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.

Tracy–Singh Product and Genetic Whale Optimization Algorithm for Retrievable Data Perturbation for Privacy Preserved Data Publishing in Cloud Computing

Abstract: This paper proposes a retrievable data perturbation model for overcoming the challenges in cloud computing. Initially, genetic whale optimization algorithm (genetic WOA) is developed by integrating genetic algorithm (GA) and WOA for generating the optimized secret key. Then, the input data and the optimized secret key are given to the Tracy–Singh product-based model for transforming the original database into perturbed database. Finally, the perturbed database can be retrieved by the client, if and only if the client knows the secret key. The performance of the proposed model is analyzed using three databases, namely, chess, T10I4D100K and retail databases from the FIMI data set based on the performance metrics, privacy and utility. Also, the proposed model is compared with the existing methods, such as Retrievable General Additive Data Perturbation, GA and WOA, for the key values 128 and 256. For the key value 128, the proposed model has the better privacy and utility of 0.18 and 0.83 while using the chess database. For the key value 256, the proposed model has the better privacy and utility of 0.18 and 0.85, using retail database. From the analysis, it can be shown that the proposed model has better privacy and utility values than the existing models.

An integrator circuit using differential difference current conveyor transconductance amplifier

Abstract: An integrator circuit is presented in this paper that has used Differntial Difference Current Conveyor Transconductance Amplifier (DDCCTA). It has one DDCCTA and one passive component. It has been realized only with first order low pass response. The operation of the circuit has been observed and enforced at a supply voltage of ± 1.8V (bias current 50pA) using cadence and the model parameters of gpdk 180nm CMOS technology. The worthy of the proposed circuit has been test checked using DDCCTA and further tested for its efficiency on a laboratory breadboard. In this commercially available AD844AN and LM13600 ICs are used. Further, the circuit presented in this paper is impermeable to noise, possessing low voltage and insensitive to temperature.

Development and evaluation of an IgY based silica matrix immunoassay platform for rapid onsite SEB detection

Abstract: The present study involves immunoassay platform development based on a surface functionalized silica matrix for rapid onsite detection of Staphylococcal enterotoxin B (SEB). Silica matrix functionalization as well as the immunoassay parameters was experimentally designed and optimized through response surface methodology (RSM). Silica surface functionalization was carried out with hydrofluoric acid (HF), ammonia, 3-aminopropyl triethoxysilane (APTES) and glutaraldehyde (GA). The RSM optimized matrix functionalization parameters for HF, ammonia, APTES and GA were determined to be 10%, 40%, 20% and 10% (V/V), respectively. Antibodies for the study were generated against recombinant SEB toxin in rabbit (anti-SEB IgG) and chicken (anti-SEB IgY). Subsequently, antibodies were immobilized on the functionalized silica matrix and were further characterized by SEM and contact angle measurements to elucidate the surface uniformity and degree of hydrophilicity. The immunoassay platform was developed with anti-SEB IgG (capturing agent) and anti-SEB IgY (revealing partner). The limit of detection (LOD) of the developed platform was determined to be 0.005 μg mL−1 and no cross-reactivity with similar toxins was observed. Upon co-evaluation with a standard ELISA kit (Chondrex, Inc) against various field isolates, the platform was found to be on par and reliable. In conclusion, the developed method may find better utility in onsite detection of SEB from resource-poor settings.

Traffic Analysis Using IoT for Improving Secured Communication

Abstract: Internet of Things can be simply referred to as Internet of entirety which is the network of things enclosed with software, sensors, electronics that allow them to gather and transmit the data. Because of the various and progressively malevolent assaults on PC systems and frameworks, current security apparatuses are frequently insufficient to determine the issues identified with illegitimate clients, unwavering quality, and to give vigorous system security. Late research has demonstrated that in spite of the fact that system security has built up, a significant worry about an expansion in illicit interruptions is as yet happening. Addressing security on every occasion or in every place is a really important and sensitive matter for many users, businesses, governments, and enterprises. In this research work, we are going to propose a secure IoT architecture for routing in a network. It mainly aims to locate the malicious users in IoT routing protocols. The proposed mechanism is compared with the state-of-the-art work and the results show that the proposed work performs well.

Identification of Faults in HVDC System using Wavelet Analysis

Abstract: The identification and classification of faults is important for safe and optimal operation of power systems. For secure operation of a system a feasible approach is to monitor signals so that accurate and rapid classification of fault is possible for making correct protection control.To identify HVDC faults by using pure frequency or pure time domain based method is difficult. The pure frequency domain based methods are not suitable for time varying transients and the pure time domain based methods are very easily influenced by noise.Wavelet analysis is one of the methods used for providing discriminative features with small dimensions to classify different disturbances in HVDC transmission system. This paper explores the application of wavelet based Multi-Resolution Analysis (MRA) for signal decomposition to monitor some faults in HVDC system. The faults in HVDC system can be classified by monitoring the signals both on AC and DC sides of the HVDC system. The fault classifier can be developed from these monitored signals which show promising features to classify different disturbances in the HVDC system. DOI: http://dx.doi.org/10.11591/ijece.v2i2.179