Vatsal Shah

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The prevention of cyto- and genotoxicity of nanocarriers is an important task in nanomedicine. In the present investigation, we, at the first time using similar experimental conditions, compared genotoxicity of nanocarriers with different composition, architecture, size, molecular weight and charge. Poly(ethylene glycol) polymers, neutral and cationic(More)
PURPOSE The proposed project is aimed at enhancing the efficiency of epithelial ovarian cancer treatment and reducing adverse side effects of chemotherapy using nanotechnology. Overexpression of the CD44 membrane receptor results in tumor initiation, growth, cancer stem cells' specific behavior, development of drug resistance, and metastases. We hypothesize(More)
In agriculture research of automatic leaf disease detection is essential research topic as it may prove benefits in monitoring large fields of crops, and thus automatically detect symptoms of disease as soon as they appear on plant leaves. The term disease is usually used only for destruction of live plants. This paper provides various methods used to study(More)
Visceral leishmaniasis (VL) has been one of the most neglected tropical diseases in India. Concurrent and correct data on the burden of VL is vital to plan, allocate trained resources and to monitor the progress of the elimination program. More emphasis on integrated vector management can help in combating the disease spread. Effective surveillance, active(More)
Drugs with low aqueous solubility and permeability possess substantial challenges in designing effective and safe formulations. Synergistic solubility and permeability enhancement in a simple formulation can increase bioavailability and efficacy of such drugs. To overcome limitations of the clinical formulation of Taxol®, Paclitaxel (PTX) was reformulated(More)
In a clustered system, the general problems in load balancing are: ill-planned task allocation, poor performance, long response time, and low throughput. The work focuses on a novel algorithm of load balancing, which is based on the entropy value for both wired and wireless connections. To improve the performance of a system the scheduling and migration(More)
Association rule mining has attracted wide attention in both research and application area recently. Mining multilevel association rules is one of the most important branch of it. This paper introduces an improved apriori algorithm so called FP-growth algorithm that will help resolve two neck-bottle problems of traditional apriori algorithm and has more(More)
Stochastic gradient descent (SGD) is the method of choice for large-scale machine learning problems, by virtue of its light complexity per iteration. However, it lags behind its non-stochastic counterparts with respect to the convergence rate, due to high variance introduced by the stochastic updates. The popular Stochastic Variance-Reduced Gradient (Svrg)(More)
The problem of predicting unobserved entries of a partially observed matrix has found wide applicability in several areas, such as recommender systems, computational biology, and computer vision. Many scalable methods with rigorous theoretical guarantees have been developed for algorithms where the matrix is factored into low-rank components, and embeddings(More)
Performance of the TCP (Transmission Control Protocol) has been promising in wired networks. In wired network the packet loss is due to congestion. But the performance of TCP has degraded in wireless network where packet loss is not only due to congestion but to be also due to high bit error rates and handoffs. In this paper we review four methods to(More)