Jaypee Institute of Information Technology

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: Cluster analysis & Wireless sensor network. The organization has 2136 authors who have published 3435 publications receiving 31458 citations. The organization is also known as: JIIT Noida.

Nanocomposite blend gel polymer electrolyte for proton battery application

Abstract: A proton-conducting nanocomposite gel polymer electrolyte (GPE) system, [35{(25 poly(methylmethacrylate) (PMMA) + 75 poly(vinylidenefluoride-co-hexafluoropropylene) (PVdF-HFP)) + xSiO2} + 65{1 M NH4SCN in ethylene carbonate (EC) + propylene carbonate (PC)}], where x = 0, 1, 2, 4, 6, 8, 10, and 12, has been reported. The free standing films of the gel electrolyte are obtained by solution cast technique. Films exhibit an amorphous and porous structure as observed from X-ray diffractometry (XRD) and scanning electron microscopy (SEM) studies. Fourier transform infrared spectrophotometry (FTIR) studies indicate ion–filler–polymer interactions in the nanocomposite blend GPE. The room temperature ionic conductivity of the gel electrolyte has been measured with different silica concentrations. The maximum ionic conductivity at room temperature has been observed as 4.3 × 10−3 S cm−1 with 2 wt.% of SiO2 dispersion. The temperature dependence of ionic conductivity shows a typical Vogel-Tamman-Fulcher (VTF) behavior. The electrochemical potential window of the nanocomposite GPE film has been observed between −1.6 V and 1.6 V. The optimized composition of the gel electrolyte has been used to fabricate a proton battery with Zn/ZnSO4·7H2O anode and PbO2/V2O5 cathode. The open circuit voltage (OCV) of the battery has been obtained as 1.55 V. The highest energy density of the cell has been obtained as 6.11 Wh kg−1 for low current drain. The battery shows rechargeability up to 3 cycles and thereafter, its discharge capacity fades away substantially.

Simulation and cost analysis of group authentication protocols

Abstract: Radio Frequency Identification (RFID) is an efficient technology for identification, tracking and group proof construction. The multi-round protocols for authentication and group proof construction increase the cost with increase in participants. In this work, computational and communication cost of multi-round protocol is calculated to identify the protocol with least cost and high security. The computational cost is computed using number of rounds and messages, Message Authentication Code (MACO) operations, messages sent per participant and messages received per participant. The communication cost is computed using size of message sent and size of message received. In order to reduce the computational and communication cost, two lightweight group authentication protocols are selected for refinement. The protocols are: Juel's protocol, and Saito and Sakurai protocol. Three refinements are proposed which convert these protocols from two-party group construction to n-party group construction. Results show that refinements reduce the cost compared to Juel's protocol and Saito and Sakurai's protocol. It is observed that high security in group proof construction is still infeasible, thus if security is required to be maximum then multi-round protocol should be preferred. In this work, a multi-round authentication protocol of [1] is analyzed for comparative security analysis. Simulation analysis shows that performance of proposed authentication protocol in multi-round category as well as single-round category is better than state-of-art protocols.

A Particle Swarm Optimization-Based Heuristic for Software Module Clustering Problem

Abstract: The large-scale software module clustering problems (SMCPs) are very difficult to solve by using traditional analytical/deterministic-based optimization methods due to their high complexity and computation cost. Recently, particle swarm optimization (PSO) algorithm, a non-deterministic meta-heuristic search algorithm, gained wide attention and has been adapted to address the various large-scale science and engineering optimization problems. However, the applicability and usefulness of PSO algorithm have not been studied by any researcher till date to solve the SMCPs. In this paper, we introduce PSO-based module clustering (PSOMC), which partitions software system by optimizing: (1) intracluster dependency, (2) intercluster dependency, (3) a number of clusters, and (4) a number of module per cluster. To this contribution, we redefine the terms “position” and “velocity” of original PSO under the discrete scenario that best suited to SMCPs. To demonstrate the performance of the proposed approach, extensive experiments on six real-world SMCPs are carried out. We also compare our approach with existing state-of-the-art software module clustering meta-heuristic approaches (group genetic algorithm, hill climbing, and simulated annealing algorithm). The experimental results show that the proposed approach is effective and promising for solving SMCPs.

Natural Agents Targeting Mitochondria in Cancer.

Abstract: Mitochondria are the key energy provider to highly proliferating cancer cells, and are subsequently considered one of the critical targets in cancer therapeutics. Several compounds have been studied for their mitochondria-targeting ability in cancer cells. These studies' outcomes have led to the invention of "mitocans", a category of drug known to precisely target the cancer cells' mitochondria. Based upon their mode of action, mitocans have been divided into eight classes. To date, different synthetic compounds have been suggested to be potential mitocans, but unfortunately, they are observed to exert adverse effects. Many studies have been published justifying the medicinal significance of large numbers of natural agents for their mitochondria-targeting ability and anticancer activities with minimal or no side effects. However, these natural agents have never been critically analyzed for their mitochondria-targeting activity. This review aims to evaluate the various natural agents affecting mitochondria and categorize them in different classes. Henceforth, our study may further support the potential mitocan behavior of various natural agents and highlight their significance in formulating novel potential anticancer therapeutics.