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: 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.

Multi-objective Grey Wolf Optimizer for improved cervix lesion classification

Abstract: This is a novel effort towards effective characterization of cervix lesions from CECT images.Two different approaches have been adopted for designing multi-objective binary GWO algorithms.For the utilized cases, Non-dominated Sorting based GWO dominates the other meta-heuristics based methods compared with.Cervix lesions are up to 91.1% accurately classified as benign and malignant with only five features selected by NSGWO.Efficiency of NSGWO is further verified on high-dimensional microarray gene expression datasets available online. Cervical cancer is one of the vital and most frequent cancers, but can be cured effectively if diagnosed in the early stage. This is a novel effort towards effective characterization of cervix lesions from contrast enhanced CT-Scan images to provide a reliable and objective discrimination between benign and malignant lesions. Performance of such classification models mostly depends on features used to represent samples in a training dataset. Selection of optimal feature subset here is NP-hard; where, randomized algorithms do better. In this paper, Grey Wolf Optimizer (GWO), which is a population based meta-heuristic inspired by the leadership hierarchy and hunting mechanism of grey wolves has been utilized for feature selection. The traditional GWO is applicable for continuous single objective optimization problems. Since, feature selection is inherently multi-objective; this paper proposes two different approaches for multi-objective binary GWO algorithms. One is a scalarized approach to multi-objective GWO (MOGWO) and the other is a Non-dominated Sorting based GWO (NSGWO). These are used for wrapper based feature selection that selects optimal textural feature subset for improved classification of cervix lesions. For experiments, contrast enhanced CT-Scan (CECT) images of 62 patients have been used, where all lesions had been recommended for surgical biopsy by specialist. Gray-level co-occurrence matrix based texture features are extracted from two-level decomposition of wavelet coefficients of cervix regions extracted from CECT images. The results of proposed approaches are compared with mostly used meta-heuristics such as genetic algorithm (GA) and firefly algorithm (FA) for multi-objective optimization. With better diversification and intensification, GWO obtains Pareto solutions, which dominate the solutions obtained by GA and FA when assessed on the utilized cervix lesion cases. Cervix lesions are up to 91% accurately classified as benign and malignant with only five features selected by NSGWO. A two-tailed t-test was conducted by hypothesizing the mean F-score obtained by the proposed NSGWO method at significance level=0.05. This confirms that NSGWO performs significantly better than other methods for the real cervix lesion dataset in hand. Further experiments were conducted on high dimensional microarray gene expression datasets collected online. The results demonstrate that the proposed method performs significantly better than other methods selecting relevant genes for high-dimensional, multi-category cancer diagnosis with an average of 12.82% improvement in F-score value.

Nanotechnology: Emerging Tool for Diagnostics and Therapeutics

Abstract: Nanotechnology is an emerging technology which is an amalgamation of different aspects of science and technology that includes disciplines such as electrical engineering, mechanical engineering, biology, physics, chemistry, and material science. It has potential in the fields of information and communication technology, biotechnology, and medicinal technology. It involves manipulating the dimensions of nanoparticles at an atomic scale to make use of its physical and chemical properties. All these properties are responsible for the wide application of nanoparticles in the field of human health care. Promising new technologies based on nanotechnology are being utilized to improve diverse aspects of medical treatments like diagnostics, imaging, and gene and drug delivery. This review summarizes the most promising nanomaterials and their application in human health.

Controlled bidirectional remote state preparation in noisy environment: a generalized view

Abstract: It is shown that a realistic controlled bidirectional remote state preparation is possible using a large class of entangled quantum states having a particular structure. Existing protocols of probabilistic, deterministic and joint remote state preparation are generalized to obtain the corresponding protocols of controlled bidirectional remote state preparation (CBRSP). A general way of incorporating the effects of two well-known noise processes, the amplitude-damping and phase-damping noise, on the probabilistic CBRSP process is studied in detail by considering that noise only affects the travel qubits of the quantum channel used for the probabilistic CBRSP process. Also indicated is how to account for the effect of these noise channels on deterministic and joint remote state CBRSP protocols.