nm/RIU.
111 citations
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01 Jan 2015TL;DR: This chapter highlights the main themes from studies on free radicals, antioxidants, and oxidative stress and effect of oxidative stress in diseases.
Abstract: Reactive oxygen species (ROS) is a collective term used for oxygen-derived free radicals (superoxide, hydroxyl radical, nitric oxide) and non-radical oxygen derivatives of high reactivity (singlet oxygen, hydrogen peroxide, peroxynitrite, hypochlorite). ROS can be either harmful or beneficial to the body. An imbalance between formation and removal of free radicals can lead to a pathological condition called as oxidative stress. However, the human body employs molecules known as antioxidants to counteract these free radicals. But late several studies have indicated that antioxidants can also have deleterious effects on human health depending on dosage and bioavailability. This makes it essential to analyze the extent of utility of antioxidants in the improvement of human health. It is noteworthy that if the generation of free radicals exceeds the protective effects of antioxidants, this can cause oxidative damage which accumulates during the life cycle, and this has been implicated in aging and age-dependent diseases such as cardiovascular disease, cancer, neurodegenerative disorders, and other chronic conditions. This chapter highlights the main themes from studies on free radicals, antioxidants, and oxidative stress and effect of oxidative stress in diseases.
108 citations
Authors
Showing all 2176 results
Name | H-index | Papers | Citations |
---|---|---|---|
Sanjay Gupta | 99 | 902 | 35039 |
Mohsen Guizani | 79 | 1110 | 31282 |
José M. Merigó | 55 | 361 | 10658 |
Ashish Goel | 50 | 205 | 9941 |
Avinash C. Pandey | 45 | 301 | 7576 |
Krishan Kumar | 35 | 242 | 4059 |
Yogendra Kumar Gupta | 35 | 183 | 4571 |
Nidhi Gupta | 35 | 266 | 4786 |
Anirban Pathak | 33 | 214 | 3508 |
Amanpreet Kaur | 32 | 367 | 5713 |
Navneet Sharma | 31 | 219 | 3069 |
Garima Sharma | 31 | 97 | 3348 |
Manoj Kumar | 30 | 108 | 2660 |
Rahul Sharma | 30 | 189 | 3298 |
Ghanshyam Singh | 29 | 263 | 2957 |