Maximisation of Expected Target Damage Value

The weabon assignment problem has been modelled as a nonlinear integer programming problem'. The problem is to assign weapons to the targets to maximise the optimum-target damagevalue. There are constsainfs on various types of weapons available and on minimum number of weapons by types to be assigned to various targets. The objective function is nonlinear, theconstraints are linear in nature, and the,decision variables are restricted to be integers.The results obtained by Bracken and McCormick' should not be applied to solve t h e problem ofweapon assignment to target to maximise the optimum target damage value, because firstly, the results violate the constraints, and secondly, instead of using the integer programming techniques, the crude method of rounding off has been used,to obtain the sglution.-In this study, the I-GRST algorithm developed by ~ c eapnd Pant2.'h as been used to solve the weapon 3ssignnient problem. The results obtained are better than the results ohrn~nedb y Bracken ;~ndM cCormick'nnd also do not violate any constraints

Object Detection using Particle Swarm Optimisation and Kalman Filter to Track Partially occluded Targets

Motion estimation, object detection, and tracking have been actively pursued by researchers in the field of real time video processing. In the present work, a new algorithm is proposed to automatically detect objects using revised local binary pattern (m-LBP) for object detection. The detected object was tracked and its location estimated using the Kalman filter, whose state covariance matrix was tuned using particle swarm optimisation (PSO). PSO, being a nature inspired algorithm, is a well proven optimization technique. This algorithm was applied to important real-world problems of partially-occluded objects in infrared videos. Algorithm validation was performed by realizing a thermal imager, and this novel algorithm was implemented in it to demonstrate that the proposed algorithm is more efficient and produces better results in motion estimation for partially-occluded objects. It is also shown that track convergence is 56% faster in the PSO-Kalman algorithm than tracking with Kalman-only filter

The technological growth in eHealth services

The infusion of information communication technology (ICT) into health services is emerging as an active area of research. It has several advantages but perhaps the most important one is providing medical benefits to one and all irrespective of geographic boundaries in a cost effective manner, providing global expertise and holistic services, in a time bound manner. This paper provides a systematic review of technological growth in eHealth services. The present study reviews and analyzes the role of four important technologies, namely, satellite, internet, mobile, and cloud for providing health services.Web of Scienceart. no. 89417

An improved block matching algorithm for motion estimation invideo sequences and application in robotics

Block Matching is one of the most efficient techniques for motion estimation for video sequences. Metaheuristic algorithms have been used effectively for motion estimation. In this paper, we propose two hybrid algorithms: Artificial Bee Colony with Differential Evolution and Harmony Search with Differential Evolution based motion estimation algorithms. Extensive experiments are conducted using four standard video sequences. The video sequences utilized for experimentation have all essential features such as different formats, resolutions and number of frames which are generally required in input video sequences. We compare the performance of the proposed algorithms with other algorithms considering various parameters such as Structural Similarity, Peak Signal to Noise Ratio, Average Number of Search Points etc. The comparative results demonstrate that the proposed algorithms outperformed other algorithms

Trim Loss Optimization by an Improved Differential Evolution

The "trim loss problem" (TLP) is one of the most challenging problems in context of optimization research. It aims at determining the optimal cutting pattern of a number of items of various lengths from a stock of standard size material to meet the customers' demands that the wastage due to trim loss is minimized. The resulting mathematical model is highly nonconvex in nature accompanied with several constraints with added restrictions of binary variables. This prevents the application of conventional optimization methods. In this paper we use synergetic differential evolution (SDE) for the solution of this type of problems. Four hypothetical but relevant cases of trim loss problem arising in paper industry are taken for the experiment. The experimental results compared with those of the other techniques show the competence of the SDE to solve the problem

Trim Loss Optimization by an Improved Differential Evolution

The “trim loss problem” (TLP) is one of the most challenging problems in context of optimization research. It aims at determining the optimal cutting pattern of a number of items of various lengths from a stock of standard size material to meet the customers’ demands that the wastage due to trim loss is minimized. The resulting mathematical model is highly nonconvex in nature accompanied with several constraints with added restrictions of binary variables. This prevents the application of conventional optimization methods. In this paper we use synergetic differential evolution (SDE) for the solution of this type of problems. Four hypothetical but relevant cases of trim loss problem arising in paper industry are taken for the experiment. The experimental results compared with those of the other techniques show the competence of the SDE to solve the problem

A balanced squad for Indian premier league using modified NSGA-II

Selecting team players is a crucial and challenging task demanding a considerable amount of thinking and hard work by the selectors. The present study formulated the selection of an IPL squad as a multi-objective optimization problem with the objectives of maximizing the batting and bowling performance of the squad, in which a player's performance is estimated using an efficient Batting Performance Factor and Combined Bowling Rate. Also, the proposed model tries to formulate a balanced squad by constraining the number of pure batters, pure bowlers, and all-rounders. Bounds are also considered on star players to enhance the performance of the squad and also from the income prospects of IPL. The problem in itself is treated as a 0/1 knapsack problem for which two combinatorial optimization algorithms, namely, BNSGA-II and INSGA-II, are developed. These algorithms were compared with existing modified NSGA-II for IPL team selection and three other popular multi-objective optimization algorithms, NSGA-II, NSDE, and MOPSO-CD, on the basis of standard performance metrics: hypervolume, inverted generational distance, and number of Pareto optimal solutions. Both algorithms performed well, with BNSGA-II performing better than all the other algorithms considered in this study. The IPL 2020 players' data validated the applicability of the proposed model and algorithms. The trade-off squads contained players of each expertise in appropriate proportions. Further analysis of the trade-off squads demonstrated that many theoretically selected players performed well in IPL 2020 matches.Web of Science1010047710046

Analyzing the Prospects of Blockchain in Healthcare Industry

Deployment of a secured healthcare information is a major challenge in a web based environment. Ehealth services are subjected to same security threats as other services. The purpose of blockchain is to provide a structure and security to the organization data. Healthcare data deals with confidential information. The medical records can be well organized and empower their propagation in a secured manner through the usage of blockchain technology. The study throws light on providing security of health services through blockchain technology. The authors have analysed the various aspects of role of blockchain in healthcare through an extensive literature review. The application of blockchain in covid-19 has also been analysed and discussed in the study. Further application of blockchain in Indian healthcare has been highlighted in the paper. The study provides suggestions for strengthening the healthcare system by blending machine learning, artificial intelligence, big data, IoT with blockchain

HPDE: A Novel Hybrid PSO-DE Algorithm for Global Optimization Problems

DE and PSO are population based heuristic search technique which can be used to solve the optimization problems modeled on the concept of Evolutionary Approach. In the present study we proposed a new algorithm based on hybridization of DE and PSO algorithm called Hybrid Particle Swarm Differential Evolution Algorithm (HPDE) for solving global optimization algorithms. The numerical and statistical results are examined on a set of six standard benchmark functions and results are compared with classical DE in term of number of function evaluations (NFE) and average fitness function values. The results show that the HPDE algorithm outperforms the classical DE in term of all considered performance measure