Vignan University

About: Vignan University is a education organization based out in Guntur, Andhra Pradesh, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 1138 authors who have published 1381 publications receiving 7798 citations.

Influence of geopolymer aggregates on microstructural and strength characteristics of OPC concrete

Abstract: This paper investigated the physical and microstructural properties of a manufactured fly ash–GGBFS-based geopolymer aggregates. The analysis on geopolymer aggregate included specific gravity, water absorption, crushing value, impact value, attrition, loss angles abrasion, and angularity index. Besides, scanning electron microscopy (SEM) was done to diagnose the microstructure of geopolymer aggregates. In contrast, the compressive strength of geopolymer aggregate-based ordinary Portland cement (OPC) concrete was studied. Besides, the microstructure and the pore structure development of geopolymer aggregate-based concrete at the interfacial transition zone (ITZ) were examined through SEM. In this paper, three types of geopolymer aggregates are prepared by replacing 0, 10, and 20% of fly ash with GGBFS cured under an oven (at 60° for 12 h) and ambient conditions. The experimental data showed that the dry density of manufactured geopolymer aggregate concrete was less than that of natural aggregate-based concrete; it is about 1000 kg/m3 for geopolymer aggregate. However, concrete prepared geopolymer aggregates (80% fly ash and 20% GGBFS) showed higher resistance among all the tests and giving similar results at ambient and oven curing.

Adaptive noise cancellation using LMS algorithm in Monte Carlo simulation

Abstract: This brief presents the concept of adaptive noise cancellation using LMS algorithm. The method uses a “primary input” containing the corrupted signal and a “reference input” containing noise correlated in some unknown way with the primary noise. The reference input is adaptively filtered and subtracted from the primary input to obtain the signal estimate. Extensive Monte Carlo Simulation is carried out and the results are presented using MATLAB.

QoS Maintenance in Cognitive Radio Networks with Priority-Supporting Novel Channel Allocation Method

Abstract: Satisfying the Quality of Service (QoS) is often a challenge in cognitive radio networks, because they depend on opportunistic channel accessing. In this context, appropriate pricing of vacant channels that is linked to the preference in their allocation, is found to be useful. However, ambiguity on the possible price at which the channel would be allotted is still a concern. In this work, an auction mechanism in which maximum value of the bid is predefined is proposed. With this, users quote their bid values as per their needs of getting the channels, up to the predefined maximum allowed bid price. However, final price of allocation is decided based on the sum total demand from all the users and the availability of vacant channels. Performance of the system is found in terms of blocking probabilities of secondary users and revenues to primary users. The proposed system is found to yield similar quantum of revenues as that of the Generalized Second Price (GSP) auction, while offering much lesser blocking probabilities to high-priority users to satisfy their QoS requirements.

A Self-Powered, Real-Time, NRF24L01 IoT-Based Cloud-Enabled Service for Smart Agriculture Decision-Making System

Abstract: Agriculture has been benefited by advanced research and development due to Internet of Things (IoT)-based automation. Environmental and deployment sensors such as DHT11, soil moisture, soil temperature and others are used in agriculture field production and IoT technology is being employed to assess field environment in smart agriculture. Most of the existing systems work only on the air temperature and humidity sensing, for agriculture health monitoring. These systems have limitations to send sensing data from long distances. The approximate range of data communication for these systems is below 100 m which is quite less for agriculture field coverage, in general. As a result of this, agricultural crop production is not up to the mark. We propose an architecture framework to address the above-mentioned shortcomings. This proposed architecture can be applied for long range communications with no data loss and no interference in the information. The system employs an NRF24L01 transceiver module, which works at 2.4 GHz for long-distance communications towards monitoring of agriculture parameters. This research is aimed into a suitable, feasible, and integrated Internet of Things (IoT) technique for smart agriculture. The proposed system saves energy and boosts productivity. This method reduces human effort while evaluating heat index measurement parameters in order to monitor the environment for optimal agriculture growth. The current consumption and life expectancy of the Agriculture Wireless Monitoring Unit (AWMU) are 0.02819 Amperes and 3 days 20 hours 13 minutes and 47 seconds, respectively, according to the experimental analysis. In an open environmental area, the maximum transmission distance for AWMU is up to 200 meters from the wireless access point.